Forest Diversity and Management (Topics in Biodiversity and Conservation)

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Author: David L. Hawksworth | Alan T. Bull

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Forest Diversity and Management

TOPICS IN BIODIVERSITY AND CONSERVATION Volume 2

The titles published in this series are listed at the end of this volume.

Forest Diversity and Management

Edited by

David L. Hawksworth and Alan T. Bull

Reprinted from Biodiversity and Conservation, volume 15:4 (2006)

123

A C.I.P. Catalogue record for this book is available from the library of Congress.

ISBN-10 ISBN-13 ISBN-10 ISBN-13

1-4020-5207-3 (HB) 978-1-4020-5207-1 (HB) 1-4020-5208-1 (e-book) 978-1-4020-5208-8 (e-book)

Published by Springer, P.O. Box 17, 3300 AA Dordrecht, The Netherlands. www.springer.com

Printed on acid-free paper

All Rights Reserved 2006 Springer No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microﬁlming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied speciﬁcally for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Printed in the Netherlands.

Contents

Forest Diversity and Management Introduction

1

D. CLOSSET-KOPP, A. SCHNITZLER and D. ARAN / Dynamics in natural mixed-beech forest of the Upper Vosges

3–33

OSWALDO TÉLLEZ-VALDÉS, PATRICIA DÁVILA-ARANDA and RAFAEL LIRA-SAADE / The effects of climate change on the long-term conservation of Fagus grandifolia var. mexicana, an important species of the Cloud Forest in Eastern Mexico

35–47

OLIVARIMBOLA ANDRIANOELINA, HERY RAKOTONDRAOELINA, LOLONA RAMAMONJISOA, JEAN MALEY, PASCAL DANTHU and JEAN-MARC BOUVET / Genetic diversity of Dalbergia monticola (Fabaceae) an endangered tree species in the fragmented oriental forest of Madagascar

49–68

HÉLÈNE GONARD, FRANÇOIS ROMANE, IGNACIO SANTA REGINA and SALVATORE LEONARDI / Forest management and plant species diversity in chestnut stands of three Mediterranean areas

69–82

FRIEDRICH PATRICK GRAZ / Spatial diversity of dry savanna woodlands Assessing the spatial diversity of a dry savanna woodland stand in northern Namibia using neighbourhood-based measures

83–97

BÄRBEL BLEHER, DANA USTER and THOMAS BERGSDORF / Assessment of threat status and management effectiveness in Kakamega Forest, Kenya

99–117

MASASHI OHSAWA and TAKUO NAGAIKE / Influence of forest types and effects of forestry activities on species richness and composition of Chrysomelidae in the central mountainous region of Japan

119–131

ANDREAS HEMP / The banana forests of Kilimanjaro: biodiversity and conservation of the Chagga homegardens

133–157

M.G.P. TCHOUTO, M. YEMEFACK, W.F. DE BOER, J.J.F.E. DE WILDE, L.J.G. VAN DER MAESEN and A.M. CLEEF / Biodiversity hotspots and conservation priorities in the Campo-Ma‘an rain forests, Cameroon

159–192

R. KINDT, P. VAN DAMME and A.J. SIMONS / Tree diversity in western Kenya: using profiles to characterise richness and evenness

193–210

GERHARD LANGENBERGER, KONRAD MARTIN and JOACHIM SAUERBORN / Vascular plant species inventory of a Philippine lowland rain forest and its conservation value

211–241

WEIBANG SUN, YUAN ZHOU, CHUNYUAN HAN, CHUNXIA ZENG, XIAODONG SHI, QIBAI XIANG and ALLEN COOMBES / Status and conservation of Trigonobalanus doichangensis (Fagaceae)

243–258

NIALL G. BURNSIDE, DAN J. METCALFE, ROGER F. SMITH and STEVE WAITE / Ghyll woodlands of the Weald: characterisation and conservation

259–278

AI-LIAN ZHAO, XIAO-YONG CHEN, XIN ZHANG and DONG ZHANG / Effects of fragmentation of evergreen broad-leaved forests on genetic diversity of Ardisia crenata var. bicolor (Myrsinaceae)

279–291

M.G.P. TCHOUTO, W.F. DE BOER, J.J.F.E. DE WILDE and L.J.G. VAN DER MAESEN / Diversity patterns in the flora of the Campo-Ma’an rain forest, Cameroon: do tree species tell it all?

293–314

JEAN-REMY MAKANA and SEAN C. THOMAS / Impacts of selective logging and agricultural clearing on forest structure, floristic composition and diversity, and timber tree regeneration in the Ituri Forest, Democratic Republic of Congo

315–337

ALFONSO GARMENDIA, SUSANA CÁRCAMO and OSCAR SCHWENDTNER / Forest management considerations for conservation of Black Woodpecker Dryocopus martius and White-backed Woodpecker Dendrocopos leucotos populations in Quinto Real (Spanish Western Pyrenees)

339–355

STEVEN M. VAMOSI / A reconsideration of the reproductive biology of the Atlantic forest in the Volta Velha Reserve

357–364

ALESSIO MORTELLITI and LUIGI BOITANI / Patterns of rodent species diversity and abundance in a Kenyan relict tropical rainforest

365–380

J. LUIS HERNANDEZ-STEFANONI / The role of landscape patterns of habitat types on plant species diversity of a tropical forest in Mexico

381–397

JANE HERBERT / Distribution, habitat and Red List status of the New Caledonian endemic tree Canacomyrica monticola (Myricaceae)

399–406

GRACE NANGENDO, HANS TER STEEGE and FRANS BONGERS / Composition of woody species in a dynamic forest–woodland–savannah mosaic in Uganda: implications for conservation and management

407–435

JÖRN THEUERKAUF and SOPHIE ROUYS / Do Orthoptera need human land use in Central Europe? The role of habitat patch size and linear corridors in the Bialowiez·a Forest, Poland

437–448

BENIGNO GONZÁLEZ-RIVAS, MULUALEM TIGABU, KARIN GERHARDT, GUILLERMO CASTRO-MARÍN and PER CHRISTER ODÉN / Species Composition, diversity and local uses of tropical dry deciduous and gallery forests in Nicaragua

449–467

B. BALAGURU, S. JOHN BRITTO, S.J., N. NAGAMURUGAN, D. NATARAJAN and S. SOOSAIRAJ / Identifying conservation priority zones for effective management of tropical forests in Eastern Ghats of India

469–483

SWEN C. RENNER, MATTHIAS WALTERT and MICHAEL MÜHLENBERG / Comparison of bird communities in primary vs. young secondary tropical montane cloud forest in Guatemala

485–515

T.R. SHANKAR RAMAN / Effects of habitat structure and adjacent habitats on birds in tropical rainforest fragments and shaded plantations in the Western Ghats, India

517–547

Biodiversity and Conservation (2006) 15:1061–1061 DOI 10.1007/s10531-006-0009-7

Springer 2006

Introduction

Topics in Biodiversity and Conservation: Forest diversity and management Natural forests, with a history of ecological continuity extending back for thousands of years, are unrivalled as the treasure store of terrestrial biodiversity on Earth. Yet to date there is no fully comprehensive inventory of the above- and below-ground biota of any forest available, even in western Europe. However, in conserving natural forests, it is reasonable to assume that the myriads of unnamed bacteria, fungi, insects, mites and nematodes present will be safeguarded along with the trees, provided that the forest structure is maintained. But forests are also a key player in the global carbon cycle, and so in the maintenance of the composition of the atmosphere crucial to Life as we know it. To endanger and clear forests is at the peril of future generations, but as so many peoples depend on forests for food and wood, the issue of how forests can be used sustainably, in a way that protects the full spectrum of organisms they contain, has to be addressed. Sadly, the compensatory planting of new forests, whether for exploitation or conservation, does not fully address the need; the trees, other plants and vertebrates may be secured by such approaches, but the full soil biota, and complete spectrum of organisms associated with a natural forest are unlikely ever to be regained. This compilation of peer-reviewed papers, drawn from researchers around the world, examines many diﬀerent aspects of forest diversity and management. They consider forests in diverse locations, including Australia, Cameroon, China, France, Kenya, the Philippines, Poland, Uganda, and the UK. The forest types considered vary from banana forests, savannah forests, and tropical rainforest to the much revered ancient oak forest of Bialowieza in Poland. The emphasis is on the trees themselves, including eﬀects of logging, changes in management practices, and climate change. In some cases the consequences of forest disturbance or destruction on other plants, birds, or vertebrates are reported for particular forests. Given the wide range of topics brought together here, this collection should be of particular interest to those involved in teaching forest conservation and management, and requiring a cross-section of current work in the ﬁeld. DAVID L. HAWKSWORTH The Yellow House, Calle Aguila 12, Colonia La Maliciosa, Mataelpino, Madrid 28492, Spain. E-mail: [email protected]

[1]

Biodiversity and Conservation (2006) 15:1063–1093 DOI 10.1007/s10531-004-1874-6

Springer 2006

-1

Dynamics in natural mixed-beech forest of the Upper Vosges D. CLOSSET-KOPP*, A. SCHNITZLER and D. ARAN LBFE, University of Metz, Campus Bridoux, rue du Ge´ne´ral Delestraint, 57070 Metz-Borny, France; *Author for correspondence (e-mail: [email protected]) Received: 10 February 2004; accepted in Revised form 22 July 2004

Key words: Mixed beech forests, Age-structure, Architecture, Soil, Light regime, Stand history Abstract. Forest dynamics were analysed in the Upper Vosges mountains of north-eastern France in two reserve areas, Frankenthal-Missheimle (FM) and Grand Ventron (GV), located in the Ballons des Vosges Natural Regional Park (Parc Naturel Re´gional des Ballons des Vosges). Two plots of 3000 m2 each were established in mixed beech woodlands located just below sub-alpine beech forests for long-term monitoring. The main aim of the study was to interpret how the diﬀerent species populations in mixed-beech woodlands in the Vosges grow and interact over the long term, and to determine the disturbance history. The study combined vegetation description, dendrological and structural data, architectural descriptions and drawings and light distribution and soil analysis. Historical information was also taken into consideration. Soils in the two plots showed available phosphate P values > 0.14 g kg1, indicating good levels of phosphorus supply for plants, except for A1/C horizon (1Va soil) which corresponds to a medium-fertility soil. However, soils were found to be shallow because of the slope, a factor that may limit water availability for adult trees and seedlings. As the canopy (composed of existing trees) consists of shade trees, the growth rates for seedlings and saplings (potential trees) depends on the canopy architecture: when growing in sunlit gaps, saplings reach full daylight (canopy height) in less than 100 years. When developing in shade (suppressed state), saplings may need up to 150 years before reaching full daylight. Alternating periods of rapid and slow growth explain why some trees present a wide range of stem diameters and ages in the area leading up to the canopy (some trees are more than 300-years-old), in contrast with the relatively homogeneous height classes distribution, indicating suppression periods. Trees in the FM and GV plots were found to have diﬀerent growth rates. Both study plots developed with similar past disturbance events, the two most important being at the beginning of the 18th century. In addition, the forests were regularly aﬀected by smaller disturbances until present. Because of the spatial heterogeneity and large range of ages represented, the forest stands within the two natural reserve areas are presently considered to be the bestpreserved sites in the upper Vosges, but their situation near the timber line prevents them from becoming models for forest management at lower altitudes.

Introduction Unmanaged forests are the last representatives of the pristine landscapes of Europe. Unfortunately, they have practically disappeared from European forest panels, with a total of only 3 millions hectares (i.e. 1.7% of the total forest area; COST Action E4 1999). These forest relics are located primarily in remote, inaccessible areas, in unproductive regions, hunting reserves or along frontier borders (Peterken 1996; COST Action 4 1999; Motta et al. 2002; [3]

1064 Schnitzler 2002). Apart from Russia, where old-growth forests may reach up to 20,000 km2 (Sittler et al. 2000), they are small patches (a mean range of 20– 100 ha) within a larger landscape patchwork of managed forests and various land uses. For example, France, with 15 million hectares of metropolitan forest cover, possesses the third largest woody domain in Europe, but only 0.2% (300 km2) of this total are natural forests (Vallauri and Poncet 2003). Most of these are concentrated in mountain regions (the Vosges, the Jura, the Pyrenees and the Alps). Studies have demonstrated that these vestiges cannot remain completely independent of their managed surroundings, and are unable to preserve their potential biodiversity (Helle and Ja¨rvinen 1986). Pollen diagrams have, however, demonstrated that even small ‘virgin’ forests remain stable in composition over hundred of years (Bradshaw and Holmqvist 1999). The main causes of such stability and resilience are the high complexity in structure and architecture associated with the complexity of biotic interactions, which lead to remarkable resistance to climatological events (White 1978; Franks and McNaughton 1991). All remaining natural forests urgently need protection in order to preserve their cultural and scientiﬁc value, to protect their wildlife and genetic diversity and to ensure sites for basic research in ecology. They also provide the necessary reference data for applied research in forest management and environmental monitoring (Leibendguth 1959; Peterken 1996). The present study looked at several aspects of the forest dynamics and biodiversity of mixed-beech woodlands of the ‘Parc Naturel Re´gional des Ballons des Vosges’ (PNRBV) (Upper Vosges, north-eastern France). The PNRBV has two natural reserves within its boundaries: the Grand Ventron (GV), created in 1995 covering over 1647 ha, and the Frankenthal–Missheimle (FM), created in 1989 with over 746 ha. Their respective elevations (GV: 720– 1204 m; FM : 690–1363 m) correspond to the submontane (400–800) and montane belts (800–1100 altitude). Both reserves harbour typical, often endangered, plant communities (Schwoehrer and Despert 1999; Schwoehrer 1999; Untereiner et al. 2002). The impact of human activity has been signiﬁcant since the French Revolution and includes logging, local ﬁres and the planting of non-indigenous spruce since the 1850s (Garnier 1994, 1998). Ungulate densities are also closely linked to human activity and their populations have increased considerably during the 20th century (ONF 2000; Heuze´ 2002). One of the main objectives of the creation of the PNRBV, within the framework of which the present research was carried out, was to contribute to the conservation and sustainable management of the forests through basic and applied research and the development of innovative methodologies. For this reason, our research focused on long-term, forest-monitoring plots situated in strictly protected woodlands of the FM and GV natural reserves which still include small stands of nearly natural woodlands (Gilg 1997). The aim of the study is: (i) to propose and innovate a sampling protocol for long-term studies,

[4]

1065 (ii) to interpret how diﬀerent species populations of Vosgian mixed-beech woodlands grow and interact over the long-term in light of their disturbance history, (iii) to propose a diagnostic of forest naturalness.

Materials and methods Study sites The Vosges form a long ridge with a continuous crest line, linked to the west and to the Rhine valley to the east by steep slopes. In the southern Vosges, the crest oscillates from 1000 to 1425 m. The climate is oceanic (1600 to 3000 + mm rainfall; mean annual temperature of 4 C above 1000 m). The hercynian bedrock is mainly composed of granite and metamorphic rock, partially covered with morainic material. They include biotitic granite rock, locally porphyroid, with acid plagioclase (An10-20), K-Feldspar, quartz and some apatite (Mansuy 1992). Soils range from acidic browns to podzols (Souchier 1971; Bonneau et al. 1978). The mixed-beech woods found between 600 and 1000 m are part of the Fagion alliance. The main plant community is the Luzulo–Fagetum (Meusel 37) which includes two sub-associations (group Vaccinium myrtillus; group Festuca altissima, Oberdorfer 1992) typical of Central European mountains and hills north of the Alps (Ellenberg 1988; Oberdorfer 1991, 1992; Bogenrieder 2001). The three plant communities include the same tree species (Fagus sylvatica, Abies alba, Acer pseudoplatanus, Sorbus aucuparia) and shrubs (Rubus tereticaulis, Rubus idaeus, Lonicera nigra). Beech (Fagus sylvatica) occupies a central position in the ecology of the Vosgian forests, outcompeting the other tree species. Silver ﬁr (Abies alba) is regular but suﬀers from browsing (Heuze´ 2002). Acer pseudoplatanus is competitive in shallow soils found in rocky habitats. Spruce (Picea excelsa)is rare, despite the importance of neighbouring plantations. Ground-level ﬂora is dominated by Vaccinium myrtillus, Luzula luzuloides, Deschampsia ﬂexuosa and Prenanthes purpurea. The GV and FM reserves are 8 km apart (Figure 1). They are close (8– 15 km) to a third natural reserve, the Guebwiller (700–950 m), which also includes some stands of nearly natural woodlands (Renaud et al. 2000).

Permanent plots Two plots measuring 3000 m2 (50 · 60 m, i.e. 30 quadrants of 10 · 10 m) each were selected within the less disturbed mixed-beech woodlands of the two reserves. Stand coordinates were referenced by means of a global positioning [5]

1066

Figure 1. Location of FM and GV natural reserves in the Upper Vosges.

system (GPS) (GV: latitude 4827¢N; longitude 665¢E; the plot is situated near the ‘Grand Ventron’ farm; FM: latitude 4830¢N ; longitude 710¢E: the plot is situated below the ‘Trois-Fours’ farm). Metallic boundary markers were buried (forced in the soil) in the ground in order to pursue the study over the very long term. The FM plot is located between 900 and 950 m while the GV plot is 50 m higher (950–1025 m), very close to the multi-stemmed beech forests that form the timber-line (Carbiener 1966). Both plots face East. Plot GV is characterized by a succession of steep slopes (50–60%), and ﬂatter (5–30%), moister zones while the FM plot exhibits more regular slopes, averaging 65%. Plot FM is adjacent to a large, permanent gap resulting from the accumulation of boulders of glacial origin. The ﬁeldwork started in 2000 and ended in 2003.

Soil data Soil-units were deﬁned according to local topography, regeneration patches and humus type characteristics. For each soil-unit, one representative proﬁle was described (horizons, colour, texture, structure, stoniness, root development). All horizons of the representative proﬁles were sampled, with special attention to the ﬁrst few centimetres (A11 horizon) where seed germination takes place. In some cases, A11 horizons were also sampled within one soil-unit, with regard to diﬀerent slopes, regeneration or humus characteristics. [6]

1067 In 2002, ﬁve soil units were deﬁned in the GV plot. In 2003, three soil-units were identiﬁed and sampled in the FM plot. All samples were air-dried, passed through a 2 mm sieve and then analysed for chemical characteristics (analysis performed by INRA Laboratory for Soil Analysis, Arras, France): residual moisture content at 105 C, organic carbon and total nitrogen (dry combustion method), ‘available’ phosphorus (extracted by H2SO4 and NaOH; Duchaufour and Bonneau 1959), and exchangeable cations (based on cobalthexamine method, Orsiny and Remy 1976). Calculations were performed for C/N ratio, cation exchange capacity (CEC: sum of exchangeable cations), base saturation (ration of exchangeable ‘basic’ cations – Ca2+, Mg2+, K+ and Na+ – to CEC), and exchangeable Mg/Al and Ca/Al ratios.

Stand characteristics Ground ﬂora The ground ﬂora coverage was identiﬁed and the coverage of each species estimated, (Braun–Blanquet cover coeﬃcient were converted in percentage cover). Tree seedling densities (height < 130 cm with d.b.h less than 10 cm) were identiﬁed and quantiﬁed per 10 · 10 m quadrant (30 per stand). Size variables and architecture Tree height, stem diameter and crown area are variables of a tree’s architecture, and an expression of its growth strategy (Halle´ and Oldeman 1970; Halle´ et al. 1978; Oldeman 1979, 1990; Oosterhius et al. 1982). Tree height yields information about ecological conditions and growth strategies: the harsher the climate, the shorter the trees. Tree height distribution is also related to regeneration processes: theoretically, in continuously regenerating stands, the number of individuals in each height-class is expected to follow an exponential decline in numbers from shorter to taller trees. Curves are modiﬁed under shady canopies due to the stagnation in growth for much of the tree’s life cycle. In these cases, stem diameter increases when height progress is nearly at a standstill (Peters 1992). Clear allometric relationships exist between these variables. The hf/H ratio (k) compares the height of the tree trunk (hf) up to the ﬁrst main fork to the total height (H). The inversion point k, where the architectural tendencies are inverted (the axes become smaller and smaller, terminating at the periphery of the crown), is important in forest stand diagnosis: the higher the inversion point (i.e. the shallower the crown depth), the higher the competition with neighbouring trees. Growth strategy can also be interpreted using tree architecture. Architecture corresponds to the visible, morphological expression of hereditary growth development. For tree species, orthotropic versus plagiotropic axes, the ability to reiterate (i.e. the capacity to partially or totally repeat hereditary architec[7]

1068 ture in the same tree, by stimulation of resting meristems, Oldeman 1979) may explain diﬀerences in size variables. Fagus sylvatica grows according to Troll’s model with plagiotropic diﬀerentiation in all axes. The ﬂattened and highly organized leaf layers (monolayers), as well as the plagiotropy are necessary for intercepting light over large surfaces. Beech is also very ﬂexible, forming shoots of diﬀerent lengths in response to environmental conditions (Halle´ and Oldeman 1970; Nicolini 1997; Roloﬀ 1999). Acer pseudoplatanus follows Rauh’s model, characterized by orthotropic axes and faster growth than the beech. However, Acer pseudoplatanus is a monolayer, which increases its ability to intercept sunlight (Halle´ et al. 1978). Abies alba follows Massart’s model, characterized by a specialized plagiotropic organization of the branches that confer them high individual survival in the lower forest storeys (Edelin 1977). Architectural criteria also allow us to deﬁne the diﬀerent phases of tree development. Oldeman (1990) has deﬁned three main phases (‘potential tree’, ‘tree of the present’ and ‘tree of the past’), considered as the principal social states in the forest ecosystem. Potential trees and trees of the present can be seen as two distinct phases in the growth of a tree. In potential trees, the growth in height is relatively more important than growth in stem diameter and crown extension. Potential trees may grow faster under the high light levels found in canopy gaps (‘released-growing trees’) or be suppressed by shading from canopy trees. After successive intervals of suppression and released growth, many potential trees reach a minimum height above which they cannot be suppressed. In this case, they develop their architecture by reiteration and reach the tree of the present phase. The transition between these two growth phases is gradual, depending on the site and the forest architecture. To distinguish the two steps in our study, an empirical threshold was set at the height of 20 m, which corresponds to the minimum needed to no longer be suppressed on the steep slopes of the Vosges (suppression is visible when trees present shallow crowns and reiterations along the trunk, and the h/d.b.h. ratio is greater than 100). Tall tree species that have gone beyond this threshold are considered full-grown. For our purposes, living and dead trees of more than 10 cm d.b.h. and height >1 m 30 were identiﬁed in the plot and measured (diameter at breast height, total height, height of the main fork. Each (living or dead) tree was carefully drawn according to its exact proportions and morphology. Crown area was deﬁned using four perpendicular directions, including one facing the slope. Tree architecture was represented visually by vertical (six, 10 · 50 m parallel drawings per stand, oriented towards the slope) and horizontal drawings (one for living and one for dead trees in each plot). Relationship between size variables and age The age distribution of the trees depends on the plot history (past and present natural disturbances, impact of historical practices). Stem diameter growth depends on altitude, light intensity, temperature, water and nutrient supply, neighbouring trees, possible pollution as well as the period in the tree’s life [8]

1069 cycle (‘potential’ versus ‘present’). Thus, tree ring analysis is useful for determining the inﬂuence of ecological conditions within the particular context of the Upper Vosges. The ring widths of 156 trees (93 in the GV plot and 63 in FM, including beech, silver ﬁr and Acer pseudoplatanus were noted. Two cores were extracted at breast height from each tree, one up-slope and one down-slope. Tree-ring widths were measured using a computer-assisted device (Becker et al. 1995) and cross-dated against previously existing site chronologies (data from INRA, Champenoux), in order to correct for missing or duplicate rings. Stem diameter growth was calculated by dividing core length by the total number of ring widths. Growth rate comparisons were done at each site for each state and each species using non-parametric Mann–Whitney U-tests (Statistica software).

Canopy geometry and light distribution Since tree growth, architecture and size variables are largely explained by light dynamics (e.g. Chazdon and Pearcy 1986; Denslow et al. 1990; Vester 1997), variations in light distribution at points within the canopy were also studied. Relationships between the tree, the forest and the light level in old-growth forests have been studied by Koop (1989). The methodology deals with the architectural parameters of the canopy (canopy geometry) that are commonly used in the literature (i.e. gap fraction and foliage area index LAI), and the light variables (i.e. direct and diﬀuse solar radiation transmitted throughout the canopy). The simultaneous treatment of canopy geometry and distribution of incident light (PAR, understood as QPAR, quantum irradiance, expressed in mol m2 d1, Varlet-Granchet et al., 1989) was studied using hemispherical canopy photography. For each plot, 25 canopy photographs were taken in each 100 m2 section, 10 m apart from each other, at 50 cm above the ground, in overcast conditions. Because some photographs were of poor quality, the ﬁnal raw data included only 21 photographs for GV and 24 for FM. The camera was equipped with a ﬁsh-eye lens with a view angle of 180, carefully levelled and oriented for true North. The raw data from each photograph consisted of a matrix with 18 intervals of 5 zenith angles and 24 sectors of 15 azimuth angles which contained the gap fraction. All values were corrected for latitude, slope, orientation and topographic mask in the GLA model (Frazer et al. 1999). Calculations were performed at hourly intervals, then integrated daily, during the vegetative season (June–September). The radiation intercepted depended upon values calculated for each canopy element involved, over the whole hemisphere and along the solar tracks. Hemispherical photographs therefore present spatial auto-correlations with each other. Values found in FM and GV will be compared with data obtained using similar methods in the Guebwiller mixed-beech forest. Data concern one plot [9]

1070 of 1 ha chosen in a nearly natural forest stand growing in deep soil (slope from 20 to 30)(Renaud et al., 2000; Pierrel 2001).

Results Soil characteristics In both plots, soils are dark coloured, stony or gravely, with a ﬂuﬀy to massive structure and are ﬁnely textured (coarser with depth). Soils are shallow. FM soils show less variability in type than those in GV. Soils belong mostly to the Rankosol (Ranker) type, except for 2V soil which belong to Alocrisol and 5V soil which presents hydromorphic features (located in bench slope). Humus type ranges from oligo-mull to hemi-moder (Brethes et al. 1992). Chemical analysis (Table 1) shows a humose trend, with relatively high organic carbon content, particularly for the 5V soil due to waterlogged conditions. Less organic matter accumulation is observed in FM soils which may be related to better biodegradability of organic materials. In both stands, rather low C/N ratios, from 14.9 to 17.7 in uppermost horizons (A11), accounted for a rapid evolution of plant material added to soil and good nitrogen nutrition for trees. C/N ratios increasing with depth (1Va, 4V and 1F soils) probably indicate a cryptopodzolisation process, morphologically hidden by the humose character of soils. Available phosphorus obtained using the Duchaufour and Bonneau (1959) method is a good indicator of soil fertility. All samples showed available P2O5 values > 0.14 g kg1, indicating a good phosphorus supply for plants, except for A1/C horizon (1Va soil) which corresponded to a medium-fertility soil (Bonneau 1995). No notable diﬀerences were observed in regeneration spots, or between GV and FM plots. Soils show a medium cation exchange capacity (CEC), mostly related to organic matter content (organic carbon), decreasing with depth and lower in FM soils. Low base saturation was always observed in depth, while it exceeded 35% in uppermost horizons in 4V and 3F soils and reached 60% in 2F soil, due to active nutrient cycling. Among basic exchangeable cations, Ca generally predominates over Mg and K (low Na). Similarly, among acid exchangeable cations, Al largely predominates over H (low Mn), except in 1Va, 1Vd, 4V and 2F soils’ uppermost horizons showing a higher H proportion, probably related to cryptopodzolisation. A plentiful supply of Al on exchange sites is known to disturb Mg and Ca supply. The lowest Mg/Al and Ca/Al ratios were found in all deeper horizons (Bw, A1/C and C) except 2F soil, suggesting a possible Mg and Ca deﬁciency. On the other hand, all uppermost horizons showed higher ratios, apart from 3V soil (Mg) and 5Va soil (Ca). On the whole, no pronounced diﬀerences in soil property features were observed between the two plots. [10]

Table 1. Chemical characteristics of soils in GV and FM plots. Stand

Soil

Horizon

Depth cm

Organic carbon g kg1

C/N

Available P2O5 g kg1

Exchangeable cations Ca

2+

Mg

2+

K

+

Na

+

Al

3+

2+

CEC

Base saturation%

Mg/ Al

Ca/ Al

pH H 2O

10.73 7.18 5.70 9.47 11.09 11.63 13.17 8.36 5.39 4.37 12.67 9.52 4.45 18.21 13.77 7.80 13.58 3.74 11.77 5.91 4.50 2.72 9.42 7.46 7.20 5.49

29.0 12.6 3.6 15.9 26.0 20.7 30.7 8.4 6.9 5.9 11.1 9.4 6.3 46.0 21.3 5.6 12.7 8.7 15.4 22.8 6.3 5.2 60.2 23.2 37.9 12.1

0.148 0.064 0.012 0.053 0.088 0.098 0.090 0.026 0.021 0.020 0.027 0.032 0.023 0.216 0.072 0.020 0.041 0.032 0.044 0.056 0.020 0.012 0.495 0.075 0.134 0.035

0.490 0.084 0.008 0.086 0.276 0.237 0.393 0.036 0.024 0.018 0.073 0.032 0.018 1.032 0.222 0.021 0.059 0.038 0.106 0.203 0.022 0.020 2.073 0.225 0.574 0.074

3.6 3.6 4.1 4.3 3.7 3.6 3.9 4.0 4.3 4.5 4.2 4.3 4.5 3.7 3.6 4.0 4.5 4.6 4.3 4.4 4.5 4.7 4.2 4.0 4.2 4.3

+

Mn

H

0.068 0.013 0.006 0.117 0.159 0.036 0.298 0.042 0.027 0.014 0.275 0.092 0.028 0.168 0.028 0.006 0.140 0.011 0.289 0.214 0.033 0.010 0.362 0.036 0.263 0.110

3.56 2.09 0.33 0.55 1.50 3.58 1.60 0.33 0.17 – 0.35 0.30 0.08 3.60 2.66 0.50 0.31 0.16 0.55 0.31 – – 1.39 1.30 0.84 0.31

cmol+kg1 GV

[11] FM

A11 A12 A1/C A11 A11 A11 A11 A12 Bw C A11 A12 C A11 A12 C A11 A12 A11 A11 A12 A1/C A11 A1/C A11 A12

0–2 2–7 7–30 0–2 0–2 0–2 0–2 2–10 10–25 25–50 0–2 2–12 12–40 0–2 2–10 10–33 0–2 2–20 0–2 0–2 2–15 15–25 0–2 2–10 0–2 2–20

14.84 7.91 5.79 18.48 15.41 16.23 18.03 12.65 6.75 6.61 29.24 17.92 6.15 30.77 19.51 8.06 34.37 5.58 18.30 6.66 4.29 3.25 12.45 8.85 7.87 5.29

17.7 17.0 21.8 15.4 16.4 17.3 17.0 15.1 15.4 15.5 17.2 16.0 14.6 17.7 17.2 21.7 17.6 15.9 14.9 15.9 15.4 17.4 16.6 14.9 16.5 14.8

0.386 0.195 0.125 0.35 0.316 0.289 0.404 0.3 0.184 0.16 0.454 0.365 0.219 0.503 0.404 0.197 0.54 0.254 0.438 0.412 0.208 0.286 0.388 0.317 0.46 0.333

1.95 0.35 0.04 0.63 1.81 1.33 2.84 0.26 0.11 0.07 0.78 0.27 0.07 6.25 1.81 0.14 0.68 0.12 0.97 0.82 0.09 0.05 4.13 0.99 1.93 0.33

0.59 0.27 0.06 0.38 0.57 0.55 0.65 0.19 0.10 0.08 0.28 0.27 0.09 1.31 0.59 0.13 0.47 0.10 0.40 0.23 0.08 0.03 0.99 0.33 0.45 0.15

0.49 0.24 0.07 0.42 0.45 0.44 0.49 0.20 0.11 0.07 0.31 0.31 0.08 0.75 0.46 0.11 0.49 0.08 0.39 0.28 0.09 0.04 0.49 0.34 0.32 0.13

0.08 0.05 0.03 0.07 0.05 0.08 0.05 0.05 0.04 0.03 0.03 0.05 0.03 0.08 0.06 0.04 0.09 0.02 0.05 0.02 0.02 0.02 0.06 0.07 0.03 0.05

Data in g kg1 of dry matter, except for available P2O5 in g kg1 of air-dried soil: below detection limits.

3.99 4.17 5.16 7.29 6.54 5.61 7.23 7.28 4.83 4.10 10.65 8.23 4.06 6.06 8.16 6.86 11.41 3.24 9.12 4.05 4.18 2.57 1.99 4.40 3.37 4.41

1071

1Va 1Va 1Va 1Vb 1Vc 1Vd 2V 2V 2V 2V 3V 3V 3V 4V 4V 4V 5Va 5Va 5Vb 1F 1F 1F 2F 2F 3F 3F

1072 Stand characteristics Density and spatial patterns Plot GV is more crowded (322 stems ha1) than FM (275 stems ha1), but FM volume values were more important (677.7 m3 ha1 and 949 m3 ha1 for GV and FM respectively)(Table 2). The dominant species is beech, which accounts for 66% in GV and 70% in FM. Multi-stemmed beech trees were also more important in GV. Abies alba and Acer pseudoplatanus are relatively minor components of the stands, accounting for 18.6 and 13.3% respectively in GV, and 18.1 and 9.4% in plot FM. Acer pseudoplatanus typically occupies rocky, sunnier sites. Sapling density is higher in FM than in GV. In plot FM, the dominant species is Acer pseudoplatanus (42%), followed by Abies alba (32.6%) and Fagus sylvatica (23.7%). Beech is largely dominant in the GV plot, representing 80% of the total number of saplings. Silver ﬁr development is limited by ungulate predation and its sensitivity to frost and drought. Picea excelsa and Sorbus aucuparia are rare. Woody regeneration is strongly clumped in several ellipsoid patches at gap margins, extending towards the slope (Figure 2a, b). The biggest gaps in both plots are caused by rocky areas where tree regeneration is diﬃcult. These gaps are mainly colonised by herbaceous species: Luzula luzuloides, ferns in GV; Festuca altissima, Oxalis acetosella, Galeopsis tetrahit, small woody species (Rubus tereticaulis, Rubus idaeus, Vaccinium myrtillus). Tree and forest architecture Because of the steep slopes, nearly all the trees present asymmetrical shapes: crowns develop marked supplementary axes (reiterations, Oldeman 1974) on trunks, and secondary axes facing the other end of the valley, while there are no secondary, supplementary axes on the opposite side (Figure 3a, a1, b, b1). Asymmetry is particularly developed in Fagus sylvatica and Acer pseudoplatanus, very ﬂexible species which reiterate their initial architectural model easily. Trees of the present reiterate more often than potential trees because they have suﬃcient energy for crown expansion. Asymmetrical shapes are explained by insertion points k which are low (0.32–0.42) on one side of the trunks and high on the opposite side. There is strong inter-penetration of crowns laterally between the middle and upper-third of tree height, while foliage is much less dense above and below. Potential trees often present triangular crown shapes (suppressed trees growing below healthy, shading trees of the present). To compensate for the small foliar volume, some potential trees have developed small reiterations along the trunk. Firs exhibit many kinds of traumas, including loss of major branches and double forks resulting from loss of apical buds (frost, wind). In plot GV, 23.4% of beech trees are multi-stemmed, with 2–14 trunks of diﬀerent dimensions. Most trunks have reached the canopy, with some big trunks reaching more than 30 m high. Within one type of individual, the range in height varied from 0 to 6 m, with stem diameters varying from 3 to 16 cm. In [12]

Table 2. Densities and volumes of tree species in FM and GV. Number saplings 4

Number, Fagus sylvatica

[13]

GV 8983 7184 FM 52300 12395 4 stems ha1; height < 1m30; d.b.h. < 4 cm Number Number, living trees 1 Fagus sylvatica GV 322 213 FM 275 193 Number Number, dead trees 1 Fagus sylvatica GV 63 16 FM 16 0 1 2 3 4 5

Number, Abies alba

Number, Acer pseudoplatanus

Number, Picea excelsa

Number, Sorbus aucuparia

592 17049

1194 22122

18 680

18 52

Number, Abies alba 43 50 Number, Abies alba 47 16

Number, Picea excelsa 6 26 Total volume dead trees 2, 4 23.3 24.8

Total volume living trees 2 677.7 949

Basal area living trees 3 22.8 53.3

Stems ha1, d.b.h. > 4 cm. m3 ha1 based on the calculation formula of volume used in Renaud et al. 2000. V = diameter2 · height · 0.35 for coniferous and V = diameter2 · height · 0.5 for broad-leaved tree. m2 ha1. Dead trunks of multi-stemmed beech trees excluded.

1073

1074

Figure 2. (a) Crown projection map (50 · 60 m) in FM (shaded areas represent regeneration). Fa for Fagus sylvatica; Ac for Acer pseudoplatanus; Ab for Abies alba. (b) Crown projection map (50 · 60 m) in VN (shaded areas represent regeneration) Fa for Fagus sylvatica; Ac for Acer pseudoplatanus; Ab for Abies alba.

[14]

1075

Figure 3a. Examples of vertical proﬁle (10 m · 50 m) in FM (tree species and age are represented for potential trees and trees of the present. (Fa: Fagus sylvatica; Ab: Abies alba; Ac: Acer pseudoplatanus).

general, one or two were big and healthy, one to three smaller and the remaining trunks (big or small) dead. The proportion of dead trunks increased as the total number of trunks increased. Size-distribution, social status and age-distribution In both plots, tree height distribution presented a simple, global architecture with foliage concentrated in the canopy:canopy trees (i.e. trees of the present) accounted for 60% of the registered trees in FM and 68.8% in GV. In spite of a regular, evenly spaced distribution of trees of the present, canopy stratiﬁcation [15]

1076

Figure 3a. (Continued)

was rather complex, with the imbrication of three main layers: 20–25 m, 25– 30 m and some emergents between 35 and 40 m. Plot GV had a nearly equal number of trees between 20–25 and 25–30 m (Figure 3a, a1), while FM included more trees in the upper canopy (Figure 3b, b1). Size-distribution is not related to age-distribution, indicating that shadetolerant species cohorts can survive for long periods in a suppressed state. Correlations are better for older trees in the upper parts of the canopy; i.e. [16]

1077

Figure 3b. Examples of vertical proﬁle (10 m · 50 m) in GV (tree species and age are represented for potential trees and trees of the present. (Fa: Fagus sylvatica; Ab: Abies alba; Ac: Acer pseudoplatanus).

maximum ages are closer to sizes: 40 m high and 111 cm d.b.h. for a 345-yearold silver ﬁr, 29 m high and 41 cm d.b.h. for a 214-year-old beech; 23 m high and 54 cm d.b.h. for a 231-year-old Acer pseudoplatanus (Table 3). Most trees of the present had a rotten heart, particularly the Acer pseudoplatanus. However, their foliage and axes were well-developed, without any sign of bark or leaf loss. Trees can be considered as reaching the stage ‘of the present’ at various ages. In general, potential trees in FM reach the canopy earlier than those in GV: a range of 48–162 years in FM compared to a range of 102 (very rare)–223 years in GV. Thus, under good light conditions, averages of 2.2 mm growth per year [17]

1078

Figure 3b. (Continued)

were recorded for three young 45- to 52-year-old beeches in FM. In this plot, potential trees and trees of the present also had similar growth rates for stem diameter while in GV, trees of the present grew signiﬁcantly (p < 0.001) faster than potential trees (Table 4). These data indicate that suppression was more marked in GV, which limits correlations between stem diameter growth and age (Figure 4). For beech trees, the Spearman correlation coeﬃcient (Rs) is 0.48 while the correlation is above 0.65 in FM. The silver ﬁr presents similar tendencies (Rs = 0.71 in FM; 0.29 in GV). Average growth rates of suppressed beech trees in GV are only 0.3– 0.6 mm per year and 0.7 mm for silver ﬁr. This explains why some GV saplings may be rather old: 119 years for a 4.5 m high silver ﬁr; 135 years for a 7.5 mhigh beech. One potential beech was still in a suppressed state at 215 year of age. Multi-stemmed beech trees present a broad range of ages (from 20 to 78 years) within one individual. [18]

1079 Table 3. Ranges of stem diameter and age for beech, silver ﬁr and sycamore in FM and GV. FM plot n

GV plot

Range of DBH (cm)

Range of ages (years)

n

Range of DBH (cm)

Range of ages (years)

Potential trees < 10 m Fagus sylvatica Abies alba Acer pseudoplatanus

6 3 2

8–11 11–79 5–7

54–102 30–59 21–68

6 2 1

5–19 6 10

41–135 37–119 55

10–20 m Fagus sylvatica Abies alba Acer pseudoplatanus

4 3 1

13–32 21–30 67

35–52 54–80 77

5 14 1

16–32 14–54 11

119–160 149–226 66

Trees of the present 20–30 m Fagus sylvatica Abies alba Acer pseudoplatanus

13 1 5

32–76 45 30–73

146–193 135 117–162

36 4 14

29–64 48–70 10–57

102–321 107–193 78–231

30–40 m Fagus sylvatica Abies alba Acer pseudoplatanus

18 6 1

45–83 57–111 54

150–281 132–345 154

8 2 14

29–54 62–64 10–57

147–223 101–200 78–231

Correlations between stem diameter and age of Acer pseudoplatanus trees were signiﬁcant for GV (0.87). For FM, Acer pseudoplatanus trees are too rare to be analysed. Dead trees Dead trees (trees of the past) represented 11.2 and 3.1% of the total volume of trees in GV and FM, respectively (Table 2). Most of them were silver ﬁrs. In FM no death was recorded among beech trees. Dead trees generated only very small gaps because they were rarely very large: average stem diameters ranged from 10–80 cm. The three dead silver ﬁr trees analysed in GV (d.b.h of 13, 13.6 and 25 cm) died at 79, 89 and 191 year of age respectively. Two beech trees (d.b.h of 25 and 22 cm) died at 145 and 149 years respectively. These trees were either snapped oﬀ at diﬀerent heights (from 2 to 24 m) or uprooted. Dead trees presented diﬀerent degrees of rot. Standing dead trees had woodpecker holes and were often infected by Fomes fomentarius. Tree establishment Tree distribution by species (Fagus sylvatica, Abies alba and Acer pseudoplatanus) and age-class (Figure 5) in FM and GV indicates a pattern of establishment and mortality during the last 350 years. There was a peak in establishment between 1800 and 1840 in FM (a total of 46 trees in 40 years). In [19]

1080 Table 4. Stem diameter growth for beech, silver ﬁr and sycamore in FM and GV. Potential versus present in each plot Potential n

Present Growth rate

n

Growth rate

FM Fagus sylvatica Abies alba Acer pseudoplatanus

10 6 3

1.37 1.6 1.3

31 7 6

1.47 1.7 1.26

NS NS NS

GV Fagus sylvatica Abies alba Acer pseudoplatanus

11 16 2

0.64 0.83 0.59

44 6 12

0.95 2.02 0.96

*** *** NS

11 16 2

Growth rate 0.64 0.83 0.59

** ** NS

44 6 12

0.95 2.02 0.96

*** NS NS

Potential versus potential per plot FM n 10 6 3

Growth rate 1.37 1.6 1.3

Present versus present per plot Fagus sylvatica 31 Abies alba 7 Acer pseudoplatanus 6

1.47 1.7 1.26

Fagus sylvatica Abies alba Acer pseudoplatanus

GV n

***p < .001 **p < .01 *p < .05 NS: not signiﬁcant

GV, the peak occurred 20 years earlier, between 1780 and 1820 (a total of 62 trees). Beech was the colonizing tree in more than 50% of the cases. After 1840, recruitment was continuous but weak (approximately 2–4 trees per 20 yearperiod except in 1920–1940 in FM). Before 1780–1800, trees were very sparse (probably most of them have died since that time): two silver ﬁrs born respectively in 1640 and 1680, two beech trees born in 1680 and 1720 and one Acer pseudoplatanus in 1760. Figure 6a, b illustrate age distribution in the two plots. Trees from 100 to 200 years of age were regularly distributed as small groups of similar ages. Trees in the 200- 300-year-old category, which had survived stress, pathogens or windstorms, were scattered as relics among these smaller groups. Trees under 100 years of age were clumped around gaps or at the margins of canopy trees. Canopy geometry and light pattern The two plots presented diﬀerences in canopy geometry and light patterns (Figure 7a, b; Table 5). Values from FM indicate a more open habitat than [20]

1081

Figure 4. Age-stem diameter distribution for Fagus sylvatica, Abies alba, Acer pseudoplatanus in FM and GV. Rs: Spearmann correlation coeﬃecient, ***: p < 0.001, **: p < 0.01, *: p < 0.05, NS: Not signiﬁcant

[21]

1082

Figure 5.

Tree establishment in GV and FM.

[22]

1083

Figure 6. (a) Tree age and spatial distribution in FM. (b) Tree age and spatial distribution in GV.

that in GV: canopy openness of 14.6% compared to 11.5% in GV; percentages of total incident light of 14.5% compared to 6.7% in GV. The diﬀerences can also be visualized when considering the horizontal variations in the gap [23]

1084

Figure 7a. Variations in canopy geometry and light condition in FM.

fraction and the total incident light (trans total): (i) for gap fraction, the highest value in FM reaches 22% compared to 16.5% in GV; (ii) for the total incident light, the highest value is 14.5% compared to 6.7% in GV.

[24]

1085

Figure 7b. Variations in canopy geometry and light condition in GV.

[25]

1086

Table 5. Mean and range of values of canopy geometry and of the distribution of light in GV and FM. n [26]

GV

21

FM

24

Mean values Range of extreme values Mean values Range of extreme values

CO%

LAI m2 m2

Trans direct mole m2 d1

Trans direct%

Trans diﬀuse mole m2 d1

Trans diﬀuse%

Trans total mole m2 d1

Trans total%

11.5 7–16.5 14.6 9.8–22

2.6 1.9–3.8 2.5 1.8–3

0.65 0.07–1.54 0.29 0.07–0.91

6.1 0.67–14.3 14.7 5.3–43.3

0.77 0.27–1.65 0.89 0.5–1.84

7.3 2.6–15.8 13.5 5.9–28

1.42 0.36–2.77 1.14 0.71–1.8

6.7 1.8–11.8 14.5 7.7–24.3

1087

Figure 8. Distribution of sun ﬂecks in FM and GV.

The sun ﬂeck distribution points to marked diﬀerences between FM and GV (Figure 8). In GV, the distribution is much more patchy, with a high number of small 5–10¢ sun ﬂecks (970 compared to only 201 in FM) in relation to the higher tree density and more complex forest architecture. There were some very long sun ﬂecks in GV (reaching 155¢) which were not observed in FM (maximum: 65¢). These long sun ﬂecks, that originated from the horizon, occurred in only one photo site near the border of the plot. Canopy geometry and PAR values vary according to the solar zenith angles. In GV, gap fraction values ranged from 22.5 to 32.5, while in FM the angles where gap fractions were highest ranged from 2.5 to 22.5. The zenithal angles where incident light was highest was, in both cases, between 32.5 and 72.5 degrees, corresponding to the slope and the topographic mask. Discussion Forest dynamics near the timber-line The examples given in plots FM and GV indicate that mixed-beech forests are spatially and temporally heterogeneous. Both plots show wide variations in stem density, size-class distribution and age distribution that are ecological traits of woodlands in a nearly natural state. Despite a higher stem density, the GV site exhibited a lower volume of stem wood than the FM site. The importance of deadwood and discontinuities in the distribution of saplings and seedlings are also ecological features regularly observed in natural, shady woodlands in Europe and North America (Jones 1945; Leme´e 1978; Mayer and Neumann 1981; Peterken 1996; Schnitzler 2002). These stand characteristics, combined with the remarkable resistance of mixed-beech forests in the FM and GV reserves (as compared to trees in the surrounding [27]

1088 managed forest stands) to the historical december 1999 storm (Schwoehrer personal observation) indicate that forest stands in the two reserves have retained a relatively high degree of ‘naturalness’ (for a detailed discussion of the word ‘naturalness’, see Peterken 1996). This ﬁnding is of interest for the interpretation of forest dynamics. The mechanism of gap formation and development is linked to the scale of disturbance events and biotic processes (pathogens, predation, mast years). In the two reserves, mixed-beech forests near the timber-line included chronic, small-scale gap creation associated with the death of single, large trees or small groups of trees. The causes of death among relatively young trees were unknown, but no doubt multiple and thought to have resulted from either natural causes (windbreaks, pathogens, stem exclusion, severe drought) or anthropogenic inﬂuences (logging, air pollution). Natural and anthropogenic causes can also have a combined eﬀect. Signiﬁcant impacts were felt from the severe growth declines of silver ﬁr in 1917–1923; 1943–1951 and 1976–1983 due to a combination of reduced rainfall (particularly in 1976) and increased air pollution (Becker 1985, 1989; Ulrich and Williot 1994). The air pollution is worst on the eastern slopes of the Upper Vosges near the timber line, coming from Eastern Europe (Becker 1985). These events explain the large numbers of dead silver ﬁrs in the two plots. Fir decline may be due to direct acid deposition on leaves, as well as acidiﬁcation processes and nutrient deﬁciencies in soils with low buﬀering capacity. In GV and FM stands, however, soils derive from biotitic granite rock, the weathering of which is supposed to partially compensate for Ca and Mg losses. In both plots, soils should thus be less sensitive to acidiﬁcation than in other parts of the Vosges mountains, like those with base-poor sandstone and acid granite catchments. Some small-scale gaps have probably expanded and coalesced in the past, thus explaining the succession of trees close in age. But there is also evidence of large-scale disturbance events during the period from 1780 to 1840 which might be of anthropogenic origin: there is historical evidence of frequent logging in forests just below summit pastures at the beginning of the 19th century (Garnier 1994, 1998) The deep shade cast by the beech and silver ﬁr canopy explains why potential trees and regeneration are largely conﬁned to gap margins. The tendency for regeneration and ground ﬂora to form ellipsoid patches below canopy trees is typical of forest stands growing on very steep slopes into which sun ﬂecks penetrate obliquely through foliage, thus displaying a multitude of sun ﬂecks far from the gap (Pierrel 2001). Steep slopes play a role in the mutual inﬂuences seen between the light regime in understoreys and the canopy architecture. The steeper the slope, the shallower the soil and the lower the stem density (also related to altitude), the higher the canopy openness and penetration of incident light. In the Guebwiller mixed-beech forest canopy, openness averages 9.7% and only 2–15.7% of the total incident light is transmitted within the plot (Pierrel 2001). Light values are more important in GV and still more in FM. In the latter, the proximity of a [28]

1089 permanent gap further increases the lateral penetration of incident light. This explains why seedling densities are higher in FM and Acer pseudoplatanus can regenerate more easily there than in GV. Presence of that specie in FM have a retroactively impact and directly inﬂuences light arrival in the underlayer. A lot of Acer pseudoplatanus seeds is probably coming from outside, and thus Acer pseudoplatanus is probably invading the woodlands plots. Better light conditions also explain why potential trees and trees of the present have similar growth rates in FM: potential trees reach the canopy in 100 years, and their growth continues thereafter in the canopy at the same rhythm. In GV many potential trees have grown in shade, and growth rates are lower: the duration of the potential state lasts lasts 200 years or more. When potential trees arrive at full light, stem growth increases with the development of axes and foliage. Beech trees of the present however, grow less rapidly in GV than in FM which suggests less favorable growth conditions, probably due to the higher altitude. The present-day, large range of ages and sizes recorded between trees of the present in both plots can be interpreted as diﬀerences in growth patterns during tree development: (i.e. alternating suppressed and released-growing periods). Such growth processes have been recorded in all forests composed of shade trees (Leme´e 1978; Koop and Hilgen 1987; Peters 1992; Korpel 1995; Peterken 1996). Acer pseudoplatanus presents a diﬀerent strategy based on its rather low tolerance for shade. Young Acer pseudoplatanus trees are numerous in open, rocky areas or at margins, where there is no suppression phase. Harsher conditions near the summits (for example, only 3 months of age at 900–1000 m) explain why canopy trees are smaller than in forests at lower altitudes: only 40 m high for 300-year-old silver ﬁrs near the crests as compared to 52–55 m for 180-year-old silver ﬁrs in the Guebwiller natural reserve (Renaud et al. 2000). In managed stands in the Vosges, some beech trees have been known to reach 42 m in 120 years (a 2–3 mm annual growth rate between ages 20–70 according to Seynave 1999) compared to only 29 m in height for a 214year-old beech in plots of similar density. In the virgin forest of Dobroc (720– 1000 m altitude, granite), Slovakia, there are 45 m beeches that are 230-yearsold (Korpel 1995). Multi-stemmed beech shape is a particularity of forests growing near the timber line. Such architecture only occurs under conditions of stress (Carbiener 1966; Peters 1992; Closset 2000). These trees are not lower in stature than single-stemmed trunks as suggested by Givnish (1984), but they are more slender than single tree trunk of similar age. Actually, competition between genetically identical trees has an impact of the lower volume of stem wood. They form large, very stable individuals in the canopy because a multistemmed growth form ensures better mechanical stability for the tree (ClossetKopp and Schnitzler (2000b), thus improving resistance to windthrow. Multi-stemmed individuals form clusters of genetically similar stems, with the

[29]

1090 potential for separate existence. This explains why stems may have diﬀerent sizes and growth rates as related to age and social state. At the present stage in the evolution of the two plots, old trees are very rare. The three trees which are more than 300-years-old discovered in the plots are the only ones recorded in the upper Vosges to date, but clearly more studies could be done on this subject. The absence of very old trees diﬀerentiates forests of the Upper Vosges from other virgin mixed-beech forests in Europe where there are silver ﬁr trees more than 400-years-old, and many more beech trees above the age of 350 (Mayer and Neumann 1981; Korpel 1995; Cenusa 2001; Schnitzler 2002). Given the present day composition of potential tree, we can predict that beech will dominate the canopy.

Objectives and priorities of woodland nature conservation in the upper Vosges Forest stands in the two reserves represent lesser-managed stands in the Upper Vosges, but human impacts have nonetheless been multiple, and often irreversible. Remnants of more natural forest stands are located near the summits and on steeper slopes, an inaccessibility which limits the data needed for a comprehensive analysis of forest dynamics. The present-day surface of strictly protected forests is also too small and too intermixed with managed forests and open landscapes to serve as reference points for management principles, because they are not representative enough of a completely pristine landscape. Given their rarity in Western Europe, these small areas must however be regarded as of utmost importance as a class of woodlands for nature conservation, research and education. A worthy objective of long-term conservation eﬀorts would be to re-create more substantial examples of missing types of mixed-beech forests in the upper Vosges, and in the meantime, to leave unmanaged the remaining forests located in natural reserves.

Acknowledgment We gratefully acknowledge the Parc Naturel Regional des Ballons des Vosges for ﬁnancial support through the study project from C. Schwoehrer. We are also much indebted to J.L. Dupouey for his invaluable assistance in dendrology and the logistical support of his laboratory (INRA Champenoux). We also wish to express their gratitude to Y. Despert, L. Domergue, C. Kieﬀer and P. Behr who have contributed core and data sampling.

References Becker M. 1985. Le de´pe´rissement du sapin dans les Vosges. Quelques facteurs lie´s a` la de´te´rioration des cıˆ mes. Revue Forestie`re Franc¸aise 37: 281–287.

[30]

1091 Becker M. 1989. The role of climate on present and past vitality of silver ﬁr forests in the Vosges mountains of northeastern France. Can. J. Forest. Res. 19: 1110–1117. Bogenrieder A. 2001. Schwarzwald und Vogesen - ein vegetationskundlicher Vergleich. Mitteilungen des Badischen Landesvereins fu¨r Naturkunde und Naturschutz 17: 745–792. Bonneau M. 1995. Fertilisation des foreˆts dans les pays tempe´re´s. ENGREF, Nancy. Bonneau M., Faivre P., Gury M., He´tier J.M. and Le Tacon F. 1978. Carte pe´dologique de la France a` 1/100000. Notice explicative, Saint-Die´. INRA, Service d’Etude des Sols et de la Carte Pe´dologique de la France, pp. 11. Bradshaw R. and Holmqvist B. 1999. Danish forest development during the last 3000 years reconstructed from regional pollen data. Ecography 22: 53–62. Brethes A., Brun J.J., Jabiol B., Ponge J.F. and Toutain F. 1992. Typologie des formes d’humus. In: Baize D. and Girard M.C.R (eds), e´fe´rentiel Pe´dologique, Association Franc¸aise pour l’Etude du sol. INRA, Paris, pp. 177–192. Carbiener R. 1966. La ve´ge´tation des Hautes Vosges dans ses rapports avec les climats locaux, les sols et la ge´omorphologie. The`se de Doctorat d’Etat, University of Orsay, France. Cenusa R. 2001. Les montagnes de Calimani. Les foreˆts vierges de Roumanie, Giurgieu, Donita, Bandku, Radu, Cenusa, Dissescu, Stoiculescu, Biris. ASBL Foreˆt wallone, pp.179–184. Chazdon R.L. and Pearcy R.W. 1986. Photosynthetic light environments in a lowland and tropical rain forest in Costa Rica. J. Ecol. 72: 533–564. Closset D. and Schnitzler A. 2000a. Naturalite´ de la heˆtraie d’altitude dans la Re´serve naturelle du Frankenthat Missheimle. University of Metz-Parc Naturel Re´gional des Ballons des Vosges. Internal Report 37p. Closset D. 2000. Sylvige´ne`se et naturalite´ de la heˆtraie d’altitude dans la Re´serve Naturelle du Frankenthal-Missheimle. DEA Sciences Agronomiques, University of Metz. COST Action E4 EU 1999. (European corporation in science and technology) Forest Research Network Final report. Mission, goals, outputs, recommendations, linkage and patterns. Oﬃce for Oﬃcial Publications of the European Communities, Luxembourg. Denslow J.S., Schultz J.C., Vitousek P.M. and Strain B.R. 1990. Growth responses of tropical shrubs to treefall gap environments. Ecology 71: 165–179. Duchaufour P. and Bonneau M. 1959. Une nouvelle me´thode de dosage du phosphore assimilable dans les sols forestiers. Bulletin de l’Association Franc¸aise pour l’e´tude du sol 4: 193–198. Edelin C. 1977. Images de la`rchitecture des conife`res. PhD thesis, University of Montpellier. Ellenberg H. 1988. Vegetation of Middle Europe. Cambridge University Press, Cambridge. Franks D.A. and McNaughton F. 1991. Stability increases with diversity in plant communities: empirical evidence from the 1988 Yellowstone drought. Oikos 62: 360–362. Frazer G.W., Canham C.D. and Lertzman K.P. 1999. Gap Light Analyser (GLA), Version 2.0: Imaging software to extract canopy structure and gap light transmission indices from true-colour ﬁsheye photographs, User’s Manual and Program Documentation. Copyright 1999: Simo, Fraser University, Burnaby, British Columbia, and Institute of Ecosystem Studies, Millbrook, New York. Garnier E. 1994. L’homme et son milieu: le massif du Grand Ventron a` travers les aˆges. Parc Naturel Re´gional des Ballons des Vosges, Internal Report. Garnier E. 1998. Jalons pour une histoire de l’environnement: la re´serve naturelle du FrankenthalMissheimle. Relations des socie´te´s et du milieu. Parc Naturel Re´gional des Ballons des Vosges, Internal report. Gilg O. 1997. Ele´ments d’e´valuation de la naturalite´ des e´cosyste`mes forestiers vosgiens. Ele´ments conceptuels et me´thodologiques, application aux heˆtraies-sapinie`res de la re´serve naturelle du massif du Grand Ventron, DEA, University of Aix Marseille. Givnish T.J. 1984. Leaf and canopy adaptations in tropical forests. In: Medina E., Mooney H.A. and Vasques-Yanes C. (eds), Physiological Ecology of Plants of the Wet Tropics. Junk, The Hague, pp. 51–83. Halle´ F. and Oldeman R.A.A. 1970. Essai sur l’architecture et la dynamique de croissance des arbres tropicaux. Masson, Paris.

[31]

1092 Halle´ F., Oldeman R.A.A and Tomlinson PB. 1978. Tropical Trees and Forests: An Architectural Analysis. Springer Verlag, Berlin. Helle T. and Ja¨rvinen O. 1986. Population trends in North Finnish land birds in relation to their habitat selection and changes in forest structures. Oikos 46: 107–115. Heuze´ P. 2002. Impact a` moyen terme des grands herbivores sur la heˆtraie-sapinie`re vosgienne. PhD Thesis, University of Metz. Jones E. W. 1945. The structure and reproduction of the virgin forest of the north temperate zone. New Phytologist 44: 130–148. Koop H. and Hilgen P. 1987. Forest dynamics and regeneration mosaic shifts in unexploited beech (Fagus sylvatica) stands at Fontainebleau (France). Forest Ecol. Manag. 20: 135–150. Koop H. 1989. Forest Dynamics. Silvistar: A Comprehensive Monitoring System. Springer Verlag, Berlin. Korpel S. 1995. Die Urwa¨lder der Westkarpaten. Gustav Fischer, Stuttgart. Leibendgut H. 1959. U¨ber Zweck und Methodik der Struktur und Zuwachsanalyse von Urwa¨ldern. Schweiz Zeitschrift fu¨r Forstwesen. 110: 110–124. Leme´e G. 1978. Structure et Fonctionnement des Ecosyste`mes Terrestre. Masson, Paris. Mansuy D. 1992. Les granites et la couverture pe´dologique dans le bassin du Rouge Rupt. Leurs participations au controˆle de l’acidiﬁcation des eaux (Cornimont – Vosges me´ridionales). PhD thesis, University of Nancy. Mayer H and Neumann M. 1981. Struktureller und entwicklungsdynamischer Vergleich der Fichten-Tannen-Buchen Urwa¨lder Rothwald Niedero¨sterreich und Corkova Urwald. Kroatien Forstwissenschaftliches Centralblatt 100: 111–132. Motta R., Nola P. and Piussi P. 2002. Long-term investigations in strict forest reserve in the eastern Italian Alps: spatio-temporal origin and development in two multi-layered subalpine stands. J. Ecol. 90: 495–507. Nicolini E. 1997. Approche morphologique du de´veloppement du heˆtre (Fagus sylvatica.). PhD thesis, Universite´ de Montpellier. Oberdorfer E. 1991. Die hochmontanen Wa¨lder und subalpinen Gebu¨sche. Der Feldberg im Schwarzwald. Subalpine Insel im Mittelgebirge. (Landesantstalt fu¨r Umweltschutz BadenWu¨rtemberg), Karlsruhe. Oberdorfer E. 1992. Su¨ddeutsche Pﬂanzen-Gesellschaften. Teil IV: Wa¨lder und Gebu¨sche. Gustav Fischer Verlag, Stuttgart. Oﬃce National des Foreˆts 2000. Evaluation de l’impact des ongule´s sur la ve´ge´tation forestie`re du Frankenthal-Missheimle. Parc Naturel Re´gional des Ballons des Vosges, Internal Report. Ooisterhius L., Oldeman R.A.A. and Sharik T.L. 1982. Architectural approach to analysis of North American temperate deciduous forests. Can. J. Forest Res. 12: 835–847. Oldeman R.A.A. 1974. L’architecture de la foreˆt guyanaise. Me´moires ORSTOM 73: 73. Oldeman R.A.A. 1979. Quelques aspects quantiﬁables de l’arborigene`se et de la sylvige´ne`se. Ecologica Plantarum 143: 289–312. Oldeman R.A.A. 1990. Forests: Elements of Silvology. Springer Verlag, Berlin. Orsini L. and Remy J.C. 1976. Utilisation du chlorure de cobaltihexamine pour la de´termination simultane´e de la capacite´ d’e´change et des bases e`changeables des sols. Science du Sol 4: 268–275. Peterken G. P. 1996. Natural Woodlands: Ecology and Conservation in Northern Temperate Regions. Cambridge University Press, Cambridge. Peters R. 1992. Ecology of beech forests in the northern hemisphere. Ph.D thesis, University of Wageningen. Pierrel S. 2001. De´termination du climat lumineux, a` l’aide de photographies he´misphe´riques et de ses relations avec la re´partition de la ve´ge´tation dans une heˆtraie sapinie`re de la re´serve biologique inte´grale en foreˆt domaniale de Guebwiller. DEA. University of Strasbourg, France. Renaud J.P., Kustner C. and Hauschild R. 2000. La Re´serve Biologique Domaniale de Guebwiller (Haut-Rhin). Pre´sentation ge´ne´rale et re´sultats d’un premier inventaire re´alise´ selon le protocole europe´en COST. Oﬃce National des Foreˆts, Internal Report. Roloﬀ A. 1999. Tree vigor and branching pattern. Journal of Forest Science 45: 206–216.

[32]

1093 Schnitzler A. 2002. Ecologie des foreˆts naturelles d’Europe. Biodiversite´, sylvige´ne`se, valeur patrimoniale des foreˆts primaires. Lavoisier, Paris. Schwoehrer C. and Despert Y. 1999. Re´serve naturelle du FM, plan de gestion. Parc Naturel Re´gional des Ballons des Vosges, Internal Report. Schwoehrer C. 1999. Re´serve naturelle du massif du Grand Ventron, plan de gestion. Internal Report PNRBV. Seynave I. 1999. Analyse de la structure de deux peuplements forestiers me´lange´s e´quiennes: la sapinie`re-heˆtraie et la cheˆnaie-heˆtraie dans le nord-est de la France. Ph.D thesis, ENGREF, Nancy. Sittler B., Tennhardt T. and Shicarts E. 2000. Die Schu¨tzgebiete Russlands vor neuen Herausforderungen. Natur und Landschaft 75: 1–9. Souchier B. 1971. Evolution des sols sur roches cristallines a` l’e´tage montagnard (Vosges). Me´moire Service Carte ge´ologique. Alsace Lorraine, pp.33. Untereiner A., Advocat A. Stoehr B. and Despert Y. 2002. Carte de la ve´ge´tation de la Re´serve naturelle du Frankenthal Missheimle. Parc Naturel Re´gional des Ballons des Vosges, Internal Report. Ulrich E. and Williot B. 1994. Les de´poˆts atmosphe´riques en France de 1850 a` 1990. ONF, Internal Report. Vallauri D. and Poncet L. 2003. La protection des foreˆts en France me´tropolitaine. Livre blanc sur la protection des foreˆts naturelles en France. Lavoisier, Paris. Varlet-Granchet C., Gosse G., Chartier M., Sinoquet H., Bonhomme R. and Allirand J.M. 1989. Mise au point: rayonnement solaire absorbe´ ou intercepte´ par un couvert ve´ge´tal. Agronomie 9: 419–439. Vester H. 1997. The Trees and the Forest. The role of tree architecture in canopy development; a case study in secondary forests (Araracuara, Columbia) PhD thesis, University of Wageningen. White P.S. 1978. Pattern process and natural disturbance in vegetation. Bot. Rev. 45: 229–299.

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Biodiversity and Conservation (2006) 15:1095–1107 DOI 10.1007/s10531-004-1868-4

Springer 2006

-1

The eﬀects of climate change on the long-term conservation of Fagus grandifolia var. mexicana, an important species of the Cloud Forest in Eastern Mexico OSWALDO TE´LLEZ-VALDE´S*, PATRICIA DA´VILA-ARANDA and RAFAEL LIRA-SAADE Laboratorio de Recursos Naturales, Unidad de Biologı´a, Tecnologı´a y Prototipos, Facultad de Estudios Superiores Iztacala UNAM., Av. de los Barrios 1, Los Reyes Iztacala, Tlalnepantla, C.P. 54090, Estado de Me´xico, Me´xico; *Author for correspondence (e-mail: [email protected]; phone: +01-55-56-23-11-27; fax: 01-55-56-23-12-25) Received 23 July 2003; accepted in revised form 22 July 2004

Key words: BIOCLIM, Bioclimatic modeling, Climate change, Cloud forest, Fagus, Sierra Madre Oriental Abstract. We examined the eﬀects of climate change on the future conservation and distribution patterns of the cloud forests in eastern Mexico, by using as a species model to Fagus grandifolia Ehr. var. mexicana (Martı´ nez) Little which is mainly located in this vegetation type, at the Sierra Madre Oriental. This species was selected because it is restricted to the cloud forest, where it is a dominant element and has not been considered for protection in any national or international law. It is probably threatened due to the fact that it plays an important social role as a source of food and furnishing. We used a ﬂoristic database and a bioclimatic modeling approach including 19 climatic parameters, in order to obtain the current potential distribution pattern of the species. Currently, its potential distribution pattern shows that it is distributed in six diﬀerent Mexican Priority Regions for Conservation. In addition, we also selected a future climate scenario, on the basis of some climate changes predictions already proposed. The scenario proposed is characterized by +2 C and 20% rainfall in the region. Under this predicted climatic condition, we found a drastic distribution contraction of the species, in which most of the remaining populations will inhabit restricted areas located outside the boundaries of the surrounding reserves. Consequently, our results highlight the importance of considering the eﬀects of possible future climate changes on the selection of conservation areas and the urgency to conserve some remaining patches of existing cloud forests. Accordingly, we believe that our bioclimatic modeling approach represents a useful tool to undertake decisions concerning the deﬁnition of protected areas, once the current potential distribution pattern of some selected species is known.

Introduction The cloud forests represent one of the most interesting biological systems in the Neotropical region (Luna et al. 1999). They are usually rare, vulnerable and threatened in the world. Its northern distribution limit is the Sierra Madre Oriental, in the state of Tamaulipas, Mexico (Briones 1991) and its southern one reaches Argentina (Webster 1995). [35]

1096 In Mexico, the cloud forests are characterized by being island-like or archipelagic. In other words, they are arranged in isolated patches that usually bear a rich ﬂora, with many endemic species (Rzedowski 1996; Luna et al. 2001). In the last years, the interest for studying the cloud forests, in particular their species richness and conservation, has been raised (Churchill et al. 1995). The reason for this interest is based on the high rates of deforestation and loss of cloud forests due to the introduction of cultivars, especially coﬀee (Moguel and Toledo 1999), but also to its irrational use for other agricultural activities, as well as for forestry and cattle farming purposes. It is recognized that these forests are threatened all over the world and that the damage that they have suﬀered is irreversible, due to their high disturbance vulnerability (Luna et al. 1988; McNeely et al. 1995). Fortunately, many of these forests are restricted to inaccessible sites in the mountains and consequently, they are still present and reasonably well conserved. In contrast, those located in places where human being has access have been drastically transformed to secondary pasture and cultivated lands. A few former studies have attempted the identiﬁcation of priority areas for the conservation of the Mexican cloud forests, using Parsimony Analysis of Endemicity and other biogeographic approaches (Morrone and Crisci 1995; Morrone and Espinosa 1998). Even though these studies have highlighted the importance and need to protect the cloud forests, they have not considered either the probable eﬀects that the climatic change might cause in their future survival, conservation and distribution patterns, nor the proposal of some general conservation strategies to be undertaken in the coming years. We believe this information is very relevant, in order to focus our eﬀorts and resources to undertake accurate long-term conservation actions that can assure the survival of these unique plant communities. In particular, we decided to use Fagus grandifolia var. mexicana as our study model, due to its restricted distribution to the cloud forests. Although, this taxon has been also treated as F. mexicana (Lo´pez and Cha´zaro 1995), F. grandifolia Ehrh. var. mexicana (Martı´ nez) Little (Little 1965; Alca´ntara and Luna 2001), F. grandifolia Ehrh. (Johnston et al. 1989), or even as the subspecies Fagus subsp. mexicana (Shen 1992) that has not yet been published, we recognize the former as the accepted name. In accordance with the fossil record, Fagus grandifolia was present in eastern Asia during the late Oligocene and in western North America, including Alaska, during late Oligocene and early Miocene. However, its current distribution pattern is restricted to eastern North America (Canada and United States) and small patches of Mexico (Tamaulipas, Hidalgo, Veracruz y Puebla). The latter represent relictual areas of a former extensive cloud forest of Fagus grandifolia (Pe´rez 1994). Fagus grandifolia Ehrh. var. mexicana used to be a dominant and common tree representative of some of the Mexican cloud forests (Williams et al. 2003). Some of these cloud forests are restricted to the Sierra Madre Oriental, from the state of Tamaulipas in northeastern Mexico to the states of San Luis [36]

1097 Potosı´ , Quere´taro, Hidalgo, Puebla and Veracruz in central-eastern Mexico. In addition, we suspect that the species might be also present in the state of Oaxaca (Figure 1), but further ﬁeldwork should be done to prove it. Even though, Fagus grandifolia var. mexicana is restricted to the cloud forests and plays an important social role, as a source of food and for furnishing activities (Malda 1990), it has not been considered as either a rare, threatened or endangered species (Vovides et al. 1997; Oldﬁeld et al. 1998; Williams et al. 2003). However, some authors have already suggested the species rareness (Malda 1990; Lo´pez and Cha´zaro 1995). In particular, Perez (1994, 1999) considers that the species is endangered at the national level. He estimates that the total number of individuals of the species existing at the present is below 20,000. He also points out that the largest and most heterogeneous, genetically speaking, population is located at the state of Hidalgo, where 50% of the total number of individuals estimated for the country is located in this area. In addition, all these authors have highlighted the lack of nation and international laws for protecting and/or conserving the species.

Figure 1. Model of the potential distribution of Fagus grandifolia var. mexicana, on relationship to the known records. On the right corner the potential distribution of the species in the state of Oaxaca is shown. [37]

1098 Some recent data documenting the wild populations status of the species have been generated, especially in the states of Tamaulipas, Hidalgo and Veracruz (Williams et al. 2003). In some sites the species is considered extinct, whereas, in other places there are still some small patches of what used to be a cloud forest of Fagus grandifolia. So far, the species has not been recorded in the cloud forests of Quere´taro, which is a neighbor state of Hidalgo and San Luis Potosı´ and bears similar environmental conditions for hosting the species. Probably the absence of Fagus in Quere´taro is due to physiographic diﬀerences as suggested by Cartujano et al. (2002). However, it might be also possible that the species has been misidentiﬁed due to its morphological similarity to Carpinus sp., Ostrya sp. or Ulmus sp., as has been suggested by Lo´pez and Cha´zaro (1995). Thus, the purpose of this work is to undertake a comprehensive review of the current situation of the cloud forests in eastern Mexico by using Fagus grandifolia var. mexicana as our species model. Consequently, we attempted to undertake the following actions: (1) to document the current recorded distribution of the species in Mexico; (2) to obtain the potential distribution patterns of the species; (3) to assess the eﬀects that the potential distribution pattern of the species might have, under a climatic change scenario; (4) to evaluate the role that the Protected Natural Areas and the Priority Regions of Mexico will be playing for the long-term conservation of cloud forests; (5) to propose a general strategy for attempting the conservation of the oriental Mexican cloud forests. Accordingly, the approach of this work includes the utilization of bioclimatic models that enable to explain the current situation of the eastern cloud forests of Mexico, on the basis of the potential distribution pattern of a representative species (Fagus grandifolia var. mexicana) that is used as a model. In addition, we present an attempt to assess the future distribution of the cloud forests, using the species data, once a predicted scenario due to climatic change is included (Te´llez and Da´vila 2003).

Methods The plant geographic distribution information that we used in this analysis was obtained from the database of the World Information Network of Biodiversity (REMIB) (http://www.conabio.gob.mx/remib/doctos/remibnodosdb.html). The herbarium data were obtained from the National Herbarium of Mexico (MEXU), from 29 specimens that beard geo-referenced information (i.e. complete latitude, longitude, and elevation). The taxonomical identiﬁcation of the specimens was undertaken by Drs. Shen Shung-Fu and Kevin Nixon who are important specialists of the Fagaceae. On the other hand, the information concerning the vegetation structure and ecological attributes of the species that is included in the discussion of this work was obtained from relevant literature (Malda 1990; Lo´pez and Cha´zaro 1995; Luna et al. 2000; Williams et al. 2003). [38]

1099 The bioclimatic modeling approach used in this work was that of the program ANUCLIM (Houlder et al. 2000). The program uses mathematically and statistically interpolated climatic surfaces (digital ﬁles in raster format) that were estimated using the information obtained from a standard network of meteorological stations. The climatic surfaces or digital ﬁles were generated using thin plate smoothing spline methods in the ANUSPLIN package (Hutchinson 1991, 1995a, b, 1997; Hutchinson and Gessler 1994). These surfaces include long-term monthly mean values of precipitation and temperature from more than 6200 stations (4000 stations including temperature data and 6000 including precipitation data from the same set of stations). The estimated mean errors for those surfaces were between 8 and 13% for monthly precipitation values and about 0.4–0.5 C for temperature values. These errors are similar to those found in the standard meteorological instruments (Nix 1986). We produced a bioclimatic proﬁle for Fagus grandifolia var. mexicana, using the program BIOCLIM. The derivation of the bioclimatic proﬁle was based on selected-simple-matching thresholds. The values for each of the 19 bioclimatic parameters (Table 1), were assessed by a systematic scanning throughout a grid of data points. We used the proﬁle to predict potential distribution pattern of the species. Using the homoclime matching principle, we identiﬁed those points on the climate grid, where the climatic conditions were present within the limits summarized in the bioclimatic proﬁle of the species (Booth et al. 1987). We matched the bioclimatic proﬁles against a grid of data points that contained climatic data from the existing network of stations (bioclimatic

Table 1. Bioclimatic proﬁle of Fagus grandifolia var. mexicana (Fagaceae). Parameter

Minimum–maximum (Mean ± SD)

Annual mean temperature (C) Mean diurnal range (C) Isothermality (2/7) (C) Temperature seasonality (C of V) (%) Maximum temperature of warmest period (C) Minimum temperature of coldest period (C) Temperature annual range (5–6) (C) Mean temperature of wettest quarter (C) Mean temperature of driest quarter (C) Mean temperature of warmest quarter (C) Mean temperature of coldest quarter (C) Annual precipitation (C) Precipitation of wettest period (C) Precipitation of driest period (C) Precipitation seasonality (C of V) (%) Precipitation of wettest quarter (C) Precipitation of driest quarter (C) Precipitation of warmest quarter (C) Precipitation of coldest quarter (C)

13.4–22.2 (16.6 ± 2.09) 8.2–15 (11.5 ± 1.88) 0.54–0.62 (0.59 ± 0.02) 0.61–1.1 (0.78 ± 0.17) 22.4–33.5 (26.3 ± 3.04) 5–9.9 (6.8 ± 1.16) 14.5–24.4 (19.5 ± 2.93) 14.3–24.7 (18 ± 2.72) 12.3–19.5 (14.6 ± 1.59) 15.5–25.6 (19.1 ± 2.48) 11–17.6 (13.4 ± 1.4) 824–2458 (1401 ± 367.19) 46–127 (75 ± 17.59) 0–15 (1 ± 3.67) 66–88 (77 ± 7.28) 418–1164 (691 ± 168.35) 52–201 (109 ± 42.39) 243–647 (397 ± 78.18) 52–239 (126 ± 54.41)

[39]

1100 parameters ﬁle). We used a regular grid of 30 arc seconds (0.00083 or approximately 1 km2) of spatial resolution. The geocoding errors were detected using the program ArcView 3.2. In addition, for a more detailed detection of anomalies and potential errors on the bioclimatic proﬁles, we used the program BIOCLIM (Houlder et al. 2000). Whenever possible, we corrected errors by using a 1:50,000 scale topographic maps. Fortunately, a single anomalous record was detected and removed. Finally, although the magnitude of climate change is uncertain and many diﬀerent future scenarios have been proposed, we generated just one climate scenario, as proposed by Karl (1998) and some other authors, whom have predicted similar future climatic conditions (Canziani and Diaz 1998; Giorgi et al. 1998; Neilson 1998). The program BIOCLIM was used, in order to set up the proposed future climate change scenario (year 2050), which shows a temperature increment of 2 C and a precipitation decrement of 20%, for any given present point, at the latitude and longitude where the range and the localities of the species are located. For inserting the climate change scenario, we produced a grid of indices in ARCINFO ASCIIGRID format through the BIOCLIM program and the Digital Elevation Model (DEM). The predicted distribution patterns of the selected species were plotted to represent the future potential distribution patterns found, after climate change conditions were entered. In this paper we only present the results of an extreme scenario for assessing the role the Priority Regions for Conservation (PRCs) proposed by CONABIO (Arriaga et al. 2000), will play in the future. The area covered by the potential distribution of the species was calculated with ArcView 3.2 (ESRI 2000).

Results The results obtained suggest that the present distribution pattern known for Fagus grandifolia var. mexicana, is indeed correct and complete, due to the fact that in all cases, the collecting sites ﬁtted within the limits of the potential distribution area obtained in the analysis (Figure 1). Thus, the species is restricted to the Sierra Madre Oriental from the state of Tamaulipas to southern Veracruz, as has been stated by Williams et al. (2003). However, on the basis of the potential distribution assessment of the species, we believe that probably its southern limit might extend to the state of Oaxaca. However, ﬁeld veriﬁcations should be done before we can assure it (Figure 1). The results also point out that the species is restricted to unique climatic conditions in the Sierra Madre Oriental, as it is shown in its bioclimatic proﬁle (Table 1). Its climatic uniqueness represents the speciﬁc spots or areas along the Oriental Sierra Madre where it can grow. In other words, although we state that Fagus grandifolia var. mexicana grows along the Sierra Madre, the fact is that it only grows in some speciﬁc areas that have a unique combination of climatic attributes and do not grow in others that have other climatic features. [40]

1101 On the basis of the species current potential geographic range, it is evident that it would be distributed in six Priority Regions for Conservation (Arriaga et al. 2000): (1) El Cielo Biosphere Reserve in the State of Tamaulipas, (2) Sierra Gorda-Rı´ o Moctezuma in the State of Quere´taro, (3) Cloud Forest of the Sierra Madre Oriental in the States of Hidalgo, Veracruz and Puebla, (4) Cuetzalan in the State of Puebla, (5) Pico de Orizaba-Cofre de Perote in the State of Veracruz and, (6) Oaxacan northern Sierra. The current potential distribution model of Fagus (the climatically suitable environments for the development of this species), covers about 5800 km2. However, once the climate change scenario was introduced, its potential distribution pattern contracts drastically in more than 66%. The remaining sites that will be suitable for the establishment of Fagus populations will be covering about 1700 km2 or in other words, about 1/3 of the original potential distribution range, including parts of the states of Quere´taro, Hidalgo, Puebla, and a very small portion of the state of Veracruz (Figure 2). Due to its drastic distribution pattern contraction, the remaining Fagus patches will probably coincide with only three of the Priority Regions for Conservation (PRCs 2, 3 and 4) in the states of Quere´taro, Hidalgo and Puebla and none will be present in the state of Veracruz (Figure 2).

Figure 2. Model of the potential distribution of Fagus grandifolia var. mexicana on relationship to the Priority Regions for Conservation (CONABIO), once the proposed climate change scenario was entered. [41]

1102 Discussion Independently of the taxonomical uncertainty of the studied taxon (whether it is a species, a variety or a subspecies), evidently, it is seriously threatened due to its intensive wood extraction, habitat fragmentation and the expansion of the agricultural land use in areas where it naturally grows. In addition, its restricted presence in the cloud forests increases its risk. Currently, the populations of Fagus grandifolia var. mexicana are distributed within the boundaries of at least ﬁve Priority Regions for Conservation (Arriaga et al. 2000), although the one from Oaxaca, remains to be proved. From them, the El Cielo Biosphere Reserve represents the only Protected Natural Area that has been oﬃcially declared. Consequently, the future protection of the cloud forest, Fagus grandifolia var. mexicana and other animal and plant species of the area is uncertain. The protection uncertainty of Fagus, has already been pointed out by Williams et al. (2003) and mentioned the extinction of the species populations from Teziutla´n, Puebla. In the case of the populations located at the Biosphere Reserve of El Cielo, in the state of Tamaulipas, the agricultural and cattle farming activities have caused a dramatic reduction of the cloud forest. Now, when the climatic change scenario is added to the current situation, the questions to be answered are the following: (1) Is it feasible to have a long-term conservation strategy to protect the cloud forest of the state of Tamaulipas and Puebla? and (2) Where do we have higher probabilities of conserving wellpreserved cloud forests in Mexico? It is clear that the cloud forest of Tamaulipas is already under strong disturbance pressures and consequently its structure and diversity has been already drastically altered. On the other hand, we believe that these communities are currently less modiﬁed in the states of Quere´taro and Hidalgo. Now, if in addition, the climate changes occur as it is proposed, the results obtained show that these states also seem to be the adequate cloud forest reservoirs, as has been partially suggested formerly by Luna et al. (2000). Alcantara and Luna (1997), mentioned that Hidalgo represents the state where the cloud forests in Mexico reach their larger extent. They also pointed out that in the central-eastern part of Hidalgo, this plant community still remains in the form of wealthy patches that cover around 100 km2 or more. In these patches, a total of 114 families, 301 genera and 452 species have been recorded by them. Several species of the region are listed in the Mexican Norm NOM-059-ECOL-2000 (Ano´nimo 2000), as vulnerable or in danger of extinction, such as Cyathea fulva, Deppea hernandezii, Nopalxochia phyllanthoides, Magnolia schiedeana, Rhynchostele rosii, Chamaedorea elegans, Psilotum complanatum, Symplocos coccinea and Ceratozamia mexicana (Vovides et al. 1997; Alcantara and Luna 1997). Consequently, Luna and Alca´ntara (2002) emphasize the need to focus the cloud forest conservation eﬀorts in the state of Hidalgo, where many endemic plant species for Mexico have been recorded, such as Bouvardia martinezii, [42]

1103 Carya palmeri, Ceratozamia mexicana, Cyathea mexicana, Dalbergia palo-escrito, Deppea hernandezii, D. microphylla and Magnolia dealbata, among others. In addition, these authors pointed out that some other taxa of the cloud forests that are disjunct between Mexico and the United States show very restricted distribution ranges in Mexico, as in the case of Illicium ﬂoridanum, Nyssa sylvatica and Schizandra glabra. In summary, this mixture of hardly known, rare and threatened species is part of a unique natural system that not only bears taxa from diﬀerent ancestral biotas, but also has high rates of species richness and endemicity, as well as, a very fragile habitat that unfortunately do not have any kind of protection. In the case of the cloud forests of the states of Quere´taro, it is documented that it bears a very rich ﬂora and plant communities. Cartujano et al. (2002), recorded 130 families, 465 genera and 774 species of vascular plants in the cloud forests of the eastern portion of this State. Among this diverse ﬂora, a number of endemics to Mexico or restricted endemics to the Sierra Madre Oriental are included (Cinnamomum bractefoliaceum, Clethra kenoyeri, C. pringlei, Ilex condensata and Inga huastecana, among others), as well as, some species listed as vulnerable, rare, or threatened (Magnolia dealbata, Tilia mexicana, Carpinus caroliniana and Litsea glaucescens, among others) under the Mexican Norm of Endangered Species NOM-059-ECOL2000. Despite the ﬂoristic richness and rareness of the cloud forests, timber extraction, livestock grazing and conversion of forest to farmland, which is risking its long-term conservation, represent the main recent disturbance sources of these forests. Unfortunately, precise assessments of the current destruction rate of these forests have not been done (Pe´rez 1994, 1999). Although, in the particular case of cloud forests there is not any former record documenting their probable shifts due to climate change in Mexico. A similar exercise assessing future distribution patterns of some cacti species was done by Te´llez and Da´vila (2003), in a semiarid region of central Mexico. They showed the drastic contraction of some of the cacti species potential distribution patterns, once the climatic changes conditions were included. In summary, in this work we attempted to highlight the importance of including the best biological knowledge available (geographic distribution, vegetation structure and ecology) and a bioclimatic modeling technique to assess the possible present and future role of any reserve or protected area. We also wish to emphasize the need to include Information concerning current and future environmental conditions and the potential distribution patterns of plants and animals, should be included in the decisions for selecting and establishing any reserve or protected area. Due to the methodology and the available data used, it is important to consider that the results obtained in this study might be slightly biased by some unrecorded errors or even by the lack of enough information. The

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1104 inclusion of only 29 records data for the model generation, might seems not representative of the species distribution pattern. However the records used cover, in general terms, all the environmental conditions that theoretically the species might occupy (the geographic, ecological and altitudinal range of the taxon). In addition, natural systems complexity represents a challenge for undertaking a modeling approach. In particular, the evident limitation of the bioclimatic models is the lack of inclusion of information concerning biotic interactions, evolutionary changes, as well as relevant biological processes such as dispersion (Pearson and Dawson 2003). Consequently, the existence of certain degree of errors is probably unavoidable. Also, the bioclimatic data, due to its own nature, shows two kinds of errors: (1) the omission (= the lack of consideration of the space that is occupied by the niche; (2) commission (= the consideration of a space that is not occupied by the niche). Consequently, each algorithm used to model a species ecological niche, has a combination of commission and omission errors (Peterson and Vieglais 2001). Even though, the existence of these errors is recognized, we believe that the bioclimatic modeling represents a useful tool or starting point for understanding the current and potential distribution patterns of animals and plants. Its usefulness has already been proved for some species at certain scales, in which this approach has generated relevant information (Pearson and Dawson 2003). In the case of this study, the model clearly reﬂects that the spatial climatic resolution used to correlate it to the species records that were included, enabled a precise and solid bioclimatic proﬁle of Fagus. Finally, we believe that with the present biological information, it is feasible and recommendable to carry out a similar exercise for other plant groups. Endemic species and main elements of plant communities should be especially important to be submitted to a bioclimatic modeling. By this means, we can increase the probability of proposing adequate conservation strategies. In the particular case of this study, the results obtained show that through the bioclimatic approach, we can be able to focus in long-term management, planning, and development of new, ﬂexible, and dynamic forms of wildlife and resource conservation (Nix 1986; Lindenmayer et al. 1991; Te´llez and Da´vila 2003).

Acknowledgements We thank to the anonymous reviewers for their valuable comments and corrections. To PAPCA 2002 program of the FES Iztacala UNAM for the ﬁnancial support to carry out part of this study.

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1105 References Alcantara O. and Luna V.I. 1997. Florı´ stica y ana´lisis biogeogra´ﬁco del bosque meso´ﬁlo de montan˜a de Tenango de Doria, Hidalgo, Me´xico. Anales del Instituto de Biologı´ a, Universidad Nacional Auto´noma de Me´xico, Serie Bota´nica 68: 57–106. Alca´ntara O. and Luna V.I. 2001. Ana´lisis ﬂorı´ stico de dos a´reas con bosque meso´ﬁlo de montan˜a en el estado de Hidalgo, Me´xico: Eloxochitla´n y Tlahuelompa. Acta Bota´nica Mexicana 54: 51–87. Ano´nimo 2000. Proyecto de Norma Oﬁcial Mexicana PROY-NOM-059-ECOL-2000, proteccio´n ambiental-especies de ﬂora y fauna silvestres de Me´xico-Categorı´ as de riesgo y especiﬁcaciones para su inclusio´n, exclusio´n o cambio. Lista de especies en riesgo. Diario Oﬁcial de la Federacio´n. de octubre de 2000. Arriaga L., Espinoza J.M., Aguilar C., Martı´ nez E., Go´mez L. and Loa E. (coordinadores) 2000. Regiones Terrestres Prioritarias de Me´xico. Comisio´n Nacional para el Conocimiento y Uso de la Biodiversidad, Me´xico. Booth T.H., Nix H.A. and Hutchinson M.F. 1987. Grid matching: a new method for homoclime analysis. Agric. For. Meteorol. 39: 241–255. Briones O.L. 1991. Sobre la ﬂora, vegetacio´n y ﬁtogeografı´ a de la Sierra de San Carlos, Tamaulipas. Acta Bota´nica Mexicana 16: 15–44. Canziani O.F. and Diaz S. 1998. Latin America. In: Watson R.T., Zinyowera M.C., Moss R.H. and Dokken D.J. (eds), The Regional Impacts of Climate Change: An Assessment of Vulnerability. Special Report of IPCC Working Group II. Cambridge University Press, Cambridge, UK, pp. 187–230. Cartujano S., Zamudio S., Alcantara O. and Luna I. 2002. El bosque meso´ﬁlo de montan˜a en el municipio de Landa de Matamoros, Quere´taro, Me´xico. Boletı´ n de la Sociedad Bota´nica de Me´xico 70: 13–44. Churchill S.P., Griﬃn III D. and Lewis M. 1995. Moss diversity of the Tropical Andes. In: Churchill S.P., Balslev H., Forero E. and Luteyn J.L. (eds), Biodiversity and Conservation of Neotropical Montane Forestes. Proceedings of the Neotropical Montane Forest Biodiversity and Conservation Symposium. The New York Botanical Garden, 21–26 June 1993, New York, pp. 335–348. ESRI (Environmental Scientiﬁc Research Institute) 2000. ArcView 3.2. ESRI. Redlands, California, USA. Giorgi F., Meehl G.A., Kattenberg A., Grassl H., Mitchell J.F.B., Stouﬀer R.J., Tokiioka T., Weaver A.J. and Wigley T.M.L. 1998. Simulated changes in vegetation distribution under global warning. In: Watson R.T., Zinyowera M.C., Moss R.H. and Dokken D.J. (eds), The Regional Impacts of Climate Change: An Assessment of Vulnerability. Special report of IPCC working group II. Cambridge University Press, Cambridge, UK, pp. 427–437. Houlder D.J., Hutchinson M.F., Nix H.A. and McMahon J.P. 2000. ANUCLIM 5.1 User Guide, Centre for Resource and Environmental Studies. Australian National University, Australian Capital Territory, Canberra. Houghton J.T., Callander B.A. and Varney S.K. 1992. Climate change 1992. The Supplementary Report to the IPCC Scientiﬁc Assessment. Cambridge University Press, Cambridge, UK. Hutchinson M.F. 1991. The application of thin-plate smoothing splines to continent- wide data assimilation. In: Jasper J.D. (ed.), BMRC Research Report Series. Bureau of Meteorology, Melbourne, Australia, pp. 104–113. Hutchinson M.F. 1995a. Interpolating mean rainfall using thin plate smoothing splines. Int. J. Geogr. Inform. Syst. 9: 385–403. Hutchinson M.F. 1995b. Stochastic space-time weather models from ground-based data. Agric. For. Meteorol. 73: 237–264. Hutchinson M.F. 1997. ANUSPLIN. Version 4.1. User guide, Centre for Resource and Environmental Studies, Australian National University, Australian Capital Territory, Canberra.

[45]

1106 Hutchinson M.F. and Gessler P.E. 1994. Splines – more than just a smooth interpolator. Geoderma 62: 45–67. Johnston M.C., Nixon K., Nesom G.L., and Martı´ nez M. 1989. Listado de plantas vasculares conocidas de la Sierra de Guatemala, Go´mez Farı´ as, Tamaulipas, Me´xico. Biotam 1: 21–33. Kappelle M., Van Vuuren M.M.I. and Baas P. 1999. Eﬀects of climate change on biodiversity. A review and identiﬁcation of key research issues. Biodiv. Conserv. 8: 1383–1397. Karl T.A. 1998. Regional trends and variation of temperature and precipitation. In: Watson R.T., Zinyowera M.C., Moss R.H. and Dokken D.J. (eds), The Regional Impacts of Climate Change: An Assessment of Vulnerability. Special Report of IPCC Working Group II. Cambridge University Press, Cambridge, UK, pp. 411–425. Lindenmayer D.B., Nix H.A., McMahon J.P., Hutchinson M.F. and Tanton M.T. 1991. The conservation of Leadbeater’s possum, Gymnobelideus leadbeateri (McCoy): a case study of the use of bioclimatic modelling. J. Biogeogr. 18: 371–383. Little E.L. Jr. 1965. Mexican beech, a variety of Fagus grandifolia. Castanea 30: 167–170. Lo´pez M.L. and Cha´zaro B.M. 1995. Plantas len˜osas raras del bosque meso´ﬁlo de montan˜a. I. Fagus mexicana Martı´ nez (Fagaceae). Boletı´ n de la Sociedad Bota´nica de Me´xico 57: 113–115. Luna V.I., Almeida L., Villers L. and Lorenzo L. 1988. Reconocimiento ﬂorı´ stico y consideraciones ﬁtogeogra´ﬁcas del bosque meso´ﬁlo de montan˜a de Teocelo, Veracruz. Boletı´ n de la Sociedad Bota´nica de Me´xico 48: 35–63. Luna V.I., Alca´ntara A.O., Espinosa O.D.E. and Morrone J.J. 1999. Historical relationships of the Mexican cloud forests: a preliminary vicariance model applying Parsimony Analysis of Endemicity to vascular plant taxa. J. Biogeogr. 26: 1299–1306. Luna V.I., Alca´ntara A.O., Morrone J.J. and Espinosa O.D.E. 2000. Track analysis and conservation priorities in the cloud forests of Hidalgo, Mexico. Div. Distribut. 6: 137–143. Luna V.I., Morrone J.J., Ayala A.O. and Organista D.E. 2001. Biogeographical aﬃnities among Neotropical cloud forests. Plant Systemat. Evol. 228: 229–239. Malda G.B. 1990. Plantas vasculares raras, amenazadas y en peligro de extincio´n en Tamaulipas. Biotam 2: 55–61. McNeely J.A., Gadgil M., Leveque C., Padoch C. and Reedford K. 1995. Human inﬂuences on Biodiversity. In: Heywood V.H. and Warton R.T. (eds), Global Diversity Assessment. Cambridge University Press, Cambridge, UK pp. 711–821. Moguel P. and Toledo M.V.M. 1999. Biodiversity conservation in traditional coﬀee systems of Mexico. Conserv. Biol. 13(1): 11–21. Morrone J.J. and Crisci J.V. 1995. Historical biogeography: introduction to methods. Annu. Rev. Ecol. Systemat. 26: 373–401. Morrone J.J. and Espinosa M.D. 1998. La relevancia de los atlas biogeogra´ﬁcos para la conservacio´n de la biodiversidad mexicana. Ciencia (Me´xico) 49: 12–16. Nix H.A. 1986. A Biogeographic analysis of Australian elapid snakes. In: Longmore R. (ed.), Atlas of the Elapid snakes of Australia. Flora and Fauna. 7: 4–15. Neilson R.P. 1998. Simulation of regional climate change with global coupled climate models and regional modelling techniques. In: Watson R.T., Zinyowera M.C., Moss R.H. and Dokken D.J. (eds), The Regional Impacts of Climate Change: An Assessment of Vulnerability. Special Report of IPCC Working Group II. Cambridge University Press, Cambridge, UK, pp. 439–456. Oldﬁeld S.F., Lusty C. and MacKinven A. 1998. The World List of Threatened Trees. World Conservation Press. Pearson R.G. and Dawson T.P. 2003. Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Global Ecol. Biogeogr. 12: 361–371. Pe´rez P.M. 1994. Revisio´n sobre el conocimiento dendrolo´gico, silvı´ cola y un censo de las poblaciones actuales del ge´nero Fagus en Me´xico. Tesis de maestrı´ a (Biologı´ a). Facultad de Ciencias. Universidad Nacional Auto´noma de Me´xico, Me´xico, DF, 146 pp.

[46]

1107 Pe´rez P.M. 1999. Las hayas de Me´xico.Monografı´ a de Fagus grandifolia spp. mexicana. Universidad Auto´noma Chapingo, Chapingo, Me´xico, 51 pp. Peterson A.T. and Vieglais D.A. 2001. Predicting species invasions using ecological niche modeling: new approaches from bioinformatics attack a pressing problem. BioScience 51: 363–371. Rzedowski J. 1996. Ana´lisis preliminar de la ﬂora vascular de los bosques meso´ﬁlos de montan˜a de Me´xico. Acta Bota´nica mexicana 35: 25–44. Pe´rez P.M. 1999. Las hayas de Me´xico.Monografı´ a de Fagus grandifolia spp. mexicana. Universidad Auto´noma Chapingo, Chapingo, Me´xico, 51 pp. Shen C.F. 1992. A monography of the genus Fagus Tourn. ex. L. (Fagaceae). Dissertation, City University of New York, New York. Te´llez V.O. and Da´vila A.P. 2003. Protected areas and climate change: a case study of the cacti in the Tehuaca´n-Cuicatla´n biosphere reserve, Me´xico. Conserv. Biol. 17(3): 846–853. Vovides A.P., Luna V. and Medina G. 1997. Relacio´n de algunas plantas y hongos mexicanos raros, amenazados o en peligro de extincio´n y sugerencias para su conservacio´n. Acta Bota´nica Mexicana 39: 1–42. Webster G.L. 1995. The Panorama of Neotropical Cloud Forests. In: Churchill S.P., Balslev H., Forero E. and Luteyn J.L. (eds), Biodiversity and Conservation of Neotropical Montane Forestes. Proceedings of the Neotropical Montane Forest Biodiversity and Conservation Symposium. The New York Botanical Garden, 21–26 June 1993, New York, pp. 53–77. Williams L.G., Rowden A. and Newton A.C. 2003. Distribution and stand characteristics of relict populations of Mexican beech (Fagus grandifolia var mexicana). Biol. Conserv. 109: 27–36.

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Biodiversity and Conservation (2006) 15:1109–1128 DOI 10.1007/s10531-004-2178-6

Springer 2006

Genetic diversity of Dalbergia monticola (Fabaceae) an endangered tree species in the fragmented oriental forest of Madagascar OLIVARIMBOLA ANDRIANOELINA1, HERY RAKOTONDRAOELINA2, LOLONA RAMAMONJISOA1, JEAN MALEY3, PASCAL DANTHU4 and JEAN-MARC BOUVET5,* 1

Silo national des Graines Forestie`res, Ambatobe BP 5091, Antananarivo, Madagascar; 2PCP Foreˆts et Biodiversite´/Foﬁfa DRFP BP 904, Antananarivo, Madagascar; 3Institut des Sciences de l’Evolution Universite´ de Montpellier II, cc 065, Universite´ Montpellier 2, Place Euge`ne Bataillon, 34095 Montpellier Cedex 05, France; 4PCP Foreˆts et Biodiversite´/Cirad, BP 853, Antananarivo, Madagascar; 5Cirad-Foreˆt, Campus international de Baillarguet TA10/C, BP 5035, 34398 Montpellier Cedex, France; *Author for correspondence (e-mail: [email protected]; phone: +33-467593728; fax: +33-467593733) Received 25 February 2004; accepted in revised form 2 August 2004

Key words: Chloroplast microsatellites, Conservation, Gene ﬂow, Genetic structure, Post-glacial recolonisation, RAPD Abstract. There is an urgent need to maintain and restore a broad genetic base for the management of Dalbergia monticola, a very economically important but endangered tree species in Madagascar. Random ampliﬁed polymorphism DNAs (RAPDs) and chloroplast microsatellite markers were used to quantify the genetic variation and to analyse the geographic distribution of diversity. Ten locations covering most of the natural range were sampled. Sixty-three RAPD polymorphic and 15 monomorphic loci were obtained from 122 individuals. Genetic diversity was low and very close among populations and regions. The unrooted neighbour-joining tree exhibited 4 groups, representing 6% (p = 0.000) of the total variation. The greater part of the variance, 81%, was observed within populations. A Mantel test suggested that genetic distances between populations were weakly correlated with geographic distances (R = 0.46, p = 0.12). The three chloroplast microsatellite primers assayed on 100 individuals gave 13 chlorotypes. Most of the populations showed 2 or 3 haplotypes. Haplotype diversity for the total population was equal to HeCp = 0.83 and ranged from 0.00 to 0.80 among the populations. The unrooted neighbour-joining tree exhibited 4 groups corresponding to the four regions representing 80% (p = 0.0000) of the total variation. Genetic diversity varies with regions, the north and south being less variable. Chlorotype distribution, the phylogenetic tree and historical information suggest that putative refugias in the centre-north region originating from the early Holocene could explain the pattern of variation observed today. By combining the results obtained at nuclear and organellar loci, a strategy of conservation based on evolutionarily signiﬁcant units is proposed.

Introduction The separation from Gondwana, 158–160 million years ago, has led to high endemism in Madagascar recognised as one of the most original in the world (Myers et al. 2000; Briggs 2003). About 80% of the plant species are endemic and the richness of fauna and ﬂora is great. Present patterns of the Malagasy [49]

1110 ecosystem have been determined by numerous factors such as climate change and human practices. Glaciation cycles, and especially the last maximum glaciation, are known to have had a strong impact on Malagasy species distributions (Burney 1996; Gasse and Van Campo 2001). Although known human presence is not very ancient in the island, 2000 years BP, practices such as ﬁre have also markedly inﬂuenced the distribution of species, especially since the 15th century (Straka 1996). The highlands would have ﬁrst undergone the action of ﬁre and today are covered with grass. More recently, over the two last centuries, the oriental forests have decreased dramatically due mainly to ‘‘slash and burn’’ practices. Today, primary vegetation probably still covers about 10% of the original area (Myers et al. 2000), so dense forest has been reduced to a fragmented landscape. In addition, forest exploitation has greatly increased over the last 50 years due to rising demand for wood as energy and saw timber. The combination of fragmentation and overexploitation threatens some economically and ecologically important tree species and a conservation strategy for these forest trees is urgently needed. Much research remains to be done to improve basic biological knowledge but, as a broad genetic base is required to maintain the evolutionary process and to preserve the gene pool, assessment of within-species genetic variation can be a useful tool when starting a conservation strategy (Newton et al. 1999; Cavers et al. 2003). Among methodologies employed to assess variation, those based on molecular markers are widely used with forest tree species (Newton et al. 1999). Random ampliﬁed polymorphism DNA (RAPD) is one of the most popular DNA-based approaches (Bekessy et al. 2002). It is the least technically demanding and oﬀers a fast method of providing information from a large number of loci, particularly in species where no study has been undertaken. Moreover, the diversity assessed by RAPD is comparable to that obtained with allozymes or RFLP (Wu et al. 1999; Esselman et al. 2000). There are some limitations, however, owing to their lack of reproducibility, and dominance prevents the distinction between homozygous and heterozygous individuals (Gillies et al. 1997). Chloroplast DNA markers are often used to study genetic diversity and structure, especially in combination with nuclear ones (Viard et al. 2001) and have provided useful information on colonisation and dispersal in plant species. Chloroplasts are maternally inherited in most angiosperms and paternally inherited in gymnosperms, so the level of diﬀerentiation is greater than bi-parental inheritance. Chloroplast microsatellite markers (cpSSRs) present high polymorphism and are now frequently used in phylogeographic forest tree analyses (Marshall et al. 2002; Palme´ and Verdramin 2002; Collevatti et al. 2003; Grivet and Petit 2003). Although molecular techniques have been widely used in tree species, no studies have been undertaken for Malagasy tree species. In this study we used both RAPD and cpSSRs to investigate the pattern of variation at the natural range scale of a species of rosewood: Dalbergia monticola Baker. This species is one of the major components of the oriental [50]

1111 forest of Madagascar but, for the reasons mentioned previously, it is threatened in its natural stands. Little research has been undertaken that provides information on ecological patterns and no information is available on genetic variation across the species range. The aims of this study were then (i) to quantify the genetic variation within and between populations using these two molecular markers, (ii) to analyse the geographic distribution of diversity in the natural range, and (iii) to deﬁne a conservation strategy based on molecular diversity.

Material and methods Species description – plant material Dalbergia monticola’s natural range extends from the northern part of Madagascar (region of Antalaha 15 latitude south) to the southern part (region of Fort Carnot 22 latitude south) forming a fragmented belt 1000 km long and 100 km wide (see the map in Figure 4). Adult trees frequently reach 20 m in height and 1 m in diameter at chest height. Recognised as a long-lived tree species (over 200 years), the natural populations are situated in two main climaxes: the submontane evergreen seasonal forest and the dense rainforest, of altitude ranging from 350 to 1600 m, mean temperature from 18 to 23 C, and mean annual rainfall from 750 to 2500 mm. Dalbergia monticola reproduces mostly sexually and is mainly insect pollinated, ﬂowering and fruiting from August to November, with some geographical variations. It fruits between July and September. The species is mainly barochorous, but its seeds can also be dispersed by animals such as birds, monkeys, and rodents, although no research has been conducted on this. Ten locations were identiﬁed, covering most of the natural range from the north to south of the island (Table 1), to sample the species. Within each location, between 6 and 25 trees were chosen randomly in fragmented forest. Due to the lack of trees in some sampling areas, the minimum distance between two consecutive trees was in some cases only 20 m (see range of distance in Table 1). The trees were generally small, most of them having a total height of 5–20 m and a diameter of 15–30 cm. This observation stresses the lack of adult trees due to the intense exploitation of the species. Five healthy leaves were collected from each tree and dried rapidly in the ﬁeld using silica gel.

DNA extraction DNA was extracted from dried leaves, following the modiﬁed protocol described by (Bousquet et al. 1990). Leaves (100 mg) were ground to a ﬁne powder with a [51]

1112 Table 1. Characteristics of the Dalbergia monticola populations sampled in the natural range. Region Location

N

Latitude Longitude Rainfall (mm)

T Elevation Distancea min–max C (m) (m)

North

12 10 17 11 11 10 7 6 25 20 139

1657¢S 1705¢S 1810¢S 1755¢S 1745¢S 1906¢S 1902¢S 1918¢S 2116¢S 2134¢S

12–28 12–28 12–29 12–29 12–29 10–26 10–26 10–26 17–27 10–26

Tsaramolotra Ampitsongona Centre- Didy north Antsevabe Ambohijahanary Centre Bekorakaka Madiorano Ankeniheny South Ranomafana Tolongoina Total a

4844¢E 4842¢E 4835¢E 4832¢E 4835¢E 4821¢E 4812¢E 4823¢E 4726¢E 4732¢E

750 750 1240 1240 1240 1790–2190 1790–2190 1790–2190 2900 2800

900–1200 900–1200 800–900 800–900 800–900 850–900 800–1100 800–1100 900–1000 800–1200

50–500 50–500 20–50 20–100 50–1500 50–1000 100–1500 100–500 20–200 20–1000

range of distance between two consecutive sampled trees.

mortar and pestle in a 1.5 ml Eppendorf tube under liquid nitrogen. DNA extraction buﬀer (5 ml) was added (100 mM Tris–HCl (pH 8.0), 20 mM EDTA, 1.4 M NaCl, 1% PEG 6000, 2% MATAB, 0.5% sodium sulphite). The tube was then incubated at 74 C for 20 min. Samples were washed with wet chloroform (CIAA, 24:1) to remove cellular debris and protein. After 15 min of centrifugation at 5000 · g, the liquid phase was transferred to 15 ml tubes. Isopropanol (5 ml) was added and mixed gently to precipitate the DNA. The resulting DNA pellets were resuspended in 400 ll of sterile water overnight at 37 C and stored at 20 C until required.

RAPD methods PCR ampliﬁcations were performed in a 20 ll reaction mix with 5 ll of DNA (3 ng/ll), 2 · buﬀer, 0.2 lM of each primer (OPB7, OPB11, OPN15, OPR15, OPW9, OPW12, OPW13, OPW14, OPX3, OPX6, OPX10), 5 U/ll of DNA Taq polymerase, completed with sterile water. The reaction mixture was overlaid with 40 ll of sterile mineral oil to prevent ﬂuid evaporation. All reactions were performed in Techne Cyclogene. Optimal ampliﬁcation conditions for RAPDs were 1 cycle of 3 min at 94 C (initial denaturation), followed by 45 cycles of 4 min at 94 C (denaturation), 1 min at 36 C (annealing) and 2 min at 72 C (extension). A ﬁnal step of 10 min at 72 C ensured full extension of all ampliﬁed products. RAPD bands were separated in 1.5% agarose gel, staining in ethidium bromide and visualised by UV transillumination. To reduce errors in comparison of RAPD proﬁles between diﬀerent PCR runs, the same 10 individuals were included in all PCR runs. Only RAPD bands that could be unequivocally scored were counted in the analysis. Bands of weight higher than 1700 bp and molecular weight lower than 300 bp were [52]

1113 not used so as to ensure good repeatability of the RAPD process and avoid misscoring.

Chloroplast microsatellite method Three universal microsatellite primers (Ccmp4, Ccmp6 and Ccmp7) described by Weising and Gardner (1999), and 1 tobacco microsatellite (Ntcp9) described by (Bryan et al. 1999) were tested over a subset of the total population. Among the 4 primer pairs tested in a sample of 8 individuals, 3 were polymorphic (Ccmp4, Ccmp6, and Ccmp7). For the primers Ccmp, PCR ampliﬁcations were done in a 8 ll reaction mix with 2 ll of DNA, 2 · buﬀer, 10 lM of each primer (R and F), 5 U/ll of DNA Taq polymerase, completed with sterile water. All reactions were performed in a ‘‘Stratagene’’ Thermocyclor. Optimal ampliﬁcation conditions were 1 cycle of 4 min at 94 C (initial denaturation), following by 30 cycles of 30 s at 94 C (denaturation), 1 min at 56 C (annealing) and 1 min at 72 C (extension). A ﬁnal step of 5 min at 72 C ensured full extension of all ampliﬁed products. PCR ampliﬁcations were done for the 9 primers in a 20 ll reaction mix with 5 ll of DNA, 10 · buﬀer, 2 lM of each primer (R and F), 5 mM of dNTPs, 50 mM of MgCl2, 99% of glycerol, 5 U/ll DNA Taq polymerase, completed with sterile water. Ampliﬁcation conditions are similar, except for the annealing temperature which is 55 C. Bands were separated and visualised in acrylamide gel.

Data analysis In the case of RAPD data, ampliﬁed DNA marker bands were scored in a binary manner as either present (1) or absent (0) and entered into a binary data matrix. Each PCR product was assumed to represent a single locus because homology is generally high at the intraspeciﬁc level. The frequency of each band and the percentage of polymorphic loci (%P) were calculated in each population. Shannon’s diversity index was P used to assess molecular variation. This parameter, deﬁned as IRAPD = i¼2 i¼1 pi log2 pi, where pi is the frequency of the RAPD phenotype (presence (1) or absence (0) of the band), is frequently used in the absence of assumptions concerning the Hardy–Weinberg equilibrium (Gillies et al. 1997; Martin and Hernandez Bermejo 2000). It was calculated for each locus and averaged over loci to provide the degree of variation within each population, IRAPDpop. Shannon’s index was also estimated for the whole sample considered as a single population, IRAPDtot. The expected genetic heterozygosity P Her was estimated with the ﬁxation index F equal to zero. HeRAPD ¼ 1 ni¼1 p2i (where pi is the frequency of the allele i in a population), [53]

1114 and the other diversity parameters, number of haplotypes (na), eﬀective number of haplotypes (ne ¼ 1 Pn1 2 , where pi is the frequency of the allele i in p i¼1 i

a population), percent of polymorphic RAPD loci (%P) and their standard errors were calculated with Popgene 1.32. (Yeh and Boyle 1997). For cpSSRs, because of the non-recombining nature of the chloroplast genome, cpDNA haplotypes were treated as alleles at a single locus. Chloroplast haplotype variation within populations was calculated with the same parameters as for RAPD (ICp HeCp ne) with Popgene software version 1.32. (Yeh and Boyle 1997). The genetic structure, for RAPD and cpSSRs, was estimated using analysis of molecular variance, AMOVA (Excoﬃer et al. 1992), with Arlequin software version 2000 (Schneider et al. 2000). The percentage variance within and among populations were estimated to partition the variation, and the associated P value was estimated with permutation techniques. To illustrate the genetic structure obtained with the two markers, a cluster analysis using the neighbour-joining method was conducted with the software package DARwin 4.0 (Perrier et al. 2003). The matrix of genetic distances was calculated using the AMOVA-derived Fst. The levels of diﬀerentiation among populations estimated from AMOVA for nuclear markers (FstRAPD) and chloroplast markers (FstCp) could be used to derive the pollen-to-seed migration ratio, using the following formula of (Ennos 1994): r ¼ mp =ms ¼ ½ðð1=FstRAPD Þ 1Þ 2ðð1=Fstcp Þ 1Þ=½ð1=Fstcp Þ 1Þ where mp and ms are pollen and seed migration rates, respectively. In the case of RAPDs the value is biased, and probably overestimated, due to the ampliﬁcation of the cytoplasmic genome. The association between geographic and genetic distances was estimated as a Spearman’s rank correlation coeﬃcient (q). The null hypothesis of the association was tested with the Mantel test using Fstat software (Goudet 2001). Minimum spanning networks between haplotypes (each network embedding all minimum spanning trees for a given distance matrix) were computed with the MINSPNET (Excoﬃer and Smouse 1994), provided with Arlequin software version 2000 (Schneider et al. 2000). The distance matrix between haplotypes was calculated using a distance matrix based on the square of the diﬀerence in microsatellite size with the formula Dij ¼

L X

ðail ajl Þ2

l¼1

where aij and ajl give the allele size in base pairs at the lth locus of individuals i and j, respectively. [54]

1115 Results Genetic diversity and structure with RAPD markers The 15 random primers generated a total of 65 RAPD polymorphic and 13 monomorphic loci ranging in size from 152 to 340 bp. This set of loci is expected to give a good sampling of the total genome and a good assessment of the genetic diversity. The number of bands per primer varied from 1 to 7. Table 2 shows that the diversity parameter for the total population was equal to 0.19 (0.15) and varied from 0.09 (0.16) for the population of Ankeniheni in the centre to 0.19 (0.21) for the population of Ambohijanahary in the centre north. Shannon’s diversity index followed the same pattern of variation, with a value for the total population equal to 0.30 (0.21) and a range between 0.15 (0.24) in Ankeniheni to 0.28 (0.27) in Ambohijanahary. The percentage of polymorphic loci varied from P = 30% in Ankeniheni to P = 65% in Didy (Table 2) and the total population value was 83%. Although diﬀerences between populations for na, ne, HeRAPDand IRAPD were marked, they were smaller than the standard deviation. No pattern of variation for na, ne, IRAPD, HeRAPD and %P was observed among the set of populations. For example, the relationship between diversity parameters and latitude was low, and the coeﬃcient of correlation between latitude and IRAPD was equal to R = 0.08, (associated p value = 0.80). When the four regions were compared, no speciﬁc trend was observed for the diversity parameter (Table 3). The diﬀerences between the parameters were lower than the standard error. The diﬀerentiation assessed among populations was marked. The analysis of molecular variance showed that 76% (p = 0.000) of the variation was present

Table 2. Population size (N), number of haplotypes (na), eﬀective number of haplotypes (ne), Shannon’s index (IRAPD), percent of polymorphic RAPD loci (%P), RAPD diversity (HeRAPD) for each population. The standard error of each parameter is given between brackets. Country

Population

N

na

ne

HeRAPD

IRAPD

%P

North

Tsaramalotro Ampisotgoina Ambohijanahary Antsevabe Didy Bekorokaka Madiorano Ankeniheny Ranomafana Tologoina

11 10 11 11 17 10 6 6 21 19 122

1.51(0.50) 1.49(0.50) 1.60(0.49) 1.43(0.50) 1.65(0.48) 1.52(0.50) 1.41(0.50) 1.30(0.46) 1.64(0.48) 1.52(0.50) 1.83(0.38)

1.21(0.30) 1.23(0.31) 1.30(0.35) 1.24(0.34) 1.25(0.29) 1.25(0.32) 1.20(0.30) 1.16(0.29) 1.20(0.24) 1.25(0.34) 1.27(0.27)

0.14(0.17) 0.14(0.17) 0.18(0.19) 0.14(0.19) 0.16(0.16) 0.15(0.18) 0.12(0.17) 0.09(0.16) 0.14(0.15) 0.19(0.19) 0.19(0.15)

0.22(0.24) 0.22(0.25) 0.28(0.27) 0.21(0.27) 0.26(0.24) 0.24(0.25) 0.19(0.25) 0.15(0.24) 0.23(0.22) 0.23(0.26) 0.30(0.21)

51 49 60 44 65 53 41 30 64 53 83

Centre-north

Centre

South Total

[55]

1116 Table 3. Population size (N), number of haplotypes (na), eﬀective number of haplotypes (ne), Shannon’s index (IRAPD), percent of polymorphic RAPD loci (%P), RAPD diversity (HeRAPD) for each region. The standard error of each parameter is given in brackets. Region

N

na

ne

IRAPD

HeRAPD

%P

North Centre-north Centre South

21 39 22 40

1.59(0.49) 1.73(0.44) 1.61(0.49) 1.74(0.44)

1.24(0.30) 1.29(0.29) 1.23(0.30) 1.25(0.28)

0.15(0.17) 0.19(0.16) 0.15(0.16) 0.16(0.16)

0.24(0.25) 0.30(0.24) 0.24(0.24) 0.27(0.23)

59 73 61 74

within populations, 18% (p = 0.000) among populations within region, and 6% (p = 0.000) among regions. As a result, the unrooted neighbour-joining tree obtained with RAPD markers (Figure 1) exhibited three main clusters corresponding to the three regions south, centre and the combination of

Figure 1. Unrooted neighbour-joining tree based on RAPD markers. The four regions are: the South (S), the Centre (C), the Centre-north (C-N), and the North (N). The tree was drawn with the Fst matrix given by analysis of molecular variance (Excoﬃer et al. 1992) with Arlequin software version 2000 (Schneider et al. 2000). [56]

1117 centre-north and north. The link of Antsevabe with the cluster of the south is diﬃcult to explain. This clustering suggested a good relationship between the geographical distance and the genetic distance. This was partly conﬁrmed by the Mantel test showing a coeﬃcient of correlation between genetic and geographic distances moderately high (R = 0.46), but not signiﬁcantly diﬀerent from zero (p = 0.12), this relationship is illustrated in Figure 2a.

Genetic diversity and structure with chloroplast microsatellite markers The three chloroplast microsatellite primers assayed on 100 individuals gave 10 diﬀerent alleles: Ccmp4, 2 alleles, Ccmp6, 4 alleles and Ccmp7, 4 alleles. The combination of the 3 loci and the 10 alleles gave 13 chlorotypes (Table 4). Except for Ampitsongoina, each population exhibited several haplotypes and generally one chlorotype was predominant. In the total population, the C11

Figure 2. Relation between genetic and geographical distances for the RAPD and chsloroplast microsatellite markers. Matrices of genetic distances were calculated using the AMOVA-derived Fst (Arlequin software version 2000 (Schneider et al. 2000)). [57]

1118 Table 4. Allelic characteristics in base pairs for the three loci, allelic combination of each chlorotype and frequencies of the chlorotypes present in each population and in the total population of Dalbergia monticola. Zone

Population

North

Tsaramalotro

N

Chlorotype

Ccmp4

Ccmp6

Ccmp7

Frequency

7

C3 121 120 152 0.14 C5 122 120 152 0.86 Ampitsongoina 6 C5 122 120 152 1.00 Centre-north Ambohijanahary 10 C1 122 119 151 0.20 C2 122 120 151 0.10 C4 122 119 152 0.20 C6 122 121 152 0.10 C9 122 120 153 0.30 C10 122 121 153 0.10 Antsevabe 11 C2 122 120 151 0.64 C4 122 119 152 0.36 Didy 15 C1 122 119 151 0.07 C2 122 120 151 0.66 C4 122 119 152 0.07 C5 122 120 152 0.07 C9 122 120 153 0.13 Centre Bekorokaka 6 C3 121 120 152 0.17 C8 121 120 153 0.67 C12 121 120 154 0.16 Madiorano 6 C8 121 120 153 0.83 C12 121 120 154 0.17 Ankeniheny 2 C2 122 120 151 0.50 C9 122 120 153 0.50 South Ranomafana 23 C7 122 122 152 0.04 C11 122 122 153 0.96 Tolongoina 14 C7 122 122 152 0.21 C11 122 122 153 0.58 C13 122 122 154 0.21 Frequencies in total population: C1(0.03), C2 (0.19), C3 (0.02), C4 (0.07), C5 (0.13), C6 (0.01), C7 (0.04), C8 (0.09), C9 (0.06), C10 (0.01), C11 (0.30) C12 (0.02), C13 (0.03)

haplotypes exhibited the highest frequency (30%), followed by C2 (19%) and C5 (13%) while others were lower than 10%. Haplotype diversity varied markedly among the populations and ranged from HeCp = 0.00 (Ampitsongoina) to HeCp = 0.80 (Ambohijanahary) (Table 5). For the total population it was equal to HeCp = 0.71. The number of alleles (na), eﬀective number of haplotypes (ne) and Shannon’s diversity index (ICp) followed the same pattern. No clear pattern of variation with latitude was observed when considering the within-population diversity. However, when the regional level was taken into account the results showed that the diversity parameters were higher in the centre-north and centre than in the north and south. For example, HeCp = 0.68 and 0.55 in the centre-north and centre, while HeCp = 0.14 and 0.32 in the north and south. [58]

1119 Table 5. Diversity parameters assessed with chloroplast microsatellite markers for each population and the total population of Dalbergia monticola. Population size (N), number of haplotypes (na), eﬀective number of haplotypes (ne), Shannon’s index (ICp), haplotypic diversity (HCp). Region

Population

N

na

ne

HeCp

ICp

North

Tsaramalotro Ampisongoina Ambohijanahary Antsevabe Didy Bekorokaka Madiorano Ankeniheny Ranomafana Tologoina

7 6 10 11 15 6 6 2 23 14 100

2 1 6 2 5 3 2 2 2 3 13

1.32 1 5 1.86 2.10 2 1.38 2 1.09 2.39 6.10

0.25 0.00 0.80 0.46 0.52 0.50 0.28 0.50 0.08 0.58 0.83

0.41 0.00 1.69 0.66 1.08 0.87 0.45 0.69 0.18 0.98 2.10

Centre-north

Centre

South Total

With cpSSR, the unrooted neighbour-joining tree exhibited four clusters corresponding to the four regions more distinctly than with RAPD data (Figure 3). Ankeniheny from the centre, however, was included in the cluster of the centre-north region, but the poor sample size of this population (2 individuals) can explain this unexpected position. This strong diﬀerentiation among populations was conﬁrmed by the analysis of molecular variance. The variation among groups represented 80% (p = 0.0000) of total variation, the within-group variation among populations 4% (p = 0.000) and the betweenindividual variation within populations 16% (p = 0.000).

Phylogenetic relation and geographic distribution of the haplotypes The distribution of the 13 haplotypes across the natural range showed a geographical structure (Figure 4). Some haplotypes were present in contiguous populations and regions but none was scattered among distant populations and regions. The network of haplotypes in Figure 4b shows that haplotype C5 has the highest number of connections and C5 is among the most frequent (13%). Generally, haplotypes that are closely related to each other, diﬀering by a single mutation at a microsatellite repeat, are geographically close. For example, the set of haplotypes C7, C11 and C13 is located in the south, haplotypes C1, C2, C4, C1 and C5 are in the centre-north, haplotypes C8, C9, C12, and C10 are in the centre and haplotypes C3, C5 in the north. This relation of isolation by distance is conﬁrmed by the signiﬁcant correlation between genetic distance (Fst) and geographic distance (q = 0.57; p = 0.02). Figure 2b shows that this linear relationship increased strongly up to 300 km and then reached a plateau, emphasising that Fst is more or less constant and close to 1 after this distance. [59]

1120

Figure 3. Unrooted neighbour-joining tree based on chloroplast microsatellites markers. The four regions are: the South (S), the Centre (C), the Centre-north (C-N), and the North (N). The tree was drawn with the Fst matrix given by analysis of molecular variance (Excoﬃer et al. 1992) with the Arlequin software version 2000 (Schneider et al. 2000).

Discussion Genetic diversity of Dalbergia monticola Although the oriental forest is strongly fragmented, the impact of fragmentation due to human agriculture on the dynamics of the genetic diversity within the remaining fragments of Dalbergia monticola is likely to be still limited because it is a very recent phenomenon. It takes several generations before the impact of genetic drift can be observed. However, the natural range of Dalbergia monticola was likely to be wider in the recent past and the second wave of settlement from the 15th century had probably reduced the whole population in Madagascar and consequently the genetic diversity of the species. With polymorphic and monomorphic loci used for calculation, the mean intraspeciﬁc genetic diversity of Dalbergia monticola obtained with RAPD markers is smaller than that estimated for other tree species (Bekessy et al. [60]

1121

Figure 4. (a) Geographic distribution of the 13 chlorotypes in the natural range of Dalbergia monticola (the limit of the natural range is represented by the dark line). The size of the circle is proportional to the size of the sample. (b) Minimum spanning network among the 13 haplotypes found in the natural range of Dalbergia monticola. The size of the circle is proportional to the frequency of the haplotype in the total population. The connection length is equal to one for the dark line and two for the dotted line.

2002; Newton et al. 2002; Bouvet et al. 2004). Shannon’s diversity index for these species ranged from 0.42 to 0.65, whereas it is 0.30 (0.21) for D. monticola. Values of expected heterozygosity are similar to those estimated for perennial species growing on smaller islands, but the percentage of polymorphic loci in Dalbergia monticola is higher (Kwon and Morden 2002). Although RAPD markers should be considered with caution as they are not a good predictor of total genetic diversity (Nybom and Bartish 2000), the low values of estimated diversity parameters in this species could be explained by the limited range of the species. An island population contains less genetic diversity than a mainland population (Barett 1998). Although Madagascar is a single large island the isolation from other sources gene could favour the eﬀect of genetic drift. Another factor that can explain the low diversity is a recent and rapid expansion after a bottleneck (Savolainen and Kuittinen 2000). There are few published studies concerning the diversity of cpSSrs in angiosperm tree species. The present study shows, however, that the results varied according to the species and the number of primers used. With 3 primers, 100 individuals distributed in 10 populations, the 13 haplotypes identiﬁed in Dalbergia monticola are consistent with previous studies on angiosperms (Palme´ and Verdramin 2002; Grivet and Petit 2003). In addition, the haplotypic heterozygosity HeCp = 0.88 is high compared with estimates for other tree species (Palme´ and Verdramin 2002) and suggest high diversity compared to a number of temperate tree species studied. [61]

1122 Genetic structure and gene ﬂow The distribution of genetic diversity with RAPD markers indicates that most of the variation is present within populations (81%). This can be explained by some biological patterns such as long-lived woody perennials and outcrossed insect pollination species according to Nybom and Bartish (2000). Nested analysis of variance with RAPDs shows that only 6% of the total variation is attributed to among-group variation, 16% to among populations within groups, and 76% among individuals within populations. This is low but signiﬁcant diﬀerentiation among regions and populations is closely related to the correlation (moderately high but not signiﬁcant) between the geographic and genetic distance. This pattern of isolation by distance is often observed in tree species wind or insect-pollinated when long distances within the natural range are considered (Bekessy et al. 2002), while no signiﬁcant correlation is seen when short distances are taken into account (Schierenbeck et al. 1997). The distribution of the diversity is very diﬀerent using chloroplast microsatellites. We note a strong diﬀerentiation between regions (80%) and a low percentage of variance within populations (16%). This is a classical result for angiosperm forest trees (Raspe´ et al. 2000) because of the maternal inheritance of the chloroplast DNA, and seeds are dispersed over shorter distances compared with pollen (Echt et al. 1998). In Dalbergia monticola, seed dispersal is mainly barochorous and contributes to this strong structure. The relationship between genetic distance and geographic distance for cpSSr (Figure 2b) conﬁrms this strong structure and shows that above 300 km Fst is close to 1. The diﬀerent patterns of genetic structure of RAPD and cpSSr can also be viewed through the relative rate of pollen ﬂow to seed ﬂow. With FstCp = 0.84 and FstRAPD = 0.23, the calculation of r showed that gene ﬂow by pollen is 15 times greater than by seeds. The diﬀerence is marked but is smaller than for temperate species such as Fagus silvatica (r = 84), Quercus robur (r = 286), Quercus petraea (r = 500) (King and Ferris 1998). This can be explained by the fact that they are wind-pollinated whereas D. monticola is insect-pollinated.

Marker distribution and historical factors One of the most consistent factors that strongly inﬂuenced the partition of genetic diversity of tree species over the natural range is the last glaciation period and the subsequent migrations from the refuges (Aide and Riviera 1998; Willis and Whittaker 2000). In Europe (Verdramin et al. 1998), South America (Dutech et al. 2000; Bekessy et al. 2002) and the Sudano-Sahelian region of Africa (Bouvet et al. 2004), the genetic variability of tree species has been analysed in connection with the last glaciation period, 15–20,000 years ago, but no studies, to our knowledge, have attempted to establish this relation in Madagascar. As many tropical regions, the island underwent climate ﬂuctuation during the Pleistocene and Holocene periods, but also the impact of human activities. [62]

1123 Three critical periods in the Quaternary should be mentioned. The ﬁrst was the Last Glaciation Maximum around 20,000–21,000 years ago which led to an extremely cold and arid climate. According to (Adams and Faure 1997), during this episode the rainforest in Madagascar was limited to the north-eastern part of the country (between latitudes 12 and 16), the high plateaus were covered with ericoid, graminoid and composite-dominated vegetation and the oriental escarpment and coastal plain presented tropical woodland characterised by low, open canopy and usually deciduous trees. Other authors have concluded that tropical montane vegetation belts must have been vertically displaced 900– 1500 m (Burney 1996). Such a cold-driven displacement of vegetation zones would have conﬁned the island’s humid forest zones to the relatively small land area along the east coast, with isolated patches elsewhere (low elevation humid refugia). From the early Holocene (8000 14C years ago) the rainforest occupied a broader zone than today. Early Holocene warming led to a gradual replacement of ericoid vegetation in the mid-elevation with forest in wetter locations of the eastern escarpment and a rise in the level of Lake Alaotra (Burney 1996). Some analyses, based on pollen records in high plateau locations (Lake Itasy, Ankatra, Andasibe) suggested that the rain forest was present up to elevations of 1800–2000 m (Straka 1996). The third period corresponds to human settlements 2000 years ago and the eﬀect of burning which increased the frequency of ﬁre and resulted in disturbance of the too wet or too dry ecosystems which generally support a natural ﬁre regime (Burney 1996). Assuming a limitation of the rainforest in the northern part of the range during LGM, we can hypothesise that this region may be the zone of putative refuges for sub-montane rainforest tree species. The assumption cannot be veriﬁed by the results of this study because no sample was collected in the northern part of the range in the latitude 15. However, our study proposes another putative refuge. Generally, the highest diversity regions are considered as putative refuges. The higher diversity in the centre-north region and the decrease in diversity in the southern and northern limits of the natural range (Table 6) suggest that the zone of Didy, Ambohijanahary and Antsevabe could be a putative refuge for this species. Phylogenetic trees based on haplotypes (Figures 4b) and their distribution across the natural range (Figure 4a) also point to a pattern of migration from the centre-north region.

Table 6. Diversity parameters assessed with chloroplast microsatellite markers for the four main regions of the natural range of Dalbergia monticola. Population size (N), number of haplotypes (na), eﬀective number of haplotypes (ne), Shannon’s index (ICp), haplotypic diversity (HCp). Region

N

na

ne

HeCp

ICp

North Centre-north Centre South

13 36 14 37

2 7 5 3

1.17 3.16 2.22 1.48

0.14 0.68 0.55 0.32

0.27 1.44 1.13 0.61

[63]

1124 Haplotype C5 occupies a central position in the phylogenetic trees with the highest number of connections (Figure 4b) and is present in the centre-north region. It is likely to be the ancestor of most of the other chlorotypes which mutate during the northward and southward expansion. A putative refuge in the centre-north region, close to Lake Alaotra, is also supported by the study of Reyes (1993) cited by (Burney 1996) who inferred the Late Quaternary climatic changes in north-eastern and central Madagascar using diatom spectra. In this study, Reyes (1993) indicated that early Holocene warming led to the gradual replacement of ericoid vegetation in the mid-elevation with forest developing in wetter locations along the eastern escarpments and a rise in the level of Lake Alaotra. Human settlement probably started 2000 years ago and the impact on the forest ecosystem of human practices has increased over the last two millennia. The probable eﬀect of burning by humans has been to reduce the natural range of Dalbergia monticola. Without an uncontrolled use of burning, the natural range of Dalbergia monticola would be wider than today. Our study does not allow us to measure this eﬀect. More recently, 50 years ago, the impact of human activity led to a marked increase in fragmentation in the oriental rainforest. Fragmentation is a factor which can seriously disturb the evolutionary process and which has to be taken into consideration in conservation. New investigations are needed to measure its impact on the genetic diversity of Dalbergia monticola.

Consequences for conservation of the species Forest genetic resources in Madagascar constitute an essential component of the biological diversity of forest ecosystems. They supply a wide range of goods and services essential to the life of rural communities and eﬀorts to promote sustainable management are required. Strategies involving genetic studies are still rare and exploration of the genetic diversity of Malagasy trees is expected. Newton et al. (1999) emphasise that intraspeciﬁc diversity has become a parameter fundamental to the management of species with the aim of maintaining their evolutionary potential. In this study we used neutral markers to assess diversity. The use of such markers to predict the diversity of adaptive genes or economic traits within populations has to be considered with caution (Lynch et al. 1999). RAPD or cpSSrs are diﬀerent from genes and may not be a good predictor of gene function diversity or of complex traits. However, molecular markers can give indications of the genetic distance between populations and of their diﬀerent evolutionary histories (Holsinger 1996), and may indicate a similar genetic structure for morphological traits (Nesbitt et al. 1995). Diﬀerent genes could have been selected, appeared by mutation or have been eliminated by genetic drift in separated populations which do not exchange genes. Some authors use intraspeciﬁc diversity to elaborate conservation strategies (Rajagodal et al. [64]

1125 2000). The concept of evolutionary signiﬁcant units (ESUs) has received increasing support as providing a rational basis for identifying suitable units for conservation (Moritz 1994; Newton et al. 1999) and has been implemented in forest genetic resources when nuclear and organelle haplotypes are available (Cavers et al. 2003). This approach can be proposed given the methodology and the results of the current study. Chloroplast markers can provide a basis for deﬁning ESUs using the main lineages, their distribution in the natural range and the result showing the diﬀerentiation between populations (AMOVA and Mantel test). The set of regions north and centre-north, the centre region and the south region can be identiﬁed as ESUs. Signiﬁcant divergence between these three groups with RAPD markers conﬁrms the identiﬁcation of the three ESUs. Although pollen gene ﬂow is important, isolation by distance was observed by means of the Mantel test, and a signiﬁcant genetic diﬀerentiation among populations and regions was shown by AMOVA. RAPD markers indicate that most of the variability is present within populations, stressing the importance of gene ﬂow among individuals. This result could help to deﬁne a strategy to elaborate ex and in situ conservation stands. To start such a programme, the population should consist of many individual trees selected within a few natural populations within the ESUs to capture a large proportion of variation. Much work is needed to elaborate an optimal strategy. As stressed by Cavers et al. (2003), the best strategy will concord with use of neutral markers and adaptive information (also ecological information), but a ﬁrst step in the identiﬁcation of ESUs with molecular markers provides a ﬁrst practical framework.

Acknowledgements We are very grateful to colleagues from ‘‘Silo National des Graines Forestie`res’’ for assistance in collecting samples, to Alexandre Vaillant and Ce´line Cardi from Cirad-foreˆt for their technical assistance in the laboratory, and to the anonymous reviewers. These results are part of master of science thesis of O. Andrianoelina, which was ﬁnancially supported by the Millennium Seed Bank (MSB) project, managed by the Seed Conservation Department, RBG Kew. The study was carried out at SNGF, which receives funds from the Malagasy Government, as well as at Cirad-Foreˆt, where laboratory work was done. L. Ramamonjisoa, head of the technique division in SNGF and J.M. Bouvet, head of the Research unit on forest genetic resources, were responsible for supervision.

References Adams J.M. and Faure H. 1997. Preliminary vegetation maps of the world since the last glacial maximum: an aid to archeological understanding. J. Archeol. Sci. 24: 623–647. [65]

1126 Aide T.M. and Rivera E. 1998. Geographic patterns of genetic diversity in Poulsenia amata (Moraceae): implications for the theory of Pleistocene refugia and the importance of ripian forest. J. Biogeogr. 25: 695–705. Barrett S.C.H. 1998. The reproductive biology and genetics of island plants. In: P.R. Grant (ed), Evolution on islands. Oxford University Press, Oxford, UK, pp. 19–34. Bekessy S.A., Allnutt T.R., Premoli A.C., Lara A., Ennos R.A., Burgman M.A., Cortes M. and Newton A.C. 2002. Genetic variation in the vulnerable and endemic Monkey Puzzle tree, detected using RAPDs. Heredity 88: 243–249. Bousquet J., Simon L. and Lalonde M. 1990. DNA ampliﬁcation from vegetative and sexual tissues of trees using polymerase chain reaction. Can. J. Forest. Res. 20: 254–257. Bouvet J.-M., Fontaine C., Sanou H. and Cardi C. 2004. An analysis of the pattern of genetic variation in Vitellaria paradoxa using RAPD markers. Agroforest. Syst. 60: 61–69. Briggs J.C. 2003. The biogeographic and tectonic history of India. J. Biogeogr. 30: 381–388. Bryan G.J., McNicoll J., Ramsay G., Meyer R.C. and De Jong W.S. 1999. Polymorphic simple sequence repeat markers in chloroplast genomes of solanaceous plants. Theoret. Appl. Genet. 99: 859–867. Burney D.A. 1996. Climate change and ﬁre ecology as factors in the quaternary biogeography of Madagascar. In: Lourenc¸o W.R. (ed.), Edition de l’ORSTOM Bioge´ographie de Madagascar. Orstrom, Paris, France, pp. 49–58. Cavers S., Navarro C. and Lowe A.J. 2003. A combination of molecular markers identiﬁes evolutionarily signiﬁcant units in Cedrela odorata L. (Meliaceae) in Costa Rica. Conserv. Genet. 4: 571–580. Collevatti R.G., Grattapaglia D. and Hay J.D. 2003. Evidence for multiple lineages of Caryocar brasiliense populations in the Brazilian Cerrado based on the analysis of chloroplast DNA sequence and microsatellite haplotype variation. Mol. Ecol. 12: 105–115. Dutech C., Maggia L. and Joly H.I. 2000. Chloroplast diversity in Vouacapoua americana (Caesalpiniaceae), a neotropical forest tree. Mol. Ecol. 9: 1427–1432. Echt C.S., DeVerno L.L., Anzidei M. and Vendramin G.G. 1998. Chloroplast microsatellites reveal population genetic diversity in red pine, Pinus resinosa Ait. Mol. Ecol. 7: 307–316. Ennos R.A. 1994. Estimating the relative rates of pollen and seed migration among plant populations. Heredity 72: 250–259. Esselman E.J., Crawford D.J., Brauner S., Stuessy T.F., Anderson G.J. and Silva O.M. 2000. RAPD marker diversity within and divergence among species of Dendroseris (Asteraceae: Lactuceae). Am. J. Bot. 87(4): 591–596. Excoﬃer L., Smouse P.E. and Quattro J.M. 1992. Analysis of molecular variance inferred from metric distance among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131: 479–491. Gasse F. and Van Campo E. 2001. Late quaternary environmental changes from a pollen and diatom record in the southern tropics (lake Tritivakely, Madagascar). Paleogeogr. Paleoclimatol. Paleoecol. 167: 287–308. Gillies A.C.M., Cornelius J.P., Newton A.C., Navarro C., Hernandez M. and Wilson J. 1997. Genetic variation in Costa Rican populations of the tropical timber species Cedrela odorata L., using RAPDs. Mol. Ecol. 6: 1133–1145. Grivet D. and Petit R. 2003. Chloroplast DNA phylogeography of the hornbeam in Europe: evidence for the bottleneck at the outset of the postglacial colonisation. Conserv. Genet. 4: 47–56. Goudet J. 2001. FSTAT, a program to estimate and test gene diversities and ﬁxation indices (version 2.9.3). Available from http://www.nil.ch/izea/softwares/fstat.html. Holsinger K.E. 1996. The scope and the limits of conservation genetics. Evolution 50: 2558–2561. King R.A. and Ferris C. 1998. Chloroplast DNA phylogeography of Alnus glutinosa (L.) Gaertn. Mol. Ecol. 7: 1151–1161. Kwon J.A. and Morden C.W. 2002. Population genetic structure of two rare tree species (Colubrina oppositifolia and Alphitonia ponderosa, Rhamnaceae) from Hawaiian dry and mesic forest using random ampliﬁed polymorphic DNA markers. Mol. Ecol. 11: 991–1001.

[66]

1127 Lynch M., Pfrender M., Spitze K., Lehman N., Hicks J., Allen D., Latta L., Ottene M., Bogue F. and Colbourne J. 1999. The quantitative and molecular genetic architecture of a subdivided species. Evolution 53: 100–110. Marshall H.D., Newton C. and Ritland K. 2002. Chloroplast phylogeography and evolution of highly polymorphic microsatellites in lodgepole pine (Pinus contorta). Theoret. Appl. Genet. 104: 367–378. Martin J.P. and Hernandez Bermejo J.E. 2000. Genetic variation in the endemic and endangered Rosmarinus tomentosus Huber-Morath & Maire (Labiatae) using RAPD markers. Heredity 85: 434–443. Moritz C. 1994. Deﬁning signiﬁcant units for conservation. Trends Ecol. Evol. 9: 373–375. Myers N., Mittermeier R.A., Mittermeier C.G., da Fonseca G.A.B. and Kent J. 2000. Biodiversity hotspots for conservation priorities. Nature 403: 853–858. Nybom H. and Bartish I.V. 2000. Eﬀects of life history traits and sampling strategies on genetic diversity estimates obtained with RAPD markers in plants. Perspect. Plant Ecol. Evol. Syst. 3: 93–114. Nesbitt K.A., Potts B.M., Vaillancourt R.E., West A.K. and Reid J.B. 1995. Partitioning and distribution of RAPD variation in a forest tree species, Eucalyptus globulus (Myrtaceae). Heredity 74: 628–637. Newton A.C., Allnutt T.R., Dvorak W.S., Del Castillo R.F. and Ennos R.A. 2002. Patterns of genetic variation in Pinus chiapensis, a threatened Mexican pine, detected by RAPD and mitochondrial DNA RFLP markers. Heredity 89: 191–198. Newton A.C., Allnutt T.R., Gillies A.C.M., Lowe A.J. and Ennos R.A. 1999. Molecular phylogeography, intraspeciﬁc variation and the conservation of tree species. TREE 14(4): 140–145. Palme A.E. and Verdramin G.G. 2002. Chloroplast DNA variation, postglacial recolonization and hybridation in hazel, Corylus avellana. Mol. Ecol. 11: 1769–1779. Perrier X., Flori A. and Bonnot F. 2003. Data analysis methods. In: Hamon P., Seguin M., Perrier X. and Glaszmann J.C. (eds), Genetic diversity of cultivated tropical plants Enﬁeld. Science Publishers, Montpellier,pp. 43–76. Rajagopal J., Bashyam L., Bhatia S., Khurana D.K., Srivastava P.S. and Lakshmikumaran M. 2000. Evaluation of genetic diversity in the Himalayan poplar using RAPD markers. Silvae Genet. 49(2): 49–66. Raspe´ O., Saumitou-Laprade P., Cuguen J. and Jacquemart A.-L. 2000. Chloroplast DNA haplotype variation and population diﬀerentiation in Sorbus aucuparia L. (Rosaceae: Maloideae). Mol. Ecol. 9: 1113–1122. Savolainen O. and Kuittinen H. 2000. Small population processes. In: Youg A., Boshier D. and Boyle T. (eds), Forest Conservation Genetics. Principles and Practises, CSIRO Publishing Collingwood Victoria, Australia. pp. 94–100. Schierenbeck K.A., Skupski M., Lieberman D. and Lieberman M. 1997. Population structure and genetic diversity in four tropical tree species in Costa Rica. Mol. Ecol. 6: 137–144. Schneider S., Roessli D. and Excoﬃer L. 2000. Arlequin version 2000: a software for population genetics data analysis. Genetics and Biometrics Laboratory, Department of Anthropology, University of Geneva, Geneva, Switzerland. Straka H. 1996. Histoire de la ve´ge´tation de Madagascar oriental dans les derniers 100 mille´naires. In: Lourenc¸o W.R. (ed.), Editions de l’ORSTOM, Bioge´ographie de Madagascar. Orstrom, Paris, France, pp. 37–47. Vendramin G.G., Anzidei M., Madaghiele A., Sperisen C. and Bucci G. 1998. Distribution of genetic diversity in Pinus pinaster Ait. as revealed by chloroplast microsatellites. Theoret. Appl. Genet. 97: 456–463. Viard F., El-Kassaby Y.A. and Ritland K. 2001. Diversity and genetic structure in populations of Pseudotsuga menziesii (Pinaceae) at chloroplast microsatellite loci. Genome 44: 336–344.

[67]

1128 Weising K. and Gardner R.C. 1999. A set of conserved PVR primers for the analysis of simple sequence repeat polymorphism in chloroplast genomes of dicotyledonous angiosperms. Genome 42: 9–19. Willis K.J. and Whittaker R.J. 2000. The refugial debate. Science 287: 1406–1407. Wu J., Krutovskii K.V. and Strauss S.H. 1999. Nuclear DNA diversity, population diﬀerentiation and phylogenetic relatioships in the California closed-cone pines based on RAPD and allozyme markers. Genome 42: 893–908. Yeh F.C. and Boyle T.J.B. 1997. Population genetic analysis of co-dominant and dominant markers and quantitative traits. Belg. J. Bot. 129: 157.

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Biodiversity and Conservation (2006) 15:1129–1142 DOI 10.1007/s10531-004-3103-8

Springer 2006

-1

Forest management and plant species diversity in chestnut stands of three Mediterranean areas HE´LE`NE GONDARD1,*, FRANC¸OIS ROMANE1, IGNACIO SANTA REGINA2 and SALVATORE LEONARDI3 1

CEFE (UMR 5175), 1919 route de Mende, 34293 Montpellier cedex 5, France; 2Instituto de Recursos Naturales y Agrobiologia de Salamanca, P. box 257 C/Cordel de Merinas 40, E-37071 Salamanca, Spain; 3Dipartimento di Metodologie Fisiche e Chimiche per l’Ingegneria, Facolta` di Ingegneria, Universita` di Catania, viale A. Doria 6, 95125 Catania, Italy; *Author for correspondence (e-mail:[email protected]; phone: +33-4-67613276; fax: +33-4-67412138) Received 6 February 2004; accepted in revised form 31 August 2004

Key words: Castanea sativa, Coppice stand, Diversity index, Functional trait, Grove Abstract. Over many centuries, chestnut fruits had an important role as food, while chestnut wood was used for local purposes. Today sweet chestnut stands are very common around the western Mediterranean Basin, and it is necessary to analyze the dynamic of plant species diversity in diﬀerent chestnut stand types (groves and coppices) to guide management strategies that will allow the conservation of biodiversity. Our objective was to analyze consequences on plant species diversity of various management strategies in chestnut stands of three Mediterranean areas, Salamanca (Spain), the Ce´vennes (France), and Etna volcano (Italy). We found that plant species diversity is diﬀerent according to management types; it is higher in groves than in coppice stands. We also demonstrated that Castanea sativa cultivated groves were characterized by small heliophillous therophytes. C. sativa abandoned groves, mixed C. sativa–Quercus pyrenaica coppice stands, Q. pyrenaica coppice stands, and young C. sativa coppice stands were characterized by hemicryptophytes with anemochorous dispersal mode and chamaephytes. Medium and old C. sativa coppice stands (that diﬀer by the shoot age) were characterized by phanerophytes with zoochorous dispersal mode. Human perturbations maintain a quite high level of species diversity. In contrast, the abandonment of chestnut stands leads to homogeneous vegetation with decreasing diversity. One solution could be to maintain a landscape mosaic constituted of diverse chestnut stands modiﬁed by human activities (groves, cultivated or abandoned, and coppice stands). This could enhance regional plant diversity.

Nomenclature – Flora Europaea (Tutin et al. 1964–1980)

Introduction Sweet chestnut (Castanea sativa Mill) stands are very common around the western Mediterranean Basin. Over many centuries, chestnut fruits had an important role as food for humans and as feed for domestic animals, while chestnut wood was used for local purposes such as wine barrels, vineyard pegs, tool handles and carpentry (Arnaud and Bouchet 1995). Today, chestnut [69]

1130 stands cover large areas particularly in Portugal, Spain, France, Italy and Greece. Thus, it is necessary to analyze the dynamic of plant species diversity in diﬀerent chestnut stand types (groves and coppices) to guide management strategies that will allow the conservation of biodiversity and at the same time to optimize productivity and proﬁtability. The characterization of community response to diﬀerent management types in terms of functional traits appears as a promising tool to achieve this goal (McIntyre et al. 1995; Hadar et al. 1999; Lavorel et al. 1999; Gondard et al. 2003). Indeed, from an ecosystem perspective, species richness (number of species), which is the conventional metric of biodiversity, is not as important as functional trait richness. This approach analyzes the functioning of the ecosystem, and its response to abandonment, by focusing on vegetation description deﬁned by functional traits not necessarily linked with taxonomic attribution (Pillar 1999). Functional traits fall into three biological categories: morphological traits describing aspect, life history traits indicating plant behavior in the environment, and regeneration traits (Lavorel et al. 1997). The use of functional traits for the comprehension and analysis of plant species dynamics in relation with perturbation is clearly demonstrated by many authors (Dı´ az and Cabido 1997; Lavorel and Cramer 1999; McIntyre et al. 1999; McIntyre and Lavorel 2001; Dı´ az et al. 2002; Gondard and Deconchat 2003). Consequently, our objective was to analyze consequences on plant species diversity of various management strategies in chestnut stands of three Mediterranean areas, Salamanca (Spain), the Ce´vennes (France), and Etna volcano (Italy). We hypothesized that, whatever area, species diversity between groves and coppice stands is diﬀerent essentially according to dendrometric characteristics and management types. Indeed, groves have, in general, large trees with regular pruning, understorey cleaning, etc., and coppices have many shoots without clearing but logging. We assumed that species diversity is highest in groves. We focused on understorey stratum which is sensitive to changes of ecosystem conditions (Pregitzer and Barnes 1982; Strong et al. 1991; Mitchell et al. 1997, 1998) and recognized like a very important component in ecosystem functioning (Host and Pregitzer 1991; Arsenault and Bradﬁeld 1995; Brakenhielm and Lui 1998).

Materials and methods The experiment was carried out in three Mediterranean areas, in the Honfrı´ a forest, located in the southern of Salamanca province in Spain, in the Ce´vennes in southern France, and on Etna volcano in Italy (Table 1). The Honfrı´ a forest is representative of traditional chestnut (Castanea sativa) management over many centuries in Spain, but also a model of possible sustainable management in the future. In this forest, chestnut is considered as a paraclimax species and the deciduous oak (Quercus pyrenaica) as a climax species. Thus, we selected ﬁve stands that are representative of this forest: a chestnut cultivated grove, a [70]

1131 chestnut abandoned grove, a chestnut coppice stand, a mixed chestnut-oak stand, and an oak pure stand. In the Ce´vennes, we identiﬁed a succession following agricultural abandonment from chestnut cultivated grove to chestnut old coppice stand. Thus, we selected ﬁve stages that form the successional gradient: a cultivated grove, an abandoned grove, a young coppice (<25 years old), a medium coppice stand (between 26 and 50 years old), and an old coppice stand (>51 years old). On Etna volcano, the tradition is coppice management and not grove. Thus, we selected ﬁve coppice stands (Fornazzo, Trisciala, Balilla, Monte Crisimo, Piano Lepre) that are representative of the study area and diﬀer by their stand characteristics (Table 2). In each stand, we established ﬁve 10 · 10 m plots. The plots were contiguous because there was only little area available at the site with relatively homogeneous topographic conditions, and in order to respect 100 m2 plot size minimum. In each plot, we recorded all plant species occurring in the understorey stratum. The plant cover of each species was estimated by the point quadrat method (Gounot 1969), using 100 points, i.e. one point each 10 cm, along a 10 m line traversing each plot. According to previous observations, realized by one of us, 100 m2 plots appeared to be suitable for monitoring this kind of vegetation. Data were collected during June month in 2001 in the Ce´vennes, 2002 in the Honfrı´ a forest, and 2003 in Italy. Moreover, plant species recorded were characterized by functional traits such as plant height and life form that refer to morphology, light tolerance that refers to life history traits, and dispersal mode to regeneration traits (Appendix 1).

Data analyses The criteria to compare stands were species richness (number of taxa per 100 m2) and species diversity (Pielou 1975; Magurran 1988). Among the many diversity indices available, we chose P the Shannon index (H’), which was recommended by Pielou (1975): H0 ¼ i¼1;n ðpi log2 ðpi ÞÞ where pi is the abundance ratio of species (i) in the square, and n is the species number in the square. Forest stands in the three geographical areas are submitted to diﬀerent silvicultural management and also to contrasting environment and climate conTable 1. Characteristics of the three Mediterranean areas studied.

Altitude (m) Mean annual rainfall (mm yr1) Mean annual temperature (C) Parent material Soil

Honfrı´ a Forest

Ce´vennes

Etna volcano

Spain

France

Italy

900 1500 11 Schist Cambisol

650 1400 11 Schist Cambisol

1000 1100 12 volcanic ash, lava regosol volcanic

[71]

1132 Table 2. Main characteristics of chestnut stands selected in the Ce´vennes in France, on Etna volcano in Italy and in Honfrı´ a Forest in Spain. Conﬁdence intervals p = 0.05. For each site, mean values in the same column followed by diﬀerent letters are signiﬁcantly diﬀerent. p < 0.05, Mann– Whitney test. Tree age Tree (years) height (m)

Diameter at breast height (cm)

Shoot density Basal area (shoot ha1) (m 2ha1)

Site

Stand

Honfrı´ a Forest Spain

C. sativa 90 cultivated grove

11.30 ± 1.3b 18.30 ± 2.1c

295 ± 20a

23 ± 5b

C. sativa 85 abandoned grove C. sativa 70 coppice stand Mixed C. sativa–Q. 60 pyrenaica stand Q. pyrenaica 75 pure stand Ce´vennes Cultivated grove 70 France Abandoned grove 75 Young coppice 16 Medium coppice 39 Old coppice 56 Etna volca Fornazzo coppice 31 Italy Trisciala coppice 28 Balilla coppice 37 Monte Crisimo 26 coppice Piano 27 Lepre coppice

8.90 ± 0.8a 20.40 ± 3.0c

382 ± 30a

19 ± 4a

15.3 ± 1.3c 12.90 ± 1.7b 1892 ± 100b

28 ± 8c

10.7 ± 0.8b

8.90 ± 1.2a 3208 ± 150c

21 ± 5a

12.2 ± 1.0b 11.60 ± 1.5b 2960 ± 125c

27 ± 7c

18.00 ± 1.0a 45.00 ± 7.1a 17.40 11.20 12.40 16.40 17.67

± ± ± ± ±

0.5a 0.8b,c 0.9c 0.5d 0.7a

44.60 ± 11.5a 9.40 ± 1.5b 17.80 ± 7.8c,d 24.00 ± 4.8d 9.20 ± 0.5a

120 ± 45a 440 ± 195a 1040 ± 611b 1080 ± 396b 840 ± 488b 4680 ± 1242a,c

26 ± 18a 45 ± 21a 8 ± 4b 17 ± 14c,d 35 ± 13d 38 ± 8a,b

12.17 ± 0.3a 16.67 ± 2.3a 16.00 ± 0.0a

7.20 ± 0.3b 6020 ± 895a 20.9 ± 1.7c 1140 ± 331b 7.10 ± 1.2d 2900 ± 919c

29 ± 3a 43 ± 8b 24 ± 6c

15.67 ± 3.2a

9.90 ± 0.5a 4180 ± 394d,c 38 ± 1a,b

ditions, so diﬀerences are expected between them. However, due to the low number of stands analyzed, we used non-parametric test that allows to work with low size samples. We chose the Mann–Whitney non-parametric test that allows to compare means pairwise (Falissard 1998). In each Mediterranean area, we used Correspondence Analysis (CA) and Canonical Correspondence Analysis (CCA, ter Braak 1987) to quantify the eﬀects of management types with species functional traits. We performed a Correspondence Analysis (CA,Greenacre 1984) of plant species observed on the entire point quadrat set (67 in Honfrı´ a forest in Spain, 41 in the Ce´vennes in France, and 40 on Etna volcano in Italy) and management types (coppice stands and groves in Honfrı´ a forest and in the Ce´vennes, and diﬀerent coppice stand types on the Etna volcano). We used CCA to determine the fraction of variance of the species among management types explained by the species and functional traits. For each Mediterranean area, we carried out the CCA by confronting the CA table with another table composed by the same species [72]

Species richness

1133 60 55 50 45 40 35

a

30 25 20 15 10 5 0

bc

C. sativa cultivated grove

b

b

C. sativa abandoned grove

C. sativa coppice stand

c

Mixed C. sativaQ. pyrenaica stand

Q. pyrenaica stand

Figure 1. Mean species richness in the understorey of the C. sativa and Q. pyranaica stands of the Honfrı´ a forest in the southern of Salamanca province in Spain. Error bars at ±95% conﬁdence limits. Two diﬀerent letters between the coppice stands indicated signiﬁcant statistical diﬀerence (Mann–Whitney non-parametric test, p < 0.05).

number and functional traits separated in subclasses. Moreover, hierarchical ascending classiﬁcation was used to make easier the identiﬁcation of groups in factorial plans (Roux 1985).

Results Species richness and species diversity (Shannon index) In the Honfrı´ a forest and the Ce´vennes, species richness was highest in cultivated groves, (Figures 1, 2). On Etna volcano, species richness was highest in

Species richness

45

a

40 35 30

b

25 20

c

cd d

15 10 5 0

Cultivated Abandoned Grove Grove

Young Coppice

Medium Coppice

Old Coppice

Figure 2. Mean species richness along a successional gradient from cultivated chestnut grove to old C. sativa coppice stand (Le Cros site in the Ce´vennes). Error bars at ±95% conﬁdence limits. Two diﬀerent letters between the coppice stands indicated signiﬁcant statistical diﬀerence (Mann– Whitney non-parametric test, p < 0.05). [73]

Species richness

1134 45 40 35 30 25 20 15 10 5 0

a b

bc cd

Monte Crisimo

Trisciala

Fornazzo

d

Balilla

Piano Lepre

Figure 3. Mean species richness in the understorey in the ﬁve coppice C. sativa stands on the Etna volcano in Italy. Error bars at ±95% conﬁdence limits. Two diﬀerent letters between the coppice stands indicated signiﬁcant statistical diﬀerence (Mann–Whitney non-parametric test, p < 0.05).

the Trisciala coppice stand (Figure 3), and not signiﬁcantly diﬀerent from the abandoned grove in the Ce´vennes (p > 0.05). Species diversity was also highest in cultivated groves and Trisciala coppice stand.

Plant functional traits and management types Consequences of various management types on plant species in term of functional traits were analyzed with CCA, and hierarchical ascending classiﬁcation allowed the identiﬁcation of several groups in each Mediterranean area 1 Axis 2 (inertia 15%) 0,8

Honfría forest - Group 2 C.sativa coppice stands Arpa, Casa, Celo, Prav, Qupy, Tesc

Geophyte 0,6

0,4

> 50 cm Axis 1 (inertia 48%) -1

Honfría forest - Group 3 C. sativa abandoned groves & Mixed C. sativa-Q. pyrenaica coppice stands & Q. pyrenaica coppice stands Anod, Caof, Capa, Daca, Gehi, Gepi, Haha, Jamo, Loco, Meme, Feru, Himu Barochorous

0,2

Heliophillous

Hydrochorous Anemochorous

Zoochorous

Therophyte

0

-0,8

-0,6 -0,4 Phanerophyte

Shade tolerant

-0,2

0 Chamaephyte -0,2

0,2 30-50 cm

0,4

0,6

0,8

1

1,2

1-30 cm

Autochorous

Honfría forest - Group 1 C. sativa cultivated groves Anpr, Boma, Brho, Cegl, Cran, Crvi, Cyec, Gaap, Tran, Trar, Trca, Scan, Vubr

-0,4 Hemicryptophyte -0,6

Figure 4. Ordination in the plane of the two axes of functional traits after a canonical correspondence analysis from a matrix composed by the 67 plant species observed on the line point quadrat of the 25 plots in the Honfrı´ a forest in Spain and a matrix composed by the same plant species and their functional traits. Groups were identiﬁed by an hierarchical ascending classiﬁcation. Plots, and some plant species associated to each group were indicated on the ﬁgure. Codes of plant species are indicated in Appendix 1. The total variation explained by CCA is 39%. [74]

1135 The Cévennes - Group 2 C. sativa abandoned groves & young coppice stands Armo, Clvu, Dagl, Erci, Hima, Himu, Pone, Prvu, Trpr, Veof, Visa

0,8 Axis 2 (inertia 28%) Autochorous

Barochorous 0,4

Phanerophyte > 50 cm

0,2

Chamaephyte

Zoochorous Shade tolerant

0 -0,8

-0,6 30-50 cm

-0,4

-0,2

0

Heliophillous 1-30 cm

Hemicryptophyte

The Cévennes - Group 3 C. sativa medium and & old coppice stands Bepe, Csa, Hede, Qupu, Rops

0,6

Therophyte

0,2 Hydrochorous

0,4 Geophyte

0,6

0,8 Axis 2 (inertia 37%)

1

-0,2

The Cévennes - Group 1 C. sativa cultivated groves Ruac, Orpe, Ptaq, Tesc

-0,4 Anemochorous -0,6

Figure 5. Ordination in the plane of the two axes of functional traits after a canonical correspondence analysis from a matrix composed by the 41 plant species observed on the line point quadrat of the 25 plots in the Ce´vennes in France and a matrix composed by the same plant species and their life traits. Groups were identiﬁed by an hierarchical ascending classiﬁcation. Plots, and some plant species associated to each group were indicated on the ﬁgure. Codes of plant species are indicated in Appendix 1. The total variation explained by CCA is 46%.

studied. In the Honfrı´ a forest, the C. sativa cultivated groves (group 1) were characterized by small heliophillous therophytes (Figure 4). The C. sativa coppice stands (group 2) were characterized by shade tolerant phanerophytes with zoochorous dispersal mode and geophytes. The C. sativa abandoned groves, mixed C. sativa–Q. pyrenaica coppice stands and Q. pyrenaica coppice stands (group 3) were composed essentially by hemicryptophytes and chamaephytes with anemochorous or barochorous dispersal mode. In the Ce´vennes, the C. sativa cultivated groves (group 1) were characterized by therophytes with anemochorous dispersal mode and geophytes (Figure 5). The C. sativa abandoned groves and the young coppice stands (group 2) were characterized by heliophillous hemicryptophytes and chamaephytes. The C. sativa medium and old coppice stands (group 3) were composed more particularly by phanerophytes with zoochorous dispersal mode. In the case of C. sativa coppice stands on Etna volcano in Italy, Monte Crisimo (group 1) were more particularly characterized by therophytes and chamaephytes (Figure 6), Triciala (group 2) by hemicryptophytes with anemochorous dispersal mode, Piano Lepre (group 3) by geophytes with barochorous dispersal mode, and Balilla and Fornazzo (group 4) by shade tolerant phanerophytes with zoochorous dispersal mode.

Discussion and concluding remarks A main trend emerging from our species richness data was higher species richness in the chestnut cultivated groves than in coppice stands; both in the [75]

1136 1,5

Etna volcano - Group 2 C. sativa coppice stands Trisciala Acli, Brsy, Crle, Himu, Rane, Sivu, Trpu

Axis 2 (inertia 29%)

Etna volcano - Group 1 C. sativa coppice stands 1 Monte Crisimo Arth, Avba, Homu, Lasp, Sete, Stme, Vidi, Vite

Anemochorous

Heliophillous 30-50 cm

Chamaephyte Hemicryptophyte 1-30 cm -0,8

-0,6

Barochorous Geophyte

0,5

-0,4

Etna volcano - Group 3 C. sativa coppice stands Piano Lepre Door, Epmi, Lagr, Lave, Leco, Muco, Ptaq

Therophyte Hydrochorous 0 -0,2 Autochorous

0

0,2

0,4

0,6

0,8 Axis 1 (inertia 43%)

-0,5

Shade tolerant -1

> 50 cm Phanerophyte Zoochorous

Etna volcano - Group 4 C. sativa coppice stands Balilla & Fornazzo Casa, Hehe, Prsp, Quda, Ruid, Ruul

-1,5

Figure 6. Ordination in the plane of the two axes of life traits after a canonical correspondence analysis from a matrix composed by the 40 plant species observed on the line point quadrat of the 25 plots on Etna volcano in Italy and a matrix composed by the same plant species and their life traits. Groups were identiﬁed by an hierarchical ascending classiﬁcation. Plots, and some plant species associated to each group were indicated on the ﬁgure. Codes of plant species are indicated in Appendix 1. The total variation explained by CCA is 49%.

Honfrı´ a forest in Spain and in the Ce´vennes in France. However, species richness in the cultivated groves of the Honfrı´ a forest (53 ± 4 species) was signiﬁcantly higher than in the cultivated groves of the Ce´vennes (38 ± 4 species) (p < 0.01). The strawberry culture in some years under chestnut groves in the Honfrı´ a forest can explain this diﬀerence. Indeed, the high biodiversity among plants was always related to perturbations (pruning, grazing, ﬁre, etc.), and often observed in Mediterranean areas (Romane et al. 1992). The species diversity decrease observed along the successional gradient in the Ce´vennes appears to be a general trend in Mediterranean Basin (Tatoni and Roche 1994; Debussche et al. 1996). On Etna volcano, tradition is coppice management and not grove, and species diversity in coppice stands was lowest than in the chestnut cultivated groves of the Honfrı´ a forest and the Ce´vennes. Nevertheless, species diversity in Trisciala coppice stand was not signiﬁcantly diﬀerent from chestnut abandoned groves in the Ce´vennes (p>0.05). In Trisciala, stumps have regular and large spacing and thus light, which is recognized as a factor linked positively with species richness (Grime and Jarvis 1975; Gilliam et al. 1995; Yorks and Dabydeen 1999), is available in the understorey and favour growth. Like in the study of Rubio et al. (1999) in Extremadure (Central Spain), or Kitazawa and Ohsawa (2002) in Chiba (Central Japan), the diﬀerence according to management type was well observed. The species composition diﬀerences among management type showed us that generally small heliophillous therophytes characterized C. sativa cultivated groves. Low intensity disturbance can explain the persistence of annual species in cultivated groves (Lavorel 1999). Hemicryptophytes with anemochorous [76]

1137 dispersal mode and chamaephytes characterized C. sativa abandoned groves, mixed C. sativa–Q. pyrenaica coppice stands, Q. pyrenaica coppice stands, and young C.sativa coppice stands. Phanerophytes with zoochorous dispersal mode characterized more particularly medium and old coppice stands (coppice stands that diﬀer by the shoot age). This pattern coincides with the general trend described in Southern France; annual plants are substituted by perennial grasses and shrubs with canopy closure (Houssard et al. 1980; Escarre´ et al. 1983; Tatoni and Roche 1994). Perturbations were necessary to maintain a quite high level of species diversity. In contrast, the abandonment of chestnut stands, for decades or even centuries, will turn into closed and homogeneous vegetation with decreasing plant diversity. One solution could be to maintain a landscape mosaic consisting of diverse chestnut stands modiﬁed by human activities (chestnut groves, abandoned chestnut groves and chestnut coppice stands) (Gondard et al. 2001; Rubio and Escudero 2003). This could enhance regional plant diversity. However, in our study we recorded only common species, thus if rare species have been observed, the estimation of biodiversity would be review, and quality aspect take into account. Moreover, due to some of the unsatisfactory aspects of the experimental design (replication number), our study only indicates, but does not validate, several possible management techniques, of which remain to be tested further.

Acknowledgements We thank the European Union (MANCHEST contracts, DG XII). We also warmly thank Maria Failla, Giuseppe Siracusa, Antonino La Mantia, Mirella Clausi, Sergio Salazar Iglesias, Alvaro Peix Geldart, Jesu´s Herna´ndez, Zuheir Shater, Alain Renaux, Michel Grandjanny, Marie Maistre, Maurice Rapp, and Franc¸ois Jardon for their participation in collecting data in the chestnut stands.

Appendix 1. Functional traits (life form, dispersal mode, plant height and light tolerance) of plant species observed along the point quadrat line and used in the Canonical Correspondence Analysis according to available data: Molinier and Mu¨ller 1938; Pignatti 1982; van der Pijl 1982; Bonnier 1990; De Bolos et al. 1993. Th – therophyte, G – geophyte, H – hemicryptophyte, Ch – chamaephyte, Ph – phanerophyte. Code

Species

Life form

Dispersal mode

Height

Light tolerance

Acli Acmi Alpe Anod Anpr Armo

Achillea ligustica Achillea millefolium Alliaria petiolata Anthoxantum odoratum Anthemis pratensis Arenaria montana

H H H H Th H

Anemochorous Anemochorous Anemochorous Anemochorous Anemochorous Anemochorous

30–50 cm 30–50 cm 30–50 cm 30–50 cm 1–30 cm 1–30 cm

shade tolerant shade tolerant shade tolerant heliophillous heliophillous heliophillous

[77]

1138 Appendix 1. Continued. Code

Species

Life form

Dispersal mode

Height

Light tolerance

Arpa Arth Asal Astr Avba Avsu Bepe Brsy Brma Brho Cadi Caof Capa Casa Cavu Cegl Celo Chju Coma Clvu Coar Coav Coli Cran Crle Crvi Cyec Cysc Daca Dagl Deme Door Epla Epmi Erar Erci Feov Feru Gaap Gamo Gasa Geﬂ Gehi Gepi Gero Gnlu Haha

Aristolochia pallida Asplenium trichomanes Asphodelus albus Asplenium trichomanes Avena barbata Avena sativa Betula pendula Brachypodium sylvaticum Bromus maximus Bromus hordeaceus Carex distachia Calamintha oﬃcinalis Campanula patula Castanea sativa Calluna vulgaris Cerastium glomeratum Cephalanthera longifolia Chondrilla juncea Conopodium majus Clinopodium vulgare Convolvulus arvensis Corylus avellana Corrigiola littoralis Crucianella angustifolia Crepis leontodontoides Crepis virens Cynosurus echinatus Cytisus scoparius Daucus carota Dactylis glomerata Deschampsia media Doronicum orientale Epilobium lanceolatum Epipactis microphylla Erica arborea Erica cinerea Festuca ovina Festuca rubra Galium aparine Galium mollugo Galium saccharatum Genista ﬂorida Genista hispanica Genista pilosa Geranium robertianum Gnaphalium lutescens Halimium lasianthumsubsp .alyssoides Hedera helix Hippocrepis comosa

G Th G H Th Th Ph H Th Th H H H Ph Ch Th G H G H H Ph H Th H Th Th Ph H H H G H G Ch Ch H H Th H Th Ch Ch Ch Th H Ch

Barochorous Anemochorous Barochorous Zoochorous Anemochorous Zoochorous Anemochorous Anemochorous Anemochorous Zoochorous Barochorous Zoochorous Anemochorous Zoochorous Anemochorous Anemochorous Anemochorous Anemochorous Barochorous Hydrochorous Barochorous Zoochorous Autochorous Anemochorous Anemochorous Anemochorous Anemochorous Autochorous Anemochorous Anemochorous Zoochorous Anemochorous Anemochorous Anemochorous Barochorous Barochorous Anemochorous Anemochorous Zoochorous Barochorous Zoochorous Autochorous Autochorous Autochorous Autochorous Autochorous Zoochorous

30–50 cm 1–30 cm 30–50 cm 1–30 cm >50 cm >50 cm >50 cm 30–50 cm 30–50 cm 1–30 cm 1–30 cm 30–50 cm 30–50 cm >50 cm 30–50 cm 1–10 cm 1–30 cm >50 cm >50 cm 30–50 cm 30–50 cm >50 cm 1–30 cm 1–30 cm 30–50 cm 30–50 cm 1–30 cm >50 cm 30–50 cm >50 cm 30–50 cm 30–50 cm 30–50 cm 1–30 cm >50 cm 30–50 cm 30–50 cm 30–50 cm 1–30 cm 30–50 cm 1–30 cm 1–30 cm 1–30 cm 1–10 cm 1–30 cm 1–30 cm 30–50 cm

shade tolerant shade tolerant heliophillous shade tolerant heliophillous heliophillous shade tolerant shade tolerant heliophillous heliophillous shade tolerant heliophillous heliophillous shade tolerant shade tolerant heliophillous shade tolerant shade tolerant shade tolerant heliophillous heliophillous shade tolerant shade tolerant heliophillous heliophillous heliophillous heliophillous shade tolerant heliophillous heliophillous shade tolerant shade tolerant shade tolerant shade tolerant shade tolerant shade tolerant heliophillous shade tolerant heliophillous shade tolerant shade tolerant shade tolerant shade tolerant shade tolerant shade tolerant heliophillous shade tolerant

Ph H

Zoochorous Autochorous

>50 cm 1–30 cm

shade tolerant shade tolerant

Hehe Hico

[78]

1139 Appendix 1. Continued. Code

Species

Life form

Dispersal mode

Height

Light tolerance

Hihi Hima Himu Hipi Hium Hola Homo Homu Hyra Ilaq Jamo Laan Lagr Lasp Lave Leco Lihe Litr Loco Loet Luca Lufo Lusi Meme Meun Muco Orco Orpe Pehi Pimu Plla Pobu Pone Posy Prav Prgr Prsp Prvu Ptaq Quda Qupu Qupy Rabu Rane Rops Ruac Ruid Rupe

Hispidella hispanica Hieracium maculatum Hieracium murorum Hieracium pilosella Hieracium umbellatum Holcus lanatus Holcus mollis Hordeum murinum Hypochaeris radicata Ilex aquifolium Jasione montana Lathyrus angulatus Lathyrus grandiﬂorus Lathyrus sphaericus Lathyrus venetus Leopoldia comosa Linaria heterophylla Linaria triornitophora Lotus corniculatus Lonicera etrusca Luzula campestris Luzula forsteri Luzula sieberi Melittis melissophyllum Melica uniﬂora Muscari commutatum Ornithopus compressus Ornithopus perpusillus Petrorhagia hispanica Piptaterum multiﬂorum Plantago lanceolata Poa bulbosa Poa nemoralis Poa trivialis subsp. sylvicola Prunus avium Prunella grandiﬂora Prunus spinosa Prunella vulgaris Pteridium aquilinum Quercus dalechampii Quercus pubescens Quercus pyrenaica Ranunculus bulbosus Ranunculus neapolitanus Robinia pseudo-acacia Rumex acetosella Rubus idaeus Rubia peregrina var . longifolia

H H H H H H H Th H Ph H Th G Th G G H H H Ph H H H H H G Th Th H H H H H H Ph H Ph H G Ph Ph Ph H H Ph G Ph H

Anemochorous Anemochorous Anemochorous Anemochorous Anemochorous Anemochorous Zoochorous Anemochorous Anemochorous Anemochorous Anemochorous Barochorous Autochorous Autochorous Barochorous Anemochorous Anemochorous Autochorous Autochorous Zoochorous Zoochorous Anemochorous Zoochorous Zoochorous Anemochorous Anemochorous Zoochorous Zoochorous Autochorous Anemochorous Anemochorous Barochorous Anemochorous Anemochorous Zoochorous Barochorous Zoochorous Hydrochorous Anemochorous Zoochorous Zoochorous Zoochorous Barochorous Anemochorous Autochorous Anemochorous Zoochorous zoochorous

1–30 cm 30–50 cm 30–50 cm 1–30 cm 30–50 cm >50 cm 30–50 cm 1–30 cm 30–50 cm >50 cm 1–30 cm 30–50 cm >50 cm 1–30 cm 30–50 cm 1–30 cm 1–30 cm 30–50 cm 1–30 cm 30–50 cm 1–30 cm 1–30 cm 1–30 cm 30–50 cm 30–50 cm 1–30 cm 30–50 cm 1–30 cm 1–30 cm >50 cm 1–30 cm 1–30 cm 30–50 cm 30–50 cm >50 cm 1–30 cm >50 cm 1–30 cm >50 cm >50 cm >50 cm >50 cm 30–50 cm 1–30 cm >50 cm >50 cm >50 cm >50 cm

heliophillous shade tolerant shade tolerant shade tolerant heliophillous heliophillous heliophillous heliophillous heliophillous shade tolerant shade tolerant heliophillous heliophillous heliophillous heliophillous heliophillous heliophillous shade tolerant heliophillous shade tolerant heliophillous shade tolerant shade tolerant shade tolerant shade tolerant heliophillous heliphillous shade tolerant heliophillous heliophillous heliophillous heliophillous shade tolerant heliophillous shade tolerant shade tolerant shade tolerant shade tolerant shade tolerant shade tolerant shade tolerant shade tolerant heliophillous shade tolerant heliophillous heliophillous shade tolerant shade tolerant

[79]

1140 Appendix 1. Continued. Code

Species

Life form

Dispersal mode

Height

Light tolerance

Ruul Scan Sete Siin Sivu

Rubus ulmifolius Scleranthus annuus Sedum tenuifolium Silene inﬂata Silene vulgaris subsp. angustifolia Solidago virgaurea Stellaria media Teucrium scorodonia Thapsia garganica Torilis arvensis Trifolium angustifolium Trifolium arvense Trifolium campestre Trifolium pratense Trifolium pratense subsp. semi-purpureum Trifolium repens Veronica oﬃcinalis Vicia disperma Vicia lutea Vicia pseudocracca Vicia sativa Vicia tenuifolia Vulpia bromoides

Ph Th Ch H H

zoochorous zoochorous anemochorous anemochorous anemochorous

>50 cm 1–30 cm 1–30 cm 30–50 cm 30–50 cm

shade tolerant heliophillous heliophillous shade tolerant shade tolerant

H Th G H Th Th Th Th H H

anemochorous anemochorous barochorous anemochorous zoochorous anemochorous anemochorous anemochorous anemochorous anemochorous

30–50 cm 1–30 cm 30–50 cm >50 cm 30–50 cm 1–30 cm 1–30 cm 1–30 cm 1–30 cm 1–30 cm

shade tolerant shade tolerant shade tolerant heliophillous shade tolerant heliophillous heliophillous heliophillous heliophillous heliophillous

H H Th Th Th H Th Th

anemochorous hydrochorous anemochorous autochorous barochorous autochorous anemochorous zoochorous

1–30 cm 1–30 cm 30–50 cm 30–50 cm 30–50 cm 30–50 cm 30–50 cm 1–30 cm

shade tolerant shade tolerant heliophillous heliophillous heliophillous heliophillous heliophillous heliophillous

Sovi Stme Tesc Thga Toar Tran Trar Trca Trpr Trpu Trre Veof Vidi Vilu Vips Visa Vite Vubr

References Arnaud M.T. and Bouchet M.A. 1995. L’aire e´cologique du chaˆtaignier (Castanea sativa Mill.) en Ce´vennes. Ecologie 26(1): 33–40. Arsenault A. and Bradﬁeld G.E. 1995. Structural-compositional variation in three age-classes of temperate rainforests in southern British Columbia. Can. J. Bot. 73: 54–64. Bonnier G. 1990. La Grande Flore. France, Suisse, Belgique et pays voisins, Belin, Paris. Brakenhielm S. and Lui Q. 1998. Long-term eﬀects of clear-felling on vegetation dynamics and species diversity in boreal pine forest. Biol. Conserv. 7: 207–220. DeBolo`s O., Vigo J., Masalles R.M. and Ninot J.M. 1993. Flora Manual dels Paı¨ sos Catalans. Portic S.A. Edition, Barcelone. Debussche M., Escarre´ J., Lepart J., Houssard C. and Lavorel S. 1996. Changes in Mediterranean plant succession: old-ﬁelds revisited. J. Veg. Sci. 7: 519–526. Dı´ az S. and Cabido M. 1997. Plant functional types and ecosystem function in relation to global change. J. Veg. Sci. 8: 463–474. Dı´ az S., McIntyre S., Lavorel S. and Pausas J. 2002. Does hairiness matter in Harare? – Global comparisons of plant trait responses to disturbance. New Phytol. 154: 7–9. Escarre´ J., Houssard C., Debussche M. and Lepart J. 1983. Evolution de la ve´ge´tation et du sol apre`s abandon cultural en re´gion me´diterrane´enne: e´tude de successions dans les garrigues du Montpellierais (France). Acta Oecol., Oecol. Plant. 4: 221–239. Falissard B. 1998. Comprendre et Utiliser les Statistiques dans les Sciences de la vie. Collection Evaluation et Statistique, Masson, Paris. [80]

1141 Gilliam F.S., Turrill N.L. and Bethadams M. 1995. Herbaceous-layer and overstory species in clear-cut and mature central Appalachian hardwood forests. Ecol. Appl. 5: 947–955. Gondard H. and Deconchat M. 2003. Eﬀects of soil surface disturbances after logging on plant species diversity. Ann. Forest Sci. 60: 725–732. Gondard H., Romane F., Grandjanny M., Junqing L. and Aronson J. 2001. Plant species diversity changes in abandoned chestnut (Castanea sativa) groves in southern France. Biodivers. Conserv. 10: 189–207. Gondard H., Jauﬀret S., Aronson J. and Lavorel S. 2003. Plant functional types: a promising tool for management and restoration of degraded lands. Appl. Veg. Sci. 6: 223–224. Gounot M. 1969. Me´thodes D’e´tude Quantitative de la Ve`ge´tation. Masson, Paris. Greenacre M.J. 1984. Theory and Applications of Correspondence Analysis. Academic Press, London. Grime J.P. and Jarvis B.C. 1975. Shade avoidance and shade tolerance in ﬂowering plants. II. Eﬀects of light on the germination of species of contrasted ecology. In: Evans G.C., Bainbridge R. and Rackham O. (eds), Light as an Ecological Factor II. Blackwell Scientiﬁc Publications. Oxford, pp. 525–532. Hadar L., Noy-Meir I. and Perevolotsky A. 1999. The eﬀect of shrub clearing and grazing on the composition of a Mediterranean plant community: functional groups versus species. J. Veg. Sci. 10: 673–682. Houssard C., Escarre´ J. and Romane F. 1980. Development of species diversity in some Mediterranean plant communities. Vegetatio 43: 59–72. Host G.E. and Pregitzer K.S. 1991. Ecological species groups for upland forest ecosystems of northwestern Lower Michigan. Forest Ecol. Manag. 43: 87–102. Kitazawa T. and Ohsawa M. 2002. Patterns of species diversity in rural herbaceous communities under diﬀerent management regimes, Chiba, central Japan. Biodivers. Conserv. 104: 239–249. Lavorel S. 1999. Ecological diversity and resilience of Mediterranean vegetation to disturbance. Diversity Distribut. 5: 3–13. Lavorel S. and Cramer W. 1999. Functional response of vegetation to land use and disturbance. J. Veg. Sci. 10: 604–732. Lavorel S., McIntyre S. and Grigulis K. 1999. Plant response to disturbance in a Mediterranean grassland: How many functional groups? J. Veg. Sci. 10: 661–672. Lavorel S., McIntyre S., Landsberg J. and Forbes T.D.A. 1997. Plant functional classiﬁcation: from general groups to speciﬁc groups based on response to disturbance. Tree 12(12): 474–478. Magurran A.E. 1988. Ecological Diversity and its Measurements. Croom Helm, London. McIntyre S. and Lavorel S. 2001. Livestock grazing in sub-tropical pastures: steps in the analysis of attribute response and plant functional types. J. Ecol. 89: 209–226. McIntyre S., Lavorel S., Landsberg J. and Forbes T.D.A. 1999. Disturbance response in vegetation-towards a global perspective on functional traits. J. Veg. Sci. 10: 621–630. McIntyre S., Lavorel S. and Tremont R.M. 1995. Plant life history attributes: their relationships to disturbance response in herbaceous vegetation. J. Ecol. 83: 31–44. Mitchell R.J., Marrs R.H. and Auld M.H.D. 1998. A comparison study of the seedbanks of heathland and succession habitats in Dorset, Southern England. J. Ecol. 86: 588–596. Mitchell R.J., Marrs R.H., Le Duc M.G. and Auld M.H.D. 1997. A study of succession on lowland heaths in Dorset, Southern England: changes in vegetation and soil properties. J. Appl. Ecol. 6: 1426–1444. Molinier R. and Mu¨ller P. 1938. La Disse´mination des Espe`ces Ve´ge´tales. Lesot A. (ed.), Paris. Pielou R.H. 1975. Ecological Diversity. A Wiley-Interscience Publication, New York. Pignatti S. 1982. Flora d’Italia. Edagricole (ed.), Bologne, 3 volumes, p. 2302. Pillar V.D. 1999. On the identiﬁcation of optimal plant functional types. J. Veg. Sci. 10(5): 631–640. Pregitzer K.S. and Barnes B.V. 1982. The use of ground ﬂora to indicate edaphic factors in upland ecosystems of the McCormick experimental forest, Upper Michigan. Can. J. Forest Res. 12: 661– 672.

[81]

1142 Romane F., Bacilieri R., Bran D. and Bouchet M.A. 1992. Natural degenerate Mediterranean forests: Which future? The examples of the holm oak (Quercus ilex.) and chestnut (Castanea sativa Mill.) coppice stands. In: Teller A., Mathy P. and Jeﬀers J.N.R. (eds), Responses of Forest Ecosystems to Environmental Changes. Elsevier Applied Science, London and New York, pp. 374–380. Roux M. 1985. Algorithmes de Classiﬁcation. Masson, Paris. Rubio A. and Escudero A. 2003. Clear-cut eﬀects on chestnut forest soils under stressful conditions: lengthening of time-rotation. Forest Ecol. Manag., 183 195–204. Rubio A., Gavila´n R. and Escudero A. 1999. Are soil characteristics and understorey composition controlled by forest management? Forest Ecol. Manag. 113: 191–200. Strong W.L., Bluth D.J., LaRoi G.H. and Corns I.G.W. 1991. Forest understorey plants as predictors of lodgepole pine and white spruce site quality in west-central Alberta. Can. J. Forest Res. 21: 1675–1683. Tatoni T. and Roche P. 1994. Comparison of old-ﬁeld and forest revegetation dynamics in Provence. J. Veg. Sci. 5: 295–302. terBraak C.J.F. 1987. The analysis of vegetation-environment relationships by canonical correspondence analysis. Vegetatio 69: 69–77. Tutin T.G., Heywood V.H., Burges N.A., Moore D.M., Valentine D.H., Walters S.M. and Webb D.A. 1964–1980. Flora Europea. Cambrige University Press. van der Pijl L. 1982. Principles of Dispersal in Higher Plants. Springer, Berlin, Heidelberg and New York. Yorks T.E. and Dabydeen S. 1999. Seasonal and successional understory vascular plant diversity in second growth hardwood clearcuts of western Maryland, USA. Forest Ecol. Manag. 119: 217– 230.

[82]

Biodiversity and Conservation (2006) 15:1143–1157 DOI 10.1007/s10531-004-3105-6

Springer 2006

-1

Spatial diversity of dry savanna woodlands Assessing the spatial diversity of a dry savanna woodland stand in northern Namibia using neighbourhood-based measures FRIEDRICH PATRICK GRAZ 1 Department of Land Management Conservation, Polytechnic of Namibia, P/Bag 13388, Windhoek, Namibia; (e-mail: [email protected]; phone: +264-061-207-2215; fax: +264-061-2072123)

Received 8 March 2004; accepted in revised form 3 August 2004

Key words: Ecology, Mingling index, Namibia, Spatial diversity, Spatial structure, Uniform angle index, Woodland savanna Abstract. The dry woodland savannas of Namibia are of signiﬁcant socio-economic importance. The paper tests the suitability of a number of diversity indicators developed for species poor systems in Europe in the woodland context. The indicators that were tested included the species speciﬁc mingling index, MSp, the measure of surround and the uniform angle index. The simple application of the methods permit relatively unschooled crews to conduct an enumeration in the ﬁeld.The results show that the indicators do not only display current diversity status, but also reﬂect the ecological context of the individual species.

Introduction and background The dry woodland savannas of northern Namibia are of signiﬁcant socioeconomic importance to many rural communities, providing a variety of timber and non-timber products. The woodland resources that are used range from building material and wood fuel to food, medicine and grazing (NFSP 1996). The quantities of the diﬀerent products that are extracted are considerable. Ollikainen (1992) estimated for example, that ﬁrewood alone amounted to a total of 1.5 million cubic metres of wood during 1992. No quantity or value estimates of non-wood products are available for the Namibian dry woodland savannas, although these may be considerable. The various woodland products diﬀer in their importance to the various communities, and at diﬀerent times. Although exact quantities were not indicated, Lee (1973) reported, for instance, that the intake of Schinziophyton rautanenii nuts could comprise up to 90% of the total food intake of some San communities. While this percentage will have changed in the meantime, Bu¨schel (1999) indicated that the nuts still represent the staple diet of nomadic and sedentary San groups. The importance of the nuts increases particularly when agricultural crops are insuﬃcient to meet normal requirements. [83]

1144 Other communities in the Kavango region of Namibia depend almost entirely on the production and sale of carvings for the tourism industry, although no studies seem to have been published in this regard. Some carvings are also produced in the Caprivi region, but the local population does not appear to depend as much on this form of income although no estimates are available. The emphasis on diﬀerent species for the carving industry is also shifting. In the early 1990s the industry in the Okavango region made use of Pterocarpus angolensis almost exclusively. Now, however, species like Guibourtia coleosperma, Baikiaea plurijuga and even S. rautanenii (despite its light weight) are being utilized extensively. This is primarily due to the overexploitation of P. angolensis. Further woodland species, such as Burkea africana or Terminalia sericea serve mainly for poles or as ﬁrewood, although they support a caterpillar that also represents an important source of food (Leger 1997).

Spatial diversity and woodland structure The word ‘‘structure’’ generally considers the composition of a population of trees in terms of speciﬁc characteristics. These may include tree age, size, species or sex (in the case of dioceous trees). Spatial structure, on the other hand looks at the arrangement of such characteristics in space. Spatial diversity refers to the arrangement of the characteristics in relation to each-other or in relation to a particular point on the ground. The woodland savanna in northern Namibia is supported by coarse Aeolian sands with poor water holding capacity and nutrient status. The trees that occur here need to cope with highly variable precipitation and high evaporation rates. Frequent ﬁres and exploitation further aﬀect the environment. Taken in combination, trees and especially their seedling have to cope with a wide variety of conditions over a very short period of time and have adapted accordingly. A number of the woodland species are frequently, though not exclusively, found in almost monospeciﬁc stands. This may be due to regeneration requirements, as in the case of P. angolensis (Graz 1996), the ability to compete, especially for water, as in the case of B. plurijuga (Mitlo¨hner 1997) or superior ﬁre tolerance as in the case of B. africana (Rutherford 1981). The monospeciﬁcity of stands of S. rautanenii and T. sericea have not been investigated. T. sericiea, however, is a pioneer that may quickly colonize open areas where it may actually form thickets (Shackleton 2001). Bu¨schel (1999) reported on the other hand that stands dominated by S. rautanenii were comprised of trees of diﬀerent sizes and species in the Okavango region of Namibia. Similarly, Mitlo¨hner (1997) also described stands of mixed species, comprising of P. angolensis, B. africana and B. plurijuga, while observations near the study site also showed mixed stands (unpublished data). [84]

1145 In addition to being almost monospeciﬁc, trees within many stands often seem to be of similar size although not necessarily of similar age. Childes (1984) reported, for instance, that B. plurijuga stands were of variable age despite the equal size of the trees. Plants remain small for a number of years until environmental conditions are suitable for further development. This is probably also the case for B. africana and S. rautanenii, although nothing seems to have been documented. The restriction of growth described by Childes for B. plurijuga is similar to the suﬀrutex development stage of P. angolensis reported by Vermeulen (1990). During this period seedlings from a number of years may accumulate in this developmental stage and develop together to the sapling stage when environmental conditions permit. In such cases the above ground parts are not of the same age as the roots. It is unclear if the diﬀerences in the ages of the roots will be reﬂected in the survival rate of the above ground parts of the trees. It is also uncertain whether or not whole stands of any of the above species will die oﬀ and be replaced by others at a diﬀerent location, or whether the existing regeneration is suﬃcient to replace those trees that have died. The data pertaining to the structure of stands in northern Namibia currently available is superﬁcial, despite its signiﬁcant importance for management. Spatial diversity, or a lack of spatial diversity, has important implications. Consider for instance the eﬀect of exploitation on an even sized, monospeciﬁc stand; selection based on a minimum diameter may result in a local clear-felling (Von Breitenbach 1968; Graz 1996). The resulting vegetation structure would be increasingly prone to ﬁre that may cause further vegetation change, as well as subsequent erosion and nutrient loss (see Graz 1996). Causes of mortality are not necessarily only of human origin, however. The diﬀerent sizes of a number of species have, for example, their own degree of ﬁre tolerance. This means that trees up to a particular size class may be removed from a stand by a suﬃciently intense ﬁre. Wilson and Witkowski (2003) found that the bark-thickness of B. africana increases with tree circumference between 0 and 400 mm. The thickness of the bark is the primary protector against the eﬀect of ﬁre on the cambium. Fire tolerance may be overcome if the bark of trees is breached by animals (Yeaton 1988) or growth stresses (Graz 2003). Studies relating to spatial aspects have in the past concentrated on the dispersion of plants using measures such as the nearest neighbour of Clark and Evans (1954) or point to plant distances after Pielou (1977). More recently the uniform angle index (UAI) (Gadow 1999; Staupendahl 2001; Gadow et al. 2003) has been implemented to describe complex forest structures. The aggregation of tree attributes have only been addressed more recently by other measures, such as the ‘‘measure of surround’’ (Hui et al. 1998) or the spatial ‘‘mingling’’ (Gadow 1999). [85]

1146 The mingling measure is used to quantify the degree of interspersion or mingling of tree characteristics, as illustrated in Figure 1. Trees that are surrounded by others of similar characteristic are aggregated in terms of the characteristic, implying a lower degree of mingling of this characteristic. On the other hand, trees surrounded by others of dissimilar characteristic imply a higher degree of mingling. Mingling should not only be considered in terms of categorical data, such as species or sex, or whether a tree is alive or dead, but should be expanded to include any measure with which a tree might be described, including height or diameter. Albert and Gadow (1998) reported on the use of these neighbourhood-based measures to assess the eﬀect of selective thinning on the diversity of a beech stand in Germany. The authors had found the measures to be sensitive to small-scale diﬀerences and changes of woodland structure, and were able to provide more intuitively acceptable results than the segregation index of Pielou (1977, p. 227 ﬀ). This study aims to achieve two main objectives. The ﬁrst objective is to assess the applicability of indicators that were developed and assessed in Europe to the Southern African context where little or no basic stand information is available for non-plantation areas. In addition, the study intends to generate information that will promote the understanding of the ecology of Namibia’s woodland resources. Description of the study area The woodland area that was enumerated covers approximately 70 ha and is situated between 1930¢ E, 1915¢ S and 1945¢ E, 1930¢ S near the Kanovlei Forestry Research Station in the western Tsumkwe district of the Otjozondjupa region, northeastern Namibia. The area is dominated by linear fossil dunes or sandy plains on calcareous deposition, similar to those in the adjoining Kavango region described by Graz (1999). The soils are Kalahari sands, classiﬁed as unconsolidated aeolian material by Coetzee (2001), with very poor water holding capacity and nutrient status, and subsequently a very low potential for any agricultural development (Department of Water Aﬀairs 1991).

Figure 1. The mingling of black, grey and white ‘trees’ within two square stands (after Gadow, 1999). [86]

1147 The region is traversed by a system of omuramba (vegetated dry riverbed), with the soils classiﬁed as unconsolidated ﬂuvial material (Coetzee 2001). These soils are shallower and have a heavier texture than the dunes (Department of Water Aﬀairs 1971). Precipitation is mostly in the form of thunderstorms amounting to an average rainfall of between 500 and 600 mm per year (Amakali 1992). However, the distribution of precipitation is highly variable and prominently positively skewed. Expected rainfall is therefore signiﬁcantly lower than the long-term averages. Rain generally falls in the period September to May, with most rain occurring between December and March. Average annual evaporation rates are between 2600 and 2800 mm (Crerar and Church 1988) resulting in an overall moisture deﬁcit. de Pauw and Coetzee (1999) have determined an approximate growing period of between 91 and 120 days, based on the relationship between available moisture, the amount of evapotranspiration and the average air temperature. Although the general vegetation is described as tree savanna and woodland by Giess (1998), there is some signiﬁcant variation in species and structural composition. The Directorate of Forestry identiﬁes a number of dissimilar patches of forest or savanna (Chakanga 1995). While the sandy planes and dunes are dominated by Burkea africana, various species of Combretum, Pterocarpus angolensis, Schinziophyton rautanenii and Terminalia sericea. Scattered patches of Baikiaea plurijuga also occur. The lower lying omuramba vegetation is comprised primarily of Acacia erioloba, Dichrostachys cinerea and Philenoptera nelsii. Nuts from the S. rautanenii trees within the stand are harvested by local communities to augment their food supply, and by the Directorate of Forestry to obtain material for the National Tree Seed Centre and for ex situ conservation of genetic material. Additionally the stand shows signs of periodic wood harvesting of B. plurijuga stems, as well as for ﬁrewood. Dry season ﬁres are frequent (Graz 2003).

Material and methods The interspersion of tree attributes The original measure of mingling and its derivatives are based on the proportion of trees with dissimilar characteristics to those of a selected sample tree. The species mingling index Mi for a given sample tree, i, using n neighbours is, for example, obtained through: ð1Þ

Mi ¼

n 1X mij ; n j¼1

[87]

1148 where

mij ¼

1; if the tree is of another species; 0; if the tree is of the same species:

When four neighbours are used to determine Mi the index may obtain one of ﬁve possible values: 0/4 none of the neighbours are of a diﬀerent species, 1/4 one of the neighbours is of a diﬀerent species, 2/4 two of the neighbours are of a diﬀerent species, 3/4 three of the neighbours are of a diﬀerent species, and 4/4 all of the neighbours are of a diﬀerent species. The arithmetic mean (MSp) of the Mi values that were obtained for a particular species sp provides a measure of the degree of interspersion of the species in the area. MSp provides a value between 0 and 1. Values close to 0 indicate that trees of the reference species sp occur in groups therefore implying a low degree of mingling and high degree of aggregation. High values of MSp, closer to 1, on the other hand, imply a high degree of mingling, i.e. trees of the reference species do not occur together. As is the case when examining the distribution of data around a mean value, additional information may be extracted from the distribution of Mi values of individual species. When the proportion that a species contributes to a stand is known, as assumed in the studies reported on by Lewandowski and Pommerening (1997) and Hui et al. (1998) a theoretical distribution of Mi values may be calculated based on the hypergeometric probability distribution. The distribution reﬂects the number of expected Mi values that would be obtained if all trees were interspersed randomly. The hypergeometric distribution is used to determine the probability, P, that a number of trees of a particular species may occur in a given sample of n trees taken from a population of N trees containing k trees of the species of interest. The probability that x trees in the sample will be of the species of interest is then determined after Newmark (1997) as: k Nk x nx P¼ for x ¼ 0; 1; 2; . . . ; n; N n which expands to: P¼

k xðkxÞ

ðNkÞ ðnxÞðNkðnxÞÞ N nðNnÞ

for x ¼ 0; 1; 2; . . . ; n:

The resulting probability multiplied by the total number of samples that were taken provides the expected number of Mi values for that species. The [88]

1149 observed and expected distributions of Mi values may then be compared with the application of standard statistical methods to test for signiﬁcance of deviations from the theoretical (random) distribution. Although no detailed data is available for any of the woodland areas in Namibia, and the extent of the woodland areas hampers the collection of such information, the sample size provided a suitable estimate of the species composition of the stand. The simulation study reported on by Graz (2004) has shown that the mingling index is sensitive to the species composition of a stand. In a stand of trees interspersed randomly, for example the aggregation of a species, 1 MSp, approximates the proportion that a species Sp contributes to the stand. This may be more intuitively understood if we consider each sample tree to provide an estimate of the proportion that its species contributes to the stand. Values of 1 MSp which are greater than the proportion contribution therefore indicate an overaggregation of the species, while lower values imply overdispersion within the stand. This relationship provides an important base from which the index may be interpreted. This study investigated the interspersion of a number of tree characteristics. In addition to the mingling of species described above, the interspersion of tree dominance is quantiﬁed on the basis of diameter (TSp) and height (HSp) using the ‘‘measure of surround’’ described by Hui et al. (1998), and which is applied in a method analogous to that of the mingling index. More particularly: ð2Þ

Ti ¼

where

tij ¼

1;

n 1X tij ; n j¼1

if the tree; j; is thicker than the sample tree i; 0; otherwise:

The species speciﬁc mean interspersion of tree diameter, TSp, is then the arithmetic mean of the values of Ti for that species. Similarly, the interspersion of tree height, Hi, is obtained through: ð3Þ

Hi ¼

where

hij ¼

1;

n 1X hij ; n j¼1

if the tree; j; is higher than the sample tree i; 0; otherwise:

The species speciﬁc interspersion of tree height, HSp, is then again determined as the mean of the values of Hi for the species. An equivalent measure was used to quantify the interspersion of dead trees (DSp) by counting the number of dead neighbours for each sample tree. [89]

1150 Uniform angle index The UAI was initially described by Gadow et al. (1998) and later by Staupendahl (2001) to provide a measure of the overall contagion of trees within a forest stand. The index is obtained by identifying the n nearest neighbours of a sample tree. Starting with the closest neighbour and moving in a clockwise direction around the sample tree the angle, aj, between two adjacent neighbours is determined in relation to the sample tree. The number of angles smaller than, or equal to, a given critical angle, a0, are then counted, i.e. ð4Þ

Wi ¼

where

wij ¼

1; 0;

n 1X wij ; n j¼1

if aj a0 ; otherwise:

The critical angle (in degrees) is determined as: ð5Þ

a0 ¼

360 : Number of neighbours

Four neighbours would therefore be evaluated in terms of a 90 critical angle1. Since all of the indexes used to measure the interspersion of tree characteristics were based on four trees, the same neighbours could be used for the UAI. A practical advantage of choosing a0 = 90 is that two adjoining sides of a record book or clipboard may be used to determine whether or not an angle is greater than or less than the critical angle. Eﬀectively, the index describes the spatial distribution around a particular reference tree. If the species of the reference tree is noted we may obtain the mean value for either for the whole population or for a particular species of interest. The mean value of the index is strongly correlated with the nearest neighbour index of dispersion of Clark and Evans (1954) that has long been used in ecological studies. Together with the number of trees in a stand, the UAI may be used to estimate the distribution of distances between a tree and its neighbours (Gadow et al. 2003). This information is generally not available and comparison of observed index values are compared to the simulation results of Gadow et al. (1998) are used.

1

More recent studies have shown that this statement needs to be modiﬁed; a more suitable critical angle is 72 (see Gadow et al. 2003). [90]

1151 Sampling The extent of the stand was recorded in the ﬁeld using a Garmin Venture GPS. The track-log was stored for subsequent mapping. A regular sample grid of one geographic second was then superimposed on the stand amounting to a sample point approximately every 30 m at that latitude. Sampling points were located using a standard GPS receiver. The accuracy of autonomous GPS readings was considered adequate for the purpose of the study. While a dense canopy reduces the reliability of a GPS reading within a stand (Dominy and Duncan 2001), many of the trees in the area had already shed their leaves and canopy interference was considered negligible after initial comparison of signal strengths in wooded and in open areas. Since the enumeration coincided with the war in Iraq it is uncertain whether GPS readings were aﬀected by selective availability on some days. It was felt, however, that this was acceptable. At each sample point the closest tree with a dbh of 5 cm or more was identiﬁed to serve as reference tree. Although trees had, in a few cases, snapped oﬀ below breast height, such trees were nevertheless sampled, since they play a role in the interspersion of plants. For each sample tree the four nearest neighbouring trees with a diameter of greater than 5 cm were determined and compared with the reference tree in terms of species, mortality, height and diameter, and the UAI was established. Time was kept short by assigning two persons to each sampling team. While the enumerator collected the measures, a navigator moved to ﬁnd the next sample point. A total of 1121 sample points were assessed. The data was entered into a spreadsheet and the indexes were calculated for each species using cross tables.

Results and discussion The species speciﬁc indexes are summarized in Table 1. The table also shows a surrogate species of ‘Dead’ created to record trees that were still standing but had been burnt beyond a stage where they might be identiﬁed. Also, species of the genus Combretum and Comiphora were lumped, as individual species could not readily be identiﬁed. The row marked ‘overall’ provides the each index as calculated over the entire data set. The overall shows a contagion (Wi) greater than 0.6, here indicating a tendency towards non-random (clumped) dispersion of trees (after Gadow et al. 1998). The dispersion around trees of the individual species does not seem to diverge very much from the mean value of 0.665, if Philenoptera nelsii and Securidaka longipedunculata are discounted because of their very low overall occurrence. This is in line with general observations in the ﬁeld. The table shows that most of the species have a tendency to aggregate.

[91]

1152 To compare the proportion of a given species within the stand and the value 1 MSp consider Table 2. The table omits those species with very few observations (less than 5% of the total). The ﬁnal column in the table reﬂects the parameter M proposed by Graz (2004) to determine the degree of interspersion. The value of M is larger than 0 and less than or equal to 1. Values close to 0 indicates a very low degree of mingling, and 1 indicates a more random distribution of the species in the stand. Table 2 shows that B. plurijuga has the highest degree of aggregation followed by Terminalia sericea. More T. sericea seedlings survive in open areas, i.e. away from conspeciﬁc trees (Smith and Grant 1986) where it has the ability to form thickets (Shakelton 2001). This was evident in the ﬁeld. T. sericea would colonize gaps in the canopy, thus causing the aggregation. The dispersion of B. plurijuga is also shown in Figure 2. The ﬁgure shows that the species occurs in a very limited area. The accompanying graph shows the relative distribution of Mi values (bar) and the theoretical hypergeometric distribution. The graph shows a clear diﬀerence between the two, due to the clumping of the species, reﬂected by the low value of M (Table 2). The cause of the aggregation of B. plurijuga is uncertain, since the trees had few larger neighbours as evidenced by the low value of TSp in Table 1. It is possible that the patch of B. plurijuga is a remnant of a larger stand that has been subject to high degrees of mortality. This possibility stems from reports by Von Breitenbach (1968) who suggested that the almost pure stands in the Caprivi region developed towards mixed stands as a result of ﬁre. The possibility is corroborated by the high degree of mortality (DSp) associated with the species (see Figure 3). The dead trees within the B. plurijuga Table 1. Mean of the various indicators for each of the identiﬁed species. Species of sample tree

N

P(Sp)

WSp

DSp

MSp

TSp

HSp

Burkea africana Baikiaea plurijuga Combretum species Comiphora species Ochna pulchra Philenoptera nelsii Pterocarpus angolensis Schinziophyton rautanenii Securidaka longipedunculata Strychnos pungens Terminalia sericea Unidentiﬁable dead tree Overall

116 194 214 36 26 16 178 75 2 26 96 142 1121

0.103 0.173 0.191 0.032 0.023 0.014 0.159 0.067 0.002 0.023 0.086 0.127 1.0000

0.688 0.665 0.657 0.639 0.635 0.750 0.647 0.653 0.625 0.683 0.641 0.701 0.665

0.226 0.116 0.148 0.201 0.087 0.141 0.163 0.137 0.125 0.163 0.130 0.285 0.169

0.751 0.653 0.697 0.875 0.962 0.820 0.813 0.875 0.962 0.893 0.781

0.323 0.249 0.484 0.382 0.567 0.563 0.198 0.243 0.375 0.462 0.565

0.332 0.256 0.479 0.556 0.673 0.625 0.218 0.300 0.625 0.548 0.602

0.794

0.360

0.399

P(Sp) denotes the proportion that a species contributes to the stand as a whole. The species speciﬁc indicators are: WSp = mean UAI, DSp = mean mortality, MSp = mean mingling, TSp = mean diameter dominance, and HSp = mean height dominance. The overall values for each indicator was calculated using the entire data set. [92]

1153 Table 2. Comparing the proportion P(Sp) that a species contributes to the population with (1 MSp). Species of sample tree

N

P(Sp)

MSp

1 MSp

P ðpÞ M ¼ 1M Sp

Baikiaea plurijuga Burkea africana Combretum species Pterocarpus angolensis Schinziophyton rautanenii Terminalia sericea Unidentiﬁable dead tree Total

116 194 214 178 75 96 142 1121

0.103 0.173 0.191 0.159 0.067 0.086 0.127

0.653 0.751 0.697 0.813 0.875 0.781

0.347 0.249 0.303 0.188 0.125 0.219 0.285*

0.298 0.696 0.631 0.883 0.627 0.391 0.447

*Note that the value of DSp is used here (the mean proportion of dead neighbours), rather than the mingling index.

patch, shown in ﬁgure 3, are generally large trees. This is not evident from the indexes but supports the suggestion by Von Breitenbach cited above. Actual tree mortality may be caused directly by repeated burning of the stem, as well as changes in the osmotic potential of the top-soil that is caused by the accumulation of ash in the upper soil layers (Mitlo¨hner pers. comm.) In contrast to B. plurijuga, P. angolensis is interspersed almost randomly according to Table 2 and in Figure 2. As is evident in the ﬁgure, the observed distribution of Mi values (bars) follow the theoretical distribution much more closely than those of B. plurijuga. It must be noted, that P. angolensis occurs comparatively seldom within the B. plurijuga patch. This exclusion from the patch is more pronounced for B. africana. The reason or cause for this is not readily apparent. Outside this patch B. africana is more aggregated resulting in the lower value of M. The random distribution of P. angolensis is probably a reﬂection of the regeneration requirements of the species. Vermeulen (1990) reports that P. angolensis is especially sensitive to competition in the seedling and establishment phases. The species therefore often regenerates in areas that have been cleared by human or other action. Other species would then establish themselves later. The interspersion of trees of diﬀerent size is reﬂected in the columns TSp (diameter speciﬁc) and HSp (height speciﬁc) in Table 1. Preliminary simulation results have shown that a random interspersion of tree sizes would result in an overall average of TSp = 0.5 and HSp = 0.5. The table shows, therefore, that size classes are not interspersed randomly. P. angolensis, S. rautanenii and B. plurijuga need to be highlighted. The low values of TSp and HSp for these species imply that few neighbouring trees are larger than the reference tree. This is supported by general observations in the ﬁeld. The species therefore dominate in the area in which they occur. It also reﬂects the regeneration requirements of P. angolensis noted previously, but highlights the importance of further research into the demography of the other two species. [93]

1154

Figure 2. The dispersion of Baikiaea plurijuga, Pterocarpus angolensis and Burkea africana, within the study area. High values of Mi are shown in large circles and vice versa. The graphs depict the observed relative distribution of Mi values (bars), and the theoretical hypergeometric distribution (lines) of the values that would indicate a completely random interspersion of the species.

Table 1 also shows a similarity between the values of TSp and HSp of the individual species. Unpublished data shows a high degree of correlation between the dbh and height of B. africana (r2 = 0.8352), as well as for P. angolensis (r2 = 0.7317) for nearby stands. [94]

1155

Figure 3. The aggregation of dead trees within the stand. The degree of interspersion is reﬂected by the size of the points, with a high degree of aggregation shown by larger points.

Diﬀerences between the two indexes are due to the number of species found in the stand, and the diﬀerences in their respective diameter height relationships. A larger diﬀerence occurs for the Comiphora species, however, reﬂecting the squat form of the trees; a relatively thick-trunked but short tree.

Conclusions In the past the applications of neighbourhood-based spatial measures were supported by detailed knowledge of the stands that were assessed, as noted above. This was not the case in this study, where only the extent of the stand was known. However, despite their simple application the indexes are able to provide information about the stands they describe, being able to reﬂect much of what is currently known about the individual tree species and their ecological circumstances. The results have also highlighted gaps in our knowledge of the ecology of a few of the important trees, such as Schinziophyton rautanenii, Baikiaea plurijuga, and Burkea africana, as well as the various Combretum species that occur in the area. These include regeneration requirements and species succession, and highlights the need for further investigation. The application of the measures described here has shown that they are easily applied in the ﬁeld with relatively little training required, although the ﬁeld crews will have to be able to identify the diﬀerent tree species. This is particularly useful in view of the trend towards community based natural resource management in Namibia, where community members will have to assess their own resources. Since most of the rural community members are able to identify diﬀerent plants in their vernaculars, species identiﬁcation should not be a problem, despite sometimes limited literacy levels. [95]

1156

Acknowledgements I would like to thank my sister Ms. H. Riehmer and Ms. R. Haipinge as well as the late Mr. H. Roth for their assistance with data collection in the ﬁeld. My sincere thanks also to the Directorate of Forestry, Namibia, for allowing me to use the Kanovlei Forest Station as a base, and the Polytechnic of Namibia who funded the ﬁeld work. I would particularly like to thank Prof. K. von Gadow, Institute of Forest Management, Univeristy of Goettingen for comments.

References Albert M. and Gadow K.v. 1998. Assessing biodiversity with new neighborhood-based parameters. In: Proceedings of the International Conference on Data Management and Modelling Using Remote Sensing and GIS for Tropical Forest Land Inventory. Jakarta, Indonesia, Oct. 26–29, 1998. Amakali M. 1992. Updated isohyetal rainfall map for Namibia. Unpublished Report. Department of Water Aﬀairs, Namibia. Bu¨schel D. 1999. A study of resource utilization: a case from Namibia, Mpungu constituency, Kavango district, northern Namibia. CRIAA SA-DC Report, Windhoek, Namibia. Chakanga M. 1995. Forest Cover Reconnaissance Mapping Project. Directorate of Forestry, Republic of Namibia, Windhoek. Childes S.L. 1984. The population dynamics of some woody species in the Kalahari sand vegetation of the Hwange National Park. M.Sc. thesis, University of the Witwatersrand, South Africa. Clark P.J. and Evans F.C. 1954. Distance to Nearest Neighbor as a Measure of Spatial Relationships in Populations. Ecology 35(4): 445–453. Coetzee M.E. 2001. NAMSOTER, A SOTER database for Namibia. Agroecological Zoning Programme, Ministry of Agriculture, Water and Rural Development, Namibia. Crerar S.E. and Church J.T. 1988. Evaporation map for south West Africa/Namibia. Hydrological Report No. 11/1/8/1/H1, Department of Water Aﬀairs, Namibia. Dominy N.J. and Duncan B. 2001. GPS and GIS methods in an African rain forest: applications to tropical ecology and conservation. Conserv. Ecol. 5(2): 6. URL: http://www.consecol.org/vol5/ iss2/art6. Department of Water Aﬀairs. 1971. Consolidated report on reconnaissance surveys of soils of northern and central south West Africa in terms of their potential for irrigation. Report TS/30/ 71, Department of Water Aﬀairs, Windhoek, Namibia. Department of Water Aﬀairs. 1991. Groundwater investigation in Kavango and Bushmanland, Namibia. Unpublished Report. Department of Water Aﬀairs, Windhoek, Namibia. De Pauw E. and Coetzee M.E. 1999. Production of an agro-ecological zones map of Namibia (ﬁrst approximation), Part 2: Results. Agricola 10: 8–68. Gadow K.v. 1999. Waldstruktur und Diversita¨t. Alg. Forst-u. J.-Ztg. 170: 117–122. Gadow K.v., Hui G.Y. and Albert M. 1998. Das Winkelmass – ein Strukturparameter zur Beschreibung der Individualverteilung in Waldbesta¨nden. Centralblatt das gesamte Forstwesen. 115(1): 1–10. Gadow K.v., Hui G.Y., Chen B.W. and Albert M. 2003. Beziehungen zwischen Winkelmass und Baumabsta¨nden. Forstw. Cbl. 122: 127–137. Giess W. 1998. A preliminary vegetation map of Namibia (3rd revised edition). Dinteria 4: 1–112. Graz F.P. 1996. Management of a Pterocarpus angolensis population under the inﬂuence of ﬁre and land use. M.Sc. thesis, University of Stellenbosch, South Africa.

[96]

1157 Graz F.P. 1999. A preliminary terrain feature classiﬁcation of the Okavango region, Namibia. S. Afr. J. Survey. Geo-Inf. 1: 123–129. Graz F.P. 2003. Fire damage to Schinziophyton rautanenii (Schinz) trees in North-Eastern Namibia. Dinteria 28: 39–43. Graz F.P. 2004. The behavior of the species mingling index MSp in relation to species dominance and dispersal. Eur. J. Forest Res. 1: 87–92. Hui G.Y., Albert M. and Gadow K.v. 1998. Das Umgebungsmaß als Parameter zur Nachbildung von Bestandesstrukturen. Forstw. Cbl. 117: 258–266. Lee R.B. 1973. Mogongo: the ethnography of a major wild food resource. Ecol. Food Nutr. 2: 307– 321. Leger S. 1997. The Hidden Gift of Nature. DED, German Development Service, Berlin, Germany. Lewandowski A. and Pommerening A. 1997. Zur Beschreibung der Waldstruktur – Erwartete und beobaachtete Arten-Durchmischung. Forstw. Cbl. 116: 129–139. Mitlo¨hner R. 1997. Pﬂanzeninterne Potentiale als Indikatoren fu¨r den tropischen Standort. Shaker Verlag. Newmark J. 1997. Statistics and Probability in Modern Life, 6th ed. Sauders College Publishing, Fort Worth. NFSP. 1996. Namibia Forestry Strategic Plan. Directorate of Forestry, Windhoek, Namibia. Ollikainen T. 1992. Study on wood consumption in Namibia. Internal Report, Directorate of Forestry, Windhoek. Pielou E.C. 1977. Mathematical Ecology. John Wiley & Sons, New York, 384 pp. Rutherford M.C. 1981. Survival, regeneration and leaf biomass changes in woody plants following spring burns in Burkea africana – Ochna pulchra savanna. Bothalia 13: 531–552. Shackleton C.M. 2001. Managing regrowth of an indigenous savanna tree species (Terminalia sericea) for fuelwood: the inﬂuence of stump dimensions and post-harvest coppice pruning. Biomass Bioenergy 20: 261–270. Smith T.M. and Grant K. 1986. The role of competition in a Burkea africana – Terminalia sericea savanna. Biotropica 18: 219–223. Staupendahl K. 2001. Das ﬂa¨chenbezogene Winkelmass Wf – Ein Index zur quantitativen Beschreibung der horizontalen Baumverteilung. In: Akca A. et al. (HRSG). Waldinventur, Waldwachstum und Forstplanung – Moderne Technologien, Methoden und Verfahrensweisen. Festschrift K. von Gadow. Zohab-Verlag, Go¨ttingen. pp. 101–115. Vermeulen W.J. 1990. A monograph on Pterocarpus angolensis. SARCCUS Standing Committee for Forestry, Pretoria, South Africa. Von Breitenbach F. 1968. Long-term plan of forestry development in eastern Caprivi Zipfel. Unpublished Report. George, South Africa. Wilson B.G. and Witkowski E.T.F. 2003. Seed banks bark thickness and damage in age and size structure (1978–1999) of the African savanna tree Burkea africana. Plant Ecol. 167: 151–162. Yeaton R.I. 1988. Porcupines, ﬁres and the dynamics of the tree layer of the Burkea africana savanna. J. Ecol. 76: 1017–1029.

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Biodiversity and Conservation (2006) 15:1159–1177 DOI 10.1007/s10531-004-3509-3

Springer 2006

-1

Assessment of threat status and management eﬀectiveness in Kakamega Forest, Kenya BA¨RBEL BLEHER1,2,*, DANA USTER3 and THOMAS BERGSDORF 4 Institut fu¨r Zoologie, Abt. V- O¨kologie, Johannes Gutenberg-Universita¨t Mainz, Becherweg 13, 55099 Mainz, Germany; 2Department of Ornithology, National Museums of Kenya, Nairobi, Kenya; 3 Universita¨t Bielefeld, Fakulta¨t fu¨r Biologie, Abt. O¨kologie, Universita¨tsstrasse 25, 33615 Bielefeld, Germany; 4Zoologisches Forschungsinstitut & Museum Alexander Koenig, Adenauerallee 160, 53113 Bonn, Germany; *Author for correspondence (e-mail: [email protected]; phone: +49-(0)61313926108; fax: +49-(0)6131-3923731) 1

Received 6 May 2004; accepted in revised form 6 September 2004

Key words: Conservation, Disturbance indicator, Forest degradation, Logging, Management Abstract. To counteract an increasing biodiversity decline, parks and protected areas have been established worldwide. However, many parks lack adequate management to address environmental degradation. To improve management strategies simple tools are needed for an assessment of human impact and management eﬀectiveness of protected areas. This study quantiﬁes the current threats in the heavily fragmented and degraded tropical rainforest of Kakamega, western Kenya. We recorded seven disturbance parameters at 22 sites in diﬀerently managed and protected areas of Kakamega Forest. Our data indicate a high level of human impact throughout the forest with illegal logging being most widespread. Furthermore, logging levels appear to reﬂect management history and eﬀectiveness. From 1933 to 1986, Kakamega Forest was under management by the Forest Department and the number of trees logged more than 20 years ago was equally high at all sites. Since 1986, management of Kakamega Forest has been under two diﬀerent organizations, i.e. Forest Department and Kenya Wildlife Service. The number of trees logged illegally in the last 20 years was signiﬁcantly lower at sites managed by the Kenya Wildlife Service. Finally, logging was lower within highly protected National and Nature Reserves as compared to high logging within the less protected Forest Reserves. Reﬂecting management eﬀectiveness as well as protection status in Kakamega Forest, logging might therefore provide a valuable quantitative indicator for human disturbance and thus an important tool for conservation managers. Logging might be a valuable indicator for other protected areas, too, however, other human impact such as e.g. hunting might also prove to be a potential indicator.

Introduction Recent decades have seen a serious biodiversity decline due to habitat loss and alteration especially of tropical forests leading to a profound species-extinction crisis (Heywood 1995; Pimm et al. 1995; Whitmore 1997). Thus, much of tropical biodiversity is unlikely to survive without eﬀective protection (Pimm et al. 1995; Myers et al. 2000). To counteract the anthropogenic impact and conserve biodiversity and ecosystem processes parks and protected areas have been established worldwide. Some studies demonstrate that parks can indeed provide basic safeguard against land-clearing in the context of high land-use pressure (Brunner et al. 2001). However, more often parks appear to lack [99]

1160 adequate management to address a host of threats within their borders (Brunner et al. 2001; Putz et al. 2001; Ervin 2003a, b). Protected areas face increasing levels of environmental degradation with more than 70% of 201 parks surveyed across 16 tropical countries being aﬀected by poaching, encroachment and logging (van Schaik et al. 1997). Consequently, the improvement of management strategies of protected areas is of top priority for conservation practitioners. To improve and optimise management strategies methods to assess the threat status of protected areas and to measure management eﬀectiveness of conservation eﬀorts have become a major environmental concern (Margoluis and Salafsky 1998; Salafsky and Margoluis 1999; Hockings et al. 2000; Salafsky et al. 2002; Ervin 2003c; Hockings 2003). These assessments are an essential component of systematic conservation planning (Margules and Pressey 2000); they can enable conservation managers and policymakers to identify management strengths and weaknesses, reveal severity and distribution of levels of human impact, respond to pervasive management problems, reﬁne their conservation strategies and reallocate budget expenditures (Brunner et al. 2001; Ervin 2003 a, c; Parrish et al. 2003). Therefore, the development of simple tools to monitor and assess whether conservation succeeds for protected areas are of great importance and require indicators that are measurable, scientiﬁcally sound, and comparable among protected areas over time, but also practical and cost-eﬀective (Margoluis and Salafsky 1998). Traditionally, biological indicators have been used to assess the level of human impact in protected areas and measure management success. Ideally, they are supposed to serve as indicators for changes in the overall biodiversity of a site (Noss 1990; Sparrow et al. 1994). However, relationships between potential indicator species and total biodiversity as well as critical ecosystem processes are not that well established (Lindenmayer et al. 2000). Few of these methods using biologically based indicators are practical and cost-eﬃcient, especially for use in the developing countries as they require substantial eﬀort and resources beyond day-to-day project activities (Salafsky and Margoluis 1999). Finally, their results are often diﬃcult to interprete for non-specialists and generally require the presence of baseline data against which to compare changes (Salafsky and Margoluis 1999). Another approach to assess human impact in protected areas and to assess management eﬀectiveness is to identify and monitor threats directly as a proxy measurement of conservation success such as e.g. implemented in the Threat Reduction Assessment (TRA) (Salafsky and Margoluis 1999) and the Rapid assessment and Prioritization of Protected Area Management (RAPPAM) program recently established by WWF’s Forest for Life program (Ervin 2003c). This approach of directly identifying threats is sensitive to changes over short time periods and throughout a site, comparisons among projects and sites are possible, data can be collected through simple techniques and the method is practical and cost-eﬀective. Furthermore, the results can be readily interpreted by conservation staﬀ and can provide detailed, adaptive management guidance [100]

1161 to protected area managers. The primary tool for RAPPAM is the rapid assessment questionnaire which covers management planning, input and processes, and the identiﬁcation of future threats and past pressures (Ervin 2003c). However, quantitative and objective approaches are still urgently required for the assessment of threat status and management eﬀectiveness of protected areas to provide reliable, scientiﬁcally sound data. In this paper we present results from a survey quantifying human impact and evaluating management eﬀectiveness in Kakamega Forest, western Kenya. Kakamega Forest is one of the last remaining indigenous forests of Kenya situated in an agricultural area with a high human density of more than 175 individuals per km2 (Tsingalia 1988). Like many other countries Kenya harbours an on-going conﬂict between forest conservation and land use needs of its increasing population (Tsingalia 1988; Wass 1995). This has put a longterm pressure on Kakamega Forest leading to its severe reduction and fragmentation in the last century. Additionally, it has suﬀered increasing degradation through both, extensive commercial and local exploitation of timber (Tsingalia 1988; Fashing et al. 2004; Mitchell, 2004). Large-scale commercial logging was reduced in the last decades, mostly through oﬃcial presidential decree banning all indigenous tree species exploitation in the forest in the early 1980s (Tsingalia 1988; Mitchell, 2004), the transfer of the northern part of the forest under the rigorous authority of the Kenya Wildlife Service (KWS), the establishment of forest stations and ranger patrols, and through tourism and long-term research (e.g. Zimmerman 1972; Cords 1987; Mutangah 1996; Fashing et al. 2004). However, illegal activities including logging, fuelwood collection and extraction of bark for medicinal purposes occur to this day and appear to be heterogeneously throughout the forest with some sites providing more protection than others (Kiama and Kiyiapi 2001; Fashing et al. 2004; Fashing, in press). Our study presents a quantitative assessment of the current threats in the main forest block of Kakamega Forest and its fragments comprising areas of diﬀerent management regimes and diﬀerent protection priorities. In order to evaluate eﬀectiveness of conservation measures we asked how diﬀerently managed and protected areas diﬀer in their level of human impact. With this assessment we aim to provide a quantitative, simple site-level monitoring tool and a ﬁrst guidance to management planners and decision makers on problems related to human impact and management in Kakamega Forest.

Kakamega Forest and its forest history Study site We conducted the study at Kakamega Forest (between latitudes 0008¢30.5¢¢ N (41,236 in UTM 36 N) and 0022¢12.5¢¢ N (15,984) and longitudes 3446¢08.0¢¢ E (696,777) and 3457¢26.5¢¢ E (717,761), G. Schaab, personal communication), [101]

1162 western Kenya, at an altitude of 1500–1700 m (Figure 1). Kakamega Forest is a mid-altitudinal tropical rainforest and considered to be the eastern most remnant of the lowland Congo Basin rainforests of Central Africa (Kokwaro

Figure 1. Satellite image (channel 5 of Landsat 7 ETM+, 05 Feb 2001) of Kakamega main forest and its ﬁve fragments in western Kenya with oﬃcial forest boundaries as gazetted in 1933 (dashed line) and oﬃcial boundaries of National and Nature Reserves (white line). Coordinates in UTM 36 N. [102]

1163 1988). Annual rainfall in Kakamega Forest is approximately 2007 mm (as averaged from FD records at Isecheno Forest Station from 1982 to 2001) and highly seasonal with a rainy season from April to November and a short dry season from December to March. The average monthly maximum temperature ranges from 18 to 29 C while the average monthly minimum ranges from 4 to 21 C (Muriuki and Tsingalia 1990).

Management history Kakamega Forest was ﬁrst gazetted as Trust Forest under proclamation No. 14 in 1933 and has since been managed by the FD; in 1964 it was declared to be a Central Forest (Blackett 1994). Three small Nature Reserves, Isecheno, Kisere and Yala, were established and gazetted within the Forest Reserve in 1967 (Blackett 1994). In 1986, the northern part of Kakamega Forest called Buyangu together with the adjacent Kisere Forest was gazetted as Kakamega National Reserve and fell under management of the KWS. Today, Kakamega Forest is part Forest Reserve, part Nature Reserve and part National Reserve, and management is under the authority of both, FD and KWS, on behalf of the state.

Fragmentation and disturbance history Kakamega Forest is a highly fragmented and disturbed forest and has been continually exploited for many years due to the high surrounding population pressure (Kokwaro 1988; Wass 1995). The main forest block gazetted in 1933 by the FD to control human activities covered 23,777 ha (Kokwaro 1988, for original forest boundaries see Figure 1). The FD aimed mostly at provision of timber for local communities and commercial demand. Clear-felling of indigenous forest to make way for fast-growing exotic tree and softwood plantations was extensive under colonial forest service. Especially the southern parts of Kakamega were exploited until the late 1980s (Bennun and Njoroge 1999; Mitchell, 2004). Clearance for settlement and tea plantations slowed over the 1980s as forest protection was better enforced, but more areas were cleared south of the Yala river (Brooks et al. 1999). Furthermore, selective logging was intense in the past and the general trend of timber extraction showed a continued rise from 1933 to 1981 (Tsingalia 1988; Mutangah 1996). Consequently, the main agents of forest degradation have been mostly logging and extraction of commercially valuable timber, followed by charcoal burning, cattle grazing, shamba system farming, hunting for bush-meat, tree debarking and removal of dead trees for ﬁrewood (Oyugi 1996; Mitchell, 2004). In the early 1980s a presidential decree banned all indigenous tree species exploitation, leading to a halt of commercial logging, however, tree poaching and other illegal activities still exist. [103]

1164 Table 1. List of 22 disturbance survey sites in Kakamega Forest. Site No. Site name

Main forest/ Area Transect Area Management Protection fragmenta (ha)b length (m) surveyed (ha) regimec statusd

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

f f mf mf mf mf mf mf mf mf mf mf mf mf mf f f f f f f f

Malava Kisere Colobus Buyangu Shikusa Salazar I Salazar II Shamiloli Central II Central I Chemneko Vihiga Sawmill Isecheno II Isecheno I Chepsugor Ikuywa I Ikuywa II Yala Kibiri Ishiru Kaimosi

77 420 8245 8245 8245 8245 8245 8245 8245 8245 8245 8245 8245 8245 8245 1370 1370 1370 1178 1178 1178 65

1200 2600 2400 1600 1000 1000 2000 1000 1000 1000 1000 1000 1000 1000 1600 1000 1000 1600 2000 1000 1000 280

2.4 5.2 4.8 3.2 2.0 2.0 4.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 3.2 2.0 2.0 3.2 4.0 2.0 2.0 0.6

fd kws kws kws kws kws kws fd fd fd fd fd fd fd fd fd fd fd fd fd fd fd

fr nr nr nr nr nr nr fr fr fr fr fr fr nr nr fr fr fr nr nr fr fr

a

Abbreviationss: f, fragment; mf, main forest block. Area sizes obtained from satellite image 05 Feb 2001 Landsat 7 ETM+. c Abbreviations: fd, Forest Department; kws, Kenya Wildlife Service. d Abbreviations: fr, Forest Reserve; nr, National or Nature Reserve. b

As a consequence of the long fragmentation and disturbance history Kakamega Forest was reduced and broken up in several fragments over the last century and today the main forest block covers only 8245 ha (G. Schaab, personal communication; for fragment sizes see Table 1) comprising a heterogenous mixture of diﬀerent succession stages including disturbed primary forest, secondary forest, clearings and glades, as well as tea and timber plantations (Bennun and Njoroge 1999). For more detailed information on the fragmentation and disturbance history of Kakamega Forest see Tsingalia (1988) and Mitchell (2004).

Methods Disturbance survey In February and April 2002 and in June and July 2003, disturbance surveys were carried out at 22 forested sites in Kakamega main forest and its peripheral fragments (for a complete list of all sites see Table 1). Twelve of the 22 sites [104]

1165

Figure 2. Location of 22 disturbance survey sites in Kakamega Forest (left) and the number of trees logged per hectare in the last 20 years for both, trees 610 cm in diameter and >10 cm in diameter for each site, respectively (right).

chosen for surveys were close to the 12 sites where Mutangah (1996) carried out his disturbance surveys in 1992/1994 (see Table 1); an additional 10 new sites where chosen where Mutangah (1996) had not carried out any surveys in the past (e.g. in the fragments Kisere, Malava and Kaimosi). This was done in order to obtain a large sample size of representative sites distributed over the whole Kakamega Forest. The sites chosen were not necessarily near points of easy access (Figure 2); in fact, many of the sites are located in the centre of the forest (e.g. No. 5, 9, 10). With many trails running through the whole of Kakamega Forest, it is easily accessible for local exploitation. At each site except for the smallest fragment (Kaimosi), transects were run at least 1000 m in length (Table 1). Transects sometimes followed existing trails, e.g. at Colobus site we chose some of the former overgrown monkey research transects established by Gathua in 1996 (Fashing and Gathua, in press). In all other cases where trails did not exist, we made our way through undergrowth along a line. Surveys included recording any of seven disturbance parameters in a belt [105]

1166 of 10 m on each side of the transect thereby covering a total area of 56.6 ha with a median of 2 ha per site (range 0.6–5.2). All disturbances recorded are thought to present mostly illegal activities. Disturbance parameters recorded were 1. the number of trees logged: For each tree stump the circumference was measured to calculate its diameter. Trees with a diameter of less than 10 cm were assumed to be collected mostly by women and used as ﬁrewood, whereas trees with a diameter of more than 10 cm were assumed to be cut mostly by men and used as polewood or timber. For each stump the approximate time since cutting was estimated to be either less than 20 years or more than 20 years for a distinction between recent and past logging, respectively. Age was estimated according to the degree of decomposition and the shape of the remaining tree stump, i.e. stumps with smooth surfaces or freshly cut stumps with clear cutting proﬁles were estimated to be logged in the last 20 years, whereas stumps with wavy or semi-decayed cut surfaces were estimated to be logged more than 20 years ago (following Mutangah 1996). Tree species were identiﬁed when possible; however, for trees having been logged more than 20 years ago, species identiﬁcation was not always possible due to a higher level of decomposition. 2. the number of trees exhibiting any signs of debarking for medicinal use. 3. the number of charcoal kilns, i.e. areas with charcoal remains such as black half-burned pieces of wood and in some cases still burning charcoal heaps. 4. the number of sawing pits, i.e. pits used for cutting large trees. 5. the number of honey gathering sites, i.e. tree stems with bee-hives from which honey had been extracted. 6. the number of abandoned and current paths used by locals e.g. for ﬁrewood collection. 7. the number of cattle tracks used to bring cattle to the glades for grazing.

Data analysis We tested the inﬂuence of management regime and protection status on the disturbance parameters 1–7 for all 22 sites. For disturbance parameter 1, we tested the inﬂuence separately on the number of logged trees of two diﬀerent age classes (trees logged in the last 20 years, trees logged more than 20 years ago) and two diﬀerent size classes (diameter 10 cm, diameter >10 cm). For management regime we distinguished between sites being managed by the KWS (n = 6) and the FD (n = 16) (Table 1). For protection status we distinguished between sites with high protection priority i.e. National or Nature Reserves (n = 10) and sites with low protection priority i.e. Forest Reserves (n = 12) (Table 1). Consequently, 6 National/Nature Reserves are managed by the KWS and 4 National/Nature Reserves and 12 Forest Reserves by the FD. Furthermore, we tested the inﬂuence of fragmentation on the number of logged trees for both, the two diﬀerent age and size classes. We calculated [106]

1167 t-tests (t) for normally distributed data with an adjustment in case variances were unequal and Mann–Whitney U-tests (U) for non-normally distributed data. We correlated the diﬀerent disturbance parameters calculating nonparametric pairwise Spearman correlations. We compared our data from 12 sites (i.e. site No. 5, 7, 8, 11–13, 15–17, 19– 21) with data from Mutangah (1996) who quantiﬁed the same disturbance parameters in 1992/1994 at the same 12 sites. Although the sites were the same, transects were not; thus, data are not dependent data. For comparisons of the two data sets we calculated Pearson and Spearman rank correlations for normally and non-normally distributed data, respectively. Data analysis was carried out using JMP (1995).

Results Evidence for human impact was found at all our 22 sites with a median number of 21.1 disturbance events per hectare (q1 = 9.8, q3 = 44.6, range 1.8–81.5, n = 22). The sites Salazar II (No. 7) situated in the northern Kakamega National Reserve and managed by the KWS as well as Yala (No. 19) situated in the Yala Nature Reserve managed by the FD showed lowest disturbance levels with 2.8 and 4.9 disturbances per hectare, respectively (Table 2). The site Ishiru (No. 21) had highest disturbance levels with 68.5 disturbances per hectare; is situated at the southern forest edge and is managed by the FD.

Management, protection status and logging Of all seven disturbance parameters, logging of trees was the most widespread at all 22 sites (Table 2), thus providing the most useful indicator of forest disturbance in this study. Over a total survey area of 56.6 ha, we found 1023 logged trees from 68 species. The most frequent tree species logged were Funtumia africana (2.1 trees logged per hectare), Prunus africana (1.3), Celtis new species name: Celtis gomphophylla (1.0), Trilepisium madagascariensis (0.9), Diospyros abyssinica (0.8) and Aningeria altissima (0.7). The average diameter of tree stumps was 27.0 cm ± 9.6 (if not otherwise noted mean ± 1 SD). Past and present logging We could not ﬁnd diﬀerences in the number of logged trees for past logging (i.e. more than 20 years ago) between diﬀerent sites indicating that logging levels in the past might have been similar throughout Kakamega Forest (Figures 3a, b; management regime, U: Z = 0.26, p = 0.79; protection status, t: t = 2.32, df = 1, p = 0.15). In contrast, a signiﬁcant eﬀect of management regime and protection status was found for present logging (i.e. in the last [107]

1168

Table 2. Summary data of disturbance survey for all 22 sites.

[108]

Site No.

No. trees logged/ha >20 years

No. trees logged/ha <20 years

Total No. trees logged/ha

No. trees with signs of debarking/ha

No. charcoal kilns/ha

No. sawing pits/ha

No. honey gathering sites/ha

No. paths/ha

No. cattle tracks/ha

Total no. trees logged/ha in 1992/1994

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

3.8 1.9 2.9 5.0 1.5 3.0 2.0 6.0 2.0 2.0 1.5 6.0 1.0 0 0 8.0 0 3.5 1.3 3.0 10.5 0

5.4 8.5 2.3 4.1 1.5 2.0 0 53.5 8.0 10.0 40.5 15.0 36.0 9.0 12.5 34.5 3.8 33.5 1.5 45.4 65.0 30.0

9.2 10.4 5.2 9.1 3.0 5.0 2.0 59.5 10.0 12.0 42.0 21.0 37.0 9.0 12.5 42.5 3.8 37.0 2.8 48.9 75.5 30.0

1.7 1.7 0 0 0 0 0.3 0.5 0 0 0 3.0 0 1.0 2.5 0.5 1.3 0 1.3 0 0.5 6.7

0 0 0 0 1.0 0 0 2.0 0 0 4.5 2.5 0.5 0 0 0 1.3 1.0 0 0 0.5 0

2.1 1.0 0 0 0.5 3.0 0 1.0 2.5 0 0 0 0 0.5 0.3 0 0.3 0 0.8 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 5.0 0 0 0 0 0 0 0 0 0

8.8 2.3 0.2 0 1.5 2.0 0.5 1.0 7.5 1.0 6.5 7.0 0 2.0 0 6.5 5.9 0.5 0 13.0 5.0 0

0.4 0.2 0 0 0 0 0 4.5 0 0 0 0 0.5 0 11.3 0 1.9 0 0 0 0 0

– – – – 14.0 – 1.0 52.0 – – 74.0 29.0 8.0 – 16.0 83.0 23.0 – 11.0 99.0 77.0 –

For logging, numbers per hectare are given separately for trees logged >20 years ago, trees logged <20 years ago and for all trees logged. For a comparison of logging between today and 1992/1994, the total number of trees logged as recorded by Mutangah (1996) are given.

1169

Figure 3. Number of trees logged more than 20 years ago (a, b) and in the last 20 years (c, d) for sites under management by the Kenya Wildlife Service (KWS, n = 6) and the Forest Department (FD, n = 16) (a, c) and for sites having high protection priority (i.e. situated within National/ Nature Reserves, n = 10) and low protection priority (i.e. situated within Forest Reserves, n = 12) (b, d). Given are medians, quartils, minimum and maximum values and signiﬁcance levels. n.s., not signiﬁcant; * p < 0.05; **p < 0.005.

20 years) with fewer trees logged at sites managed by the KWS and with high protection priority (Figures 3c, d; management regime, t: t = 19.21, df = 1, p = 0.0004; protection status, U: Z = 2.54, p = 0.0111). Firewood and polewood/timber use in the last 20 years Traces of ﬁrewood collection (tree diameter 10 cm) were often found at sites managed by the FD but rarely at sites managed by the KWS (Figure 2). The FD-managed sites situated within Nature Reserves (No. 14, 15, 19), in the centre of the forest (No. 9, 10) and in central Ikuywa (No. 17) had the lowest levels of ﬁrewood collection (Figure 2). In contrast, sites at the forest edge (No. 8, 11, 12, 16, 18, 20, 21) adjacent to local settlements had the highest logging [109]

1170 levels (Figure 2). Tree cutting for polewood/timber (tree diameter >10 cm) had low levels at KWS sites, but high levels at FD sites (Figure 2). Both, ﬁrewood collection and logging for polewood/timber was signiﬁcantly higher at FD sites as compared to KWS sites (ﬁrewood/ha: KWS median = 0, q1 = 0, q3 = 0.3, range 0–1.2, FD median = 5.5, q1 = 1.6, q3=17.3, range 0–26.0; U: Z = 3.04, p = 0.0024; polewood/ha: KWS 2.9 ± 2.6; FD 16.9 ± 12.7; t: F = 16.54, df = 1, p = 0.0007). Similarly, signiﬁcant diﬀerences in the number of logged trees for both ﬁrewood and polewood/timber, were found between sites of high and low protection priority (ﬁrewood/ha: high protection median = 0, q1 = 0, q3 = 2.0, range 0–19.0, low protection median = 10.0, q1 = 1.8, q3 = 17.3, range 0–26.0; U: Z = 2.55, p = 0.011; polewood/ha: high protection median = 3.2, q1 = 1.5, q3 = 8.1, range 0–26.5, low protection median=15.4, q1 = 7.4, q3 = 26.3, range 2.5–47.5; U: Z = 2.61, p = 0.0092). Fragmentation and logging No diﬀerences were found between the main forest and the fragments for the number of trees logged more than 20 years ago and less than 20 years ago, as well as for the number of trees logged for ﬁrewood and for polewood/timber (trees logged >20 years ago: U: Z = 0.44, p = 0.64; trees logged < 20 years ago: U: Z = 0.83, p = 0.4037; ﬁrewood/ha: U: Z = 1.57, p = 0.1164; polewood/ha: U: Z = 0.03, p = 0.97). Re-assessment of logging: 1992/1994 and today No diﬀerences for the number of logged trees per hectare were found between our data and those of Mutangah’s (1996) survey in 1992/1994. This suggests a similar overall logging level (1992/1994: 40.6 ± 34.4, today: 29.2 ± 25.2; t: t = 0.92, df = 22 p = 0.37). Furthermore, we found a signiﬁcant positive correlation between both data sets suggesting that transects at the same sites still have same logging levels after 10 years (Pearson: r = 0.72, p = 0.0088).

Management, protection status and other human impact For all other disturbance parameters diﬀerences between diﬀerently managed and protected sites were only found for the number of charcoal kilns with signiﬁcantly lower numbers in highly protected sites (high protection: median = 0, q1 = 0, q3 = 0, range 0–1.0, low protection: median = 0.5, q1 = 0, q3 = 1.8, range 0–4.5; U: Z = 2.26, p = 0.024). However, in contrast to the number of logged trees, all other disturbance parameters were mostly rare events and appear to be indicators only for localized threats (Table 2). Burning of charcoal, e.g., seems to be a serious threat at the eastern (No. 11, 12) and western edge (No. 8) of the main forest block, whereas cattle tracks appear to be a problem mostly at Isecheno I (No. 15) and at the eastern edge of the forest (No. 8) (Table 2). In [110]

1171 general, no correlation could be found between the disturbance parameters when calculating non-parametric pairwise Spearman correlations (p > 0.05).

Discussion Status quo of human impact According to our survey human impact is found everywhere in Kakamega Forest with logging being most widespread. This conﬁrms the expressions of alarm over the misuse and overexploitation of Kakamega’s forest resources through illegal human activities (Kowkaro 1988; Emerton 1991; Mutangah et al. 1992; Wass 1995; Oyugi 1996; Fashing et al. 2004). Our data support Mutangah’s (1996) survey from 1992/1994 indicating the highest logging levels occur in the most southerly part of the forest as well as along the western edge. Furthermore, some of the disturbed sites (e.g. No. 11, 21) in Mutangah’s (1996) survey have been degraded heavily in the meantime and the canopy cover reduced substantially (N. Saijita and C. Analo, personal communication). In both, Mutangah’s (1996) and our survey, the lowest logging levels were found in the northern Kakamega National Reserve, central Ikuywa and Yala.

Human impact in diﬀerently managed areas Our data do not only show the current status quo of the human impact on Kakamega Forest, but also reﬂect its management history in the last 20 years. Before 1986, when all of Kakamega Forest was managed by the FD, Colobus, Buyangu and Salazar sites (No. 3, 4, 6, 7) in the northern part were well known for intensive commercial logging through timber companies (Tsingalia 1988; Mitchell, 2004). Correspondingly, the number of trees logged more than 20 years ago appears to be equally high at those sites as compared to others. In 1986, the KWS took over the northern part of Kakamega Forest as a National Reserve and the changes in management appear to have resulted in changes in logging numbers in the last 20 years. Illegal tree poaching was reduced at sites under KWS management probably due to tightened security, whereas FD sites still experience higher tree poaching rates today. Furthermore, FD sites show various other local threats such as e.g. charcoal burning and cattle grazing. Under FD management, sites with high protection priority such as Yala and Isecheno Nature Reserves (No. 14, 15, 19) still show lower overall threat levels as compared to sites with low protection priority. For example, Fashing et al.’s (2004) results of a long-term study of tree populations in Kakamega Forest indicate that their study plots in Isecheno remained relatively undisturbed over the last 20 years. A decrease of pioneer species density by 21% in these sites are taken as evidence that the [111]

1172 forest is maturing towards a climax forest and that at least the conservation measures applied to Isecheno appear to have succeeded Fashing et al. 2004). Nevertheless, prospects for other severly disturbed sites are assumed to be bad, as is the general prognosis for Kakamega Forest if protection eﬀorts are not increased and illegal exploitation by local people remains high, particularly on its periphery (Cords and Tsingalia 1982; Kokwaro 1988; Tsingalia 1988; Fashing et al. 2004). How do the two conservation boards KWS and FD diﬀer in their management aims and strategies? The overall aim of the KWS is ‘to conserve, protect and sustainably manage the wildlife resources’ and its areas are set aside for conservation and tourism only (Wass 1995). People are not allowed to collect any forest products and these policies are strictly enforced through regular patrols by up to ﬁve game rangers (E.W. Kiarie, personal communication). The overall aim of the FD is to ‘enhance conservation and protection of indigenous forest, to improve the production of timber and fuelwood and to establish a framework for the long-term development forestry’ (Wass 1995). Some sites are also set aside for conservation, however, some used to be plantations of exotic tree species or mixtures of indigenous species, while others experienced enrichment planting (A. Oman, personal communication). Logging, tree debarking and charcoal burning is prohibited, whereas fuelwood collection was licenced until recently (A. Oman, personal communication). It appears that the FD has been largely restricted in its capacity to implement conservation policies eﬀectively due to the lack of adequate resources in contrast to the better funded KWS, leading to insuﬃcient levels of staﬃng, patrols, weaponry etc. These diﬀerences in resources might have led to diﬀerent disturbance levels as found in our survey. Besides overall funding and the number of staﬀ, other potential factors associated with management regime and eﬀectiveness might be e.g. accessibility to the forest or proximity of the forest to neighbouring settlements, population density, community relations and compensation programs to locals. In a recent assessment of the impact of anthropogenic threats on 93 protected areas of 22 tropical countries park eﬀectiveness was shown to correlate most strongly with density of guards i.e. the more guards the higher eﬀectiveness (Brunner et al. 2001). Furthermore, eﬀectiveness correlated with the level of deterrence of illegal activities in the parks and with the degree of border demarcation and existence of direct compensation programs for local communities (Brunner et al. 2001). However, it did not correlate with enforcement capacity (i.e. a composite variable of training, equipment and salary), accessibility, budget, number of staﬀ working on economic development or education, or the local involvement of communities in park management (Brunner et al. 2001). To obtain more information on the factors inﬂuencing management eﬀectiveness in Kakamega Forest more studies are highly recommended following the RAPPAM guidelines.

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1173 Management recommendations for Kakamega Forest The high human impact on Kakamega Forest especially along the western and eastern edge of the main forest block indicates an imminent danger of further fragmentation. The main forest block might fall into two separate forest blocks, i.e. Kakamega National Reserve in the North and Isecheno Nature Reserve in the South. To prevent this from happening in the near future, we strongly recommend following the management plan of forest zoning as outlined by the Kenya Indigenous Forest Conservation Programme (KIFCON 1994; Wass 1995): establishing a protection zone to provide a core for biodiversity conservation extending from the North to South; setting up a rehabilitation zone with enrichment planting where degradation has reached high levels; and establishing a subsistence use zone ﬂanking the protection zones where local people are allowed to extract forest products. This forest zoning aims both, to maintain as much indigenous forest cover as possible and to permit optimal use of forest resources on a sustainable basis (Wass 1995). We recommend placing the protection zone under strict KWS management as our survey indicates that areas of Kakamega Forest managed by the KWS appear to hold surprisingly low disturbance levels despite high land-use pressure. The degradation and logging levels in the suggested subsistence zones are already alarming, so that we suggest enrichment planting there. Finally, encouragement of on-farm-forestry projects might provide resources in the long-term and thus might relieve the subsistence use zone. This is supported by the fact that a tree nursery run by the local grassroot conservation organization KEEP (Kakamega Environmental Education Program) at Isecheno Forest Station has been successfully nursing seedlings of both, indigenous and exotic tree species, for sale to local farmers. Beyond conservation measures for the main forest block, high protection priority must also be given to the low-disturbance sites central Ikuywa (No. 17), Yala (No. 19) and the 400 ha fragment of Kisere (No. 2). Kisere Nature Reserve is of particurlar conservation signiﬁcance because it has been relatively undisturbed in the past and still harbours species-rich forest communities that include the rare DeBrazza monkeys (Cercopithecus neglectus) (Muriuki and Tsingalia 1990; Chism and Cords 1997). Although managed by KWS, it appears to have experienced increasing disturbance levels in the last few years (N. Saijita and C. Analo, personal communication). This might be due to the lack of ranger outposts in Kisere (KWS headquarters is at Buyangu), and the fact that the number of rangers (10–20) might not be suﬃcient to cover both, Buyangu and Kisere. Therefore, an immediate increase of regular ranger patrols to control logging more eﬀectively is highly recommended, as suggested by previous authors (Kokwaro 1988; Mutangah 1996; Chism and Cords 1997).

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1174 Logging as indicator for quantitative threat assessment In our survey only logging appeared to be an eﬀective indicator for human impact on the forest and might oﬀer a valuable tool to conservation managers. First, the recording of the number of logged trees provides a quantitative, objective measure of the human impact on protected areas. Most other assessments of threat status and management eﬀectiveness used qualitative rather than quantitative approaches (see e.g. Salafsky and Margoluis 1999; Brunner et al. 2001; Ervin 2003c). For example, following the RAPPAM methodology and using a questionnaire, the question arises whether the protected area managers themselves answering questions on their own management will supply objective answers. Consequently, our method collecting empirical data on the number of logged trees is more objective. Second, methods using logging as a disturbance indicator assess disturbance directly and not through biological indicators. Often, human impact is inferred from long-term studies on plant species composition or population structure as a biological indicator (e.g. Fashing et al. 2004). However, biological indicators can only assess the present situation resulting from past human impact. In contrast, quantifying disturbances directly can provide empirical data on the present human impact. Furthermore, logging as a disturbance indicator can enable us to diﬀerentiate between recent and past disturbance and might consequently help to evaluate past management policies. Third, despite its quantitative approach this method provides a simple, lowbudget method important especially for rapid and repeated assessment of disturbed forests. Repeated assessments are crucial especially in protected areas such as Kakamega Forest where heterogeneity in forest condition occurs over small spatial scales (Fashing et al. 2004). Consequently, surveys using logging as a disturbance indicator can provide the maximum amount of current up-todate and scientiﬁcally sound information for management planners in return for the eﬀort and time involved. Finally, although the list of potential threats facing protected areas worldwide is long, logging appears to aﬀect nearly 70% of more than 200 parks throughout the tropics (van Schaik et al. 1997) and emerges as one of the most hotly debated issues in tropical forest conservation (Rice et al. 1997; Bowles et al. 1998; Laurance 2001). Consequences of logging do not only include loss of habitat, but also changes in the microclimatic environment, erosion of soil and modiﬁcation of ﬁre regimes (Barlow et al. 2002; Cochrane and Laurance 2002) with the impact depending on the type of logging, i.e. whether commercial mechanized logging with heavy equipment or local exploitation of timber through e.g. pit-sawying and ﬁrewood collection. Furthermore, secondary eﬀects of logging might be increased access to remote forested areas through the creation of roads and paths leading to further logging, forest colonization and hunting (Wilkie et al. 1992; Rice et al. 1997; Laurance 1998; Robinson et al. 1999). Consequently, logging appears to be a serious constant [114]

1175 threat to tropical forests worldwide making its validity as an useful indicator even more probable. Disturbance or impact assessments in combination with long-term studies on forest structure and composition after logging (e.g. Plumptre 1996; Chapman and Chapman 1997; Struhsaker 1997; Fashing et al. 2004) can provide important information on regeneration dynamics after human impact. Studies from Kakamega Forest indicate that regeneration from the severe human impact of the last century might be possible though not without rigorous conservation measures (Fashing et al. 2004, this study). Finally, repeated disturbance assessments are important to keep track of the human impact in protected areas and can provide feedback to management planners when evaluating past management decisions and setting up new conservation goals.

Acknowledgements The study was funded by the German Federal Ministry of Education and Research within the framework of BIOTA East Africa (01LC0025 / subprojects E03, E10 & E11). We thank the Kenyan Ministry for Education and Research for the permission to carry out research in Kakamega Forest, and the KWS and FD for granting us access to their reserves. We appreciate information on management by E.W. Kiarie (Senior Warden, Kakamega National Reserve) and A. Oman (Assistant District Forest Oﬃcer, Kakamega). We highly acknowledge ﬁeld assistance by C. Analo and N. Saijita. G. Schaab kindly provided maps and data on forest patch sizes. We wish to thank the paperclub at Mainz, N. Mitchell, L. Todt, H.Todt, and two anonymous referees for comments on earlier drafts of the manuscript and K. Boehning-Gaese, H. Dalitz and M. Kraemer for overall support.

References Barlow J., Haugaasen T. and Peres C.A. 2002. Eﬀects of ground ﬁres on understorey bird assemblages in Amazonian forests. Biol. Conserv. 105: 157–169. Bennun L. and Njoroge P. 1999. Important Bird Areas in Kenya. The East Africa Natural History Society, Nairobi, Kenya. Blackett H.L. 1994. Forest inventory report no. 3: Kakamega. Kenya Indigenous Forest Conservation Programme, Nairobi, Kenya. Bowles I.A., Rice R.E., Mittermeier R.A. and da Fonseca G.A.B. 1998. Logging and tropical forest conservation. Science 280: 1899–1900. Brooks T.M., Pimm S.L. and Oyugi J.O. 1999. Time lag between deforestation and bird extinction in tropical forest fragments. Conserv. Biol. 13: 1140–1150. Brunner A.G., Gullison R.E., Rice R.E. and da Fonseca G.A.B. 2001. Eﬀectiveness of parks in protecting tropical biodiversity. Science 291: 125–128. Chapman C.A. and Chapman L.J. 1997. Forest regeneration in logged and unlogged forests of Kibale National Park, Uganda. Biotropica 29: 396–412.

[115]

1176 Chism J. and Cords M. 1997. De Brazza’s monkeys Cercopithecus neglectus in the Kisere National Reserve, Kenya. Afr. Primates 3: 18–22. Cochrane M.A. and Laurance W.F. 2002. Fire as a large-scale edge eﬀect in Amazonian forests. J. Trop. Ecol. 18: 311–325. Cords M. 1987. Mixed species association of Cercopithecus monkeys in the Kakamega Forest, Kenya. Univ. Cali. Publ. Zool. 117: 1–109. Emerton L. 1991. Summary of the Current Value of use of Kakamega Forest. Kenya Indigenous Forest Conservation Programme, Nairobi, Kenya. Ervin J. 2003a. Protected area assessment in perspective. BioScience 53: 819–822. Ervin J. 2003b. Rapid assessment of protected area management eﬀectiveness in four countries. BioScience 53: 833–841. Ervin J. 2003c. Rapid assessment and prioritization of protected area management (RAPPAM) methodology. World Wide Fund for Nature, Gland, Switzerland. Available at http:// www.panda.org/downloads/forests/rappam.pdf. Fashing P.J. Mortality trends in the African cherry (Prunus africana) and the implications for colobus monkeys (Colobus guereza) Kakamega Forest, Kenya. Biodiv. Conserv., in press. Fashing P.J., Forrestel A., Scully C. and Cords M. 2004. Long-term tree population dynamics and their implications for the conservation of the Kakamega Forest, Kenya. Biodiv. Conserv. 13: 753–771. Fashing P.J. and Gathua M. Spatial variability in the vegetation structure and composition of an East African rain forest. Afr. J. Ecol. in press. Heywood V.H. (ed.) 1995. Global Biodiversity Assessment. Cambridge University Press, Cambridge, UK. Hockings M. 2003. Systems of assessing the eﬀectiveness of management in protected areas. BioScience 53: 823–832. Hockings M., Stolton S. and Dudley N. 2000. Evaluating eﬀectiveness: a framework for assessing the management of protected areas. IUCN, Gland, Switzerland. Available at http://wcpa. iucn.org/pubs/pdfs/evaluating_eﬀect.pdf. JMP 1995. Statistics and Graphics Guide. Version 3.1. SAS Institute Inc., Cary, NC. Kiama D. and Kiyiapi J. 2001. Shade tolerance and regeneration of some tree species of a tropical rain forest in western Kenya. Plant Ecol. 156: 183–191. KIFCON 1994. Kakamega Forest – The oﬃcal guide. Kenya Indigenous Forest Conservation Programme, Nairobi, Kenya. Kowkaro J.O. 1988. Conservation status of the Kakamega Forest in Kenya: the easternmost relict of the equatorial rain forests of Africa. Monogr. Syst. Bot. Missouri Bot. Garden 25: 471–489. Laurance W.F. 1998. A crisis in the making: responses of Amazonian forests to land use and climate change. Trends Ecol. Evol. 13: 411–415. Laurance W.F. 2001. Tropical logging and human invasions. Conserv. Biol. 15: 4–5. Lindenmayer D.B., Margules C.R. and Botkin D.B. 2000. Indicators of biodiversity for ecologically sustainable forest management. Conserv. Biol. 14: 941–950. Margules C.R. and Pressey R.L. 2000. Systematic conservation planning. Nature 405: 243–253. Margoluis R. and Salafsky N. 1998. Measures of Success: Designing, Managing, and Monitoring Conservation and Development projects. Island Press, Washington, DC. Mitchell N. 2004. The exploitation and disturbance history of Kakamega Forest, western Kenya. In: Bleher B. and Dalitz H. (eds), BIOTA Report No. 1. Bielefelder O¨kologische Beitra¨ge 20. Muriuki J.W. and Tsingalia M.H. 1990. A new population of de Brazza’s monkey in Kenya. Oryx 24: 157–162. Mutangah J.G. 1996. An investigation of vegetation status and process in relation to human disturbance in Kakamega Forest, western Kenya. Ph.D thesis, University of Wales, UK. Mutangah J.G., Mwangangi O. and Mwaura P.K. 1992. Kakamega: A Vegetation Survey Report. Kenya Indigenous Forest Conservation Programme, Nairobi, Kenya. Myers N., Mittermeier R.A., Mittermeier C.G., da Fonseca G.A.B. and Kent J. 2000. Biodiversity hotspots for conservation priorities. Nature 403: 853–858.

[116]

1177 Noss R.F. 1990. Indicators for monitoring biodiversity: a hierarchical approach. Conserv. Biol. 4: 355–364. Oyugi J.O. 1996. Kakamega Forest is dying. East Afr. Nat. Hist. Soc. Bull. 26: 47–49. Parrish J.D., Braun D.P. and Unnasch R.S. 2003. Are we conserving what we say we are? Measuring ecological integrity within protected areas. BioScience 53: 851–860. Pimm S.L., Russell G.J., Gittleman J.L. and Brooks T.M. 1995. The future of biodiversity. Science 269: 347–350. Plumptre A.J. 1996. Changes following 60 years of selective timber harvesting in the Budongo Forest Reserve, Uganda. Forest Ecol. Manage. 89: 101–113. Putz F.E., Blate G.M, Redford K.H, Fimbel R. and Robinson J. 2001. Tropical forest management and conservation of biodiversity: an overview. Conserv. Biol. 15: 7–20. Rice R.E., Gullison R.E. and Reid J.W. 1997. Can sustainable management save tropical forests? Sci. Am. 276: 44–49. Robinson J.G., Redford K.H. and Bennett E.L. 1999. Wildlife harvest in logged tropical forest. Science 284: 595–596. Salafsky N. and Margoluis R. 1999. Thread reduction assessment: a practical and cost-eﬀective approach to evaluating conservation and development projects. Conserv. Biol. 13: 830–841. Salafsky N., Margoluis R., Redford K.H. and Robinson J.G. 2002. Improving the practice of conservation: a conceptual framework and research agenda for conservation science. Conserv. Biol. 16: 1469–1479. Sparrow H.R., Sisk T.D., Ehrlich P.R. and Murphy D.D. 1994. Techniques and guidelines for monitoring neotropical butterﬂies. Conserv. Biol. 8: 800–809. Struhsaker T.T. 1997. Ecology of an African Rain Forest: Logging in Kibale and the Conﬂict Between Conservation and Exploitation. University of Florida Press, Gainesville, Florida. Tsingalia M.H. 1988. Animals and the regeneration of an African rainforest tree. Ph.D. Thesis, University of California, Berkely. van Schaik C.P., Terborgh J. and Dugelby D. 1997. The silent crisis: the state of the rainforest nature reserves. In: Kramer R., van Schaik C.P. and Johnson J. (eds), The Last Stand: Protected Areas and the Defense of Tropical Biodiversity. Oxford University Press, New York, pp. 64–89. Wass P. 1995. Kenya’s Indigenous Forests – Status, Management and Conservation. IUCN, Gland, Switzerland. Whitmore T.C. 1997. Tropical forest disturbance, disappearance and species loss. In: Laurence W.L. and Bieregaard R.O.Jr. (eds), Tropical Forest Remnants: Ecology, Management, and Conservation of Fragmented Communities. University of Chicago Press, Chicago, pp. 3–12. Wilkie D.S., Sidle J.G. and Boundzanga G.C. 1992. Mechanized logging, market hunting, and a bank loan in Congo. Conserv. Biol. 6: 570–580. Zimmerman D.A. 1972. The avifauna of the Kakamega Forest, western Kenya, including a bird population study. Bull. Am. Museum of Nat. Hist. 149: 257–339.

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Biodiversity and Conservation (2006) 15:1179–1191 DOI 10.1007/s10531-004-4693-x

Springer 2006

-1

Inﬂuence of forest types and eﬀects of forestry activities on species richness and composition of Chrysomelidae in the central mountainous region of Japan MASASHI OHSAWA* and TAKUO NAGAIKE Yamanashi Forest Research Institute 2290-1 Saishoji, Masuho-cho, Minamikoma-gun, Yamanashi 400-0502, Japan; *Author for correspondence (e-mail: [email protected]; phone: +81-556-22-8001; fax: +81-556-22-8002) Received 4 May 2004; accepted in revised form 28 October 2004

Key words: Batophila acutangula, Biodiversity, Insect diversity, Larix kaempheri, Leaf beetles, Species composition, Species richness, Sphaeroderma tarsatum Abstract. Species richness and composition of the Chrysomelidae (Coleoptera) were studied in larch (Larix kaempheri [Lamb.] Carrie`re) plantations, secondary forests, and primary forests. In addition, the eﬀects of forest management practices, such as thinning and long rotation, were examined in the larch plantation. The species richness of Chrysomelidae was higher in the larch plantation than in the secondary forest or in the primary forest. Among the larch plantations, the species richness in old-aged plantations was higher than that in middle-aged plantations. The composition of the beetle assemblages in the larch plantation diﬀered from that in the secondary forest or in the primary forest. Exosoma akkoae (Chujo), Batophila acutangula Heikertinger, and Calomicrus nobyi Chujo were caught with a bias toward the larch plantation. Longitarsus succineus (Foudras) and Sphaeroderma tarsatum Baly were caught more in the secondary forest and the primary forest, respectively. More B. acutangula and S. tarsatum were caught in stands where their host plants occurred at higher rates. Species richness of understory plants was an important factor for chrysomlid species richness, and frequency of host occurrence aﬀected the number of individuals of leaf beetles examined. It seems that forest types and forest management practices aﬀect host plants as well as Chrysomelidae, and that these eﬀects on the host plants also inﬂuence chrysomelid assemblages.

Introduction The original vegetation of forestal area in the central mountainous region in Japan is considered as mixed forest of broad-leaved trees and coniferous trees dominated by Quercus crispula Blume. Since the 1940s, however, primary forests have rapidly diminished as a result of forestry activities, and now the area is known for its larch plantations. To achieve ecologically sustainable forest management in this region, studies were started to elucidate the status of biodiversity in forests and eﬀects of forest management practices in the area, i.e., a basic information necessary for ecologically susutainable management. The study area is largely occupied by Japanese larch (Larix kaempferi [Lamb.] Carrie`re) plantations and secondary broad-leaved forests, dominated by [119]

1180 Quercus crispula Blume, (41 and 33% of the total area, respectively). Larch plantations were established for timber production; thinning has been conducted twice within a 45-year period in this area, in order to enhance growth of dominant trees. Long rotations have been adopted for some larch plantations to obtain high quality wood. Secondary forests were formerly used to produce ﬁrewood, charcoal, etc. Now, however, they are mostly left unattended. Because larch plantations and secondary forests occupy large areas, their role in conserving biodiversity is important. Primary forests, though fragmented today, should also be considered important because of the potential presence of rare indigenous species inhabiting in them. Three forest types (larch plantation, secondary forest, and primary forest) and two management practices frequently used in larch plantations (thinning and long rotations) were chosen for this study. Leaf beetles (Chrysomelidae, Coleoptera) are small in size (less than 1.5 cm in general) and their antennas are usually less than half the length of their bodies. They distribute worldwide and about 500 species have so far been reported in Japan (Kimoto and Takizawa 1994). Though they are related with cerambycid beetles which are saproxylic in their larval stage, leaf beetles feed on leaves, stems or roots in both larval and adult stages and are regarded as phytophagous herbivores. The diversity of Cerambycidae, saproxylic beetles, was investigated in this area, and it was reported that higher species richness of the beetles was observed in secondary forests than in larch plantations or primary forests, and that thinning increased cerambycid diversity in larch plantations (Ohsawa 2004). This time, leaf beetles were chosen for the study of diversity to clarify the eﬀects of diﬀerent forest types and forestry activities on the phytophagous herbivores. There has been one report published on the subject of the diversity and conservation of Chrysomelidae (Greatorex-Davies and Sparks 1994). In this study, the diversity of leaf beetles and some other insects was investigated in the rides of woodlands, and it has been reported that both species richness and abundance of leaf beetles declined with increasing levels of shade, and that rides must be actively managed to keep light levels high if species richness and abundance are to be maintained. The purpose of this study was to compare the species richness and composition of Chrysomelidae, phytophagous herbivores, in larch plantations, secondary forests, and primary forests, and assess the eﬀects of forest practices, such as thinning and long rotations, on the diversity of this family in order to obtain information for conservation of leaf beetles in forest area.

Methods Study site This study was conducted in forests at altitudes ranging from 1390–1770 m (mean annual precipitation: ca. 1120 mm; mean annual temperature: ca. 9.9 C) [120]

1181 in the central mountainous region of Japan (Figure 1 of Ohsawa 2004). Three forest types in this area, i.e., larch plantations, secondary broad-leaved forest (secondary forest), and primary or near-primary broad-leaved forest (primary forest), were selected for the investigation. A total of 46 stands were chosen: 24 stands of larch plantations, aged 21–79 years; 11 stands of secondary forest, dominated by Q. crispula, with other broad-leaved trees such as Ilex macropoda Miq., Fraxinus sieboldiana Blume var. serrata Nakai, Betula platyphylla Sukatchev var. japonica (Miq.) Hara, Acer spp ., and Prunus spp.; and 11 stands of primary forest dominated by Q. crispula, but mixed with conifers such as Abies homolepis Sieb. et Zucc. and Tsuga diversifolia (Maxim.) Masters, with a high proportion of conifers in two of the stands. Larch plantations consisted of three types: 13 stands of middle-aged (21–45 years old), six stands of recently thinned (middle-aged, 1.5 and 2.5 years after thinning), and ﬁve stands of old (58– 79 years old) plantations. Survey of leaf beetles A Malaise trap was set in each of the 46 stands to capture insects, and leaf beetles were separated from among those trapped. To minimize forest edge eﬀects and micro-topographical diﬀerences within each stand, eﬀorts were made to set each trap in a typical spot for the stand on a simple slope (or in a ﬂat area if there was no slope) in the interior of the stand. Leaf beetles were captured in three 14-day periods: in middle to late June, in middle to late July, and in early to mid-August. Because of high elevation, June to August is an appropriate period for capturing many beetles including Chrysomelidae, according to the results of an investigation conducted on insects through spring to autumn in this area (Ohsawa unpublished data). Dry specimens were prepared for all species of leaf beetles trapped, and were kept in the Yamanashi Forest Research Institute. Environmental factors Environmental factors examined were altitude, gradient, larch plantation versus natural broad-leaved forest mostly dominated by Q. crispula, i.e., secondary forest and primary forest (larch plantation vs. natural broadleaved forest), openness of the canopy, the numbers of vascular plants (<2 m and 2 m in height), and age of larch plantations. In addition, for two chrysomelid species, Batophila acutangula Heikertinger and Sphaeroderma tarsatum Baly, commonly found in this area, the occurrence of their host plants was investigated as an environmental factor. For the openness of the canopy, a digital camera with a ﬁsh-eye converter (Nikon Cool Pix 950) was used to take a hemispherical photograph of the canopy from a height of 1 m above the ground at ﬁve locations. The openness of the canopy was [121]

1182 an average of ﬁve values calculated from the hemispherical photographs using HEMIPHOTO (ter Steege 1993). The number of vascular plant species was investigated in 11 stands. Vascular plants were divided into two groups by their height: the one shorter than 2 m and the other 2 m or more. Counted in the numbers of vascular plants were, for the ﬁrst group (<2 m), all species found in 40 plots (1 · 1 m), and for the second group (2 m), all species found in 40 plots (5 · 5 m) for each stand (Nagaike et al. 2003). Rubus spp. (Rubus mesogaeus Focke, R. koehneanus Focke, R. palmatus Thunb. var. coptophyllus A. Gray, and R. pungens Cambesse`des var. oldhamii [Miq.] Maxim.) and bamboo grass (Sasa nipponica Makino et Shibata and Sasamorpha borealis [Hack.] Nakai) were host plants of B. acutangula and S. tarsatum, respectively. In each 46 stand, the occurrences of Rubus spp. and bamboo grass were investigated in an area of 10 · 30 m including in the center a spot where a Malaise trap was set in. The occurrence of Rubus spp. in stands was ranked at four degrees (0: not found; 1: found in less than 10% of the area; 2: found in at least 10% and less than 25% of the area; and 3: found in at least 25%). The occurrence of bamboo grass was also ranked at four degrees (0: not found; 1: occupied less than 10% of the area; 2: occupied at least 10% and less than 25%; and 3: occupied at least 25%).

Statistical analyses One way ANOVA with Bonferroni’s post-hoc test (Bonferroni test) was conducted to compare the number of species, the number of individuals, and Shannon-Wiener diversity index (H¢, Magurran 1988) among the forest types. Logarithmic transformation was performed for the number of individuals before Bonferroni test. Simple regression analysis was conducted to identify the environmental factors that aﬀected the species richness of leaf beetles. The regression analysis was also applied to the relationship between the numbers of two chrysomelid species and occurrence of their host plants. Detrended correspondence analysis (DCA) was applied to compare the composition of leaf beetles in all investigated stands. The analysis was conducted with the software package, PC-ORD (McCune and Meﬀord 1999). Bonferroni test was applied to compare DCA scores (the ﬁrst and second axes) among forest types. To deﬁne the meaning of the ﬁrst two axes of DCA, simple correlation coeﬃcients were calculated between the two axes and stand-structure parameters, such as the number of species, the number of individuals, H¢, larch plantation vs. natural broad-leaved forest, altitude, gradient, openness of the canopy, the number of vascular plants (<2 m and 2 m in height, for 11 stands) and forest age (for larch plantations), Indicator species analysis (Dufreˆne and Legendre 1997) was carried out to compare species of Chrysomelidae among the forest types and to identify species associated with each forest type. [122]

1183 Results Number of species, individuals, and diversity index In this study, 1303 individuals of 41 species were captured. The species with the highest number of individuals captured was Aphthona perminuta Baly (635), followed by S. tarsatum (201), Exosoma akkoae (Chujo) (92), Zipangia lewisi (Jacoby) (54), Syneta adamsi Baly (51), B. acutangula (47), Cryptocephalus amiculus Baly (30), Stenoluperus nipponemsis (Laboissiere) (29), Pseudoliprus nigritus (Baly) (26), and Zeugophora annulata (Baly) (25). The average number of species, the average number of individuals, and the average H¢ in each forest type are shown in Table 1. The number of species and H¢ in the larch plantation was signiﬁcantly higher than those in the secondary forest or in the primary forest (Bonferroni test, p < 0.05). The number of individuals was not signiﬁcantly diﬀerent among three forest types. In the larch plantation, the number of species and that of individuals were signiﬁcantly higher in the old plantation than in the middle-aged plantation (Bonferroni test, p < 0.05, Table 2). H¢ was not signiﬁcantly diﬀerent among three types of larch plantations.

Environmental factors Among seven environmental factors, openness of the canopy, larch plantation vs. natural broad-leaved forest, age of larch plantation, and the number of plant species (<2 m in height) had a signiﬁcant regression coeﬃcient with the number of chrysomelid species (Table 3). The species caught in larch plantations were in higher numbers than in natural broad-leaved forests. Among larch plantations, older plantations had more chrysomelid species. Chrysomelid species were caught in higher number in stands with wider openness of the canopy and with more plant species (<2 m in height). Other factors such as gradient, altitude, and plant species (2 m in height) did not signiﬁcantly aﬀect the number of species.

Table 1. Numbers of chrysomelid species, numbers of individuals, and diversity index (H¢) in three forest types.

Larch plantation Secondary forest Primary forest

n

Number of species (Mean1) ± SD)

Number of individuals2) (Mean1) ± SD)

H¢ (Mean1) ± SD)

24 11 11

5.9a ± 2.1 3.6b ± 2.1 3.6b ± 2.1

28.6 ± 26.3 19.2 ± 30.5 36.8 ± 41.0

1.8a ± 0.5 1.2b ± 0.9 0.8b ± 0.8

1) For each comparison, diﬀerent alphabetical letters indicate mean with a signiﬁcant diﬀerence (Bonferroni test, p < 0.05). 2) Bonferroni test was performed after logarithmic transformation.

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1184 Table 2. Numbers of chrysomelid species, numbers of individuals and diversity index (H¢) in three types of larch plantations.

Middle aged plantation Recently thinned plantation Old plantation

n

Number of species (Mean1) ± SD)

Number of individuals2) (Mean 1) ± SD)

H¢ (Mean1) ± SD)

13 6 5

5.4a ± 2.1 5.2ab ± 1.3 8.0b ± 1.2

19.0a ± 13.8 21.8ab ± 10.4 61.8b ± 39.2

1.9 ± 0.6 1.9 ± 0.3 1.7 ± 0.7

1) For each comparison, diﬀerent alphabetical letters indicate mean with a signiﬁcant diﬀerence (Bonferroni test, p < 0.05). 2) Bonferroni test was performed after logarithmic transformation.

Signiﬁcant correlation coeﬃcients were obtained by calculation between the number of B. acutangula captured and the occurrence of Rubus spp., and between the number of S. tarsatum and the occurrence of bamboo grass (Table 4).

Species composition The results of detrended correspondence analysis are shown in Figure 1. The scores of the second axis were higher in the larch plantation than those in the secondary forest or in the primary forest (Bonferroni test, p < 0.05). There was no signiﬁcant diﬀerence between the scores in the secondary forest and those in the primary forest. A stand-structure parameter which possesses a signiﬁcant correlation with the ﬁrst axis was H¢, and that with the second axis was larch plantation vs. natural broad-leaved forest (Table 5). Correlations between the other stand-structure parameters and the two axes were not signiﬁcant. Table 3. Relationship between number of species and environmental factors (simple regression analysis). Environmental factors

Standardized partial regression coeﬃcient

Openness of the canopy Altitude Gradient Larch plantation vs. Natural broad-leaved forest Age of foresta Number of vascular plant species (<2 m in height)b Number of vascular plant species (2 m in height)b a

The analysis was applied for larch plantations. The analysis was applied for 11 stands. *p < 0.05; **p < 0.01. b

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0.39** 0.13 0.01 0.49** 0.50* 0.74** 0.13

1185

Figure 1. Detrended correspondence analysis ordination (ﬁrst and second axes) performed on leaf beetles in 46 stands in central Japan.

Indicator species analysis showed that E. akkoae, B. acutangula, and C. nobyi each had a signiﬁcant indicator value (Ind Val) for the larch plantation (Table 6). Longitarsus succineus (Foudras) and S. tarsatum showed a signiﬁcant Ind Val for the secondary forest and the primary forest, respectively. Among three types of larch plantation, A. perminuta, S. adamsi, and C. amiculus each had a signiﬁcant Ind Val for the old larch plantation, and E. akkoae had a signiﬁcant Ind Val for the recently thinned plantation (Table 7).

Discussion Species richness Species richness of leaf beetles in the larch plantation was signiﬁcantly higher than that in the secondary forest or in the primary forest. Nagaike (2002) Table 4. Simple correlation coeﬃcients for two chrysomelid speices between the number of individuals and occurrence of host plants. Host plants

Bamboo grass Rubus spp.

Correlation coeﬃcients S. tarsatum

B. acutangula

0.69** –a

– 0.33*

a Not analyzed. *p < 0.05; **p < 0.01.

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1186 Table 5. Simple correlaton coeﬃcients between scores of detrended corespondence analysis (ﬁrst two axes) and stand-structure parameters. Parameter

Axis 1

Number of leaf beetle species Number of leaf beetle individuals H¢ Larch plantation vs. Natural broad-leaved forest Openess of the canopy Altitude Gradient Number of vascular plant species (<2 m in height)a Number of vascular plant species (2 m in height)a Age of treeb

0.22 0.14 0.31* 0.07 0.12 0.06 0.06 0.50 0.15 0.02

Axis 2 0.25 0.06 0.28 0.53** 0.28 0.10 0.09 0.54 0.22 0.21

a

For 11 stands. For larch plantation. *p < 0.05; **p < 0.01. b

studied diversity of vascular plants in this area and reported that species richness was signiﬁcantly higher in larch plantations than in secondary forests. This result in higher species richness of vascular plants coincides with higher species richness of Chrysomelidae in the larch plantation than in the secondary forest. In this study, species richness of leaf beetles was higher in stands with higher species richness of understory plants (<2 m in height), though the relationship between species richness of leaf beetles and species richness of the plants (2 m) was not clear. Because leaf beetles feed on leaves, stems, or roots of various plants, and because host plants of the beetles vary with the beetle species, it seems that forests with more plant species enable chrysomelid species to inhabit in them in higher numbers. Among larch plantations, the old larch plantation had a higher species richness of leaf beetles than did the middle-aged plantation. This result corresponds with the result of regression analysis that the higher number of chrysomelid species was caught in older larch plantations. Species richness of vascular plants was higher in the old plantation than in the middle-aged plantation, though the diﬀerence was not signiﬁcant (Nagaike et al. 2003). They also found that plant species composition was diﬀerent between the middle-aged plantation and the old plantation. This diﬀerence may have resulted in a higher species richness of Chrysomelidae in the old plantation than in the middle-aged plantation. Further investigations will be necessary to clarify this point. Thinning did not cause signiﬁcant diﬀerence in species richness of leaf beetles, though the recently thinned plantation had wider openness of the canopy than the middle-aged plantation did (Bonferroni test, p < 0.01). S. tarsatum and B. acutangula had a signiﬁcant Ind Val for the primary forest and the larch plantation, respectively. However, more individuals of both beetles were found in stands with higher occurrences of host plants. For [126]

1187 both species, signiﬁcant correlations were ascertained by calculation between the number of the beetles and the occurrence of the host plants. This, therefore, seems to suggest that the numbers of both chrysomelid species are aﬀected by the occurrence of their host plants.

Table 6. Indicator value (Ind Val) of chrysomelid species for three forest types. Species

Ind Val

Forest type

Exosoma akkoae (Chujo) Batophila acutangula Heikertinger Sphaeroderma tarsatum Baly Calomicrus nobyi Chujo Aphthona perminuta Baly Zeugophora annulata (Baly) Pseudoliprus nigritus (Baly) Longitarsus succineus (Foudras) Stenoluperus nipponensis (Laboissiere) Syneta adamsi Baly Zipangia lewisi (Jacoby) Cryptocephalus amiculus Baly Oomorphoides cupreatus (Baly) Stenoluperus cyaneus (Baly) Stenoluperus bicarinatus (Weise) Sphaeroderma placidum Harold Basilepta balyi (Harold) Syneta brevitibialis Kimoto Hesperomorpha hirsuta (Jacoby) Cryptocephalus confusus Suﬀrian Chrysomelidae sp.1 Aspidomorpha indica Boheman Oomorphus japanus Jacoby Lochmaea capreae (Linnaeus) Agelasa nigriceps Motschulsky Calomicrus cyaneus (Jacoby) Cryptocephalus fortunatus Baly Asiorestia obscuritarsis (Motschulsky) Zeugophora unifasciata (Jacoby) Lilioceris lewisi (Jacoby) Pyrrhalta annulicornis (Baly) Zeugophora bicolor (Kraatz) Lema cirsicola Chujo Chaetocnema concinna (Marsham) Chaetocnema ingenua (Baly) Lipromela minutissima (Pic) Sphaeroderma nigricolle Jacoby Japonitata nigrita (Jacoby) Sangariola punctatostriata (Motschulsky) Taumacera tibialis (Jacoby) Chrysolina virgata (Motschulsky)

53.0* 47.7* 47.3* 45.8* 42.5 34.4* 29.2 25.7* 23.8 16.8 16.0 15.5 14.5 14.1 14.0 12.5 9.1 9.1 9.1 9.1 9.1 9.1 8.3 8.3 8.3 6.8 6.2 6.2 6.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2

Larch plantation Larch plantation Primary forest Larch plantation Primary forest Larch plantation Larch plantation Secondary forest Primary forest Primary forest Larch plantation Larch plantation Larch plantation Secondary forest Primary forest Larch plantation Secondary forest Secondary forest Secondary forest Secondary forest Primary forest Primary forest Larch plantation Larch plantation Larch plantation Secondary forest Primary forest Secondary forest Secondary forest Larch plantation Larch plantation Larch plantation Larch plantation Larch plantation Larch plantation Larch plantation Larch plantation Larch plantation Larch plantation Larch plantation Larch plantation

*p < 0.05. [127]

1188 Table 7. Indicator value (Ind Val) of chrysomelid species for larch plantation types. Species

Ind Val

Plantation type

A. perminuta S. adamsi E. akkoae C. amiculus S. tarsatum S. nipponensis Z. annulata B. acutangula P. nigritus C. nobyi P. annulicornis Z. bicolor C. fortunatus L. minutissima S. nigricolle J. nigrita S. punctatostriata L. succineus O. cupreatus Z. lewisi L. cirsicola C. concinna A. obscuritarsis S. bicarinatus C. cyaneus L. capreae A. nigriceps O. japanus S. cyaneus S. placidum C. ingenua L. lewisi T. tibialis Z. unifasciata C. virgata

71.5* 69.1* 67.3* 45.7* 38.2 36.2 31.6 24.3 23.3 23.1 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 18.1 16.7 16.7 16.7 15.4 15.4 14.4 14.4 11.3 11.3 9.3 7.7 7.7 7.7 7.7 7.7

Old plantation Old plantation Recently thinned plantation Old plantation Old plantation Old plantation Recently thinned plantation Recently thinned plantation Middle-aged plantation Recently thinned plantation Old plantation Old plantation Old plantation Old plantation Old plantation Old plantation Old plantation Old plantation Middle-aged plantation Old plantation Recently thinned plantation Recently thinned plantation Recently thinned plantation Middle-aged plantation Middle-aged plantation Old plantation Old plantation Old plantation Old plantation Old plantation Middle-aged plantation Middle-aged plantation Middle-aged plantation Middle-aged plantation Middle-aged plantation

*p < 0.05.

Species composition As the results of DCA showed that scores in the second axis was higher in the larch plantation than in the secondary forest or in the primary forest, the composition of Chrysomelidae in the larch plantation diﬀered from that in the secondary forest or in the primary forest. Six chrysomelid species had signiﬁcant Ind Vals in relation to the three forest types in this study. E. akkoae, B. acutangula, and C. nobyi each showed a signiﬁcant Ind Val for the larch plantation. B. acutangula and C. nobyi feed on Rubus spp. and Clematis apiifolia DC., respectively (Kimoto and Takizawa [128]

1189 1994). The host plants for E. akkoae are unknown. L. succineus having a signiﬁcant Ind Val for the secondary forest feeds on Artemisia spp. S. tarsatum had a signiﬁcant Ind Val for the primary forest and feeds on bamboo grass. It is interesting that host plants of these chrysomelid species having signiﬁcant Ind Vals for certain forest types in this study were not dominant tall trees, but understory herbs.

Comparison with a saproxylic family Cerambycid beetles, though closely related to Chrysomelidae, are mostly saproxylic in their larval stage. Cerambycidae had higher species richness in the secondary forest than in the larch plantation or in the primary forest (Ohsawa 2004). On the other hand, more species of Chrysomelidae inhabited in the larch plantation than in the secondary forest or in the primary forest. Among forest management practices for larch plantations, long-rotations brought about high species richness for Chrysomelidae, whereas thinning increased species richness for Cerambycidae (Ohsawa 2004). It seems that ecological diﬀerences between these families, i.e., saproxylic (Cerambycidae) and phytophagous herbivores (Chrysomelidae), can be attributed to the diﬀerence in species richness with these forest types and forest management practices. The amount of dead wood or decayed wood aﬀects the species richness of saproxylic beetles (Martikainen et al. 2000), and the secondary forest (unattended) has more amount and variety of dead or decayed wood than does the larch plantation (well managed) (Green and Peterken 1997; Kirby et al. 1998; Fridman and Walheim 2000). The recently thinned larch plantation contains more newly-made stumps and woody debris as compared with the middle-aged plantation. Consequently, there are more cerambycid species in the secondary forest and in the recently thinned larch plantation (Ohsawa 2004). On the other hand, the larch plantation had higher chrysomelid species richness than did the secondary forest or the primary forest, probably because leaf beetles are phytophagous herbivores and larch plantations have higher species richness of the plants. In this study, higher species richness of understory plants positively inﬂuenced the species richness of Chrysomelidae, and some understory plants were important hosts of leaf beetles characteristic to each forest type. More precise attention should be paid to understory plants for diversity conservation of leaf beetles, phytophagous herbivores, than for that of saproxylic beetles.

Conclusion The larch plantation had a higher species richness of Chrysomelidae than did other two natural forests. However, the composition of chrysomelid assemblage in the larch plantation was diﬀerent from that in the primary forest which is considered to have indigenous species in the area. Among the three types of [129]

1190 larch plantation, the species richness of Chrysomelidae was higher in the old plantation than in the middle-aged plantation. Long rotations of larch plantations seem favorable for chrysomelid diversity. No diﬀerence in chrysomelid species composition between the secondary forest and the primary forest could be detected by DCA. Since the primary forest which is thought to contain indigenous species has diminished and fragmented, the secondary forest is expected to maintain these leaf beetles. However, considering that the secondary forest contained only 43% (6/14 species) of species caught in the primary forest in this study, the forest type may not be suﬃcient to maintain the beetle assemblage in the primary forest. This study showed that species richness of understory plants is an important factor for chrysomelid species richness, and that the frequency of host occurrence signiﬁcantly aﬀects the number of individuals. Because forest types aﬀect plant diversity (Qian et al. 1997; Nagaike 2002; Nagaike et al. 2003), it is likely that both forest types and forest management practices aﬀect host plants as well as Chrysomelidae, and that these eﬀects on the host plants also inﬂuence chrysomelid assemblages.

Acknowledgements We wish to thank Mr. Akihiro Ohashi, Gifu Forest Science Institute, and Dr. Masahiro Isono, Forestry and Forest Products Research Institute, Japan, for identifying several leaf beetles and helpful advice. We are also grateful to Mr. Masao Osawa for correction of English for the manuscript and helpful advice. We deeply appreciate technical assistance given me by Mrs Miki Saso, and the helpful advice and encouragement by members of Yamanashi Forest Research Institute.

References Dufreˆne M. and Legendre P. 1997. Species assemblages and indicator species: the need for a ﬂexible asymmetrical approach. Ecol. Monogr. 67: 345–366. Fridman J. and Walheim M. 2000. Amount, structure, and dynamics of dead wood on managed forestland in Sweden. Forest Ecol. Manage. 131: 23–36. Greatorex-Davies J.N. and Sparks T.H. 1994. The response of Heteroptera and Coleoptera species to shade and aspect in rides of coniferised lowland woods in Southern England. Biol. Conserv. 67: 255–273. Green P. and Peterken G.F. 1997. Variation in the amount of dead wood in the woodlands of the Lower Wye Valley, UK in relation to the intensity of management. Forest Ecol. Manage. 98: 229–238. Kimoto S. and Takizawa H. 1994. Leaf Beetles (Chrysomelidae) of Japan. Tokai University Press, Tokyo. Kirby K.J., Reid C.M., Thomas R.C. and Goldsmith F.B. 1998. Preliminary estimates of fallen dead wood and standing dead trees in managed and unmanaged forests in Britain. J. Appl. Ecol. 35: 148–155. [130]

1191 Magurran A.E. 1988. Ecological Diversity and its Measurement. Princeton University Press, Princeton, NJ. Martikainen P., Siitonen J., Punttila P., Kaila L. and Rauh J. 2000. Species richness of Coleoptera in mature managed and old-growth boreal forests in southern Finland. Biol. Conserv. 94: 199–209. McCune B. and Meﬀord M.J. 1999. PC-ORD. Multivariate Analysis of Ecological data, version 4. MjM Software Design, Gleneden Beach, Oregon. Nagaike T. 2002. Diﬀerences in plant species diversity between conifer (Larix kaempferi) plantations and broad-leaved (Quercus crispula) secondary forests in central Japan. Forest Ecol. Manage. 168: 111–123. Nagaike T., Hayashi A., Abe M. and Arai N. 2003. Diﬀerences in plant species diversity in Larix kaempferi plantations of diﬀerent ages in central Japan. Forest Ecol. Manage. 183: 177–193. Ohsawa M. 2004. Species richness of Cerambycidae in larch plantations and natural broad-leaved forests of the central mountainous region of Japan. Forest Ecol. Manage. 189: 375–385. Qian H., Klinka K. and Sivak B. 1997. Diversity of the understory vascular vegetation in 40 year-old and old-growth forest stands on Vancouver Island, British Columbia. J. Veg. Sci. 8: 773–780. ter Steege H. 1993. HEMIPHOTO, A Programme to Analyze Vegetation Indices, Light Quality from Hemispherical Photographs. The Tropebos Foundation, Wageningen.

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Biodiversity and Conservation (2006) 15:1193–1217 DOI 10.1007/s10531-004-8230-8

Springer 2006

-1

The banana forests of Kilimanjaro: biodiversity and conservation of the Chagga homegardens ANDREAS HEMP Department of Plant Physiology, Universita¨t Bayreuth, Universita¨tsstr. 30, 95440 Bayreuth (e-mail: [email protected]; phone: 0921-552630; fax: 0921-552642) Received 18 May 2004; accepted in revised form 7 December 2004

Key words: Agroforestry, Apophytes, Coﬀee–banana planations, East Africa, Epiphytes, Kilimanjaro, Neophytes, Ruderal vegetation, Tropical montane forest Abstract. Natural ﬂora, vegetation, diversity and structure of 62 traditional coﬀee–banana plantations on Kilimanjaro were investigated and compared with the other vegetation formations on this volcano on basis of over 1400 plots following the method of Braun-Blanquet. The vegetation of the so-called Chagga homegardens belongs ﬂoristically to the formation of ruderal vegetation forming two main communities that are determined by altitude. These coﬀee–banana plantations maintain a high biodiversity with about 520 vascular plant species including over 400 non-cultivated plants. Most species (194) occurring in the Chagga homegardens are forest species, followed by 128 ruderal species, including 41 neophytes. Typical of the agroforestry system of the Chagga homegardens is their multilayered vegetation structure similar to a tropical montane forest with trees, shrubs, lianas, epiphytes and herbs. Beside relicts of the former forest cover, which lost most of their former habitats, there are on the other hand (apophytic) forest species, which were directly or indirectly favoured by the land use of the Chagga people. High demand of wood, the introduction of coﬀee varieties that are sun-tolerant and low coﬀee prizes on the world marked endanger this eﬀective and sustainable system.

Introduction Humans have continuously inhabitated the slopes of Mt. Kilimanjaro for the last 2000 years (Schmidt 1989). However, during the last decades the human population increased dramatically. According to ethnographic studies of Widenmann (1899) 50,000–60,000 Chagga people were estimated to live on Mt. Kilimanjaro in 1895. In 2002 the census counted 1,053,204 people (National Bureau of Statistics 2003). As such, the population has multiplied 20 times since 1895. Most of the population is concentrated at an altitude between 1000 and 1800 m, with densities varying from 500 to 1000 people per km2 in some areas (FAO 1986; Timberlake 1986). Here, within the submontane zone, a very remarkable kind of land use prevails: dense ‘banana forests’ with a scattered upper tree layer, the so-called Chagga homegardens, in Chagga language ‘vihamba’ (the term ‘homegarden’ refers to the small size and subsistence-level of the farms, cp. Nair 1993). Due to this sustainable and well developed agroforestry system (cp. e.g. Fernandes et al. 1984) degradation in this vegetation belt is rare, despite the enormous population. In their homegardens the [133]

1194 Chagga use four vegetation layers. Under a tree layer, which provides ﬁrewood, fodder and shadow, banana trees (in about 25 varieties, cp. Simmonds 1966) are grown and under the bananas coﬀee trees, and under these vegetables. This multilayer system maximizes the use of limited land. The area is irrigated by a network of canals fed by main furrows originating from the montane forest. Rough estimates give over one thousand furrows of varying lengths and capacities (Ramsay 1965) some dating back to the 17th century (Hemp and Winter 1999). This farming system evolved over several centuries and did not change much over the last decades compared with the land uses in the lower zones. This densely populated coﬀee–banana belt stretches on the climatically most favourable zone of the southern and south-eastern slopes (Figure 1) over an area of 1000 km2. The Chagga live within their homegardens in single dwellings; villages as such do not exist. But, along the main roads centres with church, village council, schools and some shops are situated. The average size of a homegarden varies between 0.5 and 1.7 ha (O’Kting’ati and Kessy 1991; Mdoe and Wiggins 1997). Livestock – cattle, goats, sheep and pigs – and sometimes poultry are kept in stalls. Women and children spend a great part of the day collecting grass along paths, ﬁelds and forest edges and on steep meadow slopes. Pasture farming is rare in submontane zone due to intensive agriculture. Therefore (based on the nature of their components) the Chagga homegardens can be classiﬁed as an agrisilvicultural system (cp. Nair 1993). Bee-keeping plays an important role. The chagga homegardens were the subject of diﬀerent studies dealing mainly with socio-economic (Clemm 1963; Brewin 1965; Fernandes et al. 1984; O’Kting’ati and Kessy 1991; Mdoe and Wiggins 1997) or ethnobotanical and ethnozoological aspects (O’Kting’ati et al. 1984; Hemp 1999; Hemp 2001). The array of cultivated species was already described in detail by the ﬁrst scientists on Kilimanjaro e.g. Volkens (1897) or Widenmann (1899). The aim of the present study is to describe natural ﬂora, vegetation and structure of the Chagga homegardens and to highlight their function for biodiversity and as a refuge area for natural plant species. For this purpose the species composition of this man-made habitat is compared with all vegetation formations of Mt. Kilimanjaro as presented by Hemp (2001a). In a parallel study the function of the Chagga homegardens as a habitat of endangered and endemic grasshopper species was investigated on the same plots (Hemp in press).

Study area Mt. Kilimanjaro, a relic of an ancient volcano, rising from the savanna plains at 700 m elevation to a snow-clad summit of 5895 m altitude is located 300 km south of the equator in Tanzania on the border with Kenya. Its climate is characterized by a bimodal rainfall pattern with the long rains from March to May forming the main rainy season, and the short rains centred around the [134]

1195

Figure 1. Land use and vegetation cover of the study area with location of plots (dots).

month of November of the small rainy season. The foothills of the southern slopes receive an annual rainfall of 800–900 mm and the lower slopes at 1500 m receive 1500–2000 mm. The forest belt between 2000 and 2300 m receives partly over 3000 mm (Hemp 2001a), which is more than on other high mountains of East Africa. In the alpine zone the precipitation decreases to 200 mm. According to the diﬀerent climatic conditions several vegetation zones are apparent on the southern slopes of Mt. Kilimanjaro (Figure 1). Between 700 and 1000 m a.s.l. the dry and hot colline savanna zone stretches around the mountain base, where most areas are farmed with maize, beans and sunﬂowers, in West Kilimanjaro with wheat. Around Lake Chala at the eastern foot of the mountain, and around Ngare Nairobi of West Kilimanjaro, savanna grasslands are still intact. The main cultivation zone with its coﬀee–banana plantations, the actual study area, is located between 1000 and 1800 m. Natural forests cover an area of about 1000 km2 on Mt. Kilimanjaro. In the lower parts of the southern slope the montane forests are characterized by the tree Ocotea usambarensis and higher up in the cloud forest zone by Podocarpus latifolius, Hagenia abyssinica and Erica excelsa. On the drier northern slope the vegetation zonation starts with Croton-Calodendrum forests, Cassipourea forests at midaltitudes and Juniperus forests at higher altitudes. At around 3100 m the forests are replaced by Erica bush. At an altitude of about 3900 m the Erica heathlands grade into Helichrysum cushion vegetation that reaches up to 4500 m. Higher altitudes are very poor in vegetation while the highest [135]

1196 elevations of Kibo peak are covered with glaciers. For a more detailed description of these vegetation types see Hemp (2001a). Methods Data have been collected since 1996. Over 1400 releve´s (plots) of all vegetation types were produced on the whole mountain using the method of Braun-Blanquet (1964), 62 of them representing banana gardens (location see in Figure 1). Special attention was given to homogeneity and representation of the stands. The releve´ size was chosen with respect to the minimum area, which was 1000 m2 in the banana gardens. In the releve´s a herb layer (<1 m tall), a shrub layer (1–10 m tall) and a tree layer (>10 m tall) were diﬀerentiated. Climbers (stranglers, scramblers, tendrillar plants, hook and root climbers and twiners, cp. Lind and Morrison 1974) reaching into the shrub and tree layer were deﬁned as lianas. Epiphytes (accidental, casual, hemi- and holo-epiphytes, cp. Kress 1986) were treated as an additional layer. To portray the structure of the banana gardens, a standproﬁle diagram according to Hammen et al. (1989) was produced. The releve´s were clustered according to ﬂoristic similarity and the resulting plant communities were united into nine formations: rocks; ruderal vegetation; vegetation of trampled grounds; grasslands; salt marshes; freshwater swamps; forest clearings; forests, and; heathlands. Constancy tables of these formations (except the vegetation of trampled ground) are presented by Hemp (2001a). Based on their constancy in the diﬀerent formations (or vegetation classes) character species of these formations were determined. pH was measured in the main root horizon in 5–10 cm depth of selected plots using a WTW pH-metre (pH 330). Two parallel samples were taken and measured in distilled water and 0.01 M CaCl2 solution, respectively. Nomenclature follows FTEA (1952–2003) and (Beentje 1994). Results Based on Landsat ETM images from the year 2000 (source: USGS/UNEPGRID-Sioux Falls) extend and distribution of the Chagga homegardens on Kilimanjaro was determined. Excluding other vegetation types of the submontane cultivated zone (e.g. riverine forests, meadows, maize ﬁelds etc.) banana ﬁelds cover an area of about 675 km2, which is about two thirds of the extend of the montane forest belt. Phytosociological and ecological aspects The vegetation of the Chagga homegardens belongs ﬂoristically to the formation (or vegetation class) of ruderal vegetation (Table 1, cp. Table 1 in [136]

Table 1. Vegetation of the Chagga homegardens.

[137]

1197

1198

Table 1. Continued.

[138]

[139]

1199

1200 Hemp 2001a). Ruderal species form in respect of species number and vegetation cover of the herb layer the most important ecological group. Widespread ruderal species (character species of the vegetation class) that can be found as well on fallow arable land, waste places in towns and roadsides from the colline savanna area up to the montane zone are e.g. Bidens pilosa, Oxalis corniculata, Commelina benghalensis and Galinsoga parviﬂora. Phyllanthus odontadenius, Didymodoxa caﬀra and Celosia schweinfurthiana occur in diﬀerent ruderal vegetation types within the submontane zone. Finally, a characteristic weed species conﬁned to the banana gardens on Kilimanjaro is Oxalis latifolia. Based on the ﬂoristic composition, two distinct plant communities were distinguished. Diagnostic species of community 1 are the ruderal species Euphorbia heterophylla, Amaranthus hybridus, Sida acuta, Blainvillea gayana and Malvastrum coromandelianum. Impatiens walleriana, Drymaria cordata and Plectranthus parvus are diagnostic for community 2; the latter species is restricted in the study area to this community. Each of these two main communities can be divided into a vicarious vegetation unit of the southern and the (north-) eastern slope, respectively, governed by the rainfall regime. This partition into a wet southern and drier northern slope is also reﬂected by other vegetation formations such as forests (cp. Hemp in press a). Determining factors for the diﬀerentiation of the two main communities 1 and 2 are altitude and factors related to altitude: community 1b of the southern slope occurs between 800 m and about 1300 m, receiving 900–1580 mm rainfall, and community 2b between 1300 and 1800 m, receiving 1580–2200 mm rainfall. Mean annual temperature varies between 23.4 and 18.8 C in community 1b and between 18.8 and 16.1 C in community 2b (climate data from Hemp in press a). As a result of the increasing precipitation mean pH-values decrease from 6.4 (CaCl2) and 6.7 (H2O), respectively in community 1b to 5.5 (CaCl2) and 6.0 (H2O), respectively in community 2b. As in the forests of Kilimanjaro (Hemp in press a, b) the inﬂuence of precipitation is reﬂected by the distribution of epiphytes and pteridophytes. Vascular epiphytes are nearly missing in community 1b and start above 1300 m in community 2b. The same holds for pteridophytes. Mean cover values of epiphytes (including mosses and lichens) in both communities are 0 and 8%, respectively. On the drier eastern slope the lowland community 1a occurs between 1100 and about 1500 m, and community 2b is less distinctly developed than on the wetter southern slope, occurring only in a narrow strip above 1500 m. Such a rising and condensation of vegetation zones due to the ‘Massenerhebungseﬀekt’ was also observed in the forest vegetation on the dryer leeward slope of Kilimanjaro (Hemp in press a).

Diversity Five hundred and twenty-three vascular plant species were recorded in the releve´s. These are about three quarter of the species occurring in the ruderal [140]

1201

Figure 2. Vascular plant species richness in the main vegetation formations (as presented with constancy tables by Hemp 2001a) of Mt. Kilimanjaro, based on the evaluation of about 1400 vegetation plots.

vegetation formation on Kilimanjaro (Figure 2). With over 700 species this formation holds rank three in respect of species richness after the forests and grasslands. Mean vascular plant species number per plot is 54. Figure 3 shows the ﬂoristic composition of the banana ﬁelds in relation to the diﬀerent vegetation formations on Kilimanjaro. Most species (194) occurring in the Chagga homegardens are forest species, followed by 128 ruderal species. Cultivated plants contribute 19% to this ﬂoristic spectrum with 99 species. A characteristic feature of the ruderal vegetation on Kilimanjaro is the high contribution of neophytes. In the Chagga homegardens nearly a quarter of the species is introduced, with 99 cultivated species and 41 neophytes (Figure 4, Table 2).

Vegetation structure Figure 5 shows a vegetation proﬁle of a Chagga homegarden in the area of Kidia (Old Moshi). Typical of the agrisilvicultural system of the Chagga homegardens is their multilayered vegetation structure similar to a tropical montane forest. Therefore the growth form spectrum (Figure 6) displays beside herbs also trees, shrubs, lianas and epiphytes. Apart from some cultivated fruit trees, e.g. Persea americana, Mangifera indica and Syzygium cumini or introduced timber trees such as Grewillea robusta and Cupressus lusitanica, most of the 55 encountered tree species (including young trees of the shrub and herb [141]

1202

Figure 3. Floristic composition of the banana ﬁelds in respect of the diﬀerent vegetation formations on Kilimanjaro.

Figure 4. Share of cultivated, neophytic and indigenous plants in the Chagga homegardens.

layer this number adds to 82) are remnants of the former forest cover (Table 3). Most widespread are Albizia schimperiana, Rauvolﬁa caﬀra, Cordia africana, Commiphora eminii and Margaritaria discoidea. Nearly all banana ﬁelds are [142]

1203 Table 2. Neophytes of the Chagga home gardens. Name

Frequency

Ageratrum conyzoides Oxalis corniculata Galinsoga parviﬂora Oxalis latifolia Euphorbia heterophylla Conyza sumatrensis Amaranthus hybridus ssp. hybridus Tagetes minuta Galinsoga quadriradiata Solanum nigrum Richardia scabra Nicandra physalodes Lantana camara Tridax procumbens Adiantum raddianum Euphorbia hirta Bryophyllum pinnatum Lepidium bonariense Senna occidentalis Stachytarpheta jamaicensis Galium aparine Ipomoea hederifolia Lagascea mollis Lantana camara Sonchus oleraceus Acanthospermum hispidum Senna bicapsularis Apium leptophyllum Argemone mexicana Caesalpinia decapetala Chenopodium ambrosioides Tradescantia zebrina Acmella oleracea Brassica juncea Crambe hispanica Datura stramonium Ipomoea nil Sambucus nigra Senna septentrionalis Solanum seaforthianum Spermacoce assurgens

57 45 39 38 33 32 31 22 20 20 14 12 8 8 7 7 5 5 5 5 4 4 4 4 4 3 3 2 2 2 2 2 1 1 1 1 1 1 1 1 1

covered by at least some trees (Figure 7); mean coverage of the tree layer is 28%, mean species number 4.5. Twenty-nine species were found growing epiphytically in the plots (Table 4). Twenty-two were holo-epiphytes, mainly restricted in their occurrence to the epiphyte layer of the forests on Kilimanjaro (cp. Hemp 2001b). Most wide[143]

1204

Figure 5. Proﬁle (27 · 2.5 m) and ground plan (27 · 5 m; bold lines indicate the area used for the proﬁle) of a typical Chagga homegarden in Kidia (Old Moshi) at 1400 m a.s.l. Exposition: south west, inclination: 25. An open light upper canopy is formed by Albizia schimperiana var. amaniensis, on which epiphytes such as the fern Drynaria volkensii and Telphairia pedata, a liana with oilcontaining seeds, ﬁnd habitats. Bananas form a dense upper shrub layer of 4–6 m height, coﬀee trees a lower shrub layer of 1.5–2 m, intermingled with 1–1.5 m high Coco Yam (Colocasia esculenta). The lower side of the banana ﬁeld borders a road; here Dracaena fragans is planted as a hedge.

spread epiphytes are the petridophytes Pleopeltis macrocarpa (growing quite often on coﬀee trees), Asplenium aethiopicum, A. theciferum, Lepisorus excavatus and Drynaria volkensii. Vascular epiphytes start to appear above 1300 m in community 2 (see above). Forty-one climbers reaching into the shrub and tree layer were found in the plots (Table 5). Including young climbers found in the herb layer this number adds to 52 species. Eleven species were cultivated plants with important

[144]

1205

Figure 6. Growth form spectrum of the Chagga homegardens; (a) species number of the respective stratum in the vegetation plots; (b) species number of all representatives of a growth form, e.g. of trees including young trees occurring in the shrub and herb layer or e.g. of herbs excluding young trees etc.

agricultural crop plants such as three Dioscorea and Passiﬂora species and the Cucurbitaceae Telphairia pedata belonging to this growth form. One hundred twenty-six species were encountered in the shrub layer of the plots. Excluding young trees, 63 species remain (Table 6). Similar to the trees, epiphytes and lianas most of the shrubs in the Chagga homegardens were forest species. However, in the shrub layer the most important cultivated plants occurred: Diﬀerent varieties of Musa · sapientium (dessert bananas) and M. · paradisiaca (cooking bananas) and Coﬀea arabica. Bananas form a dense (mean cover value 50%) upper shrub layer of about 4–6 m height and coﬀee trees a lower layer of 1.5–2 m. Already Volkens (1897) and Widenmann (1899) reported that the bananas on Kilimanjaro are most luxuriant with heights of 6– 8 m in the area of Kibosho and Kilema. This may be due to the fact that the bedrocks in these areas of the wet central southern slope consist of rhomb porphyry instead of porous tuﬀ and ashes as in the adjacent regions of the southern slope (Downie and Wilkinson 1972) and that the eastern slope receives less precipitation. Four hundred nine species were found in the herb layer of the homegardens. Excluding young trees, shrubs and lianas 304 herbs and grasses occurred in the plots. In contrast to the other strata the main species group of the herb layer consisted of representatives of ruderal vegetation. This is shown in Figure 8. In this ﬁgure species of grasslands and wet habitats are lumped together into ‘semi-natural’ species, as such habitats are mostly inﬂuenced by cutting and grazing of cattle. It appears that the tree and epiphyte layer are the most [145]

1206 Table 3. Trees of the Chagga home gardens. Name

Frequency t

Grevillea robusta Albizia schimperiana Persea americana Rauvolﬁa caﬀra Cordia africana Mangifera indica Commiphora eminii ssp. zimmermannii Margaritaria discoidea Markhamia lutea Bridelia micrantha (Citrus aurantium) Croton macrostachyus Albizia petersiana Alangium chinense Ficus sur Casearia battiscombei Ficus thoningii Jacaranga mimosiaefolia Milicia excelsa Syzygium cumini Turraea robusta Albizia gummifera (Annona muricata) Annona reticulata Artocarpus heterophyllus (Azaridachta indica) (Cassia siamea) Cassia spectabilis (Citrus limon) Cupressus lusitanica Cussonia holstii Eriobotrya japonica Ficus vallis-choudae Olea capensis ssp. welwitschii Trema orientalis Croton megalocarpus (Deinbollia kilimandscharica) Ficus lutea Prunus africana Trichilia emetica (Allophylus abyssinicus) (Bersama abyssinica) (Bombacopsis glabra) Ceiba pentandra Celtis africana (Celtis mildbraedii) Cinnamomum verum (Citrus paradisi) Citrus sinensis

f

f

f

t f

f f f x o o f t f

x

x f f

[146]

37 36 21 18 14 13 11 9 8 7 7 7 6 5 5 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 1 1 1 1 1 1 1 1 1

1207 Table 3. Continued. Name

Frequency

(Clausena anisata) Cordia goetzei Diospyros abyssinica (Ehretia cymosa) Ekebergia capensis Erythrina abyssinica Eucalyptus spec. (Euclea divinorum) Ficus exasperata Kaya anthotheca Lecaniodiscus fraxinifolius ((Lepidotrichilia volkensii)) (Macaranga capensis) (Maesopsis eminii) Manihot glaziovii (Maytenus undata) Melia azedarach (Mystroxylon aethiopicum) (Neoboutonia macrocalyx) ((Ochna holstii)) (Olea europaea ssp. africana) Phoenix reclinata (Polyscias fulva) Psidium guajava Rapanea melanophloeos ((Sorindeia madagascariensis)) Synadenium cf. volkensii Syzygium cordatum Syzygium guineense (Tabernaemontana stapﬁana) (Tabernaemontana ventricosa) Teclea nobilis (Vepris spec.)

t

t

t x x

f

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

f = fruit tree; o = ornamental tree; t = timber tree; x = introduced tree of other uses; no label: indigenous tree; in brackets = only found in the shrub layer; in two brackets = only found as young tree in the herb layer.

natural vegetation strata in the Chagga homegardens whereas the herb layer is dominated by (128) ruderal species followed by 117 forest species and 64 cultivated plants. Plants of the semi-natural grasslands and wet habitats contributed 51 and 15 species, respectively. Discussion The presented distinction of two main communities is conﬁrmed by the composition of Saltatoria species of the banana gardens, which show a parallel [147]

1208

Figure 7. Typical Chagga homegarden in Kidia (Old Moshi) with an open tree canopy and a dense banana undergrowth.

distinction of two coenoses (Hemp, C. unpub. data). The congruence of vegetation communities and Saltatoria coenoses was already proofed on Kilimanjaro by grassland communities (Hemp and Hemp 2003). The Chagga homegardens maintain a high biodiversity with over 400 not cultivated plants. However, their majority serves as forage, for household and agricultural purposes, for medical applications, as drugs and for magic purposes (Hemp 1999). Most areas of the submontane coﬀee–banana belt resemble a woodland with a dense undergrowth of bananas (Figures 5 and 7). Thus, 193 forest species were found in the studied plots, species that need a forest-like habitat structure for surviving. These are about 17% of the 1155 forest plants of Kilimanjaro (30% of the forest trees – including young trees 45%—and 17% of the forest epiphytes, cp. Hemp in press a). Compared with large scale coﬀee plantations this conserving function becomes evident: Four surveyed commercial plantations harboured only 6 forest species, and three quarter of the species were widespread ruderal or cultivated species (Hemp unpub. data). This holds not only for plants but also for insects such as Saltatoria. The Chagga homegardens serve as a refuge not only for forest grasshoppers, which contribute the majority of the species but also for endemics (Hemp in press). These ﬁndings are in line with the fact that biodiversity in general on Kilimanjaro culminates at 1000–1300 m with over 900 vascular plant species (Hemp in press c) inside the coﬀee–banana belt, the most densely populated region of the mountain. This is due to the high variety of (moderately) cultivated areas (the Chagga homegardens), forest patches, river gorges and grasslands at this altitude. This (mostly man-made) variety of habitats, the high [148]

1209 Table 4. Epiphytes of the Chagga home gardens. Name

Frequency

Pleopeltis macrocarpa Asplenium aethiopicum Asplenium theciferum Lepisorus excavatus Drynaria volkensiii Peperomia tetraphylla Drynaria volkensii Rhipsalis baccifera Impatiens walleriana Phragmanthera usuiensis Loxogramme abyssinica Polystachia simplex Erianthemum dregei Loranthaceae spec. Plicosepalus curviﬂorus Rangaeris amaniensis (Achyranthes aspera) Aerangis amaniensis Asplenium megalura Asplenium sandersonii Asplenium strangeanum Chamaeangis sarcophylla (Didymodoxa caﬀra) (Dorstenia zansibarica) (Drymaria cordata) Ficus thoningii (Pilea tetraphylla) (Poa schimperana) (Setaria homonyma)

28 21 12 8 7 6 5 5 4 4 3 3 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1

in brackets: accidental epiphytes

beta-diversity, promotes alpha-diversity, allowing species from lower altitudes to climb up the mountain. A similar phenomenon was observed in the Saltatoria fauna of Kilimanjaro (Hemp and Hemp 2003). From the forest species found in the banana gardens it can be assumed that the forest, which covered the lower slopes of Kilimanjaro before human settlement, resembled in some aspects the Cassipourea forests of the western and northern slopes (cp. vegetation table in Hemp 2001a). However, due to the much higher precipitation on the southern slope, major diﬀerences to these forests can be expected; and above 1500 m probably elements of the camphor forests constituted to their ﬂoristic composition. As nearly all of these former submontane forests disappeared, it is diﬃcult to reconstruct their full ﬂoristic composition. Since humans have continuously inhabitated the lower slopes of Mt. Kilimanjaro at least for the last 2000 years (Schmidt 1989), it can be assumed that many submontane forest species were extinguished together with [149]

1210 Table 5. Lianas of the Chagga home gardens. Name

Frequency

Dioscorea lecardii (Glycine wightii) Dioscorea bulbifera Passiﬂora edulis Telphairia pedata Passiﬂora laurifolia Zehneria scabra Toddalia asiatica Ficus thoningii Smilax anceps Dioscorea alata Passiﬂora quadrangularis Solanecio angulatus Thunbergia alata Vigna spec. Cyphostemma masukuense ssp-masukuense Cyphomandra betacea Clerodendron johnstonii Basella alba Caesalpinia decapetala Cissus oliveri Cyphostemma kilimandscharicum Diplocyclos schliebenii (Ipomoea obscura) Momordica foetida Pentarrhinum insipidum (Stephania abyssinica) (Teramnus labialis ssp. labialis) Vigna membranacea (Adenia gummifera) Adenia spec. (Begonia meyeri-johannis) Clematis brachiata Dahlbegia lactea (Diplocyclos palmatus) Embelia schimperi Helinus mystacinus Ipomoea hederifolia Ipomoea indica Ipomoea nil Landolphia buchananii (Merremia palmata) (Merremia spec.) Mondia whytei Monstera spec. Oreosyce africana Paullinia pinnata Piper nigrum (Rourea thomsonii) Rubus rosifolius Sechium edule Solanum seaforthianum c = cultivated; in brackets = only found in the herb layer.

[150]

c c c c c

c c

c

c

c c

21 13 12 8 7 6 6 5 5 4 4 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1211 Table 6. Shrubs of the Chagga home gardens. Name

Frequency

Musa Sapientium / M. X paradisiaca Coﬀea arabica Dracaena fragrans Manihot esculenta Carica papaya Ricinus communis Cyphomandra betacea Dracaena steudneri Morus alba Prunus persica Capsicum fruticosum Adhatoda engleriana Lantana camara Cajanus cajan Cestrum nocturnum Synadenium compactum Tetradenia riparia Colocasia esculenta Euphorbia pulcherrima Ochna insculpta Aloe volkensii Datura suaveolens Elettaria cardamomum Keetia gueinzii Rubus pinnatus Senna bicapsularis Solanum spec. Bauhinia tomentosa Capsicum cf. baccatum Dracaena steudneri Ensete edule Flacourtia indica Leucas grandis Phyllanthus ovalifolius Thevetia peruviana Allophylus rubifolius Arundinaria alpina Bougainvillea spec. (Cyathea manniana) Dombeya rotundifolia Euclea racemosa Grewia bicolor Hibiscus calyphyllus Jatropha curcas Lonchocarpus eriocalyx Mirabilis spec. Oxyanthus speciosus ssp. globosus Psychotria lauracea Punica granatum Rhus vulgaris

62 57 29 21 18 14 13 11 11 10 9 2 8 6 6 5 5 4 4 4 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

i

i

i i

i i

i i

i i i i i i i

i i i i i i i i

[151]

1212 Table 6. Continued. Name

Frequency i

Rubus rosifolius Sambucus nigra Senna septentrionalis Senna spec. (Sesbania sesban) Solanecio cydonifolius Solanecio mannii Sterculia cf. stenocarpa Tephrosia vogelii Vernonia lasiopus Vernonia myriantha Ximenia americana var. caﬀra Ziziphus mucronata

i i i i i i i i

1 1 1 1 1 1 1 1 1 1 1 1 1

i = indigenous species; in brackets = only found as young shrub in the herb layer.

Figure 8. Forest species, semi-natural species (i.e. species of grasslands and wet habitats), cultivated and ruderal species (including species of trampled ground) with their share in the diﬀerent strata of the Chagga homegardens.

the forest cover. Only in deep inaccessible gorges remnants of ﬂoristically very rich forests can be found, resembling the intermediate forests of the Eastern Arc. Mts. (a chain of ancient crystalline mountains in East Africa), e.g. of the Pare and Usambara Mts. Here many species, which were believed to be endemic to the Eastern Arc. Mts, were encountered on Kilimanjaro (Hemp 2002). These ﬁndings suggest a rich forest ﬂora inhabiting the southern slopes of Mt. Kilimanjaro in former times. Thus, the lower diversity of the forest ﬂora and [152]

1213

Figure 9. Records of Christella dentata on Mt. Kilimanjaro, at the base of the UTM grid. The scale of the squares is 4 km2. This apophytic fern, which thrives naturally in riverine forests was able to spread over the whole submontane banana plantation belt due to the network of over one thousand furrows. Gaps within the distribution area inside the banana plantations (especially in its eastern part) are mostly due to lack of data.

the lower share of endemic plant species of Kilimanjaro can be explained by the widely destroyed submontane (intermediate) forest rather than by the higher age and greater ecoclimatic stability of the Eastern Arc. Mts. as suggested by e.g. Rodgers and Homewood (1982) or Fjeldsa˚ et al. (1997). This is corroborated by the fact, that forest inhabitants, which become less aﬀected by forest devastation like Saltatoria, have similar numbers of endemic forest species in the submontane and montane zone on Mt. Kilimanjaro (including Mt. Meru) and the East Usambara Mts. (Hemp, C. unpub. data). Endemic grasshopper species like Ixalidium sjo¨stedti, Parepistaurus deses and Altiusambilla modicicrus have coped with the habitat change from forest to plantations (Hemp and Hemp 2003). On the other hand there are forest species, which were directly or indirectly favoured by the Chagga people. An example of an intentionally dispersed forest plant is Dracaena fragrans. This shrub or small tree has lost almost all natural habitats on Kilimanjaro, except very few submontane river gorges (cp. Hemp in press a). However it is one of the most characteristic species in the banana plantations, where it is used as a hedge plant (cp. Figure 5). Dracaena [153]

1214 hedges are protected as they serve also as burial ground. Anthropogenic inﬂuence does not only destroy natural habitats but sometimes it enlarges the distribution of indigenous species by increasing habitat diversity. An example of such apophytes sensu Rikli (1903) (i.e. indigenous species, which could extend their natural distribution area due to human inﬂuence and occupy anthropogenic habitats; for examples in the middle European ﬂora cp. e.g. Sukopp and Kowarik 1987; Sukopp and Langer 1996) is the fern Christella dentata, a species of riverine forests in the colline and submontane zone of Kilimanjaro. Its main habitat and main distribution area are nowadays the coﬀee–banana plantations with their ramiﬁed irrigation system and forest-like structure on the southern and eastern slopes (Figure 9). The same holds for Impatiens walleriana and the fern Adiantum poiretii. Another apophyte is e.g. Pellaea viridis, which naturally thrives on Kilimanjaro in submontane CrotonCalodendrum forests (Hemp in press b). Some forest plants (e.g. Pilea tetraphylla) were only encountered in the banana plantations but in none of the 583 forest plots, highlighting the important conserving function of the Chagga homegardens. The agroforestry system of the Chagga homegardens is a unique feature of Kilimanjaro, distributed over an area of about 1000 km2. If one passes from north-east to the south-western end of this belt, one could drive for 120 km through a closed ‘banana forest’ containing about 225 Million banana ‘trees’ (calculated on the base of the vegetation proﬁle) – if there was a continuous road. The same type of land use, however with a smaller extension, occurs on

Figure 10. Tschibo estate at Mweka, southern slope of Kilimanjaro in November 2003. Hundreds of old trees were felled to grow new coﬀee varieties that do not need shade. [150]

1215 the Pare Mountains and Mt. Meru, which shows nearly exact the same ﬂoristic and structural composition (Hemp unpub. data). The Chagga homegardens maintain not only a high biodiversity, they are an old and very sustainable way of land use that meets several diﬀerent demands. Beside crop production, the sparse tree layer provides people with ﬁre wood, fodder and timber. But the high demand of wood, low coﬀee prizes on the world marked and the introduction of coﬀee varieties that are sun-tolerant endanger this eﬀective system (Hemp et al. in press). In some areas of the mountain (e.g. on the eastern slopes) the trees in the banana ﬁelds are very scattered or already missing. A very bad example in this respect was observed at Mweka on the central southern slope: Here a large foreign coﬀee company felled hundreds of old trees in November 2003 to grow coﬀee (Figure 10). In order to reduce the pressure on the forest, it is necessary, to support the tree planting in the Chagga homegardens with their unique agroforestry system. Similar to environmental programmes for farmers in the European Union (e.g. for the protection of wetlands or dry meadows), there should be a programme that rewards farmers to have a certain share of their land covered by trees. It can be estimated that a homegarden supplies 1/4 to 1/3 of the fuelwood requirements of a family (Fernandes et al. 1984). As the banana belt is nearly as extensive as the forest reserve, this will of course have major eﬀects in terms of forest protection and the water balance. In combination with new marketing and farming strategies for growing organic coﬀee through traditional methods an advertising campaign should be started especially in European countries where the awareness of environmental problems is high. A concept with this idea was already proposed to the OECD (Hemp 2003).

Acknowledgements I gratefully acknowledge grants by the Deutsche Forschungsgemeinschaft and the Tanzanian Commission for Science and Technology for permitting research. For support in getting permits I owe gratitude to the Chief Park Wardens of Kilimanjaro National Park, Mr Lomi Ole Moirana and Mr Nyamakumbati Mafuru, to the Catchment Forest oﬃcers and to my counterpart Mr Jacob Mushi (Tanzania Association of Foresters), Moshi. I further thank the keepers of the East African Herbarium, Nairobi (Kenya) Dr Beatrice Khayota and Kew Herbarium, England, Prof Dr Owens for permission to study their collections, Quentin Luke and Simon Mathenge (both Nairobi) for help in identifying diﬃcult species and Prof Dr Inge Lenski, Marburg (Germany) for valuable comments on the manuscript. References Beentje H.J. 1994. Kenya Trees, Shrubs and Lianas. National Museums of Kenya, Nairobi. Braun-Blanquet J. 1964. Pﬂanzensoziologie. Springer, Wien. [151]

1216 Brewin D.R. 1965. Kilimanjaro agriculture. Tanganyika Notes Records 64: 115–117. Clemm V.M. 1963. Agricultural productivity and sentiment on Kilimanjaro. Econ. Bot. 18: 99–121. Downie C. and Wilkinson P. 1972. The Geology of Kilimanjaro. University of Sheﬃeld. FAO 1986. Rehabilitation of traditional schemes (Phase I), Tanzania AG: TCP/URT/4522, Mission Report, Rome. Fernandes E.C.M., Okting’ati A. and Maghembe J. 1984. The Chagga homegardens: a multistoried agroforestry cropping system on Mt. Kilimanjaro (Northern Tanzania). Agroforest. Syst. 2: 73– 86. Fjeldsa˚ J., Ehrlich D., Lambin E. and Prins E. 1997. Are biodiversity ‘hotspots’ correlated with current ecoclimatic stability? A pilot study using the NOAA-AVHRR remote sensing data. Biodivers. Conserv. 6: 401–422. FTEA 1952–2003. Flora of Tropical East Africa. Royal Botanic Garden, Kew. Hammen T.V.D., Mueller-Dombois D. and Little M.A 1989. Manual of Methods for Mountain Transect Studies. IUBS, Paris. Hemp A. and Winter J.C. 1999. Ergebnisse der ethnobotanischen Forschung am Kilimanjaro. Bayreuther Forum O¨kologie 64: 117–144. Hemp A. 1999. An ethnobotanical study on Mt. Kilimanjaro. Ecotropica 5: 147–165. Hemp A. 2001a. Ecology of the pteridophytes on the southern slopes of Mt. Kilimanjaro. Plant Biol. 3: 493–523. Hemp A. 2001b. Life form and strategies of forest ferns on Mt. Kilimanjaro. In: Gottsberger G. and Liede S. (eds), Life forms and Dynamics in Tropical Forests. Dissertationes Botanicae 346, pp. 95–130. Hemp A. 2002. Ecology of the pteridophytes on the southern slopes of Mt. Kilimanjaro. Part I: Altitudinal distribution. Plant Ecol. 159: 211–239. Hemp A. 2003. Climate impacts and responses on Mount Kilimanjaro. In: Agrawala S. and Moehner A. (eds), Development and Climate Change in Tanzania: Focus on Mount Kilimanjaro. OECD, Paris. Hemp A. in press a. Continuum or zonation? Altitudinal gradients in the forest vegetation of Mt. Kilimanjaro Plant Ecol. Hemp A. in press b. Ecology and altitudinal zonation of pteridophytes on Mt. Kilimanjaro. In Proceedings of the XVIIth AETFAT Congress 21–26 September 2003. Hemp A. in press c. The impact of ﬁre on diversity, structure and composition of Mt. Kilimanjaro’s vegetation. In Proceedings of the GMBA Symposium 19–24 August 2002 in Moshi, Tanzania. Hemp A., Lambrechts C. and Hemp C. (in press). Global Trends in Africa: The Case of Mt. Kilimanjaro. UNEP, Nairobi. Hemp C. and Hemp A. 2003. Saltatoria coenoses of high-altitude grasslands on Mt. Kilimanjaro, Tanzania (Orthoptera: Saltatoria). Ecotropica 9: 71–97. Hemp C. in press. The Chagga home gardens – relict areas for endemic Saltatoria species (Insecta: Orthoptera) on Mt. Kilimanjaro. Biol. Conserv. Hemp C. 2001. Ethnozoological research on invertebrates on Mt. Kilimanjaro, Tanzania. Ecotropica 7: 139–149. Kress W.J. 1986. The systematic distribution of vascular epiphytes: an update. Selbyana 9: 2–22. Lind E.M. and Morrison M.E.S. 1974. East African Vegetation. Longman, London. Mdoe N. and Wiggins S. 1997. Returns to smallholder dairying in the Kilimanjaro region, Tanzania. Agr. Econ. 17: 75–87. Nair P.K.R. 1993. An introduction to agroforestry. Kluwer, Dordrecht. National Bureau of Statistics and Central Census Oﬃce. 2003. 2002 Population and Housing census. Genaral report. The United Republic of Tanzania, Dar es Salaam. O’Kting’ati A. and Kessy J.F. 1991. The farming system on Mount Kilimanjaro. In: Newmark W.D. (ed), The Conservation of Mount Kilimanjaro. The IUCN Tropical Forest Programme, pp. 71–80. O’Kting’ati A., Maghembe J.A., Fernandes E.C.M. and Weaver G.H. 1984. Plant species in the Kilimanjaro agroforestry system. Agroforest. Syst. 2: 177–186.

[154]

1217 Ramsay J.C. 1965. Kilimanjaro – sources of water supplies. Tanganyika Notes Records 64: 92–94. Rikli M. 1903/1904. Die Anthropochoren und der Formenkreis des Nasturtium palustre DC. Berichte der Zu¨rcherischen Botanischen Gesellschaft 8: 71–82. Rodgers W.A. and Homewood K.M. 1982. Species richness and endemism in the Usambara mountain forests, Tanzania. Biol. J. Linn. Soc. 18: 197–242. Schmidt P.R. 1989. Early exploitation and settlement in the Usambara Mountains. In: Hamilton A.C. and Bensted-Smith R. (eds), Forest Conservation in the East Usambara Mountains Tanzania. The IUCN Tropical Forest Programme, pp.75–78. Simmonds N.W. 1966. Bananas, 2nd edn. London. Sukopp H. and Kowarik I. 1987. Der Hopfen (Humulus lupulus L.) als Apophyt der Flora Mitteleuropas. Natur und Landschaft 62: 373–377. Sukopp H. and Langer A. 1996. Campanula rapunculoides – ein Apophyt in der Vegetation Mitteleuropas. Verhandlungen der Gesellschaft fu¨r O¨kologie 25: 261–276. Timberlake L. 1986. Krisenkontinent Afrika. Hammer, Wuppertal. Volkens G. 1897. Der Kilimandscharo. Darstellung der allgemeineren Ergebnisse eines fu¨nfzehnmonatigen Aufenthalts im Dschaggalande. Reimer, Berlin. Widenmann A. 1899. Die Kilimandscharo-Bevo¨lkerung. Anthropologisches und Ethnographisches aus dem Dschaggalande. Petermanns geographische Mitteilungen, Erga¨nzungs-Heft 129, 104 pp.

[155]

Biodiversity and Conservation (2006) 15:1219–1252 DOI 10.1007/s10531-005-0768-6

Springer 2006

-1

Biodiversity hotspots and conservation priorities in the Campo-Ma‘an rain forests, Cameroon M.G.P. TCHOUTO1,*, M. YEMEFACK2, W.F. DE BOER3, J.J.F.E. DE WILDE4, L.J.G. VAN DER MAESEN4 and A.M. CLEEF5 1

Limbe Botanic Garden, BP 437, Limbe, Cameroon; 2International Institute for Geo-Information Science and Earth Observation (ITC), PO Box 6, 7500 AA Enschede, The Netherlands; 3Resource Ecology Group, Wageningen University, Bornsesteeg 69, 6708 PD, Wageningen, The Netherlands; 4 Biosystematics Group, Wageningen University, Generaal Foulkesweg 37, 6703 BL, Wageningen, The Netherlands; 5Institute for Biodiversity and Ecosystem Dynamics (IBED) Research Group, Palynology and Paleo/Actuo-ecology, University of Amsterdam, Kruislaan 318, 1090 GB Amsterdam, The Netherlands; *Author for correspondence (e-mail: [email protected]) Received 3 February 2004; accepted 7 January 2005

Key words: Biodiversity, Cameroon, Campo-Ma’an, Central Africa, Conservation, Endemic species, Forest refuge, Genetic Heat Index, Pioneer Index, Plant diversity, Tropical rain forest Abstract. Until recently, patterns of species richness and endemism were based on an intuitive interpretation of distribution maps with very limited numerical analyses. Such maps based solely on taxonomic collections tend to concentrate on collecting eﬀorts more than biodiversity hotspots, since often the highest diversity is found in well-collected areas. During the last decades, there has been an overwhelming concern about the loss of tropical forest biological diversity, and an emphasis on the identiﬁcation of biodiversity hotspots in an attempt to optimise conservation strategies. Furthermore, the concept of sites of high diversity, or hotspots, has attracted the attention of conservationists as a tool for conservation priority settings. With the development of GIS tools, geostatistics, phytosociological and multivariate analysis software packages, more rigorous numerical analyses of distributional and inventory data can be used for assessing conservation priorities. In the Campo-Ma’an rain forest, inventory data from 147 plots of 0.1 ha each and 7137 taxonomic collections were used to examine the distribution and convergence patterns of strict and narrow endemic species. We analysed the trends in endemic and rare species recorded, using quantitative conservation indices such as Genetic Heat Index (GHI) and Pioneer Index (PI), together with geostatistic techniques that help to evaluate and identify potential areas of high conservation priority. The results showed that the Campo-Ma’an area is characterised by a rich and diverse ﬂora with 114 endemic plant species, of which 29 are restricted to the area, 29 also occur in southwestern Cameroon, and 56 others that are also found in other parts of Cameroon. Although most of the forest types rich in strict and narrow endemic species occur in the National Park, there are other biodiversity hotspots in the coastal zone and in areas such as Mont d’Ele´phant and Massif des Mamelles that are located outside the National Park. Unfortunately, these areas, supporting 17 strict endemic species that are not found in the park, are under serious threat and do not have any conservation status for the moment. Taking into consideration that with the growing human population density, pressure on these hotspots will increase in the near future, it is suggested that priority be given to the conservation of these areas and that a separate management strategy be developed to ensure their protection.

[159]

1220 Introduction Central African rain forests are among the top conservation priority areas in the world (Davis et al. 1994; Heywood and Watson 1995; Myers et al. 2000). The Campo-Ma’an rain forest, in the southern part of Cameroon, falls under the Guineo–Congolian Regional Centre of Endemism that is reported to be species-rich with high levels of endemism (White 1979, 1983; Davis et al. 1994). It is situated in the middle of the Atlantic Biafran forest zone that extends from Southeast Nigeria to Gabon and the Mayombe area in Congo (Letouzey 1968, 1985). The vegetation in the Campo-Ma’an area is determined by climate, especially rainfall, altitude, soils, proximity to the sea and human disturbance (Tchouto 2004). The structure and composition of the forest, as well as the vegetation types change progressively from the mangrove or coastal forest on sandy shorelines through the endemic lowland evergreen forest rich in Caesalpinioideae with Calpocalyx heitzii and Sacoglottis gabonensis, to the submontane forest on hilltops and the mixed evergreen and semi-deciduous forest in the drier Ma’an area. Other vegetation types/sub-types include swamps, seasonally ﬂooded forests, riverine and secondary forests. The forest in the Ma’an area is described as transitional between the coastal evergreen forest and the semi-deciduous forest of the interior. In view of the rich and diverse ﬂora of the Campo-Ma’an rain forest, as well as its high level of endemism, it has been identiﬁed as one of the key conservation sites in Cameroon (Gartlan 1989; Foahom and Jonkers 1992). The Campo-Ma’an area is a Technical Operational Unit (TOU) that comprises a National Park, ﬁve forest management units, two agro-industrial plantations, and a multi-uses zone (Tchouto 2004). Despite the low population density, there are many stakeholders and diﬀerent types of land use. Activities such as logging, industrial and shifting agriculture exert varying ecological impact on the forest ecosystem. This has led to deforestation, habitat fragmentation and alteration of the coastal forests. With the increasing destruction of natural ecosystems, it is important to identify biodiversity hotspots and conservation priorities in order to enable an eﬀective management. To achieve this, we need to study the species composition and species distribution, so that we can target conservation resources and eﬀorts to rich and diverse areas with a high number of endemic species. Endemism is commonly regarded as an important criterion for assessing the conservation value of a given area. In this study, forest inventory data and taxonomic collections will be used to examine the distribution and convergence patterns of strict and narrow endemic species. We will use new quantitative conservation indices such as GHI (Genetic Heat Index) and Pioneer Index (PI) to analyse trends in endemic and rare species in the various forest types. Finally, geostatistic analysis and techniques will help to evaluate and identify potential areas of high conservation priority. [160]

1221 Materials and methods Study area The study was conducted in the Campo-Ma’an rain forest in south Cameroon. The site covers about 7700 km2 and it is located between latitudes 210¢– 252¢ N and longitudes 950¢–1054¢ E. Following the FAO classiﬁcation system, soils in the Campo-Ma’an area are generally classiﬁed as Ferrasols and Acrisols (Franqueville 1973; Muller 1979; van Gemerden and Hazeu 1999). They are strongly weathered, deep to very deep and clayey in texture (except at the seashores and in river valleys where they are mainly sandy), acid and low in nutrients with pH (H2O) values generally around 4. The topography ranges from undulating to rolling in the lowland area, to steeply dissect in the more mountainous areas. In the Campo area, altitudes are mostly low, ranging from sea level to about 500 m. In the eastern part, which is quite mountainous, the altitude varies between 400 and 1100 m and the rolling and steep terrain brings about a more variable landscape. The area has a typical equatorial climate with two distinct dry seasons (November–March and July to mid-August) and two wet seasons (April–June and mid-August to October). The average annual rainfall generally decreases with increasing distance from the coast, ranging from 2950 mm/year in Kribi and 2800 mm in Campo to 1670 mm in Nyabissan in the Ma’an area. The average annual temperature is about 25 C and there is little variation between years. The hydrography of the area shows a dense pattern with many rivers, small river basins, fast-ﬂowing creeks and rivers in rocky beds containing many rapids and small waterfalls. Generally, the area has a low population density of about 10 inhabitants per square kilometre and is sparsely populated (ca. 61,000 inhabitants) with most people living around Kribi, along the coast, and in agro-industrial and logging camps (ERE De´veloppement 2002; de Kam et al. 2002). Despite the low population density, there are few employment opportunities. The local people are very poor and so far rely solely on the forest resources to meet their basic needs. As a result, local pressure on the CampoMa’an rain forest is increasing and there are several activities that are carried out in the area with varying ecological impacts on the forest ecosystem. These activities include agriculture, logging, poaching and hunting.

Botanical assessment Sampling was carried out between 2000 and 2003 in 147 plots of 0.1 ha (50 m · 20 m) in representative and homogeneous vegetation types (see Table 6 for an overview of the plots per vegetation type). In each 0.1-ha plot, all trees, shrubs, herbs and lianas with DBH ‡1 cm (diameter at breast height, about 1.3 m above ground) were measured, recorded and identiﬁed. These plots were established in undisturbed forests or matured secondary forests within 12 vegetation [161]

1222 Table 1. Star categories and GHI weight classes as deﬁned for Cameroon. Star category Weight for GHI Comments Black (BK)

27

Gold (GD)

9

Blue (BU)

3

Scarlet (SC)

1

Red (RD) Pink (PK) Green (GN)

1 1 –

Species which are only found in Campo-Ma’an area (strictly endemic) or near endemics (species which also occur in some localities around Campo-Ma’an such as Bipindi, Edea-Kribi, Lolodorf or southern part of Cameroon). Urgent attention to conservation of population is needed. Cameroon endemics, rare and threatened Lower Guinea endemics. Cameroon has deﬁnitely responsibility for preserving these species. Lower Guinea and Guineo–Congolian endemics which are widespread internationally but rare in Cameroon, or vice versa. Common but under serious pressure from heavy exploitation. Exploitation needs to be curtailed if usage is to be sustainable. Protection of all scales vital. Common but under pressure from exploitation. Common and moderately exploited. Widespread Guineo–Congolian, pantropical and tropical African species that are not under pressure. No particular conservation concern.

Adapted from Hawthorne and Abu-Juam (1995), Hawthorne (1996) and Tchouto et al. (1998).

types ranging from coastal forest, mangrove, swamp, lowland evergreen forest, mixed evergreen and semi-deciduous forest to submontane forest at higher elevations (800–1100 m above sea level). Most of the plots were located in the National Park and the forest management units which are less aﬀected by human activities. Furthermore, in each representative vegetation type, a provisional plant species checklist was made in the ﬁeld with information on their growth form, guild and frequency. A guild refers to a group associated with a common way of life (Table 2). For unknown species, a voucher specimen was collected. The study also involved the collection of fertile specimens encountered in plots, vegetation types and speciﬁc habitats such as exposed rocks and riverbanks. The geographic co-ordinates of each plot, sample or specimen were recorded using the Global Positioning System (GPS, Garmin 12XL model with estimated precision of ±10 m). These co-ordinates were used for mapping main vegetation types, species distribution, and biodiversity hotspots. A duplicate of each specimen was mounted and preserved in the Kribi Herbarium. Others duplicates were sent to the National Herbarium in Yaounde, Cameroon (YA) and the Nationaal Herbarium Nederland, Wageningen University Branch (WAG) for further identiﬁcation and preservation. Criteria for taxa inclusion A plant species checklist was generated from the inventory data, from the plant collections made during the study, and from specimens previously collected in the area by other scientists, stored in the Cameroon and Wageningen herbaria. Furthermore, a taxonomic search for potential taxa of high conservation [162]

1223 Table 2. Guild and weight classes. Guild

Weight for PI

Comment

Pioneer (PI)

2

Non-Pioneer light demanding (NP)

1

Shade-bearers (SB)

0

Regenerating only in forest gaps and therefore indicating disturbed forest (e.g. Ceiba, Musanga, Harungana, Macaranga). Although some juveniles are also found in the understorey of undisturbed forest, they require gaps to develop to full maturity. Generally, non-pioneer light demanding are abundant in matured disturbed forest (e.g. Albizia, Entandrophragma, Piptadeniastrum, Pycnanthus). Understorey herbs, shrubs and trees which grow, ﬂower and fruit in undisturbed forest (e.g. Cola, Diospyros, Psychotria, Rinorea).

Adapted from Hawthorne and Abu-Juam (1995), Hawthorne (1996) and Cable and Cheek (1998).

priority such as endemic, rare, new and threatened species was carried out using existing ﬂoras and monographs (Keay and Hepper 1954–1972; Aubre´ville and Leroy 1961–1992; Aubre´ville and Leroy 1963–2000; Lebrun and Stork 2003; Satabie´ and Leroy 1980–1985; Satabie´ and Morat 1986–2001), the IUCN (2002) red list categories, and the WCMC (1998) world list of threatened trees. On the basis of this information, a list of 141 species of high conservation values was produced with information on their habit, guild, star category (Table 1) and chorology. In this list, priority was given to taxa that are strictly endemic to the Campo-Ma’an area. Followed by species that are endemic to southwestern Cameroon (also occurring in Bipindi and Lolodorf areas) or Cameroon and Lower Guinea endemics (especially if they reach their northern or southern limit of distribution in Campo-Ma’an). Furthermore, species that reach their northern or southern limit of distribution in the Campo-Ma’an area were also included in the list. Star rating of species and measurement of forest conservation value A star rating system, based on the work of Hawthorne and Abu-Juam (1995) and Hawthorne (1996) in Ghana, Cable and Cheek (1998) and Tchouto et al. (1998) in Cameroon, was used to deﬁne the conservation status of each species recorded (Table 1). The factors considered when categorising species into star categories are their distribution, ecology, local abundance, taxonomy, life history, interaction with ecosystem parameters and economic importance (Hawthorne 1996). Therefore, species that are endemic, rare, threatened, or likely to represent a scarce genetic resource, are more valuable than others are. Hence, forests richer in such species receive a higher score than others. The GHI concept was developed by Hawthorne (1996) to express the conservation value of a given forest, and the PI concept to express the level of [163]

1224 disturbance in a given forest. GHI is an attempt to provide a scale, on which to measure the genetic ‘temperature’ or value of the forest. A plot/forest with an average GHI >150 will be considered warm or hot. In general, for species with completed monographs, black stars occupy about 1–3 ﬁlled degree squares on a standard distribution map, gold stars 4–14, blue stars 15–30, and green star more than 30 degree squares. Hawthorne (1996) deﬁned the guild as a ﬂexible concept used to circumscribe a group of plant species with a similar ecology and way of life. All the species were grouped into guild classes as deﬁned in Table 2 and a PI score was calculated as an expression of the relative contribution of pioneers. Five classes of human disturbance were used to evaluate the forest quality and condition as deﬁned in Table 3. These classes were mainly based on the ﬁeld observation of the level of human disturbance and the state of forest degradation. The GHI and PI values of each sample were calculated using the TREMA database as follows: Genetic Heat Index (GHI) ¼ ½ð(BK BK weightÞ þ ðGD GD weightÞ þ ðBU BU weightÞ þ ðRD RD weight))= ðBK þ GD þ BU þ GN þ RDÞ 100; where BK = number of black star species; GD = number of gold star species; BU = number of blue star species; GN = number of green star species; and RD = number of red, scarlet and pink star species. Pioneer Index (PI) ¼

ðPioneer PI weightÞ þ (NP NP weightÞ 100; Total number of species

where PI = number of pioneer species and NP = number of non-pioneer light demanding species.

Table 3. Forest condition classes showing the degree of human disturbance on the natural forest cover. Forest condition

Classes

Notes

Excellent

Virtually undisturbed

Good

Less than 25% disturbed 25–50% disturbed

Undisturbed forest, with good canopy and few signs of human disturbance except for hunting and NTFPs collection. Small patches of recent disturbances (<25%) with good canopy cover. Obviously disturbed with signiﬁcant patches (25–50%) of recent degradation but with good predominant forest and broken upper canopy. Considerable are (>50%) of recent degradation. Patchy with heavily disrupted canopy. No signiﬁcant forest left (<2% good forest). Massive land conversion for plantation or farm.

Slightly degraded Mostly degraded Very poor

More than 50% disturbed Farm land

[164]

1225 Geostatistical analysis Conservation indices such GHI and PI are likely to vary throughout a region. Geostatistics (Isaaks and Srivastava 1989; Webster and Oliver 2001) were applied to quantify the spatial distribution of GHI within the Campo-Ma’an forest. Geographic analyses were done using ILWIS software (ILWIS 2001) and GSTAT package (Pebesma and Wesseling 1998) of R software (R Development Core Team 2002). The semivariance was calculated for GHI data on a minimum lag distance of 1250 m and each lag distance class contained at least 105 pairs of points. The semivariogram parameters (nugget, sill and range) were computed using the GSTAT ﬁt variogram function. During the study of GHI spatial variability, the main objective was to obtain a map from point observations. Since this also required the estimation of a value at un-visited locations, the technique commonly used is known as kriging (Isaaks and Srivastava 1989). The semivariogram function was then used to extrapolate the GHI values in the CampoMa’an forest at 100 m · 100 m grid, using ordinary kriging. The output map was reclassiﬁed into ﬁve classes of conservation value (Hawthorne 1996).

Results Species richness and endemism A plant species checklist made of 2297 species of vascular plants, ferns and fern allies was generated from inventory data and from 2348 herbarium specimens and 4789 ecological specimens collected in the various plots. They belonged to 851 genera and 155 families. More than 67% of the specimens were identiﬁed at species level, 28% at generic level, 4% at family level and 1% remained unidentiﬁed. The 20 most important families and genera are shown in Tables 4 and 5. In terms of growth form, tree species contributed for 26% to the total number of 2297 species recorded, followed by herbs (24%), shrubs (23%) and climbers (17%), respectively. About 72% of the total number of species recorded was also found in the Campo-Ma’an National Park and the remaining 28% were only found in the coastal forest and the semi-deciduous forests located outside the park. In addition to a list of 92 threatened species (Appendix 2) recorded in IUCN (2002) and WCMC (1998), a list with 141 plant species of high conservation priorities was produced, with information on their growth forms, guild, chorology and star categories (Appendix 1). Only species that are endemic to Cameroon and species that reach their northern or southern limit of distribution are included in this list. The Campo-Ma’an area has about 114 endemic species, 29 of which are only known from the area, 29 only occur in the southwestern part of Cameroon, and 56 near endemics that also occur in other parts of Cameroon (Appendix 1 and Figure 1). Shrubs contributed for 38% of the 114 endemic species (Appendix 1), herbs 29%, trees 20% and climbers 11%. Moreover, 540 species (23% of the total [165]

1226 Table 4. Most important families recorded in the Campo-Ma’an area. No.

Family

No. of species

Predominant growth forms

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Rubiaceae Euphorbiaceae Leguminosae-Caesalpinioideae Apocynaceae Annonaceae Acanthaceae Leguminosae-Papilionaideae Sterculiaceae Gramineae Orchidaceae Melastomataceae Moraceae Celastraceae Cyperaceae Dichapetalaceae Sapindaceae Araceae Loganiaceae Sapotaceae Begoniaceae Others(135 families)

279 117 96 80 69 68 65 62 54 54 46 40 39 39 39 36 34 33 30 29 988

Trees, shrubs, herbs and climbers Trees, shrubs, herbs and climbers Trees and shrubs Trees, shrubs, herbs and climbers Trees, shrubs and climbers Herbs Trees, herbs and climbers Shrubs and trees Herbs Terrestrial and epiphytic herbs Shrubs and herbs Trees, shrubs and herbs Climbers Herbs Climbers Trees and shrubs Herbs and hemi-epiphytes Shrubs and climbers Trees and shrubs Terrestrial and epiphytic herbs Trees, shrubs, climbers and herbs

Table 5. Most important genera recorded in the Campo-Ma’an area. No.

Genus

No. of species

Predominant growth forms

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Dichapetalum (Dichapetalaceae) Psychotria (Rubiaceae) Cola (Sterculiaceae) Begonia (Begoniaceae) Diospyros (Ebenaceae) Salacia (Celastraceae) Strychnos (Loganiaceae) Rinorea (Violaceae) Drypetes (Euphorbiaceae) Combretum (Combretaceae) Dorstenia (Moraceae) Campylospermum (Ochnaceae) Bulbophyllum (Orchidaceae) Ficus (Moraceae) Garcinia (Guttiferae) Asplenium (Aspleniaceae) Culcasia (Araceae) Landolphia (Apocynaceae) Tricalysia (Rubiaceae) Bertiera (Rubiaceae) Others (831 genera)

37 35 32 29 27 27 24 23 21 18 18 17 16 16 16 15 15 15 15 14 1867

Climbers Shrubs Trees and shrubs Terrestrial and epiphytic herbs Trees and shrubs Climbers Climbers Trees and shrubs Trees and shrubs Climbers Herbs Shrubs Terrestrial and epiphytic herbs Trees and stranglers Trees and shrubs Epiphytic herbs Herbs and hemi-epiphytes Climbers Trees an shrubs Shrubs Trees, shrubs, climbers and herbs

[166]

1227

Figure 1. Distribution of 114 strict and narrow endemic plant species recorded in the CampoMa’an area (gray circle). Black circle represents the distribution of 17 threatened strict endemics that are not found in the National Park. The size of the circle represents the relative density of endemics at a given point.

number of species) recorded are endemic to the Lower Guinea Centre of Endemism, 1123 species (49%) are Guineo–Congolian endemics and 105 species (5%) are Guinea endemics as described by White (1979). Overall, there was a high concentration of strict and narrow endemic species in the lowland evergreen forest rich in Caesalpinioideae, coastal and submontane forests located in the western and northern parts of Ma’an and a relatively low concentration of these species in Ma’an area (Figure 1). Although more than 70% of the total endemic species recorded were also found in the National Park, 17 of the 29 strict endemic species were not recorded in the park (Appendix 1). The distribution patterns of these 17 taxa showed a high concentration of species around Campo, Lobe, Massif des Mamelles, Mont d’Ele´phant and Zingui and a very poor representation in the Ma’an area (Figure 1). GHI and measurement of forest conservation value More than 57% of the plots have a high GHI score with the highest score recorded in the submontane forest (GHI = 294.4) and the lowest score in mangrove (GHI = 3.1). As shown in Figure 2, the submontane forest had the highest average GHI score of 214.7, followed by the lowland evergreen forest rich in Caesalpinioideae with Calpocalyx heitzii and Sacoglottis gabonensis [167]

1228

Figure 2. The average Genetic Heat Index (GHI = bars) and average Pioneer Index (PI = line) for the various vegetation types as deﬁned in Table 6.

(GHI = 194.1). The mangrove and the coastal forest on sandy shorelines had the lowest average GHI score (GHI = 3 and 120.2, respectively). The average PI was very high in the mangrove forest (PI = 125), coastal forest on sandy shorelines (PI = 66.9) and in the forest rich in Aucoumea klaineana (PI = 60). Generally, there was a signiﬁcant decrease in average GHI with increasing average PI (Figure 2). As shown in Figure 3, there was a very strong signiﬁcant negative correlation between the average GHI scores and the PI scores recorded in the various vegetation types (F1–10 = 111.71, R2 = 0.918, p < 0.0001). However, the correlation was rather weak with a low explanatory factor when the analysis was carried out using all plots as individual data points (F1–45 = 94.00, R2 = 0.393, p<0.0001). Most of the forest types within the National Park were virtually undisturbed or less than 25% disturbed (Figure 4). The coastal forest between Campo and Kribi, as well as the forests around Massif des Mamelles, Mont d’Ele´phant, agro-industrial plantations, logging concessions and settlements were much more aﬀected by human activities (Figure 4). These forests were often more than 25% disturbed by human activities and were characterised by a high PI scores (Figures 2 and 4).

Geostatistical results The analysis of the spatial structure of the dataset did not show any preferential spatial trend. Therefore, an omni-directional analysis of the semivariance (best described by a spherical model) was applied. Figure 5 shows the semivariogram and its characteristics. The GHI variable showed a strong spatial dependence [168]

1229

Figure 3. Correlation between the average GHI scores and the average PI scores for the various vegetation types.

Figure 4.

Impact of human disturbance on the Campo-Ma’an rain forest.

within a range of 10,500 m. The nugget (645) was low compared to the total variance or sill (3700). This suggests that more than 82% (100*(Sill-Nugget)/Sill) of the semivariance of GHI could be modelled by the variogram over a range of 10 km. The output map of the ordinary kriging (Figure 6) was reclassiﬁed into [169]

1230

Figure 5. Spherical variogram model for GHI in the Campo-Ma’an rain forest (estimated from 147 points of 0.1 ha each).

Figure 6. Ordinary kriging map showing the distribution of GHI scores and conservation hotspots within the Campo-Ma’an rain forest The following GHI values are deﬁned for the various conservation classes (Hawthorne 1996): Very high conservation value for GHI >200; High conservation value (150 ‡ GHI <200); Moderate conservation value (100 ‡ GHI <150); Low conservation value (50 < GHI <100) and very low conservation value (GHI <50). [170]

1231 ﬁve GHI classes, partitioning the conservation value of the Campo-Ma’an forest. This partition showed that 1% of the area was characterised by a very high conservation value, 45% by a high conservation value, 30% by an average conservation value, 15% by a low conservation value and 9% by a very low conservation value. A considerable portion of the National Park and the forests around Massif des Mamelles and Mont d’Ele´phant was characterised by a high conservation value, with highest values found in Dipikar Island, Massif des Mamelles, Mont d’Ele´phant and in the submontane forest on hilltops. The forests in the Ma’an area, around Campo and agro-industrial plantations, near villages and along the roads had a low conservation value. Similar patterns were observed for the distribution of strict and narrow endemic species (Figure 1).

Discussion General vegetation patterns The Campo-Ma’an has a diverse range of vegetation that changes progressively from sea level to 1100 m at higher altitudes. The wetter Campo area was dominated by the lowland evergreen forest rich in Caesalpinioideae and the drier Ma’an area by the mixed evergreen and semi-deciduous forest. More than 65% of the forest types recorded had at least 250 species (Table 6). The submontane forest had the highest frequency of species-rich plots (93% of the plots had above 100 species/0.1 ha). Other rich vegetation types included the lowland evergreen forest rich in Caesalpinioideae with Calpocalyx heitzii and Sacoglottis gabonensis (81%), the lowland evergreen forest rich in Caesalpinioideae with Sacoglottis gabonensis (78%), the lowland evergreen forest rich in Caesalpinioideae (76%) and the mixed evergreen and semi-deciduous forest (67%). The mangroves, swamps and the coastal vegetations on sandy shorelines were species-poor. The explanation for the diverse range of forest types and habitats might stem partly from the fact that the Campo-Ma’an vegetation is inﬂuenced by several environmental factors such as rainfall, altitude, soil, the proximity to the sea and the degree of human disturbance (Tchouto 2004). As a result there was a gradual variation in dominant species, forest type and structure from the coast to the hilltops and the drier forest in the Ma’an region.

Species richness and endemism The Campo-Ma’an area is characterised by a rich and diverse ﬂora with more than 2297 species of vascular plants, ferns and fern allies. The site has about 114 endemic plant species out of which 29 are strictly endemic to the site. The number of endemic plant species is relatively high considering the size of the area, and more than 75% of the current vegetation cover was characterised [171]

1232 Table 6. Number of plots, number of species and number of stem/ha recorded within the various vegetation types for all plants with DBH ‡1 cm. Vegetation types

No of plots

No of species

Average No of stems/ha

Caesalp (2.3 ha) Caesalpcasa (2.5 ha) Caesalpsa (1.4 ha) Cosaga (0.9 ha) Cosaca (0.9 ha) Cosas (0.4 ha) Mixevergreen (2.1 ha) Mixsemideci (1.6 ha) Submontane (1.4 ha) Swamps (0.5 ha) Mangrove (0.2 ha) Okoume´ forests (0.5 ha) Total for the Campo-Ma’an area

23 25 14 9 9 4 21 16 14 5 2 5 147

557 (75–128) 555 (93–139) 474 (86–138) 303 (81–140) 326 (78–108) 100 (27–55) 523 (63–135) 481 (86–147) 499 (79–148) 246 (18–108) 4 (3–4) 234 (18–107) 1116 (3–148)

4380 5326 5935 5810 5864 4710 4983 5460 6094 4276 8630 4802 5312

(2500–5750) (3120–7020) (4350–7120) (4940–8010) (4740–7570) (3630–5700) (3890–6980) (4390–6340) (3680–8449) (2070–5960) (8150–9100) (3720–5800) (2070–9100)

Minimum and maximum values are given betweem brackets. Submontane = Submontane forest; Caesalpcasa = Lowland evergreen forest rich in Caesalpinioideae, Calpocalyx heitzii and Sacoglottis gabonensis; Casealpsa= Lowland evergreen forest rich in Caselpinioideae and Sacoglottis gabonensis; Caesalp= Lowland evergreen forest rich in Caesalpinioideae; Cosaga= Coastal forest with Sacoglottis gabonesis; Mixsemideci= Mixed evergreen and semi-deciduous forest with elements predominant; Mixevergreen= Mixed evergreen and semideciduous forest with semi-deciduous elements of evergreen forest predominant; Okoume´= forest rich in Aucoumea klaineana; Cosaca= Coastal forest with Sacoglottis gabonensis and Calpocalyx heitzii; and Cosas= Coastal forest on sandy shorelines.

either by very high, high or average GHI values (Figure 6). Furthermore, the distributions of strict and narrow endemic species showed a high concentration of these species in the submontane forest between Ebianemeyong and Akom II, in Dipikar Island, and in the forests in and around Massif des Mamelles, Lobe, Mont d’Ele´phant and Zingui. Surprisingly, the mixed evergreen and semideciduous forest in the Ma’an area showed a relatively low concentration of these species (Figure 1). The explanation for the high occurrence of endemics might stem partly from the fact that the area falls within a series of postulated rain forest refugia in Central Africa (Hamilton 1982; White 1983; Maley 1987, 1989, 1990, 1993, 1996; Sosef 1994, 1996). In such refugia, the unique combination of climatic and geological histories, contemporary ecological factors, and inherent biological properties of taxa and their combinations, may have contributed to survival and/or speciation (Barbault and Sastrapradja 1995; Hawksworth and Kalin-Arroyo 1995). Furthermore, the Campo-Ma’an area forms part of the Guineo–Congolian Regional Centre of Endemism (White 1983). All families endemic to this biogeographic region are also found in the Campo-Ma’an area (White 1983). They include Hoplestigmataceae, Huaceae, Lepidobotryaceae, Medusandraceae, Pandaceae, Pentadiplandraceae and Scytopetalaceae. Moreover, 82% of endemic genera cited by White (1983) also occur in the area. [172]

1233 Forest richness and biodiversity hotspots Considering the fact that the occurrence of endemic species contributes signiﬁcantly to the conservation value of a forest, it is important to study their distribution and abundance prior to any conservation initiatives. This is mainly due to the fact that strict and narrow endemic species are restricted to small areas, and are therefore highly vulnerable to human disturbance and other forms of environmental changes (Myers 1988; Williams 1993; Heywood and Watson 1995). A study carried out in the Campo-Ma’an rain forest has revealed that the submontane forest, the lowland evergreen forest rich in Caesalpinioideae with Calpocalyx heitzii and Sacoglottis gabonensis, and the lowland evergreen forest rich in Caesalpinioideae are richer in strict and narrow endemics compared to the other forest types found in secondary forest and along the coast. This is conﬁrmed by the high average GHI scores recorded in these forest types (Figure 2). Most of these forest types were located in the National Park and the lowland evergreen forests around Massif des Mamelles and Mont d’Ele´phant. They were virtually undisturbed or less than 25% disturbed by human activities (Figure 4). This implies that the Massif des Mamelles and the Mont d’Ele´phant areas represent other biodiversity hotspots, located outside of the Park (Figure 6). There was a strong signiﬁcant negative correlation between the average GHI scores and the average PI scores recorded in the various vegetation types. Most plots located near settlements and in secondary forests were characterised by a low conservation value with low GHI scores and high PI scores. This conﬁrmed that disturbed forests are rich in pioneer species but poor in plant species with high conservation priority. It is worth reiterating that a considerable portion of the Campo-Ma’an area has been selectively logged at least twice during the past 30 years. Although logging damages were moderate and had low impact on the total forest biodiversity, it has created forest gaps that allowed the development of many pioneer species. This might have contributed to the high average PI scores registered in the coastal forest types. In these areas with conﬂicts between human and conservation activities, there is an urgent need to develop participatory approaches to sustainable natural resource management that integrates the objectives of conservation with local development.

Threatened species During the selection of species of high conservation priority, taxa were chosen on a global rather than a Cameroonian or a Campo-Ma’an perspective of conservation importance. Of the 29 strict endemic species that are only known from the Campo-Ma’an area, 17 were not recorded in the National Park illustrating the need for conservation activities outside the park. Although these 17 strict endemics are not immediately threatened with extinction, the [173]

1234 most threatened are probably those occurring in the coastal zone and in areas located at the vicinity of large agro-industrial plantations, since these areas are heavily exploited. As shown in Figure 4, their habitats are fragmented and degraded because these areas are surrounded by farms and heavily disturbed forests. Considering the fact that extinct species are taxa that are no longer known to exist in the world after repeated search in their type localities (WCMC 1998; IUCN 2002), we cannot yet talk about extinction because no attempt has been made to search for these species. Furthermore, only 67% of the total amount of specimens collected was identiﬁed at species level. However, with the ongoing speed of forest degradation noticed in the coastal area, eight of these strict endemics (Beilschmiedia dinklagei, Deinbollia macroura, Ledermanniella batangensis, Psychotria aemulans, P. batangana, P. dimorphophylla, P. oligocarpa, and Strychnos canthioides) that are only known from the coastal zone can be categorised as endangered species. While the nine others that are located inland around Efoulan, Fenda, Massif des Mamelles, Mont d’Ele´phant and Zingui can be categorised as vulnerable. They are Afrotrewia kamerunica, Bulbophyllum alinae, Begonia montis-elephantis, Calvoa stenophylla, Dorstenia dorstenioides, Guaduella mildbraedii, Hypolytrum sp. nov., Scaphopetalum acuminatum and S. brunneo-purpureum. Some of them so far are only known from type specimens or from a few collections made in the type locality before the 60s. Others such as Afrotrewia kamerunica, Begonia montis-elephantis and Hypolytrum sp. nov. have a restricted range with a small and restricted population. Furthermore, habitat fragmentation may convert a previously more continuous population structure to a metapopulation structure, with local populations becoming so small that they may have a substantial risk of extinction (Hawksworth and Kalin-Arroyo 1995).

Implications for biodiversity conservation The Campo-Ma’an National Park The National Park is the core conservation area of the Campo-Ma’an Technical Operational Unit. It is surrounded by areas under several land uses that have varying ecological impact on the park and the surrounding forests. The park is of high conservation priority with about 72% of the 2297 species of vascular plants, ferns and fern allies recorded so far in the Campo-Ma’an area. More than 70% of the total endemic species recorded were also found in the National Park, and most of the forest types with high GHI scores, low PI scores and high conservation priority species were also found in the park (Figures 2 and 6). The most important one is the endemic lowland evergreen forest rich in Caesalpinioideae with Calpocalyx heitzii and Sacoglottis gabonensis, a vegetation type that only occurs in the Campo area (Letouzey 1985; Gartlan 1989; Thomas and Thomas 1993). Other forest types such as the submontane forest on hilltops, the lowland evergreen forest rich in [174]

1235 Caesalpinioideae and the mixed evergreen and semi-deciduous forests are also well represented. So far the National Park is the only area with a legal conservation status. It is a permanent state forest that is protected by law and solely used for forest and wildlife conservation. However, its boundaries have not been marked, the management plan has not yet been produced and protection is weak. Therefore, it is of urgent need to demarcate the boundary of the park, to reinforce its protection, and to complete and implement its management plan as soon as possible.

Massif des Mamelles and Mont d’Ele´phant This study has demonstrated that other hotspots for biodiversity conservation, such as Mont d’Ele´phant and Massif des Mamelles, are located outside the National Park (Figure 6). These areas are non-permanent forest estates that can be allocated for human activities such as logging, agro-industry, agriculture, agro-forestry, community forest, communal forest or private forest. Moreover, hunting, ﬁshing, mineral exploitation or any other form of economic activities is allowed if done in accordance to the 1994 forest law. Unfortunately, these areas do not have any conservation status and a number of ongoing human activities have negative impacts on the forest ecosystem (Tchouto 2004). In addition to the construction of the Tchad-Cameroon oil pipeline terminal at Grand Batanga and the rock exploitation on Mont d’Ele´phant, there exists a plan to exploit the iron ore deposits of the Massif des Mamelles. All these activities, if realized, would aﬀect the vegetation and thus impact the biodiversity. As shown in Figure 4, these fragmented forest patches with high conservation priorities are more seriously exposed to forest degradation and habitat loss since they are surrounded by disturbed and degraded forests. Furthermore, they are the type localities for some rare endemic species such as Afrotrewia kamerunica, Begonia montis-elephantis, Bulbophyllum alinae and Hypolytrum sp. nov. that are so far only known from the type specimens or from few collections made in these areas. Pressure on these fragmented hotspots will increase in the future with the growing human population density, the few local employment opportunities and the poverty of the local people, for whom the forest is a major resource. In order to ensure the protection of these areas, it is suggested that local community be encouraged to create community forests with several management zones. Each community forest should have the identiﬁed biodiversity hotspot as the core conservation area, surrounded by a buﬀer zone stimulating the sustainable management of non-timber forest products and hunting practices.

The coastal zone, Ntem basin, Lobe and Memve’ele waterfalls The coastal zone is a narrow strip (65 km long) along the Atlantic Ocean from the Lobe waterfalls to the Ntem estuary in the Dipikar Island that extends about 2–3 km inland. It has suﬀered and continues to suﬀer from intense [175]

1236 human pressure that has led to the destruction of most of its natural vegetation (Figure 4). However, it is worth mentioning that some rare endemic species such as Deinbollia macroura, Psychotria batangana, P. dimorphophylla, P. oligocarpa, and Strychnos canthioides are so far only known from this zone. Furthermore, there is an impressive network of rivers and streams in the Campo-Ma’an area that presents a number of very specialised riparian habitats. Our study conﬁrmed that the Lobe, Bongola, Memve’ele waterfalls and Ntem basin (Boucle du Ntem) support a rich riparian ﬂora with many endemic and rare rheophile species (Cusset 1987; Thomas and Thomas 1993). Most of the endemic rheophytes are of the genus Ledermanniella in the Podostemaceae family. These rheophytes which are found on exposed rocks in streambeds, are seasonally submerged by fast-ﬂowing water, and normally reproduce in drier periods when the water level recedes. The Ntem basin is also reported to constitute an important refuge for wildlife and ﬁsh fauna because of the presence of many rare species of freshwater ﬁshes (Vivien 1991; Matthews and Matthews 2000; Djama 2001). Therefore, it is suggested to develop a separate management strategy in order to protect these riparian habitats.

Conclusion The study provides important information on the abundance and distribution of endemic species, as well as the location of biodiversity hotspots in the Campo-Ma’an area. This information is essential for any decision-making process for biodiversity conservation and sustainable natural resource management. Our study has revealed that the area is characterised by a rich ﬂora with more than 2297 species of vascular plants and about 114 endemic plant species, of which 29 are only found in the area. Although most of the forest types with plant species of high conservation priorities appeared to occur in the Campo-Ma’an National Park, there are several human activities in the area with varying negative ecological impacts on the forest ecosystem. Therefore, the successful management and long-term sustainability of the Park will largely depend on the ability to reconcile the objectives of conservation and other uses at its vicinity. The study also demonstrated that there are other biodiversity hotspots in the coastal zone and areas such as Mont dEle´phant and Massif des Mamelles that are located outside the National Park. These areas support 17 strict endemic species that are not found in the park. Unfortunately, these strict endemics are the most threatened since their habitats are fragmented and degraded as a result of past and present land conversion to subsistence and industrial plantations. Furthermore, these hotspots are the type localities for some rare endemic species that are so far only known from type specimens or from a few collections made in these areas. Contrary to the National Park, these hotspots do not yet have any conservation status per se. However, although the park is a [176]

1237 permanent state forest which is protected by law and should be solely used for forest and wildlife conservation, its boundaries have not been marked, the management plan has not yet been produced and protection is weak. It is, therefore, of urgent need to demarcate its boundary, reinforce its protection, and complete and implement its management plan as soon as possible. Furthermore, in view of the fact that pressure on these fragmented hotspots is likely to increase in the future with the growing human population density, it is suggested that a separate management strategy be developed to ensure the protection of these biodiversity hotspots and their endemic species.

Acknowledgements This study was carried out in the framework of the Campo-Ma’an Biodiversity Conservation and Management Project, Cameroon, and was ﬁnancially supported by Tropenbos International, The Netherlands. We will like to thank G. Achoundong, J.M. Onana, B. Sonke, L. Zapfack and P. Mezili at the National Herbarium, Cameroon, and F.J. Breteler and C.C.H. Jongkind at the Nationaal Herbarium Nederland, Wageningen University Branch, who assisted in plant identiﬁcation. The staﬀ of Campo-Ma’an Project is also acknowledged with gratitude for their assistance and support during the ﬁeldwork. Particular thanks are for my ﬁeld assistants Elad Maurice and Ossele Mathilde for their enthusiastic support and cooperation. We will also like to extend our sincere thanks to all chiefs and village representatives, for their active participation in the organisation and collection of ﬁeld data.

[177]

No. Family

[178]

1

Acanthaceae

2

Annonaceae

3

Annonaceae

4

Apocynaceae

5

Apocynaceae

6

Apocynaceae

7

Apocynaceae

8 9

Araceae Araceae

Species

Guild Star Habit Chorology

Notes

sb

GD Hb

Cam

Akom II, Dipikar Island, Western and South Cameroon

sb

GD Sh

Sw-Cam

sb

GD Sh

Cam

Akom II, Dipikar Island, Massif des Mamelles, Bipindi and Lolodorf Massif des Mamelles, Bipindi and Lolodorf

sb

GD Sh

Cam

Ma’an, South, Centre and East Cameroon

Np

GD Lwcl

Cam

Efoulan, Bipindi, Makak and Mt. Cameroon

sb

BK

Sw-Cam

Campo, Bipindi and Lolodorf

sb

GD Sh

Lg

sb sb

BK He GD Hb

Sw-Cam Cam

Np

GD Swcl

Cam

Northern limit of distribution, from Gabon to Akom II, Onoyong and Ma’an Massif des Mamelles, Dipikar Island, Ma’an and Bipindi Bifa, Zingui, Akom II, Dipikar Island, Bipindi, Mt Cameroon and Eseka Dipikar Island, Ebolowa and Mt. Cameroon

sb

bu

Hb

Lg

Northern limit of distribution, from Gabon to Bipindi, Zingui

sb

bu

Hb

Lg

Northern limit of distribution, from Gabon to Ebianemeyong

sb

bu

Hb

Lg

sb

bu

Hb

Lg

Northern limit of distribution, from Gabon to Bipindi, Zingui and Grand Batanga Northern limit of distribution, from Congo, Gabon to Mvini and Efoulan

10

Aristolochiaceae

11

Balsaminaceae

12

Balsaminaceae

13

Begoniaceae

Stenandrium thomense (Milne-Redh.) Vollesen Monanthotaxis elegans (Engl. and Diels) Verdc. Monodora zenkeri Engl. and Diels* Callichilia monopodialis (K.Schum.) Stapf* Landolphia ﬂavidiﬂora (K. Schum.) Persoon* Petchia africana Leeuwenb.* Tabernaemontana hallei (Boiteau) Leeuwenb. Culcasia bosii Ntepe-Nyame Culcasia panduriformis Engl. and Krause Pararistolochia preussii (Engl.) Hutch. & Dalziel Impatiens hians Hook.f. var. bipindensis (Gilg) Grey- Wilson Impatiens gongolana N.Halle´ Begonia anisosepala Hook.f.

14

Begoniaceae

Begonia clypeifolia Hook.f.

Sh

1238

Appendix 1 List of 141 plant species that are either strictly endemic to the Campo-Ma’an area (only found in Carapo-Ma’an) or near endemic (also occur in the western parts of south Cameroon or other parts of Cameroon).

15

Begoniaceae

16

Begoniaceae

17 18 19

Begoniaceae Begoniaceae Begoniaceae

20

Begoniaceae

21

Burseraceae

22

Burseraceae

23 [179]

24

25

26 27 28 29 30

Begonia mbangaensis Sosef Begonia microsperma Warb. Begonia montis’-elephantis J.J.de Wilde* Begonia zenkeriana Smith and Wassh. Aucoumea klaineana Pierre

Dacryodes buettneri (Engl.) Lam. Capparaceae Ritchiea simplicifolia Oliv. var. Caloneura (Gilg) Kers Celastraceae Pristimera luteoviridis (Exell) N.Halle´ var. kribiana N.Halle´ Chrysobalanaceae Dactyladenia cinera (Engl. ex de Wild) Prance and F.White** Chrysobalanaceae Dactyladenia icondere (Baill.) Prance and F.White Combretaceae Combretum cinnabarinum Engl. and Diels Cyperaceae Hypolytrum sp. nov. ined.* Dichapetalaceae Dichapetalum altescandens Engl. * Dichapetalaceae Dichapetalum cymulosum (Oliv.) Engl.* Dichapetalaceae Dichapetalum librevillense Pellegr.*

bu

Ep

bu

Hb

Lg

Northern limit of distribution, from Gabon to Mvini, Efoulan and around Kom River Lg Northern limit of distribution, from Gabon to Lolabe and around Kribi Sw-Cam Akom II, Efoulan, Bipindi and Lolodorf Cam Ebianemeyong, Ma’an, South-west and South Cameroon Campo-Ma’an Rare species, only known from a small population on Mt d’Ele´phant Sw-Cam Campo, Massif des Mamelles, Dipikar Island, Bipindi and Lolodorf Lg Northern limit of distribution, from Gabon to Ma’an and Ebianemeyong Lg Northern limit of distribution, from Gabon to Ma’an and Ebianemeyong Cam Lobe, Campo, Kienke, Dipikar Island, Bipindi, Lolodorf and Ebolowa Campo-Ma’an Rare species, only known from few collections on Mt d’Ele´phant and Dipikar Island

sb sb sb

BK Hb GD Hb BK Hb

sb

BK

Hb

Pi

bu

Tr

Np

bu

Tr

sb

BK

Sh

Np

BK

Swcl

sb

BK

Tr

Sw-Cam

sb

bu

Sh

Lg

np

bu

Lwcl

sb np

BK bu

Hb Lwcl

np

GD Lwcl

Northern limit of distribution, from Congo, Gabon to Grand Batanga, Campo and Dipikar Island Lg Northern limit of distribution, from Gabon to Bipindi and Dipikar Island Campo-Ma’an New species only known from Mont d’Ele´phant Lg Northern limit of distribution, from Gabon to Efoulan and Zingui Cam Grand Batanga, Campo, Bipindi, Lolodorf and Douala

np

bu

Lg

Lwcl

Rare species, only known from type specimens (Bipindi) and a record from Grand Batanga

Northern limit of distribution, from Gabon to Mt d’Ele´phant and Campo

1239

31

Begonia elaeagnifolia Hook. ep f. Begonia heterochroma Sosef sb

[180]

No. Family

Species

Guild Star Habit Chorology

32

Dichapetalaceae

np

BK

Lwcl

33

Dichapetalaceae

Dichapetalum oliganthum Breteler* Tapura tchoutoi Breteler

sb

BK

Sh

34

Dryopteridaceae

sb

bu

He

35

Ebenaceae

sb

BK

Tr

36

Ebenaceae

sb

Bu

Tr

37

Euphorbiaceae

Sh

38

sb

BK

Gnetaceae

Lastreopsis davalliaeformis (Tardieu) Tardieu* Diospyros alboﬂavescens (Gu¨rke) F.White Diospyros soyauxii Gu¨rke and K. Schum. Afrotrewia kamerunica Pax and Hoﬀm.* Gnetum buchholzianum Engl.

np

GD Hcl

39

Gramineae

Guaduella mildbraedii Pilg.*

sb

BK

Hb

40

Gramineae

pi

bu

Hb

41 42

Guttiferae Guttiferae

Hyparrhenia wombaliensis (Vanderyst ex Robyns) Clayton* Garcinia conrauana Engl. Garcinia densivenia Engl.

Sb ri

GD Tr GD Tr

43

Icacinaceae

Alsodeiopsis zenkeri Engl.

rh

GD Sh

44 45

Icacinaceae Icacinaceae

46

Icacinaceae

Iodes kamerunensis Engl. sb Rhaphiostylis ovalifolia Engl. sb ex Sleumer* Rhaphiostylis subsessilifolia sb Engl.

GD Swcl GD Swcl BK

Swcl

Notes

Grand Batanga, Campo, Mt d’Ele´phant, Kribi, Longi and Lolodorf. Campo-Ma’an Rare species, only known from few collections around Bifa and Dipikar Island Lg Northern limit of distribution, from Gabon to Bipindi and Zingui Sw-Cam Rare species, only known from few collections from Bifa, Zingui and Bipindi Lg Northern limit of distribution, from Gabon to Campo and Zingui Campo-Ma’an Rare species, only known from Massif des Mamelles Sw-Cam

Cam

Dipikar Island, Onoyong, Ma’an, Littoral, South-west and South provinces of Cameroon Campo-Ma’an Rare species, only known from few collections in the Campo area Lg Northern limit of distribution, from Congo to Campo

Cam Cam

Akom II, South-west and South Cameroon Dipikar Island, Ebianemeyong, Mvini, Littoral and South Cameroon Cam Frequent along the Bongola and Ntem rivers, and other rivers in Littoral, East and South Cameroon Cam Akom II, Dipikar Island, Bipindi, Bertoua and Nanga Eboko Cam Coastal forest around Kribi, Grand Batanga, Lolabe, Elabi Massif des Mamelles, Littoral and South Cameroon Campo-Ma’an Rare species, only known from Grand Batanga, Ebianemeyong and Mt d’Ele´phant

1240

Appendix 1 (Continued)

[181]

Ixonanthaceae

48

Lauraceae

49

Lauraceae

50

Lauraceae

51

Lauraceae

52

Lauraceae

53

Leguminosae -Caesalpinioideae Leguminosae -Caesalpinioideae Leguminosae -Caesalpinioideae Leguminosae -Caesalpinioideae Leguminosae -Caesalpinioideae LeguminosaeCaesalpinioideae Leguminosae -Caesalpinioideae Leguminosae -Caesalpinioideae Leguminosae -Caesalpinioideae

54 55 56 57 58 59 60 61

np

bu

Tr

sb

BK

Tr

sb

BK

Tr

Campo-Ma’an Rare species, only known from few records around Grand Batanga

sb

BK

Tr

Sw-Cam

sb

BK

Tr

Sw-Cam

sb

BK

Tr

Sw-Cam

np

bu

Tr

Lg

sb

GD Tr

Cam

np

GD Tr

Cam

sw

bu

Tr

Lg

np

bu

Tr

Lg

ri

bu

Tr

Lg

sb

BK

Tr

Sw-Cam

Gilbertiodendron pachyant- np hum (Harms) J.Le´onard Plagiosiphon longitubus sb (Harms) J.Le´onard

BK

Tr

Sw-Carm

BK

Tr

Sw-Cam

Ochthocosmus calothyrsus (Mildbr.) Hutch. and Dalziel Beilschmiedia cuspida (K. Krause) Robyns and Wilczek Beilschmiedia dinklagei (Engl.) Robyns and Wilczek* Beilschmiedia klainei Robyns and Wilczek Beilschmiedia papyracea (Stapf) Robyns and R.Wilczek Beilschmiedia welczekii Fouilloy Amphimas ferrugineus Pierre ex Pellegr. Anthonotha leptorrhachis (Harms) J.Le´onard Aphanocalyx hedinii (A.Chev.) Wieringa Aphanocalyx ledermannii (Harms) Wieringa Copaifera religiosa J.Le´onard Daniellia klainei A.Chev. Dialium zenkeri Harms

Lg

Northern limit of distribution, from Gabon to Cameroon (frequent in the Campo-Ma’an area) Campo-Ma’an Rare species, only known from Fenda and Akom II

Rare species, only known from few records from Akom II, Ebianemeyong and Bipindi Rare species, only known from Ebianemeyong, Akom II, Fenda and Bipindi Akom II, Mvini, Nkoelon, Dipikar Island, Ebianemeyong, Ma’an, Bipindi and Lolodorf Northern limit of distribution, from Gabon to Dipikar Island, Ma’an, Onoyong and Akom II Bifa, Campo, Dipikar Island, Lobe, Massif des Mamelles, Mt d’Ele´phant, Bipindi, Lolodorf and Mt Cameroon Akom II, Ebianemeyong, Kom, Ma’an, Bipindi and Eseka Northern limit of distribution, occurs along rivers from Gabon, Equatorial Guinea to the Dipikar Island Northern limit of distribution, from Congo to Akom II and Efoulan Northern limit of distribution, from Congo to Akom II, Eoulan and Ma’an Campo, Dipikar Island, Onoyong, Bipindi and Lolodorf Ebianemeyong, Kom, Massif des Mamelles, Bipindi and Lolodorf Akom II, Efoulan, Ma’an, Bipindi, and Lolodorf

1241

47

No. Family

Species

Guild Star Habit Chorology

Notes

62

Plagiosiphon multijugus (Harms) J.Le´onard Tetraberlinia moreliana Aubre´v.* Chlorophytum petrophyllum K.Krause Mostuea neurocarpa Gilg

sb

GD Tr

Cam

Akom II, Dipikar Island, Ma’an, Bipindi and Kribi-Edea areas

sb

bu

Lg

sb

GD Hb

Cam

Northern limit of distribution, from Gabon, Bidou and Mt. D’Ele´phant Bifa, Dipikar Island, Mvini, Littoral and South Cameroon

sb

bu

Sh

Lg

np

BK

Lwcl

ri

GD Tr

np

GD Lwcl

pa

GD Pa

pi

GD Hb

Northern limit of distribution, from Gabon to Bifa, Campo and Dipikar Island Campo-Ma’an Rare species, only known from few collections around Grand Batanga and Lolabe Cam Akom II, Dipikar Island, Ebianemeyong, Onoyong, Bipindi, Lolodorf, Kribi-Edea and South-west Cameroon Cam Dipikar Island, Mvini, Ma’an, Bipindi, Masok, Douala-EdeaKribi areas. Cam Grand Batanga, Bongola, Bipindi, Eseka, Barombi and along the Lokoundje and Nyong rivers. Cam Ma’an, Onoyong and South Cameroon

sb

BK

Hb

Sw-Cam

sb

BK

Hb

sb

BK

Hb

sb

bu

Hb

BK

Sh

64

Leguminosae -Caesalpinioideae Leguminosae -Caesalpinioideae Liliaceae

65

Loganiaceae

66

Loganiaceae

63

67 [182]

68 69 70 71 72 73 74 75

Strychnos canthioides Leeuwenb. * Loganiaceae Strychnos elaeocarpa Gilg ex Leeuwenb. Loganiaceae Strychnos mimﬁensis Gilg ex Leeuwenb. Loranthaceae Tapinanthus preussii (Engl.) Tiegh. Marantaceae Hypselodelphys zenkeriana (K.Schum.) Milne-Redh. Melastomataceae Amphiblemma letouzeyi Jacq.-Fe´l.* Melastomataceae Calvoa calliantha Jacq.-Fe´l. Melastomataceae Calvoa stenophylla Jacq.-Fe´l* Melastomataceae Guyonia tenella Naud.

Melastomataceae Memecylon arcuato-margin- sb atum Gilg ex Engl. var. arcuatomarginatum

Tr

Rare species, only known from few collections recorded on hills around Akom II, Efoulan and Bipindi Sw-Cam Rare species, only known from Ebianemeyong, Akom II and Bipindi Campo-Ma’an Rare species, only known from type specimens collected in Zingui Lg Northern limit of distribution, from Equatorial Guinea to Lobe and Bongola Cam Akom II Dipikar Island, Kom, Mt. D’Ele´phant, Kienke, Longi and Kribi-Edea

1242

Appendix 1 (Continued)

[183]

76

Menispermaceae

77

Menispermaceae

78

Moraceae

79

Moraceae

80

Myrsinaceae

Albertisia glabra (Diels and Troupin) Forman Penianthus camerounensis A.Dekker Dorstenia dorstenioides (Engl.) Hijman and C.C.Berg* Dorstenia involuta M.Hijman Ardisia dolichocalyx Taton

sb

BK

81

Myrtaceae

Eugenia kameruniana Engl.* sb

82

Ochnaceae

83

Ochnaceae

84

Ochnaceae

Campylospermum letouzeyi Farron Campylospermum zenkeri (Engl. ex Tiegh.) Farron Testulea gabonensis Pellegr.

85

Olacaceae

86

Orchidaceae

87

Orchidaceae

88

Orchidaceae

89

Orchidaceae

Swcl

sb

GD Sh

sb

BK

Hb

sb

BK

Hb

sb

GD Hb

Cam

BK

Sh

Cam

sb

GD Sh

Cam

sb

GD Sh

Cam

np

bu

Octoknema dinklagei Engl.

sb

GD Tr

Bulbophyllum alinae Szlachetko* Corymborkis minima P.J.Cribb* Podandriella batesii (la Croix) Szlachetko and Olszewski* Polystachya letouzeyana Szlachetko and Olszewski*

ep

BK

sb

GD Hb

sb

BK

Hb

ep

BK

Ep

Tr

Ep

Sw-Cam

Rare species, only known from Dipikar Island and Bipindi

Cam

Afan, Akom II, Dipikar Island, Ebianemeyong, Mekok, Littoral, South and South-west Cameroon Campo-Ma’an Rare species, only known from few collection around Kienke and Fenda Campo-Ma’an Rare species, only known from Dipikar Island and Ma’an Bifa, Campo, Dipikar Island, Onoyong, Littoral, South and South-west Cameroon Rare species, only known from Ebianemeyong, Ma’an, Nyabissan Dipikar Island and South Cameroon

Campo, Massif des Mamelles, Kribi-Edea and South Cameroon Lg Northern limit of distribution, from Gabon to Dipikar Island, Ma’an and Onoyong Cam Akok, Grand Batanga, Lolabe, South and South-west Cameroon Campo-Ma’an Rare species, only known from few collections on Mt d’Ele´phant Cam Rare species, only known from few collections around Campo, Lolabe and Korup National Park Campo-Ma’an Rare species, only known from Akom II, Efoulan and Ebianemeyong Campo-Ma’an Rare species, only known from Efoulan

1243

No. Family 90

91 92 93 94 [184]

95 96 97 98 99 100

101 102

Orchidaceae

Species

Vanilla africana Lindley subsp. cucullata (Kraenzlin and K. Shum.) Szlachetko and Olszewski * Podostemaceae Ledermanniella annithomae C. Cusset* Podostemaceae Ledermanniella batangensis (Engl.) C. Cusset* Podostemaceae Ledermanniella bosii C.Cusset Podostemaceae Ledermanniella boumiensis C. Cusset Podostemaceae Ledermanniella kamerunensis (Engl.) C. Cusset Podostemaceae Ledermanniella linearifolia Engl. Podostemaceae Ledermanniella variabilis (G.Taylor) C.Cusset Rhizophoraceae Cassipourea kamerunensis (Engl.) Alston Rhizophoraceae Cassipourea zenkeri (Engl.) Alston Rubiaceae Chazaliella sciadephora (Hiern) Petit and Verdc, var. condensata Verdc. Rubiaceae Ecpoma apocynaceum K.Schum. Rubiaceae Hymenocoleus glaber Robbr.

Guild Star Habit Chorology

Notes

np

BK

Hcl

Sw-Cam

Campo, Massif des Mamelles, Mt d’Ele´phant and Bipindi

rh

BK

Hb

Campo-Ma’an Rare species, only known from Memve’ele water falls

rh

BK

Hb

Campo-Ma’an Rare species, only known from Lobe water falls

rh

BK

Hb

rh

bu

Hb

rh

BK

Hb

rh

GD Hb

rh

GD Hb

sb

GD Sh

Campo-Ma’an Rare species, only known from the Ntem Basin, Bongola, Lobe and Memve’ele waterfalls Lg Northern limit of distribution, from Gabon to the Bongola and Memve’ele water falls Campo-Ma’an Rare species, only known from the Bongola water falls in Dipikar Island Cam Lobe and Bongola falls in the Campo-Ma’an area, and in the Nkam river in Yabassi Cam Bongola and Lobe water falls, and in Mamfe river in Southwest Cameroon Cam Akom II, Littoral and South Cameroon

sb

GD Sh

Cam

sb

GD Sh

Cam

Akom II Bifa, Ebianemeyong, Eboundja, Lobe, Ma’an, Bipindi, Lolodorf and South Cameroon Mvini, Onoyong, Ma’an, Littoral and South Cameroon

pi

BK

Sw-Cam

Rare species, only known from Bifa, Zingui and Bipindi

sb

GD Hb

Cam

Akom II, Dipikar Island, Massif des Mamelles, Mvini, Littoral, South and South-west Cameroon

Sh

1244

Appendix 1 (Continued)

[185]

103

Rubiaceae

104 105

Rubiaceae Rubiaceae

106

Rubiaceae

107 108

Rubiaceae Rubiaceae

109

Rubiaceae

110

Rubiaceae

111

Rubiaceae

112

Rubiaceae

113

Rubiaceae

114

Rubiaceae

115

Rubiaceae

116

Rubiaceae

117

Rubiaceae

118

Rubiaceae

lxora aneimenodesma K.Schum. subsp. aneimenodesma Ixora synactica De Block* Oxyanthus oliganthus K.Schum. Pavetta camerounensis S.Manning subsp. camerounensis Pavetta kribiensis J.Manning Pavetta mpomii S.Manning

GD Sh

Cam

Akom II, Dipikar Island, Bipindi and Lolodorf

sb sb

BK Sh GD Sh

Sw-Cam Cam

Rare species, only known from Efoulan, Zingui and Bipindi Akom II, Ma’an and South Cameroon

sb

GD Sh

Cam

Akom II, Bifa, Campo, Dipikar Island, Massif des Mamelles, Mt d’Ele´phant, Littoral and South Cameroon

sb sb

BK BK

Sw-Cam Sw-Cam

sb

GD Sh

Cam

Rare species, only known from Mvini, Bipindi and Lolodorf Mt d’Ee´lephant, Mvini, Nkoelon, Ebianemeyong, Bipindi and Lolodorf Dipikar Island, Mvini, Nkoelon and South Cameroon

np

GD Hb

Cam

sb

BK

Sh

Campo-Ma’an

sb

BK

Sh

Campo-Ma’an

sb

GD Sh

Cam

ri

BK

Sh

Campo-Ma’an

sb

BK

Sh

Sw-Cam

sb

BK

Sh

Campo-Ma’an

sb

GD Sh

Cam

sb

GD Sh

Cam

Sh Sh

Ebianemeyong, Nyabissan, Ma’an, Centre and South Cameroon Rare species, only known from few collections around Grand Batanga Rare species, only known from few collections around Grand Batanga Akom II, Bifa, Ma’an, Bipindi, Lolodorf, Centre and South Cameroon Rare species, only known from few collections from Grand Batanga and Lobe Rare species, only known from Akom II, Onoyong, Bipindi and Lolodorf Rare species, only known from few collections around Grand Batanga Akok, Bifa, Campo, Dipikar Island, Kom, Mvini and South Cameroon Akom II, Dipikar Island, Massif des Mamelles, Mvini, and South Cameroon

1245

Pavetta staudtii Hutch. and Dalziel Pseudosabicea medusula (K.Schum.) N.Halle´ Psychotria aemulans K. Schum.** Psychotria batangana K. Schum.* Psychotria camerunensis Petit Psychotria dimorphophylla K. Schurm.* Psychotria lanceifolia K.Schum. Psychotria oligocarpa K.Schum.* Psychotria sadebeckiana K.Schum.var. elongata Petit Psychotria sadebeckiana K.Scham. var. sadebeckiana

sb

No. Family

Guild Star Habit Chorology

Notes

sb

GD

Sh

Cam

sb

GD

Sh

Cam

Dipikar Island, Massif des Mamelles, Centre and South Cameroon Ebianemeyong, Mvini, Centre and South Cameroon

sb

GD

Swcl

Cam

Mvini, Nkoelon, Centre and South Cameroon

sb

BK

Sh

Campo-Ma’an Rare species, only known from few collections around Campo

sb

BK

Sh

sb

bu

Sh

Campo-Ma’an Rare species, only known from Bifa, Massif des Mamelles and Dipikar Island Lg Northern limit of distribution, from Gabon to Dipikar Island

sb

GD

Sh

Cam

BK

Sh

BK

Tr

128

Scytopetalaceae Rhaptopetalum sessilifoIium sb Engl.* Sterculiaceae Cola ﬁbrillosa Engl. and sb Krause Sterculiaceae Cola letouzeyana Nkongm. sb

GD

Sh

129

Sterculiaceae

sb

GD

Sh

130

Sterculiaceae

sb

BK

Sh

131

Sterculiaceae

sb

BK

Sh

132

Sterculiaceae

sb

BK

Sh

119 120 121 122 123 124 [186]

125 126 127

Species

Rubiaceae

Tricalysia amplexicaulis Robbr. Rubiaceae Tricalysia talbotii (Wemham) Keay Rubiaceae Vangueriella laxiﬂora (K.Schum.) Verdc. Sapindaceae Deinbollia macroura Gilg ex Radlkofer* Sapindaceae Deinbollia mezilii D.W.Thomas and D.J.Harris Sapindaceae Deinbollia pycnophylla Gilg ex Radlk. Scytopetalaceae Pierrina zenkeri Engl.

Cola praeacuta Brenan and Keay Scaphopetalum acuminatum Engl. and K. Krause* Scaphopetalum brunneo-purpureum Engl. and K. Krause** Scaphopetalum zenkeri K-Schum.

Bifa, Campo, Ebianemeyong, Ma’an, Nyabissan, Littoral and South Cameroon Sw-Cam Rare species, only known from few collections around Efoulan and Bipindi Sw-Cam Rare species, only known from few collections around Dipikar Island and Bipindi Cam Akora II, Dipikar Island, Ebianemeyong, Onoyong, Centre and South Cameroon Cam Bifa, Dipikar Island, Massif des Mamelles, South and Southwest Cameroon Carapo-Ma’an Rare species, only known from few collections from Efoulan and Fenda Campo-Ma’an Rare species, only known from few collections from Fenda and Zingui Sw-Cam

Akom II, Dipikar Island, Ebianemeyong, Bipindi and Lolodorf

1246

Appendix 1 (Continued)

133

Thymelaeaceae

134

Urticaceae

135

Violaceae

136

Violaceae

137 138

Dicranolepis glandulosa H.H.W.Pearson Urera gravenreuthi Engl.

sb

GD

Sh

pi

GD

Hcl

sb

BK

Sh

[187]

sb

BK

Sh

Violaceae Violaceae

Allexis zygomorpha Achoundong and Onana* Rinorea campoensis M. Brandt ex Engl. Rinorea microglossa Engl.* Rinorea sp. nov. 1 ined.*

sb sb

BK GD

Sh Sh

139

Violaceae

Rinorea sp. nov. 2 ined.*

sb

GD

Sh

140

Zingiberaceae

Sb

BK

Hb

141

Zingiberaceae

Aulotandra kamerunensis Loes. Renealmia densispica Koechlin

Sb

BK

Hb

Cam

Akom II, Dipikar Island, Grand Batanga, Campo, Littoral South, and South-west Cameroon Cam Dipikar Island, Ma’an, Littoral, South and South-west Cameroon Cam Coastal forest between Edea and Campo, Bidou, Akok, Longi, Bipindi and Lolodorf Campo-Ma’an Rare species, only known from Campo, Dipikar Island, Lobe and Massif des Mamelles Sw-Cam Efoulan, Bipindi, Lolodorf, Centre and South Cameroon Cam Coastal forest between Kribi and Campo, Dipikar Island, and Douala-Edea-Kribi regions Cam Kienke, Massif des Mamelles, Dipikar Island, Kribi, KribiEdea, Douala- Yaounde, and Eseka regions Sw-Cam Rare species, only known from few collections from Ebianemeyong, Nyabissan and Bipindi Sw-Cam Rare species, only known from few collections from Dipikar Island, Ebianemeyong and Ambam

Those species that reach their northern or southern limit of distribution in the Campo-Ma’an area are also included in the list. *Species strictly endemic to the Campo-Ma’an area that were not recorded in the National Park. **Species for which the status or range needs more investigation. Guild: ep, epiphyte; np, non-pioneer light demanding; pi, pioneer; rh, rheophyte; ri, riverine; sb, shade-bearer; and sw, swamp. Star: as deﬁned in Table 1. Habit: Ep, epiphyte; Hb, herb; Hcl, herbaceous climber; He, hemi-epiphyte; Lwcl, large woody climber; Swcl, small woody climber; Pa, parasite; Sh, shrub; and Tr, tree. Chorology: Campo-Ma’an, strict endemic to Campo-Ma’an; Sw-Cam, endemic to southwestern part of Cameroon; Cam, endemic to Cameroon; Lg, Lower Guinea endemic (especially those species that reach either their northern or southern limit of distribution in the Campo-Ma’an area).

1247

[188]

No. Family

Species

Guild Habit Chorology IUCN/WCMC

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Afroﬁttonia silvestris Lindau Sclerochiton preussii (Lindau) C.B.Clarke Antrocaryon micraster A. Chev. and Guillaum. Trichoscypha bijuga Engl. Trichoscypha mannii Hook. f. Boutiquea platypetala Le Thomas Pachypodanthium barteri (Benth.) Hutch. and Dalziel Uvariastrum zenkeri Engl. and Diels Uvariodendron connivens (Benth.) R.E.Fr. Tylophora cameroonica N.E.Br. Cordia platythyrsa Baker Aucoumea klaineana Pierre Dacryodes igaganga Aubrev. And Pellegr. Salacia lehmbachii Loes. var. pes-ranulae N.Halle´ Dactyladenia cinera (Engl. ex de Wild) Prance and F.White Terminalia ivorensis A.Chev. Hemandradenia mannii Stapf Diospyros barteri Hiern Diospyros crassiﬂora Hiern Amanoa strobilacea Mu¨ll.Arg. Crotonogyne manniana Mu¨ll.Arg. Drypetes preussii (Pax) Hutch. Drypetes tessmanniana (Pax) Pax and K.Hoﬀm. Neoboutonia mannii Benth. Pseudagrostistachys africana (Mu¨ll.Arg.) Pax and K.Hoﬀm. Garcinia brevipedicellata (Baker f.) Hutch. and Dalziel Garcinia kola Heckel Garcinia staudtii Engl. Hoplestigma pierreanum Gilg Afrostyrax kamerunensis Perkins and Gilg

sb sb pi sb sb sb sw sb sb pi pi pi np np sb np sb sb sb sb sb sb sb pi sb sb sb sb np sb

Acanthaceae Acanthaceae Anacardiaceae Anacardiaceae Anacardiaceae Annonaceae Annonaceae Annonaceae Annonaceae Asclepiadaceae Boraginaceae Burseraceae Burseraceae Celastraceae Chrysobalanaceae Combretaceae Connaraceae Ebenaceae Ebenaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Guttiferae Guttiferae Guttiferae Hoplestigmataceae Huaceae

Hb Hb Tr Tr Tr Sh Tr Sh Tr Swcl Tr Tr Tr Swcl Tr Tr Tr Tr Tr Sh Sh Tr Sh Tr Tr Tr Tr Tr Tr Tr

Lg Lg Lg Lg Lg Lg Lg Lg Lg Lg Gc Lg Lg Lg Sw-Cam Gu Lg Gu Gc Gu Lg Lg Lg Gu Lg Lg Gc Lg Lg Lg

VU A1c + 2c EN B1 + 2e VU A1cd CR A1c + 2abc VU A1C, B1 + 2c EN A1c + 2c VU A1c VU A1c, B1 + 2c LR/nt LR/nt VU A1d VU A1cd VU A1cd + 2cd VU B1 + 2c CR B1 + 2c VU A1cd LR/nt VU A1c EN A1d VU A1c, B1 + 2c LR/nt VU B1 + 2c CR A1c + 2c LR/nt VU A1c, B1 + 2c VU A1c, B1 + 2c VU A1cd VU A1c, B1 + 2c CRA1c + 2c VU A1c, B1 + 2c

1248

Appendix 2 IUCN (1994) threat categories for 92 plant species recorded in the Campo-Ma’an area that are listed in The IUCN (2002) Red List of Threatened Species and The World List of Threatened Trees (WCMC 1998).

[189]

Huaceae Irvingiaceae Irvingiaceae Leguminosae-Caesalpinioideae Leguminosae-Caesalpinioideae Leguminosae-Caesalpinioideae Leguminosae-Caesalpinioideae Leguminosae-Caesalpinioideae Leguminosae-Caesalpinioideae Leguminosae-Caesalpinioideae Leguminosae-Caesalpinioideae Leguminosae-Caesalpinioideae Leguminosae-Caesalpinioideae Leguminosae-Caesalpinioideae Leguminosae-Caesalpinioideae Leguminosae-Caesalpinioideae Leguminosae-Caesalpinioideae Leguminosae-Caesalpinioideae Leguminosae-Mimosoideae Leguminosae-Mimosoideae Leguminosae-Mimosoideae Leguminosae-Papilionoideae Leguminosae-Papilionoideae Leguminosae-Papilionoideae Leguminosae-Papilionoideae Liliaceae Melastomataceae Melastomataceae Melastomataceae Meliaceae Meliaceae Meliaceae Meliaceae Meliaceae

Afrostyrax lepidophyllus Mildbr. Irvingia excelsa Mildbr. Irvingia gabonensis (Aubry-Lecomte ex O’Rorke) Baill. Afzelia bipindensis Harms Afzelia pachyloba Harms Anthonotha leptorrhachis (Harms) J.Le´onard Aphanocalyx hedinii (A.Chev.) Wieringa Daniellia klainei A.Chev. Daniellia oblonga Oliv. Dialium bipindense Harms Dialium tessmannii Harms Didelotia unifoliolata J.Le´onard Gilbertiodendron pachyanthum (Harms) J.Le´onard Guibourtia ehie (A. Chev.) J. Le´onard Loesenera talbotii Baker f. Pellegriniodendron diphyllum (Harms) J.Le´onard Plagiosiphon longitubus (Harms) J.Le´onard Swartzia ﬁstuloides Harms Calpocalyx heitzii Pellegr. Calpocalyx letestui Pellegr. Calpocalyx ngouniensis Pellegr. Craibia atlantica Dunn Millettia laurentii De Wild. Millettia macrophylla Benth. Ormocarpum klainei Tisser. Chlorophytum petrophyllum K.Krause Memecylon candidum Gilg Memecylon dasyanthum Gilg ex Lederman and Engl. Warneckea wildeana Jacq.-Fe´l. Entandrophragma angolense (Welw.) C.DC. Entandrophragma candollei Harms Entandrophragma cylindricum (Sprague)Sprague Entandrophragma utile (Dawe and Sprague) Sprague Guarea cedrata (A.Chev.) Pellegr.

sb np np np np sb np ri np np sb sb np np sb sb sb sb np sb sb sb np pi sb sb sb sb sb np np np np np

Tr Tr Tr Tr Tr Tr Tr Tr Tr Tr Tr Tr Tr Tr Tr Tr Tr Tr Tr Tr Tr Tr Tr Tr Sh Hb Sh Tr Sh Tr Tr Tr Tr Tr

Lg Gc Gc Gc Gc Cam Cam Lg Lg Lg Lg Lg Sw-Cam Gc Lg Gu Sw-Cam Gc Lg Gc Gc Gc Gc Lg Lg Cam Lg Lg Lg Tra Gc Gc Gc Gc

VU A1c, B1 + 2c LR/nt LR/nt VU A1cd VU A1d CR A1c + 2c CR B1 + 2abcd, C1 + 2ab LR/nt VU A1c LR/nt LR/nt LR/nt VU D2 VU A1c VU A1c, B1 + 2c LR/nt CR A1 + 2c EN A1cd VU A1c, B1 + 2c VU D2 VU A1c VU A1c EN A1cd VU A1c, B1 + 2c CR A1c CR A1c + 2c VU B1 + 2c VU B1 + 2c VU D2 VU A1cd VU A1 cd VU A1cd VU A1cd VU A1c

1249

31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64

[190]

No.

Family

Species

Guild

Habit

Chorology

IUCN/WCMC

65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92

Meliaceae Meliaceae Meliaceae Meliaceae Meliaceae Moraceae Myrtaceae Ochnaceae Ochnaceae Rhizophoraceae Rubiaceae Rubiaceae Rutaceae Sapotaceae Sapotaceae Sapotaceae Sapotaceae Simaroubaceae Sterculiaceae Sterculiaceae Sterculiaceae Sterculiaceae Sterculiaceae Sterculiaceae Sterculiaceae Sterculiaceae Violaceae Violaceae

Guarea thompsonii Sprague and Hutch. Khaya anthotheca (Welw.) C. DC. Khaya ivorensis A.Chev. Lovoa trichilioides Harms Turraeanthus africanus (Welw. ex C DC.) Pellegr. Milicia excelsa (Welw.) C.C.Berg Eugenia kameruniana Engl. Lophira alata Banks ex Gaertn.f. Testulea gabonensis Pellegr. Anopyxis klaineana (Pierre) Engl. Hallea stipulosa (DC.) Leroy Nauclea diderrichii (De Wild. And T.Durand) Merrill Vepris heterophylla Letouzey Autranella congolensis (De Wild.) A.Chev. Baillonella toxisperma Pierre Gluema ivorensis Aubre´V. and Pellegr. Tieghemella africana Pierre Nothospondias staudtii Engl. Cola hypochrysea K.Schum. Cola philipijonesii Brenan and Keay Cola praeacuta Brenan and Keay Cola semecarpophylla K.Schum. Mansonia altissima (A.Chev.) A.Chev. var. kamerunica Jacq.-Fe´l. Pterygota bequaertii De Wild. Pterygota macrocarpa K.Schum. Sterculia oblonga Mast. Allexis cauliﬂora (Oliv.) Pierre Allexis obanensis (Baker f.) Melchior

np np np np sb pi sb pi np np sw pi sb np np np np np sw sb sb sb np np np pi sb sb

Tr Tr Tr Tr Tr Tr Sh Tr Tr Tr Tr Tr Sh Tr Tr Tr Tr Tr Tr Sh Sh Sh Tr Tr Tr Tr Sh Sh

Gc Gc Gc Gc Gc Tra Cam Gc Lg Gc Gc Gc Gc Gc Lg Gc Lg Gc Lg Lg Cam Lg Gu Gc Gc Gc Lg Lg

VU A1c VU A1cd VU A1cd VU A1cd VU A1cd LR/nt CR A1c VU A1cd EN A1cd VU A1cd VU A1cd VU A1cd EN A1c, B1 + 2c CR AIcd VU A1cd VU B1 + 2c EN A1cd VU B1 + 2c VU A1c EN B1 + 2c CR A1c + 2c LR/cd EN A1cd VU A1cd VU A1cd VU A1cd VU A1c, B1 + 2c VU B1 + 2c

NB: Guild, habit and chorology categories as deﬁned in Appendix 1.

1250

Appendix 2 (Continued)

1251 References Aubre´ville A. and Leroy J.-F. (eds) 1961–1992. Flore du Gabon. Muse´um National d’Histoire Naturelle, Paris. Aubre´ville A. and Leroy J.-F. (eds) 1963–2000. Flore du Cameroun, vol. 1–20. Muse´um National d’Histoire Naturelle, Paris. Barbault R. and Sastrapradja S. 1995. Generation, maintenance and loss of biodiversity. In Heywood V.H. and Watson R.T. (eds), Global Biodiversity Assessment. Cambridge University Press, UNEP, pp. 192–294. Cable S. and Cheek M. 1998. The plants of Mount Cameroon. A conservation checklist. Royal Botanic Gardens, Kew. Cusset C. 1987. Flore du Cameroun. In: Satabie´ B. and Morat Ph. (eds), Podostemaceae, vol. 30. Muse´um National d’Histoire Naturelle, Paris. Davis S.D., Heywood V.H. and Hamilton A.C. 1994. Centres of Plant Diversity. A Guide and Strategy for their Conservation. WWF, IUCN. de Kam M., Fines J.-P. and Akogo G. (eds) 2002. Sche´ma Directeur pour le developpement de l’Unite´ Technique Ope´rationnelle de Campo-Ma’an, Cameroun. Campo-Ma’an Series 1, . Djama T. 2001. Inventaire quantitatif des poissons dans l’UTO Campo-Ma’an. Projet CampoMa’an, Kribi, Cameroon. ERE De´veloppement 2002. Etude socio-e´conomique dans l’UTO de Campo-Ma’an. Rapport ﬁnal phase 2: re´sultats d’e´nquetes aupre´s des me´nages. SNV/Projet Campo-Ma’an. Foahom B. and Jonkers W.B.J. 1992. A Programme for Tropenbos Research in Cameroon. Final report. Tropenbos-Cameroon Programme (Phase I). The Tropenbos Foundation, Wageningen. Franqueville A. 1973. Atlas regional Sud-Ouest 1. Re´publique du Cameroun. ORSTOM, Yaounde´, Cameroun. Gartlan J.S. 1989. La conservation des ecosystemes forestiers du Cameroun. IUCN. Hamilton A.C. 1982. Environmental History of Africa: A Study of the Quaternary. Academic Press, London. Hawks worth D.L. and Kalin-Arroyo M.T. 1995. Magnitude and distribution of biodiversity. In: Heywood V.H. and Watson R.T. (eds), Global Biodiversity Assessment. UNEP, Cambridge University Press, Cambridge, pp. 108–191. Hawthorne W.D. 1996. Holes and the sums of parts in Ghanian forest: regeneration, scale and sustainable use. Proc. R. Soc. Edin. 104: 75–176. Hawthorne W.D. and Abu-Juam M. 1995. Forest protection in Ghana with particular reference to vegetation and plant species. The IUCN Forest Conservation Programme. Heywood V.H. and Waston R.T. 1995. Global Biodiversity Assessment. UNEP, Cambridge University Press, Cambridge. ILWIS 2001. ILWIS 3.0 Academic: User’s Guide. ITC, Enschede. Isaaks E.H. and Srivastava R.M. 1989. An Introduction to Applied Geostatistics. Oxford University Press, New York. IUCN 1994. IUCN Red List Categories. IUCN, Gland. IUCN 2002. 2002 IUCN Red list of Threatened Species. IUCN Conservation Monitoring Centre, Cambridge. Keay R.W.J. and Hepper F.N. (eds) 1954. Flora of West Tropical Africa. 2nd edn., 3 vols. Crown Agents, London. Lebrun J.P. and Stork A.L. 2003. Tropical African ﬂowering plants-ecology and distribution, vol. 1. Annonaceae-Balanitaceae. Conservatoire et Jardin Botanique de la Ville de Gene´ve. Letouzey R. 1968. Etude phytogeographique du Cameroun. Le Chevalier, Paris. Letouzey R. 1985. Notice de la carte phytoge´ographique du Cameroun, vol. 1–5. Institut de la Carte Internationale de la Ve´ge´tation, Toulouse. Maley J. 1987. Fragmentation de la foreˆt dense humide Africaine et extention des biotopes montagnards du Quaternaire recent. Paleoecol. Afr. 18: 307–309.

[191]

1252 Maley J. 1989. Late Quaternary climatic changes in the African rainforest: the question of forest refuges and the major role of sea surface temperature variations. In Lewen M. and Sarthein M. (eds), Paleoclimatology and Paleometeolorogy: Modern and Past Patterns of Global Atmospheric Transport. Kluwer, London, pp. 585–616. Maley J. 1990. Histoire re´cente de la foreˆt dense humide africaine: essai sur le dynamisme de quelques formations forestie`res. In: Lanfranchi R. and Schwartz D. (eds), Paysage quaternaire de l’afrique centrale Atlantique pp.367–382. Maley J. 1993. The climatic and vegetational history of the equatorial regions of Africa during the upper Quaternary. In: Shaw T., Sinclair P., Andah B. and Okpoko A. (eds), The Archeology of Africa: Food, Metals and Towns, pp. 43–52. Maley J. 1996. Le cadre pale´oenvironnemental des refuges forestiers africains : quelques donne´es et hypothe´ses. In: der Maesen L.J.G., der Burgt X.M. and de Rooy J.M. (eds), The Biodiversity of African Plants. Kluwer Academic Publishers, Dordrecht, pp. 519–535. Matthews A. and Matthews A. 2000. Primate Population and Inventory of Large and Medium Sized Mammals in the Campo-Ma’an Project Area in Southwest Cameroon, including Management Recommendations. Projet Campo-Ma’an, Kribi, Cameroun. Muller J.P. 1979. Carte des sols du Cameroun. Atlas de la Re´publique Unie du Cameroun. Myers N. 1988. Threatened biotas ‘hotspots’ in tropical forests. Environmentalist 8: 187–208. Myers N., Mittermeir R.A., Mittermeir C.G., da Fonseca G.A.B and Kent J. 2000. Biodiversity hotspots for conservation priorities. Nature 403: 853–858. Pebesma E.J. and Wesseling C.G. 1998. GSTAT: a program for geostatistical modelling, prediction and simulation. Comput. Geosci. 24: 17–31. R Development Core Team 2002. The R Environment for Statistical Computing and Graphics: Reference Index. The R Foundation for Statistical Computing, Vienna. Version 1.6.2. Satabie´, B. and Leroy J.-F. 1980. Flore du Cameroun, vol. 21–28. Muse´um National d’Histoire Naturelle, Paris. Satabie´ B. and Morat Ph. 1986–2001. Flore du Cameroun, vol. 29–37. Muse´um National d’Histoire Naturelle, Paris. Sosef M.S.M. 1994. Refuge Begonias. Taxonomy, phylogeny and historical biogeography of Begonia sect. Loasibegonia and sect. Scutobegonia in relation to glacial rain forest refuges in Africa. PhD Thesis, Wageningen Agricultural University. Sosef M.S.M. 1996. Begonias and African rain forest refuges : general aspects and recent progress. In: der Maesen L.J.G., der Burgt X.M. and de Rooy J.M. (eds), The Biodiversity of African Plants. Kluwer Academic Publishers, Dordrecht, pp. 602–611. Tchouto P., Pouakouyou D. and Acworth J. 1998. Rapid Botanical Survey methodology. Technical report to DFID/Mount Cameroon Project. Limbe Botanic Garden and Herbarium. Tchouto M.G.P. 2004. Plant diversity in a Central African rain forest: impliﬁcations for biodiversity conservation in Cameroon. Phd Thesis, Wageningen University. Thomas D.W. and Thomas J.C. 1993. Botanical and ecological survey of the Campo-Ma’an area. A report to the World Bank, Washington. Van Gemerden B.S. and Hazeu G.W. 1999. Landscape ecoloﬁcal survey (1:100,000) of the BipindiAkom II-Lolodorf region, Southwest Cameroon. Tropenbos-Cameroon Document 1. Vivien J. 1991. Faune du Cameroun. Guide des mammife´res et poisons. GICAM, Cameroun. WCMC 1998. The World List of Threatened Trees. World Conservation Press, . Webster R. and Oliver M.A. 2001. Geostatistics for Environmental Scientists. Wiley & sons, Chichester. White F. 1979. The Guineo-Congolian region and its relationships to other phytochoria. Bull. Jard. Nat. Belg./Bull. Nat. Plant. Belg. 49: 11–55. White F. 1983. The Vegetation of Africa. UNESCO, Paris. Williams P.H. 1993. Measuring more of biodiversity for chosing conservation areas, using taxonomic relatedness. In: Moon T.-Y. (ed.), International Symposium on Biodiversity and Conservation. Korean Entomological Institute, Seoul, pp. 199–227.

[192]

Biodiversity and Conservation (2006) 15:1253–1270 DOI 10.1007/s10531-005-0772-x

Springer 2006

-1

Tree diversity in western Kenya: using proﬁles to characterise richness and evenness R. KINDT1,*, P. VAN DAMME2 and A.J. SIMONS1 1

ICRAF, PO Box 30677-00100, Nairobi, Kenya; 2Ghent University, Laboratory of Tropical and Subtropical Agriculture and Ethnobotany, Coupure Links 653, B-9000 Gent, Belgium; *Author for correspondence (e-mail: [email protected]; phone: 254-2-524000 or 1-650-8336645; fax: 254-2524001 or 1-650-8336646) Received 18 May 2004; accepted in revised form 7 January 2005

Key words: Accumulation, Agroforestry, Diversiﬁcation, Domestication, Evenness, Rarefaction, Re´nyi diversity proﬁle, Richness Abstract. Species diversity is a function of the number of species and the evenness in the abundance of the component species. We calculated diversity and evenness proﬁles, which allowed comparing the diversity and evenness of communities. We applied the methodology to investigate diﬀerences in diversity among the main functions of trees on western Kenyan farms. Many use-groups (all trees and species that provide a speciﬁc use) could not be ranked in diversity or evenness. No usegroup had perfectly even distributions. Evenness could especially be enhanced for construction materials, fruit, ornamental, ﬁrewood, timber and medicine, which included some of the most species-rich groups of the investigated landscape. When considering only the evenness in the distribution of the dominant species, timber, medicine, fruit and beverage ranked lowest (>60% of trees belonged to the dominant species of these groups). These are also use-groups that are mainly grown by farmers to provide cash through sales. Since not all communities can be ranked in diversity, studies that attempt to order communities in diversity should not base the ordering on a single index, or even a combination of several indices, but use techniques developed for diversity ordering such as the Re´nyi diversity proﬁle. The rarefaction of diversity proﬁles described in this article could be used in studies that compare results from surveys with diﬀerent sample sizes.

Introduction One of the objectives of tree domestication research, in general and more speciﬁc, in western Kenya is the diversiﬁcation of tree species composition in agroecosystems (Kindt and Lengkeek 1999; Kindt et al. 2004). In the realm of agroforestry, underpinning the need for diversiﬁcation is the desire to enhance the stability and productivity of agroecosystems (ICRAF 1997; Atta-Krah et al. 2004). Diversity means diﬀerent things to diﬀerent people. Most often in natural or agricultural systems, species counts (species richness) are provided as the measure of diversity. Continuing this logic, diversiﬁcation means adding more species. Species diversity, however, is a function of the number of species, and the evenness in distribution of species’ abundances (Magurran 1988; Purvis and Hector 2000). Options for diversiﬁcation can therefore be dissociated into interventions that target richness and those that target evenness. [193]

1254 We investigated the diversity of various groups of trees that contributed to similar service or production functions on farms in western Kenya, as our target was diversiﬁcation within these functions, and not of overall diversity. Since heterogeneity in characteristics of species results in saturating eﬀects of increased diversity on ecosystem functioning (e.g., Hector et al. 1999; Loreau et al. 2001; Tilman et al. 2001), we expect larger eﬀects from increasing diversity within communities of lower diversity. Ranking of use-groups in diversity, therefore, allows prioritising their scope for diversiﬁcation measured as the average expected eﬀect of adding one species. In addition, such approaches provide the opportunity to model eﬀects of replacement, substitution and expansion at ﬁxed and varying tree densities. Appropriate techniques for measuring diversity and evenness were used in this article. Single indices of diversity or evenness can result in wrong interpretation since not all communities can be ranked in diversity or evenness, whereas they can always be ranked on the basis of a single index (Taillie 1979; To´thme´re´sz 1995; Ricotta and Avena 2002; Ricotta 2003). Since diversity research should not be based on single indices of diversity or evenness, techniques for diversity and evenness ordering were used that produce diversity and evenness proﬁles.

Material and methods Study area Complete tree inventories were made on 201 stratiﬁed-randomly selected farms (taken to mean all land managed by a single household) in the Vihiga and Kakamega districts of western Kenya. The study area is inhabited predominantly by the Luhya (Luyia) ethnic group and belongs to the same agroecological zone where altitude ranges 1500–1800 m above sea level, annual mean temperature ranges 18.1–20.4 C, and annual bimodal rainfall ranges 1600– 2000 mm (Jaetzhold 1982). Four villages were selected within the area, each located in a diﬀerent stratum that mainly diﬀered in farm sizes and arrangement of woody biomass in the landscape (Bradley et al. 1985; Bradley 1991). The selection of villages coincided with a gradient towards the species-rich Kakamega Forest National Reserve.

Information recorded on tree species All trees (woody perennials) were censused using Beentje (1994) as the key reference. For each tree species encountered on a farm, its abundance (the total number of trees) and uses (see below) were recorded by participatory interviews with household informants involving farm walks, tree counting by the interviewer and data recording on a species-by-species basis. [194]

1255 Households listed all the products or services (uses) that are provided by the diﬀerent species encountered on their farm. Free responses were obtained on tree uses (primary and all secondary uses) that were postcoded during data entry and checking. In total, 60 use categories were recorded, but analyses were only conducted for the 12 use categories that occurred on more than 20% of farms. Because it is possible that some informants could have forgotten some uses of particular species, information was adjusted (increasing species–farm-use combinations from 6859 to 7526) by always including all trees of a species in a use-group if more than 50% of farmers and minimum ﬁve farmers with the species mentioned the use. Use-groups were deﬁned as all the trees encountered in the survey that provided one particular type of use. These use-groups were analysed by matrices with as rows the information collected on a particular farm and as columns the various species encountered. Each cell of a use-group matrix provides the number of trees of each species that was used for a particular function on a particular farm. Diversity and evenness proﬁles The Re´nyi diversity proﬁle is one of the techniques for diversity ordering that were speciﬁcally designed to rank communities from low to high diversity. Re´nyi diversity proﬁle values (Ha) are calculated from the frequencies of each component species (proportional abundances pi = abundance of species i/ total abundance) and a scale parameter (a) ranging from zero to inﬁnity (To´thme´re´sz 1995; Legendre and Legendre 1998) as: P a ln pi Ha ¼ 1a It can be demonstrated that values of the Re´nyi proﬁle at the respective scales of 0, 1, 2 and ¥ are related to species richness S, the Shannon diversity index H, the Simpson diversity index D1 and the Berger–Parker diversity index d1 (Magurran 1988; Legendre and Legendre 1998; Shaw 2003): H0 ¼ lnðSÞ

H1 ¼ H ¼

X

H2 ¼ lnðD1 Þ ¼ ln

pi log pi

X 1 ðp2i Þ

H1 ¼ lnðd1 Þ ¼ lnðp1 max Þ [195]

1256 Community A is more diverse than a community B if the diversity proﬁle for community A is everywhere above the diversity proﬁle for community B. Communities that have intersecting proﬁles cannot be ordered in diversity. The fact that intersecting proﬁles (partial diversity ordering) could occur explains why ordering techniques such as the Re´nyi series are needed, since a single diversity index will not provide suﬃcient information. The values of the series for the various use-groups were calculated for scales a 2{0,0.25, 0.5, 1, 2, 4, 8, ¥}. From the diversity proﬁle we derived an evenness proﬁle (ln Ea,0) that orders communities in evenness in a similar way that diversity proﬁles order communities in diversity (Kindt et al. 2001; Ricotta and Avena 2002): ln Ea;0 ¼ Ha H0 Partial ordering may occur where evenness proﬁles intersect, indicating that intrinsic evenness ordering is not possible. For example, community A with species abundances of (70, 20, 10) can only be partially ordered with community B with species abundances of (60, 35, 5) and it is therefore not possible to identify the community of largest evenness. The example above is a rare case where diversity ordering equals evenness ordering since species richness is equal in community A and B. Since species richness diﬀers between most communities, diversity and evenness ordering can only be inferred through separate ordering techniques that conform to diversity ordering (such as the Re´nyi diversity series) or to evenness ordering (such as Hill’s Ea,0 subfamily, see below). Since H0 = ln S (as shown above), rearranging the above formula shows that the Re´nyi diversity proﬁle can be decomposed as: Ha ¼ ln S þ ln Ea;0 This decomposition has the attractive feature in showing mathematically that diversity combines information on species richness and evenness, which conforms to the deﬁnition of diversity (Magurran 1988; Purvis and Hector 2000; Shaw 2003). The decomposition of the Re´nyi proﬁle is a generalisation of the decomposition of the Shannon index H1 as ln S + ln E (Hayek and Buzas 1997; Kindt et al. 2001). Ea,0 is a subfamily of Hill’s parametric evenness (Hill 1973; Ricotta and Avena 2002; Ricotta 2003) deﬁned as: Ea;0 ¼

Na exp Ha ¼ N0 exp H0

Ea,0 has several desirable properties as an evenness function: it is consistent with the Lorenz ordering and therefore meets the general requirements for an evenness index (Taillie 1979; Rousseau et al. 1999; Ricotta 2003), it is formally related to diversity (Ricotta and Avena 2002; Ricotta 2003), and it is normalised between zero and one. [196]

1257 Since ln Ea,0 is a monotone transformation of Ea,0, both these measures provide the same rank order when communities are compared for evenness despite the fact that ln Ea,0 is not normalised between zero and one. In analogy with diversity proﬁles (To´thme´re´sz 1995), the various techniques provide the same ordering, but diﬀer in the resolution of the graphs that they produce.

Accumulation patterns for the Re´nyi series We calculated the Re´nyi diversity proﬁle for each use-group by calculating the frequencies of each species in the entire survey. These proﬁles allow comparing the total diversity of the various use-groups at the scale of the total survey. Since some use-groups did not occur on each farm, another comparison was made by only including farms where a speciﬁc use-group occurred. Because the total number of farms per use-group diﬀered, proﬁles were rareﬁed to the same number of farms (the number of farms of the smallest use-group) so that eﬀects from diﬀerences in sample size could be removed from the analysis. The rarefaction of the diversity proﬁle was achieved through a Monte-Carlo approach of 1000 random additions of farms (selecting the ﬁrst farm at random, adding the second farm at random,…) using sampling without replacement. We obtained accumulation surfaces for diversity proﬁles by calculating the average Ha for each subset of 1, 2, …, all farms combined, and for each a2{0,0.25, 0.5, 1, 2, 4, 8, ¥} (Kindt et al. 2001). A similar approach of rarefaction is used to calculate species accumulation curves for random pooling of sample units (e.g., Colwell 1997; Gotelli and Colwell 2001). FORTRAN and R statistical programmes developed to carry out the computations can be obtained from the authors (Kindt 2001, 2004). H¥ was the only value for which 95% conﬁdence interval (CI) limits for the expected values for the entire survey area could be calculated as it is obtained solely from the proportion of the dominant species, while other values in the diversity series include an eﬀect of species richness. Hayek and Buzas (1997) propose to calculate the variance of species frequency (p) in the case of cluster sampling as n P _2 r pclus

¼

i¼1

m2i ðpi pÞ2

ðn 1Þm2 n1

(mi = total abundance of farm i, pi = species frequency in farm i, p = species frequency of the total survey, n = number of farms, and m = total abundance). 95% CI limits for the proportion of the dominant species can then be calculated as: _

p t r pclus [197]

1258 The limits of the CI for the proportion were y=ln(x1) transformed to calculate a CI for H¥.

Results Diversity ordering and examination of richness and evenness contributions Figure 1 shows the Re´nyi diversity ordering of all trees and the 12 most frequent use-groups. By examining the values at scales 0, 1, 2, and ¥, species richness and values of Shannon, Simpson, and Berger–Parker diversity indices can be inferred. The many intersections in the ﬁgure show the diﬃculties to order most groups in diversity. Figure 2 shows many groups with intersecting evenness proﬁles, which is an indication that many groups cannot be ranked in evenness. Table 1 provides some more precise statistics for certain proﬁle values than can be inferred from the ﬁgures, and also gives some parameters that describe the pattern of the various diversity proﬁles (see below). We diﬀerentiated between ﬁve pools of use-groups based on their total species richness (H0) (which is an ordering of use-group only based on richness): (i) pool A – very high richness, including all trees and ﬁrewood; (ii) pool B – high richness, including shade; (iii) pool C – medium richness, including

Figure 1. Diversity proﬁles based on the Re´nyi series Ha for all trees and trees belonging to particular use-groups. [198]

1259

Figure 2. Evenness proﬁles for all trees and trees belonging to particular use-groups.

Table 1. Values for speciﬁc proﬁle values of the diversity and evenness proﬁles depicted in Figures 1 and 2 with for all trees and for the most frequent use-groups in western Kenya. Use-group

H0

H1

H2

H¥

ln E1,0

E1,0

H¥,I

H¥,u

All trees Firewood Shade Medicine Ornamental Timber Boundary Soil fertility Charcoal Fruit Construction Fodder Beverage

5.16 5.04 4.43 4.06 3.97 3.89 3.53 3.30 3.26 3.22 3.00 1.95 1.39

2.79 2.69 3.00 1.59 1.34 1.11 1.95 1.44 1.29 1.08 0.66 1.61 0.50

2.38 2.29 2.60 0.79 0.94 0.77 1.69 1.08 0.95 0.61 0.43 1.40 0.38

1.78 1.71 2.04 0.41 0.68 0.48 1.17 0.64 0.70 0.32 0.24 0.87 0.22

2.37 2.35 1.43 2.47 2.63 2.78 1.58 1.86 1.97 2.13 2.33 0.33 0.89

0.09 0.10 0.24 0.08 0.07 0.06 0.21 0.16 0.14 0.12 0.10 0.72 0.41

1.61 1.54 1.43 0.15 0.37 0.36 0.97 0.17 0.29 0.24 0.17 0.44 0.04

1.98 1.92 3.84 0.77 1.12 0.61 1.44 1.57 1.41 0.41 0.32 1.63 0.44

H¥;l and H¥;u are 95% CI limits for H¥. See methods for the formulas.

medicine, ornamental and timber; (iv) pool D – moderate richness, including boundary demarcation, soil fertility enhancement, charcoal, fruit and construction wood; and (v) pool E – low richness, including fodder and beverage. Some diﬀerences and similarities in diversity and evenness can subsequently be detected between and within pools (Figures 1 and 2). [199]

1260 When comparing diversity and evenness patterns for pools, it can be observed that use-groups of pool A and B were more diverse than the other use-groups. The evenness proﬁle (Figure 2) shows that shade (pool B) has a more even distribution than use-groups of pool A. Diversity proﬁles of use-groups of pool C intersected all use-groups of pool D and E, with the exception of fruit and construction (pool D) and beverage (pool E). The evenness proﬁles, however, show that ornamental and timber (pool C) had lower evenness than all use-groups of pool D, with exception of construction for which intersection can be observed. Fodder and beverage (pool E) had the most even distribution of all use-groups, with the exception of an intersection for beverage and shade. When comparing diversity for use-groups that belong to the same pool, it can be seen that all trees are more diverse but that ﬁrewood is more even within pool A although the proﬁles were almost parallel to each other. The evenness proﬁle of medicine intersected the other use-groups of pool C. All use-groups of pool C had intersecting evenness proﬁles. These groups can therefore not be ranked in evenness within pool C. Most use-groups within pool D could be ranked in diversity, since their diversity proﬁles did not intersect. Boundary demarcation is the most diverse and evenly distributed use-group within the pool. Construction is the least diverse use-group and fruit the second least diverse of pool D. Their evenness proﬁles intersect, however. Charcoal and soil fertility had intersecting diversity and evenness proﬁles. Within pool E, fodder is more diverse and more evenly distributed. Values of H¥ (Figure 1 and Table 1) lower than 0.5 indicate that the dominant species of timber, medicine, fruit, construction and beverage contains more than 60% of all trees of these use-groups. Values of H¥ between 0.5 and 1.5 indicate that the dominant species contains between 22 and 60% of all trees for soil fertility, charcoal, ornamental, fodder and boundary demarcation. The dominant species contains a smaller percentage of trees for the other usegroups. However, values of ln E¥,0 (Figure 2) show that the dominant species for all trees and ﬁrewood are less evenly distributed when comparing with many other use-groups (the formula ln E¥,0 = H¥H0 implies that when species richness increases, the frequency of the dominant species should decrease to maintain the same ln E¥,0). Medicine had the least evenly distributed dominant species.

Eﬀects of sample size on diversity Figure 3 shows the average proﬁle values and associated 95% CI for subsamples of 47 farms (the number of farms with fodder, the least frequent usegroup). Figure 3 indicates that, on average, similar proﬁles are obtained as for the full sample. Diversity proﬁles, especially medicine and shade, had large 95% CI, however. The 95% CI still allow classifying use-groups in the richness [200]

1261 pools that we diﬀerentiated above. Construction of the original pool D obtained richness values closer to the range of pool E. Within pools, most 95% CI of diversity proﬁle values overlap, although the averages showed a similar pattern in Figures 1 and 3. Figures 4–6 show that several use-groups (especially all trees, ﬁrewood, boundary, timber, fruit and construction) obtain stable (asymptotic) values for H1, H2 and H¥ after 40 farms were sampled. Some other use-groups showed some strong non-linear patterns throughout the range of pooled farms. These use-groups were especially shade, fodder, medicine, and soil fertility. Whereas the non-linear patterns were for the larger part increments of the index with increasing sample size, a declining pattern could be observed for medicine for H2 and H¥. The observed patterns suggest that to extrapolate proﬁle values, in some cases (asymptotic patterns) similar values can be expected, whereas in other cases diﬀerent values would be expected (non-linear patterns). However, extrapolation should be used carefully since we had no actual data for larger sample sizes. Table 1 (H¥,l and H¥,u) indicates the CI that is expected for the average value of H¥ when all farms would be sampled in the survey area (assuming random sampling of the farms). Relatively large CI were even obtained for

Figure 3. Averages of rareﬁed diversity proﬁles based on the Re´nyi series Ha for all trees and trees belonging to particular use-groups calculated from 1000 random subsamples of 47 farms, with 95% CI. All proﬁle values were calculated for the same scales, but groups were presented at diﬀerent scales for better discrimination. [201]

1262

Figure 4. Accumulation curve for the Shannon diversity index for all trees and trees belonging to particular use-groups. The vertical reference indicates the sample size of 47 farms depicted in Figure 3.

groups where stable values were obtained at the respective scale in Figure 6 (for example timber, fruit, construction, and beverage). However, these CI were among the smallest. Large CI corresponded to non-linear patterns for the Berger–Parker index (Figure 6, see discussion above). Medicine which had a non-linear negative pattern for the Berger–Parker index had a relatively small CI, however.

Discussion Using diversity and evenness proﬁles We compared the diversity of various use-groups by using the Re´nyi diversity proﬁle. The numerous intersections of diversity proﬁles indicate situations of partial ordering in our data set. If we would have used a single diversity index such as the Shannon, Simpson or Berger–Parker index, then we have obtained erroneous results. Studies that attempt to order communities in diversity (e.g., Dougall and Dodd 1997; Slik et al. 2002; Mishra et al. 2004; Zilihona et al. 2004) should therefore not base the ordering on a single index, or even a [202]

1263

Figure 5. Accumulation curve for H2 for all trees and trees belonging to particular use-groups. The vertical reference indicates the sample size of 47 farms depicted in Figure 3.

combination of several indices, but use techniques developed for diversity ordering such as the Re´nyi diversity proﬁle. Although the aim of our study was not to compare the performance of several diversity ordering techniques, we agree with To´thme´re´sz (1995) that the Re´nyi proﬁle is one of the most useful methods for diversity ordering. Various researchers have used models of rank-abundance curves to study biodiversity (e.g., Magurran 1988; Hayek and Buzas 1997; Hubbell 2001; Belaoussoﬀ et al. 2003; Magurran and Henderson 2003; McGill 2003). Because rank-abundance curves do not provide a direct graphical method for diversity ordering (some diversity ordering techniques are based on cumulative frequencies, but none use the frequencies of the individual species; To´thme´re´sz 1995), and since information is lost when rank-abundance curves are modelled, we do not recommend using (models of) rank-abundance distribution for diversity ordering. As for the diversity proﬁle, we observed various intersections in the evenness proﬁles for our dataset. For this reason, a single index of evenness (e.g., Zilihona et al. 2004) is not suﬃcient information to order communities in evenness in the same way that a single index of diversity is not suﬃcient for diversity ordering. [203]

1264

Figure 6. Accumulation curve for H¥ for all trees and trees belonging to particular use-groups. The vertical reference indicates the sample size of 47 farms depicted in Figure 3.

The inﬂuence of sample size on the diversity proﬁle It has been observed for a long time in ecological research that sample size has an inﬂuence on species richness (e.g., Arrhenius 1921). Since diversity is inﬂuenced by richness, sample size also has an eﬀect on diversity. We were able to investigate the inﬂuence of sample size on diversity by studying the range of values observed in subsets of the data by using a randomisation approach similar to the randomisation approach to calculate species accumulation curves (Kindt et al. 2001). This approach allowed rarefaction to the same number of sample units (farms in our example), thus removing the eﬀects from diﬀerences in sample size. This approach could be useful in other studies that compare results obtained from surveys with diﬀerent sample sizes, especially since the approach includes a diversity ordering technique which is necessary for an accurate description of the diversity of a community. Magurran (1988) indicated that a Re´nyi series value with larger scale parameter value has reduced sensitivity to sample size. Gimaret-Carpentier et al. (1998) observed that the Simpson index reached stable values at lower sample sizes compared to the Shannon index. We observed such asymptotic patterns both for H2 and H¥ for those groups where stable values were obtained for the Shannon index (timber, fruit, [204]

1265 construction, and beverage). Shade and fodder, however, showed the other extreme with increasing proﬁle values with increasing sample size, and not asymptotic values. Hayek and Buzas (1997) proposed to investigate accumulation patterns of H, ln(E) and ln(E)/ln(S) to choose the best abundance distribution model (‘SHE analysis’). Reaching asymptotic values for these statistics with increasing sample size would indicate that the species abundance distribution corresponds to respectively a log-series, a broken-stick or log-normal distribution. Based on our results, we could therefore conclude that most usegroups (and especially timber, fruit, construction and beverage) have abundance distributions more typical of the log series distribution (asymptotic H), while the distributions of shade and fodder corresponded more to a lognormal distribution (asymptotic ln(E)/ln(S), ﬁgure not included). (A preliminary analysis found that shade, medicine and ornamental conformed to the log-normal distribution, whereas all trees, ﬁrewood, timber, and boundary did not – for other use-groups, unreliable results were obtained for chisquare goodness-of-ﬁt tests.) We suggest expanding the SHE analysis to the complete diversity proﬁle, as in Figure 3. For example, for a pure log-series (and geometric series), the Simpson and Berger–Parker indices are also expected to reach constant values (May 1975), which was a phenomenon that we could observe most clearly for the groups with the clearest asymptotic H1 pattern. Since asymptotic H1 and H2 are only expected for the log-series distribution, the ﬁndings of Gimaret-Carpentier et al. (1998) described above most likely correspond to studies of systems more conform to this distribution. For the same reason, the observation of reduced sensitivity to sample size with increasing scale provided by Magurran (1988) could only apply to the log-series.

Planning diversiﬁcation based on diversity proﬁles The basic aim of our study was to plan for diversiﬁcation. The diversity and evenness proﬁles were calculated on several use-groups. By diﬀerentiating between several use-groups, use-groups of lower diversity or evenness were identiﬁed and a benchmark dataset was created to measure the impact of future diversiﬁcation. By identifying use-groups of lower relative diversity (such as beverage and construction), priority can be given to these use-groups for diversiﬁcation. Such approach can be described as a coldspot approach that focuses on subregions of lowest diversity in a study area. For example, it would be less eﬃcient for diversiﬁcation to add new species to ﬁrewood than adding new species to construction. With the rarefaction procedure, comparisons are made only for farmers that are already growing trees for a use-group. This approach should be preferred when there is no scope for increasing the number of farmers for each use-group: this is a better benchmark to plan diversiﬁcation eﬀorts (see below). [205]

1266 The value of using diversity proﬁles lays not only in determining which usegroups are more diverse. Diversity proﬁles also allow discrimination between richness and evenness contributions to diversity. If the intervention would attempt to increase diversity for two groups with intersecting diversity proﬁles, then for one group improvement of richness could be attempted, while improvement of evenness would be the target for the other group. The lack of evenness in the distribution of the dominant species and the many steep decreases in proﬁles with increasing scale parameter value showed that diversity could be increased substantially in many use-groups by targeting evenness, rather than targeting richness. No group had perfectly evenly distributed species. Evenness increment could be achieved by encouraging farmers to establish trees in more even numbers (inﬂuencing the demand for tree germplasm) or by more species-even germplasm distribution (inﬂuencing the supply of tree germplasm). The analysis shows use-groups with steep diversity and evenness proﬁles where such diversity improvements would be most useful: i.e. the construction, fruit, ornamental (although this group will probably not constitute a priority to farmers), ﬁrewood, timber and medicine groups. When considering the frequency of the dominant species only (not how evenly this species is distributed), timber, medicine, fruit and beverage are the groups with frequencies larger than 60%. Interestingly, these are also the use-groups that could be categorised as providing more cash income to farmers (‘high value trees’ that could be selected to be of higher priority for domestication for this reason). The analysis of diversity did not include all aspects that could inﬂuence decisions on alterations in tree species composition on farms. Such factors include potential diﬀerences in importance attributed by farmers to diﬀerent use-groups so that diversiﬁcation of a more important but more diverse usegroup could be given priority over that of a less diverse but also less important use-group. Another aspect is potential diﬀerentiation among farms in alpha diversity, so that farms with low diversity for a speciﬁc use-group could be targeted, rather than only targeting use-groups with lower diversity at the survey level (Kindt et al. 2004). Eﬀective diversity planning will require that the relative abundances of the composing species are analysed within use-groups that were prioritised for diversiﬁcation. When planning for increments in evenness, the potential for increasing the abundances of rare species should be investigated. Where it is not possible to add new trees to a particular farm or landscape, the potential of substituting some trees of the dominant species with trees of the rare species should be explored. Participatory research should investigate why some species occur in higher numbers than other species: substitution of common species by rare species may be easier when diﬀerences in abundance are not related to diﬀerences in farmer preference, but caused by factors such as diﬀerences between species in natural regeneration, historic promotion by development agencies, or erosion in local knowledge. Since all species within a particular use-group are used for that particular purpose, there is a deﬁnite potential for [206]

1267 increasing evenness, but such increments may require balancing diversity with diﬀerences in preference – some species may need to be promoted for the insurance that they bring at a cost for short-term productivity. McNeely and Scherr (2002) describe that a new type of agriculture is needed that leads to increased food security and conservation gains since human population density and biodiversity are positively correlated in many areas. Their book provides examples of innovative landscape management strategies that successfully combined both objectives by applying ecoagriculture strategies. Our study documented that many tree species have been integrated in farming systems already (conform Ecoagriculture Strategy 4 of mimicking natural habitats by integrating productive perennial plants). Since careful scrutiny of species identities of the various use-groups (such detailed study was beyond the scope for this article, but is a logical next step as described above) showed that the dominant species in most use-groups were exotic species (exceptions were boundary demarcation, fodder and medicine), whereas the majority of rare species were indigenous species, increments of evenness could result in increments of indigenous tree species in the farming landscape (since not only exotic species are planted, increasing abundances for indigenous species entails small relative changes in planting practices by local communities). Diversiﬁcation could therefore result in improved conservation, although the links between development and conservation goals need to be explored carefully (Adams et al. 2004). Landscape diversiﬁcation could also consider population structure and geneﬂow of particular species, especially for indigenous species. Where less frequent species are promoted, interventions should attempt to ensure that population sizes are large enough to avoid substantial genetic erosion. Diversiﬁcation planning could for example consider corridors in farmland between natural populations to reduce genetic erosion (O’Neill et al. 2001). Such considerations of genetic diversity may indicate limits to diversiﬁcation (not all species could potentially be maintained at large enough population sizes for a more even distribution of species) that could be incorporated in planning of diversiﬁcation (ﬁnding a more even species abundance distribution that avoids too small population sizes for each species, possibly with a smaller number of species). Alternatively, species can be maintained at very small population sizes given that new genetic diversity is regularly introduced from genetically diverse seed sources. Ecological reasons for diversiﬁcation within a use-group could include minimizing the chances of pest and disease outbreaks. Promotion of single species for a particular use-group should especially be avoided since several pest outbreaks on agroforestry species have been experienced after largescale promotions of monoculture agroforestry technologies (Atta-Krah et al. 2004). Ecological research has indicated that biodiversity can aﬀect ecosystem function, but that diﬀerences in species function are conditions for positive eﬀects of biodiversity on ecosystem stability and productivity (e.g., Hector et al. 1999; Loreau et al. 2001, 2002; Tilman et al. 2001). Natural [207]

1268 communities with speciﬁc species extinction and abundance patterns function diﬀerently from experimental communities of similar richness but different composition and equalized abundances, however (Zavaleta and Hulvey 2004). The ecological consequences of increasing the diversity or evenness of trees on farms can therefore not be predicted and thus needs to be evaluated on a case-by-case basis, although natural communities can provide some clues on potential richness and composition (e.g., Van Noordwijk and Ong 1999). Although the methods shown in this article are unlikely to provide all the answers for diversiﬁcation planning, they did provide meaningful insights in relationships between richness, evenness, and sample size of use-groups. They, thus, provide accurate guidance for attempts in alterations of these characteristics. Obviously, they allow also for detailed monitoring of the impact of interventions of these characteristics by providing a baseline to compare diversity before and after interventions and by using a technique that is speciﬁcally tailored to study diﬀerences in diversity. Acknowledgements We are very grateful for information provided by farmers. Roeland Kindt wants to thank Wim Buysse, Richard Coe, Ian Dawson, Ard Lengkeek, Meine Van Noordwijk and two anonymous reviewers for inputs in the article, assistance provided by the ICRAF East and Central African regional programme especially through Stephen Ruigu and Amadou Niang, assistance during data collection by Joseph Njeri, and funding provided by DFID and VVOB. References Adams W.M., Aveling R., Brockington D., Dickson B., Elliott J., Hutton J., Roe D., Vira B. and Wolmer W. 2004. Biodiversity eradication and the eradication of poverty. Science 306: 1146– 1149. Arrhenius O. 1921. Species and area. J. Ecol. 9: 95–99. Atta-Krah K., Kindt R., Skilton J.N. and Amaral W. 2004. Managing biological and genetic diversity in tropical agroforestry. Agroforest. Syst. 61: 183–194. Beentje H.J. 1994. Kenya Trees, Shrubs and Lianas. National Museums of Kenya, Nairobi 722 pp. Belaoussoﬀ S., Kevan P.G., Murphy S. and Swanton C. 2003. Assessing tillage disturbance on assemblages of ground beetles (Coleoptera: Carabidae) by using a range of ecological indices. Biodivers. Conserv. 12: 851–882. Bradley P.N. 1991. Woodfuel, Women and Woodlots, vol. 1. Macmillan Education Ltd, London and Basingstoke 338 pp. Bradley P.N., Chavangi N. and Van Gelder A. 1985. Development research and energy planning in Kenya. Ambio 14: 228–236. Colwell R.K. 1997. Estimates: Statistical Estimation of Species Richness and Shared Species from Samples. University of Connecticut, Storrs. Dougall T.A.G. and Dodd J.C. 1997. A study of species richness and diversity in seed banks and its use for the environmental mitigation of a proposed holiday village development in a coniferized woodland in south east England. Biodivers. Conserv. 6: 1413–1428. [208]

1269 Gimaret-Carpentier C., Pelissier R., Pascal J.P. and Houllier F. 1998. Sampling strategies for the assessment of tree species diversity. J. Veg. Sci. 9: 161–172. Gotelli N.J. and Colwell R.K. 2001. Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness. Ecol. Lett. 4: 379–391. Hayek L.-A.C. and Buzas M.A. 1997. Surveying Natural Populations. Columbia University Press, New York xvi, 563 pp. Hector A., Schmid B., Beierkuhnlein C., Caldeira C., Diemer M., Dimitrakopoulos P.G., Finn J.A., Freitas H., Giller P.S., Good J., Harris R., Ho¨gberg P., Huss-Danell K., Joshi J., Jumpponen A., Ko¨rner C., Leadley P.W., Loreau M., Minns A., Mulder C.P., O’Donovan G., Otway S.J., Pereira J.S., Prinz A., Read D.J., Scherer-Lorenzen M., Schulze E.D., Siamantziouras A.D., Spehn E.M., Terry A.C., Troumbis A.Y., Woodward F.I., Yachi S. and Lawton J. 1999. Plant diversity and productivity in European grasslands. Science 286: 1123– 1127. Hill M.O. 1973. Diversity and evenness: a unifying notation and its consequences. Ecology 54: 427– 431. Hubbell S.P. 2001. The Uniﬁed Neutral Theory of Biodiversity and Biogeography. Princeton University Press, Princeton xiv + 375 pp. ICRAF 1997. ICRAF Medium-Term Plan 1998–2000. International Centre for Research in Agroforestry, Nairobi 77 pp. Jaetzhold R. 1982. Farm Management Handbook of Kenya: Natural Resources and Farm Management Information vol. iia – West Kenya (Nyanza and Western Provinces). Kenya Ministry of Agriculture, 397 pp. Kindt R. 2001. RenyiAccum. Program to Calculate Average Values and Ranges for the Re´nyi Diversity Series Associated with Random Site Sequences. International Centre for Research in Agroforestry (ICRAF), Nairobi. Kindt R. 2004. Biodiversity Analysis Functions for R (Biodiversity.R). ICRAF, Nairobi. Kindt R., Degrande A., Turyomurugyendo L., Mbosso C., Van Damme P. and Simons A.J. 2001. Comparing species richness and evenness contributions to on-farm tree diversity for data sets with varying sample sizes from Kenya, Uganda, Cameroon, and Nigeria with randomized diversity proﬁles. In: IUFRO Conference on Forest Biometry, Modelling and Information Science, 26–29 June 2001. University of Greenwich, UK. URL: http://cms1.gre.ac.uk/conferences/iufro/proceedings/ (last accessed 4–2004). Kindt R. and Lengkeek A.G. 1999. Tree diversity on farm – use it or lose it. In: National Workshop on Agricultural Biodiversity Conservation, 27–29 January 1999. Intermediate Technology Development Group (ITDG, Nairobi, pp 75–85. Kindt R., Simons A.J. and Van Damme P. 2004. Do farm characteristics explain diﬀerences in tree species diversity among western Kenyan farms? Agroforest. Syst. 63: 63–74. Legendre P. and Legendre L. 1998. Numerical Ecology. Elsevier Science BV, Amsterdam 853 pp. Loreau M., Naeem S., Inchausti P., Bengtsson J., Grime J.P., Hector A., Hooper D.U., Huston M.A., Raﬀaelli D., Schmid B., Tilman D. and Wardle D.A. 2001. Biodiversity and ecosystem functioning: current knowledge and future challenges. Science 294: 804–807. Loreau M., Naeem S. and Inchausti P. 2002. Biodiversity and Ecosystem Functioning: Synthesis and Perspectives. Oxford University Press, Oxford 304 pp. Magurran A.E. 1988. Ecological Diversity and Its Measurement. Princeton University Press, Princeton, N.Jx, 179 pp. Magurran A.E. and Henderson P.A. 2003. Explaining the excess of rare species in natural species abundance distributions. Nature 422: 714–716. May R.M. 1975. Patterns of species abundance and diversity. In: Cody M.L. and Diamond J.M. (eds), Ecology and the Evolution of Communities. The Belknap Press of Harvard University Press, Cambridge and London, pp. 81–120. McGill B.J. 2003. A test of the uniﬁed neutral theory of biodiversity. Nature 422: 881–885. McNeely J.A. and Scherr S.J. 2002. Ecoagriculture: Strategies to Feed the World and Save Wild Biodiversity. Island Press, Washington 323 pp.

[209]

1270 Mishra B.P., Tripathi O.P., Tripathi R.S. and Pandey H.N. 2004. Eﬀects of anthropogenic disturbance on plant diversity and community structure of a sacred grove in Meghalaya, northeast India. Biodivers. Conserv. 13: 421–436. O’Neill G.A., Dawson I.K., Sotelo-Montes C., Guarino L., Current D., Guariguata M. and Weber J.C. 2001. Strategies for genetic conservation of trees in the Peruvian Amazon basin. Biodivers. Conserv. 10: 837–850. Purvis A. and Hector A. 2000. Getting the measure of biodiversity. Nature 405: 212–218. Ricotta C. 2003. On parametric evenness measures. J. Theor. Biol. 222: 189–197. Ricotta C. and Avena G.C. 2002. On the information-theoretical meaning of Hill’s parametric evenness. Acta Biotheor. 50: 63–71. Rousseau D., Van Hecke P., Nijssen D. and Bogaert J. 1999. The relationship between diversity proﬁles, evenness and species richness based on partial ordering. Environ. Ecol. Stat. 6: 211–223. Shaw P.J.A. 2003. Multivariate Statistics for the Environmental Sciences. Hodder Arnold, London ix + 233 pp. Slik J.W.F., Verburg R.W. and Keßler P.J.A. 2002. Eﬀects of ﬁre and selective logging on tree species composition of lowland dipterocarp forest in East Kalimantan, Indonesia. Biodivers. Conserv. 11: 85–98. Taillie C. 1979. Species equitability: a comparative approach. In: Grassle J.F., Patil G.P., Smith G.K. and Taillie C. (eds), Ecological Diversity in Theory and Practice. International Cooperative Publishing House, Fairland, pp. 51–62. Tilman D., Reich P.B., Knops J., Wedin D., Mielke T. and Lehman C. 2001. Diversity and productivity in a long-term grassland experiment. Science 294: 843–845. To´thme´re´sz B. 1995. Comparison of diﬀerent methods for diversity ordering. J. Veg. Sci. 6: 283– 290. Van Noordwijk M. and Ong C.K. 1999. Can the ecosystem mimic hypotheses be applied to farms in African savannahs? Agroforest. Syst. 45: 131–158. Zavaleta E.S. and Hulvey K.B. 2004. Realistic species losses disproportionately reduce grassland resistance to biological invaders. Science 306: 1175–1177. Zilihona I.J.E., Niemela J. and Nummelin M. 2004. Eﬀects of a hydropower plant on Coleopteran diversity and abundance in the Udzungwa Mountains, Tanzania. Biodivers. Conserv. 13: 1453– 1464.

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Biodiversity and Conservation (2006) 15:1271–1301 DOI 10.1007/s10531-005-2576-4

Springer 2006

-1

Vascular plant species inventory of a Philippine lowland rain forest and its conservation value GERHARD LANGENBERGER, KONRAD MARTIN* and JOACHIM SAUERBORN Institute of Plant Production and Agroecology in the Tropics and Subtropics (380), Agroecology Section, University of Hohenheim, 70593 Stuttgart, Germany; *Author for correspondence (e-mail: [email protected]; phone: +49-711-459-3605; fax: +49-711-459-3843) Received 22 June 2004; accepted in revised form 8 February 2005

Key words: Conservation value, Dipterocarp forests, Gene bank, Molave forest, Native species, Species richness, Tropical rain forest, Vascular plant species Abstract. The Philippines are one of the most important biodiveristy hotspots on earth. Due to the extraordinary rate of environmental destruction, leaving only 3% of the land with primary forest, this biodiversity is at high risk. Despite that situation information on Philippine forest vegetation is fragmentary and focused on trees. This study aimed at analysing forest remnants in the Leyte Cordillera on the Island of Leyte, and at evaluating their role as refuge to the largely destroyed lowland forest vegetation. A total of 49 plots (100 m2 each) between 55 and 520 m a.s.l. were studied. All vascular plant species except epiphytes were included. Records include 685 taxa from 289 genera and 111 families, representing nearly 8% of the known Philippine vascular plant species. More than half (52%) of the species are Philippine endemics. A number of 41 tree species, or 6% of all taxa recorded, are included in the IUCN red list, either as vulnerable, endangered, or critically endangered. Life form composition was dominated by phanerophytes (65.3%), followed by lianas and chamaephytes (17.1 and 16.9%, respectively). The most common families were the Rubiaceae with 35 and the Euphorbiaceae with 32 species. All ﬁve Philippine dipterocarp forest types as well as the molave forest type were represented by typical tree species. The area provides an important gene bank of the highly threatened Philippine lowland forest vegetation and is of high value for biodiversity conservation. Additionally, it can play an important role as seed source of valuable tree species for the increasing initiatives to rehabilitate and reforest degraded land with native species.

Introduction The destruction of tropical rain forests is still continuing at high rates (FAO 2003). This process, especially threatens the earth’s biodiversity hotspots such as the Philippines (Myers et al. 2000; Brooks et al. 2002). Despite this, there are only very few studies worldwide which aimed at the documentation of the total plant species richness of such sites. Most inventories were restriced to selected life forms such as ground herbs (e.g. Kiew 1987; Poulsen and Balslev 1991; Poulsen 1996) or trees of a deﬁned minimum diameter (e.g. Valencia et al. 1994; Lieberman et al. 1996; Newbery et al. 1996; Rennolls and Laumonier 2000; Slik et al. 2003). Vascular plant species composition of tropical lowland forests was studied in Ghana on 0.5- and 1-ha plots by Hall and Swaine (1981), in Amazonia on 0.02-ha plots by Takeuchi (1960) and on 10 non-contiguous plots of 0.1 ha by Duivenvoorden [211]

1272 (1994), in Ecuador on 0.1-ha plots of three lowland forest types by Gentry and Dodson (1987), and in stratiﬁed plots with a total area of about 2 ha in Puerto Rico by Smith (1970). In Southeast Asia, Kochummen et al. (1992) studied the trees and shrubs (>1 cm diameter at breast height (dbh)) in a 50-ha plot in the Pasoh Forest Reserve in Malaysia. The most comprehensive study including all vascular plants as well as mosses was conducted by Whitmore et al. (1985) on a single 100-m2 plot in the lowland rain forest of Costa Rica. However, no study representing a complete inventory of vascular plant species richness of any site of lowland rain forest in Southeast Asia was found. The Philippines are among the most seriously depleted tropical countries with only 3% of the land area still covered by primary forest (Myers et al. 2000). From 1990 to 2000, the Philippines lost 1.4%, or 89,000 ha, of the forest area annually (FAO 2003). At the same time, the Philippine archipelago is one of the most important biodiversity hotspots on earth (Myers et al. 2000) with high proportions of endemic plant and animal species (Heaney and Regalado 1998). The endemism rate of plants was estimated to be 39% (Davis et al. 1995), but for certain taxa, it can be much higher. For example, 11 of 12 species of pitcher plants (Nepenthes spp.) known from the Philippines are endemic (Cheek and Jebb 2001). Similarly, there are high rates of endemism among the fauna. Referring to terrestrial vertebrates, 64% of the archipelago’s land mammals are endemic, as well as 44% of the breeding land birds, 68% of the reptiles, and ca. 78% of the amphibians (Heaney and Regalado 1998). Most of them depend on forest ecosystems. Despite the ecological uniqueness on the one hand and the extensive destruction on the other, the study of Philippine forest vegetation has been neglected (Tan and Rojo 1989; Kartawinata 1990; Soerianegara and Lemmens 1994). Much of the current knowledge is still based on studies conducted in the early 20th century (Whitford 1906; Whitford 1911; Brown and Mathews 1914; Brown 1919), which were mainly dealing with timber trees under economical aspects. Recent studies focused on the vegetation of montane and submontane forest types on diﬀerent islands. However, in most cases (Aragones 1991; Pipoly and Madulid 1998; Proctor et al. 1998; Hamann et al. 1999) these were largely restricted to trees of a deﬁned size, which usually is ‡10 cm dbh. Buot and Okitsu (1997) only considered woody plants higher than 1.3 m, and Ingle (2003) those of at least 5 cm dbh. The only data without size limitations are provided by Gonzales-Salcedo (2001) from Mt. Amuyao, Luzon, at elevations of 1600–1800 a.s.l. and by Gruezo (1998) from the highly degraded vegetation of Pagbilao Grande Island. No study dealing with lowland forest vegetation was found in the literature. In order to provide more substantial information on species richness and composition of Philippine lowland forests, we analysed forest remnants in the rugged foothills of the Leyte Cordillera. The island of Leyte is located in the central part of the Philippine archipelago and represents a typical example of the environmental situation in the Philippines. In 1987, the remaining forest cover of Leyte was 12%, and in 1994 only 2% of the island’s area have been [212]

1273 estimated to be primary forest (Dargantes and Koch 1994). More recent data (DENR 1998) show that about 40% of the land area of Leyte is covered by grassland and barren land, resulting from abandoned cultivation and grazing land that marginalised in productivity through erosion and leaching. Another 40% of the island’s area is under coconut plantations. The remaining area is composed of settlements, agricultural land and forest. In the view of this situation, the objectives of this study were (a) to analyse the vascular plant species composition and diversity of selected plots of mature primary forest and (b) to evaluate the role of the study area as refuge to lowland forest vegetation and its signiﬁcance for conservation and as a gene bank. Material and methods Study area The Island of Leyte (Figure 1) belongs to the biogeographic region of the Eastern Visayas (DENR and UNEP 1997). It is located between 955¢ N– 1148¢ N and 12417¢ E–12518¢ E, with an extension of 214 km from north to south. Located oﬀshore the northeastern part of Leyte is the island of Samar. The southern part of Leyte is exposed to the Paciﬁc Ocean (Leyte Gulf). Leyte is characterised by the north–south running Leyte Cordillera which is part of the Philippine Fault Line. The Cordillera reaches a maximum elevation of ca. 1350 m (Mt. Lobi) in the northern part of the island. As geologically young volcanic mountain range, it shows a typical rugged topography of narrow ridges and steep slopes, where landslides are common (Bremer 1995, 1999; Walsh 1996). In its foothills, patches of primary forest without discernible human interference can still be found although the island is densely populated (ca. 262 inhabitants/ km2 as calculated after: NSCB RU-8 2001). The coastal plains have already been deforested in the ﬁrst half of the last century (Barrera et al. 1954). The study area is located in the western part of the Leyte Cordillera, ca. 8 km north of the provincial capital of Baybay, in the foothills of Mt. Pangasugan (1150 m, 1046¢ N, 12450¢ E). In this part of the island, the Cordillera reaches close to the coast. Large parts of the mountain’s western range are extremely steep and are free from trees of this reason. In the eastern part of the Cordillera, the slope has a lower gradient. Primary forest can be found from about 250 m a.s.l. up to the mountain’s summit at 1150 m a.s.l. In hillsides below this elevation, the forests has largely been replaced by coconut plantations and slash and burn agriculture. Only along the small creeks, near natural vegetation can still be found at these lower elevations. Above ca. 600 m a.s.l., the lowland forest formation changes into mossy forest, with its stunted trees and a rich epiphyte community. Within the study area, no recent logging was observed, although forest clearing continues at other localities of the mountain. This can be explained by the area’s status as Forest Reserve of the Leyte State University. Despite this, rattan collection and hunting was observed within the Forest Reserve. [213]

1274

Figure 1.

The Philippine archipelago, the Island of Leyte, and the location of the study area.

Geology and soils The soil type in the primary forest between 370 and 520 m a.s.l. is a haplic Andosol with rudic phase (FAO/UNESCO 1988) overlying basaltic and andesitic breccia (Zikeli 1998). The soil at lower elevations (100 m a.s.l.) has been classiﬁed as haplic Alisol (FAO/UNESCO 1988) over basalt (Asio 1996).

Climate According to the climatic classiﬁcation of the ‘Modiﬁed Corona’s System’, Leyte is climatically divided (Kintanar 1984). Southern Leyte belongs to the climatic type II (i.e. no pronounced dry season), but exhibits a distinct rainfall peak in December and January as a result of the northeast monsoon. The northern part of Leyte which includes the study area has been assigned to climatic type IV, showing a more or less even rainfall distribution throughout [214]

1275 the year. The standardization of the rainfall pattern in northern Leyte compared to that of southern Leyte might be explained by the protective eﬀect of the Island of Samar oﬀ the northeast-coast of Leyte, although Samar’s mountains are lower than those of Leyte (ca. 850 m a.s.l.). Local climatic conditions have been analysed from a 23-years period (1976– 1998) of record by using data from the PAGASA (Philippine Atmospheric, Geophysical and Astronomical Services Administration) weather station on the campus of the Leyte State University (7 m a.s.l.), ca. 1–3 km west of the study plots. The annual average temperature is 27.4 C and the average annual precipitation is 2586 mm. Highest precipitation occurs during November to January. Lowest rainfall is observed between March and May. On average, all months receive at least 100 mm precipitation, i.e. there is no dry month according to the deﬁnition of Walsh (1996). However, drought periods (i.e. less than 50 mm of monthly precipitation according to Walsh 1996) of up to 4 months have been recorded during El Nin˜o Southern Oscillation events. The general rainfall patterns and the climatic conditions measured at the PAGASA station are more similar to climatic type II with its clear impact of the northeast monsoon than to climatic type IV, implying that neither the mountains of Samar nor the Leyte Cordillera itself causes a distinct rain shadow west of Mt. Pangasugan. Orographic rainfalls are an important factor in the Leyte Cordillera, especially in the vicinity of the mountain summits. The summit of Mt. Pangasugan is often observed being cloud covered, and during ﬁeld work heavy rainfalls have been experienced, while the coastal plain did not receive any precipitation. An important climatic feature of the area are typhoons. Leyte lies at the southern margin of the typhoon tracks entering the Philippines, and is hit at a rate of ﬁve typhoons in three years, mainly during the summer months (Parong 1984; cited in Kintanar 1984).

Vegetation analysis Field studies were conducted in 1997 and 1998. The attempt to identify a minimum area in mature primary forest failed due to the heterogeneity of the vegetation. A plot size allowing a reasonable number of replications proved to be 100 m2. Where relief conditions and homogeneity of the vegetation allowed, plots were arranged along a catena from ridge to river bank. The 100-m2 plots were generally designed as quadrats, but on narrow ridges and river banks, other rectangular design was used due to relief constraints. A total of 49 plots was established, with 15 on the ridge, 21 on slopes, and 11 on riverbanks. Two plots were established in ca. 6-year-old land slide successions, with one of them located ca. 2 km south of the main study area. The vegetation analysis procedure was based on a ‘nested quadrat design’ (Kent and Coker 1992). All plants >2.5 m were identiﬁed from the total plots (100 m2). On central subplots of 25 m2, all plants £ 2.5 m [215]

1276 as well as the lianas were considered. Records included epiphytic and climbing plants on the stem bases of trees up to a height of 2.5 m. Crown epiphytes were not included in the analysis, but epiphytes found on the ground were identiﬁed and added to the species lists. From species which could not be identiﬁed in the ﬁeld, voucher specimens were collected. Tall trees were sampled with the help of a tree climber. However, no samples were taken from erect and climbing palms (rattans), because this would have been destructive and the chance of identiﬁcation was very low due to the lack of fertile specimens. Therefore, most palms had to be distinguished as morphospecies. Taxa were assigned to life forms on the base of ﬁeld observations, or with the help of literature information in the case of juveniles. Life form classiﬁcation followed Ellenberg and Mueller-Dombois (1967). Plant samples collected in this study were deposited at the Department of Plant Breeding, Herbarium, Leyte State University, ViSCA, Baybay, Leyte, 6521A, Philippines.

Species identiﬁcation and nomenclature Identiﬁcation of specimens was conducted with the help of literature and specialists. Publications referring to the Philippine ﬂora included de Guzman et al. (1986), Merrill (1912), Pancho (1983), Santos et al. (1986), van Steenis (1950-ongoing), and Zamora and Co 1986). Sources referring to neighbouring countries, which also include many Philippine taxa, were used in addition (Henderson 1974a, b; Ng 1978, 1989; Keng 1983, 1990; Whitmore 1983a, b; Corner 1988; Anonymous 1993, 1994, 1996; Soepadmo and Wong 1995; Soepadmo et al. 1996). Identiﬁcation of seedlings, infertile and juvenile plants was not possible in all cases. For pre-identiﬁcation of taxa and delimitation of morphospecies, ﬁeld characters were very important. Besides the description of such characters in the above mentioned literature, the speciﬁc publications by van Balgooy (1997a, b) and Keller (1996) were used. Tree seedlings were identiﬁed with help of Ng (1991) and Burger (1972). In addition, plants were identiﬁed by taxonomists from the Philippine National Herbarium, Manila, the National Herbarium of the Netherlands, Leiden Branch, and collaboratively during meetings of the Philippine Native Plant Group. Nomenclature followed various sources as cited above. However, priority was given to the Flora Malesiana (van Steenis 1950-ongoing), whenever possible. The legumes were assigned to the traditional family of Leguminosae. Scientiﬁc names were not derived from the translation of local names in any case.

Data analysis Species richness, diversity and evenness were determined for each of the 49 plots. Only those plants rooting within the plots were considered in the [216]

1277 analysis. The Shannon-Index (H¢) was used as a robust and simple diversity measure (Magurran 1988). For the analysis of species dominance patterns, Evenness (E) based on the Shannon-Index was calculated for each of the plots. To assess the area’s value as a refuge to Philippine tree species, the characterization of forest types by Whitford (1911) was used. His classiﬁcation and characterization is based on the occurrence of typical tree species and tree species combinations. He often used vernacular names or typical families or genera as e.g. ‘Apitong’ for Dipterocarpus spp. to characterise his forest types. For many of these vernacular names a scientiﬁc species could not be assigned with certainty, and therefore, were not used for comparisons. Whitford (1911) pointed out that the description of his forest types was based on a still fragmentary knowledge of Philippine forests. Most of his ‘typical’ tree species – with few exceptions such as mangroves – occur in the other forest types as well. For example, many species of the dipterocarp forest types occur at wet localities in the Molave forest (limestone forest). On the other hand, the typical Molave forest species also exist in the dipterocarp forest types, especially on dry sites. Of such reasons, Whitford’s (1911) forest types are primarily related to the major habitat conditions in the Philippines and do not represent real plant associations. The comparison of the species recorded in this study with Whitford’s (1911) forest types merely demonstrates the diverse habitat conditions in the present study area. Unfortunately, not much work has been conducted so far to improve Whitford’s system, and information on species composition of the undergrowth vegetation, which might be especially valuable to characterise habitat conditions (Schulze and Whitacre 1999), is still missing.

Results From the 49 plots, a total of 685 taxa was recorded. Of these, 58.3% were identiﬁed to species level, 86.2% to genus level, and 96.7% to family level. The remaining 3.3% of the taxa could only be assigned to higher taxonomic levels. All taxa identiﬁed to species level are listed in the Appendix. Species inventory was clearly dominated by angiosperms, accounting for 92.1% of all species. The pteridophytes represented 7.5% of the species. Only three species of gymnosperms (Podocarpus rumphii, Gnetum gnemon, G. latifolium) were found (Table 1). More than half (52%) of all species identiﬁed are endemic to the Philippines, including one endemic genus (Greeniopsis, Rubiaceae). The most common families were the Rubiaceae (35 species) and the Euphorbiaceae (32 species), followed by the herbaceous family of Araceae and the erect and climbing palms (Arecaceae) with 28 species each. The Meliaceae and Moraceae included 27 species each (Figure 2). The ratio between the number of genera and the number of species ranged between 1:1.5 (Anacardiaceae) and 1:6.7 (Moraceae). The frequency of taxa was low. Nearly half (48.5%) of all taxa were recorded from only one of the 49 plots, and nearly one third (30.5%) of the taxa were [217]

1278 Table 1. Taxonomic composition of 49 non-contiguous plots (100 m2 each) in lowland forest remnants of the study area in the foothills of Leyte Cordilliera. Spermatophytes (%)

Families Genera Species

Gymnosperms

Angiosperms

2 (1.8) 2 (0.7) 3 (0.4)

94 (84.7) 261 (90.3) 631 (92.1)

Pteridophytes (%)

Total (%)

15 (13.5) 26 (9) 51 (7.5)

111 (100) 289 (100) 685 (100)

Figure 2. The 20 most common plant families recorded from 49 plots (100 m2 each) in the study area. Figures in brackets indicate the ratio between the number of genera and the number of species. [218]

1279 represented by only one single individual. Very few species showed high frequencies as e.g. the two tree species, Calophyllum blancoi (present in 32 plots) and Dacryodes rostrata (present in 31 plots), which was due to a high rate of juveniles. The average number of species per plot was 47 and ranged between 17 and 80. Shannon diversity (H¢) reached values between 2.2 and 3.9, and evenness (E) ranged between 0.64 and 0.98. The species–area curve for all plots shows a steady increase of species numbers with only a weak tendency to level oﬀ (Figure 3). The ﬂattening of the curve at its beginning is the result of the river bank vegetation which was comparatively species poor and homogenous. The species–area curve starts to rise again with the addition of the slope plots. Life form composition is clearly dominated by phanerophytes (65.3% of all taxa), followed by lianas (17.1%) and chamaephytes (16.9%). Geophytes were rare (0.7%) and largely represented by few ground orchids. Hemicryptophytes and therophytes were absent (Figure 4). Epiphytes were not the focus of this study and are therefore not included in the calculation of life form composition. A rough estimate of epiphyte contribution to the area’s species inventory is ca. 10%. The most conspicuous epiphytic plant group observed were orchids. Many of the vegetation clusters observed in the tree crowns were composed of the accumulation of orchid bulbs belonging to a single species (e.g. Grammatophyllum multiﬂorum). The following taxa occurring in the study plots have been classiﬁed by Soepadmo (1995) as endangered and economically important lowland forest genera in SE Asia: Anisoptera, Dipterocarpus, Parashorea, Shorea, Vatica (Dipterocarpaceae), Artocarpus (Moraceae), Mangifera (Anacardiaceae), and Calamus (Arecaceae). Additionally, 41 of the tree species recorded are listed as endangered for the Philippines by IUCN (2000). Of these, 23 are classiﬁed as vulnerable, one as endangered, and 17 as critically endangered (see Appendix).

Figure 3. Species–area curve for 49 plots (100 m2 each) in the study area. [219]

1280

Figure 4. Life form spectrum (after Ellenberg and Mu¨ller-Dombois 1967) of species recorded from 49 plots (100 m2 each) in the study area.

Discussion The 685 taxa recorded from the 49 plots account for nearly 8% of the ca. 8900 vascular plant species so far described for the Philippines (Davis et al. 1995). Although the plots were not contiguous and species numbers can therefore be expected to be higher than in contiguous plots (Whitmore 1985) this ﬁgure is high, considering the small overall study area (4900 m2 in total). Only very few datasets cover tropical lowland forest vegetation comprehensively and are therefore suitable for comparison. The only study using the same plot size was conducted by Whitmore et al. (1985) in the tropical lowland rain forest of Costa Rica, who analysed a plot of 100 m2, considering all vascular plants. They recorded a total of 233 species, including 59 (25%) epiphyte species. In the present study, the highest number of species recorded from a single 100-m2 plot was 80 and thus much lower than the number found by Whitmore et al. (1985). However, in the present study the vegetation up to 2.5 m tall as well as the lianas were collected from subplots of 25 m2, and crown epiphytes were excluded. Despite this, the maximum number of vascular plant species on 100m2 plots in the study area can expected to be clearly lower than the number of 233 species recorded by Whitmore et al. (1985). An estimate of the overall vascular plant species richness of Mt. Pangasugan area, including mossy forest as well as the diﬀerent stages of succession, results in 1500–2000 species. This estimate is based on the very conservative assumption that 50% of the lowland forest species was recorded in this study, and that the mossy forest has a similar species richness as a 1-ha plot studied by [220]

1281 Meijer (1959) in a montane rainforest in Indonesia (333 vascular plant species). The numbers of tree species given by Ingle (2001) (100 species ‡5 cm dbh) and Hamann et al. (1999) (92 species ‡10 cm dbh) for 0.75- and 1-ha plots, respectively, in Philippine mountain environments show that the overall species richness including all life forms can be expected to be roughly similar to that of Meijer (1959) in Indonesia.

Representation of taxa The composition of taxa observed in this study is similar to other areas in Southeast Asia. Diﬀerences to such sites are related to the proportions of families and result mainly from diﬀerent inventory approaches. For trees alone, the dominance of the Dipterocarpaceae and the Euphorbiaceae concerning number of species is well documented (Manokaran and Kochummen 1990; Sist and Saridan 1998; Slik et al. 2003; Wilkie et al. 2004). Sist and Saridan (1998) report that the Dipterocarpaceae represent 70% of all trees ‡ 50 cm dbh in a primary forest in East Kalimantan. In our study, the Dipterocarpaceae were the most common family in the canopy layer (12 of 44 species). Turner (1994) analysed the vascular ﬂora of Singapore and its main habitat types from herbarium collections.The Orchidaceae are the most speciose family in his taxonomic spectrum. This reﬂects the large number of orchid species in Malesia (6500 species according to Soepadmo 1995). In our study, however, Orchidaceae are poorly represented because we did not include crown epiphytes. Without considering the orchids in both studies, the pteridophytes are the most speciose group, followed by the Rubiaceae and the Euphorbiaceae in both studies. The other predominant families in terms of species richness listed by Turner (1994) are Annonaceae, Moraceae, Arecaceae/Palmae, Myrtaceae, Melastomataceae and Lauraceae. With exception of the Melastomataceae, these are also the most speciose families in our study (Figure 2).

Representation of forest types The rugged relief of the study area represents a broad spectrum of Philippine habitats. The comparison of the tree species recorded from our study with the typical tree species composition of the forest types described by Whitford (1911) showed a high degree of correspondence. Many tree species typical of the ﬁve dipterocarp forest types as well as the Molave type (Figure 5) were present. From the 18 tree species listed by Whitford (1911) as typical for the Laua´n-haga´ghak, 15 were also present in our study area. Originally, this forest type is established on lowland plains on wet soils (Whitford 1911), but was transformed into rice ﬁelds in the study area. However, tree species representing this type of forest still occur on the banks of the small creeks at low [221]

1282

Figure 5. Comparison of the number of characteristic species of the diﬀerent lowland forest types in the Philippines (after Whitford 1911) with the number of respective species recorded in this study.

elevations. The typical tree species of other forest types were also well represented (Figure 5). The high number of Molave type species (50% of the typical species as mentioned by Whitford 1911) in the study area is remarkable, as this forest represents dry limestone areas (Whitford 1911). This is another indication that the area’s vegetation might be strongly inﬂuenced by drought periods.

Life form composition The dominance of trees and phanerophytes is a typical feature of tropical rain forests (Richards 1996). In our study, Phanerophytes account for 65.3% of the species. Richards (1996) provides ﬁgures from a rain forest in Guyana, which are based on the Raunkiaer System (Raunkiaer 1934) and cannot be directly compared with our data. We therefore recalculated his data by excluding the lianas from the phanerophytes and excluded the epiphytes in addition. This resulted in a life form composition of 60% phanerophytes, 16% chamaephytes, and 24% lianas. A similar recalculation of ﬁgures provided by Cromer and Pryor (1942) for a rain forest in Queensland results in 77.1% phanerophytes, 12.5% chamaephytes, and 10.4% lianas. Figures for a terra ﬁrme rain forest in [222]

1283 Brasilia (Cain et al. 1956) are: phanerophytes 74.3%, chamaephytes 0.9%, hemicryptophytes 2.8%, geophytes 0.9%, lianas 12.8%, and epiphytes 8.3%. Therophytes and hemicryptophytes are usually absent from undisturbed tropical rain forests (Richards 1996). Geophytes are also often absent as in Richards’ Guyana study or represented by few species as in the present study (0.7%), where they were mainly made up of ground orchids. The estimated proportion of epiphyte species of the total number of species in this study (ca. 10%) is clearly lower than the numbers given by Whitmore et al. (1985) (25%) for Costa Rica or by Gentry and Dodson (1987) (35%) for Ecuador.

Conservation value Kochummen et al. (1992) stated that comparatively small areas might represent high numbers of a regional ﬂora. They found that their 50-ha plot in the Pasoh Forest Reserve (Malaysia) included 25% of all trees and shrubs (‡ 1 cm dbh) of the Malay Peninsula. In our study, an overall sample area of approximately half hectare included ca. 8% of all Philippine vascular plant species. Given the small area considered as well as the fact that neither the successional vegetation nor the mossy forest is included, the representation of Philippine ﬂora in the Mt. Pangasugan area is clearly higher than 8%. The proportion of 52% endemic taxa recorded in this study is clearly higher than the proportion of 39% stated as an average for the Philippines (Davis et al. 1995). This result agrees with Ashton (1993) who stated that the southeastern part of the Philippines is especially rich in endemic plants. The area’s endemism might be even higher than 52%, as a number of taxa could not be identiﬁed. For example, only 3 of the 16 rattan species (Arecaceae) recorded, which generally show a high degree of endemism (Dransﬁeld 1990), could be assigned to a scientiﬁc name. Two of them were Philippine endemics. Another aspect referring to the conservation value of the area is the occurrence of 41 tree species in the red list of IUCN (2000). However, from the species recorded from this study, other than trees are not represented in the red list. Despite this, it can be expected that many of the non-tree taxa recorded are threatened by habitat destruction as well. For example, no rattans are listed by IUCN although this plant group is still heavily exploited and shows high rates of endemism. The IUCN red list seems to have a strong focus on well known and economically important tree species. This is supported by the fact that only dipterocarps are classiﬁed as critically endangered, although many other tree species are more rare in the study area. This was e.g. true for the valuable tree species Heritiera sylvatica (Sterculiaceae) and Xanthostemon verdugonianus (Myrtaceae) which were known by local farmers from only one mature tree each in the entire western foothills of Mt. Pangasugan. Taken together, the Mt. Pangasugan region on Leyte represents a unique refuge for a high number of species, which are characteristic of all Philippine [223]

1284 dipterocarp forest types and the molave type. In view of the large areas of degraded land in the Philippines, the conservation value of the Mt. Pangasugan region is very high and represents an important gene bank of the Philippine forest vegetation.

Acknowledgements This study was part of the ViSCA-gtz Applied Tropical Ecology Program (PN 95.2290.5–001.00) and partly funded by the Tropical Ecology Support Program (TO¨B) of GTZ (PN 90.2136.1–03.107). We are grateful to the President of the Leyte State University, Dr. P.P. Milan and her staﬀ for their support and help. We are also grateful to the Cienda San Vicente Farmer Association (CSVFA) and their community organiser Marlito Bande, who made the extensive ﬁeld trips possible. Special thanks to the curator of the Philippine National Herbarium, Dr. Madulid, and his staﬀ, as well as to the director of the National Herbarium of the Netherlands, Leiden branch, Prof. Baas and his staﬀ who helped to put species identiﬁcation on a ﬁrm ground. We are also very grateful to Leonardo Co, Nina Ingle, David and Luze Bicknell, Franz Seidenschwarz, and B.C. Tan for various assistance. We also like to thank the two anonymous referees for their comments and constructive criticism.

Appendix

Species list of the vascular plant species found in 49 plots (100 m2 each) in the foothills of the Leyte Cordillera at Mt. Pangasugan, Leyte, Philippines. The list includes only those species which could be identiﬁed to species level. Some species recorded outside the plots are provided in addition. Numbers in brackets following the species name indicate the ﬁrst voucher specimen collected of this species. Life form classiﬁcation of species is based on observations of mature individuals in the study area, or from species descriptions in literature. Life form deﬁnitions follow Ellenberg and Mueller-Dombois (1967) with a minor revision by Richter (1997). MacP, Macrophanerophyte (>20–50 m); MesP, Mesophanerophyte (>5–20 m); MiP, Microphanerophyte (>2–5 m); NP, Nanophanerophyte (>1–2 m); NP herb, herbaceous Nanophanerophyte; Ch, Chamaephyte ( £ 1 m); Ch frut, fruticose Chamaephyte; Ch suﬀ, suﬀruticose Chamaephyte; Ch herb, herbaceous Chamaephyte; G rhiz, rhizome Geophyte; PL, Phanerophytic Liana; r PL, root PL; st PL, winding PL; el PL, tendril PL; d PL, spread climber; E, Epiphyte.

[224]

1285 Species classiﬁed by IUCN (2000) as endangered are listed along with their status in bold letters. Short deﬁnitions of the status are: CR, critically endangered (‘… facing an extremely high risk of extinction in the wild in the immediate future …’); EN, endangered (‘… not critically endangered but facing a very high risk of extinction in the wild in the near future …’); VU, vulnerable (‘… not critically endangered or endangered but facing high risk of extinction in the wild in the medium-term future …’). For comprehensive deﬁnitions and criteria of classiﬁcation see www. iucnredlist.org/search-basic.html I. Spermatophyta

Life form

Aceraceae Acer laurinum Hassk. (1221)

MacP

Actinidiaceae Saurauia cf. denticulata C.B. Rob. (1078) Saurauia samarensis Merr. (235)

MiP MiP

Alangiaceae Alangium longiﬂorum Merr. (1331) VU

MesP

Amaranthaceae Deeringia polysperma (Roxb.) Moq. (2214)

Ch herb

Anacardiaceae Dracontomelon dao (Blco.) Merr. & Rolfe (660) Dracontomelon edule (Blco.) Skeels Koordersiodendron pinnatum (Blco) Merr. (162) Mangifera altissima Blco. (971) VU Rhus taitensis Guill. (818) Semecarpus cuneiformis Blco. (538)

MacP Mes MacP MacP MesP MiP

Annonaceae Alphonsea arborea (Blco.) Merr. (1009) Anaxagorea javanica Bl. (1509) Artabotrys cf. rolfei Vid. (2159) Cananga odorata (Lamk.) Hook. f. & Thoms. Goniothalamus elmeri Merr. (327) Meiogyne virgata (Bl.) Miq. Papualthia cf. lanceolata (Vid.) Merr. (206) Popowia pisocarpa (Bl.) Endl. (1054)

MesP MiP el PL MesP MiP MesP MesP MesP

Apocynaceae Alstonia macrophylla Wall. ex. G. Don (1774) Alstonia scholaris (L.) R. Br. Kibatalia blancoi (Rolfe) Merr. (467) Lepiniopsis ternatensis Val. (2220) Tabernaemontana pandacaqui Poir. (140) Voacanga globosa (Blco.) Merr. (218)

MesP MesP MesP MesP MicP MiP

Araceae Alocasia cf. zebrina Schott ex van Houtte (1677) Amorphophallus paeoniifolius (Dennst.) Nicolson (1924) Costus speciosus (J. Konig) Sm

Ch herb NP herb NP herb

[225]

1286 Spermatophyta

Life form

Pothos cylindricus Presl (1226) Raphidophora korthalsii Schott (881)

r PL d PL

Araliaceae Arthrophyllum ahernianum Merr. (1911) Osmoxylon trilobatum (Merr.) Philipson (220) Polyscias nodosa (Bl.) Seem.

MesP NP MesP

Arecaceae Calamus cf. merrillii Becc. Caryota cf. cumingii Lodd. ex Mart Caryota cf. mitis Lour. (560) Daemonorops cf. mollis (Blco.) Merr. (593) Korthalsia laciniosa Mart. (1120) Pinanga maculata Porte Caryota rumphiana Mart. var. philippinensis Becc.

d PL MiP MesP PL d PL MiP MacP

Aristolochiaceae Aristolochia philippinensis Warb. (702)

Ch suﬀ

Asclepiadaceae Hoya multiﬂora Bl. (689)

PL

Asteraceae Vernonia arborea Buch.-Ham. (826)

MesP

Bignoniaceae Oroxylum indicum (L.) Vent. Radermachera pinnata (Blco.) Seem. (1129)

MesP MesP

Burseraceae Canarium asperum Benth. (265) Canarium denticulatum Bl. (428) Canarium euryphyllum Perk. (1265) Canarium gracile Engl. (611) Canarium hirsutum Willd. (1714) Dacryodes rostrata (Bl.) H. J. Lam (247)

MacP MesP MacP MesP MesP MacP

Caprifoliaceae Sambucus javanica Reinw. ex Bl.

MiP

Casuarinaceae Gymnostoma rumphianum (Miq.) L.A.S. Johnson (1915)

MesP

Cecropiaceae Poikilospermum erectum (Blco) Merr. (321) Poikilospermum suaveolens (Bl.) Merr. (328)

d PL d PL

Celastraceae Bhesa paniculata Arn. (812) Euonymus cochinchinensis Pierre (495) Euonymus javanicus Bl. (232) Lophopetalum javanicum (Zoll.) Turcz. (1127)

MesP MesP MesP MacP

Chloranthaceae Chloranthus erectus (Buch.-Ham.) Verdc. (1522) Sarcandra glabra (Thunb.) Nakai (562)

Ch suﬀ Ch frut

[226]

1287 Spermatophyta

Life form

Chrysobalanaceae Maranthes corymbosa Bl. (790)

MacP

Clusiaceae Calophyllum blancoi Pl. & Tr. (278) Calophyllum soulattri Burm. f. (1250) Cratoxylum formosum Benth. & Hook. f. ex Dyer (452)

MesP MesP MesP

Combretaceae Terminalia microcarpa Decne. (672) Terminalia nitens Presl (481) VU

MacP MesP

Commelinaceae Floscope scandens Lour. Forrestia hispida Less. & A. Rich. (423) Pollia sorzogoniensis (E. Meyer) Steud. Pollia thyrsiﬂora (Bl.) Steud. Rhopalephora cf. vitiensis (Seem.) Fader (2102)

Ch Ch Ch Ch Ch

Connaraceae Agelaea borneensis (Hook. f.) Merr. (491) Connarus culionensis Merr. (686) Connarus semidecandrus Jack (623) Ellipanthus tomentosus Kurz (396)

st PL PL PL MesP

Crypteroniaceae Crypteronia cumingii (Planch.) Planch. ex Endl. (1693)

MesP

Cunoniaceae Weinmannia cf. hutchinsonii Merr. (130)

MesP

Datiscaceae Octomeles sumatrana Miq.

MacP

Dilleniaceae Dillenia megalantha Merr. (2007) VU Dillenia philippinensis Rolfe VU Tetracera fagifolia Bl. (674)

MesP MesP st PL

Dioscoreaceae Dioscorea hispida Dennst.

PL

Dipterocarpaceae Anisoptera thurifera Foxw. ssp. thurifera (353) Dipterocarpus gracilis Bl. (486) CR Dipterocarpus validus Bl. CR Hopea acuminata Merr. (292) CR Hopea malibato Foxw. ex Elm. (20) CR Hopea philippinensis Dyer (925) CR Hopea plagata (Blco.) Vid. (305) CR Parashorea malaanonan (Blco.) Merr. (267) CR Shorea almon Foxw. (430) CR Shorea assamica Dyer forma philippinensis (Brandis) Sym. (269) CR Shorea astylosa Foxw. (1796) CR Shorea cf. hopeifolia (Heim) Sym. (2110) CR Shorea contorta Vid. (1001) CR

MacP MacP MacP MacP MacP MacP MacP MacP MacP MacP MacP MakP MacP

[227]

herb herb herb herb herb

1288 Spermatophyta

Life form

Shorea falciferoides Foxw. ssp. falciferoides (290) CR Shorea guiso (Blco) Bl. (384) CR Shorea palosapis (Blco) Merr. (263) CR Shorea polysperma (Blco) Merr. (297) CR Vatica mangachapui Blco. (528) EN

MacP MacP MacP MacP MacP

Ebenaceae Diospyros blancoi A. DC. (163) VU Diospyros cf. nitida Merr. (1901) Diospyros curranii Merr. (1631) Diospyros multibracteata Merr. (598) Diospyros pilosanthera Blco. Diospyros pyrrhocarpa Miq. (385)

MacP MiP MesP MiP MesP MesP

Elaeagnaceae Elaeagnus triﬂora Roxb. var. triﬂora (412)

dPL frut

Elaeocarpaceae Elaeocarpus cumingii Turcz. (1123)

MesP

Euphorbiaceae Acalypha amentacea Roxb. (254) Antidesma digitaliforme Tul. (371) Antidesma nitidum Tul. (268) Antidesma tomentosum Bl. (919) Aporosa benthamiana Hook. f. (573) Baccaurea tetrandra (Baill.) Mu¨ll. Arg. (360) Bridelia glauca Bl. (233) Claoxylon brachyandrum Pax & K. Hoﬀm. (379) Cleistanthus cf. glaber Airy Shaw (628) Cleistanthus sumatranus (Miq.) Mu¨ll. Arg. (396) Codiaeum luzonicum Merr. Croton cascarilloides Raeusch. (205) Drypetes cf. megacarpa (Bl.) Pax & Hoﬀm. (374) Drypetes longifolia (Merr.) Pax et Hoﬀm. (372) Glochidion rubrum Bl. (715) Macaranga caudatifolia Elm. (735) VU Macaranga grandifolia (Blcol.) Merr. VU Macaranga hispida (Bl.) Muell.-Arg. Macaranga tanarius (L.) Muell.-Arg. Mallotus cf. paniculatus (Lam.) Muell.-Arg. (330) Mallotus ﬂoribundus (Bl.) Muell.-Arg. (228) Mallotus lackeyi Elm. (1800) Mallotus philippensis (Lam.) Muell.-Arg. (302) Neotrewia cumingii (Muell.-Arg.) Pax & Hoﬀm. (343) Omalanthus populneus (Geisel.) Pax Phyllanthus leytensis Elm. (250) Suregada glomerulata (Hassk.) Jones (287)

NP NP MiP MicP MiP MesP MesP MesP MesP MesP MiP NP MiP MiP MiP MiP MesP MiP MesP MesP MesP MesP MesP MesP MiP Ch frut NP

Fagaceae Lithocarpus buddii (Merr.) A. Camus (15) Lithocarpus caudatifolia (Merr.) Rehd. (555) Lithocarpus coopertus (Blco) Rehd. (387)

MacP MesP MesP

[228]

1289 Spermatophyta

Life form

Flacourtiaceae Casearia cf. mindanaensis Merr. (1675) Casearia grewiaefolia Vent. var. gelonioides (Bl.) Sleum. (794) Flacourtia cf. indica (Burm. f.) Merr. (378) Osmelia philippina (Turcz.) Benth. (352)

P MesP MesP MesP

Flagellariaceae Flagellaria indica L. (1128)

el PL

Gesneriaceae Cyrtandra angularis Elm. (2212) Cyrtandra glaucescens Kranzl. (960) Monophyllaea merrilliana Kranzl. (2027) Rhynchoglossum obliquum Bl.

Ch Ch Ch Ch

Gnetaceae Gnetum gnemon L. var. gnemon (375) Gnetum latifolium Bl.

MesP PL

Hamamelidaceae Sycopsis dunnii Hemsl. (739)

MesP

Hernandiaceae Illigera megaptera Merr. (721)

PL

Icacinaceae Gomphandra cumingiana (Miers) F.-Vill. (1118) Gonocaryum calleryanum (Baill.) Becc. (700) Miquelia celebica Bl. Phytocrine macrophylla (Bl.) Bl. var. macrophylla Platea excelsa Bl. var. borneensis (Heine) Sleum. (1217)

MesP MesP PL PL MesP

Ixonanthaceae Ixonanthes petiolaris Bl.

MesP

Juglandaceae Engelhardtia serrata Bl. (411)

MacP

Lamiaceae Gomphostemma javanicum (Bl.) Bth. (285)

Ch herb

Lauraceae Actinodaphne apoensis Merr. (1083) Actinodaphne bicolor (Elm.) Merr. Actinodaphne cf. multiﬂora Benth. (833) Caryodaphnopsis tonkinensis (Lec.) Shaw (441) Cinnamomum mercadoi Vid. (468) VU Endiandra coriacea Merr. (1883) Litsea garciae Vid. (478) Litsea leytensis Merr. (805) VU Neolitsea cf. vidallii Merr. (272) VU

MesP MesP MesP MesP MacP MesP MesP MesP MiP

[229]

herb herb herb herb

1290 Spermatophyta

Life form

Leeaceae Leea aculeata Bl. ex Spreng. Leea guineensis G. Don (255) Leea quadriﬁda Merr. (546)

Mip MiP MiP

Leguminosae Afzelia rhomboidea (Blco.) Vid. VU Albizia procera (Roxb.) Benth. Albizia saponaria (Lour.) Bl. ex Miq. Archidendron clypearia var. casai (Blco.) I.C. Nielsen (1082) Archidendron pauciﬂorum (Benth.) Nielsen (1852) Archidendron scutiferum (Blco.) I.C. Nielsen (323) Bauhinia integrifolia Roxb. ssp. cumingiana (Benth.) K. & S.S. Larsen (364)

MesP MacP MesP MesP MiP MesP PL

Dalbergia cf. mimosella (Blco) Prain (1435) Desmodium laxum DC. (820) Entada phaseoloides (L.) Merr. Erythrina subumbrans (Hassk.) Merr. Euchresta horsﬁeldii (Lesch.) Benn. (847) Kingiodendron alternifolium (Elm.) Merr. & Rolfe (357) Ormosia calavensis Azaola Pterocarpus indicus Willd. VU Wallaceodendron celebicum Koord. (395)

MesP Ch herb el PL MacP Ch herb MacP MesP MesP MacP

Liliaceae Dianella ensifolia (L.) DC.

Ch herb

Loganiaceae Fagraea auriculata Jack ssp. auriculata (851) Fagraea racemosa Jack ex Wall. Strychnos luzoniensis Elm. (748)

st PL MiP el PL

Magnoliaceae Magnolia liliifera (L.) Baill. var. angatensis (719)

MesP

Marantaceae Donax cannaeformis (Forst. f.) K. Schum. (1006)

MiP

Marattiaceae Angiopteris evecta (Forst.) Hoﬀm. (1188) Marattia pellucida Presl (1444)

NP herb Ch herb

Melastomataceae Memecylon paniculatum Jack (311)

MiP

Meliaceae Aglaia argentea Bl. (642) Aglaia costata Merr. (275) VU Aglaia elliptica Bl. (1295) Aglaia luzoniensis (Vid.) Merr. & Rolfe (511) Aphanamixis polystachia (Wall.) R.N. Parker (941) Chisocheton ceramicus (Miq.) C. DC.) (1184) Chisocheton cumingianus (C. DC.) Harms (211) Chisocheton pentandrus (Blco.) Merr. (753)

MesP MesP MesP MiP MesP MesP MesP MesP

[230]

1291 Spermatophyta

Life form

Dysoxylum arborescens (Bl.) Miq. (664) Dysoxylum cumingianum C. DC. (316) Reinwardtiodendron humile (Hassk.) Mabb. (965) Toona calantas Merr. & Rolfe (918) Vavaea amicorum Benth. (273) Walsura cf. pinnata Hassk. (2082)

MesP MesP MesP MacP NP MesP

Menispermaceae Arcangelisia ﬂava (L.) Merr. (1798)

el PL

Monimiaceae Matthaea pubescens Merr. (139)

MiP

Moraceae Ficus aurita Bl. (210) Artocarpus blancoi (Elm.) Merr. (1701) VU Artocarpus elastica Reinw. ex Bl. (697) Ficus balete Merr. (v) Ficus benjamina L. (1075) Ficus cumingii Miq. var. angustissima (Merr.) Corner (778) Ficus ﬁstulosa Reinw. ex Bl. (1307) Ficus heteropoda Miq. (425) Ficus odorata (Blco.) Merr. Ficus pedunculosa Miq. (1780) Ficus pseudopalma Blco. Ficus punctata Thunb. (406) Ficus ribes Reinw. ex Bl. (405) Ficus ruﬁcaulis Merr. Ficus subulata Bl. (646, 1966) Ficus ulmifolia Lam. (451) VU Maclura cochinchinensis (Lour.) Corner (1417) Streblus ilicifolia (Vid.) Corner (1700) Streblus macrophyllus Bl. (216, 335, 613)

MiP MacP MacP MacP MacP MesP MiP MiP MesP MiP NP r PL MiP MesP PL MesP d PL MesP MesP

Myristicaceae Endocomia macrocoma (Miq.) W.J.J. de Wilde subsp. prainii (King) W.J.J.de Wilde (479) Gymnacranthera farquhariana (Hook. f. & Th) Warb. var. paniculata (A. DC.) R. Schouten (541) Horsﬁeldia cf. costulata (Miq.) Warb. (2002) Knema glomerata (Blco.) Merr. (641) Knema stellata Merr. (1481) Myristica cf. frugifera W. J. J. de Wilde (743) VU Myristica cf. philippensis Lam. VU Myristica simiarum A. DC cf ssp. simiarum (417)

MesP MesP MesP MesP MesP MesP

Myrsinaceae Ardisia pardalina Mez. (815) Ardisia squamulosa Presl (204) VU Maesa denticulata Mez (241)

Ch frut Ch frut MiP

Myrtaceae Acmena acuminatissima (Bl.) Merr. & Perry (503)

MacP

[231]

MesP MesP

1292 Spermatophyta

Life form

Syzygium cf. densinervium (Merr.) Merr. (749) Syzygium cf. xanthophyllum (C.B. Rob.) Merr. Syzygium cumini (L.) Skeel Tristaniopsis decorticata (Merr.) P.G. Wilson & J.T. Waterh. (142) VU Tristaniopsis micrantha (Merr.) P.G. Wilson & J.T. Waterh. (301) Xanthostemon verdugonianus Naves (2209) VU

MesP MesP MesP MesP MesP MacP

Ochnaceae Gomphia serrata (Gaertn.) Kanis

MesP

Olacaceae Erythropalum scandens Bl. (780) Strombosia philippinensis (Baill.) Rolfe (380)

el PL MesP

Oleaceae Olea borneensis Boerl. (306)

MesP

Opiliaceae Champereia manillana (Bl.) Merr. (100) Melientha suavis Pierre ssp. suavis (366)

MesP MesP

Orchidaceae Calanthe triplicata (Willem.) Ames Ceratostylis retisquama Rchb. f.B143 Cymbidium aliciae Quis. (880) Eulophia zollingeri (Reichb.f.) J.J.Smith Grammatophyllum multiﬂorum var. tigrinum Lindley. Lepidogyne longifolia (Bl.) Bl. Liparis wenzelii Ames Phalaenopsis hieroglyphica (Rchb. f.) Sweet Robiquetia cf. compressa Schltr. Trichoglottis latisepala Ames Trichoglottis rosea (Lindl.) Ames (1055)

G E E G E G G E E E E

Pandanaceae Freycinetia cf. philippinensis Hemsl. (1353) Freycinetia cumingiana Gaudich. (388, 1234) Freycinetia multiﬂora Merr. (1130) Freycinetia vidalii Hemsl. (1352) Freycinetia membranifolia Elm. (955)

r r r r r

Pentaphragmataceae Pentaphragma grandiﬂorum Kurz (457, 458, 1407)

Ch herb

Piperaceae Piper abbreviatum Opiz (638) Piper halconense C. CD. Piper toppingii C. CD. (654, 1143) Piper viminale Opiz (1205)

st st st st

Pittosporaceae Pittosporum resiniferum Hemsl. (448)

Mesp

[232]

rhiz

rhiz rhiz rhiz

PL PL PL PL PL

PL PL PL PL

1293 Spermatophyta

Life form

Poaceae Bambusa spinosa Roxb. Dinochloa cf. pubiramea Gamble Dinochloa cf. scandens (Bl.) O. Ktze.

MesP PL PL

Podocarpaceae Podocarpus rumphii Bl. (1520)

MacP

Polygalaceae Polygala venenosa Juss. ex Poir. (284, 2011) Xanthophyllum vitellinum (Bl.) Dietr. (992)

Ch herb MesP

Proteaceae Helicia graciliﬂora Merr. (1154) Helicia loranthoides Presl. (1079) Helicia robusta (Roxb.) R. Br. ex Wall. (588)

MiP MesP MiP

Ranunculaceae Clematis javana DC. (159, 1997)

PL

Rhamnaceae Ventilago dichotoma (Blco.) Merr. (723) Ziziphus angustifolius (Miq.) Hatusima ex Steenis (488) Ziziphus crebrivenosa C.B. Rob. (492, 661)

PL MesP d PL

Rhizophoraceae Gynotroches axillaris Bl. (1538)

MacP

Rosaceae Prunus arborea (Bl.) Kalkm. var. arborea (1624) Prunus cf. fragrans (Elm.) Kalkm. (795) Prunus grisea (Bl.) Kalkm. var. grisea (71, 490) Rubus fraxinifolius Poiret (2017)

MesP MesP MesP d PL suﬀ

Rubiaceae Boholia nematostylis Merr. (1919) Canthium gynochthodes Baill. (563) Diodia ocynifolia (Willd.) Brem. (1424) Diplospora cf. fasciculiﬂora Elm. (663) Dolicholobium philippinense Trenteuse (260) Greeniopsis multiﬂora (Elm.) Merr. (279) Hedyotis baruensis (Miq.) Val. ex Merr. (329) Hypobathrum purpureum (Elm.) Merr. (1507) Ixora bartlingii Elm. (1060) Ixora cf. cumingiana Vidal (509) Ixora cf. macrophylla Bartl. (207) Ixora longistipula Merr. (1122) Ixora macrophylla Barth. Ixora salicifolia (Bl.) DC. (288) Lasianthus cf. obliquinerva Merr. (701) Morinda bracteata Roxb. (326) Mussaenda philippica A. Rich. Mussaenda vidallii Elm. (129) Mycetia javanica (Bl.) Korth. (258) Nauclea subdita (Korth.) Stend. (1958)

Ch herb MesP PL MiP MiP MesP Ch herb MesP Mip MiP MiP MiP MiP NP MiP MiP MiP MiP Ch suﬀ MiP

[233]

1294 Spermatophyta

Life form

Neonauclea formicaria (Elm.) Merr. (793) Neonauclea lanceolata (Bl.) Merr. subsp. gracilis (Vidal) Ridsdale (402) Praravinia cf. mindanensis (Elm.) Brem. (289) Psychotria cf. ixoroides Bartl. ex DC. (515) Psychotria membranifolia Bartl. ex DC. (257) Tarenna cumingiana (Vid.) Elm. (464) Tarrenoidea wallichii (Hook. f.) D.D.Tirvengadum & C. Sastre (307) Timonius arboreus Merr. (248) Uncaria cf. perrottetii (A. Rich.) Merr. (325) Uncaria lanosa Wall. f. philippinensis (Elm.) Ridsd. (900) Uncaria longiﬂora (Poir.) Merr. (1300) Wendlandia luzoniensis DC. (444) Xanthophytum fruticulosum Reinw. ex Bl. (1005)

MiP MesP NP st PL NP MesP MesP MiP el PL el PL el PL MesP NP

Rutaceae Clausena anisumolens (Blco.) Merr. (605) Lunasia amara Blco. (158) Micromelum compressum (Blco.) Merr. (771) Severinia disticha (Blco) Merr. (398)

NP NP NP NP

Sapindaceae Allophyllus cobbe (L.) Raeuschel (823) Cubilia cubili (Blco.) Adelh. (586) Dictyoneura acuminata Bl. ssp. acuminata (246) Dimocarpus fumatus (Bl.) Leenhouts ssp. philippinensis Leenhouts (72) Euphorianthus obtusatus Radlk. ex Koord. (1641) Ganophyllum falcatum Bl. (1212) Guioa cf. diplopetala (Hassk.) Radlk. (1104) Harpullia cupanioides Roxb. (212) Lepisanthes fruticosa (Roxb.) Leenh. (933) Nephelium cf. ramboutanake (Labill.) Leenh. (442) Paranephelium cf. xestophyllum Miq. (727) Pometia pinnata Forst. (578, 1546)

MesP MacP MesP MesP MesP MesP MesP MesP MesP MesP MesP MesP

Sapotaceae Palaquium philippense (Perr.) C. B. Rob. (443) VU Planchonella mindanaensis Clemens (1126) Pouteria ﬁrma (Miq.) Baehni (1237)

MacP MacP MacP

Saxifragaceae Dichroa philippinensis Schltr. Polyosma integrifolia Bl. (1219) Dichroa ﬁbrifuga (807)

Ch frut NP

Simaroubaceae Picrasma javanica Bl. (218)

MesP

Solanaceae Solanum anisophyllum Elm. (225) Solanum ferox L. (282) Sonneratiaceae Duabanga moluccana Bl.

Ch herb Ch herb MacP

[234]

1295 Spermatophyta

Life form

Staphyleaceae Turpinia borneensis (Merr. & Perry) B.L. Linden (1802)

MesP

Sterculiaceae Heritiera sylvatica Vidal (1768) Pterocymbium tinctorium (Blco.) Merr. (345) Pterospermum diversifolium Bl. (270) Pterospermum elongatum Korth. (434) Pterospermum obliquum Blco. (120) Sterculia multistipularis Elm. (251) Sterculia oblongata R. Br. (678) Sterculia philippinensis Merr. (1898) Sterculia stipulata Korth. var. jagorii (Warb.) Tantra

MesP MacP MesP MesP MesP MiP MesP MesP MesP

Symplocaceae Symplocos cochinchinensis(Lour.) Moore var. cochinchinensis (1954)

MicP

Taccaceae Tacca palmata Bl. (303)

G rhiz

Theaceae Eurya acuminata DC. (1314) Ternstroemia philippinensis Merr. var. philippinensis (1491)

NP MesP

Thymelaeaceae Aquilaria cumingiana (Decn) Ridl. (300) Phaleria perrottetiana (Dcne) F.-Vill. (160)

NP Ch suﬀ

Tiliaceae Colona serratifolia Cav. (626) Diplodiscus paniculatus Turcz. (271) VU

MesP MesP

Ulmaceae Celtis cf. philippinensis Blanco Gironniera celtidifolia Gaudich. (238) Trema orientalis (L.) Bl. (2202)

MesP MiP MesP

Urticaceae Cypholophus moluccanus (Bl.) Miq. Leucosyke capitellata (Poir.) Wedd. (242) Maoutia setosa Wedd. Villebrunea rubescens (Bl.) Bl. (324) Villebrunea trinervis Wedd. (733)

Ch frut MiP NP MesP MesP

Verbenaceae Clerodendrum villosum Bl. Teijsmanniodendron pteropodum (Miq.) Bakh. (157) Vitex parviﬂora Juss. (1837) Vitex turczaninowii Merr. (705) Premna odorata Blco. (633)

NP MesP MacP MacP MesP

[235]

1296 II. Ptaridophyta

Life form

Aspidiaceae Didymochlaena cf. truncatula (Sw.) J. Sm. (2056)

Ch herb

Aspleniaceae Asplenium nidus L. (1902) Asplenium tenerum Forst. (2096)

Ch herb Ch herb

Athyriaceae Diplazium asperum (Bl.) Milde (1809) Diplazium esculentum (Retz.) Sw. (1846)

Ch herb Ch herb

Cyatheaceae Cyathea cf. contaminans (Hook.) Copel.

MesP

Davalliaceae Davallia solida (G. Forst.) Sw. (1462) Davallia trichomanoides Bl. var. lorrainii (Hance) Holttum (222)

Ch herb Ch herb

Hymenophyllaceae Trichomanes javanicum Bl. (1042)

Ch herb

Lindsaeaceae Lindsaea lucida Bl. ssp. lucida (533) Sphenomeris chinensis (L.) Maxon Tapeinidium pinnatum (Cav.) C.Chr. (1267)

Ch herb Ch herb Ch herb

Lomariopsidaceae Bolbitis cf. guoyana (Gaudich.) Ching (2016) Bolbitis guoyana (Gaudich.) Ching Bolbitis heteroclita (Presl) Ching (1049) Lomogramma cf. copelandii Holttum (1851) Lomogramma copelandii Holttum Teratophyllum arthropteroides (Christ) Holttum (2084) Teratophyllum cf. articulatum (J. Sm. ex Fe`e) Mett. (516)

Ch herb Ch herb r PL r PL r PL Ch herb Ch herb

Osmundaceae Osmunda banksiaefolia (Pr.) Kuhn (1261, 1392)

Ch herb

Polypodiaceae Drynaria quercifolia (L.) J. Sm Leptochilus cf. decurrens Bl. Microsorum cf. longissimum J. Sm. ex Fe´e (964) Microsorum membranifolium (R. Br.) Ching Microsorum punctatum (L.) Copel. (1821) Microsorum scolopendria (Burm. f.) Copel. (1445) Pyrrosia cf. lanceolata (L.) Farwell Microsorum plukenetii (Presl) M.G. Price (1860)

E Ch Ch Ch Ch Ch PL

herb herb herb herb herb

Pteridaceae Pteris cf. pellucida Presl Pteris ensiformis Burm. f. (1806) Pteris longipinnula Wall. (334)

Ch herb Ch herb Ch herb

Schizaeaceae Lygodium auriculatum (Willd.) Alst. et Holtt. (1974) Lygodium circinnatum (Burm. f.) Sw. (1603)

st PL st PL

[236]

1297 Ptaridophyta

Life form

Selaginellaceae Selaginella cf. involvens (Sw.) Spring (856) Selaginella cf. springiana Alderw. (1526) Selaginella cupressina (Willd.) Spring (745) Selaginella engleri Hieron. (1011)

Ch Ch Ch Ch

Taenitidaceae Taenitis blechnoides (Willd.) Sw. (1091)

Ch herb

Tectaria group Ctenitis cf. silvatica Holttum (939) Cyclopeltis crenata (Fe´e) C. Chr. (1807) Pleocnemia cf. presliana Holttum (1849) Pleocnemia irregularis (Presl) Holttum (1007) Tectaria crenata Cav. (1301)

Ch Ch Ch Ch Ch

herb herb herb herb herb

Thelypteridaceae Cyclosorus sumatranus (v. Ald. v. Ros.) Ching Pneumatopteris laevis (Mett.) Holttum (1812) Pronephrium · xiphioides (Christ) Holttum (498) Pseudophegopteris paludosa (Bl.) Ching (2093) Pronephrium granulosum (Presl) Holtt. (997)

Ch Ch Ch Ch Ch

herb herb herb herb herb

frut frut frut frut

References Anonymous 1993. Flora of Taiwan Vol. 3, Angiosperms, Dicotyledons, , 2nd edn. Editorial Committee of the Flora of Taiwan, Department of Botany, National Taiwan University, Taipei, Taiwan, ROC. Anonymous 1994. Flora of Taiwan Vol. 1, Pteridophyta, Gymnospermae, 2nd edn. Editorial Committee of the Flora of Taiwan, Department of Botany, National Taiwan University, Taipei, Taiwan, ROC. Anonymous 1996. Flora of Taiwan Vol. 2, Angiospermae, 2nd edn. Editorial Committee of the Flora of Taiwan, Department of Botany, National Taiwan University, Taipei, Taiwan, ROC. Aragones E.G. Jr. 1991. Vegetation-soil pattern along altitudinal gradient in the western slopes of Mt. Banahaw, Luzon, Philippines: I. The forest communities and changes in forest composition with altitude. Sylvatrop 1(1): 15–45. Ashton P.S. 1993. Philippine phytogeography. Asia Life Sciences 2(1): 1–8. Asio V. 1996. Characteristics, weathering, formation and degradation of soils from volcanic rocks in Leyte, Philippines. Hohenheimer Bodenkundliche Hefte 33 Universita¨t Hohenheim Institut fu¨r Bodenkunde und Standortslehre, Stuttgart, 209 pp. Barrera A., Aristorenas I. and Tingzon J.A. 1954. Soil Survey of Leyte Province, Philippines. Soil Survey Report No. 18, Bureau of Printing, Manila, 103 pp. Bremer H. 1995. Boden und Relief in den Tropen: Grundvorstellungen und Datenbank. Gebru¨der Borntra¨ger, Berlin, Stuttgart, 324 pp. Bremer H. 1999. Die Tropen – Geographische Synthese einer fremden Welt im Umbruch. Gebru¨der Borntra¨ger, Berlin, Stuttgart, 428 pp. Brooks T.M., Mittermeier R.A., Mittermeier C.G., da Fonseca G.A.B., Rylands A.B., Konstant W.R., Flick P., Pilgrim J., Oldﬁeld S., Magin G. and Hilton-Taylor C. 2002. Habitat loss and extinction in the hotspots of biodiversity. Conservation Biology 16(4): 909–923. [237]

1298 Brown W.H. 1919. Vegetation of Philippine Mountains: The Relation between the Environment and Physical Types at Diﬀerent Altitudes. Bureau of Science, Manila, 434 pp. Brown W.H. and Mathews D.M. 1914. Philippine dipterocarps forests. Philippine Journal of Science A 9(5): 413–561. Buot I.E. Jr. and Okitsu S. 1997. Woody species composition in the altitudinal zones of the mossy forest of Mt. Pulog, Luzon, Philippines. Flora Malesiana Bulletin 12(1): 6–11. Burger D. 1972. Seedlings of Some Tropical Trees and Shrubs Mainly of South East Asia. Pudoc, Wageningen, 399 pp. Cain S.A., de Oliveira Castro G.M., Pires J.M. and da Silva N.T. 1956. Application of some phytosociological techniques to Brazilian rain forest. American Journal of Botany 43: 911–941. Cheek M. and Jebb M. 2001. Nepenthaceae. Flora Malesiana Vol. 15, Nationaal Herbarium Nederland, Universiteit Leiden Branch, the Netherlands, 164 pp. Corner E.J.H. 1988. Wayside Trees of Malaya. Vol. 1 and 2. Malayan Nature Society, Kuala Lumpur, 774 pp. Cromer D.A.N. and Pryor L.D. 1942. A contribution to rain-forest ecology. Proceedings of the Linnean Society 67: 249–268. Dargantes B.B. and Koch W. 1994. Case studies on the occupation and cultivation of the forest lands of Leyte, Philippines. Annals of Tropical Research 16: 13–29. Davis S.D., Heywood V.H. and Hamilton A.C. (eds) 1995. Centres of Plant Diversity – A Guide and Strategy for their Conservation, Vol. 2: Asia, Australasia and the Paciﬁc. IUCN Publications Unit, Cambridge, UK. de Guzman E.D., Umali R.M. and Sotalbo E.D. 1986. Guide to Philippine Flora and Fauna, Vol. 3: Dipterocarps, Non-Dipterocarps. Natural Resources Management Center, Ministry of Natural Resources and University of the Philippines, 414 pp. DENR 1998. Philippine atlas. Department of Environment and Natural Resources (DENR), Quezon City, Philippines. DENR and UNEP 1997. Philippine Biodiversity: An Assessment and Action Plan. Bookmark Inc., Makati City, The Philippines, 298 pp. Dransﬁeld J. 1990. Outstanding problems in Malesian palms. In: Baas P., Kalkmann K. and Geesink R. (eds), The Plant Diversity of Malesia, Proceedings of the Flora Malesiana Symposium, Leiden, the Netherlands, August 1989. Kluwer Academic Publishers, Dordrecht-BostonLondon, pp. 17–25. Duivenvoorden J.F. 1994. Vascular plant species counts in the rain forests of the middle Caqueta´ area. Colombian Amazonia. Biodiversity and Conservation 3: 685–715. Ellenberg H. and Mueller-Dombois D. 1967. A key to Raunkiaer plant life forms with revised subdivisions. Berichte des geobotanischen Instituts Ru¨bel 37: 56–73. FAO 2003. State of the World’s Forests 2003. FAO, Rome, Italy. www.fao.org/DOCREP/005/ Y7581E/Y7581E00.HTM, accessed 25 February 2004. FAO/UNESCO 1988. Soil Map of the World, Revised Legend. World Soil Resources Report 60. FAO, Rome. Gentry A.H. and Dodson C. 1987. Contribution of nontrees to species richness of a tropical rain forest. Biotropica 19(2): 149–56. Gonzales-Salcedo P.V. 2001. Floral diversity and vegetation zones of the northern slope of Province, Luzon, Philippines. Asia Life Sciences 10(2): 119–157. Gruezo W.S. 1998. Species alpha diversity of Pagbilao Grande Island vegetations, Quezon Province, Philippines. Asia Life Sciences 7(1): 39–92. Hall J.B. and Swaine M.D. 1981. Distribution and Ecology of Vascular Plants in a Tropical Rain Forest: Forest Vegetation in Ghana. Dr. W. Junk Publishers, The Hague. Hamann A., Barbon E.B., Curio E. and Madulid D.A. 1999. A botanical inventory of a submontane tropical rainforest on Negros Island, Philippines. Biodiversity and Conservation 8: 1017–1031. Heaney L. and Regalado J.C. Jr. 1998. Vanishing Treasures of the Philippine Rain Forest: A Comprehensive Introduction to the Biodiversity of the Philippines. The Field Museum University of Chicago Press, Chicago, 88 pp.

[238]

1299 Henderson M.R. 1974a. Malayan Wild Flowers: Monocotyledons, reprint of the 1954 edition. The Malayan Nature Society, Kuala Lumpur, Malaysia, 357+27 pp. Henderson M.R. 1974b. Malayan Wild Flowers: Dicotyledons, Reprint. The Malayan Nature Society, Kuala Lumpur, Malaysia, 478 pp. Ingle N. 2003. Seed dispersal by wind, birds, and bats between Philippine montane rainforest and successional vegetation. Oecologia 134: 251–261. IUCN 2000. Red List – Philippines. www.iucnredlist.org/search-basic.html. Accessed 14.01.2004. Kartawinata K. 1990. A review of natural vegetation studies in Malesia, with special reference to Indonesia. In: Baas P., Kalkmann K. and Geesink R. (eds), The Plant Diversity of Malesia, Proceedings of the Flora Malesiana Symposium, Leiden, the Netherlands, August 1989. Kluwer Academic Publishers, Dordrecht-Boston-London, pp. 120–132. Keller R. 1996. Identiﬁcation of Tropical Woody Plants in the Absence of Flowers and Fruits. Birkha¨user Verlag, Basel, Boston, Berlin, 229 pp. Keng H. 1983. Orders and Families of Malayan Seed Plants, 3rd edn. Singapore University Press, National University of Singapore, 441 pp. Keng H. 1990. The Concise Flora of Singapore: Gymnosperms and Dicotyledons. Singapore University Press, National University of Singapore, Singapore, 222 pp. Kent M. and Coker P. 1992. Vegetation Description and Analysis. Belhaven Press, London, 363 pp. Kiew R. 1987. The herbaceous ﬂora of Ulu Endau, Johore-Pahang, Malaysia, including taxonomic notes and descriptions of new species. Malayan Nature Journal 41(2 and 3): 201–234. Kintanar R.L. 1984. Climate of the Philippines. PAGASA, Quezon City, Philippines, September 1984, 38 pp. Kochummen K.M., LaFrankie J.V. and Manokaran N. 1992. Floristic composition of Pasoh Forest Reserve, a lowland rainforest in peninsular Malaysia. In: Kheong Y.S. and Win L.S. (eds), In Harmony with Nature, Proceedings of the International Conference on Conservation of Tropical Biodiversity, Kuala Lumpur, Malaysia, 12–16 June 1990. Malayan Nature Society, Kuala Lumpur, Malaysia, pp. 545–554. Lieberman D., Lieberman M., Peralta R. and Hartshorn G.S. 1996. Tropical forest structure and composition on a large-scale altitudinal gradient in Costa Rica. Journal of Ecology 84: 137–152. Magurran A.E. 1988. Ecological Diversity and Its Measurement. Chapman and Hall, London, 179 pp. Manokaran N. and Kochummen K.M. 1990. A re-examination of data on structure and ﬂoristic composition of hill and lowland dipterocarp forest in peninsular Malaysia. Malayan Nature Journal 44: 61–75. Meijer W. 1959. Plantsociological analysis of montane rainforest near Tjibodas, West Java. Acta Botanica Neerlandica 8: 277–291. Merrill E.D. 1912. A Flora of Manila. Department of the Interior, Bureau of Science, Manila, 491 pp. Myers N., Mittermeier R.A., Mittermeier C.G., da Fonseca G.A.B. and Kent J. 2000. Biodiversity hotspots for conservation priorities. Nature 403: 853–858. Newbery D.McC., Campbell E.J.F., Proctor J. and Still M.J. 1996. Primary lowland dipterocarp forest at Danum Valley, Sabah, Malaysia. Species composition and patterns in the understorey. Vegetatio 122: 193–220. Ng F.S.P. (ed.) 1978. Tree Flora of Malaya Vol. 3. Forest Department, Ministry of Agriculture and Lands, Malaysia, Longman Singapore, 339 pp. Ng F.S.P. (ed.) 1989. Tree Flora of Malaya Vol. 4. Forest Department, Ministry of Agriculture and Lands, Malaysia, Longman Malaysia, 548 pp. Ng F.S.P. 1991. Manual of Forest Fruits, Seeds and Seedlings. Vols. I and II. Malayan Forest Record No. 34. Forest Research Institute Malaysia, Kepong, 52109 Kuala Lumpur, Malaysia, 997 pp. NSCB RU-8 2001. Provincial/City statwatch: Regional Unit VIII – Eastern Visayas. National Statistical Coordination Board, www.nscb.gov.ph. Accessed 20.11.2003.

[239]

1300 Pancho J.V. 1983. Vascular Flora of Mount Makiling and Vicinity, Part 1. Kalikasan, The Philippine Journal of Biology, Supplement No. 1. New Mercury Printing Press, Quezon City, Philippines, 476 pp. Pipoly J.J.III and Madulid D.A. 1998. Composition, structure and species richness of a submontane moist forest on Mt. Kinasalapi, Mindanao, Philippines. In: Dallmeier F. and Comiskey J.A. (eds), Forest Biodiversity Research, Monitoring and Modeling: Conceptual Background and Old World Case Studies. UNESCO and The Parthenon Publishing Group Limited, Carnforth, UK, UNESCO, France, pp. 591–600. Poulsen A.D. 1996. Species richness and density of ground herbs within a plot of lowland rainforest in north-west Borneo. Journal of Tropical Ecology 12: 177–190. Poulsen A.D. and Balslev H. 1991. Abundance and cover of ground herbs in an Amazonian rain forest. Journal of Vegetation Science 2: 315–322. Proctor J., Argent G.C. and Madulid D.A. 1998. Forests of the ultramuﬁc Mt. Giting-Giting, Sibuyan Island, the Philippines. Edinburgh Journal of Botany 55(2): 295–316. Raunkiaer C. 1934. The Life-forms of Plants and Statistical Plant Geography. Oxford University Press, Oxford. Rennolls K. and Laumonier Y. 2000. Species diversity structure analysis at two sites in the tropical rain forest of Sumatra. Journal of Tropical Ecology 16: 253–270. Richards P.W. 1996. The Tropical Rain Forest: An Ecological Study. Cambridge University Press, Great Britain, 575 pp. Richter M. 1997. Allgemeine Pﬂanzengeographie. B.G. Teubner, Stuttgart, 256 pp. Santos J.V., de Guzman E.D. and Fernando E.S. 1986. Guide to Philippine Flora and Fauna. Vol. IV: Bamboos, Grasses, Palms. Natural Resources Management Center, Ministry of Natural Resources and University of the Philippines, JMC Press, Incorporated, Quezon City, Philippines, 256 pp. Schulze M.D. and Whitacre D.F. 1999. A classiﬁcation and ordination of the tree community of Tikal National Park, Peten, Guatemala. Bulletin of the Florida Museum of Natural History 41(3): 169–297. Sist P. and Saridan A. 1998. Description of the primary lowland forest of Berau. In: Bertault J.-G. and Kadir K. (eds), Silviculture research in a lowland mixed dipterocarp forest of East Kalimantan, the contribution of STREK project. CIRAD-Foreˆt Publication, pp. 51–93. Slik J.W.F., Poulsen A.D., Ashton P.S., Cannon C.H., Eichhorn K.A.O., Kartawinata K., Lanniari I., Nagamasu H., Nakagawa M., van Nieuwstadt M.G.L., Payne J., Purwaningsih, Saridan A., Sidiyasa K., Verburg R.W., Webb C.O. and Wilkie P. 2003. A ﬂoristic analysis of the lowland dipterocarp forests of Borneo. Journal of Biogeography 30: 1517–1531. Smith R.F. 1970. The vegetation structure of a Puerto Rican rain forest before and after short-term irradiation. In: Odum H. (ed.), A Tropical Rain Forest. Oak Ridge, Atomic Energy Commission, USA, pp. D103–140. Soepdadmo E. 1995. Plant diversity of the Malesian tropical rainforest and its phytogeographical and economic signiﬁcance. In: Primack R.B. and Lovejoy T.E. (eds), Ecology, Conservation, and Management of Southeast Asian Rainforests. Yale University, pp. 19–40. Soepadmo E. and Wong K.M. (eds) 1995. Tree Flora of Sabah and Sarawak. Vol. 1. Forest Research Institute Malaysia, Sabah Forestry Department, and Sarawak Forestry Department, Ampang Press Sdn. Bhd., Kuala Lumpur, Malaysia, 513 pp. Soepadmo E., Wong K.M. and Saw L.G. (eds) 1996. Tree Flora of Sabah and Sarawak. Vol. 2. Forest Research Institute Malaysia, Sabah Forestry Department, and Sarawak Forestry Department. Ampang Press Sdn. Bhd., Kuala Lumpur, Malaysia, 443 pp. Soerianegara I. and Lemmens R.H.M.J. (eds) 1994. Plant Resources of South-East Asia No. 5(1): Timber Trees: Major Commercial Timbers. Prosea Foundation, Bogor, Indonesia and PudocDLO, Wageningen, the Netherlands, 610 pp. Takeuchi M. 1960. A estrutura da vegetac¸ao na Amazonia III: A mata da campina na regiaˆo do Rio Negro. Boletim do Museo Paraense Emilio Goeldi 8: 1–13. Tan B.C. and Rojo J.P. 1989. The Philippines. In: Campbell D.G. and Hammond H.D. (eds), Floristic Inventory of Tropical Countries – The Status of Plant Systematics, Collections, and

[240]

1301 Vegetation, Plus Recommendations for the Future. New York Botanical Garden, New York, pp. 44–62. Turner I.M. 1994. The taxonomy and ecology of the vascular plant ﬂora of Singapore: a statistical analysis. Bot. J. Linn. Soc. 114: 215–227. Valencia R., Balslev H. and Paz Y. Min˜o C.G. 1994. High tree alpha-diversity in Amazonian Ecuador. Biodiversity and Conservation 3: 21–28. van Balgooy M.M.J. 1997a. Malesian Seed Plants. Vol. 1: Spot-characters. Rijksherbarium /Hortus Botanicus, Leiden, 154 pp. van Balgooy M.M.J. 1997b. Malesian Seed Plants. Vol. 2: Portraits of Tree Families. Rijksherbarium /Hortus Botanicus, Leiden, 307 pp. van Steenis C.G.G.J. (ed.) 1950-ongoing. Flora Malesiana. Martinus Nijhoﬀ Publishers, Dordrecht, the Netherlands. Walsh R.P.D. 1996. Climate. In: Richards P.W. (ed.), The Tropical Rainforest. Cambridge University Press, pp.159–205. Whitford H.N. 1906. Vegetation of the Lamao Forest Reserve. Philippine Journal of Science I: 373–431 and 637–682. Whitford H.N. 1911. The Forests of the Philippines. Part I: Forest Types and Products. Department of the Interior Bureau of Forestry, Bulletin No. 10, Manila, 94 pp. Whitmore T.C. (ed.) 1983a. Tree Flora of Malaya. Vol. 1. Corrected Reprint of the 1972 Edition. Forest Department, Ministry of Agriculture and lands, Malaysia Longman Malaysia, 473 pp. Whitmore T.C. (ed.) 1983b. Tree Flora of Malaya. Vol. 2. Corrected Reprint of the 1972 Edition. Forest Department, Ministry of Primary Industries, Malaysia, Longman Malaysia, 442 pp. Whitmore T.C. 1985. Tropical Rain Forests of the Far East. Corrected Reprint of the 1984 Edition. Clarendon Press, Oxford, 352 pp. Whitmore T.C., Peralta R. and Brown K. 1985. Total species count in a Costa Rican tropical rain forest. Journal of Tropical Ecology 1: 375–378. Wilkie P., Argent G., Cambell E. and Saridan A. 2004. The diversity of 15 ha of lowland mixed dipterocarp forest, Central Kalimantan. Biodiversity and Conservation 13(4): 695–708. Zamora P.M. and Co L. 1986. Guide to Philippine Flora and Fauna. Vol. II: Economic Ferns, Endemic Ferns, Gymnosperms. Natural Resources Management, Center Ministry of Natural Resources, and University of the Philippines, JMC Press, Incorporated, Quezon City, Philippines, 273 pp. Zikeli S. 1998. Nutrient status and nutrient cycles of the tropical rainforest, Mt. Pangasugan, Leyte, Philippines. Diploma thesis, Martin - Luther - University Halle - Wittenberg, Landwirtschaftliche Fakultaet, Institut fu¨r Bodenkunde und Pﬂanzenernaehrung, 100 pp.

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Biodiversity and Conservation (2006) 15:1303–1318 DOI 10.1007/s10531-005-3873-7

Springer 2006

-1

Status and conservation of Trigonobalanus doichangensis (Fagaceae)# WEIBANG SUN1,2,*,YUAN ZHOU1, CHUNYUAN HAN1, CHUNXIA ZENG3, XIAODONG SHI3, QIBAI XIANG2 and ALLEN COOMBES4 1

Kunming Institute of Botany, the Chinese Academy of Sciences, Kunming 650204, the People’s Republic of China (post address); 2Nanjing Forestry University, Nanjing 210037, the People’s Republic of China; 3Qujian Normal University, Yunnan, the People’s Republic of China; 4Sir Harold Hillier Gardens, Jermyns Lane, Ampﬁeld, Romsey, Hampshire SO51 0QA, UK; *Author for correspondence (e-mail: [email protected]; phone: +86-871-5223622; fax: +86-871-5216350) Received 20 January 2004; accepted in revised form 8 March 2005

Key words: Conservation, Endangered, Genetic diversity, Habitat degradation, Reproductive barriers, Trigonobalanus doichangensis (A.Camus) Forman Abstract. Trigonobalanus doichangensis is a national rare and endangered plant of China. It is restricted to 4 sites in southwest Yunnan, China and 1 site in Chiang-Rai, northern Thailand. Investigations revealed that 4 community types are currently extant in Yunnan: isolated individuals, sprouting woods, mono-dominant forest and co-dominant forest. The habitats have been severely damaged and the populations there are facing a high risk of extinction. The adult phase of T. doichangensis is reached when a tree attains a height of about 4 m. The ﬂowering and fruiting time varies slightly among populations and/or across the micro-habitats. In comparison with other fagaceous plants in the community, T. doichangensis has an inverse ﬂowering and fruiting period from October through to May. Although microspore genesis and the development of male gametes are normal, the pollen does not germinate until at least 8 h culture. The highest germination rate was 37.8%. In addition, only 9.8% of the nuts contain well-developed seeds. Genetic variation analyzed with random ampliﬁed polymorphic DNA indicated that its total genetic diversity was 0.1600 and genetic diversity within populations was 0.0749, the coeﬃcient of gene diﬀerentiation was 0.5320. Therefore, T. doichangensis has high genetic diﬀerentiation, a low level of genetic diversity and a poor gene ﬂow compared to the other fagaceous species. It seems that habitat degradation, over exploitation and reproductive barriers, are most likely to be the factors threatening the species. However, it may be a combination of geographical catastrophic events, habitat deterioration, declining genetic diversity and physiological stress. Therefore, a practical conservation strategy for T. doichangensis is urgently needed.

Introduction The fagaceous genus Trigonobalanus Forman shows many ancestral features of the family (Forman 1964; Crepet and Nixon 1989; Nixon and Crepet 1989) and was probably widely distributed (perhaps over the whole northern hemisphere) #

Supported by the important directional item of the Chinese Academy of Sciences (KSCX2-SW104) [243]

1304 during the tertiary period or even before (Zhou 1992). The genus has only three extant species and Trigonobalanus doichangensis is the only one distributed in China (Hsu et al. 1981). T. doichangensis is most closely related to the genus Quercus L. (Zhou 1992) and has a high scientiﬁc value for studies on Fagaceae phylogeny, continental drift theory and global environmental changes. Due to heavy exploitation for fuel wood, vegetation destruction in China and its restricted distribution, T. doichangensis is seriously threatened and is being pushed to the verge of extinction (Fu 1992). Hence, it was listed as a national rare and endangered plant in 1984 and has also been proposed as a second-ranked plant for national protection in China (Anon 1999). So far, its phylogeny (Wang and Zhang 1988; Nixon and Crepet 1989; Wu and Xiao 1989; Liao et al. 1998; Wang et al. 1998) and the community ﬂoristic elements (Li 1994) have been comprehensively studied. However, there are only a few recent reports on its conservation biology (Zhou et al. 2003; Zhou, 2003; Sun et al. 2004). It is well known that a practical conservation strategy for an endangered plant is based on an understanding of the threats it faces. In this study we describe the status of the current distribution, population ecology, reproductive biology and genetic variation of T. doichangensis. Our goal was to provide comprehensive information relevant to the conservation and restoration of this species.

Methods Trigonobalanus doichangensis is restricted to Thailand and south Yunnan in southwest China (Fu 1992). In this study all localities from recorded herbarium specimens, both from Thailand and China were used to determine its current distribution (including collection of vouchers and research materials). Based on this, the 4 known localities of T. doichangensis in Yunnan, China, Menglian, Lancang, Ximeng and Cangyuan, were regarded as 4 populations on which to carry out the comprehensive study. These 4 populations are situated in areas bordered by southeast Myanmar, within the southern part of the Tropic of Cancer. The climate belongs to the south subtropics type (EBYV 1987) and the soil is mainly red acid (Xiong 1987). Dai, Wa and Laku are the three indigenous ethnic groups in the region.

Threat category and the characteristics of population ecology Data analysis from the general surveys and ecological plotting studies, determined the threat category by assessment of current distribution and population size following to the IUCN Red List Categories and Criteria (IUCN 2001). Investigations were performed in the ﬂowering and fruiting season. Plot sizes of 10 · 20 m, 20 · 20 m, 30 · 30 m and 50 · 60 m were applied in accordance with [244]

1305 the population size. The characteristics recorded were: (1) Site conditions, (2) Plant height and crown size (m·m), trunk base diameter and diameter at breast height of all T. doichangensis in the plot, (3) Habitat quality, (4) The main accompanying higher plants and their abundance, and (5) Regeneration capacity of T. doichangensis from seeds.

Analysis of genetic diversity The random ampliﬁed polymorphic DNA (RAPD) technique was applied in this study. Each locality was taken as a population, which, including that in Thailand, made a total of 5 populations. Young but fully expanded leaves of 19 or 20 individuals within each population were selected and harvested, dried quickly with silica gel and stored in a refrigerator at 4 C. DNA extraction Total DNA was extracted from dried leaves using a modiﬁed CTAB method (Doyle and Doyle 1987). Modiﬁcations included incubation in CTAB at 65 C for 1.5 h; a second extraction in chloroform–isoamyl alcohol; repeated washings in 70% ethanol without ammonium acetate; a ﬁnal washing in 100% ethanol and the addition of RNase to the TE buﬀer. DNA was visualized on 1.0% agarose gels. RAPD PCR ampliﬁcation A mixed DNA from 5 randomly selected individuals was used to screen 137 primers (Operon Technologies, Alameda, CA, USA). The primers that generated clear bands with high polymorphism were determined for PCR ampliﬁcation on a T3 thermocycler (Biomotra, Goettingen, Germany) using a ﬁnal volume of 20 ll. The reaction mix consisted of 2 ng of template DNA, 2.0 mmol/L MgCl2, 0.5 lmol/l dNTP, 10·buﬀer, 2.5 lmol/L of primer and 2 units of Taq DNA polymerase. The reaction included 4 min of initial denaturation at 94 C, followed by 45 cycles of 15 s of denaturation at 94 C, 45 s of annealing at 36 C, 90 s of extension at 72 C, and a ﬁnal extension step of 4 min at 72 C. Subsequently 10 ll ampliﬁcation products were visualized on 1.5% agarose gels after electrophoresis in TAE at pH 8.0 for 3 h. The gels were photographed with a GekDoc2000 (BIORAD) image analyzer (BIORAD, Hercules, CA, USA). Data analysis The individuals were scored for the presence (1) or absence (0) of ampliﬁed bands. The data matrix of RAPD bands was statistically analyzed using POPGENE (Yeh et al. 1997). The parameters of the genetic diversity and genetic structure are the percentage of polymorphic loci P(%), Shannon’s index of diversity (I), Nei’s gene diversity (h), the coeﬃcient of gene diﬀerentiation (Gst) and an estimate of gene ﬂow (Nm). [245]

1306 Reproduction biology Flowering and fruiting time of the 4 T. doichangensis populations in China were observed and compared. The ﬂoral organs at diﬀerent developmental phases were ﬁxed with FAA (50% ethanol/acetic acid/formaldehyde = 90/6/4 by volume) and preserved. The conventional paraﬃn slice thickness was 5–7 lm. These were stained with iron alum–haematoxylin, dyed with chrysoidine G, then observed and photographed using an Olympus BX-51 optical microscope. Various levels of agar, sucrose, calcium nitrate and boric acid were selected and combined for pollen germination tests. Fresh pollen collected from each population was germinated at 25±1 C under darkness. The germination process was observed every 2 h and the ﬁnal germination rate (%) was measured at hour 24. Seeds (nuts) were harvested between April and June from each population and stored in a refrigerator at 4 C. Seed structure and embryo development were observed and recorded under the ZS-PT Olympus anatomical lens. Seed germination was tested in the LRH-250-GS climatic box made in China. A conventional seed sowing was also conducted under Kunming climatic conditions in Spring.

Results Current distribution and threat status When it was originally described, T. doichangensis was only known from northern Thailand (Forman 1964). Later it was also found to occur in China (Hsu et al. 1981). Since it was recorded in China some ﬁeld surveys and specimen identiﬁcations showed that it occurs in Menglian, Lancang, Ximeng and Mengla,Yunnan, China (Fu 1992). Recent investigations revealed that T. doichangensis still exists in fragmented populations of various sizes in Menglian (Vouchers: SWB 02T001 020), Lancang (Vouchers: SWB02T021 040), Ximeng (Vouchers: SWB02T041 060) and Chiang-Rai Province in northern Thailand (Vouchers: SWB02T081 100). In addition, the new localities in Cangyuan (Vouchers: SWB02T061 080) were recorded, and it was shown that the species does not occur in the previously recorded locality in Mengla. Therefore, it can be concluded that the natural distribution of T. doichangensis is in the south and southwest Yunnan, China and in northern Thailand, and currently only 5 populations are extant. Trigonobalanus doichangensis has been listed as one of the national secondranked protected plants in the No.4 Order of the Forest and Agricultural Ministry of China (Anon 1999) because of its threatened status in the wild. It has also been recognized as a seriously threatened species because of the amount of vegetation destruction and cutting for fuel-wood (Fu 1992). A case study from the township market in Lancang, showed that the annual trading of [246]

1307 fuel-wood of T. doichangensis was about 1000–1400 m3 . Also a natural stand close to the township is still cut continuously (Sun et al. 2004). At present the indigenous ethnic people of Dai, Wa and Laku are still causing great destruction to the habitats and using the wood resources, and as a result the populations are fragile and fragmented. T. doichangensis in China is facing a high risk of extinction. Attributes of the communities The populations in Yunnan, China showed diﬀerent characteristics in their tree-age structure and ﬂoristic composition (Table 1). Four community types were recognized during the recent investigations. (1) Type IsI (Isolated individuals): Individuals of T. doichangensis were often found in secondary woods, by roadsides, in mixed woods or farmland, and occasionally within the evergreen broadleaf forests. The forests surrounding Table 1. Population characteristics of Trigonobalanus doichangensis in diﬀerent communities. Communities

SW

MDF

CDF

Localities

Menglian

Lancang

Cangyuan BTS

Plots Altitude (m) Slope Coverage (%) Size (m2) TD no. in the plot TD no. per 100 m2 TD Avg. height (m) Hst/Shst of TD (m) % of TD ‡20 m % of TD ‡4–20 m % of TD 2–3 m % of TD £ 1.0 m % of dead TD Avg. height of DP (m) Accompanier no. Main companions (TP) Evaluation

1020 N, 30 degrees >90 800 195 24 5.1 13.5/0.2 / 59 15 26 / / 45

1450 W, 40 degrees >90 400 140 35 5.6 9.5/0.3 / 73 21 6 / / 30

RBS

1550 1590 SE, 40 degrees S, 30 degrees >95 >95 3000 600 41 101 2 17 17.9 6.8 35/0.4 32/0.28 51 6 44 55 / 23 5 16 / 17 / 1.5 10 25 27

MDS

1730 S, 30 degrees >95 400 118 30 14.4 20/0.2 0.8 92 5 3 15 3.5 18 25

1

2

3

2

3

4

5

4

5

4

5

HAD

PR

RSS

USD

MDSD

Notes: SW = Sprouting wood; MDF = Mono-dominant forest; CDF = Co-dominant forest; HTS = Huge-tree structure; RBS = Relatively balance structure; MDS = Mono-dominant structure; No. = numbers; TD = Trigonobalanus doichangensis; Hst = Highest; Shst = Shortest; Avg. = Average; DP = dead plants; TP = top layer;

1 = Vaccinium bracteatum;

2 = Castanopsis echinocarpa;

3 = Castanopsis hytrix;

4 = Castanopsis calathiformis;

5 = Schima wallichii; HAD = heavily disturbed by human activities; PR = Population in recovery; RSS = relatively stable structure; USD = unstable structure in developing; MDSD = mono-dominant structure in developing. [247]

1308 these individuals were mostly replaced by other native plant species, alien plant invaders, such as Eupatorium adenophorum (Ageratina adenophora) and Eupatorium odoratum (Chromolaena odorata), and agricultural crops. Occasionally, some seedlings or young trees appeared around scattered individuals inside the evergreen broadleaf forests. However, other plants such as Castanopsis calathiformis, Castanopsis echinocarpa, Lithocarpus fenestratus, Schima wallichii and Anneslea fragrans had already dominated in the vegetation. The formation of Type IsI is due to heavy cutting and vegetation destruction. The isolated individuals are found in the most endangered habitat and their genetic diversity is easily reduced by further human activities, grazing animals, farming and further biotic invasion. (2) Type SW (Sprouting woods): Type SW is the result of fuel wood cutting by indigenous people. Investigations show that the indigenous ethnic groups of Dai, Wa and Laku are familiar with T. doichangensis and have realized that the tree can sprout easily after top-cutting and thinning and thus they have adopted the methods of ‘alternate cutting or thinning cutting’ for the primitive sustainable use of the tree as fuel wood. As a result of these practices, plants of T. doichangensis in these woods showed some unique characteristics in tree shape, tree height structure and associated ﬂoristic composition (Table 1). In this community the tallest T. doichangensis was about 13 m and the average height was around 5 m. Some 60% of T. doichangensis reached the reproductive phase and about 25.6% of the individuals were below 1 m in height. T. doichangensis was the dominant species in woods, and 50 species of accompanying higher plants were present. The most important trees were Vaccinum bracteatum, Castanopsis hystrix, Lithocarpus fenestratus, Craibiodendron stellatum, Anneslea fragrans, Ternstroemia gymnanthera and Schima wallichii. Vernonia parishii, Arthraxon lanceolatus, Carex baccans and Zingiber striolatum were the typical herbaceous plants. Among epiphytes, Phymatodes lucida, Vanda coerulea and Eria pannea were also commonly found on the trunk. As ontogenesis of T. doichangensis was prevented by cutting, most trees could not complete their natural growth and their reproductive capacity was relatively restrained. (3) Type MDF (Mono-dominant forest): Plants of T. doichangensis in type MDF are found as small mono-dominated patches scattered in the secondary evergreen broadleaf forest. The tallest plant of T. doichangensis was about 10 m and the average height was around 5–6 m. Approximately 70% of the trees in the plots were mature with a height of ‡4 m. Around 20% of the plants were 2–3 m in height, while seedlings and young trees represented only 6% of the total population. Accompanying higher plants were represented by some 30 species and most of the woody species were the same as in Type SW, but there were far fewer herbaceous plants and epiphytes. Osyris wightiana, Viburnum cylindricum, Broussonetia papyrifera and Phyllanthus emblica were present in the community. T. doichangensis in Type MDF showed vigorous growth and a strong regenerative ability. (4) Type CDF (Co-dominant forest): Plants of T. doichangensis in Type CDF often formed a mosaic of mono-dominant patches in the primitive evergreen [248]

1309 broadleaf forest. In this type of community, T. doichangensis grows naturally without destructive disturbance from human activities. Based on the tree height-grade Type CDF can be divided into 3 ranks. These are Big Tree Structure (BTS), Relatively balanced structure (RBS) and Mono-dominant structure of mature trees (MDS) (Table 1). In rank BTS over 50% of T. doichangensis were trees with a height of ‡20 m and approximately 90% of the plants were in the reproductive phase. Compared with the other 2 ranks BTS had a lower percentage of young trees and seedlings. In rank RBS only 6% of T. doichangensis were trees with a height of ‡20 m, while some 17% of the total were dead, and almost 60% of the plants were in the ﬂowering and fruiting stage. Rank RBS had almost equal number of ﬂowering and non-ﬂowering individuals of T. doichangensis. Compared with the ranks of BTS and RBS, rank MDS had the highest number of ﬂowering individuals and nearly 90% of them were in the reproductive phase. The percentages of trees over 20 m tall or less than 1 m in the MDS were the lowest, and around 15% of all trees with a height of 3–18 m were dead. Both ranks of RBS and MDS had more individuals per 100 m2, however, both of them also had a certain percentage of plants that had died naturally. It can be inferred that T. doichangensis in the codominant forest is dynamic, and both types of RBS and MDS would develop into BTS with some individuals dying gradually because of strong competition for resources. The interrelationship of MDS M RBS M MDS may be the main characteristic for T. doichangensis in the primitive evergreen broadleaf forest. About 25 species of accompanying higher plant were found in CDF. Of these, Castanopsis calathiformis, Lithocarpus echinotholus and Lithocarpus fenestratus, were the most common in the upper canopy and Castanopsis calathiformis was the most competitive species with T. doichangensis. Other woody plants, such as Olea rosea, Eriobotrya cavaleriei, Cinnamomum bejolghota, Phoebe macrophylla, Helicia nilagirica, Ternstroemia gymnanthera, Pyrenaria diospyricarpa, Pithecellobium clypearia, and Eurya groﬃi, were also commonly found.

Genetic diversity and population genetic structure One hundred and ﬁfty seven bands from 100 to 2900 bp were generated by the 16 selected primers, with each primer producing 6–13 bands with an average of 9.81 bands. Eighty three of the total bands were polymorphic and accounted for 52.87% (Table 2). These ﬁndings show that genetic diversity at the species level was abundant. Table 2 also indicates that the percentages of polymorphic bands in both populations of Lancang and Chiang-Rrai were far lower than those in the 3 other populations of Cangyuan, Menglian and Ximeng. Therefore, the genetic variation within both populations of Lancang and Chiangrai was lower that that in others. Table 3 shows that the eﬀective number of alleles (ne), Shannon’ s index of diversity (I) and Nei’ s gene diversity (h) were 1.2646, 0.2431 and 0.1595, [249]

1310 Table 2. The sequences of random oligonucleotide primers and the number of polymorphic bands. Primers

Sequences

Total bands

Polymorphic bands

OPC05 OPC14 OPC15 OPJ 09 OPM02 OPM06 OPM13 OPM15 OPM16 OPM20 OPN14 OPN20 OPS03 OPV06 OPV10 OPV15

TCGTCTGCCC TGCGTGCTTG GACGGATCAG TGAGCCTCAC ACAACGCCTC CTGGGCAACT GGTGGTCAAG GACCTACCAC GTAACCAGCC AGGTCTTGGG TCGTGCGGGT GGTGCTCCGT CAGAGGTCCC ACGCCCAGGT GGACCTGCTG CAGTGCCGGT

9 10 11 11 6 8 10 12 13 10 12 7 11 10 9 8

4 5 6 6 0 5 4 5 7 4 9 3 6 9 4 6

Table 3. The genetic diversity and genetic structure of T. doichangensis. Population

na

ne

H

I

P/%

Ht

Hs

Gst

Nm

LC CHR CY ML XM Mean

1.1019 1.1911 1.3185 1.2930 1.3312 1.5287

1.0538 1.0804 1.1675 1.1469 1.1696 1.2646

0.0311 0.0513 0.0985 0.0911 0.1024 0.1595

0.0472 0.0812 0.1502 0.1403 0.1568 0.2431

10.19 19.11 31.85 29.30 33.12 52.87

0.1600

0.0749

0.5320

0.4398

Notes: na, observed number of alleles; ne, eﬀective number of alleles Kimura and Crow (1964); h, Nei’s (1973) gene diversity; I, Shannon’s Information index; P, the percentage of polymorphic loci; Ht, gene diversity of species; Hs, gene diversity within populations; Nm, gene ﬂow; Gst, coeﬃcient of gene diﬀerentiation.

respectively, and the genetic variation of T. doichangensis is rather low (the eﬀective number of alleles<1.5000). As the species gene diversity (Ht) was 0.1600 and the gene diversity within populations (Hs) was 0.0749, the genetic variation within populations was lower than that between populations. Table 3 also indicates that T. doichangensis shows a very strong genetic diﬀerentiation between its populations because the coeﬃcient of gene diﬀerentiation (Gst) reached 0.5320, more than 10 times that of other fagaceous plants (0.020– 0.065) (Chen et al. 1997). The analysis also indicated that T. doichangensis had a lower gene ﬂow (Nm = 0.4398) (Table 3) compared with other fagaceous plants, such as Castanopsis fargesii (Nm = 11.2645) (Zhu et al. 2002), Cyclobalanopsis glauca (Nm = 20.49) (Zhu et al. 2002) and Quercus aquifolioides (Nm = 2.66) (Li et al. 1997). Thus, there is less gene movement between T. doichangensis populations compared to other plants in Fagaceae. [250]

1311 Microspore genesis and development of male gametes Some 400 ﬂoral organs of T. doichangensis were sampled at diﬀerent development stages from the 4 populations. The anther is 4-sporangiate and the anther wall formation conforms to the dicotyledonous type. The tapetum is of the glandular type and most cells are 2-nucleate. Cytokinesis at meiosis of microspore mother cells is simultaneous and tetrads are tetrahedral, occasionally decussate. Mature pollen grains are 2-celled. These characteristics are consistent with the result of Stairs’s results on Quercus (Johri et al. 1992). The meiosis process of microspore mother cell in T. doichangensis is the same as the common angiosperms (Hu 1982). These observations also showed that diﬀerent anthers or diﬀerent anther sacs of the same anther in the meiosis phase of the microspore-mother-cell showed asynchronism in T. doichangensis. Various authors (Whelan 1974; Li and Cao 1986; Huang et al. 2001) have given diﬀerent opinions of this asynchronism. However, it seems certain that the asynchronism of the meiosis phase in the microspore-mother-cell is a universal phenomenon in angiosperms, and it does not relate to the normal development of anthers and the formation of fertile pollen. Therefore, the observations did not ﬁnd any abortion or other abnormal phenomena in anther wall development, microspore genesis and male gamete formation in T. doichangensis. Pollen germination in vitro and its abortion Pollen germination started after 8 h of culture, and was completed at 24 h. Diﬀerent combinations of agar, sucrose, boric acid and calcium nitrate could aﬀect pollen germination, but the highest germination rate was only 37.8% (Table 4) and more than 63% of the pollen of T. doichangensis was aborted. Pollen germination has rarely been reported in Fagaceae, but some major chestnut cultivars were tested (Xia et al. 1989). The pollen germination rate of Castanea mollissima was lower (31%) than that of its cultivars (60–78%), and the lower pollen germination of C. mollissima was one of the causes of its poor fruiting (Xia et al. 1989). The cause of pollen abortion in T. doichangensis may be complicated, and yet its lower pollen germination rate and the delayed germination (8 h after culture) may contribute to the lower fruiting percentage (9.8%) (Sun et al. 2004). Ovule abortion and embryo development In T. doichangensis the ovary has 3 locules with 2 ovules per locule. Observation on the ovary in transverse section showed that 6 ovules in each ovary were generated at an early stage, and at the developmental anaphase 1 of 2 ovules per chamber were well developed, while another one was aborted. Meanwhile, both axile and parietal placentas were observed, and thus [251]

1312 Table 4. Pollen germination of T. doichangensis on diﬀerent media. Medium code

Germination rate (%)

1

1.9 8.1 18.3 22.9 22.1 22.4 22.2 20.2 20.9 21.8 37.8 37.2 22.7 21.4 18.3

2

3

4

5

6

7

8

9

10

11

12

13

14

15

1 agar 7;

2 agar 7 + sucrose 100;

3 agar 7 + sucrose 150;

4 agar 7 + sucrose 200; Notes:

5 agar 7 + sucrose 250;

6 agar 7 + sucrose 200 + boric acid 100;

7 agar 7 + sucrose 200 + boric acid 150;

8 agar 7 + sucrose 200 + boric acid 200;

9 agar 7 + sucrose 200 + boric acid 300;

10 agar 7 + sucrose 200 + boric acid 400;

11 agar + sucrose 200 + calcium 12 agar 7 + sucrose 200 + calcium nitrate 200;

13 agar 7 + sucrose 200 + nitrate 100;

calcium nitrate 300;

14 agar 7 + sucrose 200 + calcium nitrate 400;

15 agar 7 + sucrose 200 + calcium nitrate 500 (All units are g/L).

T. doichangensis may show a transition trend from axile to parietal placentation. The ovule is anatropous and is enclosed by outer and inner integuments. The following 3 phenomena were also observed in the young fruits: (1) Only 1 of the 6 ovules per ovary developed into an embryo and the others were aborted. The percentage of the one-ovule developed nuts was less than 10%; (2) In some fruits all the 6 ovules in the ovary were aborted and the ovary was ligniﬁed; (3) The ovules in some fruits seem to be developed but the embryos were membranous. It can be concluded that considerable embryo abortion occurs in T. doichangensis. Flowering and fruiting Investigations in the wild indicated that T. doichangensis becomes of reproductive age once its height reaches 4 m. The ﬂowers are unisexual and plants are monoecious. Staminate ﬂowers are often clustered on the rachis forming axillary catkins or occur terminally on leaﬂess branchlets. Pistillate inﬂorescences are unbranched in the axils of the upper (younger) leaves and bear 1–3 ﬂowers on distal parts of rachis. The pollination mechanism in Fagaceae is complex. Flower characters in Quercus Subgen. Cyclobalanopsis show a transition from entomophily to anemophily (Kaul and Abbe 1989; Zhou 1992), and the upright or curved staminate inﬂorescence in genus Trigonobalanus may also represent such a [252]

1313 transition (Hsu et al. 1981). The staminate inﬂorescences of T. verticillata are erect and often branched, and are reminiscent of inﬂorescences found in subfamily Castaneoideae. And this, along with reports of odor in ﬂowers (Soepadmo 1972) suggests the possibility that T. verticillata is an entomophilous species, as are the species of Castaneoideae such as Lithocarpus densiﬂorus, Castanea sativa, C. mollissima etc (Nixon and Crepet 1989). T. doichangensis and T. excelsa have lax staminate inﬂorescences like those of Quercus, which is generally accepted as anemophilous (Nixon and Crepet 1989). However, our observation on fresh male ﬂowers of T. doichangensis under the stereo-anatomical lens, found that tiny beetles frequently visited the anthers to collect pollen. Therefore, we infer that these tiny beetles may also participate in the pollination of T. doichangensis. The ﬂowering time of T. doichangensis varies slightly between diﬀerent populations and micro-habitats. However, the period of ﬂowering and fruiting is generally from October to the following May, a period in which the weather is cool and wet (YWB 1983). This phenology is unique compared to most other plants in the community, which ﬂower in Spring and fruit in Autumn; a factor that may also contribute to its low fruiting percentage. Seeds and seed germination The nut of T. doichangensis is normally called a seed and has a kilo-grain weight of 12.7 g. In fact, the seed is exoendosperm enclosed by a semi-transparent episperm and endocarp. T. doichangensis fruits well, but only 9–11% of the nuts contain well-developed seeds (with fertile embryos). Nuts containing well-developed seeds germinated 4 d after culturing at various temperatures under darkness, and after 11 d all germination was completed. Lighting slightly stimulated the germination and the highest germination rate was around 63–73%. Epigeal germination has been reported in T. doichangensis (Nixon and Crepet 1989; Liao et al. 1998) and this was conﬁrmed by sowing nuts in Spring at Kunming,Yunnan, China. Observations indicated that hypocotyls grew rapidly at 8 d and at 11 d, 2 or occasionally 3 cotyledons emerged from the compost. Germination in compost lasted around 20 d and the germination rate was close to that found in tests in the LRH-250GS climatic box. Transplanted young plants have been growing well at Kunming (where the recorded minimum absolute temperature is 5.4 C) for 3 years. And thus, T. doichangensis may have a broad climatic adaptability. Discussion Global threat category of T. doichangensis Trigonobalanus doichangensis in China has been considered as an endangered plant for more than 10 years (Fu 1992). However, it was ranked as DD (Data [253]

1314 Deﬁcient) in The World List of Threatened Trees (Oldﬁeld et al. 1998) and its threat category has not yet been evaluated by using any version of IUCN Red List Categories and Criteria. Based on our observations and data analyses, the threat category of T. doichangensis in China is proposed as EN (Endangered) [EN, B1a, B1b(i,ii,iii)] (IUCN 2001). It is therefore considered to be facing a very high risk of extinction in the wild, because: (1) Its extent of occurrence is estimated to be less than 5000 km2, (2) Its populations are severely fragmented and (3) There is a continuing decline in the extent of occurrence, area of occupancy and quality of habitat. Judging by the limited distribution of the species in northern Thailand, and its only postulated occurrence in Myanmar, it is likely that EN will also be the Global threat category.

Identifying threats Rarity and endangerment of a plant species may be due to intrinsic (related to the biology of the species) or extrinsic (environmental) factors (Rabinowitz 1981; Fiedler and Ahouse 1992) and anthropogenic habitat fragmentation has been widely cited as a major threat to biodiversity (Simberloﬀ 1988). Destruction and disappearance of habitat are the major extrinsic factors threatening biodiversity (Pang et al. 2003; Jiang et al. 1997). Some remnant plant species, such as Metasequoia glyptostroboides, Cathaya argyrophylla and Liriodendron chinense, may maintain a present population in the ‘endangered habitats’ because large parts of their populations have disappeared due to historical events such as climate change (He et al. 1996). As a remnant species T. doichangensis may also be in an ‘endangered habitat’. Its present habitat destruction and disappearance, caused by expansion of agricultural land and over cutting, are threatening its survival. Therefore, a very low gene ﬂow among populations in T. doichangensis may certainly be due to its habitat degeneration and population isolation. Reproductive barriers are among the main factors to threaten a plant species (Pan et al. 2003). T. doichangensis does not show any abnormal phenomena in anther wall development, microspore genesis and male gamete formation. It did, however, show serious ovule development abortion, the causes of which need to be studied. The low pollen germination, as well as the length of time for pollen to germinate and the inverse ﬂowering and fruiting behaviour compared to other fagaceous plants in the population, show that T. doichangensis exhibits a reproductive barrier in seed development. In addition, its seed (nut) germination and seedling establishment need a moist environment and the establishment of young trees from seedlings needs comparatively sunny conditions (Sun et al. 2004). Evidently, the environment in the severely fragmented habitat is not ideal for seed germination and plant development into the reproductive phase. Some rare species that existed in glacial refuges, have long survived in certain restricted habitats even though their populations are isolated and the habitats [254]

1315 are already fragmented (Li et al. 2003). However, long-term species survival depends on the maintenance of suﬃcient genetic variability within and among populations to accommodate new selection pressures brought about by environmental changes (Elena et al. 2003), and populations with low genetic variation have a high risk of extinction (Li et al. 2003; Ledig et al. 2002).The decline of seed viability of Metasequoia glyptostroboides, is caused by its poor genetic base and inbreeding, and its eﬀective seed germination relies on suitable conditions (Liao and Zhou 1989). Accordingly, lower levels of genetic diversity and intense genetic diﬀerentiation in T. doichangensis will not be able to respond as well to changes in abiotic or biotic environmental conditions as can other fagaceous species. The low seed germination and plant establishment may also partly contribute to its present genetic status caused by habitat fragmentation and population isolation. We may conclude that endangerment of T. doichangensis is not caused by a single factor. It seems that habitat destruction, over-exploitation and reproduction barriers, are the most likely factors. However, it may be a combination of historic factors such as climate changes, habitat degeneration, a poor genetic base and physiological stress. Therefore, a practical conservation strategy for T. doichangensis is urgently needed.

Conservation considerations Protection and restoration of natural habitats is the best and cheapest method of preserving the biological diversity and stability of global ecosystem (Lande 1988). Undoubtedly, the long-term survival of T. doichangensis is dependent on habitat conservation. However, only 1 of the 4 extant populations of T. doichangensis in China has been legally preserved by government ownership and others are facing a high risk of habitat disappearance. Perhaps more than most endangered plant species in China, the unique characteristics of T. doichangensis, population isolation and the complex community interaction, exemplify the importance of habitat preservation and in-situ conservation. Nevertheless, both in-situ and ex-situ measures are needed for preserving T. doichangensis and its genetic diversity, and following aspects should be particularly considered: (1) Preservation of the habitat and population of T. doichangensis in Canyuan must be reinforced. The Canyuan population is the only 1 of the 4 populations in China which has been well protected inside a national natural reserve. Therefore, the population is a vital resource for further research into the origin and evolution, eco-biological characteristics and genetic realities of T. doichangensis. Furthermore, the population also has a great value in population restoration research. (2) As T. doichangensis populations in Menglian, Lancang and Ximeng are still exposed to high habitat destruction and cutting for fuel wood, it is essential that new in-situ conservation sites in these area should be urgently planned. [255]

1316 These new sites will play an important role in habitat recovery and population restoration. (3) Although cross-planting is often controversial in plant conservation planning, it is proposed that seedling cross-planting between diﬀerent populations of T. doichangensis should be considered. At least, the potential impacts of this measure should be studied to determine if low gene ﬂow would be enhanced and if overall diversity would be increased. (4) As young T. doichangensis plants propagated from seeds can tolerate temperatures below 2 C at Kunming (Sun et al. 2004), it may be cultivated for fuel wood and as a landscaping plant in northern parts of the Tropic of Cancer. However, the mixed planting of trees propagated from various populations is essential. (5) Ex-situ eﬀorts need to be undertaken to preserve genetic diversity and multiply specimens. This applies in particular to those populations outside of the well-protected national nature reserve. Ideally, ex-situ sites will be close to nature reserves or to botanical gardens. Propagation from seeds is preferred, since it would be the least detrimental to the extant populations and would include the widest range of genetic diversity. Optimally, seeds should be taken from many individuals from each of the populations.

References Anon 1999. List of National Key Protected Wild Plants (First Group). The Order of National Forestry Bureau and Agriculture Ministry of China 4: 2–13. Chen X.Y., Wang X.H. and Song Y.C. 1997. Genetic diversity and diﬀerentiation of Cyclobalanopsis glauca populations in east China. Acta Botanica Sinica 39: 149–155. Crepet W.L. and Nixon K.C. 1989. Earliest megafossil evidence of Fagaceae: phylogenetic and biogeographic implications. American Journal of Botany 76: 842–855. Doyle J.J. and Doyle J.L. 1988. Isolation of plant DNA from fresh tissue. Focus 12: 13–15. EBYV (Editorial Board of Yunnan Vegetation). 1987. Vegetation of Yunnan. Science Press, Beijing, China. Elena T., Jose M.I. and Cesar P. 2003. Genetic structure of an endangered plant, Antirrhinum microphyllum (Scrophulariaceae): Allozyme and RAPD analysis. American Journal of Botany 90: 85–92. Fiedler P.L. and Ahouse J.J. 1992. Hierarchies and cause: toward an understanding of rarity in vascular plant species. In Fielder P.L. and Jain S.K. (eds), Conservation biology: the theory and practice of nature conservation, preservation and management. Chapman and Hall, New York, USA, pp. 23–47. Forman L. 1964. Trigonobalanus: a new genus of Fagaceae. Kew Bulletin 17: 381–396. Fu L.G. 1992. China Plant Red Data Book, Vol.1. Science Press, Beijing, China. He S.A., Hao R.M. and Tang S.J. 1996. A study on the ecological factors of endangering mechanism of Liriodendron chinensis (Hemsl.) Sarg. Journal of Plant Research and Environment 5: 1–8. Hsu Y.C., Wang C.J, Wu C.Y. and Li H.W. 1981. Trigonobalanus Forman-A new recorded genus of Fagaceae in China. Acta Botanica Yunnanica 3: 213–215. Hu S.Y. 1982. Embryology of Angiosperm. Higher Education Press, Beijing, China. Huang H.Y., Ma S.B. and Li L. 2001. The genesis of microspore and the formation of male gametophyte in Dysosma versipellis. Bulletin of Botanical Research 21: 561–566. IUCN 2001. IUCN Red List Categories and Criteria: Version 3.1. Information Press, Oxford, UK.

[256]

1317 Jiang Z.G., Ma K.P. and Han X.G. 1997. Conservation Biology. Sciences and Technology Press, Hangzhou, Zhejiang, China. Johri B.M., Ambegaokar K.B. and Srivastava P.S. 1992. Comparative Embryology of Angiosperms, Vol. I. Springer-Verlag, Berlin, Heidelberg. Kaul R.B. and Abbe E.C. 1989. Inﬂorescense architecture and evolution in the Fagaceae. Journal of Arnold Arboretum 65: 375–401. Kimura M. and Crow J.F. 1964. The number of alleles that can be maintained in a ﬁnite population. Genetics 49: 725–738. Lande R. 1988. Genetics and demography in biological conservation. Science 241: 1455–1460. Ledig F.T., Hodgeskiss P.D. and Jocob-Cervantes V. 2002. Genetic diversity, mating system, and conservation of a Mexican subalpine relict, Picea Mexicana Martinez. Conservation Genetics 3: 113–122. Li T.Q. and Cao H.J. 1986. Microsporogenesis and development of male gametophyte of Camellia chrysantha (Hu) Tuyama. Journal of Beijing Forestry University 8: 30–34. Li J. 1994. A preliminary study on the ﬂoristic elements of the community of Formanodendron doichangensis. Acta Botanica Yunnanica 16: 17–24. Li J., Chen K.Y. and Li B.S. 1997. Preliminary study on genetic structure of alpine oaks in Tibet. Journal of Beijing Forestry University 19: 93–98. Li Z.Z., Gong J.J., Wang Y. and Huang H.W. 2003. Spatial structure of AFLP genetic diversity of remnant populations of Metasequoia glyptostroboides (Taxodiaceae). Biodiversity Science 11: 265–275. Liao H.M., Gou G.Q. and Ye N.G. 1998. A study on seedling morphology and anatomy and systematic position of Trigonobalanus doichangensis Form. Journal of Wuhan Botanical Research 16: 223–226. Liao S.Z. and Zhou W.L. 1989. Seed germination experiment of Metasequoia glyptostroboides. Sichuan Forestry Science and Technology 10: 71–74. Nixon K.C. and Crepet W.L. 1989. Trigonobalanus (Fagaceae): Taxonomic status and phyllogenetic relationships. American Journal of Botany 76: 828–841. Oldﬁeld S., Lusty C. and MacKinven A. 1998. The World List of Threatened Trees. World Conservation Press, Cambridge, UK. Pan Y.Z., Gong X. and Liang H.X. 2003. A study on the embryology of endangered plant Manglietia aromatica. Journal of Wuhan Botanical Research 21: 1–8. Pang X.A., Liu X., Liu H., Wu C., Wang J.Y., Yang S.X. and Wang Q.F. 2003. The geographic distribution and habitat of the Isoetes plants in China. Biodiversity Science 11: 288–294. Rabinowitz D. 1981. Seven forms of rarity. In: Synge H. (ed.), The Biological Aspects of Rare Plant Conservation. Wiley, New York, USA, pp. 205–217. Simberloﬀ D. 1988. The contribution of population and community biology to conservation sciences. Annual Review of Ecology and Systematics 19: 473–511. Soepadmo E. 1972. Fagaceae. In: Van Steenis C.G.G.J. (ed.), Flora Malesiana, Ser.1, Vol.7, Pt. 2:265–403. Sun W.B., Zhou Y., Zhao J.C. and Chen G. 2004. Current distribution,population attributes and biological characters of Trigonobalanus doichangensis in relation to its conservation. Acta Ecologia Sinica 24: 352–348. Wang P.L., Pu F.T. and Zheng Z.H. 1998. Palynological evidence for taxonomy of Trigonobalanus (Fagaceae). Acta Phytotaxonomica Sinica 36: 238–241. Wang P.L. and Zhang J.T. 1988. On the pollen morphology and systematic position of Trigonobalanus doichangensis. Acta Phytotaxonomica Sinica 26: 44–46. Whelan E.D.P. 1974. Discontinuities in the callose wall, inter-meiocyte connections, and cytomixis in angiosperm meiocytes. Canadian Journal of Botany 53: 1219–1224. Wu S.M. and Xiao S.Q. 1989. Comparative anatomical studies on the woods of Castanea Mill. and Trigonobalanus Forman in China. Guihaia 22: 567–571. Xia R.X., Ma M.T. and Mao Q.S. 1989. Observation of some features of staminate inﬂorescence and pollen of the major chestnut cultivars in Luotian county. Journal of Huazhong Agricultural University 8: 189–191.

[257]

1318 Xiong Y. 1987. China Soils. Science Press, Beijing, China. YWB (Yunnan Weather Bureau). 1983. Yunnan Agricutural Weather Data Collection. Yunnan People’s Press, Yunnan, China. Zhou Y., Sun W.B. and Li C.R. 2003. Preliminary study on seed germination of Trigonobalanus doichangensis. Journal of Wuhan Botanical Research 21: 73–76. Zhou Y. 2003. Eﬀect of diﬀerent seed provenances on seed germination and seedling growth in Trigonobalanus doichangensis. Seeds 130: 3–4. Zhou Z.K. 1992. Origin, phylogeny and dispersal of Quercus from China. Acta Botanica Yunnanica 14: 227–236. Zhu Q.H., Pan H.X., Zhu G.Q.; Yin T.M., Zou H.Y. and Huang M.R. 2002. Analysis of genetic structure of natural populations of Castanopsis fargesii by RAPDs. Acta Botanica Sinica 44: 1321–1326.

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Biodiversity and Conservation (2006) 15:1319–1338 DOI 10.1007/s10531-005-3875-5

Springer 2006

-1

Ghyll woodlands of the Weald: characterisation and conservation NIALL G. BURNSIDE1,*, DAN J. METCALFE2, ROGER F. SMITH1 and STEVE WAITE3 1

Biogeography & Ecology Research Group (BERG), School of the Environment, University of Brighton, Cockcroft Building, Moulsecoomb, Brighton BN2 4GJ, United Kingdom; 2CSIRO Tropical Forest Research Centre, PO Box 780, Atherton, Qld 4883 Australia; 3Biogeography & Ecology Research Group (BERG), Biology Division, University of Brighton, Cockcroft Building, Moulsecoomb, Brighton BN2 4GJ, United Kingdom; *Author for correspondence (e-mail: N.G.Burnside@ brighton.ac.uk; fax: +44-0-1273-642285) Received 24 May 2004; accepted in revised form 8 March 2005

Key words: Biodiversity conservation, Geographical information systems, Ghyll woodlands, The Weald, Woodland characterisation Abstract. Ghylls are linear valley features cut into the sandy beds of the Weald of south-eastern England. The ghyll’s indigenous woodlands are highly species rich at the small scale, support distinctive assemblages of cryptogamic plants, and are unique to south-east England. Field surveys were carried out for 48 ghyll woodlands in the Weald with a GIS used to examine the ecology, landform and conservation status of the ghyll woodlands. The data were analysed using spatial and multi-variate techniques in order to identify sub-groups or ghyll woodland communities based upon species composition, topography and geology. The ghylls are shown to be reasonably uniform for canopy vegetation type and structure and for their geological and soil characteristics. However, analysis shows that geomorphology, understorey and ﬁeld layer variability may act as stronger indicators of site conditions and character. Further analysis focused on the level and extent of nature conservation protection that these unique and ancient systems receive. The study concludes that despite their ecological importance and potentially international signiﬁcance, ghyll woodlands are poorly understood and protected.

Introduction The Weald of southeast England supports woodland valley systems internationally distinct in both their ecology and geomorphology. The ghyll woodlands, around 1000 in total, are typically linear features occupying deep and narrow valleys cut into the sandy and silty Hastings Beds and the Weald and Wadhurst clays (Woolridge and Goldring 1962). The sheltered valleys occupied by ghyll woodlands buﬀer temperature ﬂuctuations and maintain high humidity levels resulting in unusually oceanic micro-climatic conditions (Rose 1995). Elsewhere in northwestern Europe, ghyll-like valleys are rare, and thus the concentration of these features in lowland England has international geomorphological and ecological signiﬁcance (Rose and Patmore 1997). The Weald has retained extensive tracts of a variety of ecologically important woodland types, and notably the central High Weald (HW) is the most [259]

1320 wooded natural area in England (Countryside Commission 1994; Rose 1995; Reid et al. 1996; Forestry Commission 2001). Spatial and structural analyses suggest that the ghyll woodland systems are an important and signiﬁcant landscape feature in the Weald and are of high conservation value (Rose 1995; Rose and Patmore 1997; Burnside et al. 2002). Yet, ghyll woodlands have received only scant attention in the past. The international and national ecological signiﬁcance of these ghyll woodlands is that they support a unique assemblage of cryptogamic plants with both oceanic and sub-oceanic aﬃliations (Ratcliﬀe 1968; Hodgetts 1997). The presence of rich liverwort and moss communities suggests that the ghyll woodlands are of considerable age, and are therefore also likely to support a high biodiversity of other species of conservation concern, particularly terrestrial invertebrates, which share similar micro-environmental requirements (Peterken 1993; Rose and Patmore 1997; Woodland Trust 2000). Most can be regarded as ‘ancient woodland’ (sensu Rackham 1980; Peterken 1981; Forestry Commission 2001), and Rose and Patmore (1997) suggest that ﬁeld investigations may indicate that some fragments could represent actual remnants of prehistoric woodland. Much of south-eastern and southern England underwent preferential exploitation of woodland following a phase of human expansion in the late Neolithic/early Bronze Age (Waller and Marlow 1994). From a land-use perspective, however, the steep slopes of the ghylls have meant that, for the most part, they have remaining relatively uncultivated and thus wooded. Historically, the Weald area, though diﬃcult to cultivate, beneﬁted from the iron industry with many woods managed (coppiced1) for charcoal production and subsequent iron smelting (Brandon 1977; Cleere and Crossley 1985; Sussex Biodiversity Partnership 2000). This provided early conservation of the woodlands, as the resource was managed on a long-term sustainable basis, and may have resulted in many ghylls maintaining ‘old forest type epiphytic lichens and bryophytes’ (Rose and Patmore 1997). The geology and geomorphology of the ghylls is also distinctive. In the sandstone beds of the Weald, ghylls can take the form of narrow rock-walled gorges. Conversely, where rocks are softer, slopes tend to be shallower and the valleys less conﬁned (Rose 1995). The Wealden ghylls diﬀer from similar features in southwest England, as a result of greater continental climatic inﬂuences, and the presence of relatively clay-rich soils. Rose and Patmore (1997) report that similar ghyll-like features do occur in other parts of lowland Britain that were not blanketed by glacial drift. Most, however, are shallow with gentler relief and do not exhibit the steep morphology present in the Weald. Many ghyll valleys extend over 1 km in length and, as a result of the complexity of Wealden geology, traverse a number of diﬀerent geological strata 1 Coppicing is the productive management of woodland. Trees are cut down and encouraged to grow again from the stump. Coppicing produces a large number of thin stems, which are harvested on a regular cycle of about 5–15 years.

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1321 (Gallois 1965). This variability in geology and unusual micro-climate has clear implications for ecological diversity, and is considered to inﬂuence the high levels of bryophyte diversity observed in ghyll systems (Rose and Patmore 1997). The study presented within this paper constitutes the ﬁrst attempt to use geographical information system (GIS) approaches and contemporary surveys to analyse and characterise these unique systems. The analysis focuses on the geomorphological and ecological characteristics of the ghylls, but also considers how the ghyll systems relate to existing conservation provision. GISbased cadastral approaches and multi-variate statistical techniques are used to compare and analyse environmental, management and species information derived from ﬁeld surveys undertaken for a sample of ghyll woodlands within southeast England.

Methodology GIS techniques coupled with recent ﬁeld survey data and secondary data derived from digital maps have been used in an inductive study to analyse a range of environmental and ecological characteristics for ghyll woodlands within the central Weald.

Development of a GIS database The study used boundary data for 1130 ghylls in the Weald. The development of the GIS required the collation of large amounts of secondary data held in digital and non-digital form. Data, such as ghyll woodland boundaries, nature conservation designations, topography and soil associations, were obtained in digital form. The ghyll woodland boundary data were compiled from ﬁeld reports held at the regional Biological Records Centre. The statutory nature conservation designations examined included the boundaries of Sites of Special Scientiﬁc Interest (SSSI), Special Areas of Conservation (SAC), National Nature Reserves (NNR), and also ancient woodland (AW). The resultant GIS was structured around geographic and ecological landscape features.

Field survey This study has used data from ﬁeld surveys of 48 ghyll woodland systems throughout East and West Sussex (Figure 1). Using a uniform walkover survey approach, ﬁeld survey data recorded both biotic and abiotic characteristics of the ghylls (Table 1). The data were used to construct a GIS database containing site-speciﬁc information on the ecology, landform and management of [261]

1322 48 ghyll woodlands randomly selected from 1130 ghyll woodlands. Where there were substantial diﬀerences in the vegetational or geomorphological structure in individual ghylls, multiple surveys were undertaken so as to represent this internal variation. The variables included in the survey reﬂected those considered important in characterising ghylls (Table 1), and were integrated in a GIS and analysed using spatial and multi-variate techniques to identify subgroups or types of ghyll systems.

Table 1. Field survey information for the ghyll woodland sample in the Weald. Characteristics

Descriptors

Geology

Predominant geological bed, geological beds in choronological sequence Valley form proﬁles, channel dimensions, height of ghyll,degree of fall, length of ghyll Coppicing, thinning/selective felling, clear felling, adjacent land use Broadleaved, coniferous, mixed-woodland NVC – e.g. W6,W8,W10 Canopy, understorey, ﬁeld layer vegetation composition using DAFOR scale, presence of alien species Geomorphology – waterfalls, sandstone outcrops Ecology – bryophytes, invertebrates

Geomorphology Present land use Woodland type Vegetation structure Presence of important features

Figure 1. The location of the ghyll woodland ﬁeld survey sites. [262]

1323 Spatial and statistical multi-variate analysis of the data FragStats (McGarigal and Marks 1994) was used to measure area, perimeter length, and inter-patch distance for the ghyll woodlands. Additional spatial statistics were calculated for the digital boundary data of ghyll woodlands, to permit an assessment of the woodland pattern and physiognomy, relevant to the habitat and species of concern (HainesYoung and Choppin 1996; Gkaraveli et al. 2001). Using a cadastral approach, each ghyll woodland was examined to establish if it was either in [within] or abutted [intersected] one of the nature conservation designations (SSSI, SAC, NNR, AW) to facilitate examination of existing conservation designation for these sites. This analysis of ghyll woodland location was also undertaken for relevant English Nature landscape character areas, LCA (English Nature 2002). This analysis facilitated the classiﬁcation of ghylls within broad-scale landscape management descriptions, for example, High Weald or Low Weald character areas (English Nature 2002). The GIS was further utilised to examine the relationship between the ghyll woodland systems and soil associations using the woodland digital boundaries and digital soil information (SSLRC 2001). Soil associations known to be allied with ghyll woodlands were examined and proportional areas of ghyll woodlands situated in these soil types calculated using standard cadastral approaches (ESRI 1998). Statistical analysis involved the application of multi-variate techniques to the ﬁeld survey data. Cluster analysis and principal component analysis (PCA) were used to examine the diﬀerences in the ghyll woodlands for all major attributes recorded in the survey (the data format did not support detrended correspondence analysis) (Kent and Coker 1992; Everitt et al. 2001). The cluster analysis technique used average linkage and the Manhattan similarity index to describe the group of classiﬁcation procedures (Waite 2000). In this analysis all ghyll woodland sites were initially considered to represent unique ghyll woodland systems or sites. A hierarchical classiﬁcation was derived from a matrix, and based upon the values within that matrix samples were joined to form similar groups (Waite 2000). At each level, groups were joined based on their similarity. The process continued until all groups were joined to a common root. PCA, was also used to assess the similarity or variation between these woodland systems based upon their vegetation and environmental features (Fowler et al. 1999; Waite 2000). A PCA ordination was undertaken to examine the gradients and variation in vegetation present within the ghyll systems. Analysis was undertaken collectively for the main canopy, understorey, and ﬁeld layer vegetation data along with geological and environmental features (e.g. geological strata and valley form). This provided an initial analysis of a range of biotic and abiotic features associated with these distinct systems. [263]

1324 Results Spatial patterns Analysis indicates that ghyll woodlands cover 9332 ha of East and West Sussex, and are divided into 1130 patches (Table 2). The mean patch size (or habitat area) of ghyll woodland fragments is 8 ha. The ghyll woodlands have a high density of patches with 12 patches per 100 ha in the area of the Weald examined (Table 2). The mean patch shape calculations show that the ghyll woodland habitats (Shape Index = 17) are not uniform in shape (i.e. patch shapes move away from being regular shapes such as squares or circles). The calculation of mean nearest neighbour distance (NND) between ghyll woodland habitats gives values of 217 m (±250.5). A number of ghylls are however joined by contiguous areas of other woodland (managed and unmanaged). Thus, care must be taken to ensure that conclusions are not drawn regarding potential fragmentation eﬀects (Wiens 1989; Bailey et al. 2002).

Conservation designations Cadastral analysis of the ghyll woodland systems and national conservation designations indicate that the ghyll systems have not been a focus of conservation attention and on a site basis only 9% are included within SSSI. This proportion is also reﬂected in the sample of surveyed ghylls, where only 12% were identiﬁed as being associated with SSSIs. Furthermore, only 4% of ghyll woodland sites intersect the boundaries of SAC, and no ghyll woodlands are designated as NNR The GIS analysis shows, however, that on a site basis 85% of the ghyll woodland systems are associated with areas of AW(both semi-natural and replanted) in East and West Sussex. Additionally, a substantial number of ghyll woodlands are included in the locally designated sites of nature conservation interest (SNCI), and a number fall within important landscape Table 2. Spatial statistics for the Ghyll woodlands within the Central Weald of East and West Sussex (raster format). Raster indices

Ghyll woodland

Total area (ha) Mean area (ha) Mean area std dev Patch number Patch density (#/100 ha) Mean Shape Index Mean NND (m) Mean NND std dev

9332 8 13.3 1130 12 2.17 217 250.5

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1325

Figure 2. The relationship between ghyll woodland systems and English Nature landscape character areas.

designations such as area of outstanding natural beauty (AONB) and the HW. Comparison of the distribution of ghyll woodlands and LCA classiﬁcation (English Nature 2002) reveals that 92% of ghyll systems are associated with the HW LCA. A further 6% are found in the Low Weald LCA and, as might be anticipated, only 2% are found in the Romney Marsh LCA (Figure 2).

Plant community characteristics GIS data and ﬁeld surveys revealed that Quercus robur – Pteridium aquilinum – Rubus fruticosus woodland (NVC – W10) and Fraxinus excelsior – Acer campestre – Mercurialis perennis woodland (NVC – W8) were the most common woodland community types found. Of the woodland surveyed, 47% was found to be predominantly W10, and a further 43% dominated by W8 woodland. The remaining areas were comprised of W7, W12, W15 and some pockets of W4, W6 and W16 woodland (Rodwell 1998). Analysis using multivariate statistical approaches (Cluster analysis and PCA) was performed on the digital survey records. This provided a descriptive means of assessing similarity and diﬀerentiation both within individual ghylls and between different ghyll woodland sites. Cluster analysis was initially undertaken for the

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1326 three vegetation components surveyed; the canopy, the understorey and the ﬁeld layer.

The canopy The canopy data shows that overall there is a moderately good level of similarity in the composition of the canopy within the sampled ghyll woodland systems (Figure 3a). Values of between 38 and 55% similarity were obtained when comparing the overall data set and the various sub-groupings. When clusters were grouped, analysis showed an increase in the similarity values with groups 1–3 and 8 between 50 and 60% similar whilst groups 4–7 showed similarity values greater than 60% (see appendices). Within these groups, one major anomaly was seen at Fairlight Glen, Hastings which was clearly identiﬁed as an outlier. This is because the canopy of this southern, more coastal, section of Fairlight Glen ghyll is solely dominated by Salix species. Further analysis identiﬁed some clear ghyll woodland associations, all showing comparatively high similarity values (>64%). The data may suggest that there are some ‘canopy’ based associations within these ghyll woodlands. For example, Group 1 is shown to be 42% similar to the other ghyll woodlands surveyed yet, there is a moderately high level of canopy similarity within the group itself (56%) (see appendices). More speciﬁcally, two classes are identiﬁed and, of these, the two Brick Kiln ghyll woodland areas are identical in canopy structure. Furthermore, the analysis picks out two, somewhat individual, ghyll woodlands based upon canopy composition, Kiln Wood (Lower ghyll) (no. 11) and Sandyden Wood (no. 49). These woodlands are shown as only 38% similar to all other ghyll woodlands surveyed and have no comparative ghylls at the group or class level (Figure 3a).

The understorey The data shows that, generally, there is similarity in the composition of the understorey within the ghyll woodland systems (Figure 3b). Values of between 31 and 61% similarity were obtained when comparing the overall data set and the various sub-groupings provided through cluster analysis. The analysis at the group level showed a substantial increase in the similarity values with all groups, apart from group 1, greater than 60% similar. These ﬁndings may indicate some potential categories or communities. Analysis at the class level shows strong association within the ghyll woodland systems, with similarity values around 75–100%. The analysis shows that when the understorey vegetation is examined many of the ghyll sites display little diﬀerence (e.g. Marline Valley, Batemans and Northlands [266]

1327

Figure 3. Cluster analysis dendrogram of the ghyll woodland canopy (a), under-storey (b), and ﬁeld (c) survey data. A complete table of percentage similarity values derived from cluster analysis is provided in the appendix.

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1328 Wood). It is, however, interesting to note that the analysis shows that Marline valley does have some zonation within the ghyll – reﬂected in the fact that two surveys were conducted at the site. Marline valley (away from stream) and Marline Valley (near stream) are identical, as are Marline Valley (by watercourse) and Marline Valley (away from watercourse). When comparing these two groups the analysis only shows a similarity value of 47% between them (Figure 3b). The analysis isolates Waterfall Wood as relatively distinctive. When the GIS database and survey sheets are examined, this separation appears to be an artefact of the understorey composition. Waterfall wood is the only ghyll with the understorey solely dominated by Alnus species. Highams Ghyll and Sandyden Wood also have Alnus species present within the understorey; however, closer inspection shows that Highams also has Crataegus monogyna dominant and Ilex aquifolium occasional within the understorey, whilst Sandyden Ghyll has Sambucus nigra frequent within the understorey and Corylus avellana occasional.

The ﬁeld layer The analysis of the ﬁeld layer data using cluster analysis shows that some data sets appear very dissimilar with values ranging from 21 to 39% similarity (derived from 11 site surveys). In contrast, 48 of the remaining sites show high levels of similarity (Figure 3c). When considering the cluster analysis for ﬁeld data, the dendrogram clearly shows that those sites to the right of the ﬁgure are on the whole largely dissimilar whilst those sites to the left of the ﬁgure reveal moderately good levels of similarity, >50% (Figure 3c). When grouped, over half of the sites show similarity levels of 62%. Furthermore, within group 1, for example, the associations show 13 sites with 80% similarity and a further 15 sites with 81% similarity (see appendices). Despite these high levels of ﬁeld layer similarity within the majority of ghyll systems, there are additional ghyll systems which are shown to be relatively distinctive in character and ﬁeld layer composition. Sandyden Wood and Waterfall Wood are shown to be 50% similar to each other in presence/ absence, but are only 39% similar to all other ghyll woodlands surveyed. Wicks Copse and Tilsmore Wood are also outliers with similarity values of 25 and 21% respectively (Figure 3c). Wren’s Warren is also distinct, separated from other ghylls by the presence of Vaccinium spp. within the ﬁeld layer (see appendices).

Ghyll woodlands and soils Cadastral analysis via the GIS demonstrates that the ghyll woodlands occupy a range of soil types. At a general level, GIS analysis indicates that 85% of the [268]

1329 ghyll woodlands are associated, to some extent, with brown soils and particularly with argillic brown earths of the Curtisden association (Association 5.72i of Jarvis et al. 1984). This association is widespread throughout the HW, occurring on siltstones and sandstones. In this association, slope relief is typically strong with moderately to steeply sloping valleys [ghylls] separated by gently sloping interﬂuves. Soils of the Curtisden association are usually moderately deep on gentle or moderate slopes. Characteristically, the soils comprise slowly permeable compact subsoil, which is subject to seasonal water logging. Springs and ﬂushes are often common on the sloping ground of permeable and impermeable strata (Jarvis et al. 1984). Ghyll woodlands are also commonly found on surface-water gley soils (Stagnogley Associations 7.11e, 7.11i and 7.12b of Jarvis et al. 1984), which are linked, again to varying degrees, with 55% of ghyll systems. The Wickhams 1 and 5 Associations are extensive on the Low Weald. The Wickham Associations have slowly permeable subsoils and are often waterlogged for prolonged periods in winter. Often heavily wooded, these soils are naturally acidic and can have good reserves of available water (Jarvis et al. 1984). Other associations are linked with the ghyll systems but their importance is low. Podzolic soils, in particular gley podzolic soils, are associated with 4% of the ghyll systems. Only 1% are associated with ground water gley soils.

Cluster analysis of geological and topographical data Cluster analysis was undertaken for the geological components of the surveys, including surrounding geology, 1st, 2nd, 3rd Geological Beds (in chronological sequence), height at top of ghyll, and height diﬀerence within the ghyll valley. The geological and topographical data shows substantial level of similarity within the ghyll woodland systems with 89% of the sites being >68% similar (Figure 4). All reside on the clays and sands of the Hastings Beds. Beyond this level of similarity there are some additional sub-groupings with particularly strong associations yielding similarity values >80% (Figure 4), which reﬂect the presence of ghylls on Ashdown sands, Tunbridge sands, Wadhurst clays and Fairlight clays. Figure 4a also shows that some sites appear relatively distinctive in comparison to the majority of ghylls surveyed. Site 41 (Guestling Wood) shows low similarity values of 28% to all other ghyll systems examined. Two of the Fairlight Glen surveys (Sites 46 and 27) show good similarity when compared to each other (87%), but are only 41% similar to all other systems. Equally, Courtlands Wood (Site 5) and Little Iwood (Site 10) are similar to one another (90%) but are only 54% similar to all other survey sites. Examination of the GIS database and survey sheets suggests that these diﬀerences are related to surrounding geology, strata and average levels of fall along the ghyll. Further cluster analysis was undertaken for the geological components [269]

1330

Figure 4. Cluster analysis dendrogram of the ghyll woodland geological (a) and geological and vegetation survey data combined (b).

and the vegetational data from the ghyll woodland surveys combined (Figure 4b). The dendrogram repeats patterns observed within the previous cluster analysis showing a strong association (>62%) between the majority of ghyll woodland sites surveyed (over 80% of sites). In addition, the dendrogram isolated the same sites as being distinctive including Fairlight Glen, Guestling Wood, Courtlands Wood, Little Iwood and Marline Valley (Figure 4b). This similarity of outcomes may be associated with the dominance of geological data within the analysis of both data matrices and the relatively weak [270]

1331 contribution of the vegetational components to the geology and vegetational matrix.

PCA of geological and vegetational data PCA analysis of the geological and vegetational survey data reinforces the conclusions drawn from the cluster analysis. Analysis shows high levels of association between the majority of ghyll systems based upon the variables (shown by the main grouping on the ordination, Figure 5). This suggests that the majority of ghyll systems have similar geological and vegetational characteristics and little or no separation is present along either axis. It is however, interesting to note that there are two ghylls separated from the main grouping along the ﬁrst component showing 24% of the variation (eigenvalue = 2.419) (Figure 5). Both Fairlight Glen and Marline Valley (near watercourse) are separated along this axis and examination of the GIS database suggests that this relates to strong diﬀerences in their geological

Figure 5. PCA analysis ordination of the ghyll woodland geological and vegetational survey data. [271]

1332 beds, valley form and average degree of fall along the ghyll. Equally, a further three ghylls are separated from the main grouping along the second component showing 20% of the variation (eigenvalue=2.002). Guestling Wood, Courtlands Wood and Little Iwood are separated here and the survey data again points to geological conditions although some diﬀerences are evident within their National Vegetational Classiﬁcations (Rodwell 1998) (Figure 5).

Discussion Using a GIS-based spatial approach and multi-variate statistical techniques, this inductive study has provided an initial analysis of a sample of ghyll woodlands within the Weald of southeast England which suggests the signiﬁcance of these important ecosystems within the broader landscape context. Biological Records Centre digital data sets identify 1130 ghyll woodlands in the High and Low Weald LCA. Spatial analysis suggests that, on an area basis, these ghylls comprise 23% of the woodland within East Sussex alone. This, however, is likely to be an over-estimate due to boundary issues, and the previous classiﬁcation of substantial woodland areas as ghylls beyond the conﬁnes of the characteristic valley systems (Burnside et al. 2002). This latter point is of particular relevance to area calculations, as ghyll systems are normally regarded as restricted to small linear valley features. The analysis of the composite GIS survey database and ﬁeld surveys using multi-variate techniques has shown that the vegetation within the ghyll woodlands is relatively similar in the canopy, understorey and ﬁeld layers with similarity values of around 50–60%. The similarity reﬂects the common occurrence of NVC type W10 and W8 woodlands and a dominance of Quercus sp. and Fraxinus sp. respectively in the canopy. Equally, within the understorey and ﬁeld layer the often widespread incidence of Ilex aquifolium and Corylus avellana, and in other cases of Rubus fruticosus and Pteridium aquilinum, provided good similarity levels. In some cases, however, the vegetation within particular ghylls does appear distinctive with percentage similarity values dropping to 20–30%. In relation to the canopy this reﬂected cases whereby the vegetation was solely dominated by Salix species. In relation to the understorey layer, the distinctive nature of some ghylls reﬂected the strong presence of Castanea sativa and the management practice of rotation coppicing. Analysis of the geological data also illustrates that the ghylls are undiﬀerentiated at the general level. Cluster analysis identiﬁed that around 90% of sites were 70% similar for geological beds (e.g. Ashdown beds or Tunbridge Wells sands) and topographic characteristics (e.g. depth of ghyll and degree of fall). However, as shown by the vegetational analysis, some of the ghylls do remain relatively distinctive in topography (levels including 30–40% [272]

1333 similarity), which reﬂects the importance of landscape inﬂuence. The PCA shows, from a geological, geomorphological and ecological perspective that valley form, underlying geology and woodland type (sensu NVC) can be used to diﬀerentiate some ghyll woodlands (Figure 5). For example, Fairlight Glen and Marline valley are shown to be representative of steep-sided, conﬁned valleys, on harder Wadhurst clays with a dominance of traditional Quercus robur – Pteridium aquilinum – Rubus fruticosus woodland (NVC – W10). Whilst Guestling wood, Little Iwood and Courtlands wood, are representative of more open valleys on unconsolidated and unlithiﬁed head-material. The latter ghylls exhibit a strong presence of Fraxinus excelsior – Acer campestre – Mercurialis perennis woodland (NVC – W8), vegetation more characteristic of base-rich soils (Rodwell 1998). In comparative terms, many of the ‘main groupings’ display less distinctive traits and exhibit the more general characteristics, which include Ashdown or Tunbridge geology, a moderate depth of ghyll (circa 20 m) and more than one woodland community along the entire valley proﬁle. Comparison of the ghyll woodland data and nature conservation designation conﬁrms that in many cases the ghyll systems have received little protection. It is apparent that a substantial number of the ghyll woodlands fall within the broad remit of landscape designations, such as AONB, but on a site-by-site basis only about 10% have beneﬁted from a nationally recognised conservation designation. This may result from the small size and linear character of individual ghyll woodlands when placed in the context of the broader wooded landscape. Eﬀectively, ghyll woodlands represent small pockets of exceptionally high diversity, but often occur in broader woodlands that do not warrant designation. The analysis presented here may well indicate an under-representation of these intrinsically small and fragmented sites within existing statutory protection (Kirby 2003). These linear and fragmented sites may also be susceptable to the negative aspects of edge eﬀect and incursion by more robust and competitive species (Harrison and Bruna 1999). Alterations to the understorey and canopy layers as a result of species change could have severely detrimental eﬀects to the structure of the woodland systems (Burke 1998), and may result in a reduction in biodiversity and the loss of more specialised species indicative of the ghyll woodland habitats. The study emphasises the importance of developing appropriate management plans for these sites, and the need to set appropriate nature conservation designation. As stated earlier, many of the ghyll woodlands are AW and have for the most part remained relatively undisturbed (Hodgetts 1997; Rose and Patmore 1997). This is an important consideration in relation to both biodiversity management and biological conservation. In many cases, whilst maintaining rich (and often locally rare) cryptogamic communities, ghyll valleys have no prescribed management plans and are under private ownership. Sustaining and promoting biodiversity at the [273]

1334 landscape scale requires the characterisation and maintenance of pockets of high biodiversity (Ernoult et al. 2003). In the case of some ghyll woodlands, this may only involve non-interventionist management but, nevertheless, designation must be secured. Some ghylls have been given regional status via SNCI designation, but this is a local designation and provides only limited protection.

Conclusion GIS database and multi-variate statistical approaches have been used to investigate ghyll woodland systems of the Sussex Weald. The ghylls have been shown to be a reasonably uniform vegetation type in terms of the canopy and their geological and soil characteristics. Yet, the variation in geology and climate, along with historical factors creates a system which is very species rich at the small scale (Waller and Marlow 1994; Rose and Patmore 1997; Sussex Biodiversity Partnership 2000). Analysis shows that the ghyll woodlands oﬀer substantial opportunity for analysis of woodland characterisation and diversity. Some workers consider that bryophyte species occurrence and frequency may be the key to the systematic diﬀerentiation of ghyll woodland communities (Rose 1995; Rose and Patmore 1997), whilst others propose a more balanced approach looking at both ecological and landscape factors together (Burnside et al. 2002). However, this study shows that the geomorphology, understorey and ﬁeld layer may act as an initial indicator of site conditions and character. The research has also demonstrated that ghylls have relatively weak levels of habitat protection in respect of their known conservation value for lower plants. Addressing this protection is of critical importance given the national, and potentially international, signiﬁcance of the ghyll woodlands of the Weald. Further GIS investigations linking surveys of mosses and lichens with climatic and aspect data could provide a means to identify noteworthy ghyll woodlands for conservation targeting.

Acknowledgements Special thanks go to Neil Carrett for his assistance and input in the project, and Colin Reader (Habitat Management Services) and John Patmore (University of Brighton) for conducting the surveys. We would also like to thank David Saunders and Laetitia Tual (East Sussex County Council) for their support and provision of additional data for this project. GIS analysis was performed on ArcView 3.x software, Environmental Systems Research Institute and FragStats (ver 2), McGarigal and Marks (1992). [274]

1335 Statistical analysis performed using WinSTAT 3.1, Kalmia Co. Inc., 1995. Terrain data supplied by EDINA Edinburgh University, 2002; soil data supplied by SILSOE, Cranﬁeld University, 2002; forestry and woodland data supplied by Forestry Commission, 2002; English Nature GUI, 2002, and Sussex Biological Records Centre, 2001.

Appendices Table A1. Percentage Similarity of cluster analysis for Canopy data.

[275]

1336 Table A2. Percentage Similarity of cluster analysis for Understory data.

[276]

1337 Table A3. Percentage similarity of cluster analysis for Field data.

References Bailey S.A., Haines-Young R.H. and Watkins C. 2002. Species presence in fragmented landscapes: modelling of species requirements at the national level. Biological Conservation 108: 307–316. Brandon P. 1977. The Sussex Landscape. Hodder and Stoughton, London. Burke D.M. 1998. Edge and fragment size eﬀects on the vegetation of deciduous forests in Ontario, Canada. Natural Areas Journal 18: 45–53. Burnside N.G., Carrett N.J., Metcalfe D. and Waite S. 2002. GIS analysis of Ancient and Ghyll Woodlands within East Sussex. Biogeography & Ecology Research Group, University of Brighton, Brighton. Cleere H. and Crossley D. 1985. The Iron-industry of the Weald. Leicester University Press, Leicester. Countryside Commission. 1994. The High Weald. Countryside Commission, Northhampton. English Nature. 2002. Landscape Character Areas, Data prepared by English Nature GUI. URL http://www.english-nature.org.uk/. Ernoult A., Bureau F. and Poudevigne I. 2003. Patterns of organisation in changing landscapes: implications for the management of biodiversity. Landscape Ecology 18(3): 239–251. ESRI. 1998. ArcView 3.2, Software System. Environmental Systems Research Institute Inc. Everitt B.S., Landau S. and Leese M. 2001. Cluster Analysis, 4th ed. Arnold, London. [277]

1338 Forestry Commission. 2001. National Inventory of Woodland and Trees: England. Forestry Commission, Edinburgh. Fowler J., Cohen L. and Jarvis P. 1999. Practical Statistics for Field Biology. Wiley, Chichester, West Sussex. Gallois R.W. 1965. British Regional Geology, 4th ed. Department of Scientiﬁc and Industrial Research, London, UK. Gkaraveli A., Williams J.H. and Good J.E.G. 2001. Fragmented native woodlands in Snowdonia (UK): assessment and amelioration. Forestry 74(2): 89–103. Haines-Young R. and Chopping M. 1996. Quantifying landscape structure: a review of landscape indices and their application to forested landscapes. Progress in Physical Geography 20: 418–445. Harrison S. and Bruna E. 1999. Habitat fragmentation and large-scale conservation: what do we know for sure? Ecography 22: 225–232. Hodgetts N.G. 1997. A National and International Context for the Cryptograms in the Weald with Reference to Current and Future Conservation Initiatives for UK Cryptograms. In: Jackson A. and Flanagan M. (eds), Conservation of Cryptogams in the Weald. Proceedings of the Workshop held at Wakehurst Place 2nd May 1996. Royal Botanic Gardens, Kew pp.1–18. Jarvis M.G., Allen S.J., Fordham S., Hazelden J., Moﬀat A.J. and Sturdy R.G. 1984. Soils and their Use in South East England. Soil Survey, Harpenden. Kent M. and Coker P. 1992. Vegetation Description and Analysis a Practical Approach. John Wiley and Sons, Chichester. Kirby K.J. 2003. Woodland conservation in privately-owned cultural landscapes: the English experience. Environmental Science and Policy 6(3): 253–259. McGarigal, K. and Marks B.J. 1994. FRAGSTATS Spatial Pattern Analysis Program for Quantifying Landscape Structure, Version 2. Forest Science Department, Oregon State University, Corvallis. Peterken G.F. 1981. Wood anemone in central Lincolnshire: an ancient woodland indicator? Transactions Lincolnshire Natural Union 20: 78–82. Peterken G.F. 1993. Woodland Conservation and Management, 2nd ed. Chapman and Hall, London. Rackham O. 1980. Ancient Woodland. Arnold, London. Ratcliﬀe D.A. 1968. An ecological account of the Atlantic bryophytes in the British Isles. New Phytologist 67: 365–430. Reid C.M., Kirby K.J. and Cooke R. 1996. A Preliminary Assessment of Woodland Conservation in England by Natural Area. English Nature, Peterborough, UK. Rodwell J.S. 1998. British Plant Communities Volume 1: Woodlands and Scrub. Cambridge University Press, Cambridge. Rose F. 1995. The Habitats and Vegetation of Sussex. The Booth Museum of Natural History, Brighton Borough Council. Rose F. and Patmore J.M. 1997. Gill Woodlands in the Weald. English Nature, Peterborough. SSLRC. 2001. Sussex Soil Associations. Data prepared by National Soil Resources Institute (SSLRC), Digital Data Copyright (c) Cranﬁeld University, 2001 (SSLRC Project Code: JP7017v/ 9). Sussex Biodiversity Partnership. 2000. Woodland Habitat Action Plan. Sussex Biodiversity Partnership, Sussex. Waller M.P. and Marlow A.D. 1994. Flandrian vegetational history of southeastern England – stratigraphy of the Brede Valley and pollen data from Brede Bridge. New Phytologist 126(2): 369–392. Waite S. 2000. Statistical Ecology: A Practical Guide. Prentice Hall, Harlow, UK. Wiens J.A. 1989. The Ecology of Bird Communities, Vol. 2. Cambridge University Press, New York. Woodland Trust. 2000. Woodland Biodiversity: Expanding Our Horizons. Woodland Trust, Grantham, Lincs. Woolridge S.W. and Goldring F. 1962. The Weald, 3rd ed. Collins, London. UK.

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Biodiversity and Conservation (2006) 15:1339–1351 DOI 10.1007/s10531-005-4875-1

Springer 2006

-1

Eﬀects of fragmentation of evergreen broad-leaved forests on genetic diversity of Ardisia crenata var. bicolor (Myrsinaceae) AI-LIAN ZHAO1, XIAO-YONG CHEN1,2,*, XIN ZHANG1 and DONG ZHANG1 1

Department of Environmental Sciences, East China Normal University, Shanghai 200062, P. R. China; 2Shanghai Key Laboratory for Ecological Processes and Restoration in Urban Areas, Zhongshan R. (N.) 3663, Shanghai 200062, P. R. China; *Author for correspondence (e-mails: [email protected], [email protected]; phone: +86-21-62232697; fax: +86-21-62233669) Received 11 May 2004; accepted in revised form 20 March 2005

Key words: Ardisia crenata var. bicolor, Diﬀerentiation, Forest fragmentation, Genetic diversity, Population size, RAPD markers Abstract. Due to the long generation times and high densities, dominant tree species usually did not respond consistently with theoretical predictions to the recent fragmentation. Genetic structures of shrubs and herbs, especially those with low densities, may be more sensitive to forest fragmentation. We studied the genetic structure of a self-compatible subshrub, Ardisia crenata var. bicolor (Myrsinaceae) in a recently fragmented landscape. Ten RAPD primers used for analysis generated a total of 76 bands. We found that A. c. var. bicolor had relatively low species-level (P95 = 63.2%; H = 0.106; Shannon diversity index (SI) = 0.246) and within-population diversity (P95 = 5.346.1%; H = 0.0260.175; SI = 0.0320.253), and signiﬁcant population diﬀerentiation (GST = 0.445). Signiﬁcantly positive relationships were found between measures of diversity (P95, H and SI) and the log of estimated population size. No signiﬁcant relationship was observed between Nei’s genetic distance and spatial distance of pairwise populations, indicating no isolationby-distance. Given most species of forests are shrubs and herbs with short generation times, our observation indicated that distinct genetic consequences of recent fragmentation may be expected for quite a number of plant species.

Introduction Due to increased urbanization, intensive agricultural practices and habitat destruction, many plant species occur in highly fragmented habitats (Van Rossum et al. 2004). Usually, consequences of habitat fragmentation consist of reduced population size and increased isolation (Saunders et al. 1991; Van Rossum et al. 2004), leading to genetic erosion and increased genetic diﬀerentiation among populations, through random drift, increased levels of inbreeding and reduced gene ﬂow (Young et al. 1996; Chen 2000; Van Rossum et al. 2004). Ultimately these genetic processes may result in ﬁtness declines and extinction (Keller and Waller 2002; Bacles et al. 2004). There have been increasing studies concerning genetic eﬀects in plants of habitat fragmentation, and loss of genetic diversity and increased diﬀeren[279]

1340 tiation have been found in some systems (e.g., Raijmann et al. 1994; Hall et al. 1996; Morden and Loeﬄer 1999; Frankham et al. 2002). However, these responses to increased fragmentation are unlikely to be common, and other factors may inﬂuence the genetic consequences of fragmentation. First, most studies were conducted on long-lived species in a recently fragmented landscape and there were not suﬃcient time for bottleneck and inbreeding to take action (Young et al. 1993; Cardoso et al. 1998). Long-lasting, dormant seed banks also can buﬀer against genetic eﬀects for decades or centuries (Morris et al. 2002). Second, many plant species studied were dominant species with high density. Thus, populations in fragmented habitats were large enough to maintain relatively high genetic diversity. Thirdly, some species are naturally rare species, and have evolved mechanisms to overcome the disadvantages of small population size. Thus, genetic consequences of recent fragmentation may not be detectable for a long time (England et al. 2002). Shrubs and herbs constitute the main part of species composition of forests. Therefore, genetic eﬀects observed in dominant species of forests might not be general for most forest species. Shrubs and herbs – especially those with low densities – may be more genetically sensitive to forest fragmentation because of their much shorter life span. A shorter life span means they pass many generations even in recently fragmented habitats and, given their low densities, they therefore experience large declines in population size even if the fragmentation is not serious. However, much fewer studies have been conducted on herbs and shrubs than on tree species. For example, populations of herbaceous Swertia perennis in small, isolated habitats had reduced genetic variability and the highest within-population inbreeding coeﬃcients (Lienert et al. 2002). In the herb, Scutellaria montana, populations that were less than 100 individuals tended to have lower proportions of polymorphic loci than that of populations more than 100 individuals (Cruzan 2001). Ardisia (Myrsinaceae) is a tropical and subtropical genus and includes about 200 species. Coral ardisia, A. crenata, native to Japan to north India, is an insect-pollinated and self-compatible evergreen subshrub (Cheon et al. 2000). In China, a variant, A. crenata var. bicolor, was identiﬁed according to the purple color of the lower side of its leaves, whereas some researchers thought it as a distinct species, i.e. A. bicolor. A. crenata var. bicolor is a small upright-growth shrub. Although outcrossing rate of A. c. var. bicolor was estimated to be about 1 based on allozyme using Ritland’s (1990) MLT program (Chen et al. 2001), bag-pollination treatments indicated that it is selfcompatible (unpublished data). This species can reproduce vegetatively via rhizome, but spreading to a short distance, usually less than 1 m (personal observations). In the present study, populations of A. c. var. bicolor in a fragmented landscape were selected to determine whether there is a relationship between population size and the level of variation and to evaluate the degree of [280]

1341 population subdivision and diﬀerentiation, using RAPD markers. Although RAPDs have some limitations – such as dominant allelic expression and occasionally low reproducibility – they have advantages in investigating genetic variation, such as random sampling in the whole genome, high levels of polymorphism, and fast and easy to perform, and have been widely used in estimating genetic variation of plant populations (Nybom and Bartish 2000; Nybom 2004).

Methods Population sampling The study sites were located in Tiantong Forest Park (TFP) and adjacent areas (Figure 1). TFP was distributed by evergreen broad-leaved forests (EBLFs) dominated by Fagaceae species, such as Castanopsis fargesii, Ca. carlesii, Ca. sclerophylla, Lithocarpus glaber, L. henryi, Cyclobalanopsis nubium, and species of Theaceae (Schima superba) and Lauraceae (Machilus thunbergii) (Song and Wang 1995). Around TFP, there were EBLFs fragments of previous continuous forests or recovered from abandoned or unmanaged plantations. These fragmented EBLFs were usually dominated by Cyclobalanopsis glauca, Cy. gilva, Ca. sclerophylla, L. glaber, Ca. carlesii, M. thunbergi. Surrounding these EBLFs, there were Cunninghamia lanceolata plantations, Phyllostachys pubescens forests, and shrubs dominated by Quercus fabra and bamboos. In TFP and adjacent areas, A. c. var. bicolor usually appears in forests of lower than 300 m above sea-level. Based on detailed surveys, 10 populations of A. c. var. bicolor were sampled (Figure 1). The estimated sizes of each population ranged from 5 to about 1000 individuals (Table 1). Leaves were collected randomly from individuals with a distance of at least 2 m between each other in medium and large populations, avoiding collecting the same clones. In small populations, as many as possible individuals were collected with a distance of at least 2 m between sampled individuals.

DNA extraction and PCR condition We isolated DNA with modiﬁed Doyle and Doyle’s (1987) procedure (Fan et al. 2004). A set of random 10-mer primers was purchased from Sagon Inc., Shanghai. After screening more than 100 arbitrary primers, 10 primers that consistently ampliﬁed clear banding patterns were chosen for further studies (Table 1). RAPD assays were performed using the conditions described by Fan et al. (2004). Samples were ampliﬁed at least two replicates and same pattern was obtained by the primers used in this study. Five ll ampliﬁcation product was separated on 1.6% agarose gel in 0.5· TBE buﬀer and visualized by [281]

1342

Figure 1. Locations of sampling sites of Ardisia crenata var. bicolor in Tiantong Forest Park and adjacent areas.

[282]

1343 Table 1. RAPD primers used in the survey of Ardisia bicolor and number of scored bands. Primer

Sequence 5¢-3¢

Number of scored bands

Primer

Sequence 5¢-3¢

Number of scored bands

S59 S1200 S1221 S1238 S1341

CTGGGGACTT GTGAACGCTC CACACCGTGT GTTGCGCAGT GTCCACCTCT

8 9 3 11 4

S1361 S2068 S2084 S2100 S2160

TCGGATCCGT CATACGGGCT CCCAAGCGAA CAAAGGCGTG CACCGACATC

10 8 4 9 10

staining with ethidium bromide and photographed under UV light with BioRAD Gel Doc2000TM.

Data analysis Each PCR product was assumed to represent a single locus and was scored for presence and absence. The resulting data matrix was analyzed using Popgene 1.31 (Yeh et al. 1999). Gene diversities (H) at population and at the species level were calculated based on Lynch and Milligan’s (1994) Taylor expansion estimate using TFPGA (Tools For Population Genetic Analyses) v1.3 (Miller 1997). Nei’s unbiased genetic identity (I) and genetic distance (D) between populations were also analysed using Popgene 1.31. Because the data were larger than the up-limit of AMOVA, coeﬃcient of gene diﬀerentiation (GST) was calculated to estimate population diﬀerentiation. Shannon diversity index P (Lewontin 1972), SI = pi log2 pi, was calculated to provide a relative estimate of the degree of variation at population and species levels using Popgene 1.31 (Yeh et al. 1999). The proportion of diversity among populations was estimated as (SIspSIpop)/SIsp, whereas SIsp and SIpop were SI at species and population level, respectively. A Mantel type matrix randomization test (Mantel 1967) was performed to evaluate the relationship between the matrix of genetic distances and the matrix of geographic distances using TFPGA (Miller 1997). Relationships between measures of within-population genetic variation and population size were analyzed using Regression methods in Microsoft Excel program.

Results The RAPD proﬁle The 10 primers used for analysis generated a total of 76 bands, among which polymorphic bands were 48 (or 63.2%) and 51 (or 67.1%) based on 95 and [283]

1344 Table 2. Patterns of genetic diversity for Ardisia bicolor populations. Population

Estimated population size

A B C D E F G H I J K L M N O P Mean

1000 1000 100 100 1000 500 5 200 5 100 50 10 100 200 300 30 294

Total

4700

Sample size

P95

P

H

SI

34 33 15 14 37 34 2 21 2 32 22 5 25 23 13 8 20

35.5% 32.9% 29.0% 30.3% 46.1% 32.9% 7.89% 30.3% 5.3% 22.4% 27.6% 15.8% 21.1% 34.2% 39.5% 19.7% 26.9%

40.8% 35.5% 30.3% 32.9% 47.4% 38.2% 7.9% 31.6% 5.3% 27.6% 32.9% 15.8% 23.7% 36.8% 40.8% 19.7% 29.2%

0.144 0.122 0.120 0.128 0.175 0.127 0.039 0.122 0.026 0.073 0.113 0.065 0.077 0.129 0.171 0.072 0.106

0.208 0.178 0.168 0.179 0.253 0.186 0.048 0.174 0.032 0.112 0.163 0.089 0.112 0.186 0.236 0.103 0.152

320

63.2%

67.1%

0.192

0.246

P95 and P are percentages of polymorphic bands based on 95 and 100% criteria, respectively; H denotes mean Nei’s gene diversity based on Nei’s (1972) unbiased estimates; SI, Shannon’s diversity index.

100% criteria, respectively (Table 2). The number of scored bands ranged from 3 for primer S1221 to 11 for primer S1238. 308 of the 320 individuals from the 16 populations were found to have a unique multilocus genotype, and six genotypes have two individuals. The individuals having the same multilocus genotypes belonged to same populations. No population-speciﬁc band was observed in the data set.

Genetic diversity Percent polymorphic RAPD loci varied from 5.3 (population I) to 46.1 % (E), based on 95% criterion, with a mean of 26.9% (Table 2). The Nei’s gene diversity ranged from 0.026 to 0.175 with a mean of 0.106 and the pooled species-level value was 0.192. The relative degree of diversity in each population as measured by Shannon’s index varied from 0.032 to 0.253 (Table 2). The mean Shannon diversity for all populations was 0.152 and the pooled species-level value was 0.246. Among the 16 populations, population E exhibited the highest level of genetic variability (P, H and SI) and population O was the next, whereas population I was the lowest (Table 2). Regression analysis indicated signiﬁcantly positive relationships between measures of within-population genetic variation (P95, H and SI) and the log of population sizes (Figure 2). [284]

1345

Figure 2. Relationships between measures of within-population genetic variation and population size in Ardisia crenata var. bicolor. P95, H and SI were the percentage of polymorphic loci at 95% criterion, expected heterozygosity and Shannon diversity index, respectively.

Genetic diﬀerentiation The coeﬃcient of genetic diﬀerentiation between populations (GST) was 0.445, indicating a high diﬀerentiation among populations. The Shannon’s index analysis partitioned 38.4% of the total variation among populations. Genetic distances (D) between populations varied from 0.018 to 0.149 (Table 3) with a mean of 0.055±0.023. The level of gene ﬂow (Nm) was estimated to be 0.312. Mantel test indicated no signiﬁcant relationship between genetic distance and spatial distance (r = 0.021, P = 0.422). [285]

1346

Table 3. Nei’s unbiased genetic identity (below diagonal) and genetic distance (above diagonal) between populations of Ardisia crenata var. bicolor.

[286]

Population

A

B

C

D

E

F

G

H

I

J

K

L

M

N

O

P

A B C D E F G H I J K L M N O P

– 0.9635 0.9646 0.9790 0.9569 0.9749 0.8965 0.9580 0.9458 0.9415 0.9661 0.9625 0.9652 0.9625 0.9435 0.9565

0.0372 – 0.9611 0.9627 0.9567 0.9530 0.9145 0.9705 0.9463 0.9477 0.9704 0.9522 0.9709 0.9756 0.9347 0.9412

0.0361 0.0397 – 0.9682 0.9507 0.9558 0.9085 0.9635 0.9532 0.9366 0.9590 0.9393 0.9547 0.9709 0.9309 0.9389

0.0212 0.0380 0.0324 – 0.9583 0.9636 0.9119 0.9613 0.9482 0.9428 0.9610 0.9614 0.9650 0.9675 0.9548 0.9484

0.0441 0.0442 0.0505 0.0426 – 0.9618 0.9144 0.9668 0.9317 0.9442 0.9540 0.9301 0.9494 0.9723 0.9717 0.9553

0.0254 0.0481 0.0452 0.0370 0.0389 – 0.9091 0.9711 0.9307 0.9467 0.9513 0.9395 0.9595 0.9555 0.9361 0.9433

0.1092 0.0893 0.0959 0.0922 0.0895 0.0953 – 0.9147 0.8909 0.9178 0.9145 0.8855 0.9206 0.9411 0.9303 0.8618

0.0429 0.0300 0.0372 0.0395 0.0338 0.0294 0.0892 – 0.9597 0.9460 0.9611 0.9346 0.9623 0.9667 0.9488 0.9665

0.0558 0.0552 0.0479 0.0532 0.0707 0.0718 0.1155 0.0411 – 0.9294 0.9446 0.9258 0.9454 0.9488 0.9274 0.9563

0.0603 0.0538 0.0655 0.0589 0.0574 0.0548 0.0858 0.0555 0.0732 – 0.9818 0.9610 0.9620 0.9609 0.9312 0.8991

0.0345 0.0300 0.0418 0.0398 0.0471 0.0499 0.0894 0.0397 0.0570 0.0184 – 0.9701 0.9714 0.9708 0.9409 0.9242

0.0383 0.0490 0.0626 0.0393 0.0725 0.0624 0.1216 0.0676 0.0771 0.0397 0.0304 – 0.9746 0.9410 0.9115 0.9018

0.0354 0.0296 0.0464 0.0356 0.0519 0.0414 0.0827 0.0385 0.0562 0.0387 0.0290 0.0257 – 0.9595 0.9273 0.9161

0.0382 0.0247 0.0296 0.0331 0.0281 0.0456 0.0608 0.0339 0.0526 0.0398 0.0296 0.0608 0.0413 – 0.9495 0.9451

0.0581 0.0676 0.0716 0.0462 0.0287 0.0660 0.0722 0.0526 0.0754 0.0713 0.0609 0.0926 0.0755 0.0518 – 0.9478

0.0445 0.0606 0.0631 0.0530 0.0457 0.0584 0.1487 0.0341 0.0447 0.1064 0.0789 0.1034 0.0876 0.0565 0.0536 –

1347 Discussion The present study reveals relative low genetic diversity in A. c. var. bicolor compared to other species based on RAPD markers. Percentage of polymorphic bands, Nei’s gene diversity and Shannon index of the pooled data were 67.1%, 0.192 and 0.246, respectively (Table 2). These values were even lower than many endangered species, Metasequoia glyptostroboides (P: 87.9%, H=0.318, SI = 0.476) (Li et al. 2005), Caesalpinia echinata (P = 95.7%) (Cardoso et al. 1998), Leucadendron elimense (P = 98.8%) (Tansley and Brown 2000), Boloria aquilonaris (H = 0.402) (Vandewoestijne and Baguette 2002), but higher than Haplostachys haplostachya (H = 0.166) (Morden and Loeﬄer 1999), Dryopteris cristata (P = 2.5%) (Landergott et al. 2001). Our results were not in accordance with the predictions based on the association of life history traits and genetic variation. According to the data of RAPDs, there were strong associations between genetic diversity and breeding system or successional status (Nybom and Bartish 2000; Nybom 2004). Outcrossing species had signiﬁcantly high genetic diversity than selfers. Higher genetic diversity was found in late- than early - successional species. Species of ingested seed dispersal also possessed relatively high genetic diversity (Nybom 2004). Given such considerations, high genetic diversity was expected based on its high outcrossing rate (Chen et al. 2001), mid to late-successional status and bird dispersal manner. Relatively low genetic diversity in the studied A. c. var. bicolor populations might be explained by their geographical positions. The studied populations are located on the eastern margin of its distribution in mainland China (Figure 1). Due to eﬀects of founder events, genetic drift and inbreeding, marginal populations usually possess relative low genetic variation, which had been conﬁrmed in diverse species (Chen et al. 1997; Tyler 2002; Cassel and Tammaru 2003). Restricted geographical range in the present study might be another explanation of the low genetic diversity. Though 10 populations were sampled, their spatial distances were small. The largest distance of pairwise populations is 4.6 km. If populations were sampled in a large range, more genetic variation might be expected. Though some studies failed to observe the distinct genetic consequences of forest fragmentation on plant populations (Ellstrand and Elam 1993; Young et al. 1996), our results indicated that habitat fragmentation had played a vital role in genetic structure of A. c. var. bicolor populations. Fragmentation led to the loss of genetic diversity. In small populations, signiﬁcantly lower diversity was observed than large and medium ones. Signiﬁcant relationship was found between estimated population size and within-population genetic variation as measured by P, H and Shannon index. Decreased genetic diversity in small populations was due to various reasons. Firstly, the instantaneous eﬀects of fragmentation (i.e., sampling eﬀects) lead to stochastic loss of rare alleles because only a small portion of the original [287]

1348 gene pool remains after the decrease. Buchert et al. (1997) had compared the genetic diversity in pre-harvest and post-harvest gene pools of two virgin stands of eastern white pine (Pinus strobus). They found total and mean number of alleles was reduced by 25% after tree density reductions of 75%. About 40% of the low frequency alleles and 80% of the rare alleles were lost because of harvesting (Buchert et al. 1997). Secondly, inbreeding and genetic drift further decreased genetic variation in small populations (Young et al. 1996). In the present study, most small populations experienced bottleneck for more than 10 generations, given a generation of 3 years and deforestation of at least 50 years. It is enough for inbreeding and drift to virtually change the genetic composition of small populations of less than 50 individuals. Thirdly, founder eﬀect might also contribute to low genetic diversity in some small populations (Frankham et al. 2002). Population G, for instance, located in dense high shrubs, had only two small individuals, indicating a recent founding event. High genetic diﬀerentiation was observed among populations of A. c. var. bicolor. GST indicated that about 44.5% of the genetic variation occurred among populations with short spatial distances. This value is higher than the RAPD-based estimates of other widespread, or animal-dispersal species (Nybom and Bartish 2000). High genetic diﬀerentiation among populations was also in accordance with theoretical prediction of fragmentation, indicating the eﬀects of bottleneck and inbreeding. No signiﬁcant relationship between genetic distance and spatial distance was found in the present study. This is usually interpreted that selection or drift plays a more signiﬁcant role than gene ﬂow. In this study, no distinct diﬀerence in habitats was found among populations, though the dominant species were diﬀerent. At local scale, populations from diﬀerent communities usually showed similar genetic composition in studied species, such as, Cyclobalanopsis glauca (Chen and Song 1998). Therefore, selection plays a minor role in the diﬀerentiation of A. c. var. bicolor populations, and drift led by fragmentation contributed to the high diﬀerentiation. Our ﬁndings in A. c. var. bicolor give a gloomy implication for forest species because most species of forests are shrubs and herbs and among them most are moderate- or low-density species. For example, there were about a dozen of species in tree layer of EBLFs; among them, usually less than 3 species dominated the community. However, the number of species in shrub and herb layers was about three to four folds of that in tree layer (Song and Wang 1995). Among them, most are moderate or low density, like A. c. var. bicolor, and are vulnerable to fragmentation. This situation is also common in tropical, temperate or boreal forests. Thus, although some studies showed no distinct eﬀects on long-lived tree species which have survived hundreds of years of fragmentation, our study indicated that distinct genetic consequences of recent fragmentation may be expected for quite a number of plant species. More attention should be paid to these species and conservation eﬀorts are needed. [288]

1349 Acknowledgements We thank Mr Ling-jian Li and Ms Xiao-xia Fan for the assistance in sample collection and preparation. We thank J. P. Sniadecki of Grand Valley State University for English improvement and helpful comments and reviewers for their critical comments and suggestions. This study was supported by Natural Science Foundation of China (39870128, 30170060), The State’s Tenth Fiveyear ‘‘211 Project’’ and Shanghai Priority Academic Discipline. References Bacles C.F.E., Lowe A.J. and Ennos R.A. 2004. Genetic eﬀects of chronic habitat fragmentation on tree species: the case of Sorbus aucuparia in a deforested Scottish landscape. Molecular Ecology 13: 573–584. Buchert G.P., Rajora O.P., Hood J.V. and Dancik B.P. 1997. Eﬀects of harvesting on genetic diversity in old-growth eastern white pine in Ontario, Canada. Conservation Biology 11: 747–758. Cardoso M.A., Provan J., Powell W., Ferreira P.C.G. and de Oliveira D.E. 1998. High genetic diﬀerentiation among remnant populations of the endangered Caesalpinia echinata Lam. (Leguminosae-Caesalpinioideae). Molecular Ecology 7: 601–608. Cassel A. and Tammaru T. 2003. Allozyme variability in central, peripheral and isolated populations of the scarce heath (Coenonympha hero: Lepidoptera, Nymphalidae); implications for conservation. Conservation Genetics 4: 83–93. Chen X.Y. 2000. Eﬀects of habitat fragmentation on genetic structure of plant populations and implications for the biodiversity conservation. Acta Ecologica Sinica 20: 884–892. Chen X.Y., Li N. and Shen L. 2001. The mating system of Ardisia crenata var. bicolor (Myrsinaceae), a subtropical understory shrub, in Tiantong National Forest Park, Zhejiang Province. Acta Phytoecologica Sinica 25: 161–165. Chen X.Y. and Song Y.C. 1998. Microgeographic diﬀerentiation in a Cyclobalanopsis glauca poplation in western Huangshan, Anhui Province. Journal of Plant Resources Environment 7: 10–14. Chen X.Y., Wang X.H. and Song Y.C. 1997. Genetic diversity and diﬀerentiation of Cyclobalanopsis glauca populations in East China. Acta Botanica Sinica 39: 149–155. Cheon C.P., Chung M.Y. and Chung M.G. 2000. Allozyme and clonal diversity in Korean populations of Ardisia japonica and Ardisia crenata (Myrsinaceae). Israel Journal of Plant Science 48: 239–245. Cruzan M. 2001. Population size and fragmentation thresholds for the maintenance of genetic diversity in the herbaceous endemic Scutellaria montana (Lamiaceae). Evolution 55: 1569–1580. Doyle J.J. and Doyle J.L. 1987. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochemical Bulletin 19: 11–15. Ellstrand N.C. and Elam D.R. 1993. Population genetic consequences of small population size: implications for plant conservation. Annual Review of Ecology and Systematics 24: 217–242. England P.R., Usher A.V., Whelan R.J. and Ayre D.J. 2002. Microsatellite diversity and genetic structure of fragmented populations of the rare, ﬁre-dependent shrub Grevillea macleayana. Molecular Ecology 11: 967–977. Fan X.X., Shen L., Zhang X., Chen X.Y. and Fu C.X. 2004. Assessing genetic diversity of Ginkgo biloba L. (Ginkgoaceae) populations from China by RAPD markers. Biochemical Genetics 42: 269–278. Frankham R., Ballou J.D. and Briscoe D.A. 2002. Introduction to Conservation Genetics. Cambridge University Press, Cambridge.

[289]

1350 Hall P., Walker S. and Bawa K. 1996. Eﬀect of forest fragmentation on genetic diversity and mating system in a tropical tree, Pithecellobium elegans. Conservation Biology 10: 757–768. Keller L.F. and Waller D.M. 2002. Inbreeding eﬀects in wild populations. Trends in Ecology and Evolution 17: 230–241. Landergott U., Holderegger R., Kozlowski G. and Schneller J. 2001. Historical bottlenecks decrease genetic diversity in natural populations of Dryopteris cristata. Heredity 87: 344–355. Lewontin R.C. 1972. The apportionment of human diversity. Evolutionary Biology 6: 381–398. Li Y.-Y., Chen X.-Y., Zhang X., Wu T.-Y., Lu H.-P. and Cai Y.-W. 2005. Genetic diﬀerences between wild and artiﬁcial populations of Metasequoia glyptostroboides Hu et Cheng (Taxodiaceae): Implications for species recovery. Conservation Biology 19: 224–231. Lienert J., Fischer M., Schneller J. and Diemer M. 2002. Isozyme variability of the wetland specialist Swertia perennis (Gentianaceae) in relation to habitat size, isolation, and plant ﬁtness. American Journal of Botany 89: 801–811. Lynch M. and Milligan B.G. 1994. Analysis of population genetic structure with RAPD markers. Molecular Ecology 3: 91–99. Mantel N. 1967. The detection of disease clustering and a generalized regression approach. Cancer Research 27: 209–220. Miller M.P. 1997. Tools for population genetic analyses (TFPGA) v1.3: A windows program for the analysis of allozyme and molecular genetic data. Department of Biological Sciences Northern Arizona University, Flagstaﬀ. Morden C.W. and Loeﬄer W. 1999. Fragmentation and genetic diﬀerentiation among subpopulations of the endangered Hawaiian mint Haplostachys haplostachya (Lamiaceae). Molecular Ecology 8: 617–625. Morris A.B., Baucom R.S. and Cruzan M.B. 2002. Stratiﬁed analysis of the soil seed bank in the cedar glade endemic Astragalus bibullatus: Evidence for historical changes in genetic structure. American Journal of Botany 89: 29–36. Nybom H. 2004. Comparison of diﬀerent nuclear DNA markers for estimating intraspeciﬁc genetic diversity in plants. Molecular Ecology 13: 1143–1155. Nybom H. and Bartish I.V. 2000. Eﬀects of life history traits and sampling strategies on genetic diversity estimates obtained with RAPD markers in plants. Perspectives in Plant Ecology, Evolution and Systematics 3/2: 93–114. Raijmann L.E.L., Van Leeuwen N.C., Kersten R., Oostermeijer J.R.B., Den Nijs H.C.M. and Menken S.B.J. 1994. Alleleic variation and outcrossing rate in relation to population size in Gentiana pneumonanthe L. Conservation Biology 8: 1014–1026. Ritland K. 1990. A series of FORTRAN computer programs for estimating plant mating systems. Journal of Heredity 81: 235–237. Saunders D.A., Hobbs R.J. and Margules C.R. 1991. Biological consequences of ecosystem fragmentation: A review. Conservation Biology 5: 18–32. Song Y.C. and Wang X.R. 1995. Vegetation and Flora of Tiantong National Forest Park, Zhejiang Province. Shanghai Scientiﬁc Documentary Press, Shanghai. Tansley S.A. and Brown C.R. 2000. RAPD variation in the rare and endangered Leucadendron elimense (Proteaceae): implications for their conservation. Biological Conservation 95: 39–48. Tyler T. 2002. Large-scale geographic patterns of genetic variation in Melica nutans, a widespread Eurasian woodland grass. Plant Syst. Evol. 236: 73–87. Van Rossum F., De Sousa S.C. and Triest L. 2004. Genetic consequences of habitat fragmentation in an agricultural landscape on the common Primula veris, and comparison with its rare congener, P. vulgaris. Conservation Genetics 5: 231–245. Vandewoestijne S. and Baguette M. 2002. The genetic structure of endangered populations in the Cranberry Fritillary, Boloria aquilonaris (Lepidoptera, Nymphalidae): RAPDs vs allozymes. Heredity 89: 439–445. Yeh F.C., Yang R.C. and Boyle T. 1999. Popgene Version 1.31: Microsoft Window-Based Freeware for Population Genetic Analysis. Department of Renewable Resources, University of Alberta, Edmonton, AB Canada.

[290]

1351 Young A., Boyle T. and Brown T. 1996. The population genetic consequences of habitat fragmentation for plants. Trends in Ecology and Evolution 11: 413–418. Young A., Merriam H.G. and Warwick S.I. 1993. The eﬀects of forest fragmentation on genetic variation in Acer saccharum Marsh. (sugar maple) populations. Heredity 71: 277–289.

[291]

Biodiversity and Conservation (2006) 15:1353–1374 DOI 10.1007/s10531-005-5394-9

Springer 2006

-1

Diversity patterns in the ﬂora of the Campo-Ma’an rain forest, Cameroon: do tree species tell it all? M.G.P. TCHOUTO1,*, W.F. DE BOER2, J.J.F.E. DE WILDE3 and L.J.G. VAN DER MAESEN3 1

Limbe Botanic Garden, BP 437 Limbe, Cameroon; 2Resource Ecology Group, Wageningen University, Bornsesteeg 69, 6708 PD Wageningen, The Netherlands; 3Biosystematics Group, Wageningen University, Generaal Foulkesweg 37, 6703 BL Wageningen, The Netherlands; *Author for correspondence (e-mail: [email protected]) Received 9 February 2004; accepted in revised form 31 March 2005

Key words: Biodiversity, Cameroon, Campo-Ma’an, Central Africa, Conservation, Endemic species, Forest refuge, Plant diversity, Tropical rain forest Abstract. This study describes diversity patterns in the ﬂora of the Campo-Ma’an rain forest, in south Cameroon. In this area, the structure and composition of the forests change progressively from the coastal forest on sandy shorelines through the lowland evergreen forest rich in Caesalpinioideae with Calpocalyx heitzii and Sacoglottis gabonensis, to the submontane forest at higher elevations and the mixed evergreen and semi-deciduous forest in the drier Ma’an area. We tested whether there is a correlation between tree species diversity and diversity of other growth forms such as shrubs, herbs, and lianas in order to understand if, in the context of African tropical rain forest, tree species diversity mirrors the diversity of other life forms or strata. Are forests that are rich in tree species also rich in other life forms? To answer this question, we analysed the family and species level ﬂoristic richness and diversity of the various growth forms and forest strata within 145 plots recorded in 6 main vegetation types. A comparison of the diversity within forest layers and within growth forms was done using General Linear Models. The results showed that tree species accounted for 46% of the total number of vascular plant species with DBH ‡1 cm, shrubs/small trees 39%, climbers 14% and herbs less than 1%. Only 22% of the diversity of shrubs and lianas could be explained by the diversity of large and medium sized trees, and less than 1% of herb diversity was explained by tree diversity. The shrub layer was by far the most species rich, with both a higher number of species per plot, and a higher Shannon diversity index, than the tree and the herb layer. More than 82% of tree species, 90% of shrubs, 78% of lianas and 70% of herbaceous species were recorded in the shrub layer. Moreover, shrubs contributed for 38% of the 114 strict and narrow endemic plant species recorded in the area, herbs 29%, trees only 20% and climbers 11%. These results indicate that the diversity of trees might not always reﬂect the overall diversity of the forest in the Campo-Ma’an area, and therefore it may not be a good indicator for the diversity of shrubs and herbaceous species. Furthermore, this suggests that biodiversity surveys based solely on large and medium sized tree species (DBH ‡10 cm) are not an adequate method for the assessment of plant diversity because other growth form such as shrubs, climbers and herbs are under-represented. Therefore, inventory design based on small plots of 0.1 ha, in which all vascular plants with DBH ‡1 cm are recorded, is a more appropriate sampling method for biodiversity assessments than surveys based solely on large and medium sized tree species.

Introduction In a large, heterogeneous and structurally complex forest ecosystem such as the Campo-Ma’an tropical rain forest, selection of the most appropriate methods [293]

1354 for the assessment of plant biodiversity is a diﬃcult matter. So far, many botanical biodiversity studies in tropical rain forest are often limited to tree species (mainly medium and large trees, or for some cases trees with DBH ‡10 cm) which are assumed to reﬂect the forest ﬂoristic composition and physical structure (Letouzey 1968; Reitsma 1988; Hart et al. 1989; Mosango 1990; Koubouana 1993; Wolter 1993; Lejoly 1995a, b; Newbery and Gartlan 1996; White 1996; Sonke´ 1998; Sonke´ and Lejoly 1998; van Valkenburg et al. 1998). Moreover, for most of these studies tree species accounted for more than 50% of the overall species composition. This traditional approach of forest inventory might not be suﬃcient for biodiversity assessment because other taxa belonging to other life forms such as shrubs, small trees, woody lianas, herbaceous climbers, herbs and epiphytic ﬂora are not or under-represented. Furthermore, it has been shown in Central and West Africa that many plant species of high conservation value such as endemic and rare species are shrub and herbaceous species (Letouzey 1968, 1985; Robbrecht 1996; Sosef 1996; Achoundong 2000; Cable and Cheek 1998). However, during the last two decades shrubs, herbs and climbers are progressively being taking into consideration during biodiversity assessment, forest dynamic and ecological studies (Gentry and Dodson 1987; Poulsen and Balslev 1991; Valencia et al. 1994; Balslev et al. 1998; Condit et al. 2000). But, there is still a gap in knowledge regarding their contributions in the overall vascular plant species diversity in tropical rain forests. Some work has been done in this respect in Iquitos, Colombia and Guyana (Gentry 1988a, b; Duivenvoorden and Lips 1995; ter Steege 2000). This study is the ﬁrst attempt to study the diversity patterns in the ﬂora of a Central African tropical rain forest, and the contribution of the diﬀerent plant layers to the total species diversity. We will analyse the diversity of the ﬂora in the Campo-Ma’an rain forest, and test whether there is a correlation between tree species diversity and diversity of other growth forms such as shrubs, herbs and lianas. This will help us to understand if, in the context of African tropical rain forest, tree species diversity tells it all.

Methods Study area The study was conducted in the Campo-Ma’an rain forest in south Cameroon. The site covers about 7700 km2 and is located between latitudes 210¢– 252¢ N and longitudes 950¢–1054¢ E. The Campo-Ma’an area is a Technical Operational Unit (TOU) that comprises a National Park, ﬁve forest management units, two agro-industrial plantations, and a multi-uses zone. Following the FAO classiﬁcation system, soils in the Campo-Ma’an area are generally classiﬁed as Ferrasols and Acrisols (Franqueville 1973; Muller 1979; van Gemerden and Hazeu 1999). They are strongly weathered, deep to very [294]

1355 deep and clayey in texture (except at the seashores and in river valleys where they are mainly sandy), acid and low in nutrients with pH (H2O) values generally around 4. The topography ranges from undulating to rolling in the lowland area, to steeply dissect in the more mountainous areas. In the Campo area, altitudes are mostly low, ranging from sea level to about 500 m. In the eastern part, which is quite mountainous, the altitude varies between 400 and 1100 m and the rolling and steep terrain brings about a more variable landscape. The area has a typical equatorial climate with two distinct dry seasons (November–March and July–mid-August) and two wet seasons (April–June and mid-August–October). The average annual rainfall generally decreases with an increasing distance from the coast, ranging from 2950 mm/year in Kribi and 2800 mm in Campo to 1670 mm in Nyabissan in the Ma’an area. The Ma’an region has signiﬁcantly less rainfall than other areas. The average annual temperature is about 25 C and there is little variation between years. The hydrography of the area shows a dense pattern with many rivers, small river basins, fast-ﬂowing creeks and rivers in rocky beds containing many rapids and small waterfalls. Generally, the area has a low population density of about 10 inhabitants per km2 and is sparsely populated (ca. 61,000 inhabitants) with most people living around Kribi, along the coast, and in agro-industrial and logging camps (ERE De´veloppement 2002; de Kam et al. 2002). Despite the low population density, there are few employment opportunities. The local people are very poor and so far rely solely on the forest resources to meet their basic needs. As a result, local pressure on the Campo-Ma’an rain forest is increasing and there are several activities that are carried out in the area with varying ecological impacts on the forest ecosystem. These activities include agriculture, logging, poaching and hunting.

Field sampling After a study of satellite images, topographic and vegetation maps, a reconnaissance trip was carried out in the study area to identify representative and homogeneous vegetation types to be sampled. Sampling sites were selected on the basis of physical and human factors such altitude, slope, rainfall, soils, the proximity to the sea, and the degree of forest use. Sampling was carried out in small plots of 0.1 ha (50 m · 20 m) at irregular intervals along a line transect from a random starting point, In total 145 plots covering 14.5 ha were established in undisturbed forests or matured secondary forests within 6 main vegetation types ranging from coastal forest, swamp, lowland evergreen forest, to submontane forest at higher elevations (800–1100 m above sea level). Twenty two (22) plots were established in coastal forest, 26 in the lowland forest rich in Caesalpinioideae, 39 in the lowland forest rich in Calpocalyx heitzii and Sacoglottis gabonensis, 39 in mixed evergreen and semi-deciduous forest, 14 in the submontane forest and 5 in swamps proportion to their area [295]

1356 coverage. Most of the plots were located in the National Park and the forest management units, which are less aﬀected by human activities. In each 0.1 ha plot, all trees, shrubs, herbs and lianas with DBH ‡1 cm were measured, recorded and identiﬁed as far as possible. For unknown species, a voucher specimen was collected. Herbaceous species and seedlings of trees, shrubs and climbers were sampled in subplots of 5 m · 5 m each that were established in the 0.1 ha plots. These subplots were not used for the analyses, the output was only used to illustrate the contribution of the ground layer and herbaceous species when all vascular plant species are included in the ﬂoristic assessment of the forest.

Data analysis The analysis focused on family and species level ﬂoristic richness within the various life forms and forest strata recorded in the 145 plots. In this study tree layer comprised all vascular plant species with DBH ‡10 cm, shrub layer (1.5 cm £ DBH < 10 cm) and herbaceous layer (1 cm £ DBH < 1.5 cm). Diversity was measured by recording the number of species and their relative abundance in the diﬀerent plots and vegetation types. This study focused on the a diversity (species richness), which is deﬁned as the number of species within a chosen area, given equal weight to each species, and the b diversity, which is the diﬀerence in species diversity between areas or communities (Magurran 1988; Kent and Coker 1992; Bisby 1995). b diversity was quantiﬁed with the Shannon diversity index (H¢) using all individuals above 1 cm DBH and all species per plot. Phytosociological parameters (relative density and relative frequency) and Shannon diversity index were calculated following Whittaker (1975), Kent and Coker (1992) and Magurran (1988). The SPSS package version 10.0 for Windows was used for statistical analyses. The Spearman’s correlation test was used to correlate the species richness and diversity between the various growth forms and forest layers. We compared species diversity within forest layers and within growth forms using a General Linear Model (GLM) followed by a Tukey Multiple Comparison test (p<0.05).

Results General patterns of species richness within forest types A total of 76360 trees, shrubs, climbers and other vascular plants with DBH ‡1 cm was recorded in 145 plots of 0.1 ha each in the various vegetation types. They belonged to 1112 species, 420 genera and 97 families. In addition, 759 species of vascular plants (herbs, hemi-epiphytes, shrubs and seedlings of tree species) belonging to 101 families and 327 genera were recorded in the subplots [296]

1357 Table 1. Summary of the number of species, number of families, number of stems/ha and Shannon diversity (H¢) recorded in each vegetation type for all vascular plants with DBH ‡ 1 cm. Vegetation types

No of No of plots species

No of No of Shannon diversity families stems/ha index (H¢)

Coastal forest (mangroves excluded) Swamps Forest rich in Caesalpinioideae Forest rich in Calpocalyx heitzii and Sacoglottis gabonensis Mixed evergreen and semi-deciduous forest Submontane

22 5 26 39

381(78–140) 293 (18–108) 468 (93–147) 416 (81–143)

69 58 68 65

6208 5798 6033 5990

4.73 4.58 5.16 4.93

39

441 (63–145) 66

5867

4.77

14

412 (79–148) 64

6912

5.14

Minimum and maximum values are given between brackets.

of 5 m · 5 m each located within the 0.1 ha plots. Overall, 1471 species of vascular plants, including ferns and fern allies belonging to 542 genera and 126 families were recorded. More than 73% of all specimens collected were identiﬁed at species level, 23% at generic level, 3% at family level and 1% unidentiﬁed. The number of stems/ha for all vascular plants ‡1 cm DBH varied from 5798 in swamps to 6912 in the submontane forest (Table 1). The number of species/ha for all vascular plants‡1 cm varied from 293 in swamps to 468 in the lowland evergreen forest rich in Caesalpinioideae. The Shannon diversity (H¢) varied from 4.58 in coastal forests to 5.16 in forests rich in Caesalpinioideae. More than 57% of the plots have above 100 species/0.1 ha and a Shannon diversity (H¢)>4 with the most diverse, and species rich plots located in the submontane forests, forests rich in Caesalpinioideae, and forests rich in Calpocalyx heitzii and Sacoglottis gabonensis.

Floristic composition and diversity within forest strata The number of stems/ha and the number of vascular plant species per plot were generally higher in the shrub layer compared to the herbaceous layer and the tree layer. The number of stems/ha (Table 2) in the shrub layer varied from 3914 (mixed evergreen and semi-deciduous forest) to 4572 (coastal forest), in the herbaceous layer from 905 (swamps) to 1963 (submontane forest), and in the tree layer from 489 (coastal forest) to 785 stems/ha (submontane forest). The number of species in the shrub layer varied from 231 species (swamps) to 413 (mixed evergreen and semi-deciduous forest), in the herbaceous layer from 99 (swamps) to 229 (Calpocalyx heitzii and Sacoglottis gabonensis forest) and in the tree layer from 100 (swamps) to 183 species (submontane forest). In terms of Shannon diversity (H¢), the shrub layer was the most diverse followed by the tree and herbaceous layers (Table 2). The Shannon diversity varied in the shrub layer from 4.39 (swamps) to 5.13 (forest rich in Caesalpinioideae), in the tree layer from 3.82 (swamps) to 4.83 (forest rich in [297]

1358 Table 2. Summary of the number of species, number of families, number of stem/ha and Shannon diversity (H¢) recorded in the tree, shrub and herbaceous layers for each vegetation types for all vascular plants with DBH ‡ 1 cm. Floristic composition

Forest types Coastal forest

[298]

Tree layer: DBH‡10 cm No. of stems/ha 489 No. of species 147 No. of families 43 Shannon diversity index (H¢) 4.62 Shrub layer: 1.5 cm £ DBH<10 cm No. of stems/ha 4572 No. of species 332 No. of families 69 Shannon diversity index (H¢) 4.63 Herb layer: 1 £ DBH<1.5 cm No. of stems/ha 1147 No. of species 190 No. of families 53 Shannon diversity index (H¢) 4.20 Total no. of stems/ha 6208 Total no of species 381 Total no of families 69 Shannon diversity index (H¢) 4.73

Swamps

Forest rich in Caesalpinioideae

Forest rich in Calpocalyx and Sacoglottis

Mixed evergreen and semi-deciduous forest

Submontane forest

741 100 37 3.82

586 181 48 4.83

603 143 45 4.26

562 181 48 4.70

785 183 44 4.75

4152 231 53 4.39

4219 399 66 5.13

4316 349 57 4.82

3914 413 65 4.93

4164 344 53 5.05

905 99 34 3.76 5798 293 58 4.58

1228 225 54 4.58 6033 468 68 5.16

1071 229 47 4.65 5990 416 65 4.93

1391 217 52 3.97 5867 441 66 4.77

1963 225 51 4.66 6912 412 64 5.14

Note that species may overlap within forest strata.

1359 Table 3. Contribution to the total species richness from the various forest strata in 6 main vegetation types. Forest types

Coastal forest Swamps Forest rich in Caesalpinioideae Forest rich in Calpocalyx heitzii and Sacoglottis gabonensis Mixed evergreen and semi-deciduous forest Submontane forest

Total no. of species

Forest strata Tree layer DBH ‡10 cm

Shrub layer 1.5 cm £ DBH <10 cm

Herbaceous layer 1 £ DBH <1.5 cm

Species

%

Species

%

Species

%

381 293 468 416

147 100 181 143

39 34 41 34

332 231 399 349

87 79 90 84

190 99 225 229

50 34 51 55

441

181

39

413

88

217

46

412

183

44

344

83

225

55

Note that some species may overlap within forest strata.

Caesalpinioideae) and in the herbaceous layer from 3.76 (swamps) to 4.66 (submontane forest). The Shannon diversity (H¢) was signiﬁcantly diﬀerent among forest layers (F2, 26.7 = 38.905, p<0.001) when correcting for differences in vegetation types, by including vegetation type as a random factor in a generalized linear model (F10, 20 = 6.605, p<0.001). A Tukey multiple comparison test showed that all layers were signiﬁcantly diﬀerent from each other (p<0.05) with the shrub layer having the highest mean value (H¢ = 3.57) and the herbaceous layer the lowest (H¢ = 2.73). Species richness was also signiﬁcantly diﬀerent among forest layers (F2, 24.2 = 151.28, p<0.001) when correcting for diﬀerences in vegetation types (GLM, with vegetation type as a random factor, F10, 20 = 4.412, p<0.01), with highest values also recorded in the shrub layer. The shrub layer generally contributed more than 80% to the total number of species recorded in each vegetation type (Tables 2 and 3), followed by the herbaceous layer (40%) and tree layer (35%). There was a signiﬁcant positive correlation between the total number of vascular plant species per plot in the tree layer and that of the shrub (F1, 143 = 24.059, R2 = 0.144, p< 0.001) and herbaceous (F1, 143 = 15.702, R2 = 0.099, p<0.001) layers. In terms of the Shannon Diversity Index, there was also a signiﬁcant positive correlation between the diversity of the tree layer and that of the shrub and to a lesser extent with that of the herbaceous layers (Figures 1 and 2).

Floristic composition and diversity by life forms Tree species richness was relatively higher than that of shrubs, lianas and herbs (Table 4). The total number of species varied from 172 species [299]

1360

Figure 1. Correlation between the Shannon diversity (H¢) of all vascular plant species recorded in the tree layer and that of the shrub/small tree layer within 145 plots of 0.1 ha each.

(swamps) to 237 (forest rich in Caesalpinioideae) for trees, 71 (swamps) to 164 (forest rich in Caesalpinioideae) for shrubs, 42 (swamps) to 63 (forest rich in Caesalpinioideae) for lianas and 4 (submontane) to 9 (mixed evergreen and semi-deciduous forest) for herbs. About 63% of the total number of tree species was recorded in the tree layer, 82% in the shrub layer and 41% in the herbaceous layer. Less than 10% of the total number of shrub/small tree species was found in the tree layer, 90% in the shrub layer and 62% in the herbaceous layer. No herbaceous species was found in the tree layer, 70% was recorded in the shrub layer and 97% in the herb layer. The contribution of herbaceous species was very low in the 0.1 ha plots since many herbaceous species do not have a DBH ‡1 cm. However, their contribution was well illustrated in the 5 m·5 m subplots where there was a considerable increase in the number of herbaceous species (Table 5), moving from 25 species (in 145 plots of 0.1 ha each) to 257 species (in 136 subplots of 25 m2 each covering 0.34 ha). Trees and shrubs were the most diverse growth forms followed by lianas and herbaceous species (Table 4). The Shannon diversity (H¢) of trees varied from 3.96 (swamps) to 4.67 (submontane forest), for shrubs from 3.32 (coastal forests) to 4.66 (submontane forest) and for herbaceous species from 0.53 (coastal forests) to 1.03 (forest rich in Calpocalyx and Sacoglottis). [300]

1361

Figure 2. Correlation between the Shannon diversity (H¢) of all vascular plant species recorded in the tree layer and that of the herbaceous layer within 145 plots of 0.1 ha each.

There was a signiﬁcant positive correlation between the number of large and medium sized tree species and that of shrubs/small trees (F1, 143 = 112.033, R2 = 0.439, p<0.001) and woody climbers (F1, 143 = 26.986, R2 = 0.159, p<0.001). There was also a signiﬁcant positive correlation between the diversity of large and medium sized trees and that of shrubs/small trees and woody climbers (Table 6; Figures 3 and 4). The correlations between the diversity/species richness of large and medium sized trees and that of the herbaceous species were not signiﬁcant (F1, 143 = 0.001, R2 = 0.00002, p = 0.975 for Shannon diversity and F1, 143 = 0.0387, R2 = 0.0003, p = 0.844 for species richness). The Shannon diversity (H¢) was signiﬁcantly diﬀerent among the various growth forms (F3, 34.6 = 151.290, p<0.001) when correcting for diﬀerences in vegetation types (GLM: F10, 30 = 2.727, p<0.01 for vegetation type included as a random factor). A Tukey multiple comparison test showed that all growth forms were signiﬁcantly diﬀerent from each other (p<0.05) with trees having the highest mean value (H¢ = 3.37) and the lowest (H¢ = 0.24) for the herbaceous species. The species richness was also signiﬁcantly diﬀerent between growth forms (GLM: F3, 33.2 = 221.889, p<0.001 for layer and F10, 30 = 2.973, p<0.01 for vegetation type included as a random factor), with similar relative diﬀerence. [301]

Growth form

[302]

Total no. of tree species Tree layer: DBH ‡ 10 cm Shrub layer: 1.5 cm £ DBH <10 cm Herb layer: 1 £ DBH <1.5 cm Shannon diversity (H¢) Total no. of shrubs/small tree species Tree layer: DBH ‡10 cm Shrub layer: 1.5 cm £ DBH <10 cm Herb layer: 1 £ DBH <1.5 cm Shannon diversity (H¢) Total no. of herbaceous species Tree layer: DBH ‡10 cm Shrub layer: 1.5 cm £ DBH <10 cm Herb layer: 1 £ DBH <1.5 cm Shannon diversity (H¢) Total no. of liana species Tree layer: DBH ‡10 cm Shrub layer: 1.5 cm £ DBH <10 cm Herb layer: 1 £ DBH <1.5 cm Shannon diversity (H¢)

Forest types Coastal Forest

Swamps

Forest rich in Caesalpinioideae

Forest rich in Calpocalyx and Sacoglottis

Mixed evergreen and semi-deciduous forest

Submontane forest

207 128 177 94 4.26 127 11 113 76 3.32 8 0 7 8 0.53 46 8 40 16 3.13

172 82 132 44 3.96 71 10 58 37 4.39 7 0 4 6 0.54 42 7 39 11 3.29

237 158 198 97 4.47 164 20 153 105 4.26 5 0 3 5 0.78 63 7 60 25 3.34

211 126 169 100 4.13 155 10 143 104 4.08 4 0 3 4 1.03 50 8 8 26 3.27

222 156 192 86 4.44 161 13 152 100 4.32 9 0 6 8 0.85 59 12 54 23 3.65

216 162 173 102 4.67 152 12 137 101 4.66 4 0 3 4 0.90 43 6 36 21 3.19

Herbaceous species include herbs, herbaceous climbers and hemi-epiphytes. Lianas include small and large woody climbers. Note that species may overlap within forest strata.

1362

Table 4. Summary of the total number of species for the various growth forms recorded in 6 main vegetation types for all vascular plants with DBH ‡1 cm.

Table 5. Summary of the number of species of the various growth forms recorded in 136 vegetative subplots of 5 m · 5 m each covering 0.34 ha. Floristic composition

[303]

Trees Shrubs/small trees Herbs Lianas Total No of species Total No of families

Forest types Coastal forest

Swamps

Forest rich in Caesalpinioideae

Forest rich in Calpocalyx and Sacoglottis

Mixed evergreen and semi-deciduous forest

Submontane forest

27 87 88 30 232 67

6 14 14 3 37 27

35 148 142 36 368 76

38 102 98 33 271 63

37 134 105 32 308 68

26 74 77 11 188 47

1363

1364 Table 6. Spearman correlation coeﬃcients between the Shannon diversity (H¢) of the various growth forms recorded for all vascular plants with DBH ‡1 cm in 145 plots of 0.1 ha each. Life forms

Large trees

Shrubs/small trees

Herbs

Lianas

Large trees Shrubs/small trees Herbs Lianas

1 0.29** 0.13 0.24**

1 0.20* 0.20*

1 0.18*

1

Spearman correlation is signiﬁcant at the 0.05 level for * and at the 0.01 level for **.

Figure 3. Correlation between the Shannon diversity (H¢) of large and medium sized tree species and that of the shrub/small tree species within 145 plots of 0.1 ha each.

Species richness within families Overall, shrubs/small trees have the highest number of families (75) followed by medium trees (61), herbs and hemi-epiphytes (58), large trees (54) and woody climbers (37). Rubiaceae was by far the most species rich family (204 species) followed by Euphorbiaceae (88), Leguminosae-Caesalpinioideae (85), Annonaceae (63), Sterculiaceae (50), Apocynaceae (47) and Sapindaceae (40). Leguminosae (especially the subfamily Caesalpinioideae) was the dominant family for the large trees species (DBH ‡30 cm) in terms of relative density and frequency in the Campo-Ma’an area (Table 7). Dominant large tree species included Calpocalyx heitzii, Desbordesia glaucescens, Erythrophleum ivorensis, Lophira alata, Lovoa trichilioides, Pycnanthus angolensis, Sacoglottis [304]

1365

Figure 4. Correlation between the Shannon diversity (H¢) of large and medium sized tree species and that of the climbers within 145 plots of 0.1 ha each.

gabonensis and Terminalia superba. Common shrubs and small tree species included many species of the genera Cola, Diospyros, Drypetes, Psychotria, and Rinorea. Common large woody climber species were from the genera Agelaea, Dichapetalum, Combretum, Millettia, and Strychnos. The most important herb species were of the genera Begonia, Culcasia, Dorstenia, Geophila, Haumania, Hymenocoleus, Mapania, Marantochloa, Microcalamus and Palisota.

Discussion General patterns of species composition and diversity within forest types The Campo-Ma’an area is dominated by the lowland evergreen rain forest rich in Caesalpinioideae and is characterized by a rich and diverse ﬂora Letouzey 1968 and 1985; Thomas and Thomas 1993; Tchouto 2004). The number of species/ha for all vascular plants ‡1 cm recorded varied from 293 in swamp forest to 468 in the lowland evergreen forest rich in Caesalpinioideae. The Shannon diversity (H¢) varied from 4.73 in coastal forests to 5.16 in forests rich in Caesalpinioideae. The explanation for the high level of species richness and diversity might stem partly from the fact that the area is part of a series of postulated rain forest refugia in Central and West Africa (Hamilton 1982; [305]

1366 Table 7. Five most important families/subfamilies recorded for the various growth forms in 145 forest plots (0.1 ha each) and the vegetative subplots. Note that species may overlap between size classes. Family/subfamily

Relative density

Canopy tree: DBH ‡30 cm (286 species and 54 families) Leguminosae-Caesalpinioideae 15.00 Olacaceae 9.72 Burseraceae 8.23 Euphorbiaceae 7.94 Myristicaceae 6.44 Medium sized trees: 10 cm £ DBH<30 cm (316 species and 61 families) Olacaceae 14.47 Leguminosae-Caesalpinioideae 13.25 Euphorbiaceae 11.19 Annonaceae 8.48 Burseraceae 5.70 Shrub/small trees: 1.5 cm £ DBH<10 cm (389 species and 75 families) Euphorbiaceae 13.60 Rubiaceae 8.50 Leguminosae-Caesalpinioideae 7.01 Olacaceae 6.33 Ebenaceae 6.07 Small and large climbers (158 species and 37 families) Dichapetalaceae 26.65 Palmae 13.48 Connaraceae 12.24 Loganiaceae 8.99 Celastraceae 8.30 Herbs and hemi-epiphytes (257species and 58 families) Araceae 20.43 Marantaceae 12.69 Gramineae 8.94 Commelinaceae 8.42 Cyperaceae 7.34

Relative frequency

9.03 8.49 6.00 6.93 5.22 3.23 2.96 3.01 2.45 1.94 3.59 3.64 3.59 3.51 3.41 12.29 8.03 11.06 8.79 8.51 11.32 10.78 8.20 8.91 7.13

White 1983; Maley 1987 and 1989; Sosef 1994). Furthermore, the CampoMa’an forest falls within the Guineo-Congolian Centre of Endemism (White 1983; Gartlan 1989; Thomas and Thomas 1993; Davis et al. 1994). It is situated in the middle of the rich Biafran forest type that extends from southeast Nigeria to Gabon and the Mayombe area in Congo (White 1983; Letouzey 1968 and 1985) and shares with these sites the overall characteristic of lowland evergreen rain forest with some semi-deciduous species. In agreement with Hubbell and Foster (1983, 1986c), many species showed no apparent distributional biases with respect to habitat boundaries. Nevertheless, some species were strongly positively or negatively associated with speciﬁc habitats such as swamps, hilltops, riverbank and disturbed forests. Species composition was inﬂuenced by rainfall, altitude, soils, the proximity of the sea, and the level of human disturbance that contributed to [306]

1367 several environmental hostilities that may have limited the inﬂux of plant species and weaken competitive abilities of poorly adapted species (Tchouto 2004). The total number of vascular plant species was relatively inﬂuenced by the proximity of the sea and rainfall, thus resulting in a gradual variation in dominant species and an increase in species richness with increasing annual rainfall and distance from the sea. There was also an increase in deciduous and semi-deciduous elements with decreasing annual rainfall. Forest at higher altitudes between 800 and 1100 m above sea level appeared to be relatively more species-rich than the disturbed lowland and the coastal forests on sandy shorelines. In the undisturbed lowland evergreen forest rich in Caesalpinioideae and the submontane forest, more than 93% of the 0.1 ha plots had above 100 species. Swamps and seasonal ﬂooded forests on hydric soils with poor drainage conditions and low nutrient concentrations were species-poor. This result is in full agreement with several studies that have shown that permanent water logging in soils is a main factor limiting vascular plant species alpha diversity in Neotropical swamps (Duivenvoorden and Lips 1995; Gartlan et al. 1986; Newbery et al. 1996; Sheil et al. 2000).

Floristic composition and diversity within forest strata In general, the diﬀerence in species composition and diversity within forest strata or life forms followed the same trend within the various plots and vegetation types, with the shrub layer being the most diverse and species-rich layer, followed by the herbaceous and tree layers respectively. The number of stems/ha, species diversity (H¢), and number of vascular plant species/ha were generally higher in the shrub layer than in the herbaceous and tree layers. This must stem partly from the fact that the shrub layer is made up of many life forms such as shrubs, small trees, young large trees, woody climbers, small herbaceous and woody climbers, tall herbs, and hemi-epiphytes, which are not found in the upper tree layer. In terms of species richness, the shrub layer generally contributes to more than 80% of the total number of species recorded in each forest type, followed by the herbaceous layer (40%), and the tree layer (35%). Except for some species-poor plots recorded in swamps and disturbed forests, this trend was noticed within most of the plots. It is worth mentioning that there was some ﬂoristic overlap between the diﬀerent forest layers, since more than 50% of the species occurred in more than one stratum. Many large tree and woody liana species were found in all the strata depending on their development stage (seedlings, juveniles and immature or mature individuals). There was a positive correlation between the diversity of the tree layer and that of the shrub layer. This is partly attributed to the fact that a high proportion of the immature large tree and liana species of the upper tree layer was also recorded in the shrub layer. [307]

1368 Floristic composition and diversity by life forms A total of 533 tree species with DBH ‡10 cm was recorded in 145 plots of 0.1 ha each, with an average of 12–50 species/0.1 ha. Most plots in the lowland evergreen forest and the submontane forest had above 35 tree species/0.1 ha. These results are comparable to that of 15–60 species/0.1 ha found by Gentry (1988b) in the tree species rich Mishana and Yanamono plots near Iquitos. Balslev et al. (1998) found 307 tree species with DBH ‡10 cm in 1 ha plots of forest in Ecuador and Condit et al. (2000) between 673 and 996 tree species in two 50-ha plots in Malaysia. In this study, shrubs and small trees were by far the most species rich growth forms, more than 756 species were recorded among treelets and shrubs with DBH £ 2.5 cm, and 793 species for treelets between 2.5
1369 sampled within the 0.1 ha plots. As a result, herbaceous species contributed less than 1% of the total vascular plant species count. However, in the 136 subplots of 5 · 5 m, there was a considerable increase in herb species, from 25 species in 145 plots of 0.1 ha to 257 species in the 5 · 5 m plots (Table 5). A stratiﬁed sampling approach, with larger plots for larger individuals (e.g. 1 ha plot for DBH ‡ 10 cm) divided into small subplots for smaller individuals (e.g. 0.1 ha for DBH ‡ 1 cm and 0.01 ha for DBH <1 cm) seems therefore the best approach to measure species richness in tropical rainforests. Tree species appeared to be more diverse than shrubs, climbers and herbs. Although there was a signiﬁcant positive correlation between the diversity of trees and that of the shrubs/small trees and woody climbers, the correlations between the diversity of trees and that of the herbaceous species were not signiﬁcant. Moreover, there was a signiﬁcant positive correlation between the diversity of shrubs/small trees and that of herbaceous species. This is partly due to the fact that most of the shrubs, small trees and herbaceous plants are understorey species that live under the same physiological and biological conditions. They are either shade bearers or non-pioneer light demanding species that require little sunlight for survival. More than 40% of the herbaceous layer species contribution came from shade hemi-epiphytes that are often restricted to the lower trunk of shrubs and small trees. Hemi-epiphytic species of the genera Culcasia and Cercestis (Araceae) and several fern genera such as Lomariopsis, Hymenophyllum and Trichomanes were very common (Table 7). It is worth mentioning that species richness and diversity was higher in undisturbed forest types than in the coastal forests where there was a pronounced human disturbance. With the exception of swamps and mangroves, the coastal forest types were ﬂoristically poorer with a lower diversity index (H¢) than other forest types (Tables 1 and 2). The degree of human activities seems to have an eﬀect on species composition and decrease species diversity within the various forest types. Plots located in secondary forests, past logging concessions and plots near forest edges were more disturbed, and characterized by a high number of herbaceous, climber and pioneer species. Furthermore, undisturbed forests with open canopy, such as the mixed evergreen and semideciduous forest in the drier Ma’an area, were also characterized by an increased number of semi-deciduous, herbaceous and climber species.

Does tree diversity tell it all? Many botanical studies in tropical rain forest emphasise the structural aspect of the forest, assuming that the diversity of large and medium sized trees (DBH ‡ 10 cm) reﬂect the overall diversity of the forest. When comparing the tree diversity and ﬂoristic composition in 6 diﬀerent forest types in the CampoMa’an area, we noticed that tree species accounted for 46% of the total vascular plant species with DBH ‡ 1 cm, shrubs/small trees 39%, climbers 14% and herbs less than 1%. Only 22% of the diversity of shrubs and lianas could [309]

1370 be explained by the diversity of large and medium sized trees, and less than 1% of herb diversity was explained by the tree diversity (Figures 3 and 4). A higher percentage of tree, shrub and climber species occurred in the shrub layer than in the tree and herbaceous layers. Moreover, only 63% of the tree species were recorded in the tree layer against 82% in the shrub layer. Less than 10% of the total number of shrub/small tree species was found in the tree layer compared to 90% in the shrub layer. Furthermore, shrubs contributed for 38% to the 114 strict and narrow endemic plant species recorded in the area, herbs 29%, trees only 20% and climbers 11% (Tchouto 2004). It is worth mentioning that, although there was a signiﬁcant positive correlation between the diversity of trees and that of shrubs and woody climbers, the correlation between tree and herb diversity was not signiﬁcant. This study also demonstrated that the shrub layer was by far the most species-rich in the diﬀerent plots and vegetation types. It was signiﬁcantly more diverse and species-rich than the tree and herbaceous layers. More than 82% of tree species, 90% of shrubs, 78% of lianas and 70% of herbaceous species were recorded in this layer. The high number of species found in this layer can be attributed to the fact that, in addition to immature large trees and woody climbers, the shrub layer comprises shrubs, small trees, tall herbs, small climbers and hemi-epiphytes which are not found in the upper tree layer. This leads to the conclusion that tree diversity does not always reﬂect the overall diversity of the forest. In addition, more than 75% of plant species of high conservation value such as endemic species are shrub and herbaceous species (Tchouto 2004). Similar studies carried out by Duivenvoorden and Lips (1995) in Colombia, and by ter Steege (2000) and van Andel (2001) in Guyana, have also shown that tree diversity is not a good indicator for the diversity of shrubs and herbs. This suggests that sampling design, based on small plots of 0.1 ha, in which all vascular plants with DBH ‡ 1 cm are recorded, is a more appropriate sampling method for biodiversity conservation purposes, than assessments based solely on large and medium sized trees. Although it requires additional eﬀort, time and ﬁnancial involvement, it provides more information on other growth forms such as shrubs, climbers and herbs that are under-represented when the sampling design only includes large and medium sized trees (DBH ‡ 10 cm). In our study, large and medium sized tree species richness showed a strong positive correlation with that of lianas, indicating that in undisturbed Central African lowland evergreen rain forests, tree species richness may predict woody climber species richness relatively well. Similar results were obtained by ter Steege (2000) in Guyana. This is partly explained by the fact that woody climbers are dependent on the presence of trees for their support. Although, large trees are reported to have a negative impact on liana density through direct competition with the lianas for light and nutrients, their composition and physiognomy, as well as the forest structure, are important factors inﬂuencing the species composition and diversity of liana (Schnitzer and Bongers 2002; Parren 2003). Considering the fact that most of the Campo-Ma’an area is [310]

1371 dominated by a lowland forest rich in large canopy and emergent tree species (up to 60 m tall) that forms a fairly continuous canopy, only large non-pioneer light-demanding climber species and small woody shade bearer climbers that are adapted to low light understorey conditions can survive in such an environment. The density and species richness of small light-demanding herbaceous and woody climbers is therefore relatively low in undisturbed forests and high at forest edges, in natural tree fall gaps, in secondary forests and in opened forest with a discontinuous canopy.

Conclusion There is a general perception among scientists that, in the tropical rain forest, the diversity of large and medium sized trees (DBH ‡ 10 cm) can be used to predict the diversity of other life forms, since, in most of these studies tree species account for more than 50% of the overall species composition. This study has demonstrated that the diversity of trees does not always reﬂect the overall diversity of forest in the Campo-Ma’an area and, therefore, it may not be a good indicator for the diversity of shrubs and herbaceous species. However it is a relatively good indicator for the diversity of lianas. In terms of ﬂoristic composition, the number of tree species can be used to some extent to predict the number of species of other growth forms. Furthermore, the shrub layer (1.5 cm £ DBH <10 cm) was by far the most species rich in the diﬀerent vegetation types sampled and appeared to be more diverse and species-rich than the tree and herbaceous layers. This suggests that sampling design, based on small plots of 0.1 ha, in which all vascular plants with DBH ‡1 cm are recorded, is a more appropriate sampling method for biodiversity conservation purposes than assessments based solely on large and medium sized trees (DBH ‡ 10 cm). Moreover, if there are enough means, time and staﬀ, a stratiﬁed sampling approach, with larger plots for larger individuals (e.g. 1 ha plot for DBH ‡ 10 cm) divided into small subplots for smaller individuals (e.g. 0.1 ha for DBH ‡ 1 cm and 0.01 ha for DBH < 1 cm) is the best.

Acknowledgements This study was carried out within the framework of the Campo-Ma’an Biodiversity Conservation and Management Project, Cameroon, and was ﬁnancially supported by Tropenbos International, The Netherlands. We thank G. Achoundong, J.M. Onana, B. Sonke, L. Zapfack and P. Mezili at the National Herbarium, Cameroon, and F.J. Breteler, and C.C.H. Jongkind at the Nationaal Herbarium Nederland, Wageningen University Branch, who assisted in plant identiﬁcation. The staﬀ of Campo-Ma’an Project is also acknowledged with gratitude for their assistance and support during the ﬁeldwork. Particular thanks are for my ﬁeld assistants Elad Maurice and [311]

1372 Ossele Mathilde for their enthusiastic support and cooperation. We also extend our sincere thanks to all chiefs and village representatives, for their active participation in the organization and collection of ﬁeld data. References Achoundong G. 2000. Les Rinorea et l’e´tude des refuges forestiers en Afrique. In: Servant M. and Servant-Vildary S. (eds), Dynamique a` long terme des e´cosyste`mes forestiers intertropicaux, pp. 19–29. Balslev H., Valencia R., Paz y Mino G., Christensen L.B. and Nielsen I. 1998. Species count of vascular plants in one hectare of humid lowland forest in Amazonian Ecuador. In: Dallmeier F. and Comiskey J.A. (eds), in Forest Biodiversity in North, Central and South America, and the Caribbean. MAB series, 21: 585–594. Bisby F.A. 1995. Characterization of biodiversity. In: Heywood V.H. and Watson R.T. (eds), Global Biodiversity Assessment. UNEP, Cambridge University Press, pp. 192–294. Cable S. and Cheek M. 1998. The plants of Mount Cameroon. A Conservation Checklist. Royal Botanic Gardens, Kew. Condit R., Ashton P.S., Baker P., Bunyavejchewin S., Gunatilleke S., Gunatilleke N., Hubbell S.P., Foster R.B., Itoh A., LaFrankie J.V., Lee S.H., Losos E., Manokaran N., Sukumar R. and Yamakura T. 2000. Spatial patterns in the distribution of tropical tree species. Science 228: 1414– 1417. Davis S.D., Heywood V.H. and Hamilton A.C. 1994. Centres of Plant Diversity. A Guide and Strategy for Their Conservation 1. de Kam M., Fines J.-P. and Akogo G. (eds) 2002. Sche´ma Directeur pour le developpement de l’Unite´ Technique Ope´rationnelle de Campo-Ma’an. Cameroun. Campo-Ma’an Series 1. Duivenvoorden J.F. and Lips J.M. 1995. A Land Ecological Study of Soils, Vegetation and Plant Diversity in Colombia Amazonia. Tropenbos Series 12The Tropenbos Foundation, Wageningen. ERE De´veloppement 2002. Etude socio-e´conomique dans l’UTO de Campo-Ma’an. Rapport ﬁnal phase 2: re´sultats d’enque`tes aupre`s des me´nages. SNV/Projet Campo-Ma’an. Franqueville A. 1973. Atlas Regional Sud-Ouest 1. Re´publique du Cameroun. ORSTOM, Yaounde´, Cameroun. Gartlan J.S. 1989. La conservation des ecosystemes forestiers du Cameroun. IUCN. Gentry A.H. 1988a. Change in plant community diversity and ﬂoristic composition on environmental and geographical gradients. Annals of the Missouri Botanical Garden 75: 1–34. Gentry A.H. 1988b. Trees species richness of upper Amazonian forests. Proceedings of the National Academy of Science USA 85: 156–159. Gentry A.H. and Dodson C. 1987. Contribution of non trees to species richness of a tropical rain forest. Biotropica 19: 149–156. Hamilton A.C. 1982. Environmental History of Africa: A Study of the Quaternary. Academic Press, London. Hart T.B., Hart J.A. and Murphy P.G. 1989. Monodominant and species-rich forests of the humid tropics: causes for their co-occurrence. The American Naturalist 133: 613–633. Hubbell S.P. and Foster R.B. 1983. Diversity of canopy trees in a neotropical forest and implications for conservation. In Sutton S.L., Whitemore T.C. and Chadwick A.C. (eds), in Forest: Ecology and Management. Blackwell Science, Oxford, pp. 24–41. Hubbell S.P. and Foster R.B. 1986c. Commonness and rarity in a neotropical forest: implications for tropical tree conservation. In: Soule M.E. (ed.), Conservation Biology: The Science of Scarcity and Diversity. Sinauer Associates, Massachusetts, pp. 205–231. Kent M. and Coker P. 1992. Vegetation Description and Analysis. Belhaven Press, London. Koubouana F. 1993. Les foreˆts de la valle´e du Niari, Congo: Etudes ﬂoristiques et structurales. The`se de doctorat, Universite´ de Paris 6.

[312]

1373 Lejoly J. 1995a. Biodiversite´ ve´ge´tale dans le Parc National d’Odzala, Congo. Rapport technique. Groupement Agreco-CTFT. Lejoly J. 1995b. Utilisation de la me´thode de transects en vue de l’e´tude de la biodiversite´ dans la zone de conservation de la foreˆt de Ngotto, Re´publique Centrafricaine. Rapport technique. Projet ECOFAC, Agreco-CTFT. Letouzey R. 1968. Etude phytoge´ographique du Cameroun. Le Chevalier, Paris. Letouzey R. 1985. Notice de la carte phytoge´ographique du Cameroun, vol. 1–5. Institut de la Carte Internationale de la Ve´ge´tation, Toulouse. Magurran A.E. 1988. Ecological Diversity and its Measurement. Croom Helm, London. Maley J. 1987. Fragmentation de la foreˆt dense humide Africaine et extention des biotopes montagnards du Quaternaire recent. Paleoecology of Africa 18: 307–309. Maley J. 1989. Late Quaternary climatic changes in the African rainforest: the question of forest refuges and the major role of sea surface temperature variations. In: Lewen M. and Sarthein M. (eds), Paleoclimatology and Paleometeology: Modern and Past Patterns of Global Atmospheric Transport. Kluwer, Londonmeteo, pp. 585–616. Mosango M. 1990. Contribution a` l’e´tude botanique et bioge´ochimique de l’e´cosyste`me des foreˆts en re´gion e´quatoriale (Ile Kongolo, Zaire). The`se de doctorat, Universite´ Libre de Bruxelles. Muller J.P. 1979. Carte des sols du Cameroun. Atlas de la Re´publique Unie du Cameroun. Nabe-Nielson J. 2001. Diversity and distribution of lianas in a neotropical rain forest, Yasuni National Park, Ecuador. Journal of Tropical Ecology 17: 1–19. Newbery D. Mc and Gartlan J.S. 1996. A Structural Analysis of Rainforest at Korup and DoualaEdea, Cameroon. Proceedings of the Royal Society of Edinburg 104B: 177–224. Parren M.P.E 2003. Lianas and logging in West Africa. Tropenbos-Cameroon Series 6. PhD Thesis, Wageningen University, The Netherlands. Poulsen A.D. and Balslev H. 1991. Abundance and cover of ground herbs in an Amazonian rain forest. Journal of Vegetation Science 2: 315–322. Putz F.E and Chai P. 1987. Ecological studies of lianas in Lambir National Park, Sarawak, Malaysia. Journal of Ecology 75: 523–531. Reitsma J.M. 1988. Forest vegetation in Gabon. Tropenbos Technical Series 1. Robbrecht E. 1996. Geography of African Rubiaceae with reference to glacial rain forest refuges. In: van der Maesen L.J.G., vander Burgt X.M. and van Medenbach de Rooy J.M. (eds), The Biodiversity of African Plants. Kluwer Academic Publishers, Wageningen, pp. 564–581. Rollet B. 1974. La re´ge´ne´ration naturelle dans les troue´es Un processus ge´ne´ral de la dynamique des foreˆts tropicales humides. Revue Bois et Foreˆts des Tropiques 201: 3–34. Schnitzer S.A. and Bongers F. 2002. The ecology of lianas and their role in forests. Trend in Ecology and Evolution 17: 223–230. Sheil D., Jennings S. and Savill P. 2000. Long-term permanent plot observations of vegetation dynamic in Budongo, a Ugandan rain forest. Journal of Tropical Ecology 16: 765–800. Sonke´ B. 1998. Etudes ﬂoristiques et structurales des foreˆts de la Reserve de Faune de Dja, Cameroun. The`se pre´sente´e en vue de l’obtention du grade de Docteur en sciences, option e´cologie ve´ge´tale. Universite´ Libre de Bruxelles. Sonke´ B. and Lejoly J. 1998. Biodiversity study in the Dja Fauna Reserve (Cameroon): using the transect method. In: Huxley C.R., Lock J.M. and Cutler D.F. (eds), Chorology, Taxonomy and Ecology of the Floras of Africa and Madagascar. Royal Botanical Gardens, Kew, pp. 171–179. Sosef M.S.M. 1994. Refuge Begonias. Taxonomy, phylogeny and historical biogeography of Begonia sect. Loasibegonia and sect. Scutobegonia in relation to glacial rain forest refuges in Africa, PhD Thesis, Wageningen Agricultural University. Sosef M.S.M. 1996. Begonias and African rain forest refuges: general aspects and recent progress. In: van der Maesen, L.J.G., van der Burgt X.M. and van Medenbach de Rooy J.M. (eds), The Biodiversity of African Plants. Kluwer Academic Publishers, Wageningen, pp. 602–611. Tchouto M.G.P. 2004. Plant diversity in a Central African rain forest: implications for biodiversity conservation in Cameroon. PhD Thesis, Wageningen University.

[313]

1374 ter Steege H. 2000. Plant diversity in Guyana, with recommendations for a National Protected area strategy. Tropenbos Series 18. Valencia R., Balslev H. and Pazy Mino G. 1994. High tree alpha-diversity in Amazonian Ecuador. Biodiversity and Conservation 3: 21–28. van Andel T. 2001. Floristic composition and diversity of mixed primary and secondary forests in northwest Guyana. Biodiversity and Conservation 10: 1645–1682. van Gemerden B.S. and Hazeu G.W. 1999. Landscape ecological survey (1:100,000) of the BipindiAkom II-Lolodorf region, Southwest Cameroon. Tropenbos-Cameroon Document 1. van Valkenburg J.L.C.H., Ketner P. and Wilks C.M. 1998. A ﬂoristic inventory and preliminary vegetation classiﬁcation of the mixed semi-evergreen rain forest in the Minke´be´ region, North East Gabon. Adansonia 20: 139–162. White F. 1983. The Vegetation of Africa. UNESCO, Paris. White L.J.T. 1996. Determinants of vegetation composition in the Lope´ Reserve. Report to AGRECO/CTFT, Gabon. Whittaker R.J. 1975. Communities and Ecosystems, 2nd ed.. Macmillan, London. Wolter F. 1993. Etude des possibilite´s techniques, e´conomiques et ﬁnancie`res d’un ame´nagement des foreˆts tropicales denses humides de la cuvette centrale du Zaı¨ re, base´e sur ses capacite´s naturelles. The`se de doctorat. Universite´ de Louvain.

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Biodiversity and Conservation (2006) 15:1375–1397 DOI 10.1007/s10531-005-5397-6

Springer 2006

-1

Impacts of selective logging and agricultural clearing on forest structure, ﬂoristic composition and diversity, and timber tree regeneration in the Ituri Forest, Democratic Republic of Congo JEAN-REMY MAKANA1,2 and SEAN C. THOMAS1,* 1

University of Toronto, Faculty of Forestry, 33 Willcocks Street, Toronto, ON M5S 3B3, Canada; Centre de Formation et de Recherche en Conservation Forestie`re (CEFRECOF), Epulu, Eastern Province, Democratic Republic of Congo; *Author for correspondence (e-mail: sc.thomas@utoronto. ca; phone: 416-978-1044; fax: 416-978-3834) 2

Received 16 June 2004; accepted in revised form 5 April 2005

Key words: Forest composition, Ituri Forest, Secondary forest, Selective logging, Shifting cultivation, Timber tree regeneration, Tree diversity Abstract. Mature tropical forests at agricultural frontiers are of global conservation concern as the leading edge of global deforestation. In the Ituri Forest of DRC, as in other tropical forest areas, road creation associated with selective logging results in spontaneous human colonization, leading to the clearing of mature forest for agricultural purposes. Following 1–3 years of cultivation, farmlands are left fallow for periods that may exceed 20 years, resulting in extensive secondary forest areas impacted by both selective logging and swidden agriculture. In this study, we assessed forest structure, tree species composition and diversity and the regeneration of timber trees in secondary forest stands (5–10 and 40 years old), selectively logged forest stands, and undisturbed forests at two sites in the Ituri region. Stem density was lower in old secondary forests ( 40 years old) than in either young secondary or mature forests. Overall tree diversity did not signiﬁcantly diﬀer between forest types, but the diversity of trees ‡10 cm dbh was substantially lower in young secondary forest stands than in old secondary or mature forests. The species composition of secondary forests diﬀered from that of mature forests, with the dominant Caesalpinoid legume species of mature forests poorly represented in secondary forests. However, in spite of prior logging, the regeneration of high value timber trees such as African mahoganies (Khaya anthotheca and Entandrophragma spp.) was at least 10 times greater in young secondary forests than in mature forests. We argue that, if properly managed and protected, secondary forests, even those impacted by both selective logging and small-scale shifting agriculture, may have high potential conservation and economic value. Abbreviations: CEFRECOF – Centre de Formation et de Recherche en Conservation Forestie`re; CTFS – Center for Tropical Forest Science; DRC – Democratic Republic of Congo; ENRA – Enzyme Reﬁners Association; ITTO – International Tropical Timber Organization; NSERC – Natural Sciences and Engineering Research Council of Canada

Introduction The intrusion of human populations into primary forest areas that were previously free of anthropogenic disturbance is becoming increasingly [315]

1376 common in all major blocks of remaining tropical forest (Witte 1992; Verissimo et al. 1995; Coomes et al. 2000; Kammesheidt 2002). Selective logging of high value timber species is generally the ﬁrst stage of this process. Shifting cultivators in search of available land use roads constructed for logging operations to penetrate deep into the forest interior and clear the forest for agricultural purposes (Witte 1992; Laurance 2001). Not all farmers are traditional shifting cultivators who are familiar with the fallow systems used to restore soil fertility and protect some of the original biodiversity. The combined eﬀects of selective logging and unsustainable farming practices in agricultural frontiers are expected to result in considerable loss of biodiversity and degradation of timber resources. The Congo basin, in Central Africa, contains the second largest block of undisturbed, continuous tropical rain forests after the Amazon. Until recently, commercial logging was not causing excessive degradation in the region, but is considered a major threat as an increasing number of transnational logging companies seek to operate in the Congo basin (Wolﬁre et al. 1998). Valuable timber trees are generally present at low density in the natural forests of Central Africa and rates of extraction rarely exceed 2 trees ha1 (White 1994; Malcolm and Ray 2000; Hall et al. 2003). Although such selective logging may be relatively ecologically benign (Wilkie et al. 1992; White 1994; Hall et al. 2003), the ecological and biological complexity of the forest may be profoundly disrupted if the forest is logged repeatedly (Panayotou and Ashton 1992), or if oﬀtake rates are high enough and logged areas serve as foci for elephant disturbance (Struhsaker 1997; Struhsaker et al. 1996). In addition, the highly selective character of such timber harvesting practices can lead to severe depletion and may eventually result in the local extinction of some high value tree species. A much greater potential impact than the direct biological and environmental damage of selective logging, however, is the opening of mature forest areas for colonization (Verissimo et al. 1995; Johns 1997; Whitmore 1999; Laurance 1999, 2001). Logging companies construct new roads in forest areas that were previously inaccessible, thereby facilitating spontaneous colonization of logged forests by agricultural colonists (Wilkie et al. 2000; Mittelman 2001). The existence of a road network facilitates entry into the forest and increases potential agricultural economic returns because of increased opportunities to transport agricultural product surpluses to local and regional markets (Southgate et al. 1991). The consequences of increases in these returns may include a substantial increase in farm sizes and shortening of the fallow period, eventually leading to large scale and severe destruction of natural forest areas. Although this pattern is widely recognized as a central conservation concern in tropical rain forests, very little data are available on the actual impacts of selective logging and subsequent swidden agriculture on forest structure, species composition and diversity, and timber tree regeneration in Central Africa. Studies in the Neotropics suggest that land use type and intensity are important factors determining [316]

1377 the regrowth of woody vegetation on cleared areas (Aide et al. 1995; Guariguata and Ostertag 2001). In lightly used areas, secondary forests regrown from abandoned farms rapidly recover structural characteristics and tree diversity similar to old-growth stands. Where land use is intense, such as in grazed pastures, forest recovery is seriously impeded by the presence of grasses and other herbaceous species that inhibit the establishment of woody vegetation (Guariguata et al. 1997; Smith et al. 1999; Zahawi and Augspurger 1999; Kennard 2002). This study reports on the impacts of logging and subsequent forest clearing on forest regeneration, structure and composition in the Ituri region, northeastern Congo basin. The history of mechanized timber harvesting in the region dates back to the early 1980s, when a 52,000 ha logging concession was awarded to ENRA in 1982. Due to the collapse of local markets in the early 1990s, logging is very selective with only very large trees of highly valuable species being extracted for export. Milicia excelsa (Welw.) C. Berg. (Moraceae) and ﬁve species of African mahogany (Khaya anthotheca (Welw.) C. DC, Entandrophragma angolense (Welw.) C. DC, E. cylindricum (Sprague) Sprague, E. candollei Harms, and E. utile (Dawe and Sprague) Sprague) accounted for 87% of total volume harvested in 1999 (R. Ducarme, personal communication). High human population density in the neighboring eastern savanna regions leads to immigration of landless farmers, who take advantage of logging roads to enter the primary forest areas where land is plentiful and cheap (Witte 1992). The activities of colonists have resulted in extensive degradation of the natural forest and its conversion to farmlands. The landscape in logged forests in the Ituri region is thus dominated by regenerating secondary forest of varying ages, intermingled with patches of mature forests, active farmlands and isolated human settlements. Disturbed and fragmented tropical forests have been increasingly recognized as being important economically, socially, and for biodiversity conservation, especially in light of the destruction of the original primary forests (Lugo 1995; Cannon et al. 1998; Fredericksen 1998; Kammesheidt 2002). The aim of this study is to compare forest structure and composition and the regeneration of major timber trees, particularly African mahoganies, between secondary forests regrown after slash-and-burn agriculture in selectively logged forests and undisturbed mature forest stands in the Ituri Forest. The combined eﬀects of selective logging and forest clearing for agriculture in one of our study sites can be expected to result in secondary forests having low species diversity and reduced major timber tree regeneration. The speciﬁc hypotheses tested here are (1) secondary forests impacted by both selective logging and agriculture will have lower tree diversity than mature forests, (2) species composition of secondary forests will favor fast growing early successional species; however, (3) those species that are economically important, such as African mahoganies, will show reduced abundance in secondary forests as a result of prior selective logging.

[317]

1378 Study sites The study was conducted at two sites in the Ituri Forest, in the northeastern part of the Congo basin forest block (Democratic Republic of Congo, DRC). The ﬁrst site (Mandumbi) was a 17 years old logging concession located 25 km northwest of the town of Beni (045¢ N latitude, 2915¢ E longitude), whereas a second site was located at Epulu, in the 1,350,000 ha Okapi Wildlife Reserve. Field investigation at this site was carried out within the 5 km2 Lenda Study Area (LSA, 119¢ N and 2838¢ E) established by CEFRECOF. The elevation in the region from varies 750 m to 950 m above sea level. Mean annual rainfall in Beni is 1639 mm and 1725 mm in Epulu. A dry season occurs from December to February, during which monthly average rainfall is less than 100 mm. May and October are the wettest months of the year, with average precipitations of 186 mm and 200 mm, respectively. Annual average daily temperature at both sites is 23–25.5 C and varies little through the year (Figure 1). The vegetation in the region is a mixture of evergreen forest, including extensive areas of ‘‘mbau forest’’ dominated by Gilbertiodendron dewevrei (De Wild.) J. Le´onard, and ‘‘mixed forests’’ in which no species is predominant, but other Caesalpinoid legumes, such asJulbernardia seretii (De Wild.) Troupin and Cynometra alexandri C.H. Wright, are abundant (Makana et al. 2004). At the eastern edge of the region, evergreen forests grade into a semi-deciduous forest whose canopy is dominated by light-demanding tree species that include Entandrophragma spp. (Meliaceae), K. anthotheca (Meliaceae), Albizia spp. (Mimosaceae) andCanarium schweinfurthii Engl. (Burseraceae). Evergreen mixed forest is the main vegetation type in Epulu, while semi-deciduous forest prevails at the Mandumbi site. Large-scale human activities at the Mandumbi site have resulted in extensive areas of active crop ﬁelds and secondary vegetation of various ages. Secondary forests were generally young, less than 10 years old, and were dominated by the early pioneer tree Musanga cecropioides R. Br. There was also an old secondary forest created by shifting agriculture ﬁelds abandoned in the 1960s at the Epulu site. However, no selective logging took place prior to forest clearing at this site. Soils at both sites are derived from granitic or alluvial rocks and fall under the order Oxisols, which dominates most of the Congo basin rain forest block in central Africa. Their texture ranges from loamy sand to sandy clay. The soils are very acidic, with mean pH values at 20 cm averaging 4 in Epulu, and low in available nitrogen and phosphorus. Mean soil sand content at LSA is 70% (Hart 1985). Logging activities in the Ituri region are concentrated in the relatively drier semi-deciduous forests near the transition between closed canopy forest and eastern savanna woodlands, likely due to the proximity of export routes to the Indian Ocean through Uganda and Rwanda. The forests at the savanna margin are also richer in high-value timber trees such as African mahoganies and Milicia excelsa than moist evergreen forests found in central and western Ituri (Makana 2004). [318]

1379

Figure 1. Climatic data of the two study sites, Epulu and Mandumbi. Data for Mandumbi came from a weather station in the town of Beni. Mean annual rainfall and mean average daily temperature are given at the top corners of each graph.

Methods Vegetation sampling Censuses were conducted in regenerating secondary forests and in mature forests at both Mandumbi and Epulu in nested plots. In Epulu, plots were located every 50 m along a 500-m long transect in each forest type. Transects from the [319]

1380 two forest types were parallel and 150 m apart. In Mandumbi, where small farms are intermingled with patches of mature forest fragments, plot location was dependent on the availability of appropriate secondary forest stands (e.g. secondary forests of 5–10 years old). Plots were spatially interspersed across forest patches, with a minimum distance of 50 m between any two adjacent plots. At both sites, secondary forest plots were located at least 20 m away from the adjacent mature forest edge. All free-standing trees ‡1 cm dbh (diameter at breast height) were identiﬁed and measured for dbh in 5 m · 5 m plots. Trees ‡10 cm dbh were identiﬁed and measured in 10 m · 10 m plots extending from each 5 m·5 m plot. For the most common tree species identiﬁcations were made directly in the ﬁeld. When deﬁnitive ﬁeld identiﬁcation was not possible leaf samples were collected and compared to voucher specimens at CEFRECOF’s herbarium in Epulu. Species names follow Lebrun and Stork (1997). In addition to botanical data, environmental information was collected at each plot. This information included soil texture, herbaceous cover, exposed mineral soil and litter depth. Soil texture was assessed according to the ﬁnger assessment of soil texture of the Ontario Institute of Pedology (1985). For the purposes of this study, soil texture was classiﬁed only in three major categories: sandy, loamy and clay soils. Herbaceous cover and the proportion of surface area made of exposed mineral soil were visually estimated and recorded as a percent of total area. Litter depth was measured by inserting a knife through the litter until it reached mineral soil, then the thickness of the litter and organic matter layer was determined to the nearest half centimeter by measuring the length of the portion of the knife that was inserted into the litter. A total of 54 plots were inventoried; 32 were at the Mandumbi site and 22 at the Epulu site. Seedling demography The regeneration of timber trees was assessed in each of the 54 vegetation plots described above. Seedlings (30 cm height to 0.9 cm dbh) were identiﬁed, tagged and measured for total aboveground height and collar diameter in 5 m · 5 m plots. Saplings (1–9.9 cm dbh) were identiﬁed and measured for dbh in 10 m · 10 m. Diameter and height were taken at two diﬀerent times to assess growth. The ﬁrst measurements were done in 2000–2001 and the second ones took place in August–October 2002. Diameter was measured to the nearest 0.01 mm using an electronic caliper for seedlings and trees <4 cm dbh or to the nearest millimeter for individuals ‡4 cm dbh, whereas height was measured to the nearest cm using a graduated stick. Stem diameter of seedlings was measured at 10 cm from the ground. Data analysis For each plot, which was the experimental unit of this study, the total number of individuals, the number of species and Shannon-Wiener diversity index were [320]

1381 calculated for seedlings, saplings, trees ‡1 cm dbh, and trees ‡10 cm dbh. Seedling abundance was log-transformed before the analysis to homogenize variance and produce approximately normal residuals (Sokal and Rolhf 1981). ANOVA was used to assess the eﬀects of site, forest type and their interaction on tree and seedling abundance and diversity. If a signiﬁcant interaction was found, the means of site by forest type combinations were compared by a Tukey-Kramer test. Analysis of covariance served to assess the eﬀects of forest type on the relationship between light availability and seedling relative growth rates. Multivariate analysis was used to explore the variation of ﬂoristic composition across sites and forest types. Detrended correspondence analysis (DCA) was utilized because an arch eﬀect was observed for correspondence analysis (ter Braak 1995). Logistic regression was utilized to compare the abundance of seedlings and saplings of individual timber tree species in secondary and primary forest plots. The number of seedlings/saplings per plot was transformed into three categories: 0 for no seedling recorded, 1 for 1–4 seedlings, and 2 for >5 seedlings.

Results Vegetation structure The density of trees ‡1 cm dbh and ‡10 cm dbh diﬀered signiﬁcantly between the two study sites, Mandumbi and Epulu (Table 1). On average, Mandumbi had higher tree density than Epulu for both dbh cut-oﬀs. There was a marginally signiﬁcant eﬀect of forest type on the density of trees ‡1 cm dbh (F1,50 = 2.5, p = 0.094). In Epulu, primary forest had signiﬁcantly more stems than secondary forest, whereas the density of trees ‡1 cm dbh was only slightly higher in primary forest compared to secondary forest in Mandumbi. Basal area was signiﬁcantly higher in secondary than in primary forests for both dbh cut-oﬀs (Table 1). Higher basal area in secondary forests was in the most part due to the presence of fast growing pioneer species. The early successional and short-lived Musanga cecropioides was very common in the secondary forest of Mandumbi and it represented 55% of total basal area. Some of the basal area in secondary forest stands was also accounted for by remnant trees. In Epulu, long-lived early colonizers such as Albizia sp., Petersianthus macrocarpus (P. Beauv.) Liben, and Alstonia boonei De Wild. made up most of basal area in secondary forest plots. The number of stems decreased rapidly with increasing tree size (Figure 2). Trees <10 cm dbh represented >80% of the total number of stems in each forest type at both study sites. Although primary forest sites in Epulu had more trees ‡10 cm dbh than secondary forest, the overall size distribution was similar between the two forest types (v2 = 4.5, d.f. = 2, p = 0.210). In Mandumbi, the size distribution was signiﬁcantly diﬀerent between the two forest types (v2 = 16.3, d.f. = 2, p<0.001); small trees (<20 cm dbh) were more abun[321]

1382 Table 1. Structural characteristics and diversity of mature logged and undisturbed, and secondary forest stands in northeastern Congo basin. Values of stem density are averages per hectare, and were calculated on the basis of 5 m · 5 m subplots. Species richness and Shannon’s diversity index were calculated for 5 m · 5 m quadrats for trees ‡1 cm dbh and for 10 m · 10 m quadrats for trees ‡10 cm dbh. Figures are least squares means and standard errors1. Epulu PF3 (n = 11)

[322]

Trees ‡1 cm dbh 6473(678)a Stem density (ha1) 26.82 (5.75)a Basal area (m2 ha1) Richness 10.9 (0.89) Shannon’s index 2.0 (0.14) ab Trees ‡10 cm dbh 427 (62)a Stem density (ha1) 22.63 (6.32)a Basal area (m2 ha1) Richness 3.3 (0.41)a Shannon’s index 1.1 (0.12)ab Environmental characteristics Herb cover (%) 11.1 (3.97)a Litter depth (cm) 1.2 (0.14)a 1

Signiﬁcance2

Mandumbi SF (n = 11)

PF (n = 16)

SF (n = 16)

4509 (678)b 44.92 (5.75)b 11.5 (0.96) 1.9 (0.14)a

7571 (601)a 28.17 (4.93)ab 12.9 (0.86) 2.3 (0.13)ab

7343 (601)a 39.16 (4.93)b 12.3 (0.76) 2.3 (0.11)b

356 (62)a 41.94 (6.32)b 3.2 (0.48)a 1.0 (0.16)ab

636 (55)b 26.49 (5.60)ac 4.67 (0.77)a 1.6 (0.14)a

35.5 (4.64)b 0.9 (0.12)a

15.4 (5.81)a 2.7 (0.37)b

Site

FT

Site*FT

0.004 0.683 0.072 0.007

0.094 0.009 0.683 0.955

0.182 0.510 0.796 0.440

721 (55)b 35.40 (5.41)ab 1.9 (0.41)b 0.8 (0.18)b

<0.001 0.955 0.010 0.450

0.912 0.014 0.001 0.010

0.181 0.482 <0.001 0.027

16.5 (6.0)ab 3.8 (0.86)b

0.164 <0.001

0.014 0.612

0.047 0.167

Means with common subscripts are not signiﬁcantly diﬀerent according to Tukey’s multiple comparison test (a = 0.05). Abundance was included as explanatory variable for ‘‘richness’’ to remove the eﬀects of tree density on species richness. 3 Forest type codes: PF for primary forest and SF for secondary forest. The primary forest at Mandumbi was disturbed by logging and tree harvesting for construction; it is undisturbed at Epulu. The secondary forest stands at Mandumbi were young (<10 years old), but those at Epulu were much older ( 40 years old). 2

1383

Figure 2. Whole-forest diameter distribution in 10 cm dbh intervals for (a) Epulu primary forest, (b) Mandumbi primary forest, (c) Epulu secondary forest, and (d) Mandumbi secondary forest.

dant in primary forest, whereas secondary forest had more intermediate-sized trees (20–39 cm dbh) than primary forest stands. At both sites, understory and shade tolerant trees constituted the majority of trees in primary forest stands (Figure 2a and b), whereas light demanders and pioneers were dominant in secondary forests (Figure 2c and d). Herbaceous cover varied signiﬁcantly with respect to forest type (F1,50 = 6.6, p = 0.014). At both sites, herbaceous vegetation was more abundant in secondary forest than in primary forest, and it was dominated by species of the family Maranthaceae and Zingiberaceae. The litter layer was at least twice as thick in Mandumbi as in Epulu (F1, 50 = 33.3, p<0.001) but it did not vary signiﬁcantly with respect to forest disturbance. No signiﬁcant diﬀerences were observed in soil texture or percent of ground area in exposed mineral soil. At both sites, soil texture ranged from sandy to clay. Small areas of exposed mineral soil were recorded in seven plots, representing 0.17% of the total area sampled.

Species composition and diversity A total of 159 species were recorded in the census plots, of which 121 taxa were identiﬁed to the species level, 17 to genus, 17 to family, and the remaining four [323]

1384 were unidentiﬁed. Overall, Mandumbi plots had 122 species, while 82 species were represented in Epulu plots. Species richness and Shannon’s diversity index showed diﬀerent patterns relative to tree sizes (Table 1). For trees ‡1 cm, mean number of species per plot was similar in the two sites and forest types; however, the value of Shannon’s index was signiﬁcantly higher in Mandumbi than in Epulu (F1,50 = 8.1, p = 0.007). In contrast, species richness of trees ‡10 cm dbh varied signiﬁcantly according to both site and forest disturbance, while Shannon’s index was only aﬀected by forest disturbance. There were signiﬁcant interactions in both diversity measures between site and forest type. In Epulu, both the mean number of species per plot and the mean value of Shannon’s index were similar for primary and secondary forests. In contrast, there was a signiﬁcant diﬀerence for both parameters between the two forest types in Mandumbi. The young secondary forest at the latter site was much less diverse than primary forest for trees ‡10 cm dbh (Table 1). Among the four combinations of site and forest type, richness and Shannon’s diversity index of trees ‡10 cm dbh were highest for the primary forest of Mandumbi and lowest for the young secondary forest of the same site. The species accumulation curves in Figure 3 are far from asymptotic, indicating that the area sampled was too small to estimate the total number

Figure 3. Species-area relationships for (a) all trees ‡1 cm dbh and (c) trees ‡10 cm dbh. Species– individual curves for (b) all trees above 1 cm dbh and (d) trees ‡10 cm dbh. EP = Epulu and MN = Mandumbi, PF = primary forest and SF = secondary forest. [324]

1385

Figure 4. Axes 1 and 2 from a detrended correspondence analysis on tree species represented by at least 8 individuals in the plots: (a) plot scores (triangles represent Mandumbi site and circles Epulu site, ﬁlled symbols are for primary forest plots and open symbols for secondary forest sites) and (b) species scores (symbols with circles represent commercial timber species). Species codes as in Table 2.

of species in the studied communities. At each site, species–area curves were similar between primary and secondary forests for trees ‡1 cm dbh. The rate of species accumulation was diﬀerent between primary and secondary forests in Mandumbi for trees ‡10 cm dbh, while it was quite similar between the two forest types in Epulu (Figure 3c and d). In Mandumbi, the rate of [325]

1386 species accumulation for trees ‡10 cm dbh was much higher in primary forest than in secondary forest.

Variation in tree species composition The two sites and forest types shared most of their common species (Table 2). Overall, Epulu and Mandumbi shared 14 of their 20 most abundant species, while primary and secondary forests had 18 of their top 20 species in common at each site. In spite of sharing the majority of the most common species, there was no signiﬁcant positive correlation of ranked abundances of these species between sites or forest types. Epulu and Mandumbi showed a signiﬁcant negative correlation among abundance ranks (Spearman’s rS = 0.549, p = 0.012), as did primary and secondary forests (rS = 0.739, p<0.001). The most abundant species in Epulu, Scaphopetalum dewevrei Wildem. and Th. Dur., was totally absent from Mandumbi plots. Moreover, two of the most common species in the latter site (Musanga cecropioides and Rinorea oblongifolia Marquand) were not represented in Epulu plots. In addition, two species of African mahogany (E. utile and K. anthotheca) were much more abundant in Mandumbi than in Epulu (Table 2). Pair-wise comparisons of species abundances for site-forest type combinations showed that the young secondary forest of Mandumbi had signiﬁcant negative correlation with primary forests of both sites (rs = 0.743, p<0.001 and rs = 0.797, p<0.001 for Mandumbi and Epulu respectively). No signiﬁcant correlation was found between the old secondary forest of Epulu and the primary forest of either site. Thus, the composition of the young secondary forest in Mandumbi was signiﬁcantly diﬀerent from that of primary forests at both sites, while that of the old secondary forest at Epulu was not. The patterns of variation in ﬂoristic composition observed from correlation analysis were corroborated by the results of multivariate analysis. The ﬁrst axis of a detrended correspondence analysis (DCA), which explained 12.9% of the total variation in the species data, appeared to be related to the composition of canopy ﬂora and it separated primary and secondary forests at each site. For each site, secondary forests had higher scores of axis 1 than primary forests. The separation between primary and secondary forests on axis 1 was more distinct for Mandumbi than Epulu forests (Figure 4a). The second axis (7.6% of the total variation) also distinguished between primary and secondary forests of each site, but seemed to be more related to the composition of understory vegetation. Primary forests had higher scores than secondary forests on the second DCA axis. Primary forests of both sites and the old secondary forest in Epulu overlapped on both DCA axes. Mandumbi primary forest and Epulu secondary forest were indistinguishable on the ﬁrst axis, but the former had higher scores of axis 2 than the latter. [326]

Table 2. Abundance of the 20 most common tree species for stems ‡1 cm dbh in primary forests (PF) and secondary forests (SF) at two study sites (Epulu and Mandumbi) in northeastern Congo Basin. Figures are number of trees per hectare. Species name

[327]

Scaphopetalum dewevrei De Wild. and T. Durand Gilbertiodendron dewevrei (De Wild.) J. Le´onard Julbernardia seretii (De Wild.) Troupin Alchornea ﬂoribunda Mu¨ll. Arg. Rinorea oblongifolia (C.H. Wright) Marquand ex Chipp Diospyros bipendensis Gu¨rke Celtis mildbraedii Engl. Khaya anthotheca (Welw.) C. DC. Trichilia rubescens Oliv. Pancovia harmsiana Gilg Myrianthus preussii Engl. Cynometra alexandri C.H. Wright Musanga cecropioides R. Br. Albizia gummifera (J.F. Gmel.) C.A. Sm. Greenwayodendron suaveolens (Engl. and Diels) Verdc. Pycnanthus angolensis (Welw.) Warb. Antiaris toxicaria Lesch. Cola lateritia K. Schum Entandrophragma utile (Dawe and Sprague) Sprague Microdesmis puberula Hook. F. ex Planch.

Code

SCAPDE GILBDE JULBSE ALCHFL RINOOB DIOSBI CELTMI KHAYAN TRICRU PANCHA MYRPR CYNOAL MUSACE ALBIGU GREESU PYCNAN ANTITO COLALA ENTAUT MICRPU

Status

Understory Canopy Canopy Understory Understory Understory Canopy Canopy Understory Understory Understory Canopy Canopy Canopy Understory Canopy Canopy Canopy Canopy Understory

EPULU

MANDUMBI

PF

SF

PF

SF

1782 764 800 145 0 327 255 36 109 327 100 218 0 0 327 0 73 110 0 182

109 0 109 182 0 109 618 73 545 0 440 400 0 109 72 0 36 37 40 218

0 833 401 668 1012 467 67 167 166 401 33 0 0 68 66 264 67 233 65 0

0 0 48 175 110 150 99 724 174 98 101 0 653 399 0 224 275 48 301 0

1387

1388 Table 3. Abundance of seedlings and saplings of commercial timber tree species in primary forest (PF) and secondary forest (SF) in northeastern Congo basin. Abundances are averages of the number of stems per hectare, and were calculated on the basis of 5 m · 5 m quadrats for seedlings and of 10 m · 10 m quadrats for saplings. Signiﬁcance levels for the diﬀerence in regeneration abundance between primary and secondary forests as follows: ns p>0.05, * p<0.05, ** p<0.01. Species name

[328]

Khaya anthotheca (Welw.) C.DC. Entandrophragma cylindricum (Sprague) Sprague Entandrophragma angolense (Welw.) C. DC. Entandrophragma utile (Dawe and Sprague) Sprague Lovoa trichilioides Harms Guarea cedrata (A. Chev.) Pellegr. Albizia gummifera (J.F. Gmel.) C.A. Sm. Tieghemella africana Pierre Gilbertiodendron dewevrei (De Wild.) J. Le´onard Zanthoxylum gillettii (De Wild.) P.G. Waterman Nauclea diderrichii (De Wild.) E.M.A. Petit Canarium schweinfurthii Engl. Alstonia boonei De Wild. Klainedoxa gabonensis Pierre ex Engl. TOTAL 1

NLPD: non-pioneer light demander (Hawthorne 1993)

Shade tolerance guild1

Seedlings ha1

Saplings ha1

PF

SF

Diﬀerence

PF

SF

Diﬀerence

NPLD NPLD NPLD NPLD NPLD Tolerant NPLD NPLD Tolerant NPLD Pioneer Pioneer Pioneer NPLD

237 356 30 0 30 89 607 59 5956 0 0 0 0 0 7364

4978 370 978 89 0 59 119 59 30 0 30 0 0 0 6712

** ns ** – – ns ns ns ** – – – – –

28 31 14 4 10 7 31 21 162 7 0 4 0 7 326

120 4 52 40 24 0 60 20 0 20 24 32 32 8 436

** ns * ns ns – ns ns – ns – ns – ns

1389 A greater proportion of common species were associated with Mandumbi forests than Epulu forests (Figure 4b). Most of Epulu primary forest plots and Mandumbi secondary forest plots were more than 3 standard deviations apart on the ﬁrst axis. This suggests that the two communities share few of their most common canopy species. Examination of Figure 4 reveals that the ﬂoristic composition of the primary forest in Mandumbi was more similar to those of the primary and old secondary forests in Epulu than to that of the young secondary forest at the same site.

Regeneration of timber species The abundance of seedlings of commercial timber trees diﬀered signiﬁcantly between primary and secondary forest forests (F1,44 = 8.0, p<0.001), and there was also a signiﬁcant site by forest type interaction (F1,44 = 7.9, p = 0.008). The diﬀerence in seedling abundance with respect to forest type was entirely due to the extremely low abundance of timber tree seedlings in the secondary forest of Epulu, which averaged 15 times less seedlings than any other combination of site and forest type. The number of seedlings in the mature and undisturbed forest of Epulu was similar to that of the logged or secondary forests of Mandumbi. The abundance of saplings of timber species did not vary signiﬁcantly according to forest type. Although Mandumbi forests had consistently higher densities of saplings than Epulu forests, the diﬀerence was signiﬁcant only at p<0.1. Two species were particularly abundant in the seedling and sapling populations. Khaya anthotheca was the most abundant timber species in the secondary forest of Mandumbi, averaging densities of 8350 seedlings and 190 saplings ha1. In Epulu, K. anthoteca was totally absent from the seedling population and occurred only at a density of 73 saplings ha1. G. dewevrei dominated the seedling and sapling populations in primary forests of both sites. Mean densities of G. dewevrei seedlings and saplings in primary forests were 6000 and 162 individuals ha1, respectively. While K. anthoteca was also well represented among the seedling and sapling populations of primary forests, G. dewevrei seedlings were very rare in secondary forests ( 30 individuals ha1) and no saplings of this species were recorded in secondary forest (Table 3).

Mahogany regeneration Seedlings of four species of African mahogany (K. anthoteca, Entandrophragma angolense, E. cylindricum and E. utile) were much more abundant in secondary forests (10,775±3776 ha1) than in primary forests (1050±336 ha1) at [329]

1390 Mandumbi. No seedlings of these species were found in any of the forest plots in Epulu. The abundance of mahogany saplings (1–9.9 cm dbh) was also higher in secondary forests than in primary forests at both sites, 331 (125) vs. 113 (39) stems ha1 in Mandumbi and 27 (14) vs. 9 (9) stems ha1 in Epulu. To determine environmental factors that aﬀect the regeneration of African mahogany tree species in the region, the abundance of mahogany regeneration was compared between primary and secondary forests and the relationships between the abundance of the regeneration and recorded environmental variables was tested through regression analysis and analysis of variance. This analysis was limited to data from Mandumbi because mahogany regeneration in Epulu was negligible. The abundance of the regeneration of African mahogany species varied signiﬁcantly according to forest type (F1,44 = 17, p<0.001) and soil texture (F1,44 = 2.43, p = 0.038). There were at least ten times more seedlings of these species in secondary forests than in primary forests at Mandumbi (Table 3). Loamy and sandy soils supported a higher density of seedlings and saplings of mahogany than did clay-textured soils. Simple regression analysis showed that two factors were signiﬁcantly associated with mahogany regeneration. The abundance of M. cecropioides, an early pioneer tree species, and litter depth were positively associated with mahogany regeneration (r2 = 0.431, p<0.001 and r2 = 0.158, p = 0.022 respectively). Herb cover was marginally negatively associated with the abundance of mahogany regeneration (r2 = 0.099, p = 0.075). A simultaneous test of all factors and their interactions through multiple regression (stepwise selection) revealed that only the abundance of M. cecropioides and the interaction between the latter factor and herb cover were signiﬁcant (p<0.001 for both variables). This model explained 61.4% of the variation in the abundance of mahogany regeneration in Mandumbi. Litter depth was not maintained in the model likely due to its strong positive correlation with the abundance of M. cecropioides (r = 0.525, p = 0.002).

Discussion Secondary forests and the conservation of tree diversity It was expected that the combination of selective logging and agricultural clearing would result in the degradation and impoverishment of natural forests. Secondary forests are generally seen as having much lower conservation value than mature forests. They generally have fewer tree species, are dominated by widespread pioneer trees, and have a simpler structure (Garcia-Montiel and Scatena 1994; Guariguata et al. 1997; Whitmore 1999; Aide et al. 2000). The return of secondary forests to the complex and species-rich primary forest conditions can be very slow, partly due to the limited availability of seeds of primary forest tree species (Holl et al. 2000; Wijdeven and Kuzee 2000). However, human-induced disturbances in tropical forests span a wide gradient, [330]

1391 depending on land-use type and intensity. Forest clearing for traditional slashand-burn agriculture, such as practiced in our study sites, occupies the lower end of severe forest disturbance as compared to clearing for large commercial pastures or oil palm plantations (Lawrence et al. 1998; Mesquita et al. 2001). This study shows that secondary forests growing after the initial clearing of primary forests for shifting cultivation in the Ituri harbor surprisingly high levels of tree species diversity for small stem sizes. Overall diversity measures of trees ‡1 cm dbh were similar between secondary and primary forest stands. Two factors that may account for the observed diversity patterns in the secondary and primary forest stands include edge eﬀects and the dominance of primary forest stands by G. dewevrei. The proximity of many secondary forest plots to primary forest stands will likely result in increased diversity in these plots due to potentially high seed input from mature forests (Mesquita et al. 2001; Kennard 2002). On the other hand, most mature forest plots especially at Epulu were located in forest stands dominated by G. dewevrei, which are known to have very low diversity at small spatial scales (Hart et al. 1989; Makana et al. 2004). The diversity of larger trees (i.e. ‡10 cm dbh) was, however, signiﬁcantly lower in young secondary forest stands (<10 years old). However, notwithstanding the similarity in overall tree diversity, the ﬂoristic compositions of the two forest types were very diﬀerent. The ﬂora of secondary forests was particularly depauperate in common species characteristic of old-growth forests in the region, particularly G. dewevrei and J. seretii, and understory specialists such as S. dewevrei, Drypetes spp., Rinorea spp., and Pancovia harmsiana Gilg. In this respect, our results corroborate those of other studies on tropical forest succession (Brown and Lugo 1990; Guariguata et al. 1997; Aide et al. 2000). For example, Aide et al. (2000) noted that a 40-year old secondary forest derived from abandoned pasture had comparable tree diversity to adjacent mature forest, whereas the ﬂoristic composition was substantially diﬀerent. Stem density and basal area increased very rapidly after farm abandonment with higher basal areas observed in 10-year old secondary forests than in adjacent primary forest. However, most of the basal area in the young secondary forest of Mandumbi was accounted for by the presence of the early pioneer tree M. cecropioides, which does not persist beyond the senescence of the initial cohort, which may result in a reduction in the basal area of those stands when the initial cohort of that species dies out. Similar trends have been observed elsewhere in tropical forest succession (Aide et al. 2000). Our result are consistent with other ﬁndings suggesting that many structural characteristics of secondary forest stands in the tropics can reach levels encountered in mature forest stands quite early during succession (Brown and Lugo 1990; DeWalt et al. 2003). The rapid forest recovery observed in this study may be the result of light land-use intensity and high seed fall into abandoned ﬁelds due to the relatively small sizes of farms and the presence of remnant trees that attract seed dispersers. [331]

1392 Forest disturbance and the regeneration of major timber trees A pattern of reduced abundance of timber tree regeneration in selectively logged forests has been frequently observed in the tropical forests of Africa and Latin America (Verissimo et al. 1995; Struhsaker 1997; Mwima et al. 2001; Hall et al. 2003). Low seed availability due to the removal of most large reproductive trees (Plumptre 1995; Makana and Thomas 2004), small sizes of canopy openings created by single-tree removal, high seed and seedling predation, and the rapid invasion of logging gaps by lianas and herbaceous vegetation (Struhsaker 1997; Fredericksen 1998) are commonly blamed for this lack of timber tree regeneration after selective logging. On the other hand, several studies have reported good regeneration of Neotropical mahogany (Swietenia macrophylla King) following severe disturbances such as hurricane, ﬁre, ﬂooding or agricultural clearing (Lamb 1966; Snook 1996; Gullison et al. 1996; Mostacedo and Fredericksen 1999; Negreros-Castillo et al. 2003). Our results support the hypothesis that African mahoganies, like their Neotropical counterpart, regenerate well after severe disturbances (i.e. forest clearing for agriculture) that destroy most of the existing vegetation. Secondary forests regrowing on areas that were previously selectively logged and cleared for agricultural purposes had at least 10 times more seedlings of African mahoganies than unlogged mature forests. The positive eﬀects of forest clearing on tree regeneration were not limited to mahoganies; other light demanding timber trees such as Albizia gummifera C. A. Smith, Canarium schweinfurthii Engl., and Zanthoxylum gillettii (De Wild.) Waterman also showed better seedling recruitment in secondary vegetation than in mature forests. Good regeneration of timber trees in the secondary forest stands of this study may be the result of traditional shifting cultivation practices in the Ituri region. Mature individuals of valuable tree species (fruit trees, timber or medicinal species) are commonly left alive during forest clearing for agricultural purposes. These ‘‘remnant’’ trees likely dispersed seeds in abandoned farms while competition from existing vegetation was low, leading to abundant regeneration of major timber trees such as African mahoganies (Carrie`re et al. 2000). Slash-and-burn agriculture, which mimics hurricanes followed by wildﬁres, is now considered as one of the silvicultural treatments that favor the establishment of mahogany in the Neotropics (Negreros-Castillo et al. 2003). In the Peruvian Amazon, Smith et al. (1999) reported a high representation of valuable timber trees in secondary forests regrown after farm abandonment. Twenty of the 22 most important timber trees in the region were present as poles (>10 m height) in old secondary forests. The regeneration of African mahogany species was much more abundant in Mandumbi than in Epulu. Mandumbi is located at the margin of closed canopy forest and eastern savanna woodlands, and it has semi-deciduous vegetation, whereas the vegetation at Epulu (located in central Ituri basin) is primarily evergreen. Although African mahogany species are widely distributed across tropical Africa, their local abundance can be inﬂuenced by climate [332]

1393 (rainfall), soil conditions (moisture and nutrients), historic events, and disturbances (Bongers et al. 1999). Most African mahoganies have been described as belonging to the deciduous or semi-deciduous forests (Hall and Swaine 1981). The relatively drier and semi-deciduous forests of the eastern fringe of the Ituri basin probably oﬀer more favorable conditions for the regeneration and growth of African mahoganies than the evergreen forests of Epulu. Densities of commercial size trees (‡ 80 cm dbh) were 5 times higher in Mandumbi than in Epulu (J.-R. Makana, unpublished data). Low density of adult trees may therefore partly explain the poor regeneration of K. anthotheca and Entandrophragma spp in Epulu, due to limited seed availability (Plumptre 1995; Makana and Thomas 2004).

Implications for conservation and management Natural forests in the Ituri region host an impressive diversity of tree and animal species which has led to the designation of the Ituri forest as a refugium during late Quaternary climate ﬂuctuations (Grubb 1982; Hart et al. 1996). The Ituri forest contains large mammal species including the endemic Okapi, forest elephant, leopard, buﬀalo, as well as 13 species of anthropoid primates, seven species of forest antelopes (duikers), and many other species of mammals, birds and reptiles (Hart 1986; Thomas 1991; Hart et al. 1986; Plumptre 1996). This abundant and diverse wildlife assemblage has coexisted with small communities of horticulturalists in the Ituri for centuries (Wilkie and Finn 1990). While the presence of small areas of secondary vegetation derived from swidden agriculture may beneﬁt some mammal populations (Short 1983; Thomas 1991), the creation of large areas of secondary forests poses a threat to most mature forest dwelling species such as forest ungulates, okapi, leopard, and others. These species, especially forest ungulates, are the main source of dietary protein for local populations (Hart and Hart 1986). Therefore maintaining large tracks of undisturbed primary forest is essential to the conservation of animal diversity and to the well-being of local hunter–gatherer communities. Forest recovery on abandoned agricultural lands is possible through natural regeneration. It is shown here that some aspects of forest structure and the diversity of small trees can be rapidly restored to levels comparable to those of mature forests. However, forest recovery is possible only if secondary forests are protected from repeated clearing because the return of the species composition of secondary vegetation to assemblage similar to that of old-growth forests may require over 100 years due to limited seed availability and dispersal, and slow growth of mature forest tree species. Small-sized clearings, moderate land use intensity (long fallow periods), and a ﬁne scaled landscape mosaic may speed up the return of secondary forests to mature forest species

[333]

1394 composition. Human intervention in the recovery process may be desirable. Makana and Thomas (2004) showed that the addition of seeds in light-gaps greatly increased seedling recruitment in the study site. Thus, seed supplementation and/or enrichment planting can be valuable interventions for the rapid return of secondary forests to the complex and species-rich mature forest conditions. Our results are consistent with the generalization that tropical secondary forest resulting from farm abandonment may provide a favorable environment for the regeneration of high value timber trees (Negreros-Castillo et al. 2003). The high abundance of African mahoganies’ regeneration and the enhanced performance of their seedlings in secondary forest stands suggest that these species require suﬃcient light availability to regenerate well. Therefore, successful regeneration of African mahoganies may depend on the adoption of forestry practices that provide for larger clearings, followed by post-harvest silvicultural treatments to control competing vegetation (see Fredericksen and Putz 2003; Negreros-Castillo et al. 2003). It has been shown here that young secondary forests, growing on areas that were both selectively logged and cleared for agricultural purposes, have both high tree species diversity and abundant regeneration of valuable timber trees. This potentially favorable situation oﬀers a window of opportunity to reconcile social and ecological demands on tropical forests. Planned and controlled clearing of selectively logged forests for shifting cultivation can have the potential create favorable conditions for African mahogany regeneration as well as to provide for the needs of local communities that depend on the forest, while still conserving a high portion of the original biodiversity through appropriate fallow systems and protection of primary forest stands as a source of propagules.

Acknowledgements Financial support for the research came through grants from ITTO, CTFS and CEFRECOF, a University of Toronto fellowship, and an NSERC grant to Sean Thomas. Logistical support at the ﬁeld sites was provided by CEFRECOF and ENRA. We thank Sabuni Paluku, Simende, Nzambe, and Amisi for assisting with ﬁeldwork. Jay Malcolm, Justina Ray, Terry Carleton and two anonymous reviewers provided constructive comments on an earlier version of this manuscript. References Aide T.M., Zimmerman J.K., Herrera L., Rosario M. and Serrano M. 1995. Forest recovery in abandoned tropical pastures in Puerto Rico. Forest Ecology and Management 77: 77–86. Aide T.M., Zimmerman J.K., Pascarella J.B., Rivera L. and Marcano-Vega H. 2000. Forest regeneration in a chronosequence of tropical abandoned pastures: implications for restoration ecology. Restoration Ecology 8: 328–338. [334]

1395 Bongers F., Poorter L., van Rompaey R.S.A.R. and Parren M.P.E. 1999. Distribution of twelve moist forest canopy species in Liberia and Coˆte d’Ivoire: response curves to a climatic gradient. Journal of Vegetation Science 10: 371–382. Brown S. and Lugo A.E. 1990. Tropical secondary forests. Journal of Tropical Ecology 6: 1–32. Cannon C.H., Peart D.R. and Leighton L. 1998. Tree diversity in commercially logged Bornean rainforest. Science 281: 1366–1368. Carrie`re S.M., Letourmy P. and McKey D.B. 2002. Eﬀects of remnant trees in fallows on diversity and structure of forest regrowth in a slash-and-burn agricultural system in southern Cameroon. Journal of Tropical Ecology 18: 375–396. Coomes O.T., Grimard F. and Burt G.J. 2000. Tropical forests and shifting cultivation: secondary forest dynamics among traditional farmers of the Peruvian Amazon. Ecological Economics 32: 109–124. DeWalt S.J., Malakal S.K. and Denslow J.S. 2003. Changes in vegetation structure and composition along a tropical forest chronosequence: implications for wildlife. Forest Ecology and Management 182: 139–151. Fredericksen T.S. 1998. Limitations of low-intensity selection and selective logging for sustainable tropical forestry. Commonwealth Forestry Review 77: 262–266. Fredericksen T.S. and Putz F.E. 2003. Silvicultural intensiﬁcation for tropical forest conservation. Biodiversity and Conservation 12: 1445–1453. Garcia-Montiel D.C. and Scatena F.N. 1994. The eﬀect of human activity on the structure and composition of a tropical forest in Puerto Rico. Forest Ecology and Management 63: 57–78. Grubb P. 1982. Refuges and dispersal in the speciation of African forest mammals. In: Prance G.T. (ed.), Biological Diversiﬁcation in the Tropics. Columbia University Press, NY, pp. 537–553. Guariguata M.R. and Ostertag R. 2001. Neotropical secondary forest succession: changes in structural and functional characteristics. Forest Ecology and Management 148: 185–206. Guariguata M.R., Chazdon R.L., Denslow J.S., Dupuy J.M. and Anderson L. 1997. Structure and ﬂoristics of secondary and old-growth forest stand in lowland Costa Rica. Plant Ecology 132: 107–120. Gullison R.E., Panﬁl S.N., Strouse J.J. and Hubbell S.P. 1996. Ecology and management of mahogany (Swietenia macrophylla King) in the Chimanes Forest, Beni, Bolovia. Botanical Journal of Linnean Society 122: 9–34. Hall J.B. and Swaine M.D. 1981. Distribution and ecology of vascular plants in a tropical rain forest: forest vegetation in Ghana. Dr W. Junk, The Hague. Hall J.S., Harris D.J., Medjibe V. and Ashton P.M.S. 2003. The eﬀects of selective logging on forest structure and tree species composition in a Central African forest: implications for management of conservation areas. Forest Ecology and Management 183: 249–264. Hart J.A. and Carrick P. 1996. Climate of the Re´serve de Faune a` Okapis: Rainfall and temperature in the Epulu Sector, 1986–1995. CEFRECOF Working Paper n 2. Hart J.A., Hart T.B. and Thomas S.C. 1986. The Ituri Forest of Zaire: primate diversity and prospects for conservation. Primate Conservation 7: 42–44. Hart T.B. 1985. The Ecology of a Single-Species Dominant Forest and a Mixed Forest in Zaire, Equatorial Africa. PhD thesis, Michigan State University, East Lansing, MI. Hart T.B., and Hart J.A. 1986. The ecological basis of hunter-gatherer subsistence in African rain forests-the Mbuti of Eastern Zaı¨ re. Human Ecology 14: 29–55. Hart T.B., Hart J.A. and Murphy P.G. 1989. Monodominant and species-rich forests of the humid tropics: causes for their co-occurrence. American Naturalist 133: 613–623. Hart T.B., Hart J.A., Dechamps R., Fournier M. and Ataholo M. 1996. Changes in forest composition over the last 4000 years in the Ituri basin, Zaire. In: van der Maesen L.J.G. (ed.), The Diversity of African Plants. Kluwer Academic Publishers, the Netherlands, pp. 545–563. Holl K.D., Loik M.E., Lin E.H.V. and Samuels I.A. 2000. Tropical montane forest restoration in Costa Rica: overcoming barriers to dispersal and establishment. Restoration Ecology 8: 339–349. Johns A.G. 1997. Timber production and biodiversity conservation in tropical rain forests. Cambridge University Press, Cambridge, UK.

[335]

1396 Kammesheidt L. 2002. Perspectives on secondary forest management in tropical humid lowland America. Ambio 31: 243–250. Kennard D.K. 2002. Secondary succession in tropical fry forest: patterns of development across a 50-year chronosequence in lowland Bolivia. Journal of Tropical Ecology 18: 53–66. Lamb F.B. 1966. Mahogany of Tropical America: Its Ecology and Management. University of Michigan Press, Ann Arbor. Laurance W.F. 1999. Reﬂections on the tropical deforestation crisis. Biological Conservation 91: 109–117. Laurance W.F. 2001. Tropical logging and human invasions. Conservation Biology 15: 4–5. Lawrence D., Peart D.R. and Leighton M. 1998. The impact of shifting cultivation on rainforest landscape in West Kalimantan: spatial and temporal dynamics. Landscape Ecology 13: 135–148. Lebrun J. and Stork A.L. 1997. Enume´ration des plantes a` ﬂeurs d’Afrique tropicale. Vol. 4. Publication hors-se´rie n 7C, Conservatoire et Jardin Botaniques de ville de Gene`ve, Gene`ve. Lugo A.E. 1995. Management of tropical biodiversity. Ecological Applications 5: 956–961. Makana J.-R. 2004. Ecology and sustainable management of African mahoganies and other selected timber species in northeastern Congo Basin, Democratic Republic of Congo. PhD thesis, University of Toronto, Toronto, Canada. Makana J.-R. and Thomas S.C. 2004. Dispersal limits the natural recruitment of African mahoganies. Oikos 106: 67–72. Makana J.-R., Hart T.B., Hibbs D.E. and Condit R. 2004. Forest structure and diversity in the Ituri Forest dynamics plots. In: Losos E. and Leigh E.Jr. (eds), Tropical Forest Diversity and Dynamism: Findings from a Large-Scale Network. University of Chicago Press, Chicago, pp. 149–174. Malcolm J.R. and Ray J.C. 2000. Inﬂuence of timber extraction routes on Central African smallmammal communities, forest structure, and tree diversity. Conservation Biology 14: 1623–1638. Mesquita R.C.G., Ickes K., Ganade G. and Williamson G.B. 2001. Successional pathways in the Amazon Basin. Journal of Ecology 89: 528–537. Mittelman A. 2001. Secondary forests in the lower Mekong subregion: an overview of their extent, roles and importance. Journal of Tropical Forest Science 13: 671–690. Mostacedo B. and Fredericksen T.S. 1999. Regeneration status of important tropical forest tree species in Bolivia: assessment and recommendations. Forest Ecology and Management 124: 263– 273. Mwima P.M., Obua J. and Oryem-Origa H. 2001. Eﬀect of logging on the natural regeneration of Khaya anthotheca in Budongo Forest Reserve, Uganda. International Forestry Review 3: 131– 135. Negreros-Castillo P., Snook L.K. and Mize C.W. 2003. Regenerating mahogany (Swietenia macrophylla) from seed in Quintana Roo, Mexico: the eﬀects of sowing method and clearing treatment. Forest Ecology and Management 183: 351–362. Okali D.U.U. and Ola-Adams B.A. 1987. Tree population changes in treated rain forest at Omo Forest Reserve, south-western Nigeria. Journal of Tropical Ecology 3: 291–313. Ontario Institute of Pedology 1985. Field Manual for Describing Soils. 3rd ed. Ontario Institute of Pedology, Guelph. Panayotou T. and Ashton P.S. 1992. Not by Timber Alone: Economics and Ecology for Sustaining Tropical Forests. Island Press, Washington, D.C. Plumptre A.J. 1995. The importance of ‘seed trees’ for the natural regeneration of selectively logged tropical forest. Commonwealth Forestry Review 74: 253–258. Plumptre A.J. 1996. Shifting Cultivation Along the Trans-African Highway and Its Impact on the Understory Bird Community in the Ituri Forest, Zaire. University of Oxford, Unpublished report. Short J.C. 1983. Density and seasonal movement of forest elephant (Loxondonta africana cyclotis Matschie) in Bia National Park, Ghana. African Journal of Ecology 21: 175–184.

[336]

1397 Smith J., van de Kop P., Reategui K., Lombardi I., Sabogal C. and Diaz A. 1999. Dynamics of secondary forests in slash-and-burn farming: interactions among land use types in the Peruvian Amazon. Agriculture, Ecosystems and Environment 76: 85–98. Snook L.K. 1996. Catastrophic disturbance, logging, and the ecology of mahogany: ground for listing a major tropical timber species in CITES. Botanical Journal of the Linnean Society 122: 35–46. Sokal R.R. and Rohlf F.J. 1981. Biometry: the Principles and Practice of Statistics in Biological Research. W. H. Freeman and Company, NY. Southgate D., Sierra R. and Brown L. 1991. The causes of tropical deforestation in Ecuador: a statistical analysis. World Development 19: 1145–1151. Struhsaker T.T. 1997. Ecology of an African Rain Forest: Logging in Kibale and the Conﬂict Between Conservation and Exploitation. University Press of Florida, Gainesville, Florida. Struhsaker T.T., Lwanga J.S. and Kasenene J.M. 1996. Elephants, selective logging, and forest regeneration in the Kibale Forest, Uganda. Journal of Tropical Ecology 12: 45–64. ter Braak C.J.F. 1987. Ordination. In: Jongman R.H.G., ter Braak C.J.F. and van Tongeren O.F.R. (eds), Data analysis in community and landscape ecology. Cambridge University Press, Cambgridge, UK. Thomas S.C. 1991. Population densities and patterns of habitat use among anthropoid primates of the Ituri Forest, Zaire. Biotropica 23: 68–83. Verissimo A., Bareto P., Tarifa R. and Uhl C. 1995. Extraction of a high-value resource in Amazonia: the case of mahogany. Forest Ecology and Management 72: 39–60. White L.J.T. 1994. The eﬀects of commercial mechanized selective logging on a transect in lowland rainforest in Lope´ Reserve, Gabon. Journal of Tropical Ecology 10: 313–322. Whitmore T.C. 1999. Arguments on the forest frontier. Biodiversity and Conservation 8: 865–868. Wijdeven S.M.J. and Kuzee M.E. 2000. Seed availability as a limiting factor in forest recovery processes in Costa Rica. Restoration Ecology 8: 414–424. Wilkie D.S. and Finn J.T. 1990. Slash-burn cultivation and mammal abundance in the Ituri forest, Zaire. Biotropica 22: 90–99. Wilkie D.S., Sidle J.G. and Boundzanga G.C. 1992. Mechanized logging, market hunting, and a bank loan in Congo. Conservation Biology 6: 570–580. Wilkie D.S., Shaw E., Rotberg F., Morelli G. and Auzel P. 2000. Roads, development, and conservation in the Congo basin. Conservation Biology 14: 1614–1622. Witte J. 1992. Deforestation in Zaire: logging and landlessness. The Ecologist 22: 58–65. Wolﬁre D.M., Bruner J. and Sizer N. 1998. Forests and the Democratic Republic of Congo: opportunity in a time of crisis. World Resources Institute, Washington, D.C. Zahawi R.A. and Augspurger C.K. 1999. Early plant succession in abandoned pastures in Ecuador. Biotropica 31: 540–552.

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Biodiversity and Conservation (2006) 15:1399–1415 DOI 10.1007/s10531-005-5410-0

Springer 2006

0

Forest management considerations for conservation of Black Woodpecker Dryocopus martius and White-backed Woodpecker Dendrocopos leucotos populations in Quinto Real (Spanish Western Pyrenees) ALFONSO GARMENDIA1,*, SUSANA CA´RCAMO2 and OSCAR SCHWENDTNER2 1 Department of Agroforest Ecosystems, Polytechnic University of Valencia, E.T.S.M.R.E. (‘‘Agrı´colas’’), Blasco Iba´n˜ez 21, 46010 Valencia, Spain; 2BASOA, C/Tafalla 20, Pamplona, Spain; *Author for correspondence (e-mail: [email protected])

Received 9 November 2004; accepted in revised form 5 April 2005

Key words: Black woodpecker, Dead wood, Dendrocopos leucotos ssp. lilfordi, Dryocopus martius, Forest structure, Population dynamics, Spain, Sustainable forest management, White-backed woodpecker Abstract. The woodlands of Quinto Real (Quinto Real, Erreguerena and Legua Acotada) are a 3,000 hectare beech (Fagus sylvatica) forest managed by the shelterwood system applied to evenaged (regular) stands. This study analyses how forest management determines the local distribution of the white-backed woodpecker (Dendrocopos leucotos) and black woodpecker (Dryocopus martius) and its relationship with the type, structure and size of the stands used for nesting by both species, as well as their dead wood requirements. The most suitable nesting habitat of both species is the mature forest (stands of regular large ﬁnal crop trees), but the size of the mature fragments and a minimum quantity of dead wood is also important.

Introduction Woodpeckers (Picidae), particularly the white-backed (Dendrocopos leucotos) and black woodpeckers (Dryocopus martius), are associated with the existence of mature forests (Voous 1947). The black woodpecker and the white-backed woodpecker are two of the most threatened species in the Pyrenean Region of Spain. They need large areas of mature deciduous forest, particularly woodlands with beech (Fagus sylvatica), or beech-ﬁr (Abies alba) or beech-pine (Pinus spp.) mixed forests (Cuisin 1967; Purroy et al. 1990; Ferna´ndez et al. 1994). The surfaces of these forests are decreasing and those that still remain are variously degraded in most of continental Europe (Cramp 1985; Avery and Leslie 1990), especially in Mediterranean countries (Purroy et al. 1990; Tellerı´ a 1992). Two legal instruments that were recently approved by the Regional Government of Navarre, Spain – The forest plan (Gobierno de Navarra 1998), and The Biological Diversity Conservation Strategy (Gobierno de Navarra 1999) – are based on the sustainable management of natural resources. In Quinto Real [339]

1400 woodland, this environmental standard involves forestry management and oﬀers the chance to provide, if not an optimum, at least a suitable habitat for these species. Woodpecker species are an interesting group as ‘umbrella species for biodiversity conservation (Simberloﬀ 1999; Fleishman et al. 2000; Fleishman et al. 2001; Roberge and Angelstam 2004) because they need large areas of well conserved forest with little alteration of their structure and with a suﬃcient amount of old trees and recently dead large trees (Hogstad 1970; Angelstam 1990; Angelstam and Mikusinsky 1994; Mikusinsky and Angelstam 1997; Murphy and Lehnhausen 1998; Imbeau and Desrochers 2002; Butler et al. 2004). Therefore, the modern forestry practices of removing old and dead trees can compromise their conservation (Nilsson 1992, Tucker and Heath 1994). The Pyrenees white-backed woodpecker (Dendrocopos leucotos ssp. lilfordi) population is particularly interesting from a bio-geographical perspective. The Pyrenees represent the south – western fringe of its world distribution (Ferna´ndez et al. 1994), and it has been catalogued as endangered in Spain (Blanco and Gonza´lez 1992). This subspecies has a patchy and discontinuous distribution in mountains of southern Europe, such as the Pyrenees, the Apennines and the Carpathian ranges (Voous 1947). The Pyrenees population is the only one in the Iberian Peninsula and its conservation is therefore very important. This population has been estimated to be composed of 60–70 pairs, of which approximately 20% can be found in the woodlands of Quinto Real (Ferna´ndez et al. 1994). The white-backed woodpecker feeds mainly on wood-boring beetle larvae, mostly Cerambycidae. Therefore, the availability of dead wood in this area is an important factor for its survival (Aule´n 1988, Aule´n and Lundberg 1991). Of all Picidae, this species is the most specialised in feeding habits. Thus, it is probably the most vulnerable to changes in forestry management (Conner 1979). Another limiting factor for the distribution of this species is the presence of optimum nesting sites. During the breeding season, foraging is conﬁned to relatively small areas around the nest site. This forces this species to choose nesting sites with abundant insects, such as groups of dead trees and borders between diﬀerent forest areas (Ferna´ndez et al. 1994). The black woodpecker (Dryocopus martius) is widely distributed throughout northern and temperate forests of Europe and Asia. It inhabits mature forests, where there are usually beech trees. However, in northern Europe and Siberia it is also found in coniferous forests. In the Iberian Peninsula, this species occupies the beech forests of the Pyrenees and the Cantabrian Mountains (Martinez-Vidal 1999). It has also been spotted in the relict beech forests situated in the central portion of the Iberian Peninsula, but it seems not to be an established population, but rather composed of young dispersing individuals (Brooks 1985). It has a broad feeding spectrum: most of its food consists of ants, although it also eats many kinds of wood-boring beetle larvae. It frequently feeds on the ground, digging out ant nests or forages in the stumps of felled trees and other types of dead wood (pers. obs.). [340]

1401 The black woodpecker is an indicator species of mature forests. It is especially reliant upon dense, tall stands, and tends to disappear when the forest is degraded (Brooks 1985, Ferna´ndez and Azkona 1996). Nevertheless, a limited use of forest resources can be beneﬁcial for this species if small clearings are created and a considerable amount of standing dead wood are left over in the process. Indeed, this can increase the availability of its prey (Brooks 1985). The conservation of the black woodpecker and the white-backed woodpecker depends, to a large extent, on how the beech forests they inhabit are managed. Inappropriate management may lead to the disappearance of one or both of these species. Consequently, it is very important to implement suitable management programmes in these woodlands. The most widely-used cutting method in the beech forests of Navarre is the shelterwood system. Current management has resulted in the development of patches of diﬀerent ages. Protected patches have also been designated where no exploitation can be carried out for logistical reasons. On the other hand, there is a legal obligation to designate non-exploitable areas on at least 5% of the area (Gobierno de Navarra 1990,1992) which involves the creation of several core ‘biodiversity reserves’ areas, that complement other extensive measures for protecting the habitat. During spring 1993, Ferna´ndez and Azkona (1996) conducted a census of both species in the Quinto Real group of woodlands. The study revealed that the population density of the two species was relatively high in all the study area. They linked the presence of territories for both species with forest stands with high basal areas (>20 m2/ha). They also noticed a clear overlap between the locations of territories of both species. Dead wood amount in these woodpeckers habitats have not been quantiﬁed for this area, and the existence of dead wood threshold value has never been tested. The objective of this study was to establish how forest management aﬀects woodpeckers’ density. In particular, the addressed question is how the type and size of the forest patches, and the amount of dead wood, aﬀects the nesting sites selection for both species. Do these species utilize all the forest stands for their territories or do they prefer one? Which is the threshold stand size of the preferred type? What is more important in this area, the stand type and its size or the dead wood amount? Do all kinds of dead wood serve the same or there are some preferred diameters? Is it really necessary that the dead wood is standing, or could it be lied down? These are the questions addressed in this article.

Methods Study area The study was carried out in the Quinto Real group of woodlands, located in northern Navarre in the Bazta´n and Erro valleys on the Spanish side of the Pyrenees. The Quinto Real area consists of three woodlands: Quinto Real [341]

1402 (1666 ha), Erreguerena (941 ha) and Legua Acotada (907 ha), listed under numbers 2, 3 and 4 in the Navarre’s Public Utility Woodlands Catalogue (Gobierno de Navarra 1998). These woodlands are some of the best-preserved beech forests in the Pyrenees. As a result, the Regional Government of Navarre recently proposed them as a Place of Community Interest within the framework of the European Union’s Natura 2000 Network. Forest management in this area is governed by a Management Project and its subsequent reviews (Schwendtner and Larran˜aga 2001). The Quinto Real group of woodlands has been managed for timber production since 1904. Extensive areas of regeneration, resulting from shelterwood system harvesting, are present. This kind of exploitation was particularly intensive in the period 1950–1970. There are also mature areas where thinning has been carried out with varying degrees of intensity, while others have not been harvested in the last 70 years. Other areas are characterised by their heterogeneity and unevenness as a result of high-grading of the valuable timber.

Forest characterization The Quinto Real Natural Resources Management Plan carried out a detailed inventory for the diﬀerent forest stands and their classiﬁcation according to structural criteria (Schwendtner and Larran˜aga 2001). Table 1 provides information on the diﬀerent stand types on which the three woodlands of Quinto Real were divided. A total of 397 diﬀerent homogenous forest patches (stands) were distinguished in the three woodlands. The following variables were measured to characterize the forest structure: dominant height (DH), measured as the mean height of those trees with an average diameter, excluding the stems under 20 cm of diameter, except for the young stands (RY), in which only stems under 10 cm of diameter are excluded; basal area (BA) of all stems over 10 cm of diameter; average diameter (AD) of the stems over 10 cm, measured at breast height; and average age (AA) of the stand, based on several individuals (approximately 1%) of each stand, by counting the growth rings on wood samples. All these measures were made on all stands over all the stand area for management purposes. Site quality is a variable that is calculated from the relationship between the mean growth rate and tree age. Site quality can be categorized on a scale ranging from I to V: very good and good quality sites are I and II, while III and IV would represent intermediate qualities, and V poor quality sites (Schwendtner and Larran˜aga 2001). In better quality sites, trees grow more rapidly that on poorer quality sites, where the harvesting cycle is not as rapid. Schwendtner and Larran˜aga (2001) proposed to exploit site qualities I and II, but advised against timber harvest on the lower quality sites. Basal area of standing dead trees (DBA) and the amount of felled trunks were also determined for each stand. [342]

1403 Table 1. Stand classiﬁcation by management objectives on the Quinto Real Natural Resources Management Plan (Schwendtner and Larran˜aga 2001). Stand type

Abreviation Principal characteristics

1. Stand of regular large ﬁnal crop trees 2. Stand of regular medium sized crop trees

RLF

3. Stand of regular young trees 4. Heterogeneous and irregular stand

RY

5. Low forest stand

LF

RM

HI

6. Open large ﬁnal crop trees OF

Mature forest. Average tree diameter >45 cm. Suitable for ﬁnal cutting. Medium sized and aged stand. Average tree diameter from 20 to 45 cm. For intermediate cuttings with economic value. Young stand. Average diameter from 10 to 20 cm. For thinning without economic value. Mixed stand, It is heterogeneous when it has diﬀerent species and irregular when it has diﬀerent age classes and structures. Various diameters. Low forest stand. Generally on sites of poor quality. Open zones in regeneration process. Some residual large trees. Basal Area <15 m2/ha.

Woodpeckers census The distribution and density of the black woodpecker and the white-backed woodpecker were established by determining their breeding territories during spring 2001. The low density of both species makes sampling diﬃcult. However, since they are highly territorial animals, the location of breeding territories was used to census these species (Svenssons 1979; Tellerı´ a 1986; Bibby et al. 1992). The method was the same as the one used in the previous censuses by Ferna´ndez and Azcona (1996), so that the densities and distribution of territories could be compared. Recordings of the birdcalls and tapping patterns of both species were used as decoys for locating the breeding territories. For the density estimates, the ‘open land’ or patches with no trees were excluded of the total study area (3200 ha) and not sampled, though all the other stands of the study area were sampled. To attract territorial birds or to provoke their response during the search, the tapped calls were played every one or two hundred meters, alternating with periods of 30 s of silence, thus permitting to detect the bird response and to locate the individual. Once an individual was located, it was followed to locate the nest and the partner, registering the stands they defended and used for foraging. The wood boring signs were only taken into account when they were extremely recent and very abundant and they were only used to determine areas where investigation should be intensiﬁed. Alone they were not considered as suﬃcient proof of the existence of a nesting area. Sightings of non-territorial individuals were excluded. [343]

1404 Habitat selection The eﬀect of diﬀerent forest variables on the breeding area selection of the two bird species (presence or absence of bird territories) was investigated. Therefore, the conclusions that may be drawn from this study concern the territories used for breeding and not the habitats used during other seasons. For the study on dead wood, the three woodlands of Quinto Real were subdivided into ‘quarters’ that represent smaller management units. Quinto Real was divided into three quarters, and Erreguerena and Legua Acotada into two quarters each (Schwendtner and Larran˜aga 2001).

Statistical analysis The v2 test was used to compare the presence/absence frequencies of woodpeckers in the diﬀerent stand types and site qualities. Only the stands included in the territories were considered as presence, wandering individuals were not taken into account. As the number of low forest (LF) stands was small, these data were eliminated from the statistical analysis. To estimate the threshold stand size of the type preferred by woodpeckers, diﬀerent size classes have been separated to compare the percentages of stands of diﬀerent size classes included in territories. Also an analysis of variance (ANOVA) has been made to compare the sizes of these stands used and not used by each species. To compare quantitative variables for the forest stands used by each woodpecker species in their breeding territories, analysis of variance (ANOVA) was combined with the comparison of means of each group (LSD, student’s t). Also the diﬀerences between woodlands and stand types have been tested. To reduce the complexity of the data set and to detect the interactions between species occurrence and environmental variables, a principal component analysis (PCA) based on the correlation matrix was carried out. In this analysis only beech forest stands with data available for the four variables were used (n = 243). To determine the importance of the amount of dead wood in the territories, diﬀerent ANOVA analyses have been done at diﬀerent scales. A ﬁrst analysis was made comparing the amount of dead wood in the stands included and not included in each woodpecker territories. As no results were found with this analysis, a more detailed analysis was made, repeating it for each quarter and for each stand type. Also, the amount of dead wood in large RLF stands is analysed. The comparisons between woodlands were made on means of each quantitative variable for each stand, weighted by the area of the stand. For all the ANOVA analyses, a test for normality has been carried out to fulﬁl the assumptions. All of the statistical analyses were conducted using the Statistica 4.5 for windows from Statsoft, Inc. [344]

1405 Results Forest stand classiﬁcation From the analysis of forest stands, it appears that approximately 40% of the area consist of high-quality sites (I and II), 30% of intermediate quality sites (III and IV), and 30% of low quality sites. In the low quality sites are included the non-exploitable sites due to environmental constraints (known as protection patches). Extraction priority was given to areas that are more productive or easily accessible (Schwendtner and Larran˜aga, 2001), so there is a certain imbalance in the age histogram according to site qualities (results not shown). Stand type distribution in the studied area is explained in Table 2.

Census As can be seen in Table 3, there were 11 reproductive pairs of white-backed woodpecker (7 pairs in Quinto Real, 1 pair in Erreguerena, 1 pair between Quinto Real and Erreguerena and 2 pairs in Legua Acotada) and 14 pairs of black woodpecker (7 pairs in Quinto Real, 4 pairs in Erreguerena, 1 pair between Quinto Real and Erreguerena and 2 pairs in Legua Acotada). Comparing these data with the densities found by Fernandez and Azkona (1996) on spring 1993 (Table 3), can be seen that the population remains stable with a downward trend in the case of the white-backed woodpecker and an upward trend in the case of the black woodpecker in the whole study area, but a clear decline is detected for the white-backed woodpecker in Erreguerena and for the black woodpecker in Legua Acotada. This decline is compensated in both cases with increases in Quinto Real and for the black woodpecker in Erreguerena. Table 2. Area (hectares), number of stands and average stand size (hectares) of the tree woodlands of Quinto Real: Quinto = Quinto Real; Erreg. = Erreguerena; Legua = Legua Acotada. Stand type

Area (ha)

Number of stands

Average stand size (ha)

Quinto Erreg. Legua Total Quinto Erreg. Legua Total Quinto Erreg. Legua Total 1. 2. 3. 4. 5. 6.

RLF RM RY HI LF OF

Total

355.1 382.6 236.7 346.1 200.5 18.3

300.7 140.3 233.1 152.0 0.0 3.6

260.4 265.3 148.6 135.4 6.3 16.1

916.2 788.2 618.3 633.5 206.8 37.9

33 54 32 58 31 4

32 16 22 38 0 1

17 8 17 19 1 4

82 88 71 115 32 9

10.8 7.1 7.4 6.0 6.5 4.6

9.4 8.8 10.6 4.0 3.6

15.3 14.7 8.7 7.1 6.3 4.0

11.2 9.0 8.7 5.5 6.5 4.2

1539.3 829.7 832.0 3200.9 212

109

76

397

7.3

7.6

10.9

8.1

The abbreviations of the stand types come from Table 1: RLF, stands of regular large ﬁnal crop trees; RM, stands of regular medium sized crop trees; RY, stands of regular young trees; HI, heterogeneous and irregular stands; LF, low forest stands. [345]

1406 Table 3. Number of territories and density (pairs/Km2) of each woodpecker species (WW = White backed woodpecker, BW = Black woodpecker) in all the forested area (Total) of the three Woodlands, and in each of them (Quinto = Quinto Real, Legua = Legua Acotada). The 2001 are the census carrried by the authors of this article and the 1993 are the census carried by Ferna´ndez and Azcona in 1993 (see Ferna´ndez and Azcona 1996). 2001

Number of territories Total Quinto Erreguerena Legua Density (pairs/Km2) Total Quinto Erreguerena Legua

1993

WW

BW

WW

BW

11 7.5 1.5 2

14 7.5 4.5 2

12 6 4 2

13 6 4 3

0.34 0.49 0.18 0.33

0.44 0.49 0.54 0.33

0.38 0.48 0.38 0.33

0.41 0.48 0.38 0.49

The territories of both species reveal certain mobility compared to the 1993 census carried out by Ferna´ndez and Azkona (1996). Many of the territories are still located in exactly the same forest stands. Others clearly occupy the sites situated between former territories, presumably using the areas that were less used on the 1993 territory distribution. In territories where felling has been carried out, the pairs aﬀected have moved out, probably to other unoccupied patches. Preferences according to stand classiﬁcation and site qualities Frequencies of sightings of the two species in the diﬀerent forest types show signiﬁcant diﬀerences (v2, p lt 0.005 for the black woodpecker and p < 0.00001 for the white-backed woodpecker). Both species show a clear preference for regular large ﬁnal crop stands (RLF). For both species there is also a distinct negative selection against heterogeneous (mixed with conifers) and uneven (mixed ages) stands (HI); this is less marked in the case of the black woodpecker. Sightings in regular medium sized crop stands (RM) and regular young stands (RY) do not reveal any signiﬁcant diﬀerences. Although most of the territories cover various forest stand types, nearly all cases – except in one black woodpecker and one white-backed woodpecker territories – include an RLF stand. When nests were found, they were usually located in this stand type, while the others – mainly RM and RY – are also defended and used for feeding. In the two territories identiﬁed in a place without RLF, there were RM stands of a considerable age (on the boundary of stands regarded as RLF). In one of these cases, the territory may have been moved from a recently exploited mature stand (RLF). Nevertheless, in [346]

1407 Table 4. Means comparison (LSD) of dominant height (DH), average age, average diameter (AD) and basal area (BA) from the Quinto Real Natural Resources Management Plan (Schwendtner and Larran˜aga 2001). Stand use

DH (m)

Age (years)

AD (cm)

BA (m2/ha)

Without territory WT without BT BT without WT BT and WT Woodlands Quinto Real Erreguerena Legua Acotada Stand types RLF RM RY HI LF

20.1 21.8 22.8 25.6

D C B A

97.8 C 109.9 B 104.9 B 148.7 A

26.4 31.5 27.4 33.8

22.7 23.1 22.1 26.5

20.4 B 22.1 A 21.9 A

108.3 A 106.5 A 96.5 B

28.0 AB 28.2 A 27.1 B

21.5 C 25.8 A 23.2 B

26.0 21.9 15.8 20.0 15.9

155.3 A 91.2 D 45.3 E 119.6 B 113.3 C

36.7 28.8 15.0 28.4 25.6

26.9 28.5 13.0 21.9 16.9

A B D C D

C B C A

A B D B C

B B B A

B A E C D

Stands with black woodpecker territories (BT), with white-backed woodpecker territories (WT), both or none, the diﬀerent woodlands, and stand types (see Table 1: RLF, stands of regular large ﬁnal crop trees; RM, stands of regular medium sized crop trees; RY, stands of regular young trees; HI, heterogeneous and irregular stands; LF, low forest stands) are compared. Within each comparison, diﬀerent letters represent signiﬁcative mean diﬀerences (p < 0.05).

all cases in which a territory is included in only one big stand (3 white-backed woodpecker territories and 4 black woodpecker territories), this is a RLF stand. No signiﬁcant diﬀerences were found between the site quality of the stands used by each species with those not used. Therefore, woodpeckers do not appear to choose stands for their site quality, but rather for the physiognomic characteristics of the forest which is best reﬂected in the stand classiﬁcation (see Table 1 and 4). This supports the option for only harvesting stands with high site quality, and conserving the poorer quality sites with well-preserved mature forest (RLF).

Stand size One of the typical questions that arises from the management of these forests concerns the minimum stand size that must be left as mature forest for these species to establish their territory. To answer this question, a study was conducted on the size diﬀerences between RLF stands where territories were present and those where they were not. Figure 1 illustrates that the stands where territories for both species were present were considerably larger than those where there were not. The RLF stands in which the black woodpecker appears have an average size of 24 ha, while those of the white-backed woodpecker average 19 ha. The [347]

1408

Figure 1. Analysis of variance on the regular large ﬁnal crop trees (RLF) forest stands size according to their occupation for each woodpecker species: BN, stands where the black woodpecker territories are studied; WN, stands where the white-backed woodpecker does not appear; WT, stands where the white-backed woodpecker territories are situated. The rectangles represent the standard error and the lines the standard.

Figure 2. Percentage of RLF stands of diﬀerent sizes included in territories of black woodpecker (triangles) and white backed woodpecker (circles).

actual surfaces required are probably somewhat greater, since some territories occupy more than one mature stand. In fact, most RLF stands with an area exceeding 30 ha (8 stands) are included in a territory, except three stands in which recent cutting was carried out. In Figure 2 can be seen the percentages of the diﬀerent sizes of RLF stands that are included in the territories of each species. The total percentage for each species is higher that 100 because one territory usually extend over several stands. The occupation percentage in large stands is much higher than that for small stands. [348]

1409 Forest physiognomy Although the stand types reveal considerable diﬀerences with regard to habitat selection by Picidae, it is still basically a subjective classiﬁcation that depends on the criterion of the forest engineer responsible for the management plan. For this reason, and in order to assess the classiﬁcation more objectively, an analysis of the quantitative variables was performed using variance analysis (ANOVA), LSD means comparison and principal component analysis (PCA). There was a considerable diﬀerence between stands where the two species shared territories and the other stands (see Table 4). These stands had the tallest, oldest and largest trees, and also the largest basal area. Stands with a territory of only one of both species have intermediate values, and those with no territories have the lowest values. The white-backed woodpecker clearly prefers forests with a larger average tree diameter. However, when both woodpeckers do not occur in the same area, it selects stands of a lower height than those chosen by the black woodpecker. The ﬁrst PCA axis represents 72.6% of the total variance, while the second axis represents 12.8% (Figure 3a). On the same axes, Figure 3b shows the larger RLF stand of each territory for the black and white-backed woodpecker. It can be noted that the ﬁrst axis is a good predictor for the presence or absence of each species. Their territories were linked to high values of the ﬁrst axis, which corresponds to high values of the four morphometric variables used. The second axis separates the four variables, but there is not a clear relationship with territories and it is much less reliable.

Dead wood When stands of the three woodlands of Quinto Real were used, no signiﬁcant diﬀerences were found for total dead wood (number of trunks per ha) between stands used by each species or those that were not used, probably because many stands with considerable amounts of dead wood were not used by neither of the two species. Nevertheless, there were notable diﬀerences in the amount of thin dead wood (from 10 to 20 cm), i.e., the type of dead wood most abundant and most representative (Table 5). Comparing only stands from quarters that had comparatively little dead wood, signiﬁcant diﬀerences were found among stands where the white-backed woodpecker appeared, particularly for the 20–30 cm range (p < 0.05). This species did not choose stands with more dead wood in quarters where it was abundant, but in those quarters with little dead wood, it did a positive selection for stands with more dead wood. For the dead wood in RLF, considerable diﬀerences might be identiﬁed between stands where the white-backed woodpecker was found and stands where it was absent for the two largest diameter classes of dead wood [349]

1410

Figure 3. Principal components analysis of the stands described by the four variables that describe the forest structure. The ﬁrst two axis do account for the 85% of the variance. (a) scatter diagram of all the stands; symbols indicate the stand classiﬁcation according to Table 1. RLF, stands of regular large ﬁnal crop trees; RM, stands of regular medium sized crop trees; RY, stands of regular young trees; HI, heterogeneous and irregular stands; LF, low forest stands. (b) scatter diagram of the larger RLF stand of each woodpecker territory on the same axis that (a). Circles represent the black woodpecker territories and triangles the white backed woodpecker territories. Also the descriptors of the four variables that describe the forest structure are represented. BA, basal area; DH, dominant height; AD, average diameter; AA, average age.

(20–30 cm and >30 cm; p < 0.001). This implies that the species clearly chooses those RLF that contain a larger amount of dead wood. This relationship remains signiﬁcant comparing the diﬀerences between large-size RLF stands (>15 ha) whether the white-backed woodpecker is present or not. For the black woodpecker no diﬀerences were found for all the comparisons. [350]

1411 Table 5. Standing dead wood on the seven quarters of Quinto Real Woodlands: three in Quinto Real (Q1,Q2, Q3), two in Erreguerena (E1, E2) and two in Legua Acotada (L1, L2). Quarters

Standing dead trees Trunk diameter

Q1 Q2 Q3 E1 E2 L1 L2

10–20 cm

20–30 cm

>30 cm

DBA

22.2 A 17.4 A 12.0 B 7.0 B 6.4 B 22.7 A 4.0 B

5.4 5.7 4.6 4.5 6.9 3.5 1.2

2.0 1.1 1.6 0.4 1.7 0.7 0.6

0.915 0.728 0.645 0.394 0.666 0.662 0.208

AB AB AB AB A AB B

A A A A A A A

A AB AB B AB AB B

Trunk number per ha is given for each of the three diameter classes and dead trees basal area (DBA) is given in m2/ha. Within each column, diﬀerent letters indicate signiﬁcant diﬀerences (p < 0.05).

Discussion Although the overall densities of the two woodpecker species remain rather stable for each of the woodlands of Quinto Real, according to the 1993 census (Ferna´ndez and Azkona 1996) and the one obtained in 2001, it appears that the white-backed woodpecker is declining in Erreguerena, and the black woodpecker is declining in Legua Acotada and increasing in Erreguerena. These diﬀerences are probably due to forestry management. Nevertheless, the Quinto Real populations have increased, which seems to indicate that management has been more appropriate than in Erreguerena and Legua Acotada. It does not seem that this diﬀerence can be explained by other ecological variables, because topography, climate, and other non-anthropic factors are quite similar. Over the years both species remained faithful to their breeding territories (as also observed by McClelland and McClelland 1999). By comparing both censuses (1993–2001), it appears that there have been some shifts of territories, possibly due to forestry activities. A possible explanation could be that changes on the forest structure due to felling in a woodpecker territory, (a RLF stand is converted on a RY stand) may cause a territorial movement towards another place with more mature forest, thus ‘pushing’ adjacent territories. One of the most obvious conclusions is that the most suitable habitat for both species is the mature forest stands (RLF). These are also referred to in the Natural Resources Management Plan (Schwendtner and Larran˜aga 2001) as stands where ﬁnal cutting is most likely to be carried out because these sites have the largest amount of timber trees for felling. If the exploitation of these woodlands by town councils is intensiﬁed, these stands will soon become extremely scarce. A negative selection is observed, in both species, against heterogeneous and irregular stands. The same occurs within the stands in which other species [351]

1412 rather than beech are dominant (Larix, Pinus, Quercus). Although the black woodpecker occasionally feeds in these forests, the white-backed woodpecker has been found exclusively in monospeciﬁc beech forests. The dominant height (26 m), age (149 years), mean diameter (34 cm) and basal area (27 m2/ha) of stands where both the black and white-backed woodpecker territories coincide may help to determine the characteristics that the stands left for conservation should have (5% of the total). A suﬃcient amount of this type of stand should be left in the rest of the woodlands to ensure that the population of these species do not decrease. It has been conﬁrmed that the size of the RLF stand is another decisive factor for both species in establishing breeding territories, with minimum sizes close to 20–30 ha. As these are territorial birds, it does not appear to be a good idea to leave all the RLF stands grouped in one area. It seems much more appropriate to keep suﬃciently large (>30 ha) RLF patches separated from one other (the number of patches depends on the desired size of the population). Moreover, given that there is no correlation between the site quality and the distribution of territories, it is advisable to concentrate exploitation in the best sites with short felling cycles. The worst sites should be left unexploited in order to fulﬁll the above objectives. The amount of dead wood does not appear to be the main factor for choosing breeding territories for these birds at the scale of the whole study area, probably because it is very abundant in most of the area and therefore it is not a limiting factor. In fact, when the analysis is concentrated in the areas where dead wood is scarcer, this variables becomes an important factor for the distribution of the white-backed woodpecker territories, but the black woodpecker territories distribution do not seem to be aﬀected by this variable. This can be explained by the diet of the black woodpecker, which feeds mainly on ants, and is not so dependent on dead wood. The white-backed woodpecker territories distribution shows a relationship with the amount of thicker standing dead wood in the quarters where total dead wood is less abundant. Also the amount of dead wood seems important when comparing the territories occupancy frequencies between all RLF stands and also only with large RLF stands. But not all dead wood classes are of the same importance: thick standing dead wood seems to be more important than other classes of dead wood. This reinforce the importance of well conserved, large enough RLF stands, also with suﬃcient amount of standing thick dead trees, that could be increased by ringing some trees if necessary. It is more important in the places where the surroundings have less dead wood. There are other authors that have also found important the amount of dead wood for the woodpeckers, in particular with the specialist species (Angelstam et al. 2003; Butler et al. 2004). Although the number of felling activities is insuﬃcient to analyse their eﬀect from a statistical point of view, their eﬀects on the territories of both species seem to be very clear. When a RLF stand included in a 1993 territory disappeared, the territory has ‘moved’ to include another RLF stand in it. In this [352]

1413 study, the movement of territories have not been analysed, and we do not know if the new territories (or even the old ones) are done by the same individuals or diﬀerent ones. As example, the black woodpecker territory that has disappeared in Legua Acotada, correspond to a place where the RLF stand included in it has been fallen down, and no mature stand can be found nearby. At the moment in Legua Acotada it seems unlikely that the population of both species can be increased to levels similar to those in Quinto Real unless management is changed, for example by using smaller stand sizes and leaving the small number of mature RLF stands (there were 3 in 1993, but one has already been harvested). There is a territory of each species in each of these stands, but the nearby forests are regular young stands (RY) or ﬁnal cuttings that are extremely homogenous and have been exhaustively ‘cleaned out’. As a result, they are of no use to the picidae. If the RLF stands that remain are cut down, the territories in them will surely disappear. Nevertheless, the situation in Erreguerena is slightly more encouraging. There are suﬃciently large RLF stands in this area. Although it appears that several white-backed woodpecker territories have disappeared due to recent cuttings, they may have established in other RLF stands that were unoccupied. Black woodpecker seems to be attracted by these felling activities, possibly due to an increase of felled dead wood and therefore an increase of the amount of ants. Appropriate management would mean cutting the unoccupied stands in order not to disturb existing pairs. As the territories may vary in location, it is necessary to conduct yearly censuses in order to determine the situation before planning felling activities. The patchwork situation in Quinto Real – stands that are relatively small, with a relatively high abundance of large enough RLF stands suﬃciently separated ones from the others – has allowed the creation of a large number of breeding territories. Nevertheless, it is advisable to exploit only the stands that remain between territories and leave those that currently contain breeding territories. Another general recommendation from the results is to leave enough dead wood in all stands and to leave dead trees standing because this is where the white-backed woodpecker mainly feeds. Girdling can be carried out instead of harvesting in some cases, since this technique leaves standing dead wood. Some management plans which aimed at protecting yew trees (Taxus baccata) by girdling the beech trees that overshadow them, may be also beneﬁcial to specialist species (see Carlson 2000). White-backed woodpeckers are also beneﬁcial for the health of the beech forest as it eats a lot of the forest plagues, and keeps them under control (Butler and Schlaepfer 2003).

Acknowledgements We gratefully acknowledge Carmelo Ferna´ndez for his support and advice from the outset of this study, and Miguel A´ngel Salas for the information he [353]

1414 provided about Picidae. Our thanks also to the ‘‘Seccio´n de Montes del Servicio de Conservacio´n de la Biodiversidad del Gobierno de Navarra’’ for their support and to the Foreign Language Co-ordination Oﬃce at the Polytechnic University of Valencia for their help in translating this paper.

References Angelstam P. 1990. Factors determining the composition and persistence of local woodpecker assemblages in taiga forests in Sweden – a case for landscape ecological studies. In: Carlson A. and Aulen G. (eds), Conservation and Management of Wo‘odpecker Populations. Swedish University of Agricultural Sciences, Department of Wildlife Ecology, Uppsala, pp. 147 – 191. Angelstam P. and Mikusinski G. 1994. Woodpecker assemblages in natural and managed boreal and hemiboreal forest – a review. Annales Zoologici Fennici 31: 157 – 172. Angelstam P., Butler R., Lazdinis M., Mikusinski G. and Roberge J.M. 2003. Habitat thresholds for focal species at multiple scales and forest biodiversity conservation – dead wood as an example. Annales Zoologici Fennici 40(6): 473 – 482. Aule´n G. 1988. Ecology and distribution history of the White-backed Woodpecker Dendrocopos leucotos in Sweden. Ph.D. Thesis, Report 14, Swedish University of Agricultural Sciences Department of Wildlife Ecology, Uppsala. Aule´n G. and Lundberg A. 1991. Sexual dimorphism and patterns of territory use by the Whitebacked Woodpecker Dendrocopos leucotos. Ornis Scandinavica 22: 60 – 64. Avery M. and Leslie R. 1990. Birds and Forestry. T. & A.D. Poyser, London. Bibby C.J., Burgess N.D. and Hill D.A. 1992. Bird Census Techniques. Academic Press, London. Blanco J.C. and Gonza´lez J.L. 1992. Libro Rojo de los Vertebrados de Espan˜a. ICONA, ed. Ministerio de Agricultura Pesca y Alimentacio´n, Madrid. Brooks J. 1985. Handbook of the Birds of Europe, the Middle East and North Africa. Vol IV. Oxford University Press. Butler R., Algelstam P., Ekelund P. and Schlaepfer R. 2004. Dead wood threshold values for the three-toed woodpecker presence in boreal and subalpine forest. Biological Conservation 119: 305 – 318. Butler R. and Schlaepfer R. 2003. Three-toed woodpecker as an alternative to bark beetle control by traps?. In: Pechacek P and d’Oleire-Oltmanns W. (eds), International Woodpeckers Symposium. Berchtesgaden, pp. 13 – 26. Carlson A. 2000. The eﬀect of habitat loss on a deciduous forest specialist species: the Whitebacked Woodpecker (Dendrocopos leucotos). Forest Ecology and Management 131: 215 – 221. Conner R. 1979. Seasonal changes in woodpecker foraging methods: Strategies for winter survival Pages 95 – 105. In: Dickson J.G., Conner R.N., Fleet R.R., Kroll J.C. and Jackson J.A. (eds), The role of insectivorous birds in forest ecosystems. Academic Press, NY, pp. 381. Cramp S. (ed.) 1985. Handbook of the Birds of Europe, the Middle East and North Africa. Vol. 4. Oxford, Oxford University Press. Cuisin M. 1967. Essai d’une monographie du Pic noire (Dryocopus martius). Oiseau Rev Fr Ornithol. 37:163 – 192, 37:285 – 315, 38:20 – 52, 38:103 – 126, 38:209 – 224. Ferna´ndez C., Azkona P. and Lorente L. 1994. Corologı´ a y caracterizacio´n del ha´bitat del pico dorsiblanco (Dendrocopos leucotos) en el Pirineo occidental espan˜ol. Ardeola 41(2): 135 – 140.SEO. Ferna´ndez C. and Azkona P. 1996. Inﬂuence of forest structure on the density and distribution of the White-backed Woodpecker Dendrocopos leucotos and black Woodpecker Dryocopus martius in Quinto Real (Spanish western Pyrenees). Bird Study 43: 305 – 313. British Trust for Ornithology. Fleishman E., Blair R.B. and Murphy D.D. 2001. Empirical validation of a method for umbrella species selection. Ecological Applications 11: 1489 – 1501. [354]

1415 Fleishman E., Jonsson B.G. and Sjagren-Gulve P. 2000. Focal species modeling for biodiversity conservation. Ecological Bulletins 48: 85 – 99. Gobierno De Navarra 1990. Ley Foral 13/1990, de 31 de diciembre. Proteccio´n Y Desarrollo del Patrimonio Forestal de Navarra. Boletı´ n Oﬁcial de Navarra nu´m. 6, de 14 de enero de 1991. Gobierno De Navarra 1992. Decreto Foral 59/1992, de 17 de febrero. Reglamento de Montes en Desarrollo de la Ley Foral 13/1990, de 31 de Diciembre, de Proteccio´n y Desarrollo del Patrimonio Forestal de Navarra. Boletı´ n Oﬁcial de Navarra nu´m. 48, de 20 de abril de 1992. Gobierno De Navarra 1998. Plan Forestal de Navarra. www.cfnavarra.es, . Gobierno De Navarra 1999. Estrategia Navarra para la Conservacio´n de la Biodiversidad. www.cfnavarra.es. Hogstad O. 1970. On the ecology of the three-toed woodpecker Picoides tridactylus (L.) outside the breeding season. Nytt Magasin for Zoologi 18: 221 – 227. Imbeau L. and Desrochers A. 2002. Foraging ecology and use of drumming trees by three-toed woodpeckers. Journal of Wildlife Management 66: 222 – 231. Martinez-Vidal R. 1999. Ha´bitat de crı´ a del pito negro (Dryocopus martius) en las Sierras de Cadı´ y Moixero´: caracterizacio´n, tipologı´ a y pe´rdidas de a´rboles nido. Gestio´n y Conservacio´n de la biodiversidad en ecosistemas forestales. C.T.F.C, Solsona. Mcclelland B. and Mcclelland P. 1999. Pileated woodpecker nest and roost trees in Montana: links with old-growth and forest ‘‘health’’. Wildlife Society Bulletin 27(3): 846 – 857. Mikusinski G. and Angelstam P. 1997. European woodpeckers and anthropogenic habitat change: a review. Vogelwelt 118: 277 – 283. Murphy E.C. and Lehnhausen W.A. 1998. Density and foraging ecology of woodpeckers following a stand-replacement ﬁre. Journal of Wildlife Management 62: 1359 – 1372. Nilsson S.G. 1992. Population trends and ﬂuctuations in Swedish woodpeckers. Ornis Svecica 2: 13 – 21. Purroy F.J. 1972. El pico dorsiblanco Dendrocopos leucotos del Pirineo. Ardeola 20: 145 – 158. Purroy F.J., Alvarez A. and Pettersson B. 1990. Bosque y fauna de vertebrados terrestres en Espan˜a. Ecologı´ a 1: 349 – 363. Roberge J.M. and Angelstam P. 2004. Usefulness of the umbrella species concept as a conservation tool. Conservation Biology 18(1): 1 – 10. Schwendtner O. and Larran˜aga A. (coords.) 2001. Sexta Revisio´n de la Ordenacio´n del grupo de Montes de Quinto Real. BASOA/Gobierno de Navarra. Simberloﬀ D. 1999. The role of science in the preservation of forest biodiversity. Forest Ecology and Management 115: 101 – 111. Svenssons S.E. 1979. Census Eﬃciency and number of visits to a study plot when estimating bird densities by the territory mapping method. Journal of Applied Ecology 16: 61 – 68. Tellerı´ a J.L. 1986. Manual para el Censo de los Vertebrados Terrestres. Ed. Raı´ ces, Madrid. Tellerı´ a J.L. 1992. Gestio´n forestal y conservacio´n de las aves en Espan˜a peninsular. Ardeola 39: 99 – 114. Tucker G.M. and Heath M.F. (eds) 1994. Birds in Europe – their conservation status. BirdLife International, Conservation Series No. 3, Cambridge. Voous K.H. 1947. On the history of the distribution of the genus Dendrocopos. Limosa 20: 1 – 142.

[355]

Biodiversity and Conservation (2006) 15:1417–1424 DOI 10.1007/s10531-005-0308-4

Springer 2006

A reconsideration of the reproductive biology of the Atlantic forest in the Volta Velha Reserve STEVEN M. VAMOSI Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Canada, T2N 1N4; E-mail: [email protected] Received 6 October 2004; accepted in revised form 1 June 2005

Key words: Brazil, Dioecy, Floristic survey, Reproductive biology, Seed shadow eﬀect Abstract. Published species lists that include breeding system designations of vascular plants are rare in the primary literature and, thus, can be potentially valuable sources of information for comparative studies. The published list for vascular plants in the Volta Velha Reserve suﬀered from a number of errors, notably applying the designation of monoecious to all species with imperfect ﬂowers. Here, I reconsider the breeding systems for 97 woody vascular plant species. The majority of species initially categorized as monoecious are found to be hermaphroditic. I then examine the relationship between breeding system and numbers of individuals in a 1 ha plot. The mean number of individuals was marginally higher in dioecious than hermaphroditic and monoecious species combined. Furthermore, although only 28% of the species were characterized as possessing a dioecious breeding system, 42% of the individuals encountered belonged to a dioecious species. These results suggest that dioecious species can, at least under certain circumstances, overcome the reductions in the number of seed-bearing individuals and mate assurance that accompany possessing spatially segregated sexes.

Introduction Understanding the mechanisms responsible for the origination and maintenance of breeding system variation in ﬂowering plants has long been a fundamental issue in evolutionary biology (e.g., Darwin 1877, 1878; Geber et al. 1999; Heilbuth 2001). Although the vast majority of angiosperm species are hermaphroditic (i.e., perfect ﬂowers), a number of other breeding systems also occur. Dioecy (imperfect ﬂowers, with separate male and female individuals), for example, is present in approximately 6% of species globally (Renner and Ricklefs 1995), although its incidence in local ﬂoras can be as high as 28% (Arroyo and Squeo 1990). Although relatively rare and possessing a wide taxonomic distribution (Yampolsky and Yampolsky 1922; Renner and Ricklefs 1995; Heilbuth 2001; Vamosi and Vamosi 2004), many authors have commented on the associations between these breeding systems and various ecological and life history traits. Dioecious species, for example, frequently have a tropical distribution, woody growth form, ﬂeshy fruits, and plain white ﬂowers (reviewed by Vamosi and Vamosi 2004). [357]

1418 In an eﬀort to explore additional correlations, I have been searching monographs, books and papers for information on breeding systems. A recent article in this journal on the reproductive biology of plants from a rainforest in southern Brazil provided the breeding systems for 97 woody species in 38 families (Negrelle 2002). Many ﬂoristic surveys do not contain species-speciﬁc information (e.g., Flores and Schemske 1984); hence, such lists can be quite useful. Unfortunately, the list is currently misleading in its present form primarily because of the way in which taxa were scored for breeding system. Negrelle (2002, p. 891) stated that: ‘deﬁnitions of dioecy and monoecy followed standard deﬁnitions, except in those few cases where previous literature identiﬁed monoecious trees as functionally dioecious.’ However, the designation of monoecious (imperfect ﬂowers, with staminate and carpellate ﬂowers on the same plant) was applied to all species thought to possess imperfect ﬂowers, including hermaphroditic and polygamous species. For example, four species in the family Annonaceae were scored as monoecious, although the vast majority of the ca. 2300 species in this family are hermaphroditic (Kessler 1993) and monoecy is known only from a single genus (Uvariopsis Engl.) not encountered in the present survey. It seems likely that the source of the coding error stems from an overly liberal interpretation of the etymology of monoecy (i.e., ‘one home’). Furthermore, I encountered a smaller number of errors in breeding system designations in the list. For example, all of the Ocotea Aubl. (Lauraceae) species encountered in the survey were scored as being dioecious. Two of the seven species are, in fact, hermaphroditic (Rohwer 1986). Although such errors are nearly inevitable when dealing with breeding systems, their presence, in addition to the unorthodox scoring method, warranted a reconsideration of the entire data set. In addition to breeding system designations, Negrelle (2002) also provided potentially valuable data on the number of individuals, basal area occupied, and importance value (which accounts for density, frequency and dominance) for each species in a 1 ha plot. Such data can be used to explore the ecological consequences of spatial segregation, such as reduced mate assurance and fewer seed-bearing individuals (hereafter, seed shadow eﬀect), that are predicted to aﬀect plant species with spatially separate sexes (e.g., Pannell and Barrett 1998; Heilbuth et al. 2001). Reduced mate assurance may be alleviated if the density of individuals is high, as pollen is more likely to be transferred to females. Similarly, the disadvantage of a reduction in the number of seed-dispersing individuals by half that accompanies the evolution of dioecy will be alleviated if more females are present in a dioecious population.

Methods The Volta Velha Reserve is located in the Municipality of Itapoa´, Santa Catarina State, Brazil (2604¢ S, 4838¢ W). Although south of the Tropic of Capricorn, the ﬂora in this Reserve was found to be similar to that of a number [358]

1419 of Neotropical sites (Negrelle 2002). A total of 398 species and 99 families of vascular plants have been collected in the Volta Velha Reserve, of which the vast majority are angiosperms. In a single 1 ha plot, 734 individuals with a diameter at breast height (DBH) ‡10 cm from 97 species were sampled (Negrelle 2002; pp. 910–911). Information on breeding systems for the 97 species in the 1 ha plot was obtained from a variety of sources, especially Bush (1995), Charlesworth (1985), Hutchinson (1959), Kubitzki et al. (1993), Kubitzki (2004) and Watson and Dallwitz (1992 onwards). I consulted authorities (J. Rohwer, M. Freitas and J. Pipoly III, and L. Bohs, respectively) for Ocotea, Rapanea (= Myrsine) and Solanum species. For all species, I ﬁrst consulted the Families and Genera of Vascular Plants volumes, and subsequently used other sources for families that have not yet been catalogued in this series and for genera that have more than one breeding system represented by their constituent species. A complete list of sources is available from the author on request. Because only dioecious species are expected to suﬀer from a seed shadow eﬀect (Heilbuth et al. 2001), I compared number of individuals, basal area and importance value (Negrelle 2002, pp. 910–911) of dioecious species to hermaphroditic and monoecious species combined. Indeed, hermaphroditic and monoecious species were not signiﬁcantly diﬀerent for any of the measures (p > 0.55 in all cases). The three measures are related and produced qualitatively similar results, thus I present only the results for number of individuals. I applied a square root transformation on the number of individuals per species prior to conducting a one-way ANOVA. Means are presented as the square of the mean of square-root transformed values.

Results and discussion The main eﬀect of re-scoring breeding systems was, perhaps not surprisingly, to drastically reduce the apparent prevalence of monoecious species (Table 1). In agreement with other studies, hermaphroditic species were most common (68%), followed by dioecious and androdioecious (28%) species combined, and monoecious and polygamous (4%) species combined. These values are remarkably similar to those observed for a sample of 139 tree species from a tropical rainforest in Mexico (Ibarra-Manrı´ quez and Oyama 1992). In Los Tuxtlas, the frequency of species with the diﬀerent sexual systems was reported as 63, 27, and 9%, respectively. The apparently high incidence of dioecy in the current survey likely reﬂects the fact that only individuals with DBH ‡10 cm were sampled. Because of the correlation between dioecy and a woody growth form, especially in the tropics (Vamosi and Vamosi 2004), the incidence of dioecy in the Volta Velha Reserve will almost certainly be lower with the inclusion of herbaceous species (see also Ibarra-Manrı´ quez and Oyama 1992). There was a marginally higher number of individuals in dioecious (mean = 7.92) than hermaphroditic + monoecious (mean = 4.81) species [359]

1420 Table 1. Breeding system of 97 plant species surveyed in a 1 ha plot of the Volta Velha Reserve. Podocarpus sellowii (Podocarpaceae) is a gymnosperm, whereas the remaining species are angiosperms. Family

Species

Breeding System

Anacardiaceae Annonaceae Annonaceae Annonaceae Annonaceae Apocynaceae Aquifoliaceae Aquifoliaceae Aquifoliaceae Aquifoliaceae Arecaceae Bignoniaceae Bombacaceae [= Malvaceae] Burseraceae Caesalpinaceae Celastraceae Chrysobalanaceae Chrysobalanaceae Clethraceae Clusiaceae Clusiaceae Clusiaceae Combretaceae Cunoniaceae Elaeocarpaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Fabaceae Lauraceae Lauraceae Lauraceae Lauraceae Lauraceae Lauraceae Lauraceae Lauraceae Lauraceae Lauraceae Lauraceae Lauraceae Lauraceae Malphigiaceae Melastomataceae

Tapirira guianensis Aubl. Annona cacans Warm. Duguetia lanceolata A. St.-Hil. Guatteria australis A. St.-Hil. Xylopia brasiliensis Spreng. Aspidosperma parvifolium A. DC. Ilex dumosa Reissek I. integerrima Reissek I. pseudobuxus Reissek I. theezans Mart. ex Reissek Attalea dubia (Mart.) Burret Tabebuia alba (Cham.) Sandwith Spirotheca passiﬂoroides Cuatrec.

D H H H H H D D D D M H H

Protium kleinii Cuatrec. Copaifera trapezifolia Hayne Maytenus robusta Reissek Hirtella hebeclada Moric. ex DC. Parinari sp. Clethra scabra Pers. Calophyllum brasiliense Cambess. Clusia parviﬂora Humb. & Bonpl. ex Willd. Garcinia gardneriana (Planch. & Triana) Zappi Buchenavia kleinii Exell Weinmannia paulliniifolia Pohl Sloanea guianensis (Aubl.) Benth. Alchornea triplinervia (Spreng.) Mu¨ll. Arg. Aparisthmium cordatum (Juss.) Baill. Hyeronima alchorneoides Allema˜o Maprounea guianensis Aubl. Pera glabrata (Schott) Poepp. ex Baill. Andira anthelminthica Benth. Aiouea saligna Meisn. Aniba ﬁrmula (Nees & C. Mart.) Mez Nectandra grandiﬂora Nees & C. Mart. ex Nees Nec. megapotamica (Spreng.) Mez Nec. oppositifolia Nees & Mart. Ocotea aciphylla (Nees) Mez O. dispersa (Nees) Mez O. elegans Mez O. glaziovii Mez O. odorifera (Vellozo) Rohwer O. pulchella Mart. O. pulchra Vattimo Persea venosa Nees & Mart. ex Nees Byrsonima ligustrifolia St. Hilaire Miconia cabuc¸u Hoehne

D H H H H H AD D D H H H D D D M D H H H H H H H D H D D D D H H H

[360]

1421 Table 1. (Continued). Family

Species

Breeding System

Melastomataceae Melastomataceae Mimosaceae Mimosaceae Monimiaceae Monimiaceae Myristicaceae Myrsinaceae

M. cubatanensis Hoehne Mouriri chamissoana Cogn. Inga heterophylla Willd. Pithecellobium langsdorﬃi Benth. Mollinedia triﬂora (Spreng.) Tul. Mol. uleana Perkins Virola oleifera (Schott) A.C. Sm. Conomorpha peruviana A. DC. [= Cybianthus peruvianus (A. DC.) Miq.] Rapanea ferruginea (Ruiz & Pav.) Mez [= Myrsine coriacea (Sw.) R. Br. ex Roem. & Schult.] R. venosa (A. DC.) Mez [= Myrsine venosa A. DC.] Aulomyrcia obscura O. Berg Blepharocalyx salicifolius (Kunth) O. Berg Calyptranthes concinna DC. Ca. lucida Mart. ex DC. Campomanesia guaviroba (DC.) Kiaersk. Eugenia cerasiﬂora Miq. E. obovata Poir. E. subavenia O. Berg E. tristis D. Legrand E. umbelliﬂora O. Berg Gomidesia aﬃnis (Cambess.) D. Legrand Go. schaueriana O. Berg Marlierea eugeniopsoides (D. Legrand & Kausel) D. Legrand Ma. reitzii D. Legrand Myrceugenia campestris (DC.) D. Legrand & Kausel My. reitzii D. Legrand & Kausel Myrcia acuminatissima O. Berg My. fallax (Rich.) DC. My. pubipetala Miq. Neomitranthes cordifolia (D. Legrand) Legr. Neo. glomerata (D. Legrand) D. Legrand Psidium cattleyanum Sabine Ouratea parviﬂora (DC.) Baillon Heisteria silvianii Schwacke Tetrastylidium grandifolium (Baill.) Sleumer Chionanthus ﬁliformis (Vell.) P.S. Green Podocarpus sellowii Klotzsch ex Endl. Coccoloba ovata Benth. Prunus sellowii Koehne Amaioua guianensis Aubl. Faramea marginata Cham. Posoqueria latifolia (Rudge) Roem. & Schult. Psychotria carthagenensis Jacq. Esenbeckia grandiﬂora Mart. Cupania oblongifolia Mart. Matayba guianensis Aubl.

H H H H D D D D

Myrsinaceae Myrsinaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Myrtaceae Ochnaceae Olacaceae Olacaceae Oleaceae Podocarpaceae Polygonaceae Rosaceae Rubiaceae Rubiaceae Rubiaceae Rubiaceae Rutaceae Sapindaceae Sapindaceae

[361]

D D H H H H H H H H H H H H H H H H H H H H H H H H H H D D H D H H H H M PG

1422 Table 1. (Continued). Family

Species

Breeding System

Sapotaceae Sapotaceae Sapotaceae Solanaceae Styracaceae

Manilkara subsericea (Mart.) Dubard Pouteria beaurepairei (Glaz. & Raunk.) Baehni Po. venosa (Mart.) Baehni Solanum inaequale Vell. [= S. pseudoquina A. St.-Hil.] Styrax glabratus Schott

H H H H H

AD = androdioecious, D = dioecious, M = monoecious, H = hermaphroditic, PG = polygamous. To facilitate comparison with the original list (Negrelle 2002), all original species and family names are given, with entries in square parentheses indicating the currently accepted synonym.

combined (p = 0.075) (Figure 1). The dioecious species Tapirira guianensis (Anacardiaceae) and Aparisthmium cordatum (Euphorbiaceae) had the highest and second highest number of individuals, respectively, and seven of 18 (39%) species with ‡10 individuals were dioecious. Overall, 309 of the 734 (42%) individuals belonged to a dioecious species, which is signiﬁcantly greater than the proportion of species that were dioecious (contingency test, p = 0.007). One possible explanation for this result is that the strong correlation between a dioecious breeding system and zoochory in this ﬂora helps these species overcome the seed shadow eﬀect (Heilbuth et al. 2001). Birds are thought to disperse seeds from ﬂeshy fruits to such an extent as to obscure the spatial segregation that accompanies dioecy (e.g., Nanami et al. 1999). Although there are few comparable studies (Ibarra-Manrı´ quez and Oyama 1992; Lieberman and Lieberman 1994; Nanami et al. 1999; Pitman et al. 2001; Chazdon et al. 2003), 10

Square root number of individuals

9 8 7 6 5 4 3 2 1 0

Dioecious

Nondioecious

Breeding system Figure 1. Square root transformed number of individuals with a dioecious (diamonds) or nondioecious (hermaphroditic and monoecious; triangles) breeding system in a 1 ha plot of the Volta Velha Reserve. N = 27 dioecious species, 70 nondioecious species. [362]

1423 an overrepresentation of individuals from dioecious species has been documented into two other forests. Ibarra-Manrı´ quez and Oyama (1992; p. 387) remarked that: ‘some dioecious species are common in open large patches of the forest … and probably the density of these species is higher than that of plants with hermaphroditic or monoecious ﬂowers.’ On Mt. Mikasa, Japan, the dioecious Podocarpus nagi (Thunb.) Makino (Podocarpaceae) and Neolitsea aciculata (Blume) Koidz. (Lauraceae) were numerically the most dominant species, accounting for 72 and 20%, respectively, of 368 plants observed >5 cm diameter at breast height (Nanami et al. 1999). Although the other community members were not discussed in detail, the remaining 8% of plants were represented by 12 other species. Given the relative rarity of dioecy among all angiosperms, such dominance of dioecious species in local ﬂoras will likely be shown to occur only under particular circumstances (e.g., forests in sub- and tropical-regions). Further explorations of the relative representation of individuals with a dioecious breeding system, especially in tropical vs. temperate ﬂoras, are likely to reveal interesting insights into the costs and beneﬁts of the evolution and maintenance of spatially separated sexes (Heilbuth et al. 2001; Vamosi and Vamosi 2004).

Acknowledgements I wish to express my sincere thanks to L. Bohs, M. Freitas, J. Pipoly III, J. Rohwer, and T. Taggart for their assistance with breeding system designations, J. Ricketson for kindly putting me in touch with J. Pipoly III, J. Vamosi and an anonymous reviewer for insightful comments, and the Natural Sciences and Engineering Research Council of Canada and University of Calgary URGC Starter Grant for ﬁnancial support. References Arroyo M.T.K. and Squeo F. 1990. Relationship between plant breeding systems and pollination. In: Kawano S. (ed.), in Biological Approaches and Evolutionary Trends in Plants. Academic Press, London, pp. 205–227. Bush M.B. 1995. Neotropical plant reproductive strategies and fossil pollen representation. Am. Nat. 145: 594–609. Charlesworth D. 1985. Distribution of dioecy and self-incompatibility in angiosperms. In: Greenwood J., Harvey P.H. and Slatkin M. (eds), Evolution: Essays in Honour of John Maynard Smith. Cambridge University Press, Cambridge, pp. 237–268. Chazdon R.L., Careaga S., Webb C. and Vargas O. 2003. Community and phylogenetic structure of reproductive traits of woody species in wet tropical forests. Ecol. Monogr. 73: 331–348. Darwin C. 1877. The Diﬀerent Forms of Flowers on Plants of the Same Species. John Murray, London. Darwin C. 1878. The Eﬀects of Cross and Self Fertilisation in the Vegetable Kingdom. John Murray, London. Flores S. and Schemske D.W. 1984. Dioecy and monecy in the ﬂora of Puerto Rico and the Virgin Islands: ecological correlates. Biotropica 16: 132–139. [363]

1424 Geber M.A., Dawson T.E. and Delph L.F. (eds) 1999. Gender and Sexual Dimorphism in Flowering Plants. Springer-Verlag, New York. Heilbuth J.C. 2000. Lower species richness in dioecious clades. Am. Nat. 156: 221–241. Heilbuth J.C., Ilves K. and Otto S.P. 2001. The consequences of dioecy on seed dispersal: modeling the seed-shadow handicap. Evolution 55: 880–888. Hutchinson J. 1959. The Families of Flowering Plants, 2nd edn. Clarendon Press, Oxford. Ibarra-Manrı´ quez G. and Oyama K. 1992. Ecological correlates of reproductive traits of Mexican rain forest trees. Am. J. Bot. 79: 383–394. Kessler P.J.A. 1993. Annonaceae. In: Kubitzki K., Rohwer J.G. and Bittrich V. (eds), The Families and Genera of Vascular Plants. Volume II. Flowering Plants. Dicotyledons: Magnoliid, Hamamelid and Caryophyllid Families. Springer-Verlag, Berlin, pp. 93–129. Kubitzki K., Rohwer J.G. and Bittrich V. (eds) 1993. The Families and Genera of Vascular Plants. Volume II. Flowering Plants. Dicotyledons: Magnoliid, Hamamelid and Caryophyllid Families. Springer-Verlag, Berlin. Kubitzki K. (ed.) 2004. The Families and Genera of Vascular Plants. Volume VI. Flowering Plants Dicotyledons: Celastrales, Oxalidales, Rosales, Cornales, Ericales. Springer-Verlag, Berlin. Lieberman M. and Lieberman D. 1994. Patterns of density and dispersion of forest trees. In: McDade L.A., Bawa K.S., Hespenheide H.A. and Hartshorn G.S. (eds), in La Selva: Ecology and Natural History of a Neotropical Rain Forest. University of Chicago Press, Chicago, pp. 106–119. Nanami S., Kawaguchi H. and Yamakura T. 1999. Dioecy-induced spatial patterns of two codominant tree species, Podocarpus nagi and Neolitsea aciculata. J. Ecol. 87: 678–687. Negrelle R.R.B. 2002. The Atlantic forest in the Volta Velha Reserve: a tropical rain forest site outside the tropics. Biodiv. Conserv. 11: 887–919. Pannell J.R. and Barrett S.C.H. 1998. Baker’s Law revisited: reproductive assurance in a metapopulation. Evolution 52: 657–668. Pitman N.C.A., Terborgh J.W., Silman M.R., Nu´n˜ez V.P., Neill D.A., Cero´n C.E., Palacios W.A. and Aulestia M. 2001. Dominance and distribution of tree species in upper Amazonian terra ﬁrme forests. Ecology 82: 2101–2117. Renner S.S. and Ricklefs R.E. 1995. Dioecy and its correlates in the ﬂowering plants. Am. J. Bot. 82: 596–606. Rohwer J.G. 1986. Produmus einer monographie der gattung Ocotea Aubl. (Lauraceae), sensu lato. Mitteilungen aus dem Institut fu¨r Allgemeine Botanik Hamburg 20: 3–278. Vamosi J.C. and Vamosi S.M. 2004. The role of diversiﬁcation in causing the correlates of dioecy. Evolution 58: 723–731. Watson L. and Dallwitz M.J. 1992 onwards. The Families of Flowering Plants: Descriptions, Illustrations, Identiﬁcation, and Information Retrieval. Version: 14th December 2000. http:// biodiversity.uno.edu/delta/. Yampolsky C. and Yampolsky H. 1922. Distribution of sex forms in the phanerogamic ﬂora. Bib. Genet. 3: 1–62.

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Biodiversity and Conservation (2006) 15:1425–1440 DOI 10.1007/s10531-005-0310-x

Springer 2006

-1

Patterns of rodent species diversity and abundance in a Kenyan relict tropical rainforest ALESSIO MORTELLITI* and LUIGI BOITANI Dipartimento di Biologia Animale, Universita` ‘‘La Sapienza’’, Viale dell’Universita` 32, 00185, Rome, Italy; *Author for correspondence (e-mail: [email protected]) Received 26 July 2004; accepted in revised form 1 June 2005

Key words: African tropical rainforests, Anthropogenic disturbance, Diversity, Equitability, Population abundance, Rodents, Species richness Abstract. Patterns of rodent species abundance and diversity were examined over a 5 months period in two areas of a Kenyan relict tropical rainforest. The two areas are subjected to diﬀerent administrations which lead to various levels of anthropogenic disturbance: one can be considered relatively disturbed and one relatively undisturbed. Anthropogenic disturbance causes a reduction in woody stem density between 0 and 1.5 m and reduced understory tree canopy cover. Rodent abundance was estimated using the program CAPTURE and compared with the number of individuals actually captured. Density was estimated with three diﬀerent methods, two of these utilised a boundary strip to estimate eﬀective size of the area trapped. Density resulted in being relatively high in both areas, so population might have been at a peak. Species richness was higher in the disturbed forest, while species diversity and evenness was higher in the undisturbed forest. We suggest that in the disturbed forest the increase in number of species might be due to sporadical entrance in the forest by non-forest species, while the decrease in diversity might be due to the decrease of lower strata vegetation that occurs in the disturbed forest, hence this factor might aﬀect species equitability. Bibliographic data supports this hypothesis as rodent species diversity and ground vegetation cover have been found to be correlated.

Introduction Most studies on the ecology of African rodents have focused on communities in savanna, secondary bush, or formerly cultivated land, hence tropical rainforests are the most understudied of major habitat types (Delany 1986; Isabyrie-Basuta and Kasenene 1987). Notwithstanding this lack of attention, rodents must be seen to play an important role in tropical rainforests as seed predators and seed dispersers (Fleming 1975; Struhsaker 1997; Chapman and Chapman 1999). From a forest management perspective, changes in the ecological parameters of rodent communities can have repercussions on tree regeneration and ﬂoristic composition of the forest (Genest-Villard 1980; Isabirye-Basuta and Kasenene 1987). Modiﬁcation of natural habitat types can have quite marked eﬀects on the rodent fauna (Delany 1986). According to Jeﬀerey (1977), Delany (1986), Isabyrie-Basuta and Kasenene (1987) and Sthruhsaker (1997), rodent

[365]

1426 abundance, as well as species richness (sensu number of species in the community – Krebs (1999)) and diversity indices (Shannon–Wiener and Simpson indices), increase with logging. Isabirye-Basuta and Kasenene (1987) in the Kibale Forest found a positive correlation between rodent species richness and diversity with ground vegetation cover (0–1.2 m). All the studies in the Kibale Forest (Uganda) found that ground vegetation cover was signiﬁcantly greater in the logged rather than the unlogged forest (Struhsaker 1997). Similar results were found by Malcolm (1995) in the Amazon Forest of Brazil: as understory vegetation increased and overstory density decreased due to logging, the abundance, species richness, and diversity of the terrestrial small mammals increased, Struhsaker (1997) concludes that ground vegetation cover is an important ecological variable that probably aﬀects rodent populations. These studies focus on a particular dynamic: logging aﬀects overstory canopy, the subsequent increase in light and water reaching ground leads to an increase of ground vegetation that seems to aﬀect the composition and structure of the rodent community (abundance of some species and diversity). However, logging is only one of the many types of anthropogenic disturbance in tropical rainforests (Jordan 1986; Whitmore 1998; Primack 2000). Factors such as forest fragmentation (and consequent edge eﬀect) and degradation of understory vegetation might lead to diﬀerent reactions of the rodent community. With this study we wanted to focus on the eﬀects of these types of anthropogenic disturbance on various parametres of the rodent community: species richness, species diversity, community equitability and population abundance. We chose the Kakamega Forest (western Kenya) because of the presence of two areas subjected to diﬀerent levels of these types of anthropogenic disturbance: more speciﬁcally the degradation of ground vegetation structure and the edge eﬀect due to high interspersion between forest and pastures – cultivated ﬁelds. Details on the vegetation structure are discussed elsewhere (Mortelliti e Boitani submitted). The forest area is managed by two diﬀerent authorities: the northern part (the Buyango-Area) is managed by the Kenya Wildlife Service and locals are not allowed into the forest; the southern part (the Isecheno-Area) is managed by the Forestry Department which permits locals to enter the forest for the collection of wood and other forest resources such as fruit and medicinal plants (Rogo et al. 1999). They are also allowed to pass with their cattle (personal observation). Both these activities create foothpaths and a generalised tread and thus degradate the lower strata of vegetation (ground vegetation). This alteration of forest structure, that more speciﬁcally coincides with lower woody stem density between 0 and 1.5 m and reduced understory tree canopy cover, is thus opposite to that indirectly caused by logging, which results in an increase in the vegetation of the lower strata. Hence the Kakamega Forest appears as a suitable context to further investigate and clarify the relationships between community diversity, richness, density and ground vegetation cover plus increase in the forest open areas boundaries.

[366]

1427 Materials and methods The study area was located in the Kakamega Forest, Kenya (latitude: 0010¢ N– 0021¢ N, longitude 3447¢ E–3458¢ E; 1500–1700 m a.s.l). According to Lucas (1968) the forest is the only reasonably large patch of Central African type lowland rainforest in Kenya. Mean annual precipitation is 2000 mm (Cords 1990). Some of commonest trees are Celtis africana, Prunus africana, Albizia gummifera, Antiaris toxicaria (Cords 1990; KIFCON 1994). Research was carried out in the ﬁeld from November 2002 to April 2003, during the dry season. Rodents were live-trapped using large aluminium Sherman traps. Diced fried coconut mixed with peanut butter was used as bait. Traps were inspected once a day. Animals were marked by toe clipping and standard data was taken from each animal before releasing it: specimen number, trap location, sex, reproductive condition, body weight. The trapping pattern was determined by the number of traps temporarily available and by logistical factors. The main objective was to obtain two specular sets of grids in each type of forest in order to allow comparisons. All grids covered an area of 0.81-ha. Each forest area had: (1) one 7 · 7 grid with 15 m of trap spacing, two traps at each station, one at ground level and one arboreal trap (1–3 m), a trapping period of 4 days; (2) one 7 · 7 grid with 15 m of trap spacing, one ground level trap at each station, a trapping period of 4 days; (3) one 10 · 10 grid with 10 m of trap spacing, two traps at each station, one at ground level and one arboreal trap (1–3 m), a trapping period of 3 days (Table 1). Due to the higher interspersion between cultivated ﬁelds and forest in the disturbed forest area, the grids resulted in being closer to the forest edge (nearest trap of each grid approximately 50, 80 and 150 m) while the grids of the undisturbed forest were relatively distant (nearest trap approximately 300, 600 and 700 m). Three trapping sessions (December, February, March) were performed in the undisturbed forest whereas, due to unpredictable logistic problems, two trapping sessions (February, March) in the disturbed Forest. The 10 · 10 grid Table 1. Grid label and grid collocation, trap numbers and trap collocation. Grid number

1 2 3 4 5 6

Collocation

Disturbed forest (Isecheno forest) Disturbed forest (Isecheno forest) Disturbed forest (Isecheno forest) Undisturbed forest (Buyango forest) Undisturbed forest (Buyango forest) Undisturbed forest (Buyango forest)

[367]

Number of terrestrial traps

Number of arboreal traps

49 100 49 49 100 49

0 100 49 0 100 49

1428 was used only in February and March sessions of each forest. A removal grid with variable number of traps was occasionally added in each forest in order to gather 10 skulls of each sex of each species for accurate species determination. We followed the classiﬁcation and diagnostic characters of Lecompte et al. (2001, 2002) and Delany (1975). Rodent abundance in each grid was estimated using the program CAPTURE which selects the most appropriate model (Otis et a1. 1978). Density was estimated in three diﬀerent ways: the ﬁrst method consisted in dividing the number of individuals/grid area; the other two methods applied a correction to the grid area by adding a boundary strip in order to estimate the eﬀective size of the area trapped (Krebs 1999). The simplest procedure is to add a strip one-half the movement radius of the animals under study (Krebs 1999). In the ﬁrst case, we used movement radius of animals of the same species in the same grid. As this ﬁrst method may be biased by a low number of recaptures, in the second case we used movement radius of all individuals of the same species captured in the whole trapping period. Abundance comparisons were performed for each species using a capture index (number of unique individuals/ trap nights for each trapping session, Nichols and Dickman 1996) with a t-test. Species richness was estimated by the number of species captured. Rodent species diversity was estimated using the Shannon–Wiener and Simpson indices (Krebs 1999); the importance of species was measured by the number of individuals actually captured (Krebs 1999). Values for Shannon–Wiener Index are espressed as N1 that is number of equally common species that would produce the same diversity as H¢, while values for Simpson Index are espressed as 1/D (Krebs 1999). Community evenness was measured using the Shannon– Wiener measurement (H/Hmax) and Simpson measurement. (1/D/number of species) (Hair 1980; Krebs 1999).

Results The study covered a total of 5340 trap nights: 2376 in the undisturbed forest and 2964 in the disturbed forest. In the whole forest a total of eight species was captured. Species and number of individuals caught were: 274 Praomys jacksoni, 82 Hylomyscus stella, 13 Lophuromys ﬂavopunctatus, 4 Mus (Nannomys) minutoides, 1 Graphiurus sp., 1 Otomys sp., 1 Lemniscomis sp., 1 Mastomys sp.). Less abundant species (one single capture) were identiﬁed only to the genus level as no skull was available for accurate species determination. All species except for Graphiurus sp. were caught in the disturbed forest, instead only the ﬁrst ﬁve species were caught in the undisturbed forest. The number of individuals of both Praomys and Hylomyscus varied, changing both in grids and in time; no signiﬁcant correlation was found between rodent abundance and trap numbers (Spearman correlation: r = 0.153, p = 0.43, n = 28). Comparisons of the abundance of each species between macrohabitats was performed with a t-test on the capture index (unique individuals captured/trap nights, Table 2) [368]

1429 Table 2. Capture index (unique individuals captured/trap nights) for Praomys jacksoni and Hylomyscus stella. g6 s1

g6 s2

g6 s3

g3 s1

g3 s2

g1 s1

g1 s2

g4 s1

g4 s2

g4 s3

g5 s1

g5 s2

g2 s1

g2 s2

Praomys 0.06 0.09 0.07 0.08 0.11 0.14 0.1 0.07 0.11 0.11 0.03 0.02 0.05 0.06 jacksoni Hylomyscus 0.04 0.02 0.01 0.03 0.04 0 0.01 0.04 0.04 0.02 0.01 0.01 0.02 0.01 stella Results are shown for each session of each trapping grid; g – grid; s –session.

no signiﬁcant diﬀerence was found (Praomys: t = 1.1 p = 0.28 n = 14; Hylomyscus: t = 0.699, p = 0.49, n = 14). Capture estimate was performed only for the two most abundant species: Praomys jacksoni and Hylomyscus stella. The model most used for Praomys jacksoni was model 0 which assumes constant capture probabilities; the model most used for Hylomyscus stella, instead, was model th: capture probabilities vary according to time and the individual animal (Figure 1) (see Otis et al. 1978 for models description). The estimate of CAPTURE and the actual number of individuals captured were often very close, or even coincident (Figure 2). In some cases, though, diﬀerences are relevant, for example Praomys jacksoni: second session of grid 6 and second session of grid 3 (Figure 2). The precision of the CAPTURE estimate is given by the conﬁdence interval (Figures 3 and 4). The density estimate varies with the methodology of correction used, values range from 7.17 to 69.09/ha (Praomys jacksoni) and 1 to 23.45/ha (Hylomyscus stella) (Tables 3 and 4). No signiﬁcant diﬀerence was found when we compared results from Corrected Density (1) and Corrected Density (2) for both species (P. jacksoni t = 0.229, df=26, p = 0.82; H. stella t = 0.73, df=26, p = 0.94). Praomys jacksoni, Hylomyscus stella and Lophuromys ﬂavopunctatus were caught in all the grids; Mus (Nannomys) minutoides was caught in grid 3

Figure 1. Models used by program CAPTURE. In black Praomys jacksoni, in white Hylomyscus stella. X axis – model name; Y axis – absolute frequencies. See Otis et al. (1978) for models description. [369]

1430

Figure 2. Comparison between CAPTURE estimate and actual number of individuals captured. Praomys jacksoni (above) and Hylomyscus stella (below): in white CAPTURE estimate, in black actual number individuals captured. X axis – number of rodents; Y axis – grid number and session number.

Figure 3. Praomys jacksoni CAPTURE estimate (with selected model) and conﬁdence interval. Leg: p – Praomys jacksoni; g6-1 – grid 6 session 1. [370]

1431

Figure 4. Hylomyscus stella. CAPTURE estimate (with selected model) and conﬁdence interval. Leg: h – Hylomyscus stella; g6-1 – grid 6 session 1.

(undisturbed forest) and grid 1 and 2 (disturbed forest); Graphiurus sp. was caught only in grid 6 (undisturbed forest), Lemniscomys was caught only in grid 3 (disturbed forest); Otomys sp. and Mastomys sp. were caught only in grid 2 (disturbed forest). Grid 1 and 2 of the disturbed forest supported a higher number of species than their corresponding grids in the undisturbed forest, but in grid 6 of the undisturbed forest a higher number of species was caught in comparison to its analogous in the disturbed forest (Table 5). In all the comparisons with the Shannon–Wiener Index between analogous grids, species diversity resulted higher in the undisturbed forest, while with the Simpson Index in grid 6 (undisturbed forest) we found a lower diversity than its equivalent grid in the disturbed forest. As one more trapping session was performed in grid 4 and 6 of the undisturbed forest, the Diversity Indices were also calculated without considering individuals caught in the last session, results partially conﬁrm the higher values for the undisturbed forest: in this case in grid 6 (undisturbed forest) we found a higher value of the Simpson Index in comparison to the analogous grid (grid 3) in the disturbed forest thus, all the undisturbed forest grids were characterised by a higher diversity (Table 5). In grid 4 and 5 of the undisturbed forest there was a higher Evenness than their correspondant grids in the disturbed forest, but this pattern was inverted in grid 6 of the undisturbed forest. If we pool data from all the grids of the same forest type we obtain a higher community diversity and higher evenness in the undisturbed forest (Table 5). In the double-trap grids Hylomyscus stella was captured above ground (1–3 m) 55.7% of times (n = 159), Praomys jacksoni 25.3 % of times (n = 247). The number of above ground captures for Hylomyscus stella resulted signiﬁcantly higher than the number of above ground captures for Praomys

[371]

1432

Table 3. Praomys jacksini: density estimates. Praomys jacksoni

Session 1

[372]

Session 2

Session 3

Density Corrected Corrected Density Corrected Corrected Density Corrected Corrected

density (1) density (2) density (1) density (2) density (1) density (2)

Grid 4 Buyango/ha

Grid 1 Isecheno/ha

Grid 6 Buyango/ha

Grid 3 Isecheno/ha

Grid 5 Buyango/ha

Grid 2 Isecheno/ha

18.51 7.17 11.02 32.09 18.7 19.11 27.16 14.37 16.17

/ / / 34.56 17.5 20.5 28.39 15.75 16.9

41.97 25 25 93.82 69.09 55.8 37.03 19.6 22.05

/ / / 66.66 43.90 39.7 55.55 30.4 33

/ / / 23.45 16.1 13.9 17.28 10 10.29

/ / / 46.91 33.62 27.9 56.79 41.81 33.8

Density – CAPTURE estimate of number of individuals/grid area. Corrected density 1 – CAPTURE estimate of number of individuals/grid area plus boundary strip (mean movement radius of Praomys of the grid). Corrected density 2 – CAPTURE estimate of number of individuals/grid area plus boundary strip (mean movement radius of Praomys of all grids). Buyango – undisturbed forest; Isecheno – disturbed forest.

Table 4. Hylomyscus stella: density estimates. Hylomyscus Stella

Session 1

[373]

Session 2

Session 3

Density Corrected Corrected Density Corrected Corrected Density Corrected Corrected

density (1) density (2) density (1) density (1) density (1) density (1)

Grid 4 Buyango/ha

Grid 1 Isecheno/ha

Grid 6 Buyango/ha

Grid 3 Isceheno/ha

Grid 5 Buyango/ha

Grid 2 Isecheno/ha

22.2 7.5 11 18.51 9.67 9.43 6.17 3.16 3.14

/ / / 1.23 * 0.62 2.46 ** 1.25

30.86 18.11 15.7 9.87 4.21 5.03 6.17 3.67 1.88

/ / / 16.04 8.96 8.17 23.45 9.94 11.94

/ / / 8.64 3.91 4.4 7.4 4.19 3.77

/ / / 32 17.8 16.35 12.3 6.09 6.2

Density – CAPTURE estimate of number of individuals/grid area. Corrected density 1 – CAPTURE estimate of number of individuals/grid area plus boundary strip (mean movement radius of Praomys of the grid). Corrected density 2 – CAPTURE estimate of number of individuals/grid area plus boundary strip (mean movement radius of Praomys of all grids). *1 capture, **2 captures Buyango – undisturbed forest; Isecheno – disturbed forest.

1433

Grid

Species richness

Shannon-Wiener indexa (ln)

Simpson Indexb

Shannon-Wiener measure of evenness

Simpson’s measure of evenness

Grid 6 undisturbed

5 (P. jacksoni, H. stella, L. ﬂavopunctatus, M. minutoides, Graphiurus sp.) 4 (P. jacksoni, H. stella, L. ﬂavopunctatus, Lemniscomys sp.) 3 (P. jacksoni, H. stella, L. ﬂavopunctatus) 4 (P. jacksoni, H. stella, L. ﬂavopunctatus, M. minutoides) 3 (P. jacksoni, H. stella, L. ﬂavopunctatus) 6 (P. jacksoni, H. stella, L. ﬂavopunctatus, M. minutoides, Otomys sp., Mastomys sp.) 5 (P. jacksoni, H. stella, L. ﬂavopunctatus, M. minutoides, Graphiurus sp.) 7 (P. jacksoni, H. stella, L. ﬂavopunctatus, M. minutoides, Otomys sp., Mastomys sp., Lemniscomys sp.)

2.03 (2.11)

1.66 (2.08)

0.44 (0.46)

0.33 (0.41)

1.91

1.75

0.59

0.58

1.93 (2.05)

1.74 (1.83)

0.60 (0.37)

0.58 (0.61)

1.5

1.29

0.29

0.32

2.24

2.14

0.74

0.71

2.1

1.78

0.43

0.29

2.24

2.03

0.5

0.4

2.03

1.69

0.36

0.24

Grid 3 (disturbed) Grid 4 undisturbed Grid 1 (Disturbed)

[374]

Grid 5 undisturbed Grid 2 (disturbed)

Undisturbed forest (all data pooled) Disturbed forest (all data pooled)

a

The value is the number of equally common species that would produce the same diversity as H¢ (Krebs 1999). The value is 1/D (Krebs 1999); in brackets, value calculated excluding last session.

b

1434

Table 5.

1435 jacksoni (paired t-test: t = 8.45 df=8 p < 0.001). No signiﬁcant diﬀerence was found in the number of above ground captures for each species between the two forest types (P. jacksoni t = 1.11 df=7 p = 0.3; H. stella t = 1.5 df=7 p = 0.15). The individual Graphiurus was captured above ground.

Discussion Our results show that anthropogenic disturbance does not necessarily lead to an increase in rodent species diversity. We found that damage to the vegetation of the lower strata and increase in the forest – open area boundaries lead to a variation in the diversity, evenness and richness of the rodent community. More speciﬁcally it appears that the proximity to forest edge increases the species richness while the decrease in ground vegetation cover leads to a decrease in the community diversity. The population study results show that there is a high similarity between the CAPTURE estimate and the actual numbers of individuals trapped. This might suggest that the estimate was accurate and that most of the animals present in the trapping area were caught. At the same time from Figures 3 and 4 we can see that the estimates were often precise as they have a very small conﬁdence interval. The comparison of the capture index of each species between macrohabitats did not give signiﬁcant results, in fact most variations occur between grids and between trapping sessions and not between macrohabitats: this might depend on actual diﬀerences in population sizes, or sampling error as well as diﬀerences in trap numbers (but no signiﬁcant correlation was found between rodent abundance and trap numbers). Struhsaker (1997), reports that in some cases these two species showed higher abundance in logged forest, but in other cases diﬀerences were not signiﬁcant. Chapman and Chapman (1999) reported that their capture success doubled in the disturbed forest, while Isabirye-Basuta and Kasenene (1987) found signiﬁcant diﬀerences for Hylomyscus stella but not for Praomys jacksoni. Waweru and Odanga (2004) in the Kakamega Forest found higher abundance in a portion of mature forest when compared to a fragment of regenerating forest (clear felled 15 years before). In all these cases anthropogenic disturbance coincided with logging; as previously stated this is not the case for our study areas, so the fact that we did not observe signiﬁcant diﬀerences could be due the fact that this kind of anthropogenic disturbance does not aﬀect this demographic parametre. However, since populations of African rainforest rodents ﬂuctuate to some extent (Struhsaker 1997) long-term studies are needed to conﬁrm this hypothesis. The density estimate varies with the method used. For example in grid 5 (disturbed forest), with the ﬁrst method, that might overestimate density, we obtain a value of 46.91 individuals/ha, with one of the corrections the estimate drops down to 27.9 individuals/ha. Even if we consider the lowest values still we obtain very high values of density. The boundary strip correction is a very useful tool to estimate the eﬀective size of Area trapped and is often used, also in [375]

1436 tropical rainforests (Isabyrie-Basuta and Kasenene 1987). No signiﬁcant difference was found between these two corrections for both species, however, since the ﬁrst method may be biased by a low number of recaptures, the second method, that considers movement radius of all individuals of the same species captured in the whole trapping period, might be relatively more reliable although it is insensitive to variations in movement radius occuring between grids. Struhsaker (1997) reviewed data of 10 years of study in the Kibale Forest, for Praomys jacksoni density estimates vary from 1.98 to 4.98 individuals/ha while for Hylomyscus stella they vary from 1.78 to 6.76 individuals/ha. However, in another forest in Uganda, Delany (1986) reports, for all rodent species, density peaks up to 58.7 rodents/ha. If we pool data for Praomys and Hylomyscus, data is consistent with Delany’s results. Thus it appears that, during the period of study, the population of Praomys jacksoni and Hylomyscus stella might have been at a peak. If we extend our comparisons, density in the Kakamega Forest is still very high: Mares and Ernest (1995) in a gallery forest of central Brazil found a density of rodents below 10/ha, while in his review of many studies in tropical rainforest Fleming (1975) reports values of rodent density below 15/ha. There is a need for long-term studies in order to investigate whether this is a temporary situation; in any case this research highlights the presence (temporary or not) of extreme abundances of rodents, which could have drastic consequences on seed ecology, thus it underlines the necessity and importance of studies focusing on the eﬀects of rodent communities on seed predation and seed dispersal. The comparisons relative to community richness, diversity and equitability regard corresponding grids of the two forest types: grids with the same number of traps and trapping pattern, that is grids with the same probability of capturing rare species. Some factors that may bias results are: (a) traps and baits are species-speciﬁc so it is possible that many species are not trapped (Gurnell and Flowerdew 1994; Barnett and Dutton 1995); (b) rare species were represented by one single capture, so probability of capture for these species was very low, hence prone to stochastic variability; in this case the Simpson Index, as it is less sensitive to rare species, might be more indicative (Hair 1980); (c) although we used arboreal traps, our eﬀorts were limited to the ﬁrst 3 m: to obtain a complete inventary of species one should sample up to the canopy (Delany 1986; Barnett and Dutton 1995). Our list of species is similar to the one obtained by Waweru and Odanga (2004) in the Kakamega Forest except for Colomys goslongi and Rattus rattus which they caught in a fragment of regenerating forest (clear-felled 15 years before) therefore in a diﬀerent habitat. Our list of species and community structure is also similar to the ones of similar studies in forests of East Africa: Isabyrie-Basuta and Kasenene (1987) and Chapman and Chapman (1999), in the Kibale Forest found that the two forest specialist Praomys jacksoni and Hylomyscus stella, were the most abundant species, followed by Lophuromys ﬂavopunctatus and Mus (Nannomys) minutoides. At the grid level, species richness, in two out of three comparisons, is [376]

1437 higher in the disturbed forest. If we pool data from all the grids of the same forest type, species richness is higher in the disturbed forest (7 species) than in the undisturbed forest (5 species). With the Shannon–Wiener Function we found a higher community diversity in all the grids of the undisturbed forest, while with the Simpson’s Index we obtained the same result in two of the three comparisons. The decrease of rodent species diversity together with the decrease in lower strata vegetation seems to be coherent with the considerations of Isabyrie-Basuta and Kasenene (1987) on the positive correlation between rodent species diversity and ground vegetation cover. The only diﬀerence is that in their case anthropogenic disturbance (logging) leads to an increase of ground vegetation cover, which is the opposite of our case. On the other hand, our data reveals an increase in species richness in the disturbed forest which is characterised by lower ground vegetation density. Isabyrie-Basuta and Kasenene (1987) instead, found a positive correlation between ground vegetation cover and rodent species richness. This particular pattern of inversion between rodent species richness and diversity in the two areas of the Kakamega Forest may be due to two diﬀerent aspects of anthropogenic disturbance: (1) proximity to the forest edge might favour the occasional entrance of non-forest species, thus increasing rodent species richness; (2) alteration of lower strata vegetation might increase the other component of diversity: equitability, that is the relationships of dominance between species. First, as was anticipated in the Introduction, the disturbed forest grids were near to the forest edge, so very near to the cultivated ﬁelds and pastures, that sustain a diﬀerent rodent fauna (Delany 1975; Delany 1986). Although identiﬁcation of single capture species stops at the genus level, Mastomys, Lemniscomys and Otomys are three genus with only non-forest species and they were captured only in the disturbed forest, Lophuromys ﬂavopunctatus and Mus (Nannomys) minutoides are habitat generalists and are often captured in forests (Kingdon 1974; Delany 1975; Delany 1986), these species were captured in both forest types. Graphiurus, Praomys jacksoni and Hylomyscus stella are the only forest-specialist species (Kingdon 1974; Delany 1975; Delany 1986; Lecompte et al. 2002). Graphiurus sp. was captured only in grid 6 of the undisturbed forest, which is the only grid of the undisturbed forest characterised by higher species richness than its corresponding in the disturbed forest. Thus this data supports the hypothesis that the proximity to forest edge is the main factor responsible for increase in species richness. A short-term study such as this is not able to assess whether the 3 non-forest species captured in the disturbed forest are permanent components of the rodent forest community, however, these same open area species are known to invade forest, particularly secondary forest (Delany 1975; Isabyrie-Basuta and Kasenene 1987; Struhsaker 1997). As regards point two, in two out of three comparisons evenness is higher in the undisturbed forest, if we pool data we conﬁrm that evenness is higher in the undisturbed forest. As structural complexity or heterogeneity of a habitat increases, the number of microhabitats potentially available increases (Hair [377]

1438 1980). In the other part of our research (Mortelliti and Boitani, submitted) we found that in the Kakamega Forest microhabitat heterogeneity decreases in the disturbed forest as a result of the reduction of low strata vegetation. The higher variability of microhabitats in the undisturbed forest might hence lead to a more even distribution of species increasing and/or decreasing the proportion of individuals of a certain species in the community. The pattern observed in the corresponding grids 6 and 3 does not ﬁt in this hypothesis, so one can only postulate that some other factor might be aﬀecting community diversity and evenness. In synthesis our results support the hypothesis that proximity to forest edge increases species richness while degradation of ground vegetation cover reduces the evenness parametre, thus decreasing community diversity. A comprehensive formulation of this hypothesis will need further long-term studies with the utilisation of various types of traps at various heights in order to reduce bias of the species checklist. Furthermore it is important to highlight that woody stem density or low-strata vegetation in general might not be the actual feature responsible for this change, it might be correlated to the actual factors eﬀectively inﬂuencing rodent species diversity. Data on vertical stratiﬁcation appears to be consistent with bibliographic data (Kingdon 1974; Delany 1975; Delany 1986; Struhsaker 1997): Praomys jacksoni and Hylomyscus stella are two scansorial species, the latter being relatively more arboreal. Our results show that in the Kakamega forest anthropogenic disturbance does not seem to inﬂuence vertical stratiﬁcation since no signiﬁcant diﬀerence in above-ground captures was found between macrohabitats. Struhsaker (1997) suggested that anthropogenic disturbance leads to an increase in the degree of segregation between arboreal and terrestrial niches (more speciﬁcally Hylomyscus stella appeared to be strictly arboreal rather than scansorial). However, in his case anthropogenic disturbance coincided with logging and thus with an increase of ground vegetation cover, which is the opposite of our case. Our data refers only to the ﬁrst 3 m of height, a detailed analysis of vertical stratiﬁcation will require traps located right up to the overstory canopy (Delany 1986). Our short-term study shows that during the period of study the Kakamega forest supported an extremely high abundance of Praomys jacksoni, and in some cases of Hylomyscus stella, this highlights the importance of studies focusing on possible eﬀects of this high density of rodents on seed ecology. This study also supports the hyphothesis that ground vegetation might be (directly or indirectly) the factor responsible for variation in community diversity (through a variation in evenness), while proximity to the forest edge might be responsible for variation in species richness. This study further demonstrates the ability of man to modify the structure of animal communities, even in the form of a ‘light’ impact such as wood collection and cattle passage by local communities inhabiting forest surroundings and thus pones evidence on the importance of these studies to forest management.

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1439

Acknowledgements Thanks to the following Institutions that provided us with the necessary permits to conduct research: National Museums of Kenya, Kenya Wildlife Service, Isecheno Forestry Department. This study was ﬁnanced with a grant from ‘‘La Sapienza’’ University of Rome. Two anonymous reviewers signiﬁcantly improved the manuscript. References Barnett A. and Dutton J. 1995. Expedition ﬁeld techniques: small mammals (excluding bats). Expedition Advisory Centre, London, England. Chapman C.A. and Chapman L.A. 1999. Forest restoration in abandoned agricultural land: a case study from east Africa. Conserv. Biol. 13(6): 1301–1311. Cords M. 1990. Mixed-species association of East-African Guenons: general pattern or speciﬁc examples? Am. J. Primat 21: 101–114. Delany M.J. 1975. The Rodents of Uganda. British Museum of Natural History. Delany M.J. 1986. Ecology of Small Rodents in Africa. Mammal review Vol. 16. Fleming T.H. 1975. The role of small mammals in tropical ecosystems. In: Golley F.B., Petrusewicz K. and Ryszkowski L. (eds), Small Mammals: Their Productivity and Population Dynamics. Cambridge University Press. Genest-Villard H. 1980. Regime alimentaire des rongeurs Myomorphes de foret equatoriale (region de M’Baiki Republique Centrafricaine). Mammalia 44: 432–484. Gurnell J. and Flowerdew J.R. 1994. Live Trapping Small Mammals –A Practical Guide – Occasional Publication No3. Mammal Society, London. Hair J.D. 1980. Measurements of ecological diversity. In Schennitz (ed.), Wildlife Management Techniques Manual. Isabirye-Basuta G. and Kasenene J.M. 1987. Small rodent population in selectively felled and mature tracts of Kibale forest, Uganda. Biotropica 19(3): 260–266. Jeﬀerey S.M. 1977. Rodent ecology and land use in western Ghana. J. Appl. Ecol. 14: 741–755. Jordan C.F. 1986 Local eﬀects of tropical deforestation. In: Soule` E. (ed.)1986 Conservation Biology: The Science of Scarcity and Diversity. Sinauer Associates. KIFCON (Kenya Indigenous Forest Conservation) 1994. Kakamega Forest: The Oﬃcial Guide. KIFCON, Nairobi. Kingdon and J. 1974. East African Mammals (Rodentia, Insectivora, Macroscelida). Academic Press. Krebs Charles J. 1999. Ecological Methodology 2nd edn. Addison Wesley Longman Inc. Lecompte E., Denys C. and Granjon L. 2001. An identiﬁcation key of the Praomys species (Rodentia: Muridae). In: 1’IRD (ed.), African Small Mammals. colloques et se´minaires, paris, pp. 127–139. Lecompte E., Granjon L. and Denys C. 2002. The phylogeny of the Praomys complex (Rodentia: Muridae) and its phylogeographic implications. J. Zool. Syst. Evol. Res. 40(2002): 8–25. Lucas G.L. 1968. Kenya. In: Hedberg I. and Hedberg O. (eds), Conservation of Vegetation in Africa South of the Sahara. Acta phytogeographica suecica 54, pp.152–166. Mares M.A. and Enest K.A. 1995. Population community ecology of small mammals in a gallery forest of central Brazil. J. Mammal. 76(3): 750–768. Malcolm J.R. 1995. Forest structure and the abundance and diversity of neotropical small mammals. In: Lowman M.D. and Nadkarni N.M. (eds), Forest Canopies. Academic Press, New York, 624 pp. Nichols and Dickmanin Wilson D.E., Cole R.T., Nichols J.D., Rudran R. and Foster M.S. 1996. Measuring and Monitoring Biological Diversity: Standard Methods for Mammals. Smithsonian Institution Press. Primack R.B. 2000. A Primer in Conservation Biology. Sinauer Associates.

[379]

1440 Otis D.L., Burnham K.P., White G.C. and Anderson D.R. 1978. Statistical Inference from Capture Data on Closed Animal Populations. Wildlife Monographs – A publication of the Wildlife Society No62. Rogo L., Lwande W., Miller S., Herren H. and Chapya A. 1999. Kakamega Forest: an integrated conservation project. Bull. East African Nat. History Soc. 29(3): 9–13. Struhsaker T.T. 1997. Ecology of an African Rainforest: Logging in Kibale and the Conﬂict between Conservation and Exploitation. University Presses of Florida, Gainesville. Waweru C. and Odanga J.C. 2004. Demographic aspects of sympatric Praomysjacksoni and P. Stella in a tropical lowland forest in Kekamega, Kenya. Afr. J. Ecol. 42: 93–99. Whitmore T.C. 1998. An Introduction to Tropical Rainforests. Oxford University press.

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Biodiversity and Conservation (2006) 15:1441–1457 DOI 10.1007/s10531-005-0598-6

Springer 2006

-1

The role of landscape patterns of habitat types on plant species diversity of a tropical forest in Mexico J. LUIS HERNANDEZ-STEFANONI1,2,* 1

Watershed Ecosystems Graduate Program, Trent University, Peterborough, Ontario, Canada; Present address: Servicio de Informacio´n y Estadı´stica Agroalimentaria y Pesquera, Av. Benjamı´n Franklin 146, Col. Escandon, C.P. 11800, Me´xico, USA; *Author for correspondence (e-mail: [email protected]; phone: +1-52-55-5271-7111, ext. 134) 2

Received 5 April 2004; accepted in revised form 24 June 2005

Key words: Landscape fragmentation, Landscape patterns, Plant diversity, Shannon diversity index, Simpson diversity index, Tropical forest Abstract. The relationships among landscape characteristics and plant diversity in tropical forests may be used to predict biodiversity. To identify and characterize them, the number of species, as well as Shannon and Simpson diversity indices were calculated from 157 sampling quadrats (17,941 individuals sampled) while the vegetation classes were obtained from multi-spectral satellite image classiﬁcation in four landscapes located in the southeast of Quintana Roo, Mexico. The mean number of species of trees, shrubs and vines as well as the mean value of the total number of species and the other two diversity indices were calculated for four vegetation classes in every one of the four landscapes. In addition, the relationships between landscape patterns metrics of patch types and diversity indices were explored. The multiple statistical analyses revealed signiﬁcant predictor variables for the three diversity indices. Moreover, the shape, similarity and edge contrast metrics of patch types might serve as useful indicators for the number of species and the other two diversity variables at the landscape scale. Although the association between the three diversity indices and patch types metrics showed similar behavior, some diﬀerences were appreciated. The Shannon diversity index, with its greater sensitivity to rare species, should be considered as having a greater importance in interpretation analysis than Simpson index.

Introduction Tropical forests of the world are being destroyed by degradation and conversion to other forms of land use, induced by increasing human needs or simply by economic gain. The loss of biodiversity is considered to be one of the most important of all negative eﬀects on these forests. High diversity implies that there is a source of new species executing functions or ecosystem services for human needs (Bengtsson 1998). Therefore, a reduction of biological diversity means less environmental functions and ecological processes that generate and maintain soils, convert solar energy into plant tissue, absorb pollutants, supply clean air and water, store essential nutrients, regulate weather, and climate and so on (Myers 1995). The Yucatan peninsula has been recognized as one of the world’s biodiversity ‘‘hotspots’’ areas with high levels of biological diversity (Myers et al. [381]

1442 2000). Nevertheless, forests of the peninsula are subject to disturbance by hurricanes and forest ﬁres (Whigham et al. 1991) but also by land use changes. These disturbances produce a mosaic of forest in diﬀerent stages of succession, as well as small forest remnants embedded in a matrix of agriculture and grassland areas. Conversely, the practice of ‘‘slash and burn’’ agriculture, by Mayan farmers, allows the re-growth of native vegetation over a period of time or fallow in the areas opened to cultivation (Hernandez-Xolocotzi et al. 1995). These changes have profound consequences in the forest area and on its biological diversity. Although these changes are occurring in the Yucatan peninsula, the exact magnitude on which these changes aﬀect the diversity of the area is not well understood. Disturbance is one of the main functional elements in landscapes. It is also a key factor to maintain biological diversity (Roberts and Gilliam 1995). There are diﬀerent phases of forest succession after a disturbance event takes place (Whitmore 1989); each of them poses particular problems and advantages for arrival, regeneration and establishment of diﬀerent species (Whitmore 1989; Alvarez-Buylla and Garcia-Barros 1991). For example, pioneer or shadeintolerant species generally reach maturity if they establish themselves in large, newly opened gaps (Brokaw 1987). However, the greatest likelihood of regeneration of pioneer species occurs in the neighborhood of maturing gaps (Schupp et al. 1989) because of seeds and seedlings being released from adjacent forested areas. On the other hand, non-pioneer will germinate and get established almost entirely beneath the forest canopy, due to few seeds reach a gap, and most of the seeds that ﬁnd a gap are eaten by mammals (Schupp et al. 1989; Alvarez-Buylla and Martinez-Ramos 1992). Nevertheless, some of the species of this group requires an open canopy for growth and reproduction (Denslow 1995). In other words, non-pioneer species become gap dependant or need a condition with certain amount of canopy opening, such as that created at the edge of the patches (Howe 1990). Therefore, the presence or absence and spatial distribution of plant species may be inﬂuenced by both physical and biotic conditions created in the diﬀerent phases of forest succession and then the area, distance and similarity or contrast of adjacent forest areas as well as the perimeter or shape of the habitat types may be factors that can describe the species composition (Mazerolle and Villard, 1999; Debinski and Holt, 2000). The quantiﬁcation of spatial heterogeneity of landscapes can be studied in term of patches and their characteristics, through landscape metrics (McGarigal et al. 2002), which are used to create quantitative measures of spatial patterns. Such patterns are found on categorical maps, classiﬁed air photographs and remote sensing imagery and their metrics have been linked to ecological functions. Thus, the most important reason to use landscape metrics is that landscape patterns can be linked in a quantitative way with ecological and environmental processes (Krummel et al. 1987; McGarigal et al. 2002). Consequently, it is possible to study changes in habitat of particular species or communities of organisms and determine whether or not the habitats are too fragmented for the species or communities to survive. [382]

1443 The purpose of this paper is to examine the relationships between landscape patterns of habitat types and plant diversity estimates. This was based on the understanding that the environmental conditions in the study area have small variation and in particular based on the fact that several studies have suggested that spatial patterns may be important determinant of species distribution at landscape scale (Mazerolle and Villard, 1999; Debinski and Holt 2000; McGarigal and Kushman 2002). The main goal of this study was to investigate the relationships between the estimates of plant diversity and landscape metrics of patch types in order to ﬁnd out whether spatial patterns of habitat types are reliable mechanisms for predicting biodiversity. This was done with a view of predicting plant species diversity from landscape features easily observable/measurable from satellite images or maps. The assessment and modeling of the spatial distribution of plant diversity is of considerable importance for conservation and forest management purposes. To preserve biodiversity, knowledge of where species richness is the highest and how species assemblages change over the space is required. For example the presence of species and the habitat occupied by species are signiﬁcant criteria for prioritizing and selecting sites for preservation in land use planning (Rossi and Kuitunen 1996) or for locating areas where plant diversity is critical (Carroll 1998).

Methods Study area and plant diversity data The study was conducted in a tropical forest over four contiguous landscapes of 4 km · 4 km, located in the southeastern portion of the Yucatan peninsula, Mexico. Tropical sub-deciduous forests in diﬀerent stages of succession, which are characterized by the age, as well as secondary associations that prosper mainly in ﬂood areas, cover the majority of the four landscapes (Cabrera et al. 1982). The forest consisting of 2 or 3 canopy layers with trees, shrubs and vines between 3 and 25 m of height. Mayan farmers identiﬁed the stages of succession with indigenous local names. ‘‘kanah kax’’ refers to a forest from 20 to 60 years old; ‘‘kelenche’’ is used for vegetation between 11 and 19 years of age; ‘‘juche’’ used for plant species between 4 and 10 years of age and ‘‘saakab’’ with plants species of 3 or less years of age. The secondary plant associations in the area are ‘‘savanna’’, which have few sparse tree species between 3 and 10 m of height and ‘‘akalche’’ (in local Mayan language) consisting of a shrub stratum. A plant survey based on a stratiﬁed random sampling design was performed in the study area during the summer of 2000, 2001 and 2003. This survey had a total of 157 sampling quadrats, which were located on the ground using a GPS unit in the six vegetation types. Of the total number of quadrats 42 fell within the class ‘‘kanah kak’’, 27 in ‘‘kelenche’’, 22 in ‘‘juche’’, 25 in ‘‘saakab’’, 22 in ‘‘akalche’’ and 19 in the ‘‘savanna’’ vegetation class. The sampling quadrat [383]

1444 consisted of two nested sites, one of them of 10 · 10 m used to sample trees and vines that have 3 or more meters of height, the other, a nested sub-site of 5 · 5 m used for sampling all the shrubs taller than 1.0 m. In every one of the quadrats three diversity indices were computed, those are species richness (i.e., the number of species present in an area) and two measures based on species frequencies or abundance, including exponent Shannon and reciprocal Simpson indices (Magurran 1988; Krebs 1989). A total of 17,941 sampled individuals were identiﬁed to species and enumerated.

Land cover mapping A land cover map for the entire area was obtained from Landsat 7 Thematic Mapper (TM) imagery acquired on April 2000, after applying a supervised classiﬁcation on bands 5 (short-wave infrared: 1.55–1.75 gm), 4 (near infrared: 0.76–0.90 gm) and 3 (red: 0.63–0.69 gm). Each band was geo-referenced and radiometrically corrected. The ‘‘Maximum Likelihood Algorithm’’ implemented by the image analysis software ER MapperTM 6.1 (Earth Resource Mapping Ltd. 1998) was used as the classiﬁcation method. The sampling quadrats were used for assessing the accuracy of the classiﬁed land cover maps, which resulted in an overall accuracy of 82.3%. The ﬁnal land cover map of the four landscapes is shown in Figure 1. Details of the classiﬁcation and the accuracy assessment procedures of the resulting land cover maps are found in Hernandez-Stefanoni (2004) and Hernandez-Stefanoni and Ponce-Hernandez (2004).

Calculation of landscape-pattern metrics The ER MapperTM raster ﬁles of the four landscape mosaics were exported to the GIS program IDRISI (Eastman 1999), in order to calculate the landscapepattern metrics using the program software FRAGSTATS 3.0 (McGarigal et al. 2002). The six vegetation types identiﬁed during the classiﬁcation and the remaining of the land cover classes grouped as ‘‘background’’ were considered for the calculations. The individual patches were classiﬁed as clusters of vertical, horizontal or diagonal pixels as in other studies (Gustafson et al. 1994), while a patch type considers all the individual patches of the same vegetation class. Most of the metrics applied to vegetation classes can be interpreted as fragmentation indices, because they measure the conﬁguration of a particular patch type (McGarigal et al. 2002). The four landscapes in the study area were considered for the computation of the indices per class (patch type). The division of the study area in four landscapes was done to obtain diﬀerent replicas of landscape conﬁgurations. The four landscapes, deﬁned for estimating landscape metrics of patch types, still retain a suﬃcient size as to allow for the occurrence of several patches of plant diversity. Gustafson (1998) used [384]

1445

Figure 1. Land cover maps obtained from supervised classiﬁcation of the four landscapes.

the range of inﬂuence, as depicted from the spatial auto-correlation of sample units, to deﬁne the maximum patch size of the variable of interest. Here, the range of inﬂuence of diversity indices found from the semi-variance analysis is ranged between 1.2 and 2.1 km (Hernandez-Stefanoni 2004), this indicates that the four landscapes are suﬃciently large to include patches of various sizes while aﬀording for replication. Moreover, the size of the landscape maybe arbitrary but needs to be relevant to the process or organisms studied (McGarigal et al. 2002); in this case the four landscapes continue to be relevant to deﬁne patches of plant diversity. Several indices at this level are calculated by FRAGSTATS all of them were considered for reviewing and further examination. Many of patch-type indices are redundant or represent an alternative formulation of the same information (Riitters et al. 1995; Hargis et al. 1998). Thus, only selected measurements were considered in this study. To choose the group of indices, their correlations were analyzed. Pearson correlation coeﬃcients between each pair of landscape metrics, as well as the correlation of these metrics with plant diversity values were computed. The selection of the indices also considered criteria including variables that quantify diﬀerent aspects of the patch type conﬁguration. Six indices were ﬁnally included in this study. The selected indices represent factors (landscape metrics) that might explain the plant diversity in the tropical forests of the study area. The ﬁnal selection of the landscape metrics was made [385]

1446 considering both, how commonly such measurements of landscape metrics are in landscape studies literature (Mazerolle and Villard 1999), as well as the explanatory power that such metrics may have to describe plant species composition. On these bases, four groups of metrics were selected to relate plant diversity indices and landscape-patterns of habitat types. Those groups and metrics are: area/density/edge (percentage of landscape, patch density and edge density), shape (mean area weighted shape index), isolation/proximity (mean area weighted similarity index) and contrast (total edge contrast index). A description of each metric is given next. Percentage of landscape (PLAND) is calculated as the sum of the areas (m2) of all patches of the corresponding patch type, divided by the total landscape area (m2), multiplied by 100 (to convert a percentage). This metric is a measure of landscape composition, speciﬁcally, how much of the landscape is comprised of a particular patch type (vegetation class). Patch Density (PD) is calculated as the number of patches of a given patch type divided by the total landscape area (m2), multiplied by 10,000 and 100 (to convert to 100 ha). This metric represents the number of patches on a per unit area basis, which facilitates comparisons among landscapes of varying size. Edge Density (ED) is calculated as the sum of the length (m) of all edge segments involving the corresponding patch type, divided by the total landscape area (m2), multiplied by 10,000 (to convert to hectares). ED is a measure of total edge length of all patch types on a per unit area bases that facilitates comparisons among landscapes of varying size. Mean area weighted shape Index (SHAPE_AM) is the sum, across all patches of the corresponding patch type, of the shape index value multiplied by the proportional abundance of the patch [i.e., patch area (m2) divided by the sum of patch areas]. The shape index is calculated as the perimeter of a patch (m) divided by the square root of a patch area (m2). Therefore, this metric is a measure of shape complexity of a patch compared to a standard shape (square) of the same size. Mean area weighted similarity index (SIMI_AM) is the sum, across all patches of the corresponding patch type, of the similarity index value multiplied by the proportional abundance of the patch [i.e., patch area (m2) divided by the sum of patch areas]. The similarity index is calculated as the sum, over all neighboring patches with edges within a speciﬁed distance (m) of the focal patch, of neighboring patch area (m2) times a similarity coeﬃcient between the focal patch type and the class of the neighboring patch, divided by the nearest edge-to-edge distance squared (m2) between the focal patch and the neighboring patch. The similarity index considers the size and proximity of all patches, regardless of class, whose edges are within a speciﬁed search radius of the focal patch. In resume, the similarity index quantiﬁes the spatial context of a (habitat) patch in relation to its neighbors of the same or similar class; speciﬁcally, the index distinguishes sparse distributions of small and insular habitat patches from conﬁgurations where the habitat forms a complex cluster of larger, hospitable (i.e., similar) patches (McGarigal et al. 2002). [386]

1447 Table 1. Values used to give a similarity weight between the diﬀerent patch types.

Kanah Kax Kelenche Juche Saakab Akalche Savanna

Kanah Kax

Kelenche

Juche

Saakab

Akalche

Savanna

1.00 0.73 0.60 0.39 0.08 0.01

1.00 0.77 0.47 0.09 0.02

1.00 0.52 0.10 0.02

1.00 0.11 0.02

1.00 0.08

1.00

In order to calculate the SIMI_AM, a search radius of 10 pixels (300 m) was considered. This radius is arbitrary but coincides with empirical evidence gathered in the ﬁeld about an expected average size of a patch type. In addition to the radius, this index requires for its calculations some similarity weights for each pairwise of patch types. In this case the mean values of 4 estimates of beta diversity between each pair of vegetation types were used as those weights (Table 1). These beta diversity estimates are similarity measures and are described by Magurran (1988). They were calculated using cumulative values of the sampling quadrats for each vegetation class. Two of these measures use presence and absence of species (i.e., Jaccard and Sorenson) while the other two require abundance data for their calculations (i.e., Sorenson-abundance and Morisita-Horn). Total edge contrast index (TECI) is the sum of the lengths (m) of each edge segment involving the corresponding patch type multiplied by the corresponding contrast weight, divided by the sum of the lengths (m) of all edge segments involving the same type, multiplied by 100 (to convert to a percentage). This metric is a relative measure. That is to say, given any amount or density of edge, they measure the degree of contrast in that edge. High values of these indices mean that the edge present is of high contrast, and vice versa (McGarigal et al. 2002). The weighted edge contrast between vegetation classes demanded to compute this metrics was calculated as the inverse values of the similarity weights (Table 1). Statistical analysis The statistical analysis to evaluate the relationship between landscape-patterns metrics and mean diversity values of trees, shrubs and vines per unit area, includes simple correlations and regression analysis. The mean diversity value of each patch type was calculated as the average value of all plots inside of a vegetation class. Since the dimensionality of the problem was large due to the multiple number of landscape metrics in the data, a principal components analysis was used to summarize the conﬁguration for the 6 metrics of classes to obtain new variables that were independent of each other (i.e., orthogonal), and yet represent the ‘‘aggregation’’ of the data reducing with it the dimensionality [387]

1448 of the problem. This was done while trying to avoid the well-known multicolinearity problem that often emerges among explanatory variables when the correlations between them are high. The variables need to be transformed with 1/x, log10(x), log10(x + 1) and sqrt(x) as necessary to meet the assumptions of normality and linearity (Tabachnick and Fidell 1996). The ﬁnal components at each level were found by a rotation procedure using the varimax method, yielding the ﬁnal principal components. Then, these were interpreted using component loading (correlation between the principal component and the original variable). In order to create a predictive model of plant diversity as a function of the computed ‘‘compound’’ variables represented by the principal components, the factor scores and the plant diversity indices were related using multiple regression analysis, producing models to predict plant diversity indices based on components created from landscape metrics of patch types. Finally, to avoid that the correlations between landscape pattern metrics and species diversity were confounded by habitat type, the analysis was conducted just for the four stages of succession in the tropical sub-deciduous forest class. Results Estimations of plant diversity indices The mean values of the tree plant diversity indices in each patch type for the four landscapes are presented in Table 2. The mean values of the diversity indices for the six vegetation types in every one of the four landscapes showed a similar pattern. Thus, kanah kax class (i.e., the oldest stage of succession in the forest) has more species and less dominance than kelenche, juche and saakab, which are early successional stages of the forest. Relating landscape-pattern metrics and plant diversity measures To evaluate the degree of association between metrics of patch types and plant diversity indices, correlation coeﬃcients between them were computed (see Table 3). The total edge contrast index (TECI), percentage of land (PLAND), edge density (ED) and mean area-weighted shape index (SHAPE_AM) showed the highest correlation coeﬃcients with most of the plant diversity variables. These coeﬃcients varied from 0.351 to 0.869 in absolute values. PLAND, ED and SHAPE_AM are positively correlated while TECI is negatively correlated with the diversity indices. This means that the diversity of a patch type increases with the augment in its area, irregular shape and perimeter, and when the contrast with other patch types decreases. So, classes that occupy larger proportion of the area of the landscape and show less contrast with neighboring patch types favor diversity of plants. Moreover, another variable of patch type metrics (SIMI_AM) was found moderately correlated with plant diversity indices varying from 0.351 and 0.395 in absolute values. [388]

1449 Table 2. Mean plant diversity values for the four landscapes of the study area. Vegetation type

Landscape 1 Kanah Kax Kelenche Juche Saakab Landscape 2 Kanah Kax Kelenche Juche Saakab Landscape 3 Kanah Kax Kelenche Juche Saakab Landscape 4 Kanah Kax Kelenche Juche Saakab

Number of species

Exponent Shannon

Reciprocal Simpson

Total

Trees

Shrubs

Vines

34.45* 33.00* 27.67* 19.67

26.70* 27.57* 19.00* 12.00

5.09* 6.00* 6.00* 4.67*

2.63* 1.92* 2.66* 2.00*

23.28* 20.13* 12.52* 13.22*

16.95* 14.12* 7.31* 9.32*

35.36* 34.67* 29.75* 16.20

27.57* 25.66* 22.50* 10.90

5.78* 7.00* 5.37* 3.90

1.92* 3.00* 1.87* 1.40*

22.74* 20.06* 16.78* 9.49

16.10* 13.38* 10.86* 6.67

34.08* 30.27* 28.71* 15.11

28.08* 23.45* 21.57* 9.77

4.33* 5.00* 5.28* 3.33*

1.66* 1.88* 2.00* 1.88*

20.63* 18.50* 15.90* 8.57

13.65* 13.18* 10.96* 6.24

36.60* 30.71* 27.00* 17.66

28.00* 24.85* 20.25* 10.67

4.80* 4.42* 3.75* 4.33*

4.00* 1.42* 3.00* 1.66*

19.66* 18.04* 15.32* 9.85*

12.51* 12.06* 10.45* 6.95*

*A Turkey HSD test was performed to compare the mean diversity values among vegetation classes by landscape, no signiﬁcant diﬀerences between these groups.

Considering the correlation of number of species of the diﬀerent group of plants (trees, shrubs and vines) with the landscape metrics of classes, the results vary according to the group of species considered. In the case of number of Table 3. Pearson correlation coeﬃcients between landscape spatial patterns of patch and between plant diversity indices and landscape patterns of patch types. VARIABLE

PLAND

PLAND PD 0.340* ED 0.513 SHAPE_AM 0.651 SIMI_AM 0.470 TECI 0.740 Number of species Total 0.791 Trees 0.829 Shrubs 0.351 Vines 0.186* Exp Shannon 0.865 Rec Simpson 0.869

PD

ED

SHAPE_AM

SIMI_AM

0.411 0.178* 0.305* 0.514

0.590 0.151* 0.091*

0.736 0.333*

0.283*

0.317* 0.289* 0.093* 0.354* 0.323* 0.314*

0.596 0.616 0.593 0.051* 0.591 0.575

0.561 0.652 0.464 0.016* 0.583 0.575

0.353 0.357 0.395 0.074* 0.351 0.369

*Correlations are not signiﬁcant at p < 0.05. Values in bold are for pairs highly correlated (r > |0.5|). [389]

TECI

0.490 0.520 0.125* 0.046* 0.603 0.619

1450 tree-species, the correlation with PLAND is very high (r = 0.829, Table 3), alternatively in the case of shrubs, there is a moderate correlation with the percentage of land (r = 0.351, Table 3) and there was not signiﬁcant correlation between PLAND and number of species of vines. This gives some idea of the importance of the percentage of land in the distribution of number of treespecies. In the case of richness of trees and shrubs it can be observed that edge density and shape have an important weight as explanatory factors, as opposed to the richness of vines, which is not associated with any of landscape metrics. On the other hand, no signiﬁcant correlation was found between the number of patches by hectare or patch density (PD) and plant diversity variables (p > 0.05, Table 3). The correlations between the 6 metrics of landscape patterns for patch types are also shown in Table 3. Most of the paired combinations of the metrics of patch types were signiﬁcantly correlated between them and 6 of the 15 possible paired combinations are highly correlated (r > |0.5|, Table 3), which may indicate a degree of redundancy in terms of the information that they provide about the structure of the landscape. Principal component analysis was performed on 6 landscape metrics of patch types for 16 observations. Two components in the studied area were selected as meaningful factors with eigenvalues greater than one, which explained 77.24% of the variation. After applying a varimax rotation, the components were interpreted as a gradient in percentage of land corresponding to a class (PLAND), the shape (SHAPE_AM), similarity (SIMI_AM) and the total edge contrast of the patch type (TECI). This ﬁrst principal component (PC1) explained 50.50% of the total variation in the original data. The second principal component (PC2) explained the additional 26.74% of the variation, and it is essentially a measure of number of patches found in a hectare (PD) and the edge density (ED). The percentage of variance explained by the two components and the correlation between the principal component and the original metrics of patch types are shown in Table 4. To ﬁnd a model for predicting plant diversity indices from uncorrelated variables derived from landscape metrics of patch types, a regression analysis was performed. The regression uses number of species (total, trees, shrubs and vines), exponent Shannon and reciprocal Simpson indices as dependent variables and the two components retained from the Principal Component Analysis (PCA) as independent variables. The results are shown in Table 5. The variability in total number of species and in the other two indices is explained by a moderately correlated variable related to percentage of land, similarity, shape and total edge contrast index (PC1) with Sr2 ranged from 0.453 to 0.479. Also the number of patches and edge density (PC2) explained the variability of the diversity indices, with Sr2 ranged from 0.113 to 0.154. The positive correlation with axis 1 of the PCA indicates that a patch types is more diverse when it is larger in area, more similar to its neighbors, has irregular shape and it is less contrasted with other patch types. The results of the regression considering the number of species of the three groups of plants and the two factors of landscape structure of patch types show [390]

1451 Table 4. Variance explained by two principal components derived from metrics of patch types and the weights of the variables in each component after rotation.

Explained variance Observed Eigenvalue % Variance Cum. % Variance Variable PLAND PD ED SHAPE_AM SIMI_AM TECI

PC1

PC2

3.03 50.50 50.50

1.60 26.74 77.24

0.90 0.50 0.42 0.83 0.75 0.73

0.11 0.79 0.85 0.36 0.05 0.33

*Marked loadings are >0.70.

diﬀerent responses and reveal that the factor associated with area, shape, similarity and contrast is more related to the richness of trees, and shrubs (Sr2 = 0.528 and 0.313, Table 5). On the other hand the factor (PC2) associated with number of patches and edge density is of variable importance depending on the group of species considered. Axis 2 of PCA appears to be only correlated with the richness of trees (Sr2 = 0.115, Table 5).

Discussion The analysis of the relationships between plant diversity variables and metrics of habitat types yield the following main results. The percentage of land (PLAND), a measure of landscape composition, showed a strong correlation Table 5. Summary of the regression procedures for predicting plant diversity indices from principal components derived from metrics of patch types. Dependent variable

Intercept*

Model parameters

B

Sr2

Adj R2

R2

Number of species Total

28.18

0.588

0.643

Shrubs Vines Exponent Shannon

4.94 – 16.54

0.264 – 0.584

0.313 – 0.640

Reciprocal Simpson

11.29

0.453 0.113 0.528 0.115 0.313 – 0.485 0.154 0.479 0.153

0.566

21.15

4.84 2.41 4.90 2.28 0.54 – 3.26 1.84 2.29 1.34

0.500

Trees

PC1* PC2** PC1* PC2** PC1* – PC1* PC2* PC1* PC2*

0.577

0.632

*Variables included in the model with p < 0.05. **Variables included in the model with p < 0.09. [391]

1452 with species richness (total, trees, and shrubs) and the other two additional diversity indices. This result together with the weak relationship between plant diversity and area of a fragment (Hernandez-Stefanoni 2005) may indicate the importance that fragmentation and diversity of habitats have on plant species diversity. Several small spread habitat patches usually contain more plant species than a few large habitat patches (Margules et al. 1994; Honnay et al. 1999), indicating that the availability of diﬀerent resources may be important for the establishment of plant species. Canopy openings events such as treefall, and ‘‘slash and burn’’ agriculture promote spatial variation of patch types that create several physical environments for plants that oﬀer an increasing in the availability of resources (Martinez-Ramos et al. 1988; Denslow 1995). This can improve species diversity for a speciﬁc patch type. However, forests with both very high or low frequency of disturbances, may both lead to low diversity, due to the fact that either pioneer species (fast-growing) or non-pioneer species (highly competitive and slow-growing) are respectively selected in each situation (Martinez-Ramos et al. 1988). Thus, this allows for the regeneration of similar group of species. The diﬀerent response to percentage of land by various groups of species (trees, shrub and vines) shows the importance of the frequency of disturbances and the diﬀerent life history of the species within each group. Given the fact that newly formed patches cover a lower proportion of the forest in the studied area (Hernandez-Stefanoni 2004), and that the community of oldest patches contains more individuals and includes the shade-intolerant species, the predominant class life history in the tropical forest (Whitmore 1989), it would be expected that a higher association between tree-species and percentage of land existed. The reason for this expectation is that the development of a similar group of species established under the canopy (shade-intolerant species) is favored. In contrast, in the shrub community the pioneer, shade-intolerant species are the predominant group (Denslow et al. 1990), making this group more dependant of gaps. In the case of vines, they depend on large plants for support and living, where vines maturation takes place. The availability of light however, has been proposed as other factor that promotes liana-species distribution, particularly near the edges where lianas can grow faster (Ibarra-Martinez and MartinezRamos 2002). Not all liana species however, are light demanding (Putz and Chai 1987). Therefore, vines-species presence could be favored by two main factors. First, vines can be established in oldest patches, where trees can provide them support. Second, several liana species are light demanding and grow well in natural or man-made disturbances (Putz 1984). Consequently, it is diﬃcult to establish an association between richness of vines and the diﬀerent metrics if there is not a division of these two main groups of vines. The degree of contrast between a patch type and its neighbors classes, measured as total edge contrast index, was a metric highly related to species richness (total, tree and shrub) and the other two plant diversity indices. These results may be explained by the fact that resource availability of a class is given [392]

1453 by the quality of the surrounding areas (Alvarez-Buylla and Garcia-Barrios 1991). However, Multivariate analysis of plant species diversity and metrics of patch types revealed that the three diversity indices are best predicted by the degree of contrast and similarity between classes as well as the percentage of land and the shape of a habitat type. These results may indicate that plant diversity of the tropical forest in the studied area is explained by a combination of factors. The relationship among plant diversity and various landscapemetrics shows that the number of species present in a given patch type is determined by several conditions, such as number of seed dispersed to the site, number of dormant seeds on the soil, the probabilities of germination and survival until they can reach maturity, and the resources provided by the environmental conditions of the patches or classes during their development (Schupp et al. 1989). Several studies have found that the conﬁguration or spatial arrangement of habitat types such as the degree of isolation, connectivity and fragmentation can be signiﬁcant predictors of species richness and other diversity variables. For instance Mazerolle and Villard (1999) found that landscape variables were signiﬁcant predictors of animal species richness in 36 studies reviewed, the groups of animal analyzed include amphibians, reptiles, mammals, arachnids, birds and several insects. There have been reports, also of similar results between plant species and landscape conﬁguration, for example Kollmand and Schneider (1999), investigating the correlation among mean a-diversity of woody species and attributes of habitat patches, found that landscape attributes such as patch size, total edge and patch fractal dimension are important in explaining species richness at forest edges. Similarly, Grasholf-Bokdam (1997) found that habitat heterogeneity and isolation of the habitat types might determine plant species composition and species richness within a habitat type. The statistical analysis applied to relate diversity variables with landscape metrics of patch types, shows the three diversity indices as having similar behavior. This behavior can be explained by the fact that these variables are highly correlated amongst themselves. This can be appreciated by examining the Spearman correlation coeﬃcient between species richness and the other two diversity indices of the ranked diversity values for the 16 patch types (0.96 and 0.91, p > 0.001 for Shannon and Simpson respectively). Although the strength and nature of the association between the diversity variables (number of species, exponent Shannon and reciprocal Simpson) and the metrics of patch types show a similar behavior, some diﬀerences can be appreciated. First, the relationships between percentage of land and species richness, exponent Shannon, as well as reciprocal Simpson indices (Table 3) showed a strong correlation. As it was discussed before, this result may indicate that events resulting in canopy openings, such as treefall, and ‘‘slash and burn’’ agriculture promote diﬀerent environmental conditions in the boundaries of the patches, compared with those at the center. This oﬀers an increasing in the availability of resources for plant species (Martinez-Ramos et al. 1988), and [393]

1454 creates an augmentation of habitat diversity (Honnay et al. 2003), which can improve plant species diversity for a speciﬁc patch type. However, the association between percentage of land and plant diversity indices is higher in Shannon and Simpson indices, compared with that of number of species. Second, in a similar way the shape index of patch types is more associated with Shannon and Simpson indices than with the number of species (Table 3 and 5). One of the reasons that may explain these relationships is that both plant species diversity and the number of individuals in a population increase as a consequence of a larger amount of resource availability (Brokaw 1985; Denslow 1995). That is, after a disturbance process takes place in a tropical forest, such as treefall, or a ‘‘slash and burn’’ event, the creation of canopy opening allows for the regeneration, establishment and growth of some particular species that require high light levels. These species can be pioneer species (Brokaw 1987) or those non-pioneer species that are suppressed under the canopy (Hubbell and Foster 1986). The canopy opening aﬀects species diversity in part because disturbances generally produce a local increase in tree density as a result of few large trees being replaced with numerous small ones (Uhl et al. 1988; Denslow 1995). Therefore, Shannon and Simpson indices may be more correlated to percentage of land and shape indices because they consider not only the number of species, but also their abundance. Additionally, it was also observed that the Simpson index was more strongly associated to the percentage of land and to the shape of a given patch type than the Shannon diversity index (Table 5). A possible explanation for this result lies in the diﬀerential sensitivity to rare and dominant species of both diversity indices (Peet 1974). The stronger association found between the Simpson diversity index and indices of patch types possibly results from the fact that Simpson index is more sensitive to the presence of the dominant species, such as those species that allows for an increase on plant density within the patch type. The results of this paper indicated that plant diversity estimates of patch types at landscape scale, such as number of species (total, tree and shrubs), Shannon and Simpson indices can be predicted from landscape metrics of habitat types. The appearance of shape, similarity and edge contrast indices in most of the models might imply that some generalization can be made about the eﬀects of patch type metrics over plant species, which may have a conservation use. Although it is diﬃcult to ﬁnd strategies that can help in the design of conservation areas or maintenance of particular groups of species, some generalizations can be made based on the results of this investigation. For instance, the maintenance of the ‘‘slash and burn’’ agricultural activities (Hernandez-Xolocotzi et al. 1995) or the promotion of small clear-cutting areas distributed in the forest (Hartshorn 1989), may lead to a high level of diversity not only allowing the establishment of pioneer species but also increasing the availability of resources at the limits of the patch types, thus providing conditions for the regeneration and establishment of other species.

[394]

1455 On the other hand the use of Shannon and Simpson diversity indices to assess plant diversity and its relationships to landscape patterns should be considered with caution. However, the question remains as to which diversity index should de used, and under what situations. Occurrences of rare species are among the most frequently used criteria for selecting and prioritizing habitat sites for preservation (Prendergast et al. 1993; Rossi and Kuitunen 1996). Moreover, the relative species abundance distribution of a tropical forest often follows a J-inverted shape (Magnussen and Boyle 1995), in particular in the studied area (Hernandez-Stefanoni 2004), which implies the probability of ﬁnding many species with low abundances. Thus, the Shannon diversity index, with its greater sensitivity to rare species, should be considered as having a greater importance in interpretation of the analysis. In fact, several published studies of plant diversity in tropical forests have elected to use this index (Fanliang et al. 1996; Nangendo et al. 2002). However, in particular cases where a single dominant species is of interest for management or conservation proposes, the Simpson diversity index should be preferred.

References Alvarez-Buylla E. and Garcia-Barros R. 1991. Seed and forest dynamics: a theoretical framework and an example from the neotropics. Am. Nat. 137(2): 133–154. Alvarez-Buylla E. and Martinez-Ramos M. 1992. Demography and allometry of Cecropia obtusifolia, a neotropical pioneer tree and evaluation of the climax-pioneer paradigm for tropical rain forest. J. Ecol. 80: 275–290. Bengtsson J. 1998. Which species? What kind of diversity? Which ecosystem function? Some problems in studies of relations between biodiversity and ecosystem function. Appl. Soil. Ecol. 10: 191–199. Brokaw N.V.L. 1985. Treefalls, regrowth and community structure in tropical forest. In: Pickett S.T.A. and White P.S. (eds), The Ecology of Natural Disturbances and Patch Dynamics. Academic Press, Orlando, Florida, USA, pp. 53–69. Brokaw N.V.L. 1987. Gap-phase regeneration of three tree pioneer species in a tropical forest. J. Ecol. 75: 9–19. Cabrera C.E., Souza S.M. and Tellez V.O. 1982. Imagenes de la ﬂora Quintanaroense. Centro de Investigaciones de Quintana Roo, Mexico. Carroll S.S. 1998. Modelling abiotic indicators when obtaining spatial predictions of species richness. Environ. Ecol. Stat. 5: 257–276. Debinski D. and Holt R.D. 2000. A survey and overview of habitat fragmentation experiments. Conserv. Biol. 14: 63–76. Denslow J.S., Schultz J.C., Vitousek P.M. and Strain B.R. 1990. Growth responses of tropical shrubs to treefall gap environments. Ecology 71(1): 165–179. Denslow J.S. 1995. Disturbance and diversity in tropical rain forest: the density eﬀect. Ecol. Appl. 5(4): 962–968. Eastman J.R. 1999. IDRISI 32: User’s Guide. Clark Labs for Cartography, Technology and Geographic Analysis. Clark University, Worcester, Massachusetts, USA. Earth Resource Mapping Ltd. 1998. ER Mapper 6.1. User Guide. San Diego CA. Fanliang H., Legendre P. and LaFrankie J.V. 1996. Spatial patterns of diversity in a tropical rain forest in Malaysia. J. Biogeogr. 23: 57–74. Grashof-Bokdam C.J. 1997. Forest plants in an agricultural landscape in the Netherlands: eﬀect of habitat fragmentation. J. Veg. Sci. 8: 21–28. [395]

1456 Gustafson E.J. 1998. Quantifying landscape spatial patterns: what is the state of the art? Ecosystems 1: 143–156. Gustafson E.J., Parker G.R. and Backs S.E. 1994. Evaluating spatial patterns of wildlife habitat: a case study of the wild turkey (Meleagris gallopavo). Am. Midl. Nat. 131: 24–33. Hartshorn G.S. 1989. Application of gap theory to tropical forest management: natural regeneration on strip clear-cuts in the Peruvian Amazon. Ecology. 70(3): 567–569. Hargis C.D., Bossonette J.A. and David J.L. 1998. The behavior of landscape metrics commonly used in the study of habitat fragmentation. Landscape Ecol. 13: 167–186. Hernandez-Stefanoni J.L. 2004. A Framework for Evaluating the Diversity Status of Trees, Shrubs and Vines in a Tropical Forest in Mexico based on Landscape Patterns Metrics and Spatial Modelling with GIS. Ph. D. dissertation, Trent University, Peterborough, Ontario, Canada. Hernandez-Stefanoni J.L. 2005. Relationships between landscape patterns and species richness of trees, shrubs and vines in a tropical forest. Plant Ecol. 179: 53–65. Hernandez-Stefanoni J.L. and Ponce-Hernandez R. 2004. Mapping the spatial distribution of plant diversity indices in a tropical forest using multi-spectral satellite image classiﬁcation and ﬁeld measurements. Biodiv. Conserv. 13: 2599–2621. Hernandez-Xolocotzi E., Baltaza E. and Tache S. 1995. La milpa en Yucatan, Un sistema agricola tradicional. Colegiode Postgraduados, Mexico. Honnay O., Hermy M. and Coppin P. 1999. Eﬀects of area, age and diversity of forest patches in Belgium on plant species richness, and implications for conservation and reforestation. Biol. Conserv. 87: 73–84. Honnay O., Piessens K., Van Landuyt W., Hermy M. and Guilinck H. 2003. Satellite based land use and landscape complexity indices as predictors for regional plant species diversity. Landscape Urban Planning 63(4): 241–250. Howe H.F. 1990. Habitat implications of gap geometry in tropical forest. Oikos. 59: 141–143. Hubbell S.P. and Foster R.A. 1986. Biology, change and history and the structure of tropical rain forest communities. In: Diamond J. and Case T.J. (eds), Community Ecology. Harper and Row, New York, pp. 314–329. Ibarra-Martinez G. and Martinez-Ramos M. 2002. Landscape variation of liana communities in a neotropical rain forest. Plant ecology. 160: 91–112. Kollman J. and Schneider B. 1999. Landscape structure and diversity of ﬂashy-fruited species at forest edges. Plant Ecol. 144: 37–48. Krebs C.J. 1989. Ecological Methodology. Harper Collins, New York. Krummel J.R., Gardner R.H., Sugihara G., O’Neill R.V. and Coleman P.R. 1987. Landscape patterns in a disturbed environment. Oikos. 48: 421–424. Magnussen S. and Boyle T.J.B. 1995. Estimating sample size for inference about Shannon-Weaver and the Simpson indices of species diversity. For. Ecol. Manage. 78: 71–84. Magurran A.E. 1988. Ecological Diversity and its Measurement. Princeton University Press, Princeton, NJ. Margules C.R., Nicholls A.O. and Usher M.B. 1994. Apparent species turnover, probability of extinction and the selection of natural reserves: a case of study of the Ingleborough limestone pavements. Conserv. Biol. 8: 398–409. Martinez-Ramos M., Alvarez-Buylla E., Sarukhan J. and Pin˜ero D. 1988. Treefall age determination and gap dynamics in a tropical forest. J. Ecol. 76: 700–716. Mazerolle M.J. and Villard M.A. 1999. Patch characteristics and landscape context as predictor of species presence and abundance: a review. Ecoscience 6(1): 177–124. McGarigal K. and Cushman S.A. 2002. Comparative evaluation of experimental approaches to the study of habitat fragmentation studies. Ecol. Appl. 12(2): 335–345. McGarigal K., Cushman S.A., Neel M.C. and Ene E. 2002. FRAGSTATS: Spatial Pattern Analysis for Categorical Maps. University of Massachusetts. Myers N. 1995. Environmental services of biodiversity. Proc. Natl. Acad. Sci. USA. 3: 2764–2763. Myers N., Mittermeier R.A, Mittermeier C.G., da Fonseca G.A.B. and Kent J. 2000. Biodiversity hotspots for conservation priorities. Nature 43(24): 853–858.

[396]

1457 Nangendo G., Stein A., Gelens M., Gier A. and Albricht R. 2002. Quantifying diﬀerences in biodiversity between a tropical forest area and a grassland area subject to traditional burning. For. Ecol. Manage. 164: 109–120. Peet R.K. 1974. The measurement of species diversity. Annu. Rev. Ecol. Syst. 5: 285–307. Prendergast J.R., Quinn R.M., Lawton J.H., Eversham B.C. and Gibbons D.W. 1993. Rare species, the coincidennce of diversity hotspots and conservation strategies. Nature 365: 335–337. Putz F.E. 1984. The natural history of lianas on Barro Coloraco Island, Panama. Ecology 65(6): 1713–1724. Putz F.E. and Chai P. 1987. Ecological studies in lianas in Lambir National Park, Sarawak. J. Ecol. 75: 523–531. Riitters K.H., O’Neill, R.V., Hunsaker C.T., Wickham J.D., Yankee D.H., Timmins S.P., Jones K.B. and Jackson B.L. 1995. A factor analysis of landscape pattern and structure metrics. Landscape Ecol. 10: 23–39. Roberts M.R. and Gilliam F.S. 1995. Patterns and mechanisms of plant diversity in forested ecosystems: implications for forest management. Ecol. Appl. 5(4): 969–977. Rossi E. and Kuitunen M. 1996. Ranking of habitats for the assessment of ecological impact in land use planning. Biol. Conserv. 77: 227–234. Schupp E.W., Howe H.F., Augspurger C.K. and Levey D.J. 1989. Arrival and survival in tropical treefall gaps. Ecology 70(3): 562–564. Tabachnick B.G. and Fidell L.S. 1996. Using Multivariate Statistics. Harper Collins College Publishers, New York. Uhl C., Clark K., Dezzeo N. and Maquirino P. 1988. Vegetation dynamics in Amazonian treefall gaps. Ecology 69: 751–763. Whigham D.F., Olmsted I., Cabrera Cano E. and Harmon M.E. 1991. The impact of hurricane Gilbert on trees, literfall and woody debris in a dry tropical forest in the northeastern Yucatan peninsula. Biotropica 23: 434–441. Whitmore T.C. 1989. Canopy gaps and the mayor groups of forest trees. Ecology 70(3): 536–538.

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Biodiversity and Conservation (2006) 15:1459–1466 DOI 10.1007/s10531-005-0599-5

Springer 2006

-1

Distribution, habitat and Red List status of the New Caledonian endemic tree Canacomyrica monticola (Myricaceae) JANE HERBERT School of Biology, Sir Harold Mitchell Building, University of St Andrews, KY16 9TH, UK; Present address: School of Integrative Biology, University of Queensland, Brisbane QLD 4072, Australia; (e-mail: [email protected]; phone: +01334-463372; fax: +01334-463366) Received 24 May 2004; accepted in revised form 24 June 2005

Key words: Bush ﬁre, Endangered, In situ conservation, Mining, Primary forest, Serpentine, Ultramaﬁc Abstract. The monotypic genus Canacomyrica Guillaumin is a small tree endemic to the rare remaining fragments of primary forest growing on ultramaﬁc geology in New Caledonia. In the rich ﬂora of this island it is one of many endemics to be threatened by habitat loss due to a variety of factors, most signiﬁcantly open-cast mining for nickel. Using ﬁeld observations and data from herbarium specimens the extent of occurrence of Canacomyrica monticola is established to be approximately 1420 km2. Within this area the distribution of C. monticola is very fragmented and limited to just 11 known localities. Six localities are outside protected areas; two of these may be imminently threatened by mining activity and another may be threatened by bush ﬁres. It is recommended that the IUCN Red List status of Endangered (EN B1ab (i,ii,iv,v)) is assigned to this species.

Introduction Canacomyrica is a monotypic genus endemic to the paciﬁc island group of New Caledonia, a territory renowned for its rich ﬂora (Jaﬀre´ et al. 2001b). Grande Terre, the main island has an area of just 19,000 km2 yet it is home to ﬁve endemic families, 106 endemic genera and more than 3200 species of vascular plants, a remarkable 74–75% of which are endemic (Jaﬀre´ et al. 2001b). Among these endemics are representatives of ancient lineages such as the taxon considered to be sister to all other extant ﬂowering plants, Amborella trichopoda (Zanis et al. 2002). The combination of high endemism and the presence of ‘relict’ taxa has lead to the recognition of New Caledonia as a distinct phytogeographic region (Takhtajan 1986). The unique ﬂora of New Caledonia is under threat from a number of factors including deforestation, introduced species, ﬁre, agriculture and livestock grazing (Olson et al. 2000). However, the greatest single threat posed to the island’s plants is the practice of open-cast mining for metals. New Caledonia has one third of the world’s reserves of nickel ore, found in the ultramaﬁc geology of the southern region and in the isolated massifs of the west coast of [399]

1460 Grande Terre (Brooks 1987). It is to these ultramaﬁc outcrops with their economically valuable, nutrient-deﬁcient soils, that many endemic plant taxa are restricted (eg. Pintaud et al. 1999; Jaﬀre´ et al. 2001a; Herbert et al. 2002; Whitlock et al. 2003). According to IUCN criteria (IUCN 1997) 14.4% of plant species in New Caledonia are Red Listed. However, this ﬁgure is likely to be much higher for plants endemic to, or growing predominantly on, ultramaﬁc substrate. The lack of suﬃcient data on many species is likely to be a further factor contributing to a misrepresentation of the true number of plants threatened with extinction in New Caledonia. Where speciﬁc groups have been examined in detail, the number of threatened species is found to be high. For example, the 43 species of conifer in the Territory are all endemic and of these, 67% are Red Listed (Farjon and Page 1999); similarly, of the 37 endemic palms, 35% are considered to be threatened (Pintaud et al. 1999). Regrettably only 5000 km2 of primary vegetation (28% of the original extent) remains in New Caledonia (Myers et al. 2000) and less than 10% of the land area has protected status (WWF and IUCN 1995; Jaﬀre´ et al. 1998; Pintaud et al. 1999). It has become clear in recent years that there is an urgent need for understanding and protection of the ﬂora of this island, along with its unique terrestrial fauna and marine biota (Bouchet et al. 1995; Jaﬀre´ et al. 1998; Mittermeier et al. 1996; Proctor 2003). New Caledonia has been acknowledged as one of the world’s 25 biodiversity ‘hotspots’ (Myers et al. 2000) and has been identiﬁed as one of the WWF’s ‘Global 200’ ecoregions, singled out as priority targets for conservation action (Olson et al. 2000). Canacomyrica monticola is an evergreen shrub or small tree (up to 7 m) with coriaceous leaves, ﬂowers borne in spikes and black drupaceous fruits. It is entirely restricted in its distribution to primary forest on the ultramaﬁc soils in the south of Grande Terre. Since its description (Guillaumin 1940) Canacomyrica has been largely neglected, almost nothing is known of its ecology, the plant is not in cultivation anywhere in the world, and its conservation status remains unknown. As the sole member of a geographically isolated genus, Canacomyrica has an important bearing on our understanding of evolutionary processes in Myricaceae (Herbert 2005). Basic data about its ecology and distribution is much needed to further knowledge about the entire family. Such information will also contribute to a better appreciation of the ecology of the rare remaining fragments of primary vegetation in New Caledonia. The aim of this study is to determine the distribution and habitat of Canacomyrica in New Caledonia and to assess its conservation status.

Materials and methods A list of all known localities for Canacomyrica was compiled from herbarium specimens held in three collections: Royal Botanic Garden, Edinburgh (E) (16 [400]

1461 specimens); Institut de recherche pour le de´veloppement, Noume´a (NOU) (35 specimens); the Muse´um National D’Histoire Naturelle, Paris (P) (47 specimens). The latter two institutions hold large numbers of collections of the New Caledonian ﬂora. Herbarium specimens have been acknowledged as suitable data sources for assessing plant distributions in the absence of other information (Willis et al. 2003). During a 3 week expedition to New Caledonia (RBGE expedition, May 2001) populations of Canacomyrica were sought from throughout the ultramaﬁc region of Grande Terre. Field observations, collections of herbarium specimens, seed and seedling collections were made by the author. Two populations were located and at each ﬁeld site, data were recorded on substrate, elevation, habitat features and threats to habitat. An attempt was made in each case to assess the extent and demography of the population. The conservation status of Canacomyrica was determined using the IUCN Red List criteria (IUCN 2001). Measurement of extent of occurrence is the ﬁrst step in estimating the geographic distribution of a species. The known localities of Canacomyrica were plotted on a map and a boundary drawn between them, the extent of occurrence was estimated by manual measurement of the area within this boundary.

Results A survey of the herbarium specimens held in Edinburgh (E), Paris (P) and Noumea (NOU) revealed 10 localities for Canacomyrica, and another was reported by T. Jaﬀre´ (personal communication). The exact positions of collection sites given on herbarium specimens were determined by consulting the H.S. MacKee gazetteer (Muse´um National D’Histoire Naturelle, Paris; http:// phanero.novcal.free.fr/site.html). The eleven localities, all of which were in the south of the island on ultramaﬁc substrate, are shown in Figure 1 and details are given in Table 1. Manual measurement of the area between the 11 known localities gave an extent of occurrence of 1420 km2. Canacomyrica was examined in the ﬁeld at Mont Bouo and Mont Mamie´ (Table 1, Figure 1). Plants at both sites were highly localised, occurring in almost monospeciﬁc stands with few or no outlying individuals. The local distribution of the populations appeared to be limited by water availability. At Mont Bouo plants of Canacomyrica were found only between altitudes of 1050 m and approximately 1150 m, growing in a rainforest community on ultramaﬁc substrate. Mature individuals were 3–4 m in height. The habitat at Mont Bouo appeared to be undisturbed and access was diﬃcult. At Mont Mamie´ plants of Canacomyrica were found at 500 m, the lowest recorded altitude for the plant (most collections have been made above 800 m). Canacomyrica was growing in a low scrub community co-dominated by Cyperaceae species on ultramaﬁc substrate, inundated with water from abundant natural springs. Mature individuals were up to 1 m in height; many [401]

1462

Figure 1. Map of New Caledonia showing the extent of ultramaﬁc geology and the position of the 11 known localities for Canacomyrica (extent of ultramaﬁc follows Jaﬀre´ et al. 1987).

seedlings were observed in this population. The habitat at Mont Mamie´ was disturbed and access was relatively easy due to the presence of mining prospecting tracks. At both sites there were more than 30 mature individuals but, it was not possible to estimate the total number of mature plants at either site due to the time constraints of the expedition. The total area occupied by the population at Mont Bouo was estimated to be approximately 100 m2. Time constraints also prevented estimation of the total area occupied by the population at Mont Mamie´. It was expected that further populations would be found at Mont Mou and Rivie`re Bleue but plants of Canacomyrica were not found at these localities during the expedition. All suitable habitat for Canacomyrica was searched at Mont Mou. At Rivie`re Bleue it was not possible to search all suitable habitat due to the diﬃculty of the terrain. On the basis of these observations, it is considered that a single collection from Mont Mou (Baumann-Bodenheim 15679, P) is a doubtful locality for Canacomyrica. It is thought likely that the specimen was collected elsewhere and incorrectly labelled, alternatively (but less likely) this collection may represent an extinct population. It was not possible to gain access to populations within the strictly protected Nature Reserve of Montagne des Sources. Other locations were not visited due to the time constraints of the ﬁeld study.

[402]

Table 1. Known localities for Canacomyrica, with coordinates and protected status details. Protected status and notesa

[403]

Locality

Coordinates

Mont Bouo (Koghis range)b Mont Mamie´b N’Goic Montagnes des Sourcesc Pourinac

2210¢ 2206¢ 2149¢ 2207¢ 2201¢

S S S S S

16630¢ 16653¢ 16630¢ 16633¢ 16644¢

E E E E E

Ouinne´c Kouakoue´c Humboldtc Nembrouc Ne´kandoc Foreˆt de Sailled

2157¢ 2157¢ 2153¢ 2145¢ 2150¢ 2140¢

S S S S S S

16642¢ 16632¢ 16625¢ 16613¢ 16620¢ 16613¢

E E E E E E

Protected – amenity protected area, adjacent to the Strict Nature Reserve of Montagne des Sources Unprotected – mining activity observed Unprotectede – adjacent to existing Special Botanical Reserve of Mt Humboldt (5 km) Protected – Strict Nature Reserve of Montagne des Sources Unprotected – adjacent to Special Botanical Reserve of Haute Pourina (3 km) and Natural park of Rivie´re Bleue (5 km) Unprotectede Protectedf – Special Fauna and Flora Reserve of Mt Kouakoue´ Protectedf – Special Botanical Reserve of Mt Humboldt Unprotected – adjacent to Special Botanical Reserve of Foreˆt de Saille (5 km) Unprotected – adjacent to Special Botanical Reserve of Mt Humboldt Protected – Special Fauna and Flora Reserve of Foreˆt de Saille

a

Sources of information on protected status: Pintaud et al. (1999), J. Manaute (personal communication). Locality visited by the author. c Locality determined from herbarium specimens. d Locality according to T. Jaﬀre´ (personal communication). e Site adjacent to proposed ‘Ni-Kouakoue´-Ouinne´’ reserve. f Site expected to be included in the proposed ‘Ni-Kouakoue´-Ouinne´’ reserve. Map coordinates are intended as a guide only. b

1463

1464 Discussion Canacomyrica is known to occur in 11 localities in the south of Grande Terre, New Caledonia where it grows exclusively on ultramaﬁc substrates. Of these localities, six are aﬀorded no oﬃcial protection and disturbance has been observed at the Mont Mamie´ site. There is evidence of disturbance caused by mining prospecting at the Ouinne´ site and the Nembrou site is potentially threatened by bush ﬁre (J. Manaute and T. Jaﬀre´, personal communication). Canacomyrica is estimated to have an extent of occurrence of 1420 km2 and within this area its distribution is patchy. If the population at Mt Bouo is typical, where Canacomyrica occurs in an area of approximately 100 m2, then it is tempting to speculate that the total area of occurrence for the species is signiﬁcantly smaller than its area of occupancy. Continuing decline is projected in both the area and extent of occurrence, and number of locations. Also, continuing decline in number of mature individuals is inferred at the Mont Mamie´, Ouinne´ and Nembrou sites. It is therefore recommended that Canacomyrica monticola is given the IUCN (2001) Red List status of Endangered (EN B1ab (i,ii,iv,v)). The principal threats to Canacomyrica are likely to be open-cast mining and bush ﬁres in areas of its occurrence lacking protected status. The most imminently threatened populations are at Mont Mamie´, Ouinne´ and Nembrou. Habitat destruction in an area where Canacomyrica occurs may entirely destroy localised and fragmentary populations that are characteristic of this species. It is encouraging that age structure, indicative of recent regeneration, was observed at Mont Mamie´ although it is stressed that this was only observed on undisturbed substrate. In experimental work, approximately 90% of fruits examined were sterile and ex situ germination of seeds and cultivation of seedlings was unsuccessful (Herbert 2005). This suggests that in situ measures are likely to be the best if not the only approach for the conservation of this species. Conservation achieved through a network of protected areas is considered to be the most eﬀective way to preserve biodiversity (Primack 2000). This is never more appropriate than in the case of species with highly specialised ecological requirements that are unlikely to thrive anywhere but in their natural habitat, such as Canacomyrica. Whilst it is desirable for additional data to be collected on numbers of individuals, area of occurrence and threats to localities other than those detailed here, the data presented are suﬃcient to permit the following recommendations to be made: (1) expansion of the Special Botanical Reserves of Haute Pourina and the Foreˆt de Saille should be undertaken to protect the populations at Pourina and Nembrou; (2) the proposed ‘NiKouakoue´-Ouinne´’ reserve (project under consideration; J. Manaute, personal communication) should include the sites at N’Goı¨ and Ouinne´; (3) special attention should be given to Canacomyrica when botanical surveys or inventories are carried out at sites on ultramaﬁc to enhance knowledge of the distribution and demography of this species; (4) an investigation to assess the level [404]

1465 of genetic diversity, both within and among populations, should be carried out to act as a guide for the prioritisation of populations in future conservation management. Protection of the above mentioned populations would raise the number of protected localities for Canacomyrica from ﬁve to nine, or 82% of all known sites. These measures represent the ﬁrst steps towards ensuring the continued survival of Canacomyrica. Furthermore, conservation measures targeted at Canacomyrica will help to raise the proﬁle and survival prospects of some of the last remaining fragments of New Caledonia’s primary forest.

Acknowledgements I would like to thank two anonymous reviewers for comments on an earlier draft of this manuscript. T. Jaﬀre´ (IRD, Noume´a, New Caledonia) and J. Manaute (Province Sud) are acknowledged for valuable additional information and comments on earlier drafts of the manuscript. M. Hughes (RBGE) is thanked for comments on the manuscript. P.M. Hollingsworth and M. Gardner (RBGE) are thanked for organising the expedition to New Caledonia and, along with A. Ponge, for their help with collecting Canacomyrica. The administration of Province Sud, New Caledonia is acknowledged for permission to collect. H. Hodge (University of St Andrews) and A. Ensoll (RBGE) are thanked for cultivation of plants. Financial support for ﬁeld work was provided by the Russell Trust (University of St Andrews) and the Davis Expedition Fund (University of Edinburgh). This study was supported by a NERC studentship (NER/S/A/2000/03638).

References Bouchet P., Jaﬀre´ T. and Veillon J.M. 1995. Plant extinction in New-Caledonia – Protection of sclerophyll forests urgently needed. Biodivers. Conserv. 4: 415–428. Brooks R.R. 1987. Serpentine and its Vegetation. A Multidisciplinary Approach. Croom Helm, London, UK, pp. 330–353. Farjon A. and Page C.N. (compilers) 1999. Status Survey and Conservation Action Plan. IUCN/ SSC Conifer Specialist Group, IUCN, Gland, Switzerland, pp. 41–50. Guillaumin A. 1940. Mate´riaux pour la ﬂore de la Nouvelle-Cale´donie. LVII. La pre´sence d’une Myricace´e. Bulletin de la Socie´te´ Botanique de France 87: 299–300. Herbert J. 2005 Systematics and biogeography of Myricaceae. Unpublished Ph.D. Thesis, University of St Andrews, St Andrews. Herbert J., Hollingsworth P.M., Gardner M.F., Mill R.R., Thomas P.J. and Jaﬀre´ T. 2002. Conservation genetics and phylogenetics of New Caledonian Retrophyllum (Podocarpaceae) species. New Zeal. J. Bot. 40: 175–188. IUCN 1997. Red List of Threatened Plants. IUCN Species Survival Commission, http://iucn.org/ themes/ssc/97plrl/table5.htm [accessed 26 April 2004]. IUCN 2001. IUCN Red List Categories and Criteria: Version 3.1. IUCN Species Survival Commission, Gland, Switzerland. [405]

1466 Jaﬀre´ T., Bouchet P. and Veillon J.M. 1998. Threatened plants of New Caledonia: Is the system of protected areas adequate? Biodivers. Conserv. 7: 109–135. Jaﬀre´ T., McCoy S., Rigault F. and Navarro E. 2001a. A comparative study of ﬂora and symbiotic microﬂora diversity in two Gymnostoma formations on ultramaﬁc rocks in New Caledonia. S. Afr. J. Sci. 97: 599–603. Jaﬀre´ T., Morat Ph., Veillon J.M. and MacKee H.S. 1987. Changements dans la ve´ge´tation de la Nouvelle-Cale´donie au cours du Tertiaire: la ve´ge´tation et la ﬂore des roches ultrabasiques. Adansonia 4: 356–391. Jaﬀre´ T., Morat Ph., Veillon J.M., Rigault F. and Dagostini G. 2001b. Composition and Characteristics of the Native Flora of New Caledonia. IRD, Noume´a, pp. 28–29. Mittermeier R.A., Werner T.B. and Lees A. 1996. New Caledonia – A conservation imperative for an ancient land. Oryx 30: 104–112. Myers N., Mittermeier R.A., Mittermeier C.G., da Fonseca G.A.B. and Kent J. 2000. Biodiversity hotspots for conservation priorities. Nature 403: 853–858. Olson D.M., Dinerstein E., Abell R., Allnutt T., Carpenter C., McClenachan L., D’Amico J., Hurley P., Kassem K., Strand H., Taye M. and Thieme M. 2000. The Global 200: A Representation Approach to Conserving the Earth’s Distinctive Ecoregions. World Wildlife Fund-US, Conservation Science Program, Washington, DC. http://www.panda.org/about_wwf/where_ we_work/ecoregions/global200/downloads [accessed 26 April 2004]. Pintaud J.C., Jaﬀre´ T. and Veillon J.M. 1999. Conservation status of New Caledonia palms. Pac. Conserv. Biol. 5: 9–15. Primack R.B. 2000. A Primer of Conservation Biology. Sinauer Associates Inc., Sunderland, Massachusetts, pp. 183. Proctor J. 2003. Vegetation and soil and plant chemistry on ultramaﬁc rocks in the tropical Far East. Perspect. Plant Ecol. Evol. Syst. 6: 105–124. Takhtajan A. 1986. Floristic Regions of the World. University of California Press, Berkeley, pp. 248–253. Whitlock B.A., Karol K.G. and Alverson W.S. 2003. Chloroplast DNA sequences conﬁrm the placement of the enigmatic Oceanopapaver within Corchorus (Grewioideae : Malvaceae S. L., formerly Tiliaceae). Int. J. Plant Sci. 164: 35–41. Willis F., Moat J. and Paton A. 2003. Deﬁning a role for herbarium data in Red List assessments: a case study of Plectranthus from eastern and southern tropical Africa. Biodivers. Conserv. 12: 1537–1552. WWF and IUCN 1995. Centres of Plant Diversity. A Guide and Strategy for their Conservation Vol. 2. IUCN Publications Unit, Cambridge, UK, pp. 529–541. Zanis M.J., Soltis D.E., Soltis P.S., Mathews S. and Donoghue M.J. 2002. The root of the angiosperms revisited. Proc. Natl. Acad. Sci. USA 99: 6848–6853.

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Biodiversity and Conservation (2006) 15:1467–1495 DOI 10.1007/s10531-005-1876-z

Springer 2006

-1

Composition of woody species in a dynamic forest–woodland–savannah mosaic in Uganda: implications for conservation and management GRACE NANGENDO1,*, HANS TER STEEGE2 and FRANS BONGERS3 1

International Institute for Geo-information Science and Earth Observation, P.O Box 6, 7500 AA Enschede, The Netherlands; 2National Herbarium Netherlands, Utrecht University Branch, Heidelberglaan 2, 3584 CS Utrecht, The Netherlands; 3Forest Ecology and Forest Management Group, Centre for Ecosystem Studies, Wageningen University, P.O. Box 47, 6700 AA Wageningen, The Netherlands; *Author for correspondence (phone: +31-53-4874444; fax: +31-53-4874388) Received 21 December 2004; accepted in revised form 19 July 2005

Key words: Budongo Forest Reserve, Fire disturbance, Forest–woodland–savannah mosaics, Species gradient, Woody species composition Abstract. Forest–woodland–savannah mosaics are a common feature in the East African landscape. For the conservation of the woody species that occur in such landscapes, the species patterns and the factors that maintain it need to be understood. We studied the woody species distribution in a forest–woodland–savannah mosaic in Budongo Forest Reserve, Uganda. The existing vegetation gradients were analyzed using data from a total of 591 plots of 400 or 500 m2 each. Remotely sensed data was used to explore current vegetation cover and the gradients there in for the whole area. A clear species gradient exists in the study area ranging from forest, where there is least disturbance, to wooded grassland, where frequent ﬁre disturbance occurs. Most species are not limited to a speciﬁc part of the gradient although many show a maximum abundance at some point along the gradient. Fire and accessibility to the protected area were closely related to variation in species composition along the ordination axis with species like Cynometra alexandri and Uvariopsis congensis occurring at one end of the gradient and Combretum guenzi and Lonchocarpus laxiﬂorus at the other. The vegetation cover classes identiﬁed in the area diﬀered in diversity, density and, especially, basal area. All vegetation cover classes, except open woodland, had indicator species. Diospyros abyssinica, Uvariopsis congensis, Holoptelea grandis and all Celtis species were the indicator species for the forest class, Terminalia velutina and Albizia grandbracteata for closed woodland, Grewia mollis and Combretum mole for very open woodland and Lonchocarpus laxiﬂorus, Grewia bicolor and Combretum guenzi for the wooded grassland class. Eleven of the species occurred in all cover classes and most of the species that occurred in more than one vegetation cover class showed peak abundance in a speciﬁc cover class. Species composition in the study area changes gradually from forest to savannah. Along the gradient, the cover classes are distinguishable in terms of species composition and vegetation structure. These classes are, however, interrelated in species composition. For conservation of the full range of the species within this East African landscape, the mosaic has to be managed as an integrated whole. Burning should be varied over the area with the forest not being burnt at all and the wooded grassland burnt regularly. The diﬀerent vegetation types that occur between these two extremes should be maintained using a varied ﬁre regime.

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1468 Introduction Large areas of East Africa are covered with forest–woodland–savannah (FWS) mosaics. Fire, both of natural and anthropogenic origin, is typical for the woodland–savannah part of the mosaic (Walter 1985). The fresh grass that regrows after ﬁre is advantageous for the many ungulates of East Africa and many of these ecosystems are, therefore, managed mainly for wildlife conservation. Forests, on the other hand, are managed for timber production, for woody species conservation, as water catchment areas, and for their aesthetic values. Consequently the forest and the woodland–savannah areas, even where they occur together as a mosaic, are often treated as independent conservation entities. Uganda is has large tracts of FWS mosaics. Several of these FWS mosaics have been enlisted for demarcation as conservation areas because of their high biodiversity value (Forest Department Uganda 1999), yet surveys in such areas have focused on the forest and have not taken the woodland areas into account. Although forests are arguably richer in species (Sheil and Burslem 2003), this does not do justice to the speciﬁc ﬂora and fauna found in woodlands that are adjacent to or within the forests. In our study area, Budongo Forest Reserve, ﬁre has been used as a management tool in the woodland areas for hundreds of years (Paterson 1991). The local people, resident on the outskirts of the forest reserve, set most of the ﬁres. Changes in management of the area, which resulted in more active policing of the protected area and the establishment of a gate entrance to the only access route, have led to less use of ﬁre in the woodland areas. As a consequence, forest vegetation is now colonizing the woodland areas (van Straaten 2003). It is unknown to what extent accessibility to the protected area acts as a controlling factor. As speciﬁc ﬂoristic information for the area is lacking, it is as yet unknown what the eﬀects of continuing reforestation will be on the tree diversity of Budongo Forest Reserve. In this paper, we explore the current status of the forest in terms of species composition and diversity, and how it is distributed in space. Studies that have explored the species interrelationship within FWS mosaics are rare (Hovestadt et al. 1999). Most studies have concentrated on species distribution within the forest (Eggeling 1947; Sheil et al. 2000; Mwami and McNeilage 2003; Eilu et al. 2004) or the woodland–savannah (Swaine et al. 1992; Schwilk et al. 1997; Schwartz and Caro 2003; Li et al. 2004). Previous data of Budongo forest (Eggeling 1947) stimulated the emergence of the important Intermediate Disturbance Hypothesis (Connell 1978), which states that in a landscape, species diversity is highest in areas with an intermediate level of disturbance. In areas of high disturbance and areas of low or no disturbance, species diversity is low. At the time of Eggeling’s (Eggeling 1947) study, frequent burning had arrested the forest succession into the woodland. Eggeling’s gradient mainly reﬂects succession within the forested area. With the increased control of burning over the years, resulting in variation of burning [408]

1469 with some areas burnt more often than others, forest succession into the woodland became possible. Hence, an added component of our study is the extension of a historically important succession gradient, exploring its range into the woodland areas. In our study, special emphasis was placed on how the existing vegetation types can be characterized in terms of the woody plants and the implication of the observed species patterns to conservation of woody plants in such landscapes. The hypothesis made is that all the vegetation types that exist within the study area, and the species they support, are an integral part of a compositional/successional gradient that stretches across the FWS mosaic. We asked the following questions: Is it possible to quantify the gradient? What species are speciﬁc for certain areas? How does the species composition vary along the succession gradient? Can the gradient be explained in relation to environmental variables? A further question we address is whether a satellite image classiﬁcation of the area can be used to adequately map the vegetation and its composition in the area. For this we made use of discrete vegetation cover classes, obtained from a classiﬁcation carried out using a combination of spectral information and environmental variables’ information (Nangendo et al., submitted). The vegetation classes are considered a proxy of the vegetation types found in the area. Standard vegetation indices (NDVI and Tasseled Cap vegetation index) based on the same image were also compared in their ability to explain the observed gradient. Finally, we discuss the conservation and management implications of our results.

Materials and methods Study area The work was carried out in the northern part of Budongo Forest Reserve in north-western Uganda. The area is located between 135¢ and 155¢ N and 3118¢ and 3142¢ E. It receives between 1397 and 1500 mm of rain annually on 100 to 150 days. There are two main forest blocks: the main Budongo Forest block and the Kaniyo-Pabidi Forest block (Figure 1). A woodland area, interspersed with forest patches, commonly referred to as Kaniyo-Pabidi woodland, separates these two blocks. The underlying geology of the Budongo Forest is Precambrian origin consisting of high-grade metamorphic rocks of the 2.9 billion-year-old granulite group (van Straaten 1976). The soils over 90% of the study area are orthic Ferralsols: highly weathered, deep, well drained soils with low pH. The remaining 10% of the area has typically shallow soils, called Lithosols. These soils are mainly found on hilltop regions and are predominantly underlain by rocks. In river valleys, eutric Fluvisols are present. [409]

1470

Figure 1. Map of study area location.

In the woodlands, ﬁre has been prevalent for hundreds of years (Paterson 1991). The woodland burning was initially carried out by the local people for purposes of hunting and refreshing grass for both domestic and wild ungulates (Buechner and Dawkins 1961). With the transfer of the control of the woodlands from the local people (Bunyoro Kingdom) to the central government (Forest Department) in 1968, measures to control burning were put in place (Forest Department Uganda 1997). These were not very eﬀective, however, until the establishment of the joint management between Forest Department and Uganda Wildlife Authority in the mid 1980s. Fewer, and smaller, areas are now burnt and the burning is also less frequent. The woodland is therefore heterogeneous and made up of vegetation patches at varying stages of recovery since they were last burnt.

Data collection Data was collected from 591 plots, 266 of which had an area of 400 m2 and 326 with an area of 500 m2. All data were collected during the same period (August–October 2002). Along a transect, perpendicular lines were laid every 300 m. Along each perpendicular line, data were collected at every 75 m. For sites 1–5, a plot size of 400 m2 was used (Figure 2), while for sites a–e, it was 500 m2. Based on a 2002 satellite image of the study area, sites 1–5 were located in areas that showed a similar spectral reﬂectance, whereas sites a–e were located in areas that showed varying spectral reﬂectance. The variation [410]

1471

Figure 2. The location of the data collection points. 1, 2, 3, 4 and 5 are locations where the plots were 400 m2 and a, b, c, d, e and f are locations where the plot size was 500 m2.

[411]

1472 of the site locations was to ensure that we capture as much as possible of the species variation within the area. In each plot, the following data were collected: • Plot coordinates • Species names, diameter at breast height (DBH) for all woody plants ‡10 cm DBH, measured at 130 cm. If the tree was buttressed and abnormal at 130 cm, the diameter was measured just above the buttress where the stem assumes a near cylindrical shape. • Canopy cover percentage, using a canopy densiometer (Robert E: Lemmon, Forest Densiometers, Oklahoma, USA), following the provided guidelines. Four measurements were taken in each plot and an average of these measurements was calculated to determine the ﬁnal canopy cover of the plot. • A ﬁre indicator value. The ﬁre indicator value was based on several factors (1) the degree of scorching on the woody stems i.e. if it was fresh or old, (2) if there existed remains of burnt grass in the undergrowth and (3) whether fresh ash was found in the area. The last two factors were used to conﬁrm areas with recent ﬁre. Plots with fresh ﬁre scorching on the woody stems, remains of burnt grass or ash were recorded as ‘recent burns’ and labelled class 2. Plots with old signs of ﬁre were labelled class 1 (old ﬁres) and plots with no sign of ﬁre were labelled class 0 (no ﬁre). Species identiﬁcation was based on Eggeling and Dale (1952) and Hamilton (1991). Samples of the species that could not be clearly identiﬁed in the ﬁeld by the botanists on the team (Israel Tinka and Hezekias Ddumba) were sent to the Uganda National Herbarium, Makerere University, where they were identiﬁed.

Data preparation A Detrended Correspondence Analysis (DCA) (Multi-Variate Statistical Package MVSP 3.11, Kovach Computing Services, UK) was run using the two data sets i.e. for the 400 m2 plots and the 500 m2 plots. When the plot scores of DCA axis one and two were plotted together, using a separate symbol for each plot size, the data for the two sets fell within the same range i.e. they showed near to identical results and complemented each other. As the plots also overlap spatially, it was therefore decided to pool the two data sets. Expressing density as the number of trees per 1000 m2, the abundance values were calculated for each plot. Plots with less than 10 individuals were removed from the data. As the larger plots have more individuals and thus capture more species on average than the smaller plots, rare species, deﬁned as those having a total of less than 25 individuals, were also removed from the data set. The ﬁnal dataset consisted of 491 plots with 45 species. From the DBH values measured in the ﬁeld, basal area (BA, m2 ha1) was calculated for each plot, including all trees of the actual plot data. [412]

1473 Remote sensing Values of the Normalized Diﬀerence Vegetation Index (NDVI), which is well correlated with vegetation biomass (Tucker 1979) and Tasseled Cap vegetation index (TC), which has a good correlation with forest stand density (Crist et al. 1986), were extracted for each plot from the respective vegetation index maps calculated using a 2002 Landsat ETM+ satellite image. These values were used for further analyses. Vegetation indices provide values that are indicative of the spectral reﬂectance of the vegetation at a given place. Depending on the satellite image bands selected and the ratios used, each vegetation index measure will result in a diﬀerent value for a speciﬁc plot. Because there is a high variation in reﬂectance over a forested area, the resultant pixel values for a given index vary from point to point resulting in continuous values over the forested area. NDVI used two bands, red and near infrared. Tasseled Cap incorporates more information by using six diﬀerent light bands (blue, green, red, near infrared and far infrared). Depending on the ratios of combination of the six bands, diﬀerent multispectral features are obtained (Crist and Cicone 1984). The ﬁrst three features usually account for most of the variation in a single date image (Collins and Woodcock 1996). These three have been labelled brightness, greenness and wetness, respectively. All three were used in this study. Vegetation cover class values for each plot were extracted from a vegetation cover map of the area obtained from an earlier classiﬁcation (Nangendo et al., submitted) of a Landsat ETM+ image using both spectral and environmental information. All 592 plots were separated into the discrete cover classes (forest, closed woodland, open woodland, very open woodland and wooded grassland). Having used a Landsat satellite image, with a pixel size of 30 m, in the classiﬁcation, the minimum area belonging to a speciﬁc cover class is 900 m2. Species composition, diversity and forest structure were analyzed in consideration of the cover class in which each plot fell with the assumption that these vegetation cover classes were representative of the major vegetation variation within the area.

Accessibility We used distance from the southern forest boundary to each plot as a surrogate for accessibility, by the local people, to the sampled areas. The conservation area gate marks the southern boundary between the conservation area and the local people’s settlements. From here on, distance will be referred to as ‘distance from gate.’ During ﬁeldwork, it was observed that because of the gate control, the local people entered the protected area at other points along the boundary of the protected area, instead of using the road. Having recorded the coordinate of the gate location, an east–west line was established at this point

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1474 and distance for each plot was calculated based on this line. This provided the plot distance relative to the conservation area gate.

Analysing the gradient We used Detrended Correspondence Analysis to explore the species distribution within the study area. To determine which variables best explained the gradient in species composition, the plot scores on the DCA axes were related to the site variables using stepwise regression.

Linking remote sensing with the gradient Two approaches were used in analysing remote sensing outputs. First, plot values obtained from vegetation indices (such as TC), which are continuous classiﬁers, were compared to DCA plot scores. To identify the vegetation index that best explained the gradient, a non-linear regression method was used since the scatter plot of the DCA vs. the index values showed a non-linear relationship. Second, discrete classes obtained from an earlier classiﬁcation (Nangendo et al., submitted) were analyzed for diﬀerences in terms of species composition and diversity and, in basal area. Although the same satellite image was used for the classiﬁcation and for the creation of the index maps, the plots used for the classiﬁcation are not the same as those used in the analysis.

Diﬀerences in composition We used the Multiple-Response Permutation Procedure (MRPP) and Indicator Species Analysis of PC-ORD (McCune and Meﬀord 1999; McCune et al. 2002) to test for diﬀerences in composition between the diﬀerent vegetation units. MRPP, a non-parametric procedure was used for testing the hypothesis that no diﬀerence existed in composition between two or more groups of plots. For distance in composition between the plots, Relative Sørensen (Bray–Curtis) was used because it takes into account both compositionP (presence–absence of species) and abundance. For weighting option: CI = nI/ nI was used, which is the most widely used and recommended measure. CI is the weight and is dependent on the number of items in a group, say I, and nI is the number of items in group I. The software uses 9999 permutations in the test. Two tests were carried out based on a priori selection: cover classes and ﬁre classes. An Indicator Species Analysis was also carried out on the basis of these two classiﬁcations. Indicator species Analysis combines information on the concentration of species abundance in a particular group (transect) and the faithfulness of occurrence of the species in that group. A perfect indicator species of a [414]

1475 particular group should always be present and should also be exclusive to that group (not occurring in other groups). From the analysis, an indicator value is obtained for each species in each group (Dufreˆne and Legendre 1997; McCune and Meﬀord 1999; McCune et al. 2002). The indicator values are tested for statistical signiﬁcance using a Monte Carlo randomization. Species diversity was expressed as species dominance, which was calculated using the Simpson Index (SI) (Magurran 1988), and Fisher’s a (Fa), (Fisher et al. 1943). These indices have low sensitivity to plot size diﬀerences (Magurran 1988). Diﬀerences between plots in diﬀerent ﬁre and cover classes with respect to SI, Fa and BA were tested with ANOVA using SPSS (SPSS 10, SPSS Inc. USA). To check for variation in species abundance and diversity in relation to disturbance, graphs of number of species per 100 m2 and Fisher’s a per plot were made. Having the assumption, which was also backed by ﬁeld observation, that disturbance was lowest in the forest class and highest in the wooded grassland class, plots were arranged according to vegetation cover classes. The order of plot arrangement was; forest (1–147), closed woodland (148–310), open woodland (311–459), very open woodland (460–555) and wooded grassland (556–592). Within each vegetation cover class the plots are randomly ordered.

Results Species distribution A total of 26,076 individuals from 121 species, 89 genera, and 38 families were recorded on the 591 plots. The most species-rich family was Moraceae with 11% of all species found (13), followed by Euphorbiaceae and Mimosaceae with 8% each (10). The most species-rich genus was Ficus with 5% of all species (6), followed by Acacia, Albizia, Celtis and Combretum with 3% each (4). Nine species or 7% of all species could not be identiﬁed to genus level. A full species list with abundances is given in Appendix 3. The most abundant genus, in terms of total individuals encountered, was Combretum, with close to 16% of all individuals, followed by Terminalia (14%), Grewia (13), Stereospermum (6%), and Uvariopsis (6%). The DCA analysis on combined and trimmed data (491 plots and 45 species) ordered the plots mainly along 1 axis (Figure 3a). This axis had a relatively high eigenvalue (0.465) suggesting signiﬁcant woody species variation along this axis. The eigenvalue for the second axis was 0.172. With 491 plots included, axis 1 explained 11.8% of the variation. There was, however, one outlier plot strongly inﬂuencing the second axis. This outlier plot was dominated by Sapium elipticum, a species that rarely occurred in the study area. After removing this plot, axis 1 explained 12.5% of the variation and axis 2 an additional 4.6%. Plots with a low axis score (close to 0) are found in the forest area, plots with a high score (>7) are found in the most open areas. As most of [415]

1476

[416]

1477 the discussion here on will pertain to axis 1, the main gradient, we will abbreviate ‘DCA axis 1 plot scores’ to ‘DCA scores.’ The species plot (Figure 3b) also shows most of the variation along the ﬁrst axis. The eﬀect of the second axis is only evident close to zero along axis 1, the forest side, where there appear to be two groups (the same can be said for the plot scores). Based on this interpretation the species can be divided into three groups; A, B and C (Figure 3b). Groups A and B occur within the forest area and group C, probably starting at the forest edge, stretches through to the woodland area. Species found in group A include Cynometra alexandri, Diospyros abyssinica and Khaya anthotheca. Group B species include Uvariopsis congensis, Celtis wightii, Holoptelea grandis and Funtumia elastica. And species found in group C include Albizia grandibracteata, Terminalia velutina, Grewia mollis, Combretum molle and Lonchocarpus laxiﬂorus. Fire indicator best explained the gradient in species composition followed by slope and then distance from gate. Using the stepwise regression analysis, ﬁre alone had r2 of 0.324 with a standard error of 1.395. Including slope in the model the r2 was raised to 0.354 and the standard error reduced to 0.365. When distance from gate was included, the r2 increased to 0.359 and the standard error was reduced to 1.361. Vegetation cover type was not signiﬁcant and so it does not appear in the results table. Relating the site variables individually to DCA (results not shown) showed that while all the other variables had a positive correlation with the DCA, distance from gate had a negative correlation.

Species composition and vegetation indices All the vegetation-indices explained well the DCA variation. TC-wetness and TC-greenness showed the best relationship with DCA scores with r2 of 0.73 and 0.70, respectively. TC-brightness had the lowest value (r2 = 0.46). NDVI had an r2 of 0.64.

Species distribution in discrete vegetation cover classes The classes derived from the analyses of the satellite image diﬀered considerably in their DCA scores (Figure 4a and b). Plots of the ‘No-ﬁre’ class had consistently low DCA scores, whereas the plots from the class ‘Recent-ﬁre’ have high DCA scores. Plots from the class ‘Old-ﬁre’ were intermediate. The Fire classes also diﬀered considerably in their TC-greenness values. Consequently a combination of DCA scores and TC-greenness value segregated the ﬁre classes well. A similar result was found for the cover classes. These classes are segregated both by their DCA scores and TC-greenness values (Figure 4b). [417]

1478

Figure 4. DCA axis 1-Tasseled Cap relationship as subdivided by (a) ﬁre regimes and (b) vegetation cover classes.

Plots of diﬀerent ﬁre classes also diﬀered signiﬁcantly in their species composition (MRPP, A = 0.061, p > 0.0001). Uvariopsis congensis, Celtis wightii, Diospyros abyssinica, Phyllanthus discoideus, Celtis zenkeri, Alstonia boonei, Cynometra alexandri and Trichilia prieuriana, all exclusively occur in the No-ﬁre class i.e. relative abundance (RA) equals 100% for each of the species. The indicator species analysis also identiﬁed the above named species as indicators for the No-ﬁre class i.e. signiﬁcant p values (Appendix 1). Although no species had 100% relative frequency in any class, Terminalia velutina and Grewia mollis had very high relative frequency, 90 and 87%, in Old-ﬁre and Recent-ﬁre classes, respectively. For the Old-ﬁre class, species that had signiﬁcant species indicator values include Terminalia velutina, Stereospermum kunthianum and Piliostigma thoningii. And for the Recent-ﬁre, species that had signiﬁcant species indicator values include Grewia mollis, Annona senegalensis, Combretum molle, Loncocarpus laxiﬂorus and Grewia bicolor. Plots of diﬀerent cover classes also diﬀered signiﬁcantly in their species composition (MRPP, A = 0.148, p > 0.0001). Of the species exclusively found in the no ﬁre area, Uvariopsis congensis, Celtis wightii, Celtis zenkeri, Cynometra alexandri and Trichilia prieuriana were also exclusively found in the [418]

1479 forest area. In addition, Pterygota mildbreadii was also exclusively found in the forest (Appendix 2). Funtumia elastica, Uvariopsis congensis and Celtis wightii had the highest relative frequency in the forest class; 55, 54 and 50%, respectively. Species with the highest relative frequency in the closed woodland are Terminalia velutina and Grewia mollis with 97 and 70%, respectively. In the open woodland plots, Terminalia velutina and Grewia mollis still had the highest relative frequency of 85 and 88%, respectively. In the very open woodland, Grewia mollis occurred in 99% of the plots while in the wooded grassland, Stereospermum kunthianum had the highest relative frequency of 67%. Overall, Grewia mollis in the very open woodland had the highest relative frequency i.e. it occurred in 99% of the closed woodland plots. Whereas in the forest some of the species that had the highest relative frequency are part of those that had the highest relative abundance, it is diﬀerent for the other cover classes. In the closed woodland, the species with the highest relative abundance were Bridelia michrantha (70%), Albizia grandibracteata (55%) and Maesopsis eminii (55%). In the open woodland there were no species with relative abundance above 50%. The highest was Ficus exasperata with 48%. In the very open woodland, Combretum molle, Securinega virosa and Dombeya rotundifolia had the highest relative abundance with 74, 71 and 75%, respectively. Combretum guenzi exclusively occurred in the wooded grassland. Other species with high relative abundance in the wooded grassland were Combretum binderanun, Grewia bicolor, Lonchocarpus laxiﬂorus and Hymenocardia acida with 78, 66, 58 and 50%, respectively. Most of the species identiﬁed as belonging to groups A and B e.g. Cynometra alexandri, Khaya anthotheca, Diospyros abyssinica, Uvariopsis congensis and Holoptelea grandis (Figure 3b) were also identiﬁed through indicator species analysis as good indicators for the No-ﬁre class. Of these, Diospyros abyssinica, Uvariopsis congensis, Holoptelea grandis and all Celtis species were also good indicators of the forest class (Appendix 2). The species in group C belonged both to Old-ﬁre and Recent-ﬁre classes. Considering the cover classes, Terminalia velutina and Albizia grandbracteata were good indicators for closed woodland, Grewia mollis and Combretum mole for very open woodland and Lonchocarpus laxiﬂorus, Grewia bicolor and Combretum guenzi were good indicators for the wooded grassland class. Several of these species e.g. Uvariopsis congensis, Terminalia velutina and Grewia mollis have distinctively high abundance in speciﬁc areas along the gradient (Figure 5). Although the closed woodland had the largest area sampled followed by the open woodland, the forest had the highest number of species and genera identiﬁed (Appendix 3). The lowest number of species and genera was found in the wooded grassland. The highest ratio of species to genera was in very open woodland (1.4) and the lowest in wooded grassland (1.2). Eleven species occur in all classes and most species occur in more than one cover class but their abundance varies greatly between classes. Forest and closed woodland classes had an equal number of families and wooded grassland class had the lowest number of families. [419]

1480

Figure 5. Relationship between DCA axis 1 and some of the most abundant species whose maximum abundance occur in diﬀerent areas along the gradient. The selected species also display a variation in their distribution range.

The Simpson index of all vegetation classes diﬀered only slightly except that of wooded grassland (Figure 6a). The wooded grassland had the highest value and the highest standard error. The forest class had the highest mean Fisher’s a (Figure 6b) followed by the closed woodland class. These two classes were signiﬁcantly diﬀerent from all other classes but not from each other. The open woodland was also signiﬁcantly diﬀerent from the wooded grassland. The wooded grassland had the lowest Fisher’s a. The basal area (Figure 6c) decreased from the forest, which had the highest value, to the wooded grassland, which had the lowest. The forest also showed the highest variation. All cover types were signiﬁcantly diﬀerent from each other. The mean stem density values for the forest, closed woodland and open woodland were very close (Figure 6d) and there was no signiﬁcant diﬀerence between them. The very open woodland also had a high mean value although slightly lower than the other 3. The wooded grassland is much lower than all others. The very open woodland and the wooded grassland are each signiﬁcantly diﬀerent from all others. So while many individual trees may be found in each cover type, they vary in size with the forest having larger trees than any of the other cover types. Details of the species occurring in each cover type and their abundance are indicated in Appendix 3.

Discussion Variation in species composition along the gradient The species composition along the gradient gradually changes from species that attain maximum abundance in areas of minimum disturbance e.g. [420]

1481

Figure 6. comparison of cover class mean and standard deviation for (a) Simpson index, (b) Fisher’s a, (c) basal area and (d) stem density. The class numbers consistently represent 1, forest; 2, closed woodland; 3, open woodland; 4, very open woodland; and 5, wooded grassland. The letters beside each bar indicate signiﬁcance diﬀerences. Bars, for a speciﬁc variable, which have the same letter mean that they are not signiﬁcantly diﬀerent (ANOVA: p = 0.05).

Cynometra alexandri and Uvariopsis congensis to species that attain maximum abundance in areas with frequent disturbance e.g. Grewia mollis. On the other hand, species like Terminalia velutina attain maximum abundance in the moderately disturbed areas (Smart et al. 1985). Many species, as evidenced by the species abundance plot (Figure 5), are wide ranging although they have a clear optimum, which occurs at species speciﬁc locations along the gradient. Identiﬁcation of a vegetation type should, therefore, be based on species abundance proportions rather than species incidence alone. This variation in species tolerance range has also been observed in a Mexican dry forest (Balvanera et al. 2002). In another study (Nangendo et al., submitted), it was observed that the wide-ranging species often have their diﬀerent development sizes (seedlings, saplings and trees) in species speciﬁc locations along the gradient.

[421]

1482 Relationship between site variables and the observed gradient Of the environmental variables recorded, ﬁre best explained the gradient. This is evidenced by the high correlation between DCA and ﬁre (Table 1) and the fact that the compositional gradient could be divided using the ﬁre regime (Figure 4a). Areas that had recent ﬁres, and are probably most frequently burnt, had species that characteristically display ﬁre resistant traits e.g. a thick bark, pealing oﬀ of the old bark and good sprouting ability after a ﬁre (Gashaw et al. 2002; Saha and Howe 2003; Vesk and Westoby 2004). The occurrence of some species is thus inﬂuenced by their ﬁre-tolerance level (Cauldwell and Zieger 2000) with increasingly more of the less ﬁre resistant species in the Old-ﬁre class. Here, seed dispersal (a factor not explored in this study) may have an important role. A number of the species that occurred in the Old-ﬁre class were most abundant in the No-ﬁre class. Their seeds were probably dispersed into the Old-ﬁre class areas e.g. by wind and, when conditions became favorable, they got established. Hence we suggest that the existent ﬁre regime inﬂuences their low occurrence (Huston 1994). Although water is often a limiting factor for plant survival, in humid FWS mosaics, water distribution is not a critical controlling factor (Favier et al. 2004). Despite the variation in rainfall over Budongo Forest Reserve, with the northern part receiving less rain than the south (Plumptre 1996), the north still receives over 1200 mm a year (Forest Department Uganda 1997) which is suﬃcient for forest maintenance. Also elephants that previously restricted forest expansion (Laws et al. 1975) are no longer present. The species turnover could possibly be explained by an additive eﬀect of the environmental variables considered in this study, the historical impact by elephants and probably other factors that were not considered in this study e.g. seed dispersal mechanisms, which have been shown to favor establishment of species with higher dispersal ability in the post disturbance period (Hovestadt et al. 1999; Ohsawa et al. 2002). However, just like in other studies where FWS occur (Elliott et al. 1999; Hovestadt et al. 1999), ﬁre plays a major role in controlling species distribution pattern but it does not explain all the variation (Weiher 2003). Accessibility to the protected areas, where local people mainly utilize areas closest to them (Acharya 1999; Obiri et al. 2002), also showed a signiﬁcant relationship with the species composition gradient.

Vegetation variation and composition as mapped using satellite image classiﬁcation The image classiﬁcation provided a good representation of the vegetation types. Each cover class had signiﬁcant indicator species and diﬀerences in structural and species diversity existed among the cover classes (Figure 6). Although the best diﬀerentiating factor was basal area, where each cover class was signiﬁcantly diﬀerent from the others, indicator species have also been [422]

1483 shown (Cousins and Lindborg 2004) to correspond well with the succession gradient. Classiﬁcation of mosaic areas using remotely sensed data could therefore be a good start for identiﬁcation of the vegetation types that exist within them. This would require less time (Schmidt et al. 2004) as compared to when only ﬁeld surveys would have been used. Our study has shown that although the forest signiﬁcantly diﬀered in species diversity and vegetation structure, especially basal area, there was a systematic decrease in variation from forest to wooded grassland (Figure 5). A major gradient stretching from the forest to the wooded grassland is evident (Dezzeo et al. 2004) and species composition and forest structure vary along this gradient. Most of the areas sampled by Eggeling (1947) and followed up in Sheil et al. (2000) had not had disturbance for a long time. Areas sampled in this study, however, cover both areas with ranging times since last disturbance and areas that are still experiencing frequent disturbance. Thus, in this study we observe a wider range of vegetation variation. Although subtle variations in vegetation structure may be evident in some landscapes, the species composition variation is often more complex (Muhlenberg et al. 1990). In our study, the observed gradual change in species composition along the gradient and the compositional interrelationship between the vegetation cover classes indicate that the FWS mosaic is a single, interacting, integrated unit.

The eﬀect of continuing reforestation on the biodiversity of Budongo Eggeling (1947), also followed up in Sheil (1999), identiﬁed successional stages within the forest, with ironwood (Cynometra alexandri) at the climax end of the spectrum and the colonizing (woodland) forest as the starting point. In their study, the lowest woody plant diversity occurred in the ironwood forest. In our study, although diversity is low at the ironwood end of the gradient, it is even lower on the wooded grassland side of the gradient (plot results not shown) indicating a drop on either end of the gradient. The highest diversity is within the forest area and it gradually reduces until the lowest level, which occurs in the wooded grassland. The colonizing forest, identiﬁed by Eggeling (1947) as the starting point of the succession, occurs somewhere towards the middle of the current gradient. The current study has, therefore, extended the succession gradient to further into the wooded grassland and yet still conforms with the Intermediate Disturbance Hypothesis (IDH) (Connell 1978). Another DCA run, after combining a resampled set of Eggeling’s data with data used in this study, revealed more of the similarities between the two gradients. It, additionally, emphasized the existence of more than one succession path in the forest (Eggeling 1947; Sheil et al. 2000) and the variation within the forest (Plumptre 1996). To incorporate Eggeling’s data, resampling from the original data set was carried out. Having known the plot size and the number of individuals collected from each of his plots, the number of [423]

1484 individuals expected to occur in a 500 m2 plot was calculated. The calculated number of individuals was then randomly sampled from the original individuals of the respective plot. The abundance of each species in each plot was then raised to that which would occur in an 1000 m2 plot. After crosschecking the species names for possible changes in naming, the data were combined with the rest of the tree data used in this study and a DCA was carried out. All Eggeling’s plots, considering the ﬁrst axis, occurred at one end of the gradient but in line with the rest of the plots (Figure 7). Eggeling’s observation of compositional convergence (Eggeling 1947) is still evident in his plots (see dotted lines in Figure 7). Plumptre (1996) identiﬁed a north–south compositional gradient. In our study, the variation along the second axis of Figure 7 is an indicator of this gradient. Eggelling’s plots collected from the southern part of the forest occur separate from most of our plots, which were collected from the northern part of the forest. Succession always starts with very few species, then progresses awhile along one line with more species coming in as conditions become more favorable (Huston 1994). In our study, few species were observed in the wooded grassland end of the gradient and species numbers increased as one moved towards the forest (Figure 3b). Although the forest side of the gradient had more species, other species occur away from the forest environment. The diversity of an area is inﬂuenced by the type, frequency and intensity of the disturbance (Trapnell 1959; Petraitis et al. 1989). Hence, if the whole succession gradient occurs in an area, there would be more species (Connell 1978; Huston 1994) than if one or a few stages of the succession gradient were conserved. So while the areas that have high species numbers e.g. forest

Figure 7. DCA graph obtained after combining a resampled set of Eggeling’s data to the data used in this paper. Axis 1 had an eigenvalue of 0.38 and explained 9.8% of the variation. The second axis had an eigenvalue of 0.19 and explained 4.9%. [424]

1485 ought to be preserved (Sheil and Burslem 2003), the woodland areas should not all be allowed to become forest since that would mean loosing the woodland dependant species. And the highest number of species can only be conserved when complementary areas are included in the conservation plan (Howard et al. 1998). The maintenance of the high diversity of Budongo, being an isolated forest with no immediate source of additional forest species, may be more attributed to the existence of all stages of the succession gradient (Richardson-Kageler 2004; Shea et al. 2004) than acquisition of more forest species from elsewhere, which, additionally, often takes a long time (Chapman et al. 1997). Hence, if reforestation of Budongo Forest Reserve would continue to the extent that the woodland areas would be lost, the biodiversity of the reserve would probably decrease. For purposes of conserving woody plants in a dynamic landscape, it is thus important that each vegetation type represented is included and maintained within the conservation area (Bengtsson et al. 2003). In the area under study, ﬁre disturbance is a requirement for species coexistence (Shea et al. 2004). In areas where ﬁre may be applied, the vegetation type and its development stage may aﬀect the potential for ignition and spread of the ﬁre (Everett et al. 2000). Although no evidence exists of ﬁres having destroyed tropical rain forests in Uganda, it has been observed elsewhere that tropical forests can burn (Cochrane and Schuize 1999; Cochrane and Laurance 2002; Laurence 2003). This, however, mainly occurs in the presence of very dry conditions, in fragmented forest landscapes and when ﬁre is carelessly applied in or adjacent to logged over areas. Fire also remains a highly debated conservation management tool (Mentis and Bailey 1990; Trollope et al. 1995; van Wilgen et al. 1998). It is therefore important that ﬁre be used cautiously and, probably learning and using burning methods that have been used in the past (Goma et al. 2001) will be a prerequisite. In this respect, conservationists need to focus more attention on the current vegetation management practices of local people surrounding conservation areas (Leone and Lovreglio 2004) since they have been noted to use ﬁre destructively (Condit et al. 1998; Wheater 1971). In Africa FWS mosaics are prevalent in areas surrounding the Congo basin forests, including Uganda. These areas have been deﬁned as transitional zones between the moist tropical forest and the drier savanna landscape typical of much of Africa. On the northern side, the transition occurs at about 8 N with the exception of Togo and Benin and part of Ivory Coast (Gautier and Spichiger 2004). Many FWS mosaics occur in Uganda because of its location in a zone of overlap between the ecological communities characteristic of the dry East African savannas and the West African rainforests (Howard 1991). The observations made in this study and their management implications are, therefore, relevant to many areas in Africa and in much of the tropical world where such landscapes occur.

[425]

1486 Conclusions and recommendations • Species composition in the area gradually changes from the forest to savannah. • Although many of the species occurred in more than one vegetation cover class, each class had species that can be used to identify it. These are the classes where such species had a signiﬁcantly higher relative abundance as compared to other classes. • The gradient could be divided into sections using vegetation cover classes and the ﬁre indicator. These cover classes were compositionally separable and vegetation structure signiﬁcantly diﬀered between the classes. • Among the environmental variables, ﬁre best explained the compositional variation along the gradient. Areas with such a dynamic FWS mosaic need a purposeful management that takes into account the relationship between the observed vegetation pattern and how this has been generated over time (Alados et al. 2004). Since each vegetation cover class was compositionally separable from the others, a portion of each of these classes needs to be conserved. An area where all cover classes occur would be preferable since many species tend to occur in more than one cover class and another study (Nangendo 2005) showed that the juveniles and adults of some species do not occur in the same vegetation patches. A well balanced management, including a controlled ﬁre management system that will prevent forest from colonizing the whole area yet allowing the existence of varying disturbance regimes is a prerequisite for maintaining species diversity (Crow and Perera 2004).

Acknowledgements We thank Mr Hezekias Ddumba for being there for us to sort out our species identiﬁcation problems and for all the logistical support he provided while we stayed at Kaniyo-Pabidi ecotourism camp. We express our gratitude to Mr Oliver van Straaten who contributed part of the data used in this study. We also express our gratitude to Professor Dr Alfred De Gier for his continued support and for his valuable comments during the preparation of this manuscript.

Appendix 1. The Indicator Species Analysis output based on ﬁre indicator classes. Species names

RA-0

RF-0

RA-1

RF-1

RA-2

RF-2

IV

p

Fire class

Terminalia velutina Grewia mollis Combretum collinum Uvariopsis congensis Annona senegalensis

39 14 23 100 18

66 47 37 26 33

52 37 39 0 35

90 80 56 1 59

9 49 38 0 47

47 87 49 0 55

46.7 42.4 21.7 25.7 25.7

0.001 0.001 0.046 0.001 0.005

1 2

[426]

0 2

1487 Appendix 1. Continued. Species names

RA-0 RF-0 RA-1 RF-1 RA-2 RF-2 IV

p

Fire class

Albizia grandibracteata Stereospermum kunthianum Combretum molle Lonchocarpus laxiﬂorus Vitex doniana Funtumia elastica Lanea barteri Celtis wightii Acacia hockii Piliostgma thonningii Caloncoba schweinfurthii Holoptelea grandis Maesopsis eminii Diospyros abyssinica Ficus sur Grewia bicolor Khaya anthotheca Dombeya mukole Bridelia micrantha Celtis durandii Combretum binderanum Margaritaria discoidea Phyllanthus discoideus Albizia zygia Celtis zenkeri Pterygota mildbreadii Hymenocardia acida Olea welwitschii Oncoba spinosa Tapura ﬁsheri Securinega virosa Dichrostachys cinerea Alstonia boonei Cynometra alexandri Ficus exasperata Combretum gueinzii Sapium ellipticum Carpololobia alba Dombeya rotundifolia Trichilia prieuriana

64 22 1 10 38 94 27 100 22 25 86 99 62 100 43 8 86 79 87 86 2 71 100 56 100 70 11 95 37 80 0 73 100 100 37 0 81 0 8 100

0.001 0.003 0.001 0.001 0.585 0.001 0.174 0.001 0.033 0.004 0.001 0.001 0.003 0.001 0.245 0.001 0.001 0.013 0.001 0.003 0.012 0.004 0.001 0.829 0.001 0.059 0.008 0.001 0.326 0.009 0.004 0.064 0.001 0.007 0.272 0.749 0.403 0.006 0.012 0.007

0 1 2 2

41 28 5 12 33 31 25 24 19 18 23 22 21 10 15 5 15 8 12 12 0 11 10 2 10 5 3 9 5 9 0 5 9 5 3 0 2 0 2 5

31 44 31 19 36 6 41 0 46 53 14 1 38 0 48 23 14 17 9 14 37 29 0 20 0 30 27 5 14 20 38 27 0 0 63 73 19 21 25 0

22 50 24 22 36 3 32 0 29 31 6 1 12 0 15 9 2 3 1 2 6 2 0 2 0 1 5 1 1 2 5 1 0 0 3 1 1 3 5 0

5 34 68 71 26 0 32 0 32 23 0 0 0 0 9 69 0 5 4 0 61 0 0 24 0 0 62 0 49 0 62 0 0 0 0 27 0 79 67 0

6 47 49 45 25 0 29 0 23 15 0 0 0 0 3 18 0 1 1 0 9 0 0 3 0 0 9 0 6 0 10 0 0 0 0 1 0 6 8 0

26.2 21.9 33.7 31.7 12.8 28.9 13.1 24.2 13.4 16.2 20.2 21.6 12.8 9.6 7.1 12.8 12.6 6.4 10.7 9.9 5.6 7.6 9.6 1.3 10.4 3.8 5.7 8.8 2.8 7.1 6.4 3.9 8.8 5 2.2 0.5 1.2 4.5 5.4 5.4

0 0 1 0 0 0 0 2 0 0 0 0 2 0 0 0 2 0 0 2 0 0

2 2 0

It indicates the concentration of each species in each class (Relative abundance, RA), the faithfulness of occurrence of the species in that class (Relative frequency, RF), the highest species indicator value across the classes (IV) the statistical signiﬁcance of the indicator value (p) and the class in which a particular species had the highest indicator value (Fire class). For species that were not signiﬁcant indicators for any class, ﬁre class was left blank. RA is expressed as a proportion of a particular species in a particular class relative to its abundance in other classes. RF is expressed as the percentage of sample units in a class that contain that species. p is signiﬁcant at 0.01. 0, No ﬁre; 1, old ﬁre; and 2, recent ﬁre.

[427]

1488 Appendix 2. The Indicator Species Analysis output based on vegetation cover classes. Species

Terminalia velutina Grewia mollis Combretum collinum Uvariopsis congensis Annona senegalensis Albizia grandibracteata Stereospermum kunthianum Combretum molle Lonchocarpus laxiﬂorus Vitex doniana Funtumia elastica Lanea barteri Celtis wightii Acacia hockii Piliostgma thonningii Caloncoba schweinfurthii Holoptelea grandis Maesopsis eminii Diospyros abyssinica Ficus sur Grewia bicolor Khaya anthotheca Dombeya mukole Bridelia micrantha Celtis durandii Combretum binderanum Margaritaria discoidea Phyllanthus discoideus Albizia zygia

RA-1 RF-1 RA-2 RF-2 RA-3 RF-3 RA-4 RF-4 RA-5 RF-5 IV

P

Cover cord

12

30

44

97

31

85

8

57

5

44

42.8 0.001 2

2 11

16 18

16 20

70 52

32 38

88 64

48 22

99 43

1 10

11 22

47 0.001 4 24.3 0.042

100

54

0

0

0

0

0

0

0

0

54.4 0.001 1

6

14

23

52

30

58

42

64

0

0

26.9 0.02

28

26

55

60

14

15

3

3

0

0

32.9 0.002 2

7

11

26

51

22

45

17

39

29

67

19.2 0.063

0

2

2

6

15

23

74

66

8

22

48.4 0.001 4

0

0

2

10

14

36

26

47

58

56

32

5 89

11 55

33 11

51 11

23 0

36 0

16 0

24 0

23 0

22 0

16.8 0.095 49.4 0.001 1

2 100 7 5

3 50 10 8

23 0 16 18

30 1 22 24

35 0 31 22

40 0 37 31

34 0 17 10

43 0 21 16

6 0 29 45

11 0 11 44

14.7 49.4 11.6 19.8

74

38

24

13

2

2

0

0

0

0

27.9 0.005 1

94

42

6

3

0

0

0

0

0

0

39.8 0.001 1

45

23

55

28

0

0

0

0

0

0

15.7 0.033

96

18

3

1

1

1

0

0

0

0

17.7 0.005 1

18 0 71

10 0 20

43 3 23

20 3 10

31 11 6

14 13 1

8 20 0

4 20 0

0 66 0

0 56 0

8.8 0.133 36.9 0.001 5 14.2 0.03

82

14

5

2

11

4

3

1

0

0

11.1 0.04

26

7

70

16

2

1

3

1

0

0

11.3 0.046

93 0

23 0

7 1

3 1

0 9

0 5

0 11

0 10

0 78

0 22

61

14

39

9

0

0

0

0

0

0

97

18

3

1

0

0

0

0

0

0

67

3

12

2

7

1

15

4

0

0

[428]

0.001 5

0.095 0.001 1 0.15 0.024

21.5 0.005 1 17.4 0.005 5 8.3 0.078 17.8 0.011 1 2.1 0.469

1489 Appendix 2. Continued. Species

RA-1 RF-1 RA-2 RF-2 RA-3 RF-3 RA-4 RF-4 RA-5 RF-5 IV

P

Celtis zenkeri Pterygota mildbreadii Hymenocardia acida Olea welwitschii Oncoba spinosa Tapura ﬁsheri Securinega virosa Dichrostachys cinerea Alstonia boonei Cynometra alexandri Ficus exasperata Combretum gueinzii Sapium ellipticum Carpololobia alba Dombeya rotundifolia Trichilia prieuriana

100 100

22 13

0 0

0 0

0 0

0 0

0 0

0 0

0 0

0 0

0

0

3

2

20

9

27

7

50

22

11.2 0.045

92

17

8

3

0

0

0

0

0

0

15.4 0.016

48

9

6

1

12

3

33

6

0

0

4.2 0.166

90 0

18 0

10 8

2 1

0 21

0 3

0 71

0 14

0 0

0 0

63

6

18

4

12

1

8

1

0

0

86

14

14

3

0

0

0

0

0

0

12.4 0.033

100

10

0

0

0

0

0

0

0

0

10.4 0.022

6

1

46

5

48

4

0

0

0

0

2.2 0.454

0

0

0

0

0

0

0

0

100

22

82

2

18

1

0

0

0

0

0

0

2

0

0

32

1

38

4

30

4

0

0

1.4 0.607

0

0

8

2

17

4

75

13

0

0

9.7 0.04

100

11

0

0

0

0

0

0

0

0

11.2 0.03

Cover cord

21.6 0.006 1 12.8 0.025

16.6 0.014 1 10.1 0.03 4

0.138

22.2 0.001 5 0.174

It indicates the concentration of each species in each class (Relative abundance, RA), the faithfulness of occurrence of the species in that class (Relative frequency, RF), the highest species indicator value across the classes (IV) the statistical signiﬁcance of the indicator value (p) and the class in which a particular species had the highest indicator value (Cover cord). For species that were not signiﬁcant indicators for any class, cover cord was left blank. RA is expressed as a proportion of a particular species in a particular class relative to its abundance in other classes. RF is expressed as the percentage of sample units in a class that contain that species. p is signiﬁcant at 0.01. 1, Forest; 2, closed woodland; 3, open woodland; 4, very open woodland; and 5, wooded grassland.

Appendix 3. The 121woody species identiﬁed in the ﬁeld, their abundance per class. Number of individuals Family Mimosaceae Mimosaceae

Species Acacia hockii De Wild. Acacia seyal Delile

Fo 20 .

[429]

cw 55 .

Ow 97 .

Vow 25 1

Wg 7 .

1490 Appendix 3. Continued. Number of individuals Mimosaceae

Mimosaceae Euphorbiaceae Mimosaceae Mimosaceae Mimosaceae Mimosaceae Apocynaceae Sapotaceae Annonaceae Rubiaceae Sapindaceae Euphorbiaceae Euphorbiaceae Elacourtiacea Polygalaceae Caesalpinioideae Caesalpinioideae Ulmaceae Ulmaceae Ulmaceae Ulmaceae Moraceae Sapotaceae Rutaceae Annonaceae Rubiaceae Rubiaceae Sterculiaceae Combretaceae Combretaceae Combretaceae Combretaceae Boraginaceae Aralliaceae Caesalpiniaceae Mimosaceae Ebenaceae Sterculiaceae Sterculiaceae Mimosaceae Meliaceae

Acacia sieberiana Dc. Var. woodii (Burtt Davy) Keay & Brenan Acacia spp. Acalypha neptunica Mu¨ll. Arg. Var. Albizia coriaria Oliver Albizia grandibracteata Taub. Albizia spp. Albizia zygia (DC.) Macbr. Alstonia boonei de Wild Aningeria altissima (A. Chev.) Aubr. & Pellegr. Annona senegalensis Pers. Balemetea gramofolia Belonophora glomerata Blighia unijugata Baker Bridelia micrantha (Hochst.) Baill. Bridelia scleroneuroides Pax. Caloncoba schweinfurthii Glig. Carpololobia alba G. Don Cassia siamea Lam. Cassia spp. Celtis durandii Engl. Celtis mildbraedii Engl. Celtis wightii Planch. Celtis zenkeri Engl. Chlorophora excelsa (Welw.) Benth Chrysophyllum albidum G. Don Citropsis articulata (Wild. Ex Spreng) Swingle & M. Kellerm Cleistopholis patens (Beth.) Engl. & Diels Closophila magida Coﬀea canephora Pierre ex Froechner. Coﬀea euginiodes Cola gigantea A. Chev. Combretum binderanum Kotschy Combretum collinum Fresen. Combretum gueinzii Sond. Combretum molle R. Br. Ex G. Don Cordia millenii Baker Cussonia arborea Hochst. Ex A. Rich. Cynometra alexandri CH Wright Dichrostachys cinerea (L.) Wright & Arn Diospyros abyssinica (Hiern) F. White Dombeya mukole Sprague Dombeya rotundifolia (Hochst.) Planch. Entada abyssinica Steud. Ex A. Rich Entandrophragma angolense (Welw.) C. DC.

[430]

1

6

.

3

.

2 9

. .

. .

. .

. .

9 120 . 33 24 15

8 257 . 5 5 2

2 57 1 3 . 1

. 7 . 3 . 2

. . . . . .

35 1 2 2 15 . 107 . 2 . 59 7 204 43 . 6 1

157 . 1 6 49 2 42 9 13 1 6 . 1 . 3 . .

194 . . . 1 5 3 12 . . . . . . . . .

129 . . . 1 2 . 4 . . . . . . . . .

1 . . . . . . . . . . . . . . . .

1 1 5 5 13 . 107 . 4 7 . 29 19 90 56 2 . 3

. . . . . 3 240 . 18 7 1 . 8 3 3 3 . .

. . . . . 16 431 2 92 . 4 . 3 1 6 6 1 .

. . . . . 14 137 . 243 . 12 . 1 . 1 12 . .

. . . . . 17 12 21 6 . . . . . . . . .

1491 Appendix 3. Continued. Number of individuals Meliaceae Papilionaceae Leguminosae Rutaceae Moraceae Moraceae Moraceae Moraceae Moraceae Moraceae Moraceae Moraceae Moraceae Apocynaceae Rubiaceae Tiliaceae Tiliaceae Simaroubaceae Ulmaceae Euphorbiaceae Meliaceae Meliaceae Bignoniaceae Anacardiaceae Anacardiaceae Rhamnaceae Sapindaceae Papilionaceae Capparidaceae Rhamnaceae Meliaceae Euphorbiaceae Rignoniaceae Celastraceae Papilionaceae Moraceae Rubiaceae Moraceae Moraceae Oleaceae Flacourtiaceae Palmae Euphorbiaceae Caesalpiniaceae Verbenaceae Proteaceae Anacardiaceae

Entandrophragma cylindricum (Sprague) Sprague Erythrina abyssinica Lam. Ex DC Erythrophleum suaveolens (Guill. & Perr.)Brenan Fagaropsis angolensis (Engl.) HM. Gardner Ficus capensis Thunb Ficus casuarina Ficus exasperata Vahl Ficus mucuso Welw ex Ficalho Ficus polita Vahl Ficus saussureana DC. Ficus spp. Ficus sansibarica Warb. Ficus sur Forssk Funtumia elastica (Preuss) Stapf Gardenia Jovis-tonantis (Welw.) Hiern. Grewia bicolor Juss. Grewia mollis Juss. Harrisonia abyssinica Oliv. Holoptelea grandis (Hutch.) Mildbr. Hymenocardia acida Tul. Khaya anthotheca (Welw.) C. DC. Khaya grandifolia C. DC. Kigeria africana (Lam.) Benth Lanea barteri (Oliv.) Engl. Lannea welwitschii (Hiern.) Engl. Lasiodiscus mildbraedii Engl. Lepisanthes senegalensis (Juss. Ex Poir.) Lonchocarpus laxiﬂorus Guill. & Perr. Maerua duchensii Maesopsis eminii Engl. Mahogany spp. Margaritaria discoidea (Baill.) Webster Markhamia platycalyx (Baker) Sprague Maytenus undata (Thunb.) Blakelock Mildbraediodendron excelsum (Harms) Milicia excelsa (Welw.) CC Berg Mitragyna stipulosa (DC.) O. Ktze Morus lactea (Sim) Mildbr. Myrianthus holstii Engl. Olea welwitschii (Knobl.) Gilg & Schellenb. Oncoba spinosa Forsk. Phoenix reclinata Jacq. Phyllanthus discoideus Muell. Piliostgma thonningii (Schum.) Premna angolensis Guerke Protea madiensis Oliv. Pseudospondias microcarpa (A. Rich.) Engl.

[431]

1

.

.

.

.

1 8

4 .

1 .

3 .

. .

5

1

.

.

.

1 . 1 1 9 . 1 1 17 227 . . 58 . 99 3 50 1 . 5 . 1 6 . 12 47 8 29 2 . 3 2 1 . 4 36 24 12 46 21 18 . 4

1 1 10 5 5 1 . . 41 32 1 10 424 1 10 3 16 . . 78 3 . 5 20 . 61 . 21 1 1 . 2 . 1 . 4 3 . 2 66 2 . 2

. . 8 1 1 . . . 26 . 1 27 761 . . 22 4 . 5 107 . . . 116 . . . . . 4 . . . . . . 5 . . 75 . . .

. . . . . . . . 3 . 1 26 531 . . 15 . . 1 48 1 . . 108 . . . . . 7 . . . . . . 8 . . 18 . 9 .

. . 5 . . . . . . . . 17 6 . . 3 . . . 2 . . . 34 . . . . . 4 . . . . . . . . . 12 . . .

1492 Appendix 3. Continued. Number of individuals Sterculiaceae Euphorbiaceae Violaceae Violaceae Capparidaceae Rubiaceae Celestraceae Euphorbiaceae Oleaceae Polygalaceae Euphorbiaceae Bignoniaceae Umbelliferae Bignoniaceae Apocynaceae Chailletiaceae Rutaceae Combretaceae Euphorbiaceae Ulmaceae Meliaceae Meliaceae Meliaceae Annonaceae Rubiaceae Compositae Verbenaceae Rhamnaceae Total Total Total Total Total

Pterygota mildbraedii Engl. Ricinodendron excelsum Rinorea dentata (P. Beauv.) Kuntze Rinorea ilicifolia (Welw. Ex Oliv.) Ritchiea albersii Gilg Rothmannia urcelliformis (Hiern) Bullock exRobyns Salacia elegans Welw. Ex Oliv. Sapium ellipticum Pax. Schrebera arborea A. Chev. Securidaca spp. Securinega virosa (Roxb. Ex Willd.) Baill Spathodea campanulata P. Beauv. Steganotaenia araliacea Hochst. Stereospermum kunthianum Cham. Tabernaemontana holstii K. Schum Tapura ﬁsheri Teclea nobilis Del. Terminalia velutina Rolfe Thecacoris lucida Trema orientalis (L.) Blume Trichilia prieuriana A. Juss Trichilia spp. Turrae ﬂoribunda Uvariopsis congensis Robyns & Ghesq. Vangueria apiculata K. Schum Vernonia amygdalina Delile Vitex doniana Sweet. Zizyphus abyssinica Hochst. Ex A. Rich

individuals species genera families area (sq. m)

40 8 1 13 1 .

2 2 . . . .

. . . . . 4

. . . . . 5

. . . . . 6

. 20 9 . 2 4 2 41 13 32 11 308 . 1 23 3 1 663 . 1 20 1

. 1 . 4 3 12 2 162 1 6 10 1288 . 2 . . . . 2 2 143 .

3 . . 10 5 . 2 126 . . 2 824 . . . . 1 . . . 92 1

2 . . 19 . . 9 55 . . . 103 4 . . . . . . . 29 .

5 . . . . . . 18 . . . 14 . . . . . . . . 6 .

3042 95 73 33 65300

3394 77 60 33 71000

3172 48 35 23 65500

1602 39 28 19 42100

196 18 15 13 16500

References Acharya B. 1999. Forest biodiversity assessment: a spatial analysis of tree species diversity in Nepal. Ph.D. Thesis, Leiden University, Enschede, 199 pp. Alados C.L. et al. 2004. Variations in landscape patterns and vegetation cover between 1957 and 1994 in a semiarid mediterranean ecosystem. Landscape Ecol. 19: 543–559. Balvanera P., Lott E., Segura G., Siebe C. and Islas A. 2002. Patterns of B-diversity in a Mexican tropical dry forest. J. Vege. Sci. 13(2): 145–158. Bengtsson J. et al. 2003. Reserves, resilience and dynamic landscapes. Ambio 32(6): 389–396. Buechner H.K. and Dawkins H.C. 1961. Vegetation change induced by elephants and ﬁre in the Murchison falls national park, Uganda. J. Ecol. 42(4): 752–766. [432]

1493 Cauldwell A.E. and Zieger U. 2000. A reassessment of the ﬁre-tolerance of some miombo woody species in the Central Province, Zambia. Afr. J. Ecol. 38: 138–146. Chapman C.A., Chapman L.J., Wrangham R., Isabirye-Basuta G. and Ben-David K. 1997. Spatial and temporal variability in the structure of a tropical forest. Afr. J. Ecol. 35: 287–302. Cochrane M.A. and Laurance W.F. 2002. Fire as a large-scale edge eﬀect in Amazonian forests. J. Trop. Ecol. 18: 311–325. Cochrane M.A. and Schuize M.D. 1999. Fire as a recurrent event in tropical forests of eastern Amszon: eﬀects on forest structure, biomass, and species composition. Biotropica 31: 2–16. Collins B.J. and Woodcock E.C. 1996. An assessment of several linear change detection techniques for mapping forest mortality using multitemporal Landsat TM data. Remote Sens. Environ. 56: 66–77. Condit R., Sukumar R., Hubbell S.P. and Foster R.B. 1998. Predicting population trends from size distributions: a direst test in a tropical tree community. Am. Natural. 152(4): 495–509. Connell J.H. 1978. Diversity in tropical rain forests and coral reefs. Science 199: 1302–1310. Cousins S.A.O. and Lindborg R. 2004. Assessing changes inplant distribution patterns-indicator species versus plant functional types. Ecol. Indicators 4: 17–27. Crist E.P. and Cicone R.C. 1984. Application of the Tasseled Cap concept to simulated Thematic Mapper data. Photogramm. Eng. Remote Sens. 50: 343–352. Crist E.P., Laurin R. and Cicone R.C. 1986. Vegetation and soils information contained in transformed Thematic Mapper data. Proceedings of the IGARSS ’86 Symposium, Zurich, Switzerland, ESA, Paris, pp. 1465–1470. Crow T.R. and Perera A.H. 2004. Emulating natural landscape disturbance in forest management – an introduction. Landscape Ecol. 19: 231–233. Dezzeo N., Chaco´n N., Sanoja E. and Pico´n G. 2004. Changes in soil properties and vegetation characteristics along a forest–savanna gradient in southern Venezuela. Forest Ecol. Manag. 200: 183–193. Dufreˆne M. and Legendre P. 1997. Species assemblages and indicator species: the need for a ﬂexible asymmetrical approach. Ecol. Monogr. 67(3): 345–366. Eggeling W.J. 1947. Observations on the ecology of the Budongo rain forest, Uganda. J. Ecol. 34(1): 20–87. Eggeling W.J. and Dale R.I. (eds) 1952. The Indigenous Trees of the Uganda Protectorate. Uganda Government printer, Entebbe. Eilu G., Hafashimana D.L.N. and Kasenene J.M. 2004. Tree species distribution in forests of the Albertine Rift, Western Uganda. Afr. J. Ecol. 42: 100–110. Elliott K.J., Hendrick R.L., Major A.E., Vose J.M. and Swank W.T. 1999. Vegetation dynamics after a prescribed ﬁre in the southern Appalachians. Forest Ecol. Manag. 114: 199–213. Everett R.L., Schellhaas R., Keenum D., Spurbeck D. and Ohlson P. 2000. Fire history in the ponderosa pine/Douglas-ﬁr forests on the east slope of the Washington Cascades. Forest Ecol. Manag. 2000: 207–225. Favier C., Chave J., AFabing A., Schwartz D. and Dubois M.A. 2004. Modelling forest–savanna mosaic dynamics in man-inﬂuenced environments: eﬀects of ﬁre, climate and soil heterogeneity. Ecol. Model. 171: 85–102. Fisher R.A., Corbet A.S. and Williams C.B. 1943. The relation between the number of species and the number of individuals in a random sample of an animal population. J. Anim. Ecol. 12: 42–58. Forest Department Uganda 1997. Forest management plan for Budongo Forest Reserve for 1997 to 2007. Forest Department, Kampala, 107 pp. Forest Department Uganda 1999. Forestry Nature Conservation Master Plan, Ministry of Water. Lands and Environment, Kampala. Gashaw M. et al. 2002. Post ﬁre regeneration strategies and tree bark resistance to heating in frequently burning tropical savanna woodlands in Ethiopia. Nord. J. Bot. 22(1): 19–33. Gautier L. and Spichiger R. 2004. The forest–savanna transition in West Africa. In: Poorter L., Bongers F., Kouame´ F.N. and Hawthorne W.D. (eds), Biodiversity of West African Forests: An Ecological Atlas of Woody Plant Species. CAB International, Wallingford, pp. 33–40.

[433]

1494 Goma H.C., Rahim K., Nangendo G., Riley J. and Stein A. 2001. Participatory studies for agroecosystem evaluation. Agric. Ecosyst. Environ. 87: 179–190. Hamilton A. 1991. A Field Guide to Ugandan Forest Trees. Makerere University, Kampala. Hovestadt T., Yao P. and Linsenmair E.K. 1999. Seed dispersal mechanisms and the vegetation of forest islands in a West African forest savanna mosaic (Comoe´ National Park, Ivory Coast). Plant Ecol. 144: 1–25. Howard P.C. 1991. Nature Conservation in Uganda Tropical Forest Reserves. IUCN, Gland. Howard P.C. et al. 1998. Complementarity and the use of indicator groups for reserve selection in Uganda. Nature 394: 472–475. Huston M.A. 1994. Biological Diversity. The Coexistence of Species on Changing Landscapes. Cambridge University Press, London. Laurence W.F. 2003. Slow burn: the insidious eﬀects of surface ﬁres on tropical forests. Trends Ecol. Evol. 18(5): 209–212. Laws R.M., Parker I.S.C. and Johnstone R.C.B. 1975. Elephants and Their Habitats. The Ecology of Elephants in North Bunyoro, Uganda. Oxford University Press, London. Leone V. and Lovreglio R. 2004. Conservation of Mediterranean pine woodlands: scenarios and legislative tools. Plant Ecol. 171: 221–235. Li J., Loneragan W.A., Duggin J.A. and Grant C.D. 2004. Issues aﬀecting the measurement of disturbance response patterns in herbaceous vegetation – a test of the intermediate disturbance hypothesis. Plant Ecol. 172: 11–26. Magurran A.E. 1988. Ecological Diversity and its Measurement. Princeton University Press, Princeton, New Jersey, 179 pp. McCune B., Grace J.B. and Urban D.L. 2002. Analysis of the Ecological Communities. MjM Software, Gleneden Beach, Oregon, US. McCune B. and Meﬀord M.J. 1999. Multivariate Analysis of Ecological Data. Version 4.25. MjM Software, Gleneden Beach, Oregon, US. Mentis M.T. and Bailey A.W. 1990. Changing perceptions of ﬁre management in savanna parks. J. Grassland Soc., Southern Africa 7: 81–85. Muhlenberg M., Galat-Luong A., Poilecot P., Steinhauer-Burkart B. and Kuhn I. 1990. The importance of forest islands within wet savannas for the conversation of rainforest animals in the Ivory Coast. Revue d’Ecologie (Terre et la Vie) 45(3): 197–214. Mwami P.M. and McNeilage A. 2003. Natural regeneration and ecological recovery in Bwindi Impenetrable National Park, Uganda. Afr. J. Ecol. 41: 93–98. Nangendo G. 2005. Changing forest–woodland–savanna mosaics in Uganda: with implications for conservation. Ph.D. Thesis, Wageningen University, Wageningen, 139 pp. Nangendo G., Skidmore A.K. and van Oosten H. submitted. Mapping East African tropical forests and woodlands: a comparison of classiﬁers. ISPRS J. Photogramm. Remote Sensing. Nangendo G., van Straaten O.ter Steege H., de Gier A. and Bongers F. submitted. Vegetation cover change and its relationship with species distribution dynamics. J. Biogeogr.. Obiri J., Lawes J. and Mukolwe M. 2002. The dynamics and sustainable use of high-value tree species of the coastal Pondoland forests of the Eastern Cape Province, South Africa. Forest Ecol. Manag. 166: 131–148. Ohsawa K., Kawasaki K., Takasu F. and Shigesada N. 2002. Recurrent habitat distribution and species diversity in a multiple-competitive species system. J. Theor. Biol. 216: 123–138. Paterson D.J. 1991. The ecology and history of Uganda’s Budongo forest. Forest Conserv. Hist. 35: 179–186. Petraitis P.S., Latham R.E. and Niesenbaum R.A. 1989. The maintenance of species diversity by disturbance. Quarter. Rev. Biol. 64: 393–418. Plumptre A.J. 1996. Changes following 60 years of selective timber harvesting in the Budongo Forest Reserve, Uganda. Forest Ecol. Manag. 89: 101–113. Richardson-Kageler S.J. 2004. Eﬀects of large herbivore browsing on the functional groups of woody plants in a southern African savanna. Biodivers. Conserv. 13: 2145–2163.

[434]

1495 Saha S. and Howe H.F. 2003. Species composition and ﬁre in a dry deciduous forest. Ecology 84(12): 3118–3123. Schmidt S.K. et al. 2004. Mapping costal vegetation using an Expert System and Hyperspectral imagery. Photogramm. Eng. Remote Sens. (in press). Schwartz M.W. and Caro T.M. 2003. Eﬀect of selective logging on tree and understory regeneration in Miombo woodland in western Tanzania. Afr. J. Ecol. 41: 75–82. Schwilk D.W., Keeley J.E. and Bond W.J. 1997. The intermediate disturbance hypothesis does not explain ﬁre and diversity pattern in fynbos. Plant Ecol. 132: 77–84. Shea K., Roxburgh S.H. and Rauschert E.S.J. 2004. Moving form pattern to process: coexistence mechanisms under intermediate disturbance regimes. Ecol. Lett. 7: 491–508. Sheil D. 1999. Developing tests of successional hypotheses with size-structured populations, and an assessment using long-term data from a Ugandan rain forest. Plant Ecol. 140: 117–127. Sheil D. and Burslem F.R.P.D. 2003. Disturbing hypothesis in tropical forests. Trends Ecol. Evol. 18(1): 18–26. Sheil D., Jennings S. and Savill P. 2000. Long-term permanent plot observations of vegetation dynamics in Budongo, a Ugandan rain forest. J. Trop. Ecol. 16: 765–800. Smart N.O.E., Hatton J.C. and Spence D.H.N. 1985. The eﬀect of long-term exclusion of large herbivores on vegetation in Murchison Falls National Park, Uganda. Biol. Conserv. 33: 229–245. Swaine M.D., Hawthorne W.D. and Orgle T.K. 1992. The eﬀects of ﬁre exclusion on savana vegetation at Kpong, Ghana. Biotropica 24: 166–172. Trapnell C.G. 1959. Ecological results of woodland burning experiments in Northern Rhodesia. J. Ecol. 47: 129–168. Trollope W.S.W., Biggs H.C., Potgieter A.L.F. and Zambatis N. 1995. A structured versus a wilderness approach to burning in the Kruger National Park in South Africa. In: West N.E. (ed.), Rangelands in a Sustainable Biosphere. Society for Rangeland Management, Denver. Tucker J.C. 1979. Red and Photographic Infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 8: 127–150. van Straaten H.P. 1976. Pra¨kambrium und junges Western Rift im Bunyoro District NW-Uganda. Unpublished Ph.D., Universita¨t Go¨ttingen, Hanover. van Straaten O. 2003. Changing woodland systems: post-disturbance woody species succession dynamics and spatial trends. M.Sc. Thesis, International Institute for Geoinformation Science and Earth Observation, Enschede, 70 pp. van Wilgen B.W., Biggs H.C. and Potgieter A.L.F. 1998. Fire management and research in the Kruger National Park, with suggestion on the detection of thresholds of potential concern. Koedoe 41: 69–87. Vesk P.A. and Westoby M. 2004. Sprouting ability across diverse disturbances and vegetation types worldwide. J. Ecol. 92(2): 310–320. Walter H. 1985. Vegetation of the Earth and Ecological Systems of the Geo-Biospere. SpringerVerlag, 318 pp. Weiher E. 2003. Species richness along multiple gradients: testing a general multivariate model in oak savanna. OIKOS 101: 311–316. Wheater R.J. 1971. Problems of controlling ﬁres in Uganda National parks, Annual Tall Timbers Fire Ecology Conference.

[435]

Biodiversity and Conservation (2006) 15:1497–1508 DOI 10.1007/s10531-005-2356-1

Springer 2006

Do Orthoptera need human land use in Central Europe? The role of habitat patch size and linear corridors in the Białowie_za Forest, Poland JO¨RN THEUERKAUF1,*, SOPHIE ROUYS2 1

Museum and Institute of Zoology, Polish Academy of Sciences, Wilcza 64, 00-679 Warsaw, Poland; Marine Laboratory for Environmental Resource Studies, University of New Caledonia, BP 4477, 98847 Noume´a Cedex, New Caledonia; *Author for correspondence: BP 2549, 98846 Noume´a Cedex, New Caledonia (e-mail: jtheuer@miiz. waw.pl; fax: +687-254473) 2

Received 13 January 2005; accepted in revised form 8 August 2005

Key words: Blattodea, Dermaptera, Habitat size, Road corridors, Herbivores, Marsh corridors, Orthoptera Abstract. We studied Orthoptera, Dermaptera, and Blattodea of the Białowie_za Forest (Poland) in order to assess (1) the minimum patch size of open habitat necessary for each species, (2) the role of linear corridors as habitat, and (3) the impact of herbivores on diversity by comparing the fauna at periods of diﬀerent ungulate densities. Many species occurred in the farthest clearings from the forest edge to arable land. Two third of species occurred in clearings smaller than 10,000 m2. Dry linear corridors of 10–40 m width and wet linear corridors of 100–200 m width had a species richness that corresponded to that of clearings of about 10,000 m2. Four species disappeared from the Białowie_za Forest when ungulate density decreased from 20 individuals/km2 (3000 kg/km2 biomass) at the beginning of the 20th century to 10 individuals/km2 (1000 kg/km2) at the end of the 20th century. We conclude that most Orthoptera, Dermaptera, and Blattodea species could survive in Central Europe if human land use was replaced by intensive grazing and browsing by wild herbivores.

Introduction Closed forest has long been regarded as the natural vegetation of most parts of Central Europe (Birks 2005). As a result, it is widely believed that there was little space available to species associated with open landscape until humans cleared the forest and created meadows and heathland. This image of closed forest as the natural vegetation has been discussed over the last decade (e.g. Svenning 2002). Vera (2000) argued that natural forests in the lowlands of Central Europe were rather park-like landscapes that were shaped and maintained by herbivores. This ‘‘wood-pasture’’ hypothesis is in opposition to the ‘‘high-forest" hypothesis (Bradshaw et al. 2003), which has been favoured throughout the 20th century and that considers closed forest as the climax for Central Europe but does not acknowledge the major inﬂuence of herbivores. Maybe because the concept of forest has long been that of a closed canopy without larger clearings, forests are generally not considered an important habitat for Orthoptera, which are considered indicators of [437]

1498 grassland naturalness (Ba´ldi and Kisbenedek 1997). Consequently, little is known of the distribution and habitats favoured by Orthoptera before human actions (mainly pastoralism and agriculture) shaped the landscape of Central Europe. As traditional land use is being abandoned throughout Europe, there are increasing concerns that man-made habitats should be maintained in order to preserve open land species (e.g. Firbank et al. 1994). As the majority of Orthoptera are open land species (Ingrisch and Ko¨hler 1998), the importance of openings in forests is recognised (Shure and Phillips 1991, Clayton 2002, Bouget and Duelli 2004) and forest clearings are sometimes maintained for the conservation of Orthoptera (Kati et al. 2003). However, the minimal size of openings in forests is still unknown for most species and it is still not clear which species would actually disappear on a large scale when habitats return to a non-managed state. Some types of forest cover may even be favourable to thermophilous species (Liana 1981, Bo¨nsel and Runze 2000). On the other hand, forest can represent a barrier for species of open habitats and Orthoptera usually prefer using habitat corridors for dispersal (Collinge 1998, Berggren et al. 2002, Jorda´n et al. 2003), although some species are able to cross long distances through unsuitable habitats: in a German forest 13 Orthoptera species occurred on newly created clearings (Laußmann 1993). The knowledge of the necessary patch size and the role of corridors is crucial for conservation. An important factor that determines the necessary patch size for a species is the shading eﬀect of the forest edge (Bieringer and Zulka 2003). The relationship between patch size and Orthoptera biodiversity has been studied in Hungarian steppe patches (Ba´ldi and Kisbenedek 1999) and in North American forests (Shure and Phillips 1991). We studied Orthoptera, Dermaptera, and Blattodea in a Central European forest in order to assess the minimum patch size of open habitat necessary for each species and the role of linear corridors as habitat. The results are intended to help assess which species actually depend on human land use under the current ecological situation and which species would occur in Central Europe if most of its surface was closed forest or if it was a parkland.

Study area and methods The study area lies in the Polish lowlands on the border to Belarus and includes the Polish side of the Białowie_za Forest (600 km2) and its surroundings (Figure 1). The Białowie_za Forest is a forest complex of 1450 km2 (5230¢–5300¢ N, 2330¢–2415¢ E) that straddles the Polish–Belarussian border. The forest is a mosaic of deciduous, coniferous, and mixed tree stands where large ungulates such as the European bison (Bison bonasus), moose (Alces alces), red deer (Cervus elaphus), roe deer (Capreolus capreolus), and wild boar (Sus scrofa) occur. The Polish side of the Białowie_za Forest consists of the Białowie_za National Park and a commercial forest (480 km2), in which timber harvest, [438]

1499

Figure 1. Sample sites (open circles) in the Białowie_za Forest (light grey) and the near surroundings (sample sites at the Bug river not within the ranges of the ﬁgure) in 1997–2000. Open land (white), strict reserve of the Białowie_za National Park (dark grey), rivers and lakes (black lines and area), state border (dashed and dotted line).

reforestation, and hunting take place. Fifty km2 of the Białowie_za National Park have been protected as a strict reserve since 1921. No hunting or forestry is permitted in the strict reserve. The vegetation structure of the strict reserve and of some places in the commercial forest is little inﬂuenced by humans. Most of the study area is covered by closed forest (Figure 1). Open habitats that occur within the forest are clearings of natural origin (usually few square meters but sometimes up to several thousand square meters), young pine regrowth areas (either plantations or natural, usually dry and sunny), sandpits (mainly small-scale with bare sandy parts and older parts with vegetation), mesophilic forest meadows (usually covered by high grasses), and sandy meadows (mostly dry and with low vegetation). Linear corridors in the forest consist in roads and railway lanes (10–40 m wide) and open marshes along rivers, which are semi-natural as the use of meadows and reed in the marsh almost completely stopped in the 1950s, so the marsh is now often covered by reed and willow shrubs. The open land around the village Białowie_za is [439]

1500 connected with the open land outside the Białowie_za Forest by a large river marsh (Narewka) and a railway lane 30–40 m wide. The open land outside the Białowie_za Forest is mainly non-intensive arable land, but also includes sandpits, fallow land, dry and wet meadows. Koz´min´ski (1925) recorded 32 species of Orthoptera, 1 species of Dermaptera and 1 species of Blattodea (see Table 1) in the Białowie_za Forest at a period just after the total density of ungulates (including cattle) was of 20 individuals/km2 and of a crude biomass of 3000 kg/km2 (Je˛drzejewska et al. 1997). The forest still bears the signs of the almost medieval use that persisted until recently (mid 20th century) as clearings were used for hay making, sand and stone quarries were created throughout the forest, cattle grazed extensively in the forest whilst some game species were protected. The impact of herbivores was therefore much higher. Human use of the forest has changed, forestry exploitation is now being promoted and ungulate densities are being kept low by hunting. In addition, the European bison are being fed in winter, which reduces their impact on forest re-growth, As a result, the total ungulate density was around 10 individuals/km2 for a biomass of 1000 kg/km2 at the time of this study (Je˛drzejewska et al. 1997). On 150 days from April to October in 1997–1999 and in September 2000, we recorded Orthoptera, Blattodea, and Dermaptera at 187 sites in the Białowie_za Forest and its surroundings (Figure 1). The furthest 2 sites in the surroundings were 50 km south-west from the Białowie_za Forest: dunes in the Kozki Nature Reserve 5 km south of the town Siemiatycze and sandy meadows along the Bug river east of the town Drohiczyn. As we were primarily interested in the minimum patch size and the total numbers of species in each patch size class, a standardised sampling eﬀort or a complete species list of each site were not necessary. However, as we recorded species everywhere where we encountered them, the sample size for each patch size class was ﬁnally comparable considering that larger plots need a larger sample size (Table 1), except for the size class from 0.1–1 km2. The small sample size of this size class was related to the little diversity of habitats in these clearings (mainly ﬁelds and meadows for cattle grazing). All size classes included sites in dry and wet habitats and from all months to avoid any inﬂuence of habitat or season on the patch size analyses. We visited most sites only once and searched for animals until we could no longer ﬁnd new species. However, if we expected species to exist in a site but could not ﬁnd them during our ﬁrst visit, we usually returned at least once to the site (287 samples on the 187 sites). Because of earlier experience in identifying Orthoptera in the ﬁeld, we were able to identify species in the ﬁeld acoustically (Bellmann 1985; Bellmann 2004) or by their morphology (Harz 1957) using magnifying glasses. Identiﬁcation of Orthoptera using combinations of stridulation and morphological characteristics are not only ethically preferable but also more reliable than retrospective identiﬁcations of dead individuals. When we were not sure about a ﬁeld identiﬁcation of Blattodea or Dermaptera, we collected the animals and identiﬁed them later with a stereoscope and a key (Harz 1957). We used a [440]

Table 1. Frequency of occurrence (in % of sites) of Orthoptera, Dermaptera, and Blattodea at 187 sites in 6 size classes of clearings in the Białowie_za Forest, on linear corridors (roads of 10–40 m width, river marshes of 100–200 m width), in the glade of Białowie_za (106–107 m2) and in the open land within 50 km around the Białowie_za Forest ( > 108 m2). The maximal distance to forest edge was measured from sites to the forest edge with agricultural land outside the Białowie_za Forest or the glade of Białowie_za (max. possible: 10 km). Species

Number of sites (number of samples)

[441]

0–10

10–10

2

2

3

10 –10

12 (12)

23 (23)

12 (12)

3

10 –10

4

28 (39)

5

Roads

Marsh

10 –10

34 (43)

9 (18)

23 (44)

3 4 4 4 7 7 11 14 14 18 7

4

3 9 9

11 11 22 22 22

44 11

6 9

11

5

10 –10 6 (7)

4 9 9 9 13

33 33 50

17 9 17 13 13 17 9

17 17 33 50

6

6

10 –10

7

21 (55)

5 10 29 19 5 19 14 14 10 5 5 43 10 19 14 10

8

> 10

Max distance to forest edge (km)

19 (34)

+ + 51 51 51 111 5 21 53 5 11 11 16 16

16 11 5 47 84 37

6.2 2.0 3.1 8.7 5.8 4.6 4.1 2.8 6.4 8.7 6.3 9.8 9.8 9.8 9.8

1501

Orthoptera Podisma pedestris * Stenobothrus lineatus* Psophus stridulus* Stenobothrus stigmaticus* Aiolopus thalassinus Chorthippus vagans Omocestus ruﬁpes Meconema thalassinum Decticus verrucivorus* Tettigonia viridissima* Gryllotalpa gryllotalpa* Phaneroptera falcata Conocephalus dorsalis* Chorthippus montanus* Stethophyma grossum* Conocephalus discolor Barbitistes constrictus* Gryllus campestris* Chrysochraon dispar* Tetrix tenuicornis* Chorthippus mollis Metrioptera bicolor Omocestus haemorrhoidalis* Euthystira brachyptera

Size of open habitat patch (m2)

(Continued).

Species

Number of sites (number of samples)

[442]

Gomphocerippus rufus* Chorthippus parallelus* Metrioptera brachyptera* Chorthippus albomarginatus Oedipoda caerulescens* Myrmeleotettix maculatus* Chorthippus brunneus* Chorthippus dorsatus* Chorthippus biguttulus* Tetrix bipunctata* Chorthippus apricarius* Omocestus viridulus* Metrioptera roeselii* Chorthippus pullus* Tettigonia cantans* Pholidoptera griseoaptera* Tetrix subulata* Dermaptera Forﬁcula auricularia* Labia minor Apterygida albipennis Chelidurella acanthopygia Blattodea Ectobius lapponicus* Ectobius silvestris

Size of open habitat patch (m2) 0–10

10–10

2

2

3

10 –10

12 (12)

23 (23)

12 (12)

9 22 26 4 61 26 13

8 8 17 25 17 42 25 50 25 50 17 67 8 58 33 8

3

10 –10

4

28 (39)

4

5

Roads

Marsh

10 –10

34 (43)

9 (18)

23 (44)

11

4 17 22 30 13 30 26 39 4 52 52 57 9 43 30 17

5

6

6

7

8

10 –10

10 –10

6 (7)

21 (55)

19 (34)

> 10

38

42 + 37 47 42 47 58 68

7

8 25 33

4 11 29 14 46 21 43 11 54 46 61 25 50 43 4

8 8 33

3 3

3 3 6 18 18 12 12 15. 21 15 29 6

33 11 11 11 44 33 44 56 56 56 22 22

17 33 17 17 67 50

38 10 5 24 38 29 5 33 33 43

26 53 63

48 5 29

11 16 26 5

11

14 5 5

4 4

5

50 67 67 17

6

4

7

3

Max distance to forest edge (km)

5.5 3.2 8.4 9.8 9.8 9.7 9.8 9.8 9.8 7.7 9.8 9.8 9.8 9.6 9.8 9.8 9.2

3.1 5.4 8.4 8.9

*species found by Koz´min´ski (1925) in the Białowie_za Forest, +found by Bo¨nsel and Runze (2000) 100 km north-west of the Białowie_za Forest, 1found only on dunes in the Kozki Nature Reserve and on sandy meadows along the Bug river 50 km south-west of the Białowie_za Forest. Scientiﬁc names of Orthoptera follow Heller et al. (1998) and of Blattodea and Dermaptera follow Harz (1957).

1502

Table 1.

1503 geographic information system to calculate distances from a clearing to the next forest border and the total number of species found in a given patch or corridor size class as measure for species richness. We plotted the numbers of species against the mean size of clearings (log transformed) for each size class and tested with SPSS 11.0 for Windows which regression model (linear, logarithmic, inverse, quadratic, cubic, power, compound, S-curve, logistic, growth, and exponential) best explained the increase in species numbers.

Results We found 44 species (38 Orthoptera, 4 Dermaptera, 2 Blattodea) in our study area. Of these, 16 species occurred in closed forest, natural clearings or in the strict reserve of the national park. Many species occurred in clearings that were the furthest from the forest edge to arable land or the glade of Białowie_za (Table 1). Most species already occurred in clearings < 0.01 km2. Six species only occurred outside the Białowie_za Forest but the total number of species outside was lower than the number of species living in the Białowie_za Forest. No species occurred exclusively in closed forest. Although all logarithmic models were also signiﬁcant, power models best explained the increase of the mean, total and cumulative numbers of species (Figure 2). Linear corridors were habitat to 22 (roads) and 21 (marsh) species, respectively. The numbers of species found in corridors correspond to the number of species found in clearings of about 10,000 m2.

Discussion We found 44 species of Orthoptera, Dermaptera and Blattodea in the Białowie_za Forest and its surroundings. This list includes 9 species that Koz´min´ski (1925) did not report for the area. We did not ﬁnd one species of Dermaptera (Labidura riparia) and one species of Blattodea (Ectobius erythronotus) that have been found in the Białowie_za Forest (Liana 2001) and that probably still exist. Only few other species might occur in and around the Białowie_za Forest, but even if some other species exist in the area, they would not have greatly inﬂuenced the general results of this study. Four species (Podisma pedestris, Psophus stridulus, Stenobothrus lineatus and Stenobothrus stigmaticus), which were common in the study area when the ungulate density was twice as high and ungulate biomass 3 times higher (Koz´min´ski 1925) than at the time of this study, disappeared from the Białowie_za Forest. We however found one of these species, Stenobothrus stigmaticus, at a study site 50 km south-west of the Białowie_za Forest in dunes of the Bug river (Table 1). All four species, which also became rare in other parts of Central Europe (Harz 1957, Liana 1981) and of which the ﬁrst two stand on the Polish red list (Liana 1992), probably disappeared due to changes [443]

1504

Figure 2. Best ﬁt models (power regression) of mean numbers of species (regression line for single sites and 95% conﬁdence intervals for sites of each size class) and of total numbers of species (solid regression line with closed circles for each size class, dotted regression line with open circles for cumulative number of species) of clearings in the Białowie_za Forest and the open land around the forest.

[444]

1505 in land use such as the disappearance of forest pasture and the abandonment of heathland. In contrast, Liana (1981) found that dry habitats in forested areas were richer in Orthoptera species than those in the open land. Five species (Barbitistes constrictus, Chorthippus pullus, Euthystira brachyptera, Gomphocerippus rufus, Metrioptera brachyptera) were even restricted to forested areas. Psophus stridulus occurred in the Biebrza area (north-east Poland) only on a dune surrounded by trees, which had a warmer micro climate than the surroundings (Bo¨nsel and Runze 2000). It is likely that clearings in forested areas are better habitats for thermophilous species due to thermal advantages. Dragonﬂies also exhibited a similar dependence to forest in the Białowie_za Forest where the most thermophilous species reproduced only in ponds of forest clearings but not in the surroundings (Theuerkauf and Rouys 2001). Forests might therefore play an important role in maintaining Orthoptera diversity in Central Europe. Although forest can improve the habitat quality for thermophilous species, it can also reduce the survival chances of species that depend on relatively large open habitat patches. Bieringer and Zulka (2003) found that shading aﬀects the occurrence of Orthoptera up to 30 m from the forest edge. Clearings under 1000 m2 are therefore almost entirely aﬀected by shading from the forest edge, and indeed we found only about one third of species on these clearings. Two third of species already occurred in the next size class (0.01–0.1 km2), which is probably linked to a reduced shading eﬀect. Those species that disappeared from the Białowie_za Forest, however, probably needed a larger surface of habitat. High density of cattle and wild ungulates might have provided the necessary extension of habitat for these thermophilous Orthoptera species at the beginning of the 20th century, but the current grazing intensity did not allow these species to persist. We think that these species probably disappear in Central Europe where human land use is discontinued and not taken over by intensive ungulate grazing. In the Bieszczady National Park (Southeast Poland), Psophus stridulus and Aiolopus thalassinus probably disappeared after human land use (cattle grazing) was discontinued 60 years ago (Theuerkauf et al. 2005). Habitat corridors are known to be important for the dispersal of Orthoptera (Collinge 1998; Berggren et al. 2002; Jorda´n et al. 2003). However, our study indicated that linear corridors in forests are also an important habitat for Orthoptera. Both corridors in river marshes and along forest roads had numbers of species that corresponded to clearings of about 10,000 m2. Whilst the number of species on the wet marsh corridors can be explained by their width of 100–200 m, the number of species on the road corridors of 10–40 m was much larger than might be expected by the patch size. Obviously, the shading eﬀect was not an important limitation in species numbers on these dry corridors. From an evolutionary perspective, it is possible that species of drier habitats must be able to exist on smaller habitat patches than those of wet habitats. The reason might be that river marshes are open on a larger scale than dry clearings due to regular ﬂooding or activity of beavers (Castor ﬁber). Dry [445]

1506 clearings on the other hand can be maintained by ungulates but ﬁrst need to be created (for example by wind), which occurs probably on a smaller area. We conclude that Central Europe might loose a few Orthoptera species (e.g. the ﬁrst 7 species in Table 1) if human land use was replaced by grazing by wild animals. However, under the current ecological situation with low herbivore densities and only a few species in most regions, it would take considerable management measures to re-establish natural grazing communities. Many species of Orthoptera and even some Dermaptera species would probably disappear from regions where human land use is discontinued and not replaced by natural grazing. Rather than keeping forest clearings open for the conservation of Orthoptera (Kati et al. 2003), we argue that the concept of species conservation in open habitats needs to be reconsidered to include a full array of herbivores at densities that might appear high but that were common in historical times (Beutler 1996).

Acknowledgements We thank C. Okołow, the director of the Białowie_za National Park, for permission to work in the strict reserve, B. Jaroszewicz for providing us with information during the study, P.-M. A. Dettinger-Klemm and two anonymous reviewers for useful comments.

References Ba´ldi A. and Kisbenedek T. 1997. Orthopteran assemblages as indicators of grassland naturalness in Hungary. Agric. Ecosyst. Environ. 66: 121–129. Ba´ldi A. and Kisbenedek T. 1999. Orthopterans in small steppe patches: an investigation for the best-ﬁt model of the species-area curve and evidences for their non-random distribution in the patches. Acta Oecologica 20: 125–132. Bellmann H. 1985. Die Stimmen der heimischen Heuschrecken [the calls of native orthoptera]. Verlag J. Neumann-Neudamm, Melsungen [audio tape]. Bellmann H. 2004. Heuschrecken – Die Stimmen von 61 heimischen Arten [Orthoptera – Calls of 61 Native Species]. Ample Edition, Musikverlag. [audio CD]. Berggren A˚., Birath B. and Kindvall O. 2002. Eﬀect of corridors and habitat edges on dispersal behavior, movement rates, and movement angles in Roesel’s bush-cricket (Metrioptera roeseli). Conserv. Biol. 16: 1562–1569. Beutler A. 1996. Die Großtierfauna Europas und ihr Einﬂuß auf Vegetation und Landschaft [The megafauna of Europe and its impact on vegetation and landscape]. In: Gerken B. and Meyer C. (eds), Wo lebten pﬂanzen und Tiere der Naturlandschaft und der fru¨hen Kulturlandschaft Europas? [Where did Plants and Animals Live in the Natural and Early Cultural Landscapes of Europe?]. Natur- und Kulturlandschaft 1, Ho¨xter, pp. 51–106. [In German] Bieringer G. and Zulka K.P. 2003. Shading out species richness: edge eﬀect of a pine plantation on the Orthoptera (Tettigoniidae and Acrididae) assemblage of an adjacent dry grassland. Biodiv. Conserv. 12: 1481–1495.

[446]

1507 Birks H.J.B. 2005. Mind the gap: how open were European primeval forests? Trends Ecol. Evol. 20: 154–156. Bo¨nsel A. and Runze M. 2000. Ein Habitat der Rotﬂu¨geligen Schnarrschrecke (Psophus stridulus L., 1758) im nordo¨stlichen Polen [A habitat for Psophus stridulus L., 1758 in northeastern Poland]. Articulata 15: 49–62. [In German with English abstract] Bouget C. and Duelli P. 2004. The eﬀects of windthrow on forest insect communities: a literature review. Biol. Conserv. 118: 281–299. Bradshaw R.H.W., Hannon G.E. and Lister A.M. 2003. A long-term perspective on ungulatevegetation interactions. Forest Ecol. Manage. 181: 267–280. Clayton J.C. 2002. The eﬀects of clearcutting and wildﬁre on grasshoppers and crickets (Orthoptera) in an intermountain forest ecosystem. J. Orthoptera Res. 11: 163–167. Collinge S.K. 1998. Spatial arrangement of habitat patches and corridors: clues from ecological ﬁeld experiments. Landscape and Urban Planning 42: 157–168. Firbank L.G., Telfer M.G., Eversham B.C. and Arnold H.R. 1994. The use of species-decline statistics to help target conservation policy for set-aside arable land. J. Environ. Manage. 42: 415–422. Harz K. 1957. Die Geradﬂu¨gler Mitteleuropas [The Orthoptera of Central Europe]. Gustav Fischer, Jena. [In German] Heller K.G., Korsunovskaya O., Ragge D.R., Vedenina V., Willemse F., Zhantiev R.D. and Frantsevich L. 1998. Check-list of European Orthoptera. Articulata Beiheft 7: 1–61. Ingrisch S. and Ko¨hler G. 1998. Die Heuschrecken Mitteleuropas [The Orthoptera of Central Europe]. Neue Brehm-Bu¨cherei Bd. 629. Westarp Wissenschaften, Magdeburg Germany. [In German] Je˛drzejewska B., Je˛drzejewski W., Bunevich A., Miłkowski L. and Krasin´ski Z. 1997. Factors shaping population densities and increase rates of ungulates in Białowie_za Primeval Forest (Poland and Belarus) in the 19th and 20th centuries. Acta Theriologica 42: 399–451. Jorda´n F, Ba´ldi A, Orci K.-M., Ra´cz I. and Varga Z. 2003. Characterizing the importance of habitat patches and corridors in maintaining the landscape connectivity of a Pholidoptera transsylvanica (Orthoptera) metapopulation. Landscape Ecol. 18: 83–92. Kati V., Dufreˆne M., Legakis A., Grill A. and Lebrun P. 2003. Conservation management for Orthoptera in the Dadia reserve, Greece. Biol. Conserv. 115: 33–44. Koz´min´ski Z. 1925. O¨kologische Untersuchungen an Orthopteren des Urwalds von Białowie_za [Ecological studies of Orthoptera in the Białowie_za Forest], Bulletin de l’Acade´mie Polonaise des Sciences et des Lettres – Classe des Sciences Mathe´matique et Naturelles – Se´rie B: Sciences. Naturelles 1925: 447–475. [In German] Laußmann H. 1993. Die Besiedlung neu entstandener Windwurﬄa¨chen durch Heuschrecken [Colonisation of newly created wind-fall sites by Orthoptera]. Articulata 8: 53–59. [In German with English abstract] Liana A. 1981. Prostoskrzydłe (Orthoptera) w siedliskach kserotermicznych Pojezierza Mazurskiego [Orthoptera in xerothermic habitats of the Mazurian lakeland]. Fragmenta Faunistica 25: 479–510. [In Polish with Russian and French abstracts] Liana A. 1992. Owady prostoskrzydłe Orthoptera [Orthopteroid insects]. In: Głowacin´ski Z. (ed), Czerwona lista zwierza˛t gina˛cych i zagro_zonych w Polsce [Polish Red List of Threatened Animals]. Polish Academy of Sciences, Nature Protection Research Centre, Krako´w, pp. 85–91. [In Polish with English abstract] Liana A. 2001. Orthoptera-Blattodea. In: Gutowski, J.M. and Jaroszewicz B. (eds), Katalog Fauny Puszczy Białowieskiej. [Faunal catalogue of the Białowieza Forest]. Instytut Badawczy Les´ nictwa, Warszawa, pp. 92–93. Shure D.J., Phillips D.L. 1991. Patch size of forest openings and arthropod populations. Oecologia 86: 325–334. Svenning J.-C. 2002. A review of natural vegetation openness in north-western Europe. Biol. Conserv. 104: 133–148. Theuerkauf J., Rouys S. 2001. Habitats of Odonata in the Białowie_za Forest and its surroundings (Poland). Fragmenta Faunistica 44: 33–39.

[447]

1508 Theuerkauf J., Rouys S. Grein G. Becker A. 2005. New records of Orthoptera in the Bieszczady Mountains (Southeast Poland) with special regard to the genus Isophya. Fragmenta Faunistica 48: 9–14. Vera F.W.M. 2000. Grazing Ecology and Forest History. CABI Publishing, Wallingford.

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Biodiversity and Conservation (2006) 15:1509–1527 DOI 10.1007/s10531-005-2632-0

Springer 2006

-1

Species Composition, diversity and local uses of tropical dry deciduous and gallery forests in Nicaragua BENIGNO GONZA´LEZ-RIVAS1, MULUALEM TIGABU2,*, KARIN GERHARDT3, GUILLERMO CASTRO-MARI´N1 and PER CHRISTER ODE´N2 1 Facultad de Recursos Naturales y del Ambiente, Universidad Nacional Agraria Apartado Postal 453, Managua, Nicaragua; 2Department of Forest Genetics and Plant Physiology, Tropical Silviculture and Seed Laboratory, Faculty of Forest Sciences, Swedish University of Agricultural Sciences, SE-901 83 Umea˚, Sweden; 3Department of Plant Ecology and Evolutionary Biology Centre, Uppsala University, Villava¨gen 14, SE-752 36 Uppsala, Sweden; *Author for correspondence (e-mail: [email protected], [email protected]; phone: +46-90-786-83-19; fax: +46-90786-58-96)

Received 6 December 2004; accepted in revised form 15 August 2005

Key words: Biodiversity, Central America, Endangered species, Floristic composition Abstract. The ﬂoristic composition and diversity of tropical dry deciduous and gallery forests were studied in Chacocente Wildlife Refuge, located on the Paciﬁc coast in Nicaragua during 1994 and 2000. Density, dominance and frequency as well as species and family important values were computed to characterize the ﬂoristic composition. A variety of diversity measures were also calculated to examine heterogeneity in each forest community. A total of 29 families, 49 genera and 59 species were represented in 2 ha dry deciduous forest. In the gallery forest, the number of families, genera and species recorded in 2000 inventory was 33, 48 and 58, respectively and slightly higher than the 1994 inventory. The number of stems ‡10 cm dbh varied from 451 to 489 per hectare in the deciduous forest, and from 283 to 298 per hectare in the gallery forest. The basal area was much larger for species in the gallery than dry deciduous forest. Fabaceae, sub family Papilionoideae, was the most specious family in the deciduous forest while Meliaceae was the dominant family in the gallery forest. Similarity in species composition and abundance between deciduous and gallery forests was low. In terms of species diversity, the gallery forest was found more diverse than the deciduous forest using Fisher’s diversity index. Both forest communities were characterized by a typical inverse J shape. Therefore, emphasis should be given to the protection of rare species, i.e. as the forests are still under continued human pressure, an immediate action should be taken to conserve the remaining ﬂora.

Introduction Dry forests once covered more than 40% of the total area of tropical forests (Murphy and Lugo 1986). They are considered to be one of the most threatened of all the major tropical forest habitats and are argued to deserve a high priority for conservation (Janzen 1988; Gillespie et al. 2000). According to the Holdridge system of life zone classiﬁcation, dry tropical and subtropical forests and woodlands occur in frost-free areas with a mean annual temperature [449]

1510 higher than 17 C, a mean annual rainfall between 250 and 2000 mm, and an annual ratio of potential evapotranspiration to precipitation exceeding unity (Murphy and Lugo 1995). The area of natural forests in Central America is estimated to be 190,000 km2, representing ca. 15% of the total land cover. In addition, some 130,000 km2 deforested land is considered suitable only for forestry, adding to 24% of the total area (Segura et al. 1997). The deforestation rate in Central America is estimated as 0.5 km2 per year (Roldan 2001). The tendency of human populations to concentrate in drier climates is hastening the rate of dry forest degradation (Murphy and Lugo 1995) and deforestation has increased dramatically with population growth during the last century. Large areas are cleared for grazing and agriculture and only fragments of dry forests remain (Gerhardt 1994). Nicaragua has 2500 km2 of tropical dry forests, representing ca. 2% of the total forest cover (Harcourt and Sayer 1996). The dry forests are found mainly on the Paciﬁc coast where ca. 50% of the population also lives. Nicaraguan dry forests have been intensively exploited for commercial timber production. The major commercial timber species are Swietenia humilis, Cedrela odorata, Bombacopsis quinata, Dalbergia retusa and Guaiacum sanctum (Sabogal 1992). The extraction of valuable commercial trees for export started in early 1900 (Tercero and Urrutia 1994), and continued for decades, resulting in considerable reduction of commercially important species. The Nicaraguan Paciﬁc railway was constructed in the 1950s and most of the railway sleepers used was extracted from the dry forest in Chacocente (Tercero and Urrutia 1994). The dry forests are still major sources of wood for ﬁre, poles and timber, and provide opportunities for hunting and collection of other important non-timber forests products (NTFP). In addition to cutting of trees for wood and related products, the major causes of deforestation have been conversion of dry forests into coﬀee plantations, crop ﬁelds and ranches (Roldan 2001). Chacocente National Wildlife Refuge was established in 1983 to protect the nesting beach of marine turtles and the last area of the tropical dry forest due to the social, economic, ecological and scientiﬁc relevance of this type of ecosystem. During the Sandinista Revolution big ranches were expropriated and became property of the state. In 1990 this land was given to peasant cooperatives. By 1998, the land tenure changed very rapidly since land was being sold and cooperative land was converted into private land (Anonymous 2002). Today, the Chacocente National Wildlife Refuge consists mainly of private farms (84 owners), although some are quite small. The only state land in the refuge is a small property donated to Ministry of Natural Resources and Environment (MARENA) by the International Fauna and Flora Organization. The refuge is not fully protected against human impact and is utilized both legally and illegally by the local people living inside as well as outside the refuge. Anthropogenic disturbances such as burning, grazing, wood collection and illegal cutting are factors aﬀecting plant population density (Gillespie et al. 2000). The eﬀect of this land use dynamics and forest fragmentation on biological diversity in Chacocente is not well documented (Sabogal and Valerio 1998). An [450]

1511 assessment of species composition and diversity provide information for developing guidelines for conservation priorities in the region since few comparative or quantitative studies in remaining forest fragments in Central America have been made (Gillespie et al. 2000). In this study, we described the ﬂoristic composition and species diversity of two tropical dry forest types, dry deciduous and gallery forests, at two diﬀerent times. The vegetation description presented will hopefully contribute to a better understanding of the ﬂoristic composition and diversity of the tropical dry forests. Given the threatened status of dry forests throughout the tropics, particularly in Nicaragua, and the fact that dry forests are less studied than moister tropical forest types, this study will provide important baseline data for the region. Materials and methods Study area This study was carried out in Chacocente Wildlife Reserve (1136¢–1130¢ N and 8608¢–8615¢ W) located on the Paciﬁc coast in the department of Carazo, Nicaragua (Figure 1). The refuge consists of closed deciduous forest (1099 ha), gallery forest (471 ha), open low forest (1842 ha), fallows area (554 ha), annual crops (311 ha), grassland (294 ha), and beach area (71 ha) (Anonymous, 2002). Chacocente has a dry period of 7 months with less than 50 mm precipitation per months, and during the rainy season (June–October) rainfall is irregular with many days without rainfall (Anonymous 2002). The mean annual precipitation during the last 13 years has been 1422 mm, with a maximum in 1995

Figure 1. Distribution of tropical dry forests in Nicaragua and location of the study site, Chacocente. [451]

1512 (1962 mm) and the minimum in 1991 (991 mm). During October 1998, hurricane Mitch passed over the area and the precipitation that month was as high as 775 mm. The average annual temperature is 26 C (Anonymous 2002). The gallery forest, deﬁned as narrow patches along the fringes of semipermanent watercourses (Lamprecht 1989), occurs along the main water course, the Rı´ o Escalante. It has a diﬀerent species composition, structure and stand density than the more common deciduous forest. The vegetation is mostly evergreen, the trees are tall and the majority of the trees have a diameter exceeding 35 cm at breast height. The deciduous forest trees totally or partially shed their leaves during the dry season.

Sampling and data analyses Two permanent plots in each forest type were established by Universidad Nacional Agraria, Managua, Nicaragua in 1989. The area of each permanent plot was 1.0 ha and subdivided into 25 subplots of 20 · 20 m. Each plot was systematically surveyed by identifying, measuring, and tagging all trees with diameter at breast height (dbh) ‡10 cm. The inventories were made in 1994 and 2000. In addition, local names were recorded and information about uses of the tree species was gathered by consulting a Nicaraguan forest use specialist (Claudio Calero, personal communication) and relevant literature (Salas 1993; Stevens et al. 2001). All scientiﬁc names were thoroughly cross-checked in the TROPICOS nomenclatural database (http://mobot.mobot.org/W3T/search/ Vast.html) of the Missouri Botanical Garden. The importance value index (IVI) and family importance value (FIV) were used to describe the species composition of the plots. IVI of a species is deﬁned as the sum of its relative dominance, its relative density and its relative frequency, which in turn are calculated as follows: Relative dominance¼ total basal area for a species/total basal area for all species Relative density¼ number of individuals of a species/total number of individuals Relative frequency¼ frequency of a species/sum frequencies of all species The frequency of species is deﬁned as the number of subplots (20 · 20 m) in which the species is present. The theoretical range for relative dominance, relative density and relative frequency is 0–100%, thus IVI of species may vary between 0 and 300%. The FIV was computed in the same way as IVI except that relative frequency was replaced by the relative diversity, computed as the number of species in a family/total number of species. All species encountered during both inventories were clustered into three groups based on the mean number of individuals of a species per hectare as rare (4 individuals per

[452]

1513 hectare), intermediate (4–24 individuals per hectare) and abundant (>24 individuals per hectare). According to Duque and Cavelier (2003), a species with two or fewer individuals in 2.16 ha is considered as locally rare. A variety of commonly used diversity indices were computed in order to permit a more precise comparison of the alpha diversity between the two forest communities. These indices were Margalef’s species richness index, Shannon’s measure of evenness, Shannon–Wiener’s diversity index, Simpson’s diversity index and Fisher’s diversity index. These indices are widely employed to measure biological diversity (Magurran 2004). In addition, the species-abundance patterns in each forest community were plotted. Floristic similarity between forest communities was assessed using Jaccard’s coeﬃcient of similarity, based on the presence/absence of the species, and Morisita’s index of similarity, based on number of individuals per species. Jaccard’s coeﬃcient of similarity and Morisita’s index vary between 0 and 1 and a value close to 1 indicates greater similarity between forest communities (Krebs 1999). The conservation status of species encountered in our plots was assessed based on the 2004 IUCN Red List of Threatened Species directory (IUCN 2004). In addition, candidate species for future IUCN listing were identiﬁed based on their rarity and regional distribution based on Flora of Nicaragua (Stevens et al. 2001) and the Missouri Botanical Garden’s TROPICOS database.

Results Floristic composition A total of 29 families, 49 genera and 59 species were found in the dry deciduous forest during both inventories (Table 1). While the stem density slightly increased in 2000 inventory, the basal area was relatively less compared to the inventory made in 1994. Fabaceae, sub-family Papilionoideae was the most specious family with higher FIV (Table 2). Other families (sub-families) with ‡4 species were Caesalpinioideae and Boraginaceae. Hernandiaceae, though represented by one species (Gyrocarpus americanus), had the second and third higher FIV in 1994 and 2000 inventories, respectively owing to the large stem density per hectare (62 individuals/ha in 1994 and 37 individuals/ha in 2000). Gyrocarpus americanus stood out as the most abundant species during both inventories in terms of basal area, relative dominance, relative frequency and IVI (Table 3). While Tabebuia ochracea was the second most abundant species during both inventories, Lonchocarpus minimiﬂorus and Myrospermum frutescens were more abundant in 1994 and 2000 inventories, respectively. The rarest species during both inventories were Celtis caudata and Zanthoxylum caribaeum (Table 4). Four species, Acacia costaricensis, Ficus obtusifolia, Pithecellobium saman and Trichilia hirta, recorded in 1994 inventory were not encountered in 2000, but four other species, Adelia barbinervis, Casearia

[453]

1514 Table 1. Summary of ﬂoristic composition and structure of trees ‡10 cm dbh in dry deciduous and gallery forests inventoried in 1994 and 2000. Forest types-Inventory time

Families

Genera

Species

Stem densitya

Basal areab

Deciduous-94 Deciduous-00 Gallery-94 Gallery-00

29 29 33 33

49 49 47 48

59 59 55 58

451 489 298 283

31.5 29.0 45.3 49.3

a

stem density = Number of individuals ha1. basal area (m2 ha1).

b

Table 2. The ten most important families (sub-families) in the dry deciduous and gallery forests of Chacocente in 2000 inventory according to decreasing order of family importance value (FIV). Forest type

Family

Genus

Species

N/ha

IFV

Deciduous

Papilionoideae Caesalpinioideae Hernandiaceae Mimosoideae Bignoniaceae Achatocarpaceae Boraginaceae Apocynaceae Spindaceae Tiliaceae Miliaceae Capparidaceae Sapindaceae Hernandaceae Sterculiaceae Annonaceae Boraginaceae Simaroubaceae Apocynaceae Rhamnaceae

8 3 1 2 1 1 1 1 2 1 3 1 1 1 2 2 1 1 1 2

10 5 1 3 1 1 4 1 2 1 4 1 1 1 2 2 4 1 1 2

82 45 37 19 40 23 13 30 17 12 39 14 13 7 8 15 13 16 8 8

58.3 29.3 23.3 20.7 19.2 14.8 14.0 12.7 10.4 7.2 40.0 17.6 17.3 15.5 11.6 11.4 14.0 10.7 10.0 8.5

Gallery

corymbosa, Cordia dentata and Trema micrantha, were found in 2000 inventory (Appendix). In the gallery forest, the number of families, genera and species encountered in 1994 inventory were 33, 47 and 55, respectively while 48 genera and 58 species were recorded in 2000 inventory (Table 1). The total stem density (298 individuals/ha) was comparatively higher in 1994 inventory than in 2000 inventory while the basal area was relatively larger in 2000 than in 1994 inventory. In both inventories, Meliaceae was the most specious family with higher IFV (Table 2). Most of the important families were represented by 1 or 2 species. The most abundant species, in terms of basal area, relative dominance, and IVI was Pithecellobium saman, followed by Trichilia hirta (Table 5). In both inventories, Cordia alliodora was the rarest species, followed by Hymenaea courbaril in the [454]

1515 Table 3. The ten most abundant species in the dry deciduous forest of Chacocente in 1994 and 2000 inventories according to decreasing order of importance value index (IVI) together with structural characteristics. Species

1994 Inventory Basal area (m2/ha)

Relative dominance (%)

Relative density (%)

Relative frequency (%)

IVI

Gyrocarpus americanus Tabebuia ochracea Lonchocarpus minimiﬂorus Stemmadenia obovata Caesalpinia exostemma Myrospermum frutescens Lysiloma divaricatum Achatocarpus nigricans Gliricidia sepium Luehea candida

6.5326 2.0714 2.1939 1.2935 1.8645 1.3467 2.0737 1.3346 1.8495 0.7214

20.72 6.57 6.96 4.10 5.91 4.27 6.58 4.23 5.87 2.29

13.57 8.57 9.79 9.23 7.45 6.01 3.34 5.78 2.78 2.78

8.12 7.48 5.56 6.84 4.70 5.34 4.70 1.92 2.78 4.06

42.4 22.6 22.3 20.2 18.1 15.6 14.6 11.9 11.4 9.1

Gyrocarpus americanus Tabebuia ochracea Myrospermum frutescens Caesalpinia exostemma Stemmadenia obovata Achatocarpus nigricans Lonchocarpus minimiﬂorus Gliricidia sepium Luehea candida Allophylus psilospermus

2000 Inventory 3.548 12.23 2.1671 7.47 1.4233 4.91 1.8082 6.23 1.0028 3.46 2.0956 7.23 0.9979 3.44 1.8574 6.40 0.6862 2.37 0.5432 1.87

9.41 10.04 6.52 7.28 7.53 5.90 7.90 2.38 3.14 2.76

8.28 7.63 6.10 3.92 5.88 3.05 4.79 2.83 3.92 2.40

29.9 25.1 17.5 17.4 16.9 16.2 16.1 11.6 9.4 7.0

1994 inventory, and Triplaris melaenodendronin the 2000 inventory (Table 6). Four species, Casearia tremula, Pithecellobium dulce, Piper aduncum and Randia nicaraguensis recorded in 1994 inventory were missing in 2000 inventory while seven other species were encountered in 2000 inventory; namely, Acacia costaricensis, Bursera simaruba, Caesalpinia exostemma, Caesalpinia violacea, Coccoloba sp., Licania arborea and Tabebuia rosea (Appendix). As a whole, the number of species recorded in dry deciduous and gallery forests was nearly the same. However, the stem density in the dry deciduous forest was twice higher than the gallery forest while the basal area was much bigger in the latter. It was found that the similarity in species composition between the two forest communities in both inventories was very low, as shown by low Jaccard’s (0.27) and Morisita’s (0.35) similarity indices. Species diversity The species-abundance patterns of dry deciduous and gallery forests displayed a typical inverse J-distribution or the log series distribution (Figure 2). The [455]

1516 Table 4. The ten rarest species in the dry deciduous forest of Chacocente in 1994 and 2000 inventories according to increasing order of IVI together with structural characteristics. Species

1994 Inventory Relative Relative Relative IVI Basal area (m2/ha) dominance (%) density (%) frequency (%)

Zanthoxylum caribaeum Celtis caudata Ficus obtusifolia Coursetia elliptica Diospyros nicaraguensis Dalbergia retusa Calycophyllum candidissimum Swietenia humilis Chomelia spinosa Haematoxylon brasiletto

0.0154 0.0305 0.0366 0.0266 0.0566 0.0137 0.0113 0.278 0.0715 0.6026

0.05 0.10 0.12 0.08 0.18 0.04 0.04 0.88 0.23 1.91

0.11 0.11 0.11 0.22 0.22 0.44 0.56 0.33 0.67 0.56

0.21 0.21 0.21 0.43 0.43 0.64 1.07 0.64 1.07 1.07

0.37 0.42 0.44 0.73 0.83 1.12 1.67 1.85 1.97 3.54

Celtis caudata Zanthoxylum caribaeum Malpighia stevensii Coursetia elliptica Dalbergia retusa Chomelia spinosa Diospyros nicaraguensis Calycophyllum candidissimum Haematoxylon brasiletto Swietenia humilis

2000 Inventory 0.0167 0.06 0.0191 0.07 0.0216 0.07 0.0281 0.10 0.0097 0.03 0.0216 0.07 0.0923 0.32 0.0113 0.04 0.1863 0.64 0.3244 1.12

0.13 0.13 0.13 0.25 0.50 0.63 0.75 0.63 0.50 0.50

0.22 0.22 0.22 0.44 0.65 0.87 0.65 1.09 0.87 0.87

0.40 0.41 0.42 0.78 1.19 1.57 1.72 1.76 2.02 2.49

majority of the species in both forest communities were represented by few individuals while few species in both forests were represented by many individuals. In the dry deciduous forest, out of the 59 species recorded during both inventories, 37 species were considered as rare (<4 individuals/ha), 15 species as intermediate (4–24 individuals/ha) and 7 species as abundant (>24 individuals/ha). Of all the species recorded in the gallery forest during both inventories, 43 species was considered as rare (<4 individuals/ha), 8 species as intermediate (4–24 individuals/ha) and 4 species as abundant (>24 individuals/ ha). The various diversity measures for each forest community are presented in Table 7. Although the total number of species recorded in both forest communities was very close, the number of individuals in 2 ha plot was much higher in the dry deciduous than gallery forests. In terms of numerical species richness (S/N), the two forest communities diﬀered slightly (cf. 0.1 for gallery and 0.06 for deciduous forest). According to Margalef’s index of species richness (DMg), which combines mathematically number of species (S) and numerical species richness (S/N), the gallery forest (in 2000 inventory) was found to be more diverse than the dry deciduous forest. Shannon’s measure of evenness did not diﬀer much between and within forest communities. The Shannon–Wiener diversity index, which combines species richness and [456]

1517 Table 5. The ten most abundant species in the gallery forest of Chacocente in 1994 and 2000 inventories according to decreasing order of importance value index together with structural characteristics. Species

1994 Inventory Basal area (m2/ha)

Relative dominance (%)

Pithecellobium saman Trichilia hirta Thouinidium decandrum Simarouba glauca Capparis pachaca Gyrocarpus americanus Astronium graveolens Stemmadenia obovata Guarea glabra Trichilia moschata

12.462 4.2525 2.9502 1.5827 0.8255 2.4077 1.6976 0.7411 0.9649 0.8863

27.49 9.38 6.51 3.49 1.82 5.31 3.74 1.63 2.13 1.96

Pithecellobium saman Trichilia hirta Capparis pachaca Thouinidium decandrum Gyrocarpus americanus Simarouba glauca Annona reticulata Astronium graveolens Stemmadenia obovata Guarea glabra

2000 Inventory 12.7787 25.89 2.4232 4.91 1.3614 2.76 2.9474 5.97 4.6233 9.37 2.01 4.08 1.3844 2.80 2.0686 4.19 0.8589 1.74 1.2341 2.50

Relative density (%)

Relative frequency (%)

IVI

0.76 7.89 5.43 2.97 4.75 2.21 1.87 3.99 2.97 2.04

2.34 8.31 6.23 9.09 6.49 4.16 5.97 4.16 4.16 4.68

30.6 25.6 18.2 15.6 13.1 11.7 11.6 9.8 9.3 8.7

1.22 15.29 13.15 9.63 4.43 4.89 4.13 3.21 6.57 5.35

2.07 8.55 7.51 6.74 3.63 8.29 6.74 5.44 4.15 4.40

29.2 28.8 23.4 22.3 17.4 17.3 13.7 12.8 12.5 12.3

evenness into a single value, declined over time within each forest community, and identiﬁed the dry deciduous forest as more diverse than the gallery forest. The complement of Simpson’s index, which attaches more weight to the abundance of the most common species, also identiﬁed the dry deciduous forest as more diverse than the gallery forest. Fisher’s diversity index, the most widely recommended measure of diversity, revealed that the galley forest is more diverse than the dry deciduous forest.

Local uses Although we did not make a systematic ethno-botanical study, the local uses of the tree species in both forest communities were identiﬁed based on information gathered from the local people, expert consultation and existing literature. Accordingly, ten major use categories were identiﬁed (Figure 3). It was found that the largest number of species in both forest communities (53% of the total species) was used for ﬁrewood, followed by timber extraction (35%), rural construction (27%) and charcoal production (23%). Interest[457]

1518 Table 6. The ten rarest species in the gallery forest of Chacocente in 1994 and 2000 inventories according to increasing order of IVI together with structural characteristics. Species

1994 Inventory Basal area (m2/ha)

Relative dominance (%)

Relative density (%)

Relative frequency (%)

IVI

Cordia alliodora Hymenaea courbaril Karwinskia calderonii Triplaris melaenodendron Guaiacum sanctum Ceiba pentandra Cordia gerascanthus Albizia caribaea Sterculia apetala Cedrela odorata

0.0174 0.0287 0.0613 0.0931 0.0257 0.5064 0.09 0.7178 0.4611 1.0955

0.04 0.06 0.14 0.21 0.06 1.12 0.20 1.58 1.02 2.42

0.1 0.2 0.2 0.2 0.3 0.1 0.3 0.1 0.3 0.6

0.26 0.52 0.52 0.52 0.78 0.26 1.04 0.26 1.04 1.82

0.38 0.75 0.83 0.90 1.09 1.46 1.58 1.92 2.40 4.83

Cordia alliodora Triplaris melaenodendron Hymenaea courbaril Karwinskia calderonii Cedrela odorata Guaiacum sanctum Cordia gerascanthus Albizia caribaea Ceiba pentandra Sterculia apetala

2000 Inventory 0.0209 0.04 0.0607 0.12 0.0264 0.05 0.0821 0.17 0.0095 0.02 0.2346 0.48 0.0804 0.16 0.7854 1.59 0.8202 1.66 0.4898 0.99

0.15 0.15 0.31 0.31 0.46 0.31 0.46 0.15 0.31 0.61

0.26 0.26 0.52 0.52 0.78 0.52 0.78 0.26 0.52 1.04

0.45 0.53 0.88 0.99 1.26 1.30 1.40 2.00 2.49 2.64

ingly, 24% of the species are not currently under any kind of use. The abundance of species by use group was also examined for each forest community (Figure 3). Given the large number of species used for ﬁrewood, the overall abundance was also high. The most interesting part of this result is that the abundance of species used for ﬁrewood and timber declined from 1994 to 2000 in both forest communities. Although the abundance of the ‘‘not used’’ species in the gallery forest showed an increasing tendency, the reverse held true in the deciduous forest.

Species with high conservation importance Most of the species in our plots were represented by few individuals (Figure 2). Some of the rarest species were already short-listed in IUCN red list directory as threatened species. Among these threatened species, ﬁve species were categorized as vulnerable and six species as endangered (Table 8). Bombacopsis quinata, considered as vulnerable, was not encountered in our plots. We also identiﬁed seven candidate species that could be included in IUCN red list directory in the future (Table 8). [458]

1519 125

125

100 75

75

50

50

25

25

0

0 0

10

20

30

40

50

0

10

Species rank

20

30

40

50

Species rank

100

100

Gallery-00

Gallery-94 Abundance

100

Abundance

Deciduous-00

75

75

50

50

25

25

0

Abundance

Abundance

Deciduous-94

0 0

10

20

30

40

0

10

20

30

40

Species rank

Species rank

Figure 2. Species abundance plots for dry deciduous and gallery forests inventoried in 1994 and 2000.

Discussion The number of families, genera and species reported in the present study lies within the range reported earlier in most Neotropical dry forests. For example, Gentry (1988) reported 35 families and 55 species per hectare in a gallery forest in Guanacaste, Costa Rica and Sabogal and Valerio (1998) reported on average 44 species per hectare in Chacocente dry deciduous forest in Nicaragua. The most common family in the deciduous forest was Fabaceae/Papilionoideae with 10 species, a pattern common in most Neotropical dry forests (Gentry 1988). This result also coincides with a study carried out in Central America where Fabaceae was found to be the dominant tree and shrub family in six of seven sites studied (Gillespie et al. 2000). Gillespie et al. (2000) made an inventory in Chacocente and found the same common species as in the present study. However, the present study found L. minimiﬂorus and C. exostemma as common species. In tropical dry forest across the north central Yucatan, the following important natural forest species were reported: Bursera simaruba, Caesalpinia gaumeri, Gymnopodium ﬂoribundum and Piscidia piscipula (White and Hood 2004), which are also encountered in our study. It was observed that some species recorded in the ﬁrst inventory (1994) were missing in the subsequent inventory (2000) while new species were encountered in the second inventory. Given the large number of species with 1 or 2 individuals, [459]

1520 unknown carvings ornamental timber fruits construction fodder firewood live fence Charcoal

0

10

20

30

40

50

No. species unknown carvings ornamental timber fruits construction fodder firewood live fence Charcoal

1994 2000

Deciduous 0

50

100

150

200

250

300

Abundance (individuals/2ha) 1994 2000

Gallery 0

20

40

60

80

unknown carvings ornamental timber fruits construction fodder firewood live fence Charcoal

100 120 140 160

Abundance (individuals/2ha) Figure 3. Local uses of tree species and their abundance in dry deciduous and gallery forests in Chacocente, Nicaragua.

[460]

1521 Table 7. Diversity measures for trees ‡10 cm dbh in the dry deciduous and gallery forests inventoried in 1994 and 2000 on 2 ha plots. Diversity Measures

Deciduous

Gallery

1994

1994

2000

2000

No. of individuals recorded in 2 ha plots 902 979 597 566 Total number of species recorded 59 59 55 58 Rate of species increase per individual enumerated (S/N) 0.065 0.060 0.092 0.102 Margalef ’s index of species richness (DMg = (S 1)/ln N) 8.52 8.42 8.45 8.99 Shannon’s measure of evenness (J¢ = H¢/lnP S) 1.16 1.15 1.17 1.10 Shannon–Wiener’s diversity index (H¢ = pi log2pi) 4.71 4.69 4.69 4.48 The reciprocal of Simpson’s index (1/D) 17.1 16.9 14.6 14.5 Fisher’s index of diversity (a = N(1 x)/x) 14.1 13.8 14.8 16.2

Table 8. List of threatened species and suggested candidate species for future IUCN listing. Species

Status

Bombacopsis quinata Cedrela odorata Dalbergia retusa Maclura tinctoria Swietenia humilis Esenbeckia litoralis Guaiacum sanctum Lonchocarpus minimiﬂorus Lonchocarpus phlebophyllus Platymiscium pleiostachyum Zanthoxylum belizense Albizia caribaea Celtis caudate Diospyros nicaraguensis Hymenaea courbaril Jacquinia aurantiaca Manilkara achras Phyllostylon brasiliense

Vulnerable Vulnerable Vulnerable Vulnerable Vulnerable Endangered Endangered Endangered Endangered Endangered Endangered Candidate Candidate Candidate Candidate Candidate Candidate Candidate

illegal cutting might have caused the disappearance of this species. However, the plausible explanation for the appearance of species in the second inventory could be ascribed to the transition from seedling class in the 1994 inventory to higher class (trees ‡ 10 cm dbh) in the subsequent inventory. Tree species richness is diﬃcult to compare for diﬀerent sample sizes and geographical variation (Murphy and Lugo 1995). Dry forest at Palo Verde on the Paciﬁc side of Costa Rica had approximately 52 tree species per hectare (Murphy and Lugo 1995). Lower values have been found in the drier areas and particularly in insular forests, such as in Southwestern Puerto Rico near Guanica where 30–50 tree species per hectare were found. Gentry (1995) reported an average of 65 tree species per ha in 23 Neotropical dry forests, which [461]

1522 is considerably higher than the number of species found in the deciduous forest of Chacocente. However, Gentry’s data set included individuals with dbh ‡2.5 cm. In addition, dry forests of Chacocente have a history of severe selective logging which may be the main factor causing the low number of species in this forest. Gillespie and Jaﬀre´ (2003) compared species richness in seven diﬀerent countries using 1000 m2 area and found that species richness is high in Chamela-Mexico (89), Quiapaca (86) and Chaquimayo-Bolivia (79). The lower species richness was found in Mudumalai (India) with 15 species. The number of species for trees ‡10 cm dbh ranged from 3 to 28 species with a mean value of 16 species per hectare in the Vindhyan dry tropical forest of India (Sagar and Singh 2005). As a whole, the total number of species recorded in the present is comparable with other tropical dry forests. With regard to stem density and basal area, our result lies with the range of values reported earlier for other tropical dry forests, and in some cases comparably higher. For example, Sabogal and Valerio (1998) reported 389 trees/ha with a basal area of 14.48 m2/ha in the Chacocente dry deciduous forest, Rundel and Boonpragob (1995) reported 20–88 trees/ha and a basal area ranging from 7 to 42 m2/ha for tropical dry forest in Thailand. For tropical dry forest at the north central Yucatan, White and Hood (2004) documented the basal area in two sites as 20.7 m2/ha and 28.4 m2/ha. Gillespie and Jaﬀre´ (2003) inventoried two tropical dry forests of New Caledonia and found the following basal area per hectare for each site: Ouen-Toro 32.7 m2/ha and Pindai 32.3 m2/ ha. Gillespie and Jaﬀre´ (2003) also pointed out that tropical dry forests in the Neotropics have greater structural similarity. In the present study, the similarity in species composition and abundance between dry deciduous and gallery forests was low. The stem density was much higher in the dry deciduous forest while the basal area was much greater for the gallery forest. This could be related to better soil moisture condition in the latter than the former, as moisture is the major environmental factor limiting tree growth in dry areas. A variety of diversity measures were computed to describe the heterogeneity of the two forest communities, and it was Simpson’s index and Fisher’s a that consistently diﬀerentiated the two communities. According to Simpson’s dominance index the dry deciduous forest is more diverse than the gallery forest. This could be related to the relatively large number of abundant species in the deciduous forest than the gallery forest (cf. 7 species in dry deciduous and 4 species in gallery forests with abundance >24 individuals/ha). In 1994 and 2000 inventories of the dry deciduous forest, Gyrocarpus americanus, Lonchocarpus minimiﬂorus, Stemmadenia obovata, Tabebuia ochracea and Caesalpinia exostemma represented 49% and 42% of the total individuals per hectare, respectively. While Trichilia hirta, Capparis pachaca, Thouinidium decandrum and Stemmadenia obovata represented 44% and 45% of the total individuals per hectare found in the gallery forest during 1994 and 2000 inventories, respectively. Fisher’s diversity index showed that the gallery forest is more diverse than the dry deciduous forest. One implication of this ﬁnding would be the majority of the [462]

1523 species inventoried have irregular and clumped spatial distribution in the deciduous forests, and therefore the gallery forest is characterized by high alpha diversity. The Shannon–Wiener diversity index is usually found to fall between 1.5 and 3.5 and only rarely surpasses 5.0 (Magurran 2004). The values of Shannon–Wiener index for the deciduous and gallery forests falls within the expected range. Gentry (1988) reported values of Shannon–Wiener diversity index for two sites of 0.1 ha in Nicaragua; Cerro Olumo with 5.80 and Cerro El Picacho with 5.22 (Clould forests). These values are higher than the present study; however, the precipitation and altitude of these sites are higher than Chacocente. Hence, the larger diversity of these sites may be due to higher precipitation and low temperature favoring growth and survival of more species. Almost 50% of Nicaragua’s population lives around tropical dry forest and in spite of the partial protection of Chacocente, human pressure on the remaining forests are obvious. The result from the present study provides evidence that the abundance of species used for ﬁrewood and timber declined from 1994 to 2000 in both forest communities. For example Cordia alliodora, though very common elsewhere in Nicaragua; was one of the rarest species in Chacocente. Even the abundance of the ‘‘not used’’ species in the deciduous forest showed a decreasing tendency, indicating an on-going disturbance (anthropogenic and natural) in the forest reserve and loose protection of the forest reserve. It is also important to note that species with high commercial values, such as Swietenia humilis, Cedrela odorata, Dalbergia retusa and Guaiacum sanctum were among the rarest species in our study. Illegal logging of commercially valuable species is still a common problem in the whole country. Apparently, the continuing loss of biodiversity is attributed to mainly deforestation, as in the case of many tropical dry forests (Thiollay 2002). If this anthropogenic disturbance is not curved as early as possible, the tree species, particularly commercial species that appear almost absent in the forest, will become locally extinct (e.g., Bombacopsis quinata). As both forest communities are characterized by many species with few individuals, active management, such as reintroduction of threatened species (Table 8) on private and community lands is highly desirable to maintain viable populations. Simultaneously, an immediate action should be taken to assist the natural regeneration process to restore species diversity of the remaining relics of tropical dry forest in the country. We further recommend a detailed assessment of the suggested candidate species for IUCN listing to determine their conservation status.

Acknowledgements We thank Claudio Calero for his support during the ﬁeldwork. Also he made a great contribution with his knowledge about species uses. Thanks also to Ali Water and Alvaro Noguera for their help during the ﬁeldwork. The Ministry of Natural Resources and Environment kindly allowed us to carry out this research at Chacocente National Wildlife Refuge. The study was ﬁnanced by [463]

1524 the Swedish International Development Cooperation Agency (UNA-SLU PhD Program). Finally, the anonymous reviewer is highly appreciated for the valuable and constructive comments.

Appendix Appendix. List of tree species ‡10 cm dbh recorded in 1994 and 2000 inventories in dry deciduous and gallery forests in Chacocente Wildlife Refuge, Nicaragua together with their uses (CH – charcoal; LF – live fence; FW – ﬁre wood; FOD – fodder; RC – rural construction; FRU – fruit; W – timber; P – pole; O – ornamental; HC – handicrafts and carvings). Species

Acacia costaricensis Achatocarpus nigricans Adelia barbinervis Albizia caribaea Allophylus psilospermus Annona reticulata Ardisia revolute Astronium graveolens Bixa orellana Brosimum alicastrum Bunchosia cornifolia Bursera simaruba Caesalpinia coriaria Caesalpinia exostemma Caesalpinia violacea Calycophyllum candidissimum Capparis odoratissima Capparis pachaca Casearia corymbosa Casearia tremula Cecropia peltata Cedrela odorata Ceiba pentandra Celtis caudata Chomelia spinosa Coccoloba caracasana Coccoloba ﬂoribunda Coccoloba sp. Cordia alliodora Cordia collococca Cordia dentata Cordia gerascanthus Coursetia elliptica Croton niveus Dalbergia retusa

Family

Mimosoideae Achatocarpaceae Euphorbiaceae Mimosoideae Sapindaceae Annonaceae Myrsinaceae Anacardiaceae Bixaceae Moraceae Malpighiaceae Burseraceae Caesalpinoideae Caesalpinoideae Caesalpinoideae Rubiaceae Capparidaceae Capparidaceae Flacourtaceae Flacourtaceae Cecropiaceae Meliaceae Bombacaceae Ulmaceae Rubiaceae Polygonaceae Polygonaceae Polygonaceae Boraginaceae Boraginaceae Boraginaceae Boraginaceae Papilionoideae Euphorbiaceae Papilionoideae

[464]

Deciduous

Gallery

1994

1994

* *

*

2000

*

* * * * * * * *

* * * * * * * * * *

* *

*

*

* * * * *

* * * * *

*

*

*

* *

*

*

* * *

*

*

* * * * *

* * * *

* * * *

2000

* *

*

* *

* * * * *

*

*

Uses

* * * *

* * * * * * *

*

*

FW, CH FW, RC NO FW, P, CH FW, CH, RC FRU NO P, W NO W, FW, CH, HC FW, RC, CH LF, P FW NO FW, LF, CH FW, CH, O FW NO FW FW NO W, FW, HC W NO NO NO NO FW P, HC, W CH, HC, W P, LF CH, HC, W NO FW FW, W, FOD

1525 Appendix. Continued Species

Family

Diospyros nicaraguensis Erythroxylum havanense Esenbeckia litoralis Ficus obtusifolia Gliricidia sepium Guaiacum sanctum

Ebenaceae Erythroxylaceae Rutaceae Moraceae Papilionoideae Zigophyllaceae

Guarea glabra Guazuma ulmifolia Gyrocarpus americanus Haematoxylon brasiletto Hippocratea rovirosae Hymenaea courbaril Inga sp. Jacquinia aurantiaca Karwinskia calderonii Licania arborea Lonchocarpus minimiﬂorus Lonchocarpus phlebophyllus Lonchocarpus sp Luehea candida Luehea seemannii Lysiloma divaricatum Lysiloma sp Machaerium biovulatum Maclura tinctoria Manilkara achras Malpighia stevensii Myrospermum frutescens Pithecellobium dulce Pithecellobium saman Phyllostylon brasiliense Piper aduncum Pisonia macranthocarpa Platymiscium pleiostachyum Pterocarpus rohrii Randia armata Randia cookii Randia nicaraguensis Sapranthus nicaraguensis Senna atomaria Simarouba glauca Spondias purpurea Spondias sp. Stemmadenia obovata Sterculia apetala Swietenia humilis

Meliaceae Sterculiaceae Hernandiaceae Caesalpinoideae Hippocrataceae Caesalpinoideae Mimosoideae Theophrastaceae Rhamnaceae Chrysobalanaceae Papilionoideae Papilionoideae Papilionoideae Tiliaceae Tiliaceae Mimosoideae Mimosoideae Papilionoideae Moraceae Sapotaceae Malpighiaceae Papilionoideae Mimosoideae Mimosoideae Ulmaceae Piperaceae Nyctaginaceae Papilionoideae Papilionoideae Rubiaceae Rubiaceae Rubiaceae Annonaceae Caesalpinoideae Simaroubaceae Anacardiaceae Anacardiaceae Apocynaceae Sterculiaceae Meliaceae

Deciduous

Gallery

1994

2000

1994

* * * * *

* * *

* * * *

* *

* *

* * * *

* * * *

* * *

* * * * *

*

*

*

*

* * *

* * *

* *

* *

*

* *

*

* *

* *

* *

* * *

*

* *

* * *

*

*

* *

* *

*

*

* *

* *

*

*

*

*

*

*

[465]

2000

*

* * * *

Uses

* *

*

*

*

* * * * * * * *

* * * * * * *

FW, RC FW FW O FW, FOD, W P, HC, W CH, P, HC, W FW, CH, FOD NO FW W, RC HC, W FW W, RC W, HC FW, FOD, W FW, CH, W NO RC, W FW, CH, P, W FW, CH, RC FW, CH, RC FW FW, CH, P, W FW, P, W FW, LF W, RC FW, CH FW, FOD, HC, W FW, CH NO NO FW FW, LF, W FW FW FW NO FW, CH W, CH NO NO FW FW W, CH, HC

1526 Appendix. Continued Species

Tabebuia ochracea Tabebuia rosea Terminalia oblonga Tetrorchidium rotundatum Thouinidium decandrum Trema micrantha Trichilia hirta Trichilia moschata Triplaris melaenodendron Ximenia americana Zanthoxylum belizense Zanthoxylum caribaeum Ziziphus guatemalensis Zuelania guidonia

Family

Bignonaceae Bignonaceae Combretaceae Euphorbiaceae Sapindaceae Ulmaceae Meliaceae Meliaceae Polygonaceae Olacaceae Rutaceae Rutaceae Rhamnaceae Flacourtiaceae

Deciduous

Gallery

1994

2000

1994

2000

*

*

* * * *

* * * * *

* * * * * *

* * * * * *

*

* *

* *

*

*

*

* * *

* * *

Uses

FW, LF, W FW, LF, W FW, HC, W NO FW, CH, HC FW, CH, P W, FW P, W P, LF NO W, RC NO W, FW, P NO

References Anonymous 2002. Plan de manejo del refugio de vida silvestre Rı´ o Escalante- Chacocente. Ministerio de Recursos Naturales y del Ambiente. Ramboll/Posaf. Managua, Nicaragua. Duque A. and Cavelier J. 2003. Strategies of tree occupation at a local scale in terra ﬁrme forests in the Colombian Amazon. Biotropica 35: 20–27. Gentry A.H. 1988. Changes in plant community diversity and ﬂoristic composition on environmental and geographical gradients. Ann. Missouri Bot. Garden 75: 1–34. Gentry A.H. 1995. Diversity and ﬂoristic composition of Neotropical dry forest. In: Bullock S.H., Mooney H.A. and Medina E (eds), Seasonally Dry Tropical Forests. Cambridge University Press, Cambridge, UK, pp. 9–34. Gerhardt K. 1994. Seedling Development of Four Tree Species in Secondary Tropical Dry Forest in Guanacaste, Costa Rica. PhD thesis, Uppsala, Sweden. Gillespie T.W., Grijalva A. and Farris C.N. 2000. Diversity, composition, and structure of tropical dry forests in Central America. Plant Ecol. 147: 37–47. Gillespie T.W. and Jaﬀre´ T. 2003. Tropical dry forests in New Caledonia. Biodiv. Conserv. 12: 1687–1697. Harcourt C.S. and Sayer J.A. 1996. The Conservation Atlas of Tropical Forest. The Americas, Simon & Schuster. IUCN. 2004. 2004 IUCN Red List of Threatened Species. www.iucnredlist.org. Downloaded on 14 December 2004. International Union for Conservation of Nature and Natural Resources, Cambridge, UK. Janzen D. 1988. Management of habitat fragments in a tropical dry forest: growth. Ann. Missouri Bot. Garden 75: 105–116. Krebs C.J. 1999. Ecology Methodology. 2nd ed. Addison-Wesley Educational Publishers. Inc. Lamprecht H. 1989. Silviculture in the Tropics: Tropical Forest Ecosystems and their Tree Species. GTZ, Eschborn. Magurran A.E. 2004. Measuring Biological Diversity. Blackwell Publishing, Malden, Oxford and Victoria. Murphy P.G. and Lugo A.E. 1986. Ecology of tropical dry forest. Ann. Rev. Ecol. Syst. 17: 67–88.

[466]

1527 Murphy P.G and Lugo A.E. 1995. Dry forest of Central America and the Caribbean. In: Bullock S.H., Mooney H.A and Medina E (eds), Seasonally Dry Tropical Forests. Cambridge University Press, Cambridge, England, pp. 9–34. Roldan H. 2001. Recursos forestales y cambio en el uso de la tierra, Republica de Nicaragua. Santiago, Chile. Rundel P.W. and Boonpragob K. 1995. Dry forest of Central America and the Caribbean. In: Bullock S.H., Mooney H.A. and Medina E (eds), Seasonally Dry Tropical Forests. Cambridge University Press, Cambridge, England, pp. 93–119. Sabogal C. 1992. Regeneracio´n de bosques secos naturales en Centro Ame´rica, con ejemplos de Nicaragua. J. Veget. Sci. 3: 407–416. Sabogal C. and Valerio L. 1998. Forest Composition, Structure and Regeneration in a dry forest of the Nicaraguan Paciﬁc Coast. In: Dallmeier F and Comiskey J.A. (eds), Forest Biodiversity in North Central and South America, and the Caribbean: Research and Monitoring. Man and The Biosphere Series, Vol. 21. UNESCO, New York pp.187–212. Sagar R. and Singh J.S. 2005. Structure, diversity, and regeneration of tropical dry deciduous forest of northern India. Biodiv. Conserv. 14: 935–959. Salas J.B. 1993. Arboles de Nicaragua. Instituto Nicaragu¨ense de Recursos Naturales y del Ambiente. Servicio Forestal Nacional., Managua, Nicaragua. Segura O., Kaimowitz D. and Rodrı´ guez J. 1997. Polı´ ticas forestales en Centro Ame´rica: Ana´lisis de las restricciones para el desarrollo del sector forestal. IICA-Holanda/LADERAS. Stevens W.D., Ulloa C.U., Pool A. and Montiel O.M. 2001. Flora de Nicaragua. Missouri Botanical Garden Press. Tercero M.G. and Urrutia G.S. 1994. Caracterizacio´n ﬂorı´ stica y estructural del bosque de galerı´ a en Chacocente, Carazo, Nicaragua. Trabajo de diploma. Universidad Nacional Agraria, Managua, Nicaragua. Thiollay J.M. 2002. Forest ecosystems: threats, sustainable use and biodiversity conservation. Biodiv. Conserv. 11: 943–946. White D.A. and Hood C.S. 2004. Vegetation patterns and environmental gradients in tropical dry forests of the northern Yucata´n Peninsula. J. Veget. Sci. 15: 151–160.

[467]

Biodiversity and Conservation (2006) 15:1529–1543 DOI 10.1007/s10531-004-6678-1

Springer 2006

Identifying conservation priority zones for eﬀective management of tropical forests in Eastern Ghats of India B. BALAGURU1, S. JOHN BRITTO, S.J.2,*, N. NAGAMURUGAN3, D. NATARAJAN4 and S. SOOSAIRAJ5 1

Department of Botany, Jamal Mohamed College, Tiruchirappalli 620 020, Tamil Nadu, India; Rapinat Herbarium, St. Joseph’s College (Autonomous), Tiruchirappalli 620 002, Tamil Nadu, India; 3Department of Biotechnology, Kurinji College of Arts and Science, Tiruchirappalli 620 024, Tamil Nadu, India; 4Department of Microbiology, Kandaswami Kandar’s College, P. velur Namakkal 638 182, Tamil Nadu, India; 5Department of Botany, St. Joseph’s College (Autonomous), Tiruchirappalli 620 002, Tamil Nadu, India; *Author for correspondence (e-mail: sjcbritto@rediﬀmail.com; phone: +91-431-2721-304; fax: +91-431-2701-501) 2

Received 3 December 2003; accepted in revised form 2 November 2004

Key words: Conservation priority zones, Eastern Ghats, Endemism, Geographical information system, Red listed plants, Shervarayan hills, Tropical forest Abstract. There are thousands of protected forest areas existing on earth, yet the deforestation rate continues unabated both inside and outside the protected areas especially in the tropical forests. It identiﬁes the less eﬀectiveness of the current conservation strategies, which is normally oriented around the forest area cover rather than the quality of the protected areas. This calls for realistic and eﬀective management strategies for forests. Based on the drawbacks the present study aims at identifying conservation priority sites within the protected areas (Reserved Forests) of Shervarayan hills, Eastern Ghats of Tamil Nadu, India. The remnant forest patches having less eﬀective management/protection is identiﬁed and analysed for its qualitative contribution to the ecosystem. Quadrats of 20 · 20 m were laid in diﬀerent vegetation based on the percentage of forest cover and assess the species diversity pertaining the richness, Endemism and Red list categories. Thematic layers (maps) such as vegetation type, ﬂoristic species richness, ﬂoristic endemism, and red list ﬂora are created and categorized according to their weightage classes and overlaid in GIS domain to demarcate the Conservation Priority Zones (CPZ). The CPZ are classiﬁed according to the priority status i.e., high, moderate and low based on the contributing species richness, levels of endemism and concentration of Red listed plants.

Introduction The present global biodiversity is diminishing at an accelerated pace (Myers 1980; Wilson 1988) especially in the tropical countries (Hamilton 1984; Bowles et al. 1998; Malcolm and Ray 2000) where the biodiversity is concentrated. The current status of our forest resources has called for conservation planning (Mooney and Chapin 1994; Western and Wright 1994; Calridge and O’Callaghan 1997; O‘Neill et al. 1997; Bawa and Seidler 1998) which seeks to identify spatial options for the preservation of biodiversity (Williams et al. 1996). The ultimate purpose of conservation is to inform and aﬀect the [469]

1530 conservation policy (Robertson and Hull 2001). Within the realm of conservation measures, the forest strategists have identiﬁed and conserved large tracts of vegetation as protected areas (Gaston et al. 2002; Margules et al. 2002). Still the deforestation rate has markedly increased (Downton 1995) and has spread to the protected areas of tropical region too (Hamilton 1984; Howard 1991; Redford 1992) rendering ineﬀectiveness in arresting it. Ecologists nowadays are on the consensus that biological diversity is not eﬀectively conserved by reserves alone (Wilcove 1989). Various quantitative methods that allow relatively expeditious identiﬁcation of conservation-priority areas have been proposed in recent years and these approaches include identiﬁcation of hotspots of biodiversity (Myers 1988, 1990; Dobson et al. 1997), rapid biodiversity assessment (Oliver and Beattie, 1993 and 1996), identiﬁcation of indicator and surrogate species (Curnutt et al. 1994), development or rarity and complementary sets (Williams et al. 1996), identiﬁcation of key eco-region (Olson and Dinerstein 1998), and cost-minimizing or land-values analyses (Ando et al. 1998). This may be due to the very size of the forest tract whereby the porosity of the protected forest will lead to its ineﬀective management. Now, it is better to identify the quality of the vegetation in the protected and non protected areas, rather than the area size for eﬀective conservation management (Sheil 2001). Most often we had adopted the conventional approach to maintain biological diversity by following a protocol based on species by species and threat-bythreat approach, but it too has its own detriments i.e., the ﬁnancial drawbacks, inaccurate complicated database of the forest community (Hutto et al. 1987; Scott et al. 1987, 1991; Margules 1989, Noss 1991) etc. In recent years the focus for conservation has shifted from single species management approach to protection of biodiversity in the aggregate i.e., to maintain the native plant species in extensive natural landscapes (habitats) restricting to a minimal size factor, that are suﬃciently linked (i.e. corridors) to allow interaction and genetic interchange among distinct populations (Noss 1983). This approach requires a cohesive and representative system of areas to be managed for the maintenance of biodiversity. Hence there is a need to prioritize only those areas, which are considered most essential for conservation, which are termed as biodiversity priority areas (Olson and Dinerstein 1998). The procedures involve scoring and ranking, which make priority setting more systematic and explicit (Margules et al. 2002). Prioritization of strategies is essential to ensure that eﬀorts at conservation yield best possible results and undesirable side eﬀects, such as the alienation and impoverishment of local communities can be avoided (Singh and Taneja 2000). Prioritization of sites for conservation also needs to be done with reference to the (often least studied) vegetation type (Williams et al. 2002), species richness (Terborgh and Winter 1983; Scott et al. 1987), endemism based on Kier and Barthlott (2001) and concentration of red listed plants (Ahmedullah 2000; Kumar et al. 2000). The methods for identifying priority areas vary with the entity selected for the overall biological conservation planning and management (Margules et al. 2002; Gaston et al. 2002) and for example Ramesh et al. (1997) have suggested [470]

1531 conservation priority based on the biodiversity gaps by considering the vegetation uniqueness, species richness, endemic ﬂora and endemic fauna in Western Ghats, whereas on the other hand Menon et al. (2001) and Amarnath et al. (2003) have identiﬁed conservation priority zones based on the land use changes, vegetation patch characteristics, phytosociological data, topographic, bioclimatic and disturbance level in wet evergreen forests of Western Ghats in Tamil Nadu. Thus the present study has deviated from the approaches described above and have considered a new concept with the vegetation type, species richness, endemic and IUCN red listed plants as base for identifying Conservation Priority Zones (CPZ) in GIS (Geographical Information System) domain.

Study area The Shervarayan hills (a part of Eastern Ghats) are located in the northern part of Salem city, Tamil Nadu, South India and with an area of 469.9 km2. The study area lies between latitudes 1143¢00¢¢ to 1200¢00¢¢ N and longitudes of 7800¢00¢¢ to 7822¢30¢¢ E (Map 1) and falls in the Survey of India toposheets (SOI) 581/1, 2, 5 and 6 (i.e., 1: 50,000 scales). The mean annual rainfall at the upper hill reaches is 1638 mm and 850 mm at the foothills. The temperature

Map 1.

Study area. [471]

1532 ranges from 13–29C on the hill plateau to 25C and 40C at the foothills. The soil is red loamy and lateritic. The area is made up of Archaean crystalline rock like amphibolites, leptinites, garnetiferous granites and charnockites. Bauxite and Magnesite are the chief mineral resources in the Shervarayan hills. There are 71 villages, which are administrated by two taluks (political unit equivalent of an English county) i.e., Yercaud and Omalur. Most of the hill plateau is in private ownership, which includes coﬀee estates, villages and their agricultural lands. Colonial planters had been maintaining and harvesting the coﬀee estates till the time of independence of the country and later, the ownership has been entrusted to the natives. There are 45 reserved forests, which are administered by the Salem Forest Division. Almost all the reserved forest area is on the outer slopes of the hill tract facing the human habitats on the fringing foothills thereby enhancing the proneness to deforestation and very much is the evident fact.

Methodology Mapping vegetation type Vegetation type map of Shervarayan hills (Balaguru et al. 2003) is used which covers nearly half (49.50%) of the hill area (23260.76 ha) under reserved forests comprising about six major forest types - evergreen (111.33 ha), semi evergreen (1057.67 ha), riparian (1145.15 ha), dry mixed deciduous (10179.10 ha), southern thorn scrub (10735.70 ha), and evergreen scrub (31.81 ha), respectively (Map 1). To evolve potential conservation priority elements, the virgin and primary forest patches comprising the evergreen, semi evergreen, riparian, and dry mixed deciduous forests are used as the base, while the evergreen scrub and southern thorn scrub forests are excluded due to their highly degraded nature. The scores for each forest type are attributed according to the species concentration (Figure 1) and substituted to all the representing polygons accordingly.

Mapping ﬂoristic richness Representative polygons for each forest type are analysed for assessing species richness contribution by adopting quadrat method (20 · 20 m) (CES 1998; Ferreira and Prance 1998). This study has taken optimum sampling quadrats to cover all variations within each type of the vegetation and the number of quadrats for each forest type is based on the area percentage of the forest cover (>1000 ha area 0.5%; 1000–2000 (0.5%) and >2000 (0.01%). All living plant species within the quadrat are identiﬁed and the number of species in each forest type is summed and represented by species richness values and these [472]

1533

Figure 1. Conceptual diagram illustrating the building identiﬁcation of conservation priority zone.

values are attributed or extrapolated to all such polygons representing the respective forest type. To produce the species richness maps the ensuing polygons are regrouped and classiﬁed into categories of low, medium and high according to the ranges of species richness values.

Mapping ﬂoristic endemism The plant species thus collected in the quadrats are identiﬁed with the endemic ﬂora of Peninsular India as enlisted by Ahmedullah and Nayer (1986). Procedures for deciding on CPZ need more systematic and explicit approach for priority setting wherein multiple criteria are given scores. These scores are then combined and ranked accordingly and priority (high, moderate or low) is given to those areas (Margules et al. 2002). The number of endemic species are allocated to the respective scores/classes based on their signiﬁcant status in [473]

1534 Indian context (Roy 1999; Ajith Kumar et al. 2000) i.e. individual species endemic to India is considered as ‘Indian Endemic’ in distribution, hence they received low score (1), similarly individual species endemic to peninsular India is considered as ‘Regional Endemic’ (2) and species endemic to Eastern Ghats (including Shervarayan hills) is ‘Local Endemic’ and received the highest score (3). The number of species and their scores in each of the polygon is then summed up and values attributed as described for species richness. To produce endemic species map, the polygons are ﬁnally regrouped/reclassiﬁed into low, medium and high degree of endemism according to the summed values attributed to each polygon (see Figure 1), the polygon with the highest score had the high degree of endemism and likewise.

Mapping ﬂoristic red listed plants The methodology to map red listed plants is the same as for the endemic plants map or species richness map. The ensuing plant species in the quadrats are evaluated based on version 3.1; IUCN/SSC (1999) criteria and cross checked with Indian Red Data books (Nayer and Sastry 1987–1990) and other relevant literature Kumaravelu and Chaudhuri 1999). The red listed categories and their scores are classiﬁed into (a) Critically Endangered (CE) 5; (b) Endangered (En) 4; (c) Vulnerable (VU) 3; (d) Lower risk (LR)/Least Concern (Lc) 2; (e) Data Deﬁcient (DD) 1 (Table 2). To produce the red listed plant species map, the polygons are ﬁnally grouped into low, medium and high wherein the scoring is similar to the one adopted for the endemic classiﬁcation.

Modelling conservation priority zone (CPZ) The components of various units (classes) from the thematic maps like the vegetation type, ﬂoristic richness, endemism and red lists with their respective weightages (Figure 1) are essential to develop conservation priority zones for this study. Considering the conservational importance and status for each class (unit) of the respective thematic maps, the classes are given weightages to designate and identify the CPZ. Overlay or superimposition creates a composite output GIS ﬁle by combining a number of input GIS ﬁles based on the minimum or maximum values of the input ﬁles (Murthy 2000). To prepare the CPZ map, the respective thematic maps (species richness map, red list map and ﬁnally endemism map) are overlaid on the vegetation type map, which comprised the lowermost tier (the base map) using a remote sensing and GIS software (ERDAS imagine). The model maker (a tool in the ERDAS software) is used to analyse the overlays, wherein the diﬀerent features of the thematic layers are intersected/extracted and new class values are attributed to the resulting polygons. The polygons are classiﬁed according to the conservation priority status and ﬁnally integrated (union criteria in model maker) to generate [474]

1535 the CPZ. The authenticity of the areas/zones proposed for conservation priority is conﬁrmed with ground truthing.

Results Totally 322 species are recorded from the Shervarayan hills (based on the quadrats studied in the study area), of which 24 species are endemic (Table 1) and 23 species are red listed (Table 2). The ﬂoristic richness (Map 2) are regrouped/reclassed into high (>80 species), medium (40–80 species) and low (>40 species) rich areas respectively. The endemism and red listed species are grouped into three zones based on the number of contributing species. The CPZ map (Map 3) is generated with three classes according to the criteria described before, based on the combination of scores – high, moderate and low priority zones.

High priority zone High priority zone is distributed in ﬁve sites with moderate to high species richness. This zone accounts for 1582.53 ha (6.80%) of the total hill forest area. The priority sites are authenticated with the presence of select/target species (under diﬀerent criteria) like Rubia cordifolia, Crotalaria shevaroyensis, Litsea oleoides, Smilax zeylanica, Ixora notoniana, Neolitsea scrobiculata, Psychotria octosulcata, Randia candolleana var. candolleana, Peperomia dindigulensis, Celastrus paniculatus and Nothopegia colebrookiana in the evergreen forests. The riparian forests comprise Terminalia arjuna, Mangifera indica, Ficus microcarpa and Syzygium cumini and on the other hand the semi evergreen forests is represented mainly by Nothopegia colebrookiana, Celastrus paniculatus, Decalepis hamiltonii, Santalum album, Naravelia zeylanica, Gymnema sylvestre,

Table 1. Endemic plant species and their distribution status. Distribution

Species Name

Local Endemic (endemic to Eastern Ghats) Regional Endemic (endemic to Peninsular India)

Crotalaria shevaroyensis

Indian Endemic (endemic to India)

Peperomia dindigulensis, Vaccinium neilgherrense Miliusa eriocarpa, Litsea oleoides, Neolitsea scrobiculata, Curcuma neilgherrensis, Eranthemum capense, Dolichandrone arcuata, Neonotonia wightii, Elaeagnus indica, Decalepis hamiltonii, Jasminum trichotomum, Ixora notoniana, Pavetta blanda, Psychotria octosulcata, Randia candolleana var. candolleana, Wendlandia angustifolia, Mallotus stenanthus, Tetrastigma sulcatum, Pamburus missionis, Leucas diﬀusa, Shorea roxburghii, Chionanthus mala-elengi.

[475]

1536 Table 2. Red listed plant species and their status. Species Name

Red listed categories

Buchanania lanzan Celastrus paniculatus Cycas circinalis Decalepis hamiltonii Gloriosa superba Nothopegia colebrookiana Pseudarthria viscida Santalum album Sapindus emarginata Smilax zeylanica Terminalia arjuna Gardenia gummifera Michelia champaca Symplocos cochinchinensis Rubia cordifolia Gnetum edule Naravelia zeylanica Hemidesmus indica Withania somnifera Stephnia japonica Evolvulus alsinoides Gymnema sylvestre Vernonia arborea Polystachya concreta

Lower risk Vulnerable Threatened Endangered Lower risk Data Deﬁcient Lower risk Endangered Lower risk/Least concerned Vulnerable Lower risk Endangered Vulnerable Lower risk Critically endangered Endangered Vulnerable Vulnerable Vulnerable Vulnerable Lower risk Vulnerable Endangered Endangered

Ixora notoniana, Pseudarthria viscida, Buchanania lanzan, Hemidesmus indicus and Sapindus emarginata. The above described forests also are characterized with the occasional presence of some priority species like Withania somnifera, Hemidesmus indicus, Celastrus paniculatus, Cycas circinalis and Symplocos cochinchinensis with endemic constraints.

Moderate priority zone The zone occupies an area of about 6282.4 ha (27%) enclosing parts of evergreen forests and dry mixed deciduous forests with species richness ranging from moderate to low. The evergreen forest under this class includes the endemic and red listed species like Symplocos cochinchinensis, Vaccinium neilgherrense, Gnetum edule, Rubia cordifolia, Peperomia dindigulensis, Elaeagnus indica and Curcuma neilgherrensis. The endemic and IUCN red listed plant species in the dry mixed deciduous forests has both moderate and high richness and the representing species are Withania somnifera, Naravelia zeylanica, Dolichandrone arcuata, Hemidesmus indicus, Sapindus emarginatus, [476]

1537

Map 2. Species richness map of Shervarayan hills.

Pseudarthria viscida, Nothopegia colebrookiana, Pamburus missionis and Evolvulus alsinoides.

Low priority zone This zone with moderate to low species richness occupies an area of about 4524.92 ha (19.45%) of the total forest area and the zone comprises mostly of the dry mixed deciduous types and to a lesser extent the riparian forests. The red listed plant species in dry mixed deciduous forests species are Celastrus paniculatus, Nothopegia colebrookiana, Pseudarthria visida and Hemidesmus indicus and the select endemic species like Mallotus stenanthus, Pamburus missionis, Shorea roxburghii and Pavetta blanda The riparian forest has only one endemic and endangered plant species i.e. Cycas circinalis, [477]

1538

Map 3.

Conservation priority zones.

Discussion Most of the forests on the outer slopes and plateau of Shervarayan hills are still facing the wrath of deforestation in spite of its protected status. There are multidimensional reasons to it and the size of the protected area is the ﬁrst detriment rendering the very base of protection as ineﬀective. Secondly it is followed by easy accessibility to the forest patches by the illegal loggers wherein the dense network of the footpaths crisscrossing the forest patches conﬁrm the same. Thirdly the ineﬀectiveness of the protection status is the poor knowledge of conservation prior sites within the protection realms of the forest. This study also identiﬁes a similarity in species contribution between the evergreen forests of Shervarayan hills (a part of Eastern Ghats) with that of the evergreen forests of Western Ghats. Species like Chionanthus ramiﬂorus, [478]

1539 Ligustrum perrottetii, Olea paniculata, Vaccinium neilgherrense, Viburnum punctatum, Gnetum edule, Elaeocarpus serratus, Syzygium cumini, Memecylon edule, Symplocos cochinchinensis and Litsea deccanensis are common only in Western Ghats, but are present in Shervarayan hills too (a trait unique to this hill when compared to other hills in the Eastern Ghats) (Balaguru 2002). The vegetation types like evergreen, riparian and semi-evergreen are potentially most vulnerable owing to their proximity to the surrounding anthropogenic environment (mining, coﬀee estates and human habitation) and are designated with high conservation value, so as to eﬀectively conserve the remnant forest patches within the realm. These areas as discussed before harbor a number of red listed and endemic species of conservation importance. Some of the evergreen and semi-evergreen forests are inadequately represented on the outer slopes whereas the dry mixed deciduous in the same zone is well represented i.e., rich species diversity. However widespread logging in these areas may deplete (in future) the existing forest cover and add to the deforestation extents. Hence conservation of such areas too is included in conservation priority. The CPZ map thus generated will help to concentrate the protection strategy to the zones thus demarcated and help the forest department to have an eﬀective approach to conserve and maintain the virgin forests – a positive approach which can be adopted elsewhere in similar forests. This study eﬀectively defends the sole purpose of selecting the virgin forests on Shervarayan hills for conservation priority zone and its mapping for eﬀective conservation strategies. The present study identiﬁes itself with similar studies by Menon et al. (2001) wherein it is discussed that the conservation priorities require the conservation value of an area and its vulnerability (proximity to human interference in this case) towards deforestation. Fixing biodiversity priorities (CPZ in this case) are necessary but in themselves are not suﬃcient for the long-term maintenance. Biological diversity requires other tools, and approaches such as sustainable development (Peters et al. 1989; Hartshorn 1995) and management prescriptions to minimize the risk of extinction of local plant population, which have to be focused more sharply in such CPZ. More eﬀective strategy involves people’s participation, while realizing and ensuring their domestic needs (fuel wood, fodder, minor forest produce including the medicinal plants) (Margules et al. 2002). This will enforce a harmonious facet to the whole process leading to the success of the strategy adopted (Serrao and Homma 1993; Dawson 1996). What is required therefore is an appropriate developmental paradigm that can provide a more relevant perception and an interpretative framework from which such conservation strategies may emerge (Upreti 1994). Such planning for the stabilization of natural ecosystem is essential and this will reduce the pressure on the natural forests and prevent further loss of biodiversity and in the longer run will reestablish the lost forest stand. The development plans with Sustainable forest management would enable the eﬀective management of biodiversity in Tropical forests and is eﬀectively adopted in most revised cases for most of the policies and strategies associated with forest. [479]

1540 The potential utility of remote sensing and GIS to identify the CPZ in this study and culmination of all aspects dealing with the sole purpose of conservation has been eﬀective and reliable (based on the ground truth and ﬁeld checks). The resultant maps gives a picture of the CPZ providing a birds eye view of the areas thus identiﬁed. The accessibility to the zones thus identiﬁed can be deciphered and planned, ﬁnally paving way for better and eﬀective conservation.

Conclusion For identifying priority areas, there must be acceptable ways of measuring biological diversity, a way of determining an acceptable level of representation of that diversity in conservation areas. Having set that goal, it is necessary that a cost eﬀective way of allocating limited resources should be a thought of criteria. The methods outlined in this paper have made the most eﬀective use of available ﬁeld data with the remotely derived satellite data and involves innovative scoring and ranking procedure that is developed and improved in this study. As a result, priority setting has been approached systematically and explicit tolerance. Though the conservation priority areas are geared towards the future, the forest departments should advocate an alternate approach to protected area management that would integrate biodiversity conservation with social development. Such an approach would entail an improved understanding of the local pattern of resource use. As a result, the contemplated conservation strategies would beneﬁt the local population to enable security to their local livelihood and the base of conservation.

Acknowledgements The authors are grateful to D. Stoms, California University, Santa Barbara and to Dr. B. R. Ramesh, Director of Research, French Institute, Pondicherry for their expertise and assistance. We would also like to thank the Tamil Nadu forest department and the committed oﬃcers of Salem Forest Division for the permission to carry out study in the Shervarayan hill forests.

References Ahmedullah M. and Nayer M.P. 1986. Endemic plants of the Indian Region (Vol. I) – Peninsular India. Deep printers, New Delhi. Ahmedullah M. 2000. Prioritisation of endangered plants of India. In: Singh S., Sastry A.R.K., Mehta R. and Uppal V. (eds), Setting Biodiversity Priorities for India, vol. 2. World Wide Fund for Nature-India, New Delhi, pp. 442–459.

[480]

1541 Ajith Kumar, Walker S. and Molur S. 2000. Prioritization of Endangered species. In: Singh S., Sastry A.R.K., Mehta R. and Uppal V. (eds), Setting Biodiversity Priorities for India. World Wide Fund for Nature-India, New Delhi, pp. 341–425. Amarnath G., Murthy M.S.R., Britto S.J. and Dutt C.B.S. 2003. Diagnostic analysis of conservation zones using remote sensing and GIS techniques in Wet evergreen forests of the Western Ghats- An ecological hotspot, Tamil Nadu, India. Biodiv. Conserv. 12(12): 2331–2359. Ando A., Camm J., Polasky S. and Solow A. 1998. Species distribution, land values and eﬃcient conservation. Science 279: 2126–2128. Balaguru B., John Britto S., Nagamurugan N., Natarajan D., Soosairaj S., Ravipaul S. and Arockiasamy D.I. 2003. Vegetation mapping and slope characteristics in Shervarayan hills, Eastern Ghats using Remote Sensing and GIS. Current Science 85(5): 645–653. Balaguru B. 2002. Plant Diversity Assessment and its Conservation in Shervarayan Hills Eastern Ghats of Tamil Nadu Using Remote Sensing and Geographical Information System. Ph.D thesis, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India. Bawa K.S. and Seidler R. 1998. Natural forest management and conservation of biodiversity in tropical forests. Conserv. Biol. 12(1): 46–53. Bowles I.A., Rice R.E., Mittermeier R.A. and da Fonseca G.A.B. 1998. Logging and tropical forest conservation. Science 280: 1899–1900. Calridge G. and O’Callaghan B. (eds) 1997. Community Involvement in Wetland Management: Lessons from the Field. Incorporating the proceeding of workshop 3: wetlands, local people, and development, of the international conference on wetlands, Kuala Lumpur, Malaysia, pp. 19–24. CES (Centre for Ecological Sciences) 1998. Monitoring Biodiversity – A manual of methods. IISC, Bangalore. Curnutt J., Lockwood J., Luh H., Nott P. and Russell G. 1994. Hotspots and species diversity. Nature 367: 326–327. Dawson K.J. 1996. Interior and exterior land use as factors in landscape biodiversity from case studies. In: Szaro R.C. and Johnston D.W. (eds), Biodiversity and managed landscapes-Theory and Practice. Oxford University Press, Oxford, pp. 514–530. Dobson A.P., Rodriguez J.P., Roberts W.A. and Wilcove D.S. 1997. Geographic distribution of endangered species in the United States. Science 275: 550–553. Downton M.W. 1995. Measuring tropical deforestation: Development of the methods. Environ. Conserv. 22(3): 229–240. Ferreira L.V. and Prance G.T. 1998. Species richness and ﬂoristic composition in four hectares in the Jau National Park in upland forests in Central Amazonia. Biodiv. Conserv. 7: 1349–1364. Gaston K.J., Pressey R.L. and Margules C.R. 2002. Persistence and vulnerability: retaining biodiversity in the landscape and in protected areas. J. Biosci. 27(4): 361–384. Hamilton A.C. 1984. Deforestation in Uganda. Oxford University Press and The African Wildlife Society, Nairobi, Kenya. Hartshorn G.S. 1995. Ecological basis for sustainable development in tropical forests. Ann. Rev. Ecol. Systemat. 26: 155–175. Howard P.C. 1991. Nature Conservation in Uganda’s Tropical Forest Reserves. Publication 3. Forest Conservation Programme, World Conservation Union, Gland, Switzerland. Hutto R.L., Heel S. and Landres P.B. 1987. A critical evaluation of the species approach to biological conservation. Endangered species Updata 4(11): 1–4. IUCN/SSC criteria Review working group. 1999. IUCN Red list criteria review provisional report; draft of the proposed changes and recommendations. Species 31 & 32: 43–57. Kier G. and Barthlott W. 2001. Measuring and mapping endemism and species richness: a new methodological approach and its application on the ﬂora of Africa. Biodiv. Conserv. 10: 1513– 1529. Kumar A., Walker S. and Molur S. 2000. Prioritisation of endangered species. In: Singh S., Sastry A.R.K., Mehta R. and Uppal V. (eds), Setting Biodiversity Priorities for India. World Wide Fund for Nature – India, New Delhi, pp. 341–386.

[481]

1542 Kumaravelu G. and Chaudhuri K.K. 1999. Proceedings of a National Seminar on Endemic and Endangered Plants and Animal Species of Eastern and Western Ghats. Tamil Nadu Forest Department, Chennai. Malcolm J.R. and Ray J.C. 2000. Inﬂuence of timber extraction routes on central African smallmammal communities, forest structure and tree diversity. Conserv. Biol. 14(6): 1623–1628. Margules C.R. 1989. Introduction to some Australian developments in Conservation evaluation. Biol. Conserv. 50: 1–11. Margules C.R., Pressey P.L. and Williams P.H. 2002. Representing biodiversity: data and procedures for identifying priority areas for conservation. J. Biosci. 27(4): 309–326. Menon S., Gil Pontius J.R.R., Rose J., Khan M.L. and Bawa K.S. 2001. Identifying conservation – Priority areas in the tropics: A land - use change modeling approach. Conserv. Biol. 15(2): 501– 512. Mooney H.A. and Chapin F.S.III 1994. Future directions of global change research in terrestrial ecosystems. Trends Ecol. Evol. 9: 371–372. Murthy K.S.R. 2000. Ground water potential in a semi-arid region of Andhra Pradesh - a geographical information system approach. Int. J. Remote Sensing 21(9): 1867–1884. Myers N. 1980. Conversion of Tropical Moist Forests. National Academy of Science, Washington, DC, USA, pp. 250 (illus). Myers N. 1988. Threatened biotas: ‘‘hotspots’’ in tropical forests. The Environmentalist 8: 1–20. Myers N. 1990. The biodiversity challenge: expanded hotspots analysis. The Environmentalist 10: 243–256. Nayer M.P. and Shastry A.R.K. (eds) 1987–1990. Red Data Book on Indian Plants 1,2,3. BSI, Calcutta. Noss R.F. 1983. A regional landscape approach to maintain diversity. Bioscience 33: 700–706. Noss R.F. 1991. From endangered species to biodiversity. In: Kohm K. (ed), Balancing on the Brink of Extinction the Endangered Species Act and Lessons for the Future. Island Press, Washington, DC, pp. 227–246. O’Neill R.V., Hunsaker C.T., Jones K.B., Ritters K.H., Wickham J.D., Schwartz P.M., Goodman I.A., Jackson B.L. and Bailargeon W.S. 1997. Monitoring environmental quality at the landscape scale. Bioscience 47: 513–519. Oliver I. and Beattie A.J. 1993. A possible method for the rapid assessment of biodiversity. Conserv. Biol. 7: 562–568. Oliver I. and Beattie A.J. 1996. Designing a cost-eﬀective invertebrate survey: a test of methods for rapid assessment of biodiversity. Ecol. Appl. 6: 594–607. Olson D.M. and Dinerstein E. 1998. The global 200: a representation approach to conserving the Earth’s most biodiversity valuable ecoregions. Conserv. Biol. 12: 502–515. Peters C.M., Gentry A.H. and Mendelson R.O. 1989. Valuation of an Amazonian rain forest. Nature 339: 655–656. Ramesh B.R., Menon S. and Bawa K.S. 1997. A vegetation based approach to biodiversity gap analysis in the Agasthyamalai region, Western Ghats, India. Ambio 26(8): 529–536. Redford K.H. 1992. The empty forest. Bioscience 22: 412–422. Robertson D.P. and Hull R.B. 2001. Beyond biology: toward a more public ecology for conservation. Conserv. Biol. 15(4): 970–979. Roy P.S. 1999. Remote sensing application in forestry and environment: retrospective and perspective. In: Proceedings of ISRS National Symposium on Remote Sensing Applications for Natural Resources Retrospective and Perspective. Bangalore, pp. 169–185. Scott J.M., Csuti B., Jacobi J.D. and Estes J.E. 1987. Species richness: a geographic approach to protection future biological diversity. Bioscience 37: 782–788. Scott J.M., Csuti B., Smith K., Estes J.E. and Caicco S. 1991. Gap analysis of species richness and vegetation cover; an integrated biodiversity conservation strategy. In: Kohm K. (ed), Balancing on the Brink of Extinction the Endangered Species Act and Lessons for the Future. Island Press, Washington, DC, pp. 282–297.

[482]

1543 Serrao E.A.S. and Homma A.K.D. 1993. Sustainable Agriculture and the Environment in the Humid Tropics. National Academy Press, Washington, DC, pp. 265–351. Sheil D. 2001. Conservation and Biodiversity monitoring in the Tropics: Realities, Priorities, and distractions. Conserv. Biol. 15(4): 1179–1182. Singh S. and Taneja B. 2000. Prioritisation for biodiversity conservation: values and criteria. In: Singh S., Sastry A.R.K., Mehta R. and Uppal V. (eds), Setting Biodiversity Priorities for India. World Wide Fund for Nature – India, New Delhi, pp. 28–33. Terborgh J. and Winter B. 1983. A method of sitting parks and reserved with species reference to Colombia and Ecuador. Biol. Conserv. 27: 45–58. Upreti G. 1994. Environmental conservation and sustainable development require a new developmental approach. Environ. Conserv. 21(1): 18–29. Western D. and Wright R.M. 1994. Natural Connections: Perspective in Community Based Conservation. Island press, Washington, DC, pp. 581. Wilcove D.S. 1989. Protecting biodiversity in multiple-use lands: Lessons from the U.S. Forest Service. Trends Ecol. Evol. 4: 385–388. Williams P.H., Margules C.R. and Hilbert D.W. 2002. Data requirements and data sources for biodiversity priority area selection. J. Biosci. 27(4): 327–338. Williams P.H., Gibbons D., Margules C.R., Rebelo A., Humphires C. and Pressey R. 1996. A comparison of richness hotspots, rarity hotspots, and complementary areas for conserving diversity of British birds. Conserv. Biol. 10: 155–174. Wilson E.O. (ed) 1988. Biodiversity. National Academy press, Washington, DC.

[483]

Biodiversity and Conservation (2006) 15:1545–1575 DOI 10.1007/s10531-005-2930-6

Springer 2006

Comparison of bird communities in primary vs. young secondary tropical montane cloud forest in Guatemala SWEN C RENNER1,*, MATTHIAS WALTERT2 and MICHAEL MU¨HLENBERG2 1 Conservation and Research Center, Smithsonian Institution, 1500 Remount Road, Front Royal, VA 22630, USA; 2Centre for Nature Conservation, Georg-August University of Go¨ttingen, Von-SieboldStraße 2, 37075 Go¨ttingen, Germany; *Author for correspondence (e-mail: [email protected])

Received 10 August 2004; accepted in revised form 14 February 2005

Key words: Avian species richness, Conservation, Deforestation, Diversity, Guatemala, Land-use Abstract. Cloud forests in central Guatemala are fragmented and decreasing in area due to slashand-burn agricultural activities. We studied bird species composition, abundance, guild composition, and site tenacity of a 102 ha plot located in a cloud forest region of the Sierra Yalijux in Guatemala, half of which was primary forest and half young secondary forest (<7-years-old). Of the 100 species present 14 were restricted to the Endemic Bird Area ‘Northern Central American highlands’ (i.e. 66% of a total of 21 endemics). Five of the 100 analysed species, including one of the restricted-range species (Troglodytes rufociliatus), had a signiﬁcantly diﬀerent abundance in primary and secondary forests. Theoretical analysis suggests that seven species out of a community comprised of 141 bird species are already extirpated and only three out of the 14 present restrictedrange species might survive the current state of deforestation. Insectivores were the dominant guild on the plot in terms of numbers of species, followed by omnivores, frugivores and granivores. However, in terms of individuals, omnivores made up nearly half of the bird individuals in primary forest, but declined by 44% in secondary forest, whereas granivores more than doubled in this habitat type. Numbers of species per guild were not signiﬁcantly diﬀerent between habitats, while numbers of individuals per guild were signiﬁcantly diﬀerent. In general, individuals per species are signiﬁcantly diﬀerent in the two habitats. Results suggest that most of the species that are currently surviving in the remnant forests of the Sierra Yalijux might be fairly well adapted to a range of forest conditions, but that populations of a number of restricted-range species might be small. Even generalists species like the Common Bush Tanager (Chlorospingus ophthalmicus) are less abundant in secondary vegetation than in primary forest of the study plot.

Introduction Annual deforestation in Central America is very high, especially in El Salvador (4.6%), Nicaragua (3.0%), and Guatemala (1.7%) (World Bank 2001; cf. FAO 2001; World Conservation Monitoring Centre 1992). One potential consequence of deforestation is loss of species (Bierregaard 1990; Bierregaard and Stouﬀer 1997; Myers et al. 2000; World Bank 2001), mainly aﬀecting forest specialists (e.g., McGowan and Gillman 1997; Stattersﬁeld and Capper 2000). Expanding subsistence agriculture to meet the needs of an increasing human population (e.g., Ma´n˜ez-Costa and Renner 2005) threatens biodiversity in [485]

1546 forest remnants world-wide (e.g., Hughes et al. 2002; Schulz et al. in press) and especially in Latin America (Markussen 2004). In central Guatemala, natural habitats, such as primary cloud forests, are often converted and used as part of the milpa system (slash-and-burn agriculture) (Renner 2003; Markussen 2004; Markussen and Renner 2005). It is questionable whether secondary forest regrowth after farming can preserve numbers of species comparable to natural habitats in tropical landscapes over the long term (Hughes et al. 2002; Renner 2003). In addition, the time required for secondary forest biodiversity to approach that of primary forest is not known (e.g., Shankar-Raman et al. 1998; Terborgh 1999; Shankar-Raman 2001; Shankar-Raman and Sukumar 2002). Cloud forest areas in many parts of the tropics are increasingly deforested, and many forest remnants have likely already lost a large proportion of their original avifauna (Kappelle and Brown 2001). Some sites are presumed to have lost forest bird populations, e.g., the Brazilian Atlantic forests. Other sites may still retain endemic forest species because of persisting habitat heterogeneity (Marsden et al. 2004). Nevertheless, fragmentation and loss of forest habitats are important causes of regional species extinction (Marsden et al. 2004). The province Alta Verapaz in central Guatemala is located within a Biodiversity Hotspot (Myers et al. 2000) and an Endemic Bird Area (Stattersﬁeld et al. 1998), and is therefore of high importance for conservation (Veblen 1976; Islebe 1995; Stattersﬁeld et al. 1998; Markussen and Renner 2005). This region contains primary forests subject to decreasing area and increasing fragmentation that currently contain endemic and specialised bird species. We examined species richness, abundance, site tenacity and body mass distribution of birds in primary cloud forest compared to neighbouring young secondary forest in the highlands of central Guatemala near the village of Chelemha´. We used within-one-habitat recaptures as a measure of habitat quality. Special emphasis was placed on restricted-range species and Central American cloud forest specialists.

Study area The Sierra Yalijux where the study site was located, belongs to the northeasternmost slopes of the northern Cordillera of Guatemala (Municipio Tucuru´, Alta Verapaz). The total forest cover above 1,800 m (ca. the altitudinal border of cloud forests in Guatemala) is estimated at 5,500 ha (Markussen 2004). In this region, the climate is tropical to sub-tropical (MAGA 2001) and precipitation is high, up to 4000 mm per year (Markussen 2004). We chose a 102 ha study plot in the Sierra Yalijux near the settlement of Chelemha´ (Figure 1). The geographic plot co-ordinates are 9004¢ W and 1523¢ N. It is situated at an elevation between 1,980 m and 2,550 m and contains approximately 51 ha of primary forest and 51 ha of secondary forest. The primary forest in the region is mainly mixed oak and pine forest with Pinus maximinoi as the dominant species (Veblen 1976; Mozin˜o 1996). [486]

1547

Figure 1. (a) Location of the study plot (n) in Guatemala and Endemic Bird Area ‘Central American highlands’ (Stattersﬁeld et al. 1998) (- - - -). Grey indicates areas in Guatemala with elevations above 1000 m. (b) The study plot (bold line — ) with main trails for transect counts (thin line —), mist net sites (black dots •) and vegetation classiﬁcation (n grey: primary forest, white: secondary habitats of all kinds). Dotted line indicates the Rı´ o Chelemha´; arrow on map resembles approximately 400 m in nature.

The canopy exceeds 35 m and there are generally three vegetation strata, i.e. understorey <7 m, mid-story 7–20 m, and overstorey >20 m. Stem diameter at breast height for overstorey trees exceeds 1 m. Young secondary forest (<10 years-old), is – aside from primary forest – the most abundant vegetation in the study region and probably also within the whole of Alta Verapaz. Secondary forests >10 years cover <5 ha within the community of Chelemha´. Young secondary vegetation is the result of slash-and-burn agriculture (milpa system), and the secondary forest we studied had an age of less than 7 years. After corn and bean cultivation, shrubs can grow up to 10 m in height during a fallow period of 7 years. However, a fallow period of this duration is exceptional occurring only in the study plot. Generally in the community of Chelemha´ there is a fallow period of <2 years. The shrubby habitat is composed of many diﬀerent tree species, including oaks (Quercus sp.); but in contrast to primary forest the pines (Pinus sp.) are rare and the shrubs form only a single vegetation layer. For both the understorey and overstorey, the estimated tree height, diameter at breast height and density were measured for each 25 m section of the bird count transects.

Methods Bird surveys employing audio/visual counts as well as standardised mist netting were conducted during the region’s main breeding season between March and September 2001 and 2002 in both primary forest and adjacent secondary forest. [487]

1548 In primary and secondary forest, an existing trail system was used to count birds by means of regular transect counts in order to assess population densities for diﬀerent habitats of the plot (Bibby et al. 1995; Krebs 1999; Gilbert et al. 2000). A total of 3,300 m of counts were conducted along the trails (no trail intersections allowed, all trails were separated at least by 50 m), 50% in each vegetation type. A series of three visits per trail were conducted in 2002 between 0530 h and 0900 h. A maximum trail length of 450 m was visited per day. All sight records and singing individuals were recorded while slowly walking along the trail. The trails of the entire plot were divided into 22 trail sections of 150 m each. Eleven sections were situated in primary forest, and 11 in secondary forest. All displaying birds within 100 m distance to both sides of the trail were recorded, so that each trail section represented a 3-ha-sized rectangular strip (150 · 2 · 100 m = 3 ha). Each record contained the perpendicular observation distance, as well as information on species, sex, age, and number of individuals. Density estimates were derived from the maximum number of birds recorded on each 3-ha strip. For some cryptic species, (e.g. Grallaria guatimalensis) or species with low voices (Buarremon brunneinucha, Atlapetes gularis), the strip width was reduced to 50 m and the corresponding observations within 50 m from the transect for the density calculations. Cyanocorax melanocyaneus and Cyanolyca pumilo were estimated conservatively by directly counted individuals. Most ﬂocks (especially the frequent Chlorospingus ophthalmicus ﬂocks) disbanded early in the breeding season and could be noted as pairs. Singing and territorial display behaviour of males was counted as a breeding unit for all other species, except for species where females also display territorial behaviour. Trochilidae were treated in the same way, except for trapliners where only females (if distinctive) were recorded as a breeding unit. Identiﬁcation was made using Land (1970), Howell and Webb (1995), and Edwards (1998). Taxonomy and systematic order follows the checklist of the American Ornithologists’ Union (1998) with the relevant supplements (American Ornithologists’ Union 2000, 2002). Transect and mist netting procedures are often combined in tropical forest bird community studies since the two methods select diﬀerent portions of the community, thus achieving a more accurate assessment of community composition (Poulsen 1994; Remsen 1994; Remsen and Good 1996). Twelve mist net lines were established, six in natural and six in secondary forest. The net lines were distributed randomly at existing tracks to avoid pseudo-replication (Hurlbert 1984). Each net line consisted of eight nets of 12 m each and was opened for 8.5 h per capture day. Capturing was conducted for 2 days at each line in 2001, and for 4 days in 2002 with a total of 4,896 net hours (12 m net). Each captured bird was marked and body mass determined with spring balances. Eﬀects of land-use were measured as diﬀerences in bird community structure, including changes in species richness, species composition, numbers of individuals (trail data) as well as in individual turnover, body size and body mass (mist net data) between primary forest and secondary forest. [488]

1549 Statistics Bird density, diﬀerences in species numbers and comparisons of species similarity between habitats were calculated. Similarity measures are common methods for distinguishing between entities (Magurran 1988; Rosenzweig 1995; Krebs 1999; Gaston and Blackburn 2000). The Sørensen and Morisita-Horn indices are more useful than Jaccard or other indices (Magurran 1988; Krebs 1999), and similarity analyses based on Sørensen were used (in Colwell 2000: Sørensen-Inc.). For each combination of the 12 mist net lines and for each trail section, Sørensen values were computed and arranged in a dissimilarity matrix. Ordination of the samples (trail sections, mist net lines) using multi-dimensional scaling (MDS) was carried out. To estimate the inﬂuence of land-use on bird abundance at species level, observation frequencies were tested using the v2-test with primary forest as the ‘expected variable’ and secondary forest as the ‘observed variable’. The Mann-Whitney-U test was used to compare abundance between primary and secondary forest.

Estimation of total species richness Species richness is normally not detected completely, that is neither all species, nor all individuals are detected in natural environments (e.g., Rosenzweig 1995; Begon et al. 1996; Krebs 1999). For the purpose of estimation of total species richness, several indices were established with diﬀerent purposes (e.g., Chao and Lee 1992; Colwell and Coddington 1994; Rosenzweig 1995). These estimators and indices give an approximate number of species that might be detected when making repeated observations (Magurran 1988; Rosenzweig 1995; Krebs 1999). Diﬀerent estimators are of diﬀerent value according to their purpose. Here we used the Bootstrap estimator due to the large sample (Magurran 1988). Otherwise the Jackknife estimator must to be used. Based on the trail data, we ﬁrst described species accumulation from the pooled data of the whole study plot (Sobs in Colwell 2000). Then diﬀerences between primary forest and secondary forest were established from the separate samples. In addition, primary and secondary forest were compared with regard to species composition. To describe the community, observed species numbers (Sobs), observed individuals numbers (N), and indices were calculated, and Bootstrap (SBoot), Evenness (E), and the Abundance-based Estimator of Species Richness (ACE) were used. For calculation and formulas of the estimators see Magurran (1988) and Colwell (2000). See Krebs (1999) and Renner (2003) for a complete summary. Body mass analyses required splitting of sexes for certain species. A group is either a species or one sex of a species. For Diglossa baritula, Lampornis amethystinus, L. viridipallens, Lamprolaima rhami, and Turdus infuscatus, a [489]

1550 sexual separation for analysis is essential due to signiﬁcant body mass diﬀerences between the sexes.

Recapture data Impact on tropical avifaunas is frequently estimated with mark-recapture methods (e.g., Lambert 1992; Johns 1992; Holbech 1996; Dranzoa 1998; Waltert and Mu¨hlenberg 2001). Optimal habitats are usually correlated with high captures and/or recaptures, and pessimal habitat quality with low captures and/or recaptures (Matthysen et al. 1995; Reitsma et al. 2002; and others). Winker et al. (1995) presumed that intra-speciﬁc competition in territorial birds forces (behaviourally) sub-dominant individuals to occupy sub-optimal or pessimal habitats with increasing population density. Mainly territorial and dominant individuals should occupy optimal habitats. In this study, the recapture rate Rt was deﬁned as the ratio of ﬁrst captures Fc to recaptures Rc (Rt = Rc/Fc), with all same-day-recaptures excluded, and each recaptured individual being counted only once even when recaptured twice or more times. In total, each net line was sampled two times in 2001 and four times in 2002 (see above).

Results Vegetation Mean distance between trees with diameter at breast height of <0.20 m of the Chelemha´ Plot was 2.94 m±1.77 in primary forest and 1.16 m±0.82 in secondary forest. Mean height of overstorey trees was 25.9 m±6.6 in primary forest, 4.9 m±1.9 for understorey trees in primary forest, and 2.9 m±1.9 for trees in secondary forest (see Table 1).

Table 1. Parameters of the vegetation structure. Overstorey

Primary forest

Secondary forest

Mean ±s.d. n Mean ±s.d. n

Understorey

dbh

h

d

dbh

h

d

84.3 53.4 142 59.2 74.5 6

25.9 6.6 142 11.67 2.58 6

294.6 177.2 142 233.3 182.6 6

5.1 2.8 145 2.1 1.5 67

4.9 1.9 145 2.6 1.9 67

164.5 114.2 145 112.8 81.2 67

dbh: diameter at breast height (cm), h: height (m), d: density (cm). Further details on methods are given in the chapter ‘Study Area and Study Plot’. [490]

1551 Avifauna of the study area On the 102-ha plot, a total of 100 avian species was found to be present of which 75 are presumably residents. Sixty-six of the 100 avian species recorded were detected by mist netting, 75 from regular counts along trails, and eight by incidental records. Forty-seven species were recorded by both mist netting and transect counts, 17 by mist netting alone and 28 by transect counts alone. Out of the 100 species, 75 species were presumed resident breeding species, hereafter treated as ‘residents’. This number is an estimate and includes incidental records of species which are believed to breed but were only rarely recorded (1–2 observations) by regular transect counts (Coragyps atratus, Lophostrix cristata, Glaucidium gnoma, Streptoprocne zonaris, Sclerurus guatemalensis, Tachycineta bicolor, Saltator caerolescens, Dives dives). The total species numbers for the entire plot was estimated (Colwell 2000) at 61 (Sobs) and 62.75±0.00 (Bootstrap±s.d.). Further results on the bird community structure and comparisons to other tropical and temperate studies are drawn in Renner (2003).

Eﬀects of land-use on the bird community structure Based on the maximum abundance of each species at each trail section, a total of 1405 individuals was estimated to be present on the plot. While, in total, more species were observed in secondary forest (51 and 55 observed species in primary forest and secondary forest, respectively), more individuals were observed in primary forest (753) than in secondary forest (652). The diﬀerence in overall population size is signiﬁcant (v2 = 7.41, pdf1<0.01), representing a decrease of 14% between primary and secondary forest. The higher observed species numbers in secondary forest is also reﬂected in higher estimated total species richness: the Bootstrap estimator in primary forest amounted to 52.91 (±0.77 s.d.) and in secondary forest to 57.80 (±0.00). This suggests that only a few more species remained undetected (Figures 1 and 2). Diversity statistics of birds are summarised in Table 2.

Table 2. Summary of diversity statistics (calculated with Colwell 2000) depending on habitat compiled from transect count data.

Sobs Individuals Singletons Doubletons ACE Bootstrap

Primary forest

±s.d.

Secondary forest

±s.d.

51 1563 0.0 0.0 51.0 52.9

– – 0.00 0.00 0.00 0.77

55 1766 0.0 0.0 55.0 57.1

– – 0.00 0.00 0.00 0.00

[491]

1552

Figure 2. Expected species E (transect counts data from 2002) in primary forest and secondary forest. Error bars were left out for better illustration. Data were calculated with Rarefaction 1.3 (Holland 2003).

Average pair-wise similarity of bird species composition (mean Sørensen ±s.d.) of the 22 three-ha sections was nearly constant for both within and between habitat comparisons. It amounted to 0.61±0.11 (mist netting: 0.65±0.11) between the 11 primary forest samples, 0.58±0.11 between secondary forest samples (mist netting 0.66±0.34) and 0.61±0.11 (mist netting 0.63±0.16) between primary and secondary forest samples. When ordinating samples from transect counts using non-linear multidimensional scaling the two groups of sites did largely overlap (Figure 4). A one-way MANOVA of the sample scores extracted from the two-dimensional ordination revealed no signiﬁcant diﬀerence between the two groups of sites (Rao’s R2.19 = 1.18, p = 0.33). However,

Figure 3. Observed species Sobs (transect count data from 2002) in primary forest and secondary forest in the Chelemha´ Plot. Error bars were left out for better illustration. Calculated with Colwell (2000). [492]

1553

Figure 4. Non-linear multidimensional scaling (MDS) plot of avifaunal similarity based on Sørensen-incidence values for 22 transect counts section of 3 ha. Lines connect study sites belonging to the same habitat category. Habitats: PF – primary forest, YSF – young secondary forest. Note diﬀerent scaling on axes.

using the bird data from the twelve net lines, there are two distinct groups (primary, secondary forest) forming the ordination plot (Figure 5), with sample scores of trapped bird assemblages showing signiﬁcant diﬀerences between habitats (Rao’s R2,9 = 8.27, p<0.01).

Figure 5. Non-linear multidimensional scaling (MDS) plot of avifaunal similarity based on Sørensen-incidence values for 12 mist net lines, each of 102 m length. Lines connect study sites belonging to the same habitat category. Habitats: PF – primary forest, YSF – young secondary forest. Note diﬀerent scaling on axes. [493]

1554 Forty-three species had individuals in both habitats; three species had similar mean individual numbers, 17 had higher mean individual numbers in primary forest and 23 had higher mean individual numbers in secondary forest. Five species showed signiﬁcant diﬀerences in abundance in the two habitats (Table 6). Zimmerius villisimus, Troglodytes rufociliatus, Atthis ellioti, Myadestes unicolor, and Atlapetes gutteralis had signiﬁcantly diﬀerent individual numbers in primary forest and secondary forest. C. ophthalmicus (p = 0.08), Henicorhina leucophrys (p = 0.06), and Sclerurus mexicanus (p = 0.06) had almost signiﬁcant diﬀerences. The most common species, C. ophthalmicus, was comparatively less abundant in secondary forest than in primary forest (Table 6). Three species (Z. vilissimus, T. rufociliatus, and M. unicolor; Tables 3 and 7) were signiﬁcantly less abundant in secondary forest compared to primary forest. While 23 species are less abundant in primary forest than in secondary forest, at least 22 have 50% more individuals in primary forest. At the species level, ﬁve species were found in signiﬁcantly diﬀerent numbers in the two habitats (Table 3). This represents a minor part of the 100 species observed, and should be treated with caution. Given that from an accepted signiﬁcance level of 5% (p = 0.05) and 61 analysed species with any N to perform the Mann–Whitney-U test out of the 100 residents (see Table 6), already 3.05 species (61 · 0.05) could be expected to show signiﬁcant diﬀerences in abundance between habitat types by chance alone. Within the Chelemha´ Plot there are three species inﬂuenced signiﬁcantly negatively and two positively in accordance to individual numbers. Several primary forest birds (Table 7) and especially endemic primary forest birds of the Central American highlands are still present in the respective parts of this plot.

Guild composition Guild composition was signiﬁcantly diﬀerent between habitats concerning numbers of individuals but not concerning numbers of species (Table 4). In Table 3. Species showing signiﬁcant diﬀerences in abundance between habitat types. Abundance given as mean numbers of individuals calculated from the maximums recorded on 3-ha transect strips. p: p-level (corrected) based on the Mann-Whitney-U test. Exclusively species with signiﬁcant diﬀerence (p<0.05) are listed. Species

Atthis ellioti Zimmerius vilissimus Troglodytes ruﬁciliatus Myadestes unicolor Atlapetes gutteralis

p

0.07 0.04 <0.01 0.02 0.03

Primary forest

Secondary forest

Mean

±s.d.

Mean

±s.d.

0.00 2.36 1.56 2.73 4.25

– 1.57 0.73 1.42 4.03

1.20 2.17 1.00 1.36 4.20

0.45 1.94 0.00 0.92 3.65

[494]

Table 4. Numbers of species and individuals per guild (transect count data). Primary forest represents expected and secondary forest observed frequency for v2-test. The ﬁrst number is total N, the second the relative portion. Diﬀerences to Table 2 occur to the fact that here counted and there estimated individuals are given. As indicated in Table 6, several species and individuals were accounted for more than one guild when clear nutrition preferences were not given.

PF SF PF [495]

SF PF SF PF SF

Species % Species % Individuals % Individuals % Individuals % Individuals % Individuals % Individuals %

Exclusiona

Insectivores

Omnivores

Frugivores

Nectarivores

Granivores

Carnivores

NO NO NO NO NO NO NO NO O O O O G G G G

24 0.46 19 0.34 230 0.31 219 0.34 230 0.42 219 0.41 230 0.33 219 0.37

9 0.18 11 0.20 346 0.46 195 0.29 137 0.25 83 0.15 346 0.49 195 0.33

6 0.13 5 0.09 42 0.06 46 0.07 42 0.08 46 0.09 42 0.06 46 0.07

5 0.11 8 0.14 76 0.10 67 0.10 76 0.14 67 0.12 76 0.11 67 0.11

5 0.09 10 0.19 57 0.08 123 0.19 57 0.11 123 0.23 4 0.01 65 0.11

2 0.04 2 0.03 2 0.00 2 0.00 2 0.01 2 0.01 2 0.01 2 0.01

Total (N) 51

v2 (p) 8.4 (0.20) df = 5

55 753

144.3 (<0.01) df = 5

652 544

99.7 (<0.01) df = 5

540 700

998.1 (<0.01) df = 5

594

a

Exclusion of the most abundant species from analysis. NO: no exclusion, O: Exclusion of the three omnivores Chlorospingus ophthalmicus, Myadestes unicolor, and Cyanolyca pumilo, G: Exclusion of the three granivores Atlapetes gutteralis, Columba fasciata, and Carduelis notata. Further explanations and justiﬁcation see text (‘Results’ and there ‘Guild composition’). PF: primary forest, SF: secondary forest

1555

1556 Table 5. Body mass changes in recaptured individuals. BM 1: body mass at ﬁrst capture, BM 2: body mass at ﬁnal recapture in the same breeding season. PF: primary forest, SF: secondary forest. Species

Habitat

BM 1[g]

BM 2[g]

Change[g]

Relative change

Asphata gularis Atlapetes gutteralis Atlapetes gutteralis Basileuterus belli Basileuterus belli Basileuterus belli Basileuterus belli Buarremon brunneinucha Buarremon brunneinucha Catharus frantzii Catharus frantzii Catharus frantzii Catharus frantzii Catharus frantzii Catharus frantzii Chlorospingus ophthalmicus Chlorospingus ophthalmicus Chlorospingus ophthalmicus Chlorospingus ophthalmicus Chlorospingus ophthalmicus Chlorospingus ophthalmicus Chlorospingus ophthalmicus Chlorospingus ophthalmicus Chlorospingus ophthalmicus Chlorospingus ophthalmicus Diglossa baritula Diglossa baritula Diglossa baritula Diglossa baritula Henicorhina leucophrys Henicorhina leucophrys Henicorhina leucophrys Lampornis amethystinus Lamprolaima rhami Lamprolaima rhami Lamprolaima rhami Lamprolaima rhami Lamprolaima rhami Lamprolaima rhami Lamprolaima rhami Lamprolaima rhami Myadestes occidentalis Myadestes occidentalis Myadestes unicolor Myioborus miniatus Troglodytes ruﬁciliatus Wilsonia pusilla Xiphorhynchus erythropygius

SF SF SF PF PF PF SF PF SF PF PF PF PF PF SF PF PF PF PF SF SF SF SF SF SF SF SF SF SF PF PF SF PF PF PF PF PF PF PF PF PF PF SF PF SF SF SF PF

52.50 33.50 33.00 10.00 10.00 9.75 10.75 42.25 38.00 19.00 19.00 22.00 28.50 31.00 28.50 16.75 9.25 18.75 21.25 17.50 14.50 17.25 18.50 19.25 17.75 9.25 9.25 9.50 9.75 12.75 15.00 15.00 5.10 5.75 5.60 8.30 6.40 8.50 8.20 9.10 8.30 35.50 24.75 38.00 8.25 11.75 9.00 37.25

55.25 42.00 32.00 10.25 9.50 9.50 11.25 42.00 38.25 33.00 30.50 39.00 27.75 30.50 29.25 17.75 19.70 15.25 19.50 21.50 18.50 18.00 19.50 18.00 17.00 9.75 9.00 8.25 9.25 13.75 13.25 15.50 5.50 6.25 5.70 8.40 6.50 8.60 8.40 8.00 8.20 36.75 33.25 36.50 7.25 12.00 7.75 45.00

2.75 8.50 1.00 0.25 0.50 0.25 0.50 0.25 0.25 14.00 11.50 17.00 0.75 0.50 0.75 1.00 10.45 3.50 1.75 4.00 4.00 0.75 1.00 1.25 0.75 0.50 0.25 1.25 0.50 1.00 1.75 0.50 0.40 0.50 0.10 0.10 0.10 0.10 0.20 1.10 0.10 1.25 8.50 1.50 1.00 0.25 1.25 7.75

0.05 0.20 0.03 0.02 0.05 0.03 0.04 0.01 0.01 0.42 0.38 0.44 0.03 0.02 0.03 0.06 0.53 0.23 0.09 0.19 0.22 0.04 0.05 0.07 0.04 0.05 0.03 0.15 0.05 0.07 0.13 0.03 0.07 0.08 0.02 0.01 0.02 0.01 0.02 0.14 0.01 0.03 0.26 0.04 0.14 0.02 0.16 0.17

Total individuals: 48

Mean:

18.10

19.74

1.64

0.04

[496]

Table 6. Abundance for forest species, given as maximum records on 51 ha primary forest (PF) and 51 ha secondary forest (SF) and population estimates (for 102 ha and 5500 ha, the latter represents the natural pine–oak forests of the Sierra Yalijux). All species potentially abundant in the Sierra Yalijux are listed. However, guild, habitat, etc. is only listed for the relevant species deﬁnitely observed. Taxonomy and systematics follows American Ornithologist’s Union (1998, 2000, 2002). Family

Species

Exp.a

Guildb

Habitatc

Methodd

Abundancee

Estimate for the Sierra Yalijux (PF)

PF

SF

Ind./102 ha

TC

2

0

4

216

– TC

16

16

31

1725

G

TC

1

4

2

108

G

TC

Ind./5,500 ha

Cracidae Ortalis vetula Penelope purpurascens Oreophasis derbianus Penelopina nigra

H,C H H H,C

F

Dendrortyx leucophrys Odontophorus guttatus Dactylortyx thoracicus Cyrtonyx ocellatus

H,C H H H

Ardea herodias Bubulcus ibis

C C

Coragyps atratus

H,C

Ca

I

Chondrohierax uncinatus Elanoides forﬁcatus Accipiter chinogaster Asturina nitida Buteo platypterus Buteo solitarius Buteo jamaicensis

H,C C H,C C C H H,C

C

TC

F F

PF

Phasianidae [497] Ardeidae

Cathartidae Accipitridae

1557

Family

Species

Exp.a

Guildb

Habitatc

Methodd

Abundancee

Estimate for the Sierra Yalijux (PF)

PF

SF

Ind./102 ha

9

3

18

971

Ind./5,500 ha

Falconidae Micrastur ruﬁcollis Falco sparverius

H,C H,C

Bartramia longicauda

C

Columba livbia Patagioenas fasciata Zenaida asiatica Zenaida macroura Columbina inca Columbina passerina Claravis mondetoura Leptotila verreauxi Geotrygon albifacies

H H,C H C H H H C H,C

Bolborhynchus lineola

H,C

Piaya cayana

H

Tyto alba

H

Megascops trichopsis Megascops barbarus Lophostrix cristata Glaucidium gnoma Ciccaba virgata Strix fulvescens superspecies varia

H H H H,C H,C H,C

Scolopacidae Columbidae

[498]

F,G

TC

F,G

N

F,G

N

G,F

TC

2

1

4

216

C C C C

I I TC TC

0

1

0

0

Psittacidae Cuculidae Tytonidae Strigidae

1558

Table 6. (Continued).

[499]

H H H H,C

I

TC

1

0

2

108

H,C H,C H,C H,C H,C

I

TC

I

I

I

TC

H,C H,C H H,C H H,C H,C H,C H,C H H,C H,C

N N N N N N N N N N N N

N N,TC N,TC N N N,TC N,TC N,TC N,TC N TC N,TC

0 0

1 2

0 0

0 0

0 46 11

2 45 7

0 90 22

0 4961 1186

0

6

0

0

H H,C H,C

I,F I,F F

TC TC N,TC

2 11 17

0 7 13

4 22 33

216 1186 1833

H,C

F,I

N,TC

3

7

6

324

H,C

F

N,TC

7

5

14

755

1559

Asio stygius Aegolius ridgway Caprimulgidae Chordeiles acutipennis Caprimulgus vociferus) arizonae Apodidae Cypseloides niger Streptoprocne rutila Streptoprocne zonaris Chaetura vauxi Aeronautes saxatalis Trochilidae Campylopterus hemileucurus Colibri thalassinus Abeillia abeillei Hylocharis leucotis Amazilia cyanocephala Lampornis viridipallens Lampornis amethystinus Lamprolaima rhami Eugenes fulgens Doricha enicura Tilmatura dupontii Atthis ellioti Trogonidae Trogon collaris Trogon mexicanus Pharomachrus mocinno Momotidae Aspatha gularis Ramphastidae Aulacorhynchus prasinus

Family

Species

Exp.a

Guildb

Habitatc

Methodd

Abundancee

Estimate for the Sierra Yalijux (PF)

PF

SF

Ind./102 ha

Ind./5,500 ha

Picidae Melanerpes formicivorus Melanerpes aurifrons Sphyrapicus varius Colaptes auratus Picoides villosus Piculus rubiginosus

H H,C C H,C H,C H

I I

N,TC N,TC

1 10

3 8

2 20

108 1078

H,C H,C H,C -

I I I

N,TC TC I

5 5

2 2

10 10

539 539

H H,C H,C

I I

N,TC N,TC

1

1

2

108

H

I

N

H C H,C H,C H C C C C

I

N 26 12

13 12

51 24

2804 1294

Furnaridae

[500]

Anabacerthia variegaticeps Automolus rubiginosus Sclerurus mexicanus Sclerurus guatemalensis Dendrocolaptidae Xiphorhynchus promeropirhynchus Xiphorhynchus erythropygius Lepidocolaptes aﬃnis Formicaridae Grallaria guatimalensis Tyrannidae Camptostoma imberbe Elaenia frantzii Zimmerius vilissimus Mitrephanes phaeocercus Cantopus pertinax Cantopus sordidulus Contopus virens Cantopus cinereus Contopus borealis

I I I

SF

N,TC TC TC

1560

Table 6. (Continued).

Empidonax ﬂaviventris Empidonax virescens Empidonax minimus Empidonax hammondii Empidonax oberholseri Empidonax aﬃnis Empidonax ﬂavescens Empidonax fulvifrons Sayornis nigricans Pachyramphus major Pachyramphus aglaiae

C C C C C H H,C H,C H,C H H,C

Vireo plumbeus Vireo huttoni Vireo gilvus Vireo leucophrys Vireo philadelphicus Cyclarhis gujanensis

H,C H,C C C C C

Cyanocitta stelleri Cyanocorax melanocyaneus Cyanolyca pumilo Aphelocoma unicolor Corvus corax

H H,C H,C H H

Tachycineta bicolor Tachycineta thalassina Notiochelidon pileata Petrochelidon pyrrhonota Hirundo rustica

H,C H H,C C C

Certhia americana

H

I I

N N,TC

0

1

0

0

I

N,TC

7

0

14

755

O O

N,TC N,TC

1 16

3 8

2 31

108 1725

O

TC

I I I

I TC TC

0

1

0

0

SF

Vireonidae

[501] Corvidae

Hirudinidae

Certhididae

1561

Family

Species

[502]

Troglodytidae Thryothorus modestus Troglodytes musculus Troglodytes rufociliatus Henicorhina leucophrys Turdidae Sialia sialis Myadestes occidentalis Myadestes unicolor Catharus aurantiirostris Catharus frantzii Catharus mexicanus Catharus dryas Catharus ustulatus Catharus guttatus Turdus infuscatus Turdus plebejus Turdus grayi Turdus ruﬁtorques Mimidae Dumatella carolineus Melanotis hypoleucus Ptilogonatidae Ptilogonys cinereus Peucedramidae Peucedramus taeniatus Parulidae Vermivora chrysoptera

Exp.a

H,C H,C H,C H,C H,C H,C H,C H,C H,C H H C C H,C H,C H,C H,C C H,C

Guildb

Abundancee

Estimate for the Sierra Yalijux (PF)

PF

SF

Ind./102 ha

Ind./5,500 ha

N,TC N,TC N,TC N,TC

13 7 14 35

13 10 2 29

25 14 27 69

1402 755 1510 3775

O O O O

N,TC N,TC N,TC N,TC

15 30 4 35

16 15 5 31

29 59 8 69

1618 3235 431 3775

O O O O

N,TC N,TC N,TC TC

15 5 35 1

8 8 33 4

29 10 69 2

1618 539 3775 108

11

13

22

1186

I I I I

Habitatc

PF

Methodd

I,F

SF

N,TC

I

PF

N

H,C H,C H

1562

Table 6. (Continued).

[503]

Vermivora peregrina Parula superciliosa Dendroica pensylvanica Dendroica coronata Dendroica virens Dendroica townsendi Dendroica occidentalis Dendroica fusca Dendroica graciae Mniotilta varia Seiurus noveboracensis Seiurus motacilla Oporornis tolmiei Geothlypis poliocephala Wilsonia pusilla Wilsonia canadensis Ergaticus versicolor Myioborus miniatus Basileuterus ruﬁfrons Basileuterus belli

C H,C C C C C C H,C H C C C H,C H,C H,C C H,C H,C H,C H,C

Chlorospingus ophthalmicus Piranga ﬂava Volatinia jacarina Sporophila torqueola Tiaris olivacea Haplospiza rustica Diglossa baritula Atlapetes gutteralis Buarremon brunneinucha Melozone biarcuata

I

N,TC

3

7

6

324

I

N,TC

I I I

N,TC N N,TC

5

1

10

539

4

0

8

431

I I I I

N N,TC N N,TC

6

4

12

647

55

54

108

5931

H,C H

O

N,TC

163

89

320

17578

C H,C H,C H H,C H,C H,C H

G G G I N G G G

N N,TC N,TC TC N,TC N,TC N,TC N,TC

0 0 2 17 45 0

2 3 6 42 52 3

0 0 4 33 88 0

0 0 216 1833 4853 0

Thraupidae

Emberezidae

PF SF

1563

Family

Species

Exp.a

Guildb

Habitatc

Methodd

Aimophila rufescens Zonotrichia capensis Spizella passerina

H,C H,C H

G G G

N N,TC N

Saltator caerolescens Saltator atriceps Pheucticus ludovicianus

C H C

G G

Dives dives Quiscalus mexicanus Molothrus aeneus Icterus chrysater Icterus galbula

H,C H,C H H,C C

Euphonia elegantissima Chlorophonia occipitalis Carduelis atriceps Carduelis notata Coccothraustes abeillei

H,C H,C – H,C H,C

Abundancee

Estimate for the Sierra Yalijux (PF)

PF

Ind./102 ha

SF

Ind./5,500 ha

3

5

6

324

I TC

3

2

6

324

G,I O

I TC

1

4

2

108

F F,G,I G G

TC TC N N,TC

9 1

4 0

18 2

971 108

4

13

8

431

Cardinalidae

Icteridae

[504] Fringillidae

:extinct species (not considered as resident) a Species expected according to H: Howell and Webb (1996), C: found in Chicacnab 12 km west of Chelemha´ (Eisermann 2000). List is derived with the following criteria: species are resident in the northern mountain ridge of Guatemala and forest species above 1,800 m. b Key for relevant species: Ca: carrion F: frugivore G: granivore I: insectivore O: omnivore C: raptor, carnivore N: nectarivore c Key: PF: more than 75% of detections in primary forest SF: more than 75% of detections in secondary forest d TC: transect counts, N: mist netting, I: incidental record, blank ﬁeld: not recorded in the Chelemha´ Plot. e Adapted from transect count data, mist netting data was not used here.

1564

Table 6. (Continued).

Table 7. Abundance and estimated population size for threatened forest birds of the Sierra Yalijux. The ﬁrst 21 entries listed are restricted-range species of the Northern Central American Highlands (Stattersﬁeld and Capper 2000).

[505]

#

Species

Global statusa

Endemicb

Mean individuals in primary forest ind./51 ha*

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Podilymbus gigas Oreophasis derbianus Cyrtonyx ocellatus Otus barbarus Strix fulvescens Campylopterus rufus Lampornis viridipallens Lampornis sybillae Doricha enicura Atthis ellioti Asphata gularis Notiochelidon pileata Xenotriccus callizonus Troglodytes rufociliatus Melanotis hypoleucus Turdus ruﬁtorques Tangara cabanisi Ergaticus versicolor Icterus maculialatus Carduelis atriceps Cyanocorax melanocyaneus

Extinct Vulnerable Near threatened Near threatened Least concern Near threatened Least concern Least concern Least concern Least concern Least concern Least concern Near threatened Least concern Least concern Least concern Endangered Vulnerable Least concern Least concern Least concern

X X X X X X X X X X X X X X X X X X X X X

NO Extinct Non in NO Non in NO Non in NO Non in Non in 3 Non in NO 14 11 1 NO Non in NO Non in 1

102 ha (primary forest) ind./102 ha

Sierra Yalijux (primary forest) ind./5500 ha

0 <1

0 max. 55

PF

0

0

PF

0

0

PF PF

0 0 6 0

0 0 330 0

28 22 2

1540 1210 110

PF

0

0

PF

0 2

0 110

(app. 1990) PF

PF

1565

1566

Table 7. (Continued). #

Species

Global statusa

[506]

Additional species of conservation concernc 22 Pharomachrus mocinno Near threatened 23 Penelopina nigra Near threatened 24 Chlorospingus ophthalmicus 25 Zimmerius vilisimus a

Endemicb

Mean individuals in primary forest ind./51 ha*

102 ha (primary forest)ind./102 ha

Sierra Yalijux (primary forest) ind./5500 ha

17 16 163 26

34 32 336 52

1870 1760 18,480 2860

adapted from Stattersﬁeld and Capper (2000). Endemics classiﬁed as endemic and part of the Endemic Bird Area ‘Central American highlands’ after Stattersﬁeld et al. (1998). c Forest species that are found to be aﬀected by land use or have low population sizes based on data of this study. *NO: no records, neither in the Chelemha´ Plot, nor in Sierra Yalijux. In total Guatemala, 1 species is extinct, 4 are endangered, 2 vulnerable, 12 near threatened and 1 lacks suﬃcient data according to Stattersﬁeld and Capper (2000). PF: primary forest. b

1567 both habitats, the largest group in terms of numbers of species was insectivores (24 sp. in primary vs. 19 sp. in secondary forest), followed by omnivores (9 vs. 11 sp.). However, in primary forest omnivores were much more abundant than insectivores. This was mainly a consequence of the large numbers of the tanager C. ophthalmicus in primary forest which is responsible for roughly half (45% drop in C. ophthalmicus from primary to secondary forest) of the 56% drop in individual numbers of omnivores in secondary forest. M. unicolor and Cyanolyca pumilo are the second and third species with the largest drop of individuals between primary and secondary forest for omnivores with 8% and 4%, respectively. If these three species (C. ophthalmicus, M. unicolor, and C. pumilo) are excluded from the analyses, omnivores have a percentage of 25.2% individuals in primary forest and 15.4% in secondary forest. When excluding the three species, insectivores stay the largest group but granivores double their relative proportions (10.5% vs. 22.8%) (Table 4). The only other guild that showed remarkable diﬀerences in abundance between habitats was granivores. Granivores were more than twice as abundant in secondary forest (219% of primary forest) than in primary forest, a result largely caused by high numbers of the emberizids Atlapetes gutteralis (responsible for 34% of the increase) and Carduelis notata (11%), but also of the dove Columba fasciata (2% decrease). When excluding the three species, granivores are represented with 10.9% in secondary forest and 0.6% in primary forest. Numbers of individuals and species of frugivores, nectarivores and carnivores are each represented in similar proportions in both habitats. When excluding these six species as mentioned before the diﬀerences in individuals per guild are still signiﬁcantly diﬀerent with p<0.01 (Table 7).

Recaptures There were 25 species with at least one recapture, of which seven had recaptures in both habitats. Twelve species were recaptured exclusively in primary forest and six exclusively in secondary forest. However, using diﬀerent species as sampling units, the numbers of recaptures for all 25 species were not signiﬁcantly diﬀerent between the two habitats (Wilcoxon test, T=125.0, Z=0.714; p = 0.48). Members of ﬁve species endemic to Central American highland forests (not to be confused here with the Endemic Bird Area; Stattersﬁeld et al. 1998) were recaptured in primary forest (Abeillia abeillei, D. baritula, Empidonax ﬂavescens, Asphata gularis, Melanotis hypoleucus). The recapture rate Rt is £ 0.01, except for E. ﬂavescens with a recapture rate of Rt = 0.20 in primary forest. Leaving species level and going one step beyond to the individual level, of all 140 recaptures (plus 28 excluded same-day recaptures) 51 individuals were recaptured at the same net line (Table 5). Except for three individuals recaptured at the same net line, all marked individuals were recaptured at diﬀerent [507]

1568 localities within the same habitat, i.e. at one of the six net lines in the same habitat but diﬀering from the original ﬁrst-capture net line. Individual recaptures show that just three out of 180 were recaptured in a habitat diﬀerent from previously captures during the study period in 2001 and 2002. Two of the three were ﬁrst captured in primary forest and one moved into primary forest after being marked in secondary forest. Two habitat-switching individuals had a higher body mass in secondary forest than in primary forest. A female L. amethystinus ﬁrst captured in primary forest on 20 March 2002 was recaptured in secondary forest on 12 April 2002 (5.5 g ﬁ 6.5 g). C. frantzii ﬁrst captured in primary forest on 17 March 2002 was recaptured in secondary forest on 17 May 2002 (26.0 g ﬁ 28.3 g). C. ophthalmicus banded in secondary forest on 17 July 2001 was recaptured in primary forest on 17 April 2002 with dramatically decreased body mass (16.5 g ﬁ 8.5 g). Of all recaptures, 28 individuals were recaptured twice, one individual of B. belli three times within three months in primary forest at neighbouring mist nets.

Body mass Individual recaptures (within same habitat and within the same season, i.e. within the 2001 or 2002 netting period) indicate that 10 individuals lost body mass in secondary forest and 12 in primary forest. While eight species were heavier in primary forest, 14 had higher body mass in secondary forest. For all species with both more than ﬁve captures in each habitat (Nprimary forest 5 \ Nsecondary forest 5), the species’ body mass distribution was not signiﬁcantly diﬀerent between habitats (v2-test, p>0.05). Forty-eight individuals were recaptured and body mass was determined (Table 5). Thirteen of the 23 groups (for deﬁnition of ‘group’ see methods) with at least two individuals in each habitat had a higher mean body mass in secondary forest. Eight groups had higher body mass in primary forest. The body mass diﬀerences are not signiﬁcant (MANOVA, variable: ‘habitat’, p = 0.21, Posthoc: Newman-Keuls test). Body mass distribution did not indicate that primary forest represented a diﬀerent habitat quality compared to secondary forest in the Sierra Yalijux (Table 5). Also, the total biomass was generally similar.

Restricted-range species From the 21 restricted-range species of the Central American Highlands, 10 are considered to be mainly or exclusively forest birds (Stattersﬁeld et al. 1998). Within the study plot, 14 range restricted species were recorded (Table 7) of which one, the Mountain Guan Oreophasis derbianus, might be regarded as [508]

1569 extinct in the recent past (Table 6). Eight of the remaining 13 restricted-range species were exclusively observed in secondary forest in the Sierra Yalijux (see also Table 7). Of the remaining ﬁve species, four did not reveal important diﬀerences in abundance between primary and secondary forest. One restricted-range species, T. rufociliatus, was signiﬁcantly more abundant in primary than secondary forest (Table 3).

Discussion According to the species–area relationship, it is to be expected that deforestation in the study region (Sierra Yalijux) should result in loss of both bird species and individuals. Even if deforestation stopped immediately and the remaining primary forest area was preserved for the future, the 10 forest species currently present at the study site in low numbers (Table 7) have an increased risk of extinction (see also Ma´n˜ez-Costa and Renner 2005). Species and area are related according to the formula S = cAz, where S = number of species, A = area, and z and c are empirically proven constants (MacArthur and Wilson 1967; Rosenzweig 1995; Waltert et al. 2004; Brooks et al. 1997, 1999a, b and c). Assuming the bird’s sub-populations of the Sierra Yalijux have limited genetic exchange with other sub-populations in the vicinity (e.g., the Sierra de las Minas beyond the Polochic valley, 20 km south of the Sierra Yalijux), one can set Asurviving to 5500 ha as the remaining primary montane cloud forest (Mu¨hlenberg et al. 1989) with Aoriginal = 16,500 ha for the Sierra Yalijux (Mu¨hlenberg et al. 1989). The original area of EBA # 018 Central American highlands is Aoriginal = 1,500,000 ha (Stattersﬁeld et al. 1998). Out of the 21 species endemic to the Central American highlands (EBA # 018 ‘Central American highlands’), ten species are found in primary forest and oak–pine forests (Stattersﬁeld et al. 1998). Applying the species area relationship it is theoretically expected that only 2.68 endemic species will remain (Ssurviving) in the 5500 ha of forest remnants in the Sierra Yalijux. In contrast, 13 endemic species were still present, more species than might be carried by primary forest on basis of the species–area equilibrium. Even if the forest area is not decreasing and the deforestation rate immediately halted, an optimistic estimate of six to seven (or more) out of the observed 10 primary forest highland endemics might not survive. In order to obtain information on potential historical bird species loss from the study plot before ﬁeldwork, we established a list of bird species potentially occurring in the Sierra Yalijux. One-hundred-forty-one species are expected to occur above 1980 m in northern central Guatemalan highlands (Howell and Webb 1995), including residents but no migrants as classiﬁed by Howell and Webb (1995). We can assume that of the 141 species expected to occur, nearly 41 species have already become extinct or were not recorded at our study site. However, it is most likely, that we did not record all species of the Sierra Yalijux within the 102 ha, because (i) area and species are related by S = cAz [509]

1570 (see above) and (ii) most species are patchily distributed and/or rare (Thiollay 1994a and b). Even in 100 ha of tropical landscapes ca. 95% of species are recorded with the methods we used according to Terborgh et al. (1990). The second aspect would suggest 133 recorded species at the Sierra Yalijux (95% of 141 species), the missing 33 species may be the result of the area–speciesrelationship and extinction. The area–species-relationship suggests the presence of 107 species at our study site, assuming here Aoriginal = 5500 ha, Asurviving = 102 ha, Soriginal = 133, and a mean empirically proven z-value = 0.26 for tropical bird communities (Brooks et al. 1997, 1999a, b and c). Therefore seven species are most likely already extinct. Due to the fact that this calculation is not a species-speciﬁc analysis, the nomination of the seven species is impossible. Nevertheless, based on the previous analysis, it appears that at least seven species are extirpated, and more species are likely to vanish from the study plot.

Land-use eﬀects on the bird community Diﬀerences at the community level between primary and secondary forest were generally small. Species richness and species similarity were comparable between habitat types. Only the numbers of individuals revealed a signiﬁcantly higher bird abundance in secondary than in primary forest. While multidimensional scaling of the community data yielded signiﬁcant diﬀerences when using only mist net captures, the diﬀerences for transect counts were not signiﬁcant. This might be the result of a collapsed stratiﬁcation of the bird community trapped in secondary forest, where even canopy species occur at levels that make them vulnerable to capture. Accurate comparisons of the importance of one habitat vs. another requires measurement of individual ﬁtness. The question of whether species of conservation interest (e.g., endemics and specialists, see Table 7) are able to ﬁnd suitable conditions to reproduce in secondary forest as well as they can in primary forest is of considerable interest. Reproductive success for P. mocinno is most likely directly linked to primary forest (Renner 2005). The species breeds in primary forest and ﬁnds stable breeding sites only there (Renner 2003; Renner 2005; compare also Gillespie 2001). The same potentially applies for other forest species and endemics listed in Table 7 (cf. Renner 2003). Some authors aﬃrm that young secondary forest and old secondary forest are suitable to preserve a degree of diversity and species richness comparable to primary forests (Shankar-Raman et al. 1998; Shankar-Raman 2001; ShankarRaman and Sukumar 2002). Older secondary forest (10+ years) might be suitable for preservation of biodiversity and a high degree of species richness, but unfortunately, at least in the study region of central Guatemala, secondary forests older than 7 years are rare, even more rare than primary forest. Therefore, primary forest must be preserved as long as data are lacking to indicate that young secondary forest might also be suitable for conservation of biodiversity. Currently and most likely in the future also, young secondary [510]

1571 forest is more frequent than old secondary forest and primary forest in the Sierra Yalijux. The relative proportion of the diﬀerent types of forest areas is a consequence of expanding slash-and-burn agriculture and ongoing agricultural activities in secondary re-growth areas (Markussen 2004; Markussen and Renner 2005).

Guild composition Guild structure is diﬀerent for the two habitats, indicating that the resources are not equal. While the percentage of insectivore bird individuals did not diﬀer signiﬁcantly between primary forest and secondary forest, there is a higher portion of insectivore species in primary forest than in secondary forest, probably an indication of a more complex vegetation structure and absolute numbers show signiﬁcant diﬀerences (see results). Nectarivore species numbers diﬀer slightly and granivore species numbers are almost doubled in secondary forest. This indicates that the food availability for species and for individuals per species is higher in secondary forests. One striking diﬀerence between primary and secondary forest is the large amount of granivores in the latter, twice that of primary forest. This is attributed to the larger supply of granivore food. Omnivores are more abundant in primary forest, which superﬁcially implies that there are less specialised resources and species present. However, most omnivores in primary forest are ground dwellers, which is obvious because the vegetation structure near ground in secondary forest is much denser than in primary forest (see ‘Vegetation’ and compare Renner 2003).

Recaptures Impact on tropical avifaunas is frequently estimated with recaptures (e.g., Lambert 1992; Johns 1992; Holbech 1996; Dranzoa 1998). Optimal habitats are usually correlated with high captures and/or recaptures and pessimal habitat quality with low captures and/or recaptures (cf. Reitsma et al. 2002; for exceptions see Winker et al. 1995). There were no signiﬁcant diﬀerences between recaptures in the two surveyed habitats of the Sierra Yalijux. This might be due to the fact that the amount of immature individuals (as far as recognisable for species, e.g. for C. ophthalmicus 1:0.5 in primary forest before and 1:1.5 in secondary forest after ﬂedging) is larger in secondary forest than in primary forest. This implies that immatures move to sub-optimal or pessimal habitats before potentially occupying an optimal habitat in primary forest (compare Winker et al. 1995; Waltert and Mu¨hlenberg 2001; Reitsma et al. 2002). Twelve species were recaptured exclusively in primary forest and six exclusively in secondary forest, indicating that primary forest might be a ‘better’ [511]

1572 habitat for birds and could contain more territories per area (cf. Renner 2003; Matthysen et al. 1995; Reitsma et al. 2002). Conclusions Results indicate that, in the cloud forests of the Sierra Yalijux, specialised forest species are extinct or at least diminished in remaining primary forest and mostly habitat generalists have survived which also inhabit secondary forest. Even abundant species that are recorded in both habitats (C. ophthalmicus) show lower populations in secondary forest (Table 7). Based on our calculations of population sizes, the forest-dependent species P. mocinno, P. nigra and Z. vilissimus are threatened since they already have small populations. P. mocinno depends on nesting sites (nest holes in rotting trees), only found in primary forest. This species will not survive complete deforestation, even when few breeding holes remain in old secondary forest for approximately 25 years (Renner 2005). P. nigra is feeding in old secondary forest also, but not in slashand-burn agriculture or young secondary forest. Both species are still abundant, but they will disappear when primary forests vanish. Z. vilissimus has twice as many individuals in primary forest than in secondary forest and will suﬀer from deforestation and further fragmentation. All forest endemics from the Central American highlands (Table 7) will be aﬀected by deﬁnition. Contrastingly, generalists and non-forest birds and non-forest breeders will gain from deforestation or at least will not be inﬂuenced. Acknowledgements This study was supported by the German Research Foundation (DFG) and was part of the DFG GK 642/1 ‘‘Valuation and Conservation of Biodiversity in Guatemala’’ and partly by the Gesellschaft fu¨r Tropenornithologie. John Rappole and two unknown reviewers gave valuable comments and Aerin Jacob was helpful with English. This study was performed with the current laws of Guatemala and CONAP authorised the study (No. 139–2001). We also would like to thank the local people of all nationalities and ethnic groups in the community of Chelemha´ supporting our ﬁeldwork and discussing with us interesting aspects of conservation and ‘development’.

References American Ornithologists’ Union 1998. The Checklist of North American birds. American Ornithologists’ Union, Washington DC. American Ornithologists’ Union 2000. 42nd supplement to the American Ornithologists’ Union check-list of North American birds. Auk 117: 847–858. American Ornithologists’ Union 2002. 43rd supplement to the American Ornithologists’ Union check-list of North American birds. Auk 119: 897–906. [512]

1573 Begon M., Harper J. and Townsend C. 1996. Ecology. Individuals, Populations, and Communities. Blackwell, London. Bibby C.J., Burgess N.D. and Hill D.A. 1995. Bird Census Techniques. Neumann, Radebeul. Bierregaard R. 1990. Avian communities in the understorey of Amazonian forest fragments. In: Keast A. (ed.), Biogeography and Ecology of Forest Bird Communities. SPB Academic Publishing, Den Haag, pp. 333–343. Bierregaard R. and Stouﬀer P. 1997. Understorey birds and dynamic habitat mosaics in Amazonian rainforests. In: Laurence W. and Bierregaard R. (eds), Tropical Forest Remnants. University of Chicago Press, Chicago, pp. 139–155. Brooks T.M., Pimm S.L. and Collar N.J. 1997. The extent of deforestation predicts the number of threatened birds in insular south-east Asia. Conservation Biology 11: 382–394. Brooks T.M., Tobias J. and Balmford A. 1999a. Deforestation and bird extinctions in the Atlantic forest. Animal Conservation 2: 211–222. Brooks T.M., Pimm S.L., Kapos V. and Ravilious C. 1999b. Threat from deforestation to montane and lowland forest birds and mammals in insular south-east Asia. Journal of Animal Ecology 68: 1061–1078. Brooks T.M., Pimm S.L. and Oyugi J.O. 1999c. Time lag between deforestation and bird extinction in tropical forest fragments. Conservation Biology 13: 1140–1150. Chao A. and Lee S. 1992. Estimating the number of classes via sample coverage. Journal of the American Statistical Association 87: 210–217. Colwell R. 2000. EstimateS 6.0: Statistical estimation of species richness and shared species from samples. Version 6.0. http://viceroy.eeb.uconn.edu/estimates. Colwell R. and Coddington J. 1994. Estimating terrestrial biodiversity through extrapolation. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 345: 101–118. Dranzoa C. 1998. The avifauna 23 years after logging in Kibale National Park, Uganda. Biodiversity and Conservation 7: 777–797. Edwards E. 1998. A Field Guide to the Birds of Mexico and Adjacent Areas. Belize, Guatemala, and El Salvador. University of Texas Press, Austin. Eisermann K. 2000. Avifaunistisch-o¨kologische Untersuchungen in der Sierra Caquipec, Coban, Alta Verapaz, Guatemala. Fachhochschule Eberswalde, Eberswalde. FAO 2001. State of the Worlds Forests. FAO, Roma. Gaston K.J. and Blackburn T. 2000. Pattern and Process in Macroecology. Blackwell, London. Gilbert G., Gibbons D.W. and Evans J. 2000. Bird Monitoring Methods. A Manual of Techniques for Key UK Species. A & C Black Publishers. Gillespie T.W. 2001. Application of Extinction and Conservation Theories for Forest Birds in Nicaragua. Conservation Biology 15: 699–709. Holbech L. 1996. Faunistic diversity and game production contra human activities in the Ghana high forest zone with references to the western region. Dissertation, University of Copenhagen, Copenhagen. Holland S. 2003. Analytic rarefaction 1.3. http://www.uga.edu/ strata/software/. Howell S.N.G. and Webb S. 1995. A Guide to the Birds of Mexico and Northern Central America. Oxford University Press, Oxford. Hughes J., Daily G. and Ehrlich P. 2002. Conservation of tropical forest birds in countryside habitats. Ecology Letters 5: 121–129. Hurlbert S.H. 1984. Pseudoreplication and the design of ecological ﬁeld experiments. Ecological Monographs 54: 187–211. Islebe G.A. 1995. High elevation coniferous vegetation of Guatemala: A phytosociological approach. Vegetatio 116: 7–24. Johns A. 1992. Vertebrate responses to selective logging: implications for the design of logging systems. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 335: 437–442. Kappelle M. and Brown A.D. 2001. Bosques Nublados Del Neotro´pico. Instituto Nacional de Biodiversidad, San Jose´.

[513]

1574 Krebs C. 1999. Ecological Methodology. Addison-Welsey Educational Publisher, Menlo Park. Lambert F. 1992. The consequences of selective logging for Bornean lowland birds. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 335: 443–457. Land H. 1970. Birds of Guatemala. Livingston Publishing Company, Wynnewood. MacArthur R.H. and Wilson E.O. 1967. The Theory of Island Biogeography. Princeton University Press, Princeton, New Jersey. MAGA 2001. Mapas digitales a escala 1:250,000 elaborados por el Sistema de Informacio´n Geogra´ﬁca (SIG-MAGA). Ministerio de Agricultura, Ganaderı´ a y Alimentacio´n, Guatemala. Magurran A. 1988. Ecological Diversity and its Measurement. Princeton University Press, Princeton. Ma´n˜ez-Costa M.A. and Renner S.C. 2005. Incentives for conservation. The importance of environmental measures in farming systems for bird populations in a fragmented landscape. A case study in Guatemala. In: Markussen M., Marggraf R., Buse R., Garrelts H., Ma´n˜ez-Costa M.A. and Menzel S. (eds), Valuation and Conservation of Biodiversity – Interdisciplinary Perspectives on the Convention on Biological Diversity. Springer Verlag, Berlin, Heidelberg, pp. 343–356. Markussen M. 2004. Waldkonversion und Bodendegradation in Bergnebelwaldgebieten Guatemalas (Alta Verapaz) - Untersuchungen zur Biodiversita¨tsforschung unter besonbderer Beru¨cksichtigung der landschaftso¨kologsichen Kompartimente in sensiblen O¨kosystemen. Ecoregio 11. Shaker Verlag, Berlin. Markussen M. and Renner S.C. 2005. Biotic and abiotic aspects as a base for the conservation of biodiversity in a tropical montane cloud forest (Guatemala). In: Markussen M., Marggraf R., Buse R., Garrelts H., Ma´n˜ez-Costa M.A. and Menzel S. (eds), Valuation and Conservation of Biodiversity – Interdisciplinary Perspectives on the Convention on Biological Diversity. Springer Verlag, Berlin, Heidelberg, pp. 357–372. Marsden S.J., Whiﬃn M., Galetti M. and Fielding A.H. 2004. How well will Brazil’s system of Atlantic forest reserves maintain viable bird populations? Biodiversity and Conservation XX: 1–19. Matthysen E., Lens L., van Dongen S., Verheyen G., Wauters L., Adriansen F. and Dhont A. 1995. Diverse eﬀects of forest fragmentation on a number of animal species. Belgium Journal of Zoology 125: 175–183. McGowan P. and Gillman M. 1997. Assessment of the conservation status of partridges and pheasants in south East Asia. Biodiversity and Conservation 6: 1321–1337. Mozin˜o J.M. 1996. Flora de Guatemala. Ediciones Doce Calles, Madrid. Mu¨hlenberg M., Hovestadt T. and Unger D. 1989. Schutz des Nebelwaldes in Guatemala. O¨kologische Station der Universita¨t Wu¨rzburg, Wu¨rzburg. Myers N., Mittermeier R., Mittermeier C., da Fonseca G. and Kent J. 2000. Biodiversity hotspots for conservation priorities. Nature 403: 853–858. Poulsen B. 1994. Mist netting as a census method for determining species richness and abundances in an Andean cloud forest bird community. Le Gerfaut 84: 39–49. Reitsma L., Hunt P., Burson S. and Steele B. 2002. Site ﬁdelity and ephemeral habitat occupancy: Northern Waterthrush use of Puerto Rican Black Mangroves during non-breeding season. Wilson Bulletin 114: 99–105. Remsen J. 1994. Use and misuse of bird lists in community ecology and conservation. Auk 111: 225–227. Remsen J. and Good D. 1996. Misuse of data from mist net captures to assess abundance in bird populations. Auk 113: 381–398. Renner S.C. 2003. Structure and diversity of cloud forest bird communities in Alta Verapaz, Guatemala, and implications for conservation. Niedersa¨chsische Staats- und Universita¨tsbibliothek, (http://webdoc.sub.gwdg.de/diss/2003/renner/index.html). Renner S.C. 2005. The Resplendent Quetzal (Pharomachrus mocinno) in the Sierra Yalijux, Alta Verapaz, Guatemala. Journal of Ornithology 146: 79–84. Rosenzweig M.L. 1995. Species Diversity in Space and Time. Cambridge University Press, Cambridge.

[514]

1575 Schulze C.H., Waltert M., Kessler P., Pitopang R., Shahabudin, Veddeler D., Steﬀan-Dewenter I., Mu¨hlenberg M., Gradstein S., Leuschner C. and Tscharntke T. 2004. Biodiversity indicator groups of tropical land-use systems: comparing plants, birds and insects. Ecological Applications. Vol. 14(5): 1321–1333. Shankar-Raman T. 2001. Eﬀect of slash-and-burn shifting cultivation on rainforest birds in Miozoram, north-east India. Conservation Biology 15: 685–698. Shankar-Raman T., Rawat G. and Johnsingh A. 1998. Recovery of tropical rainforest avifauna in relation to vegetation succession following shifting cultivation in Mizoram, north-east India. Journal of Applied Ecology 35: 214–231. Shankar-Raman T. and Sukumar R. 2002. Responses of tropical rainforest birds to abandoned plantations, edges and logged forest in the Western Ghats, India. Animal Conservation 5: 201– 216. Stattersﬁeld A. and Capper D. 2000. Threatened Birds of the World. BirdLife International, Lynx Ediciones, London, Barcelona. Stattersﬁeld A., Crosby M., Long A. and Wege D. 1998. Endemic Bird Areas of the World. Priorities for Biodiversity and Conservation. Bird Life International, London. Terborgh J., Robinson S.K., Parker T.A., Munn C. and Pierpont N. 1990. Structure and organization of an Amazon forest bird community. Ecological Monographs 60: 213–238. Terborgh J. 1999. Requiem for Nature. Island Press, Washington DC. Thiollay J.M. 1994a. Disturbance, selective logging and bird diversity: a Neotropical forest study. Biodiversity and Conservation 6: 1155–1173. Thiollay J.M. 1994b. Structure, density and rarity in an Amazonian rainforest bird community. Journal of Tropical Ecology 10: 449–481. Veblen T. 1976. The urgent need for forest conservation in highland Guatemala. Conservation Biology 4: 141–154. Waltert M., Langkau M., Maertens M., Ha¨rtel M., Erasmi S. and Mu¨hlenberg M. 2004. Predicting losses of bird species from deforestation in Central Sulawesi. In: Gerold G., Guhardja E. and Fremerey M. (eds), Land Use, Nature Conservation and the Stability of Rainforest Margins in Southeast Asia. Springer, Berlin, Heidelber, pp. 327–338. Waltert M. and Mu¨hlenberg M. 2001. Zur Beziehung zwischen Abundanz und Habitatqualita¨t: Fangraten territorialer Gelbbartbu¨lbu¨ls Andropadus latirostris. In: Gottschalk E., Barkow A., Mu¨hlenberg M. and Settele J. (eds), Naturschutz und Verhalten. Umweltforschungszentrum Halle Leipzig, Leipzig, pp. 103–110. Winker K., Rappole J.H. and Ramos M. 1995. The use of movement data as an assay of habitat quality. Oecologia 101: 211–216. World Bank. 2001. World development indicators 2001. Worldbank, Washington, DC. World Conservation Monitoring Centre. 1992. Global Biodiversity. Status. Chapman & Hall, London.

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Biodiversity and Conservation (2006) 15:1577–1607 DOI 10.1007/s10531-005-2352-5

Springer 2006

-1

Eﬀects of habitat structure and adjacent habitats on birds in tropical rainforest fragments and shaded plantations in the Western Ghats, India T.R. SHANKAR RAMAN Centre for Ecological Research and Conservation, Nature Conservation Foundation, 3076/5 IV Cross, Gokulam Park, Mysore 570002, India; Address for correspondence: Rainforest Restoration Research Station, 8/364 Cooperative Colony, Valparai 642127, Tamil Nadu, India (e-mail: podocarp@ vsnl.net; phone: +91-4253-221527; fax: +91-821-2513822) Received 31 August 2004; accepted in revised form 4 August 2005

Key words: Agriculture, Anamalai hills, Bird communities, Cardamom, Coﬀee, Countryside biogeography, Fragmentation, Habitat structure and ﬂoristics, Landscape matrix, Tropical wet evergreen forest Abstract. As large nature reserves occupy only a fraction of the earth’s land surface, conservation biologists are critically examining the role of private lands, habitat fragments, and plantations for conservation. This study in a biodiversity hotspot and endemic bird area, the Western Ghats mountains of India, examined the eﬀects of habitat structure, ﬂoristics, and adjacent habitats on bird communities in shade-coﬀee and cardamom plantations and tropical rainforest fragments. Habitat and birds were sampled in 13 sites: six fragments (three relatively isolated and three with canopy connectivity with adjoining shade-coﬀee plantations and forests), six plantations diﬀering in canopy tree species composition (ﬁve coﬀee and one cardamom), and one undisturbed primary rainforest control site in the Anamalai hills. Around 3300 detections of 6000 individual birds belonging to 106 species were obtained. The coﬀee plantations were poorer than rainforest in rainforest bird species, particularly endemic species, but the rustic cardamom plantation with diverse, native rainforest shade trees, had bird species richness and abundance comparable to primary rainforest. Plantations and fragments that adjoined habitats providing greater tree canopy connectivity supported more rainforest and fewer open-forest bird species and individuals than sites that lacked such connectivity. These eﬀects were mediated by strong positive eﬀects of vegetation structure, particularly woody plant variables, cane, and bamboo, on bird community structure. Bird community composition was however positively correlated only to ﬂoristic (tree species) composition of sites. The maintenance or restoration of habitat structure and (shade) tree species composition in shade-coﬀee and cardamom plantations and rainforest fragments can aid in rainforest bird conservation in the regional landscape.

Introduction Fragmentation of tropical forests creates landscapes that typically contain many habitat remnants surrounded by relatively inhospitable environments. Studies of tropical forest fragmentation are providing increasing evidence that the ability of species to survive in fragments may depend on surrounding habitats and whether the species uses such habitats (Stouﬀer and Bierregaard 1995a, b; Laurance et al. 1997; Renjifo 2001). This landscape approach to [517]

1578 conservation of rainforest fragments requires an assessment of the conservation values per se of lands outside conservation reserves that may include habitat fragments, secondary forests, private lands, and countryside habitats such as agricultural plantations (Brown and Lugo 1990; Turner and Corlett 1996; Daily 2001). Approaches that supplement habitat protection by conserving wildlife habitats adjoining protected areas, increasing landscape-level connectivity of patches, and restoring degraded areas are thus gaining ground as a means to conserve biological diversity (Laurance et al. 1997). Such an approach to conservation is pertinent to the Western Ghats hill ranges of India. This hill chain is recognised as a global biodiversity hotspot (Myers et al. 2000), one of the Global 200 most important eco-regions (Olson and Dinerstein 1998), and an Endemic Bird Area (Stattersﬁeld et al. 1998). The Western Ghats faces severe threats from human disturbance due to deforestation, developmental activities, conversion to plantations, and habitat fragmentation (Nair 1991). Between 1920 and 1990, forest cover in the region declined by 40%, resulting in a four-fold increase in the number of fragments, and an 83% reduction in size of forest patches (Menon and Bawa 1997). This is partly due to this region being one of the hotspots with the highest human population densities (Cincotta et al. 2000). One of the major causes of forest fragmentation in the Western Ghats is the spread of plantations, particularly tea, coﬀee, and Eucalyptus. The area under plantations is large and growing. Tea plantations in the south Indian states increased by 17.7% in the period 1987–1998 from 74,765 to 87,993 ha (Tea Board 2002). Large areas of Eucalyptus plantations also occur with tea as it is used as fuel-wood for tea-curing in the factories. Similarly, during 1999–2000, the US$ 447 million Indian coﬀee industry had plantations of about 340,306 ha, almost entirely in the Western Ghats region of southern India, having increased in area coverage by 25.7% from 270,821 ha in 1990–1991 (Coﬀee Board 2001). These coﬀee plantations, particularly where grown traditionally under the shade of native forest trees, form a substantial area of forest canopy cover in the Western Ghats. Although shade-coﬀee plantations are known to support many forest species, especially birds (Estrada et al. 1997; Greenberg et al. 1997a, b; Perfecto and Vandermeer 2002; Tejeda-Cruz and Sutherland 2004), their conservation value is still debated (Rappole et al. 2003). This is partly because there is considerable variation in bird species richness and composition across coﬀee plantations diﬀering in habitat structure and shade tree mixtures (Greenberg et al. 1997a, b; Wunderle 1999; Perfecto et al. 2003; Tejeda-Cruz and Sutherland 2004). Although it has been suggested that such plantations may act as eﬀective refuges and buﬀer habitats in fragmented landscapes (Shahabuddin 1997), the landscape-level inﬂuence of forest fragments and plantations on each other is poorly understood (Perfecto et al. 2003). This study examines bird communities in a fragmented landscape of plantations and rainforest remnants in the Anamalai hills, southern Western Ghats of India. The study had two main objectives: [518]

1579 1. What is the inﬂuence of the landscape matrix adjacent to or surrounding fragments on tropical rainforest birds? This question is explored by comparing fragments that adjoin shade-coﬀee plantations or other forest types with those that are ‘‘isolated’’ being surrounded by tea plantations, a relatively inhospitable habitat for birds. 2. What is the inﬂuence of the composition of shade tree species mixture in coﬀee estates on the bird community? Rainforest sites were compared with plantations with a near-monoculture of exotic shade tree species, with mixed canopy, and with diverse, native rainforest tree canopy to test the hypothesis that greater similarity in tree species composition with rainforest supports a more rainforest-like bird community.

Study area The Western Ghats is a 1600 km long chain of hills running along the west coast of the Indian Peninsula (8–21 N) and is recognised as a unique biogeographic province (Mani 1974). Moist forests, including tropical wet evergreen rainforest, are found largely south of 16 N, particularly south of the Palghat Gap at 11 N, a region often called the southern Western Ghats (Pascal 1988). The Anamalai hill ranges are a major conservation area in the southern Western Ghats containing mid-elevation rainforest in the Indira Gandhi Wildlife Sanctuary (958 km2, 1012¢ N to 1035¢ N and 7649¢ E to 7724¢ E) and in private-owned fragments on the Valparai plateau (Figure 1). The natural vegetation of this region, receiving around 3500 mm of rainfall annually, particularly during the southwest monsoon (June–September), is classiﬁed as mid-elevation tropical wet evergreen forest of the Cullenia–Mesua–Palaquium type (Pascal 1988). The Valparai plateau contains around 220 km2 of tea, coﬀee, and cardamom plantations surrounded by Wildlife Sanctuaries, National Parks, and Reserved Forest. Clearing of primary rainforest for plantations began in 1896 and was mostly complete by the 1930s, although some clearing and conversion of coﬀee and cardamom to tea plantations continues to the present day (Congreve 1942, Raman and Mudappa 2003a). The plateau has one town (Valparai) and a population of over 106,000 people (1991 Census), mostly estate labourers, scattered across the town and estates. At least 25 rainforest fragments have been identiﬁed so far in and around the Valparai plateau (Umapathy and Kumar 2000) and additional sites do exist. Besides two large fragments (2000 and 2600 ha) within the Indira Gandhi Wildlife Sanctuary, the remaining rainforests all occur as fragments of 0.3–650 ha in size, much of which is on private land. These fragments are vital for conservation as they contain signiﬁcant proportions of the native fauna (Umapathy and Kumar 2000) and provide landscape-level connectivity between patches critical for wide-ranging species such as the Great Hornbill (Buceros bicornis, Raman and Mudappa 2003b), Asian elephants Elephas maximus, tigers Panthera tigris, and wild dogs Cuon alpinus (Kumar et al. 2002). [519]

1580

[520] Figure 1. Map of the Indira Gandhi Wildlife Sanctuary showing location of the plantation areas in the Valparai plateau (within dashed lines), some rainforest fragments (light grey), and reservoirs (stippled) on the Valparai plateau.

1581 Avifauna The Western Ghats contains 16 species of restricted-range birds including 12 of near-threatened conservation status (Collar et al. 1994; Stattersﬁeld et al. 1998) and one endangered, three vulnerable, and seven near-threatened bird species, of which all but two inhabit tropical rainforests (BirdLife International 2001). A number of other rare species with range largely restricted to the Western Ghats and other mountain ranges in the Indian peninsula, Sri Lanka, or the Himalaya, also occur in these tropical rainforests: e.g. Malabar Trogon Harpactes fasciatus, Asian Fairy Bluebird Irena puella, Mountain Imperial Pigeon Ducula badia, Jerdon’s Baza Aviceda jerdoni, Black-crested Baza A. leuphotes, Sri Lanka Frogmouth Batrachostomus moniliger. Of the 230 bird species identiﬁed in the Anamalai hills, around 90 are typical rainforest birds, including 13 endemic species (Kannan 1998; Raman 2001).

Selection of study strata and sites Thirteen sites were selected for vegetation and bird sampling: six rainforest fragments, six plantation sites, and a ‘control’ or reference site containing a large and relatively undisturbed tract of tropical rainforest in the same elevation range (Table 1). Of the six fragments, three were relatively isolated as they occurred within tea plantations that had a very sparse canopy of pruned, non-indigenous silver oak (Grevillea robusta) trees planted at 12 m · 12 m spacing. The remaining three fragments adjoined shade-coﬀee estates with extensive canopy cover. The ﬁve shade-coﬀee plantations diﬀered in the canopy tree species composition and the cardamom plantation, maintained by a local tribal settlement, contained a canopy entirely of native rainforest tree species (rustic cardamom, see Table 1). Three plantation sites adjoined continuous forest tracts within the Indira Gandhi Wildlife Sanctuary, whereas the remaining three sites only adjoined smaller fragments that were in private lands. The control site was an approximately 2600 ha tract of tropical rainforest (Iyerpadi–Akkamalai complex) within the Indira Gandhi Wildlife Sanctuary adjoining the plantations on the Valparai plateau. All sites were within a restricted elevation range of 900–1400 m containing mid-elevation tropical wet evergreen forest vegetation (Pascal 1988). Sites (except largest fragments and plantations) were mapped by walking around them with a hand-held GPS (Garmin 12 XL) with the track option activated. The larger fragments and plantation sites were digitised using a combination of Survey of India 1:50,000 topographic sheets, GPS tracking, and satellite imagery. Maps were prepared and areas of sites estimated using MapInfo Professional software (version 7.0). Areas of plantation sites are approximate as exact areas and boundaries were not indicated by all the private companies. [521]

1582 Table 1. Study sites selected for vegetation and bird sampling in the Valparai plateau and Indira Gandhi Wildlife Sanctuary (IGWLS), Anamalai hills; RF = rainforest fragment, P = plantation. Code

Site (Stratum, adjacent habitat canopy connectivity)

Description

A B

Iyerpadi–Akkamalai (Control, High) Andiparai (RF, Low)

C

Injipara (RF, Low)

D

Korangumudi (RF, Low)

E

Manamboli (RF, High)

F

Puthuthottam Fragment (RF, High) Tata Finlay Fragment (RF, High) Puthuthottam Coﬀee (P, Low)

2600 ha primary rainforest in IGWLS with very low disturbance levels 200 ha fragment surrounded largely by tea estates, connected by narrow corridor to the control site 18 ha fragment, an abandoned cardamom plantation, with many exotic shade trees in the canopy, surrounded by tea estates and a logged Eucalyptus fuel clearing area 56 ha fragment, an abandoned cardamom plantation with highly disturbed rainforest canopy, more isolated since conversion of adjoining coﬀee to tea plantation in 2000 200 ha primary rainforest fragment within IGWLS continuous with large area of forest 92 ha fragment, an abandoned cardamom plantation, with highly disturbed rainforest canopy 33 ha moderately disturbed fragment adjoining coﬀee estates with mixed native and exotic tree canopy c. 50 ha, mixed canopy dominated by the exotics Maesopsis emenii, Erythrina indica and Eucalyptus sp., with few native trees such as Artocarpus heterophyllus; adjoins Puthuthottam fragment 45 ha, dominantly exotic tree canopy of silver oak Grevillea robusta; adjoins Korangumudi fragment c. 100 ha, mixed tree canopy of exotics such as Erythrina indica andMaesopsis emenii with existing native species such as Cullenia exarillata, Mesua ferrea, and Palaquium ellipticum; adjoins Tata Finlay fragment c. 50 ha, dominantly exotic tree canopy of Erythrina indica, continuous with Manamboli and forests in IGWLS c. 80 ha, mostly exotic tree canopy of Erythrina indica and Maesopsis emenii, continuous with rainforest fragments and forests in IGWLS c. 60 ha, established by clearing ground vegetation under a completely native canopy of rainforest tree species, continuous with rainforest fragments and forests in IGWLS

G H

I

Siva Coﬀee (P, Low)

J

Tata Finlay Coﬀee (P, Low)

K

Surulimalai Coﬀee (P, High) Old Valparai Coﬀee (P, High)

L

M

Sankarankudi Cardamom (P, High)

Methods Vegetation sampling In 12 sites, densities of trees greater than 30 cm girth at breast height (GBH at 1.3 m) were estimated using 15–25 point-centred quarter plots (PCQ sample of 60–100 trees/site, Krebs 1989). In the Siva Coﬀee plantation it was not possible to do PCQ plots and hence 5 m radius circular plots (N = 25 plots and 52 [522]

1583 trees) were laid and an additional 28 random trees were identiﬁed to species. Tree species were identiﬁed using available guides (Gamble and Fischer 1935; Pascal and Ramesh 1997). Shrubs (or in plantations: coﬀee bushes, cardamom plants) were counted in 25 plots of 2 m radius and the presence of cane (Calamus sp.), bamboos, and lianas was recorded within 5 m radius of the centres of these 25 plots. Elevation was noted at these points using an altimeter. Canopy variables (height, cover, stratiﬁcation) and leaf litter depth were measured at 25 points, evenly spaced 25 m apart as described elsewhere (Raman and Sukumar 2002).

Bird sampling I attempted to sample all sites in a relatively uniform and eﬃcient manner over the winter and breeding season (December to May) when both migrants and residents were present in the study area. Point counts (Verner 1985; Bibby et al. 1992; Ralph et al. 1995) were used for bird surveys. Point count surveys of 5 min duration were carried out during the ﬁrst three hours after sunrise when bird activity was highest (see Raman 2003 for further details). Densities were estimated using a ﬁxed radius (50 m) approach as they are known to be highly correlated to variable-radius point count estimates across species (Raman 2003). As some degraded fragment and plantation sites contained relatively more open vegetation some bias due to detectability diﬀerences may have existed and the results can only be taken as a conservative assessment of the eﬀects of fragmentation and plantations. In each site, 30 point count surveys (25 in Sankarankudi cardamom and 26 in Manamboli) were carried out yielding 173–308 detections and an estimated 321–633 individual birds per site. I attempted to ensure independence of data points to the extent possible by spacing out points and survey days. Successive points sampled in any day were at least 100 m apart to avoid overlap and intermediate points were sampled on diﬀerent days. Although points sampled on diﬀerent days overlapped to some extent, the procedure followed ensured uniform coverage of the site. Data analysis For each site, tree density and basal area were calculated using the PCQ method (Krebs 1989). Average values across replicate samples in each site were calculated for other habitat variables. Vertical stratiﬁcation (average number of strata with foliage) and its coeﬃcient of variation (indexing horizontal heterogeneity) were calculated following Raman et al. (1998). Tree species richness was indexed by the number of tree species recorded in the PCQ plots. The vegetation data was summarised by principal components analysis to determine fewer uncorrelated components. The factor matrix was rotated by [523]

1584 the Varimax method to assist in interpretation and display of the results (Norusˇ is 1990). The 106 bird species recorded during the study were classiﬁed into rainforest and open-forest (non-rainforest) birds. The rainforest species included birds that normally occurred even in mature undisturbed rainforests in the southern Western Ghats (Ali and Ripley 1983; Raman 2001). Open-forest birds occurred only in disturbed rainforest fragments or in naturally drier and open habitats and never in mature, undisturbed tropical rainforest. Analyses were performed using all species, only rainforest species, and only open-forest species. Bird species richness (per point and cumulative list) and bird abundance per point were major parameters of interest. Flock sizes for aural detections of birds were randomly selected from ﬂock-size distribution data of each species (Raman 2003). As only 25 point count surveys were carried out in one site, I obtained rarefaction estimates of bird species richness for all sites for 24 sampled points using the program EstimateS (Colwell and Coddington 1994; Colwell 1997; 100 permutations, sampling without replacement). Cumulative species richness and abundance (individuals/ha) of birds belonging to diﬀerent species categories was also estimated: Western Ghats endemics, priority species, migrants (all, rainforest, and open-forest migrants). Priority species were deﬁned as birds of restricted-range (Stattersﬁeld et al. 1998), discontinuous distribution (in rainforests of southwest India, Sri Lanka, and northeast India; Ali and Ripley 1983), or near-threatened (Collar et al. 1994) and excluded endemics. The eﬀects of stratum (rainforest fragment, plantation, or control), adjacent habitat (with high or low tree canopy connectivity) and point count (repeated measure) on bird richness and abundance were assessed in a multivariate analysis of variance (MANOVA) as an alternative to repeated-measures analysis of variance (Zar 1999). To jointly examine the inﬂuence of area, adjacent habitat, and vegetation structure, multiple linear regression was used to examine relationships between bird community parameters and four independent variables: site area, level of canopy connectivity in adjacent habitat (scored as 1 – low, 2 – medium, and 3 – high as in Table 1), and scores of two vegetation components extracted by the principal components analysis (PC1 and PC2, see Results). The analysis was carried out on the mean values of bird community parameters estimated for the N = 13 sites and a backward stepwise selection procedure was used to identify statistically signiﬁcant variables (Zar 1999). As the nature (positive versus negative) and strength of inﬂuence of these variables was of primary interest, only the standardized regression coeﬃcients (b, with signiﬁcance levels from t-tests) are presented and ANOVA and other regression diagnostics are omitted. The bird species-abundance data was used to estimate similarities between sites in bird community composition using the Morisita index (Wolda 1981). Structural dissimilarity (using distribution of foliage in diﬀerent vertical strata) and ﬂoristic dissimilarity (tree species composition data) were estimated as 1–Morisita index (Raman et al. 1998). Partial Mantel tests were used to assess [524]

1585 the inﬂuence of ﬂoristic and structural dissimilarity on change in bird community composition with 10,000 permutations to assess statistical signiﬁcance (Hemelrijk 1990; Manly 1994). Analysis of similarities (ANOSIM) with the Bray–Curtis index was used to assess signiﬁcance of bird community compositional change between strata (Clarke and Warwick 1994; Clarke and Gorley 2001). For analysis of habitat use by species, a simple deviation index (D) was computed for each habitat stratum (rainforest control, fragment, shade-coﬀee, and cardamom) as: Dij = (Obs xij Exp xij)/(Obs xij + Exp xij), where Obs xij= the average detections of the species i across replicate sites in stratum j, and Exp xij = (nj/N)* ni, where ni=number of detections of species i, nj=number of bird detections in stratum j, and N = total number of detections. Values of the deviation index ranged from 1 (avoidance) to +1 (preference). Values £ 0.25 or ‡0.25 were considered to indicate signiﬁcant avoidance or usage of the habitat stratum. Results Vegetation structure in fragments and plantations Foliage proﬁle and vegetation attributes showed distinct diﬀerences across sites. The foliage proﬁle data on frequencies of foliage presence at diﬀerent vertical strata showed highly signiﬁcant variation across the four habitats: primary rainforest control, fragment, coﬀee, and cardamom (v2 = 89.92, df = 21, p < 0.001, Table 2). At the highest strata (>32 m), shade-coﬀee plantations practically lacked canopy foliage whereas other sites had 20–24% of the points with foliage. The shade-coﬀee plantations tended to have foliage concentrated in the 0–2 m interval (coﬀee shrubs) and 8–16 m interval (shade trees), with less foliage in other strata. The cardamom plantation had foliage concentrated in the 0–2 m interval (cardamom plants), and in the two highest strata (tall rainforest tree species canopy), whereas intermediate strata (2–16 m) had less foliage than rainforest as small trees and shrubs had been Table 2. Variation in foliage distribution at diﬀerent vertical levels in plantations, rainforest fragments and primary rainforest control sites in the Anamalai hills. Vertical strata (m) >32 24–32 16–24 8–16 4–8 2–4 1–2 0–1

Control

Fragment

Coﬀee

20.0 45.0 80.0 65.0 80.0 75.0 85.0 90.0

20.0 46.0 50.7 60.7 62.0 58.0 76.7 96.0

– 8.0 45.6 83.2 59.2 48.0 94.4 95.2

Tabled values are means of estimates across sites in each stratum. [525]

Cardamom 24.0 76.0 72.0 56.0 48.0 32.0 72.0 88.0

1586 cleared for planting cardamom (Table 2). Tree density, canopy cover, and litter depth were highest in primary rainforest, intermediate in fragments, and least in plantations. Canopy height and basal area were highest in the cardamom plantation, and shrub density was highest in fragments (Table 3). Notably, bamboos, canes, and lianas were absent from the plantation sites due to their elimination during plantation maintenance and weeding. Principal components analysis of the eleven vegetation variables extracted two components (PC1 and PC2) accounting for 76.8% of the total variation in the data-set (Table 4). PC1 was signiﬁcantly positively correlated to variables reﬂecting the density of woody plants, cane, and bamboo. PC2 was positively correlated to vertical structure and canopy closure and negatively to horizontal patchiness of sites (Table 4). The ordination of the sites using PC scores shows the primary rainforest and two large fragments (Manamboli and Andiparai) forming a cluster at the top right indicating a well developed woody plant community, vertical structure, and canopy closure (Figure 2). The plantation sites aggregate on the left indicating poorer development of Table 3. Vegetation characteristics of the study strata in the Anamalai hills. Parameter

Rainforest Control

Number of sites (N) Tree density (no./ha)

1 583.00 SE

Basal area (m2/ha)

61.38 SE

Altitude (m)

1304 SE

Canopy cover (%)

99.40 SE

Canopy height (m)

26.05 SE

Shrub density (no./plot)

9.75 SE

Cut trees (no./plot) SE Vertical stratiﬁcation (no. of strata)

0.40 0.15 5.35

SE Horizontal heterogeneity Leaf litter depth (cm)

6.25 7.33 SE

Bamboo prevalence (proportion of plots) Cane prevalence (proportion of plots) Liana prevalence (proportion of plots) Coﬀee density (no./plot)

0.05 0.40 0.45 SE

Cardamom density (no./plot) SE

Plantation Fragment

Coﬀee

6 349.00 57.16 62.28 12.76 1065 64.6 88.71 4.38 23.28 1.86 13.42 2.65 0.74 0.20 4.71 0.29 5.00 4.31 0.62 0.05 0.12 0.24

5 236.60 62.78 27.83 5.74 1118 27.8 68.79 8.72 15.25 1.55 0.51 0.45 0.00 4.14 0.51 4.92 3.13 0.19 0.00 0.00 0.00 4.88 0.37 0.00 0.00

Tabled values are means and standard errors (SE) across sites in each stratum. [526]

Cardamom 1 229.00 89.54 1074 87.72 28.52 0.00 0.00 4.68 5.34 2.52 0.27 0.00 0.00 0.00 0.00 0.00 6.36 0.61

1587 Table 4. Principal components analysis of vegetation variables: correlations of original variables with extracted components. Variable

PC1

PC2

Tree density Basal area Shrub density Litter depth Bamboo prevalence Cane prevalence Liana prevalence Canopy cover Canopy height Vertical stratiﬁcation Horizontal heterogeneity

0.801*** 0.682** 0.741** 0.849*** 0.845*** 0.956*** 0.968*** 0.455 0.442 0.268 0.321

0.198 0.393 0.152 0.213 0.032 0.088 0.131 0.874*** 0.569* 0.938*** 0.821***

Eigenvalue Cumulative variance explained (%)

5.519 50.17

2.929 76.79

*p < 0.05, **p < 0.01, ***p < 0.005.

Figure 2. Ordination of primary rainforest control (n), fragment (m), and plantation (d) sites in and around the Valparai plateau using principal components analysis of vegetation variables. Site codes as in Table 1.

woody plants, but varied in vertical structure from poorly developed (Surulimalai and Siva coﬀee low on PC2) to well developed (Old Valparai coﬀee and Sankarankudi cardamom). The remaining four fragments were structurally interspersed among plantation sites, with the more disturbed ones (Korangumudi and Injipara) being low on PC2 due to poorly developed vertical structure (Figure 2). [527]

1588 Bird community structure in plantations and fragments Point count sampling yielded 3299 bird detections with an estimated 5987 individuals belonging to 106 species across the 13 sites. Of the 106 bird species, 70 (66%) were rainforest birds and 36 (34%) were open-forest (non-rainforest) birds. Birds detected at least thrice during sampling comprised 78 species, including 57 (73%) rainforest and 21 (27%) open-forest species. The total numbers of bird species seen in the four main habitat strata were: 43 (primary rainforest control – one site), 95 (rainforest fragments – ﬁve sites), 76 (shadecoﬀee plantations – ﬁve sites), and 49 (cardamom plantation – one site). The percentage of rainforest bird species was highest in the primary rainforest control (95.3%) and the cardamom plantation under natural shade (89.8%). More open-forest birds had inﬁltrated into rainforest fragments and shadecoﬀee plantations and the percentage of rainforest bird species in the community was lower at 70.5% and 59.2%, respectively, in these strata. These diﬀerences in the number of rainforest vs. open-forest species across the four habitat strata were statistically signiﬁcant v2 = 34.1, df = 3, p < 0.001).

Bird species richness and abundance: eﬀects of stratum and adjacent habitat Both stratum (control vs. rainforest fragment vs. plantation) and adjacent habitat (with low vs. high canopy connectivity) had signiﬁcant eﬀects on bird species richness and abundance (MANOVA, p < 0.001, Table 5). The repeated measure (point), which represented the replicate samples taken within each site, had no signiﬁcant direct eﬀect or 2-way or 3-way interactions with the other main eﬀects (stratum and connectivity) in the multivariate analysis (Table 5). However, there was a signiﬁcant 2-way interaction between stratum and connectivity (p < 0.001, Table 5).

Table 5. Results of multivariate analysis of variance (MANOVA) on the eﬀects of habitat stratum and connectivity on total, rainforest, and open-forest bird species richness and abundance in point count samples in the Anamalai hills. Main Eﬀects Intercept Stratum Adjacent habitat Point 2-way interactions Stratum · Adjacent habitat Stratum · Point Connectivity · Point 3-way interaction Stratum · Adjacent habitat · Point

Wilks’ k

F

0.097 0.679 0.785 0.665

529.42 26.93 7.32 0.85

0.903 0.694 0.458 0.647

[528]

Hypothesis df

Error df

P

4 4 8 116

228 228 456 908.6

0.000 0.000 0.000 0.871

6.12 0.75 0.85

4 116 232

228 908.6 913.3

0.000 0.973 0.935

0.91

116

908.6

0.747

1589 When individual variables were examined, habitat stratum had a signiﬁcant eﬀect (p < 0.001) on rainforest bird species richness with plantations having per-point richness values about one-half to a third lower than in the rainforest control. Rainforest fragments had up to one-fourth lower rainforest bird species richness than control sites but the means were higher than in plantations (Figure 3). The presence of adjacent habitats with higher canopy connectivity also resulted in higher rainforest bird species richness and abundance in plantations and fragments (p < 0.001). The repeated-measure (point) did not have a signiﬁcant eﬀect on species richness (p = 0.564) but was signiﬁcant for rainforest bird abundance (p = 0.008). There were no signiﬁcant 2-way or 3-way interactions except for an interaction between connectivity and the repeated measure factor (point) for rainforest bird abundance (p = 0.002). Stratum and adjacent habitat had signiﬁcant (p < 0.001) but reverse eﬀects on open-forest birds with the primary rainforest control site having fewest, fragments intermediate, and plantations highest richness and abundance (Figure 3). Fragments that adjoined shaded plantations with higher canopy connectivity had lower open-forest bird richness and abundance. For plantation sites, there was little eﬀect of adjoining low and high canopy connectivity habitats; thereby resulting in a signiﬁcant interaction between connectivity and stratum for open-forest bird species richness and abundance (p < 0.001). Openforest bird species richness and abundance showed no signiﬁcant direct or interaction eﬀects with the repeated-measure factor (point). As in the case of rainforest birds, richness and abundance of all birds combined showed signiﬁcant eﬀects of stratum (p < 0.001) and adjacent habitat (p < 0.009). In fragments, however, adjoining habitats with better canopy connectivity had little eﬀect on all birds taken together, as the positive eﬀect on rainforest birds was compensated by the negative eﬀect on open-forest birds (Figure 3). In plantation sites, total bird species richness and abundance was enhanced in sites that adjoined rainforest fragments mainly due to the positive eﬀects it had on rainforest birds. There was thus a signiﬁcant interaction eﬀect of stratum and adjacent habitat on total bird species richness (p < 0.001) and abundance (p = 0.001). There was no signiﬁcant direct or interaction eﬀect of the repeated measure (point) on total bird species richness. The repeated measure factor had a signiﬁcant direct (p = 0.006) eﬀect, two-way interaction with adjacent habitat (p = 0.001), and 3-way interaction for total bird abundance.

Bird community composition: eﬀects of stratum and adjacent habitat The eﬀects of habitat stratum and adjacent habitat were tested using analysis of similarities (ANOSIM, using the Bray–Curtis similarity index between sites and 1000 random permutations). As suﬃcient replicate sites were unavailable for a simultaneous two-way analysis of both factors, each factor was analysed separately. Bird community composition diﬀered signiﬁcantly between the two [529]

1590

Figure 3. Eﬀects of habitat stratum (rainforest fragment, primary rainforest control, and plantations) and adjacent habitat (with low vs. high canopy connectivity) on bird community variables in the Anamalai hills. Figures illustrate estimated means per point and their standard errors for bird species richness (panels on the left) and bird abundance (panels on the right).

[530]

1591 habitat strata, rainforests vs. plantations (global R = 0.365, p = 0.023). Diﬀerences between sites diﬀering in adjacent habitats’ canopy connectivity were not signiﬁcant (R = 0.111, p = 0.162) when only two categories of connectivity was considered (low vs. high, where the latter includes the primary rainforest control site). The analysis was repeated with four categories: rainforests adjoining habitats with low and high canopy connectivity (RL, RH), and plantations adjoining habitats with low and high canopy connectivity (PL, PH). Bird community composition varied signiﬁcantly across these four categories (global R = 0.314, p = 0.042). Pair-wise comparison of categories revealed signiﬁcant diﬀerences only between RH and PL (R = 0.87, p = 0.029, 1 of 35 possible permutations) and near signiﬁcance between RL and RH (R = 0.296, p = 0.086, 3 of 35 possible permutations) and between RL and PL (R = 0.519, p = 0.10, 1 of 10 possible permutations). Diﬀerences in bird community composition between rainforest sites and plantation sites that adjoined rainforest fragments with high canopy connectivity (PH) were not statistically signiﬁcant (R < 0.26, p > 0.17). Bird community structure: correlations with vegetation structure and ﬂoristics The species richness and abundance of bird species categories (all, rainforest, open-forest, endemics, priority species, rainforest migrants, and all migrants) was compared between rainforest and plantation sites. Except for open-forest birds and all migrants, values were lower in plantations than rainforests (Table 6). Species richness and density of rainforest birds was 43–47% lower in plantations than in rainforest sites. Although the richness of priority species and rainforest migrants was not signiﬁcantly diﬀerent between the strata, the abundance of these categories was signiﬁcantly lower in plantations (Table 6). Multiple regression analysis indicated a signiﬁcant positive inﬂuence of PC1 on rainforest and rarefaction bird species richness as well as on the abundance of all birds, rainforest birds, endemic birds, and priority species (Table 6). The results indicated that woody plant variables, cane, liana, and bamboo, represented in PC1 had a generally positive eﬀect on rainforest birds, endemic and priority species and a negative eﬀect on open-forest bird species richness. Canopy structural variables represented on PC2 had signiﬁcant positive eﬀects on species richness of all birds taken together and for the subset of rainforest birds as well as on the abundance of priority species and rainforest migrants. PC2 had a negative eﬀect only on open-forest bird abundance (Table 6). The level of canopy connectivity in adjacent habitat was signiﬁcantly positively related only to richness of priority species. Site area did not appear to have a signiﬁcant inﬂuence on any of these variables barring a weak positive eﬀect on migrant species richness (Table 6). Mantel tests were used to examine the eﬀects of dissimilarity in vegetation structure and ﬂoristics (tree species composition) on bird community dissimilarity between sites. Bird community dissimilarity was strongly positively [531]

1592 Table 6. Cumulative species richness and abundance (individuals/ha) of various categories of birds in rainforest and shade-coﬀee and cardamom plantation sites in the Anamalai hills and signiﬁcant coeﬃcients from multiple regression with area, adjoining habitat connectivity level, and habitat components (PC1 and PC2) as independent variables. Rainforests Plantations Mann– Standardized regression coeﬃcient (b) Whitney Mean SE

Bird species richness Alla Rainforesta Open-foresta Rarefaction estimate Endemic Priority Rainforest migrants All migrants Bird abundance All Rainforest Open-forest Endemic Priority Rainforest migrants All migrants

Mean SE

U

28.6 24.7 3.9 38.6 5.0 11.9 5.4 7.4

0.97 21.2 0.99 14.0 1.37 7.2 1.69 28.1 0.31 3.2 0.91 8.8 0.53 5.0 0.69 8.3

2.17 2.11 1.40 3.43 0.65 1.72 0.26 0.49

3.5** 2.5** 11.0 6.0* 6.0* 10.5 18.0 15.5

22.7 20.3 2.5 2.4 5.8 2.4 3.1

0.94 15.8 1.37 11.1 0.92 4.7 0.43 0.9 0.58 3.3 0.16 1.6 0.29 2.8

1.48 3.0** 2.10 4.0* 0.89 13.0 0.43 5.0* 0.78 6.0* 0.20 5.0* 0.47 14.0

Area Adjoining habitat

– – – – – – – 0.545+

– – – – – 0.621* – –

– – – – – – –

– – – – – – –

PC1

– 0.676* 0.728** 0.503+ 0.586* – – –

PC2

0.554* 0.489* – 0.433+ – – – –

0.683** – 0.761** – – 0.659* 0.666* – 0.644** 0.507* – 0.578* – –

p £ 0.10, *p £ 0.05, **p £ 0.01 Includes only species detected >2 times in the pooled point count samples in each site. Mean and standard error (SE) were calculated from 7 rainforest and 6 plantations sites. + a

correlated to ﬂoristic dissimilarity (Mantel test, Kr = 346, p < 0.001) and weakly to structural dissimilarity (Kr = 101, p = 0.092). When the eﬀects of the positive correlation between structural and ﬂoristic dissimilarities were controlled using partial Mantel tests, only ﬂoristic dissimilarity was positively correlated to bird community dissimilarity (partial T = 0.409, p < 0.001) and structural dissimilarity had a non-signiﬁcant eﬀect (partial T = 0.057, p = 0.73). Identical results were obtained when only the six plantation sites and the primary rainforest control site were included in the analysis (N = 7 sites, 21 pair-wise similarities).

Bird species distributions in rainforests and plantations Analysis of species habitat use with the deviation index showed that most open-forest species (residents and migrants) occurred more often than expected in shade-coﬀee plantations, and less often than expected in rainforest control, [532]

1593 fragments, and cardamom plantations (Appendix). A majority of rainforest residents showed no signiﬁcant preference or avoidance of rainforest control and fragment sites, whereas their abundance tended to be negatively inﬂuenced by plantations. There were a number of exceptions, however, and many rainforest birds persisted in shade-coﬀee plantations, being absent or found less often than expected in rainforest control and cardamom sites (possibly because of the lower sampling intensity in these two sites). Three rainforest priority species showed signiﬁcant preference for rainforest control sites (Yellow-browed Bulbul, Large Woodshrike, and Malabar Trogon, see Appendix for scientiﬁc names). The latter species along with Little Spiderhunter and Mountain Imperial Pigeon also occurred more often than expected in the cardamom plantation (Appendix). Among rainforest migrants, positive preference was shown by Grey and Forest Wagtails to shade-coﬀee, by Rusty-tailed Flycatcher to cardamom, and by Large-billed Leaf Warbler to the rainforest control site. Of the ten species of endemics recorded, the Crimson-backed Sunbird and White-bellied Blue Flycatcher appeared to prefer the rainforest control and cardamom plantation sites. In addition, the Nilgiri Flycatcher and Black-and-Orange Flycatcher chieﬂy used the rainforest control site. Shadecoﬀee plantations were mostly used less by endemics, except for the Malabar Grey Hornbill and Rufous Babbler. The three endemics not recorded from the control site during sampling were typically lower-elevation birds (Malabar Grey Hornbill, Malabar Parakeet) and forest edge species (Rufous Babbler). These three species have been recorded from the control site during supplementary observations.

Discussion Bird community change: eﬀects of stratum and adjacent habitats An increasing number of studies show the importance of habitat in the surrounding landscape matrix on bird communities of tropical forest fragments (Stouﬀer and Bierregaard 1995a, b, Daily et al. 2001; Renjifo 2001; Luck and Daily 2003). These studies have shown that structurally complex matrices have greater potential for supporting populations of forest birds than open areas such as pastures. In the present study, this general pattern is supported in the comparison of forest fragments that adjoin sites with better canopy cover and connectivity (shade-coﬀee plantations) versus more isolated sites (mostly surrounded by relatively treeless tea plantations). The major diﬀerence in bird community composition was between rainforest fragments that adjoined sites with high canopy connectivity and plantations that adjoined sites with low canopy connectivity. Obviously, conversion to plantations followed by isolation from forests has a greater eﬀect on bird community change than either factor alone. While the eﬀects of adjacent habitat were [533]

1594 found to be signiﬁcant in addition to habitat stratum for a suite of bird community variables in the MANOVA, this eﬀect did not emerge as very signiﬁcant in multiple regression analyses that included vegetation structure components (PC1 and PC2) as independent variables. This suggests that the observed eﬀects of adjacent habitat are mediated mainly by changes in vegetation structure, for instance, through the presence or absence of hard edges or the distribution of rainforest versus open-forest species in the adjacent habitat. Although the beneﬁt to rainforest birds by increased canopy connectivity in adjoining sites is easily understood, the factors inhibiting openforest birds in fragments adjoining sites with better canopy connectivity is not directly apparent. Possible explanations include better-developed habitat structure in such fragments due to absence of hard edges, competitive eﬀects of persisting rainforest birds, or the paucity of adjoining open habitats that can act as source pools for open-forest birds. Among the suite of variables that may inﬂuence bird community structure in these sites, habitat structure and ﬂoristics (tree species composition) appear to have a particularly strong inﬂuence.

Bird community change: eﬀects of habitat structure and tree species composition The lower abundance and richness of rainforest birds in plantations and fragments is partly attributable to alteration of habitat structure and the tree canopy. Shade-coﬀee plantations were structurally and ﬂoristically poorer than the other habitats with most foliage concentrated in the relatively uniform coﬀee-shrub and canopy shade-tree layers. The cardamom plantation under diverse natural shade was ﬂoristically similar to primary rainforest in canopy trees but had a higher basal area and canopy height possibly due to the greater stature developed by shade trees after release from competition by removal of understorey and mid-storey vegetation (Parthasarathy 2001; Raman and Sukumar 2002). This is not, however, a general feature of cardamom plantations in the study area because other cardamom plantations had a monoculture canopy of Eucalyptus sp. The potential of shade-coﬀee and other plantations to support a high diversity or abundance of birds relative to forest has been attributed to factors such as forest stature and vertical stratiﬁcation (Daniels et al. 1992; Thiollay 1995; Greenberg et al. 1997a; Shahabuddin 1997) and food availability (Johnson and Sherry 2001). In the Eastern Ghats of India, Beehler et al. (1987) suggested structural and ﬂoristic complexity and availability of remnant forest patches as key ingredients for supporting and sustaining forest bird populations. These studies did not directly assess the inﬂuence of habitat structure and ﬂoristics in consonance with landscape variables across replicate sites. In the present study, woody vegetation variables associated with PC1 (density, basal area, leaf litter depth, cane, bamboo, liana prevalence) had the strongest inﬂuence on the species richness and density of rainforest birds, particularly [534]

1595 endemic species. Bird community composition, however, was signiﬁcantly inﬂuenced mainly by ﬂoristics (tree species composition). This pattern of woody plant variables inﬂuencing rainforest bird species richness and abundance and of tree species composition inﬂuencing bird community composition has also emerged strongly in studies across man-altered habitats in other Indian rainforests (Raman et al. 1998; Raman and Sukumar 2002). Trees, shrubs, and lianas contribute to the bulk of the physical vegetation substrate within rainforest and rainforest birds, being adapted to these substrates for foraging and nesting sites, respond positively to increasing woody vegetation density. For vertical stratiﬁcation, strong eﬀects have been noticed in other studies where more drastically altered habitats such as open habitats (Terborgh 1985; Bowman et al. 1990), shade-less tea plantations (Raman 2001), or other kinds of plantations (Daniels et al. 1992) are included in the reckoning. In the present study, canopy cover and vertical stratiﬁcation (on PC2) negatively inﬂuenced open-forest bird abundance, and positively inﬂuenced species richness (all birds and rainforest birds) and abundance of priority species and rainforest migrants. In some cases, these eﬀects supplemented the eﬀects of PC1 thereby reinforcing the view that bird community structure is strongly inﬂuenced by habitat structure in these rainforests and plantations. Area of the sites did not appear to have a signiﬁcant inﬂuence on most community measures, possible because no small sites were sampled during the study (all sites >18 ha). In an earlier study of the eﬀects of fragmentation on birds, rainforest bird species richness was found to be positively correlated to fragment area, but substantial decrease in richness occurred only below a fragment size of 10 ha (Raman 2001). In addition to factors indicated earlier and below, others such as tree species composition, availability of food resources, and variation in environmental conditions may also play important roles in bird community structuring.

Biological inﬁltration: conservation value of plantations for birds A simple assessment of conservation value for birds based on species richness or abundance in plantations is insuﬃcient. From a conservation perspective, it is important to analyse persistence and usage of these habitats by rainforest birds (‘forest-aﬃliated avifauna’, Daily et al. 2001) vis-a-vis open-forest species. That only 59–67% of the avifauna in shade-coﬀee plantations were rainforest species is signiﬁcant in this respect. Many typical rainforest bird species such as the Malabar Trogon, Brown-cheeked Fulvetta, White-bellied Blue Flycatcher, and Common Flameback were absent in coﬀee plantations, whereas others such as Great Hornbill and Dark-fronted Babbler were scarce or noted only in sites adjoining rainforest fragments. Among migrants, some species frequently noted in rainforests were absent (Western Crowned Warbler, Large-billed Leaf Warbler, Rusty-tailed Flycatcher) or scarce (Indian Blue Robin) in shade-coﬀee. On the other hand, habitat openings and estate roads [535]

1596 in these plantations beneﬁted two species of migrant wagtails (Grey and Forest Wagtails). The process of incursion of a large number of open-forest species into rainforest fragments (‘biological inﬁltration’, Raman 2001) is explained by alteration of habitat structure as well as the inﬂuence of the surrounding landscape. Fragments, particularly the more-disturbed ones with their patchier canopy and denser shrubbery, allow the persistence of species that thrive in open areas and weedy vegetation (e.g., Common Tailorbird, Red-whiskered Bulbul) due to changes in microhabitat and microclimate. Such open-forest species derive from the deciduous and thorn forests of the region and such inﬁltration into disturbed rainforests is known from many other rainforest regions (Leck 1979; Daniels et al. 1990; Raman 2001). Dense thickets of invasive weeds such as Lantana camara within these fragments, with more light and warmth due to canopy openness, allows the persistence of such species that do not occur in the cool, dark, evergreen vegetation of undisturbed rainforest understorey. Another aspect of conservation relevance to consider is whether these plantations provide resources for birds throughout the year. The data from this study over the main breeding season only indicate usage as it was not possible to establish breeding. Plantations that consist mainly of exotic trees may oﬀer few resources for frugivorous and nectarivorous birds (Greenberg et al. 1997a). Such plantations may only temporarily support frugivores such as the hornbills and Pompadour Pigeon that visit the scattered fruiting trees (e.g., Ficus sp., Litsea glabrata, and Actinodaphne angustifolia). Nectar-seeking birds such as sunbirds, drongos, orioles, and Vernal Hanging-Parrot visited ﬂowers of exotics such as Eucalyptus sp., Grevillea robusta, Erythrina sp., and even coﬀee bushes (Crimson-backed Sunbird) in season, besides ﬂowers of native plants. In the more open coﬀee plantations, however, an open-forest species (Purple Sunbird) was often more abundant than the endemic Crimson-backed Sunbird.

Endemic and priority species The responses of endemic and priority species to habitat alteration were mostly idiosyncratic. In general, alteration in habitat structure, particularly woody plant variables, aﬀected their richness and abundance, suggesting the importance of rainforest structural niches and ﬂoristic attributes for the persistence of these species, as noted in the Agasthyamalai region of the Western Ghats (Raman and Sukumar 2002). As a consequence, many endemic and priority species avoided shade-coﬀee plantations, such as Malabar Trogon, Mountain Imperial Pigeon, Yellow-browed Bulbul, and Common Flameback. The occurrence of Malabar Grey Hornbills in shadecoﬀee estates can be attributed to the retention of fruit-trees in the canopy that provide food for hornbills (Raman and Mudappa 2003b). Forest-edge species, including the endemic Rufous Babbler, also persist in shade-coﬀee as [536]

1597 they contain suitable habitat. Continuous rainforest emerges as an important habitat for priority species such as Malabar Trogon and Large Woodshrike and the endemic ﬂycatchers. However, a number of priority species and endemics showed strong avoidance (deviation index) of the rainforest control site (Appendix). This was mainly because these species were lower-elevation birds that occurred in good numbers in relatively undisturbed lower elevation rainforest but were scarce or absent in the control site available for this study.

Conservation implications This study shows that the nature of adjoining habitats aﬀects rainforest bird communities in tropical rainforest fragments. Speciﬁcally, having shade-coﬀee rather than tea plantations adjoin fragments has beneﬁcial eﬀects on rainforest birds, and these eﬀects are probably mediated through the inﬂuence of habitat structure and canopy tree species composition on bird community structure. Such plantations can thus promote the persistence in the entire landscape of larger populations of rainforest birds (Beehler et al. 1987; Renjifo 2001). Individual rainforest birds resident or dispersing from such sites can reduce the likelihood of chance extinction in fragments through recolonization (‘rescue eﬀect’, Brown and Kodric-Brown 1977). Increased canopy connectivity in adjoining habitats also has value for shade-coﬀee plantations. Again, beneﬁts accrue mainly to rainforest birds: more species and individuals were supported per unit area in plantations that adjoined continuous forest. Although there were no completely isolated (surrounded by tea estates) shadecoﬀee plantations in the study area, it seems likely that such plantations will be more depauperate in rainforest birds than those adjoining fragments or continuous forest. If increased canopy connectivity in adjoining forest habitats beneﬁts rainforest birds it may also beneﬁt coﬀee plantation owners. The bird populations may enable ‘eco-friendly’ or ‘bird-friendly’ coﬀee certiﬁcation (Sherry 2000; Rappole et al. 2003) and reduce insect attack on coﬀee leaves (Guatemala: Greenberg et al. 2000), while bees from adjoining forest may enhance pollination of coﬀee plants (Costa Rica: Ricketts 2004, Ricketts et al. 2004). In the study region, ongoing conversion of shade-coﬀee to tea plantations driven largely by market forces, is therefore of conservation concern because tea plantations represent a poorer habitat for rainforest birds and because of the fallouts for fragments in the landscape. Eﬀorts should be made to halt such changes while encouraging landowners through tax and other incentives to promote the relatively more benign form of land use represented by shadecoﬀee. Schemes, currently non-existent in India, to certify shade-coﬀee plantations that are good for birds (Smithsonian Migratory Bird Center 1999) need to be explored as a means to promote conservation while directly extending beneﬁts to landowners (Venkatachalam 2005). Such certiﬁcation should [537]

1598 incorporate recognition of steps taken by landowners to promote the diversity of native tree species used as shade trees in coﬀee plantations. As many bird species are clearly dependent on rainforests in the landscape, it needs to be emphasised that eﬀorts to prevent land-use conversion and promote use of a diversity of native shade tree species can only supplement and not replace conventional conservation eﬀorts that aim to protect and restore primary rainforests and fragments.

Acknowledgements This research was ﬁnancially supported by the Wildlife Conservation Society, USA. I am also grateful to Netherlands Committee for IUCN, Tropical Rainforest Programme, and Barakat Inc., USA, for follow-up support. I thank the Tamil Nadu Forest Department, especially Dr. Sukhdev and Mr. V. Ganesan, for permits and support. A number of plantation company managers allowed me to work on their property for which I am grateful. I thank Divya Mudappa for help in designing the study, being a soundingboard and critic of the ideas developed, and for helpful comments on the manuscript. My colleagues at NCF, especially M.D. Madhusudan, infused additional enthusiasm into this work through their support and encouragement. I thank R. Raghunath and Pavithra Sankaran for assistance with ﬁeldwork, Vena Kapoor for help with data entry, and A. Silamban for being a reliable ﬁeld assistant.

[538]

Appendix. List of birds detected in point count sampling in rainforest and plantation sites within and adjoining the Indira Gandhi Wildlife Sanctuary in the Anamalai hills, Western Ghats. The total number of detections of each species, average detections per 25 point counts and deviations from expected detections (signiﬁcant values in bold) are presented. Category codes: Res = resident, Mig = Migrant, Pri = priority species, End = endemic to Western Ghats; Habitat codes: OF = open-forest, RF = rainforest. S. No. Habitat Species

Category Detections Detections/25 point counts

Deviations

Control Fragment Coﬀee Cardamom Control Fragment Coﬀee Cardamom

[539]

OF OF OF

4

OF

5

OF

6

OF

7

OF

8

OF

9 10 11

OF OF OF

12 13

OF OF

14

OF

15

OF

Ashy Woodswallow Artamus fuscus Asian Koel Eudynamus scolopocea Black-headed Cuckooshrike Coracina melanoptera Black-rumped Flameback Dinopium benghalense Blue-winged Leafbird Chloropsis cochinchinensis Brown-capped Pygmy Woodpecker Dendrocopos nanus Chestnut-headed Bee-eater Merops leschenaulti Chestnut-tailed Starling Sturnus malabaricus Common Hoopoe Upupa epops Common Iora Aegithina tiphia Common Tailorbird Orthotomus sutorius Greater Coucal Centropus sinensis Grey-bellied Cuckoo Cacomantis passerinus Grey-breasted Prinia Prinia hodgsonii Jungle Myna Acridotheres fuscus

Res Res Res

1 8 2

– – –

0.14 0.14 0.14

– 1.00 0.14

– – –

1.00

0.61

0.48

1.00

Res

6

–

0.28

0.57

–

1.00

0.22

0.37

1.00

Res

1

–

–

0.14

–

Res

6

–

0.57

0.29

–

1.00

0.12

0.04

1.00

Res

10

0.83

0.14

1.00

1.00

0.05

0.68

0.39

0.11

Res

2

–

0.28

–

–

Res Res Res

2 10 62

– – –

0.14 0.85 2.13

0.14 0.29 6.71

– 2.00 –

1.00 1.00

0.07 0.37

0.21 0.42

0.43 1.00

Res Res

23 1

– –

0.71 0.14

2.57 –

– –

1.00

0.41

0.43

1.00

Res

18

–

0.85

1.71

–

1.00

0.22

0.37

1.00

Res

2

–

–

0.29

–

1599

1 2 3

S. No. Habitat Species

Category Detections Detections/25 point counts

1600

Appendix. (Continued). Deviations

Control Fragment Coﬀee Cardamom Control Fragment Coﬀee Cardamom

[540]

16 17 18 19 20

OF OF OF OF OF

21 22

OF OF

23 24 25 26

OF OF OF OF

27

OF

28

OF

29

OF

30 31

OF OF

32

OF

33 34

OF OF

Kestrel Falco tinnunculus Large-billed Crow Corvus macrorhynchus Oriental Magpie Robin Copsychus saularis Pied Cuckoo Clamator jacobinus Plum-headed Parakeet Psittacula cyanocephala Purple Sunbird Nectarinia asiatica Red-whiskered Bulbul Pycnonotus jocusus Shikra Accipiter badius Small Minivet Pericrocotus cinnamomeus Spotted Dove Streptopelia chinensis Streak-throated Woodpecker Picus xanthopygaeus White-breasted Waterhen Amaurornis phoenicurus White-throated Kingﬁsher Halcyon smyrnensis Asian Brown Flycatcher Muscicapa dauurica Black-naped Oriole Oriolus chinensis Blue-capped Rock Thrush Monticola cinclorhynchus Blyth’s Reed Warbler Acrocephalus dumetorum Brown Shrike Lanius cristatus Common Roseﬁnch Carpodacus erythrinus

Res Res Res Res Res

1 44 27 1 34

– – – – –

– 3.13 1.14 – 2.70

0.14 3.00 2.71 0.14 2.14

– 1.00 – – –

1.00 0.02 1.00 0.27

0.21 0.56 0.39 1.00

1.00

0.04

0.18 1.00

Res Res

27 151

– –

0.57 7.81

3.29 13.29

– 3.00

1.00 0.56 1.00 0.18

0.47 1.00 0.33 0.60

Res Res Res Res

5 4 2 1

– – – –

0.57 0.28 0.14 0.14

0.14 0.29 0.14 –

– – – –

1.00

0.21

0.21 1.00

Res

2

–

–

0.29

–

Res

4

–

0.14

0.43

–

Mig

11

–

0.85

0.71

–

1.00

0.02

0.19 1.00

Mig Mig

1 1

– –

– –

0.14 0.14

– –

Mig

206

9.00

0.65

0.09

0.24 0.29

Mig Mig

14 9

– –

1.00 1.00

0.02 0.08

0.24 1.00 0.29 1.00

3.33 – –

12.64

14.86

0.99 0.57

1.00 0.71

[541]

OF OF RF

38

RF

39 40 41 42 43 44

RF RF RF RF RF RF

45 46 47 48 49

RF RF RF RF RF

50 51

RF RF

52 53

RF RF

54 55

RF RF

56 57

RF RF

58

RF

Eurasian Golden Oriole Oriolus oriolus Mig Red-throated Flycatcher Muscicapa parva Mig Res Asian Paradise-Flycatcher Terpsiphone paradisi Bar-winged Flycatcher-Shrike Hemipus Res picatus Besra Accipiter virgatus Res Black-lored Tit Parus xanthogenys Res Black-naped Monarch Hypothymis azurea Res Blue-bearded Bee-eater Nyctyornis athertoni Res Bronzed Drongo Dicrurus aeneus Res Res Brown-cheeked Fulvetta Alcippe poioicephala Crested Serpent Eagle Spilornis cheela Res Drongo Cuckoo Surniculus lugubris Res Emerald Dove Chalcophaps indica Res Eurasian Blackbird Turdus merula Res Res Golden-fronted Leafbird Chloropsis aurifrons Greater Flameback Chrysocolaptes lucidus Res Res Greater Racket-tailed Drongo Dicrurus paradiseus Grey Junglefowl Gallus sonneratii Res Grey-headed Canary Flycatcher Culicicapa Res ceylonensis Hill Myna Gracula religiosa Res Res Indian Scimitar Babbler Pomatorhinus horsﬁeldii Orange-headed Thrush Zoothera citrina Res Res Oriental Honey-Buzzard Pemis ptilorhynchus Oriental White-Eye Zosterops palpebrosus Res

1.00 0.44

0.44 1.00

0.16

0.05

0.20 1.00

0.54

0.04

0.56 0.29

1.00 0.36

0.14 0.03

0.17 1.00

1.00 0.47

0.20 0.14

0.16 1.00 1.00 0.12

– – – – –

1.00 0.32 -0.19 0.09 1.00 0.29

1.00 1.00 0.01 1.00 0.40 1.00

0.86 0.14

2.00 8.00

0.07 0.45

0.07 0.11

0.13 0.80

0.00 0.55

0.57 3.41

0.29 –

1.00 15.00

1.00 0.52

0.05 0.09

0.04 1.00

0.29 0.55

5.83 5.00

3.98 5.97

1.86 3.29

14.00 2.00

0.11 0.05

0.07 0.05

0.19 0.48 0.01 0.49

47 1

1.67 –

4.26 0.14

1.86 –

2.00 –

0.36

0.10

0.06 0.30

119

14.17

7.67

6.57

2.00

0.22

0.07

0.11 0.65

10 1 15

– – 0.83

0.28 – 0.99

1.14 0.14 1.00

– – –

23

5.83

1.85

0.29

1.00

4 23 31 1 18 48

0.83 – 5.00 – – 10.00

0.43 2.27 2.41 0.14 1.99 4.69

– 0.71 – – 0.57 –

– 2.00 8.00 – – 3.00

3 1 6 16 7

– – – 0.83 –

0.14 0.14 0.85 1.42 0.28

0.29 – – 0.71 0.71

25 29

1.67 0.83

2.13 2.70

7 55

– 13.33

62 73

0.05 0.53

1601

35 36 37

S. No. Habitat Species

Category Detections Detections/25 point counts

1602

Appendix. (Continued). Deviations

Control Fragment Coﬀee Cardamom Control Fragment Coﬀee Cardamom

[542]

59

RF

60 61 62 63 64 65 66

RF RF RF RF RF RF RF

67 68

RF RF

69

RF

70 71 72

RF RF RF

73 74

RF RF

75 76

RF RF

77

RF

78

RF

Pompadour Green Pigeon Treron pompadora Puﬀ-throated Babbler Pellorneum ruﬁceps Red Spurfowl Galloperdix spadicea Scarlet Minivet Pericrocotus ﬂammeus Velvet-fronted Nuthatch Sitta frontalis Asian Fairy Bluebird Irena puella Black Bulbul Hypsipetes leucocephalus Black-crested Bulbul Pycnonotus melanicterus Common Flameback Dinopium javanense Crimson-fronted Barbet Megalaima rubricapilla Dark-fronted Babbler Rhopocichla atriceps Dollarbird Eurystomus orientalis Great Hornbill Buceros bicornis Heart-spotted Woodpecker Hemicircus canente Large Woodshrike Tephrodornis gularis Little Spiderhunter Arachnothera longirostra Malabar Trogon Harpactes fasciatus Malabar Whistling Thrush Myophonus horsﬁeldii Mountain Imperial Pigeon Ducula badia Plain Flowerpecker Dicaeum concolor

Res

17

0.83

0.85

0.57

6.00

0.22

0.19

0.14

Res Res Res Res Pri Pri Pri

35 9 70 66 38 33 12

3.33 0.83 2.50 5.00 4.17 9.17 –

3.27 0.99 5.82 5.54 2.56 2.98 1.42

0.71 0.14 2.71 2.29 0.29 – 0.14

3.00 – 7.00 5.00 13.00 1.00 1.00

0.11 0.10 0.36 0.00 0.18 0.57 1.00

0.12 0.20 0.06 0.06 0.05 0.10 0.23

0.37 0.04 0.47 1.00 0.06 0.11 0.12 0.02 0.71 0.62 1.00 0.45 0.58 0.02

Pri Pri

6 20

0.83 –

0.57 1.42

– 1.43

1.00 –

0.29 1.00

0.12 0.02

1.00 0.35 0.24 1.00

Pri

21

2.50

2.27

0.14

1.00

0.22

0.19

0.73 0.25

Pri Pri Pri

1 2 4

– 0.83 0.83

– – 0.14

0.14 0.14 –

– – 2.00

Pri Pri

17 69

3.33 3.33

0.85 7.10

0.86 0.14

1.00 14.00

0.44 0.22

0.19 0.16

0.07 0.15 0.91 0.44

Pri Pri

5 83

0.83 8.33

0.43 7.10

– 2.00

1.00 9.00

0.37 0.14

0.07 0.07

1.00 0.29

0.43 0.15

Pri

22

2.50

1.42

0.14

8.00

0.20

0.07

0.74

0.64

Pri

290

16.67

20.74

15.71

14.00

0.14

0.02

0.63

0.10 0.24

[543]

79 80

RF RF

81

RF

82

RF

83 84 85

RF RF RF

86 87

RF RF

88 89 90 91

RF RF RF RF

92

RF

93 94

RF RF

95

RF

96

RF

97

RF

Rufous Woodpecker Celeus brachyurus Vernal Hanging Parrot Loriculus vernalis White-bellied Woodpecker Dryocopus javensis White-cheeked Barbet Megalaima viridis Yellow-browed Bulbul Iole indica Ashy Drongo Dicrurus leucophaeus Brown-breasted Flycatcher Muscicapa muttui Forest Wagtail Dendronanthus indicus Greenish Warbler Phylloscopus trochiloides Grey Wagtail Motacilla cinerea Indian Blue Robin Luscinia brunnea Indian Pitta Pitta brachyura Large Hawk Cuckoo Hierococcyx sparverioides Large-billed Leaf Warbler Phylloscopus magnirostris Pied Thrush Zoothera wardii Rusty-tailed Flycatcher Muscicapa ruﬁcauda Verditer Flycatcher Eumyias thalassina Western Crowned Warbler Phylloscopus occipitalis Black-and-Orange Flycatcher Ficedula nigrorufa

Pri Pri

2 70

– 6.67

0.14 4.83

– 3.00

1.00 7.00

Pri

1

–

0.14

–

–

Pri

125

11.67

8.95

5.86

Pri Mig Mig

102 35 3

15.83 – –

9.38 2.98 0.14

Mig Mig

24 306

– 23.33

Mig Mig Mig Mig

15 48 1 2

Mig

100

Mig Mig

2 19

Mig

0.11

0.03

0.01

7.00

0.10

0.02

0.03 0.17

1.00 2.00 0.14

10.00 – 1.00

0.34 1.00

0.11 0.07

0.64 0.10 0.13 1.00

0.57 21.73

2.71 15.71

1.00 15.00

1.00 0.51 0.00 0.02

0.44 0.31 0.08 0.24

– 0.83 – –

0.28 5.40 – 0.14

1.86 0.71 0.14 0.14

– 4.00 – –

1.00 0.59 0.63 0.21

0.47 1.00 0.50 0.02

17.50

9.52

–

12.00

0.39

0.13

1.00

0.20

– –

0.28 2.27

– –

– 3.00

1.00

0.24

1.00

0.33

1

–

0.14

–

–

Mig

4

0.83

0.43

–

–

End

10

5.83

0.28

–

1.00

0.77 0.44

1.00

0.11

0.11

1603

S. No. Habitat Species

Category Detections Detections/25 point counts

1604

Appendix. (Continued). Deviations

Control Fragment Coﬀee Cardamom Control Fragment Coﬀee Cardamom

[544]

98

RF

99

RF

100

RF

101

RF

102 103 104

RF RF RF

105

RF

106

RF

Crimson-backed Sunbird Nectarinia minima Grey-headed Bulbul Pycnonotus priocephalus Malabar Grey Hornbill Ocyceros griseus Malabar Parakeet Psittacula columboides Nilgiri Flycatcher Eumyias albicaudata Rufous Babbler Turdoides subrufus White-bellied Blue Flycatcher Cyornis pallipes White-bellied Treepie Dendrocitta leucogastra Wynaad Laughingthrush Garrulax delesserti

22.50

12.36

2.29

26.00

156

End

1

–

0.14

–

–

End

33

–

2.41

2.14

1.00

1.00 0.01

End

30

–

3.27

0.71

2.00

1.00

0.19

0.30 0.09

End End End

29 10 21

6.67 – 3.33

2.84 0.85 1.42

0.14 0.57 –

– – 7.00

0.50 0.14 1.00 0.07 0.35 0.04

0.80 1.00 0.13 1.00 1.00 0.62

End

3

–

0.43

–

–

End

2

–

0.14

–

1.00

0.31

0.03

0.50

End

0.35

0.19 0.45

1605 References Ali S. and Ripley S.D. 1983. Handbook of the Birds of India and Pakistan. Compact edition, Oxford University Press, Delhi. Beehler B.M., Raju K.S.R.K. and Ali S. 1987. Avian use of man-disturbed forest habitats in the Eastern Ghats, India. Ibis 129: 197–211. Bibby C.J., Burgess N.D. and Hill D.A. 1992. Bird Census Techniques. Academic Press, London. BirdLife International 2001. Threatened Birds of the World. Lynx Edicions and BirdLife International, Barcelona and Cambridge. Bowman D.M.J.S., Woinarski J.C.Z., Sands D.P.A., Wells A. and McShane V.J. 1990. Slash-andburn agriculture in the wet coastal lowlands of Papua New Guinea: response of birds, butterﬂies and reptiles. J. Biogeogr. 17: 227–239. Brown J.H. and Kodric-Brown A. 1977. Turnover rates in insular biogeography: eﬀect of immigration on extinction. Ecology 58: 445–449. Brown S. and Lugo A.E. 1990. Tropical secondary forests. J. Trop. Ecol. 6: 1–32. Cincotta R.P., Wisnewski J. and Engelman R. 2000. Human population in the biodiversity hotspots. Nature 404: 990–992. Clarke K.R. and Gorley R.N. 2001. Primer v5: User Manual/Tutorial. PRIMER-E, Plymouth. Clarke K.R. and Warwick R.M. 1994. Change in Marine Communities: An Approach to Statistical Analysis and Interpretation. Plymouth Marine Laboratory, Plymouth. Coﬀee Board 2001. Database on Coﬀee. Coﬀee Board, Bangalore. Collar N.J., Crosby M.J. and Stattersﬁeld A.J. 1994. Birds to Watch 2: The World list of Threatened Birds. BirdLife International, Cambridge. Colwell R.K. 1997. EstimateS: Statistical Estimation of Species Richness and Shared Species from Samples. Version 6.01b. Internet URL: http://viceroy.eeb.uconn.edu/EstimateS. Colwell R.K. and Coddington J.A. 1994. Estimating terrestrial biodiversity through extrapolation. Philos. Trans. Roy. Soc. London Series B 345: 101–118. Congreve H.R.T. 1942. The Anamalais. Associated Printers, Madras. Daily G.C. 2001. Ecological forecasts. Nature 411: 245. Daily G.C., Ehrlich P.R. and Sa´nchez-Azofeifa G.A. 2001. Countryside biogeography: use of human-dominated habitats by the avifauna of southern Costa Rica. Ecol. Appl. 11: 1–13. Daniels R.J.R., Hegde M. and Gadgil M. 1990. Birds of man-made habitats: the plantations. Proc. Ind. Acad. Sci. (Anim. Sci.) 99: 79–89. Daniels R.J.R., Joshi N.V. and Gadgil M. 1992. On the relationship between bird and woody plant species diversity in the Uttara Kannada District of south India. Proc. Nat. Acad. Sci. (USA) 89: 5311–5315. Estrada A., Coates-Estrada R. and Meritt D.Jr. 1997. Anthropogenic landscape changes and avian diversity at Los Tuxtlas, Mexico. Biodiv. Conserv. 6: 19–43. Gamble J.S. and Fischer C.E.C. 1935. Flora of the Presidency of Madras. Reprint, 3 volumes. Bishen Singh Mahendra Pal Singh, Dehra Dun. Greenberg R., Bichier P., Angon A.C. and Rietsma R. 1997a. Bird populations in shade and sun coﬀee plantations in central Guatemala. Conserv. Biol. 11: 448–459. Greenberg R., Bichier P. and Sterling J. 1997b. Bird populations in rustic and planted shade coﬀee plantations of Eastern Chiapas, Mexico. Biotropica 29: 501–514. Greenberg R., Bichier P., Angon A.C., MacVean C., Perez R. and Cano E. 2000. The impact of avian insectivory on arthropods and leaf damage in some Guatemalan coﬀee plantations. Ecology 81: 1750–1755. Hemelrijk C.K. 1990. Models of, and tests for, reciprocity, unidirectionality and other social interaction patterns at a groups level. Anim. Behav. 39: 1013–1029. Johnson M.D. and Sherry T.W. 2001. Eﬀects of food availability on the distribution of migratory warblers among habitats in Jamaica. J. Anim. Ecol. 70: 546–560. Kannan R. 1998. Avifauna of the Anaimalai hills (Western Ghats) of southern India. J. Bombay Nat. Hist. Soc. 95: 193–214.

[545]

1606 Krebs C.J. 1989. Ecological Methodology. Harper and Row, New York. Kumar M.A., Singh M., Srivastava S.K., Udhayan A., Kumara H.N. and Sharma A.K. 2002. Distribution patterns, relative abundance and management of mammals in Indira Gandhi Wildlife Sanctuary, Tamil Nadu, India. J. Bombay Nat. Hist. Soc. 99: 184–210. Laurance W.F., Bierregaard R.O.Jr., Gascon C. and others 1997. Tropical forest fragmentation: synthesis of a diverse and dynamic discipline. In: Laurance W.F. and Bierregaard R.O.Jr. (eds), Tropical Forest Remnants: Ecology, Management, and Conservation of Fragmented Communities. University of Chicago Press, Chicago, pp. 502–514. Leck C.F. 1979. Avian extinctions in an isolated tropical wet forest preserve. Auk 96: 343–352. Luck G.W. and Daily G.C. 2003. Tropical countryside bird assemblages: richness, composition, and foraging diﬀer by landscape context. Ecol. Appl. 13: 235–247. Mani M.S. (ed) 1974. Ecology and Biogeography of India. Dr. W. Junk Publishers, The Hague. Manly B.F.J. 1994. Multivariate Statistical Methods: A Primer. 2nd edn. Chapman and Hall, London, UK. Menon S. and Bawa K.S. 1997. Applications of geographical information systems, remote sensing and a landscape ecology approach to biodiversity conservation in the Western Ghats. Curr. Sci. 73: 134–145. Myers N., Mittermeier R.A., Mittermeier C.G., da Fonseca G.A.B. and Kent J. 2000. Biodiversity hotspots for conservation priorities. Nature 403: 853–858. Nair S.C. 1991. The Southern Western Ghats: A Biodiversity Conservation Plan. INTACH, New Delhi. Norusˇ is M.J. 1990. SPSS/PC+ Statistics 4.0. SPSS Inc., Chicago. Olson D.M. and Dinerstein E. 1998. The global 200: a representation approach to conserving the Earth’s most biologically valuable ecoregions. Conserv. Biol. 12: 502–515. Parthasarathy N. 2001. Changes in forest composition and structure in three sites of tropical evergreen forest around Sengaltheri, Western Ghats. Curr. Sci. 80: 389–393. Pascal J.P. 1988. Wet Evergreen Forests of the Western Ghats of India: Ecology, Structure, Floristic Composition and Succession. Institut Franc¸ais de Pondiche´ry, Pondicherry. Pascal J.P. and Ramesh B.R. 1997. A Field Key to the Trees and Lianas of the Evergreen Forests of the Western Ghats (India). Institut Franc¸ais de Pondiche´ry, Pondicherry. Perfecto I. and Vandermeer J. 2002. Quality of agroecological matrix in a tropical montane landscape: ants in coﬀee plantations in southern Mexico. Conserv. Biol. 16: 174–182. Perfecto I., Mas A., Dietsch T. and Vandermeer J. 2003. Conservation of biodiversity in coﬀee agroecosystems: a tritaxa comparison in southern Mexico. Biodiv. Conserv. 12: 1239–1252. Ralph C.J., Sauer J.R. and Droege S. (eds) 1995. Monitoring Bird Populations by Point Counts. USDA, Forest Service, Paciﬁc Southwest Research Station, Albany, California. Raman T.R.S. 2001.Community Ecology and Conservation of Tropical Rainforest Birds in the Southern Western Ghats, India. Ph.D. thesis, Indian Institute of Science, Bangalore. Raman T.R.S. 2003. Assessment of census techniques for inter-speciﬁc comparisons of tropical rainforest bird densities: a ﬁeld evaluation in the Western Ghats, India. Ibis 145: 9–21. Raman T.R.S. and Mudappa D. 2003a. Bridging the gap: sharing responsibility for ecological restoration and wildlife conservation on private lands in the Western Ghats. Social Change 33: 129–141. Raman T.R.S. and Mudappa D. 2003b. Correlates of hornbill distribution and abundance in rainforest fragments in the southern Western Ghats, India. Bird Conserv. Int. 13: 199–212. Raman T.R.S., Rawat G.S. and Johnsingh A.J.T. 1998. Recovery of tropical rainforest avifauna in relation to vegetation succession following shifting cultivation in Mizoram, north-east India. J. Appl. Ecol. 35: 214–231. Raman T.R.S. and Sukumar R. 2002. Responses of tropical rainforest birds to abandoned plantations, edges and logged forest in the Western Ghats, India. Anim. Conserv. 5: 201–216. Rappole J.H., King D.I. and Rivera J.H.V. 2003. Coﬀee and conservation. Conserv. Biol. 17: 334–336.

[546]

1607 Renjifo L.M. 2001. Eﬀect of natural and anthropogenic landscape matrices on the abundance of subandean bird species. Ecol. Appl. 11: 14–31. Ricketts T.H. 2004. Tropical forest fragments enhance pollinator activity in nearby coﬀee crops. Conserv. Biol. 18: 1–10. Ricketts T.H., Daily G.C., Ehrlich P.R. and Michener C.D. 2004. Economic value of tropical forest to coﬀee production. Proc. Nat. Acad. Sci. (USA) 101: 12579–12582. Shahabuddin G. 1997. Preliminary observations on the role of coﬀee plantations as avifaunal refuges in the Palni hills of the Western Ghats. J. Bombay Nat. Hist. Soc. 94: 10–21. Sherry T.W. 2000. Shade coﬀee: a good brew even in small doses. Auk 117: 563–568. Smithsonian Migratory Bird Center 1999. Certiﬁed shade-grown coﬀees. . Stattersﬁeld A.J., Crosby M.J., Long A.J. and Wege D.C. 1998. Endemic Bird Areas of the World: Priorities for Biodiversity Conservation. Birdlife International, Cambridge. Stouﬀer P.C. and Bierregaard R.O.Jr. 1995a. Use of Amazonian forest fragments by understory insectivorous birds. Ecology 76: 2429–2445. Stouﬀer P.C. and Bierregaard R.O.Jr. 1995b. Eﬀects of fragmentation on understory hummingbirds in Amazonian Brazil. Conserv. Biol. 9: 1085–1094. Tea Board 2002. Tea Board home page. . Terborgh J. 1985. Habitat selection in Amazonian birds. In: Cody M.L. (ed.), Habitat Selection in Birds. Academic Press, Inc., Orlando, pp. 311–340. Tejeda-Cruz C. and Sutherland W.J. 2004. Bird responses to shade coﬀee production. Anim. Conserv. 7: 169–179. Thiollay J.M. 1995. The role of traditional agroforests in the conservation of rain forest bird diversity in Sumatra. Conserv. Biol. 9: 335–353. Turner I.M. and Corlett R.T. 1996. The conservation value of small isolated fragments of lowland tropical rain forest. Trends Ecol. Evol. 11: 330–333. Umapathy G. and Kumar A. 2000. The occurrence of arboreal mammals in the rain forest fragments in the Anamalai hills, south India. Biol. Conserv. 92: 311–319. Venkatachalam L. 2005. Coﬀee: need to achieve market balance. The Hindu Survey of Indian Agriculture 2005: 113–115. Verner J. 1985. Assessment of counting techniques. Curr. Ornithol. 2: 247–302. Wolda H. 1981. Similarity indices, sample size and diversity. Oecologia 50: 296–302. Wunderle J.H.Jr. 1999. Avian distribution in Dominican shade coﬀee plantations: area and habitat relationships. J. Field Ornithol. 70: 58–70. Zar J.H. 1999. Biostatistical Analysis. 4th edn. Prentice-Hall, New Jersey.

[547]

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