ENVIRONMENTAL SCIENCE, ENGINEERING AND TECHNOLOGY
LAGOONS: BIOLOGY, MANAGEMENT AND ENVIRONMENTAL IMPACT
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ENVIRONMENTAL SCIENCE, ENGINEERING AND TECHNOLOGY
LAGOONS: BIOLOGY, MANAGEMENT AND ENVIRONMENTAL IMPACT
ADAM G. FRIEDMAN EDITOR
Nova Science Publishers, Inc. New York
Copyright © 2011 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com
NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers‘ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Additional color graphics may be available in the e-book version of this book. LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA Lagoons : biology, management, and environmental impact / editor, Adam G. Friedman. p. cm. Includes index. ISBN 978-1-61122-086-5 (eBook) 1. Lagoons. I. Friedman, Adam G. GB2203.2.L34 2010 551.46'18--dc22 2010033077
Published by Nova Science Publishers, Inc. † New York
CONTENTS
Preface Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
vii Metabolic and Structural Role of Major Fish Organs as an Early Warning System in Population Assessment C. Fernandes , A. Afonso and M.A. Salgado Benthic Foraminifera in Coastal Lagoons: Distributional Patterns and Biomonitoring Implications F. Frontalini, E. Armynot du Châtelet, J.P. Debenay, R. Coccioni and G. Bancalà
1
39
Coastweb, a Foodweb Model Based on Functional Groups for Coastal Areas Including a Mass-Balance Model for Phosphorus Lars Håkanson and Dan Lindgren
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Form and Functioning of Micro Size Intermittent Closed Open Lake Lagoons (ICOLLs) in NSW, Australia W. Maher, K. M. Mikac, S. Foster, D. Spooner and D. Williams
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Waterbirds as Bioindicators in Coastal Lagoons: Background, Potential Value and Recent Research in Mediterranean Areas Francisco Robledano Aymerich and Pablo Farinós Celdrán
153
How Important are Local Nutrient Emissions to Eutrophication in Coastal Areas Compared to Fluxes from the Outside Sea? A CaseStudy Using Data from the Himmerfjärden Bay in the Baltic Proper Lars Håkanson and Maria I. Stenström-Khalili Environmental Consequences of Innovative Dredging in Coastal Lagoon for Beach Restoration Emmanuel Lamptey
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vi Chapter 8
Contents State of Knowledge of the Trophic State of Worldwide Lagoon Ecosystems: Leading Fields and Perspectives Monia Renzi, Antonietta Specchiulli, Raffaele D’Adamo and Silvano E. Focardi
Chapter 9
Treatment of Contaminated Sediments by Chemical Oxidation Sabrina Saponaro, Alessandro Careghini, Kevin Gardner and Scott Greenwood
Chapter 10
Reconstruction of the Eutrophication in the Gulf of Finland Using a Dynamic Process-Based Mass-Balance Model Lars Håkanson
Chapter 11
Chapter 12
Chapter 13
Environmental Management and Sustainable Use of Coastal Lagoons Ecosystems Rutger de Wit, Behzad Mostajir, Marc Troussellier and Thang Do Chi Involvement of Local Users is the Overlooked Background Information for Improving Implementation of Conservation Solutions in Coastal Lagoon Management: The Case of the Ichkeul National Park (Tunisia) Caterina Casagranda Birth, Evolution and Death of a Lagoon: Late Pleistocene to Holocene Palaeoenvironmental Reconstruction of the Doñana National Park (SW Spain) F. Ruiz,, M. Pozo, M. I. Carretero, M. Abad M. L. González-Regalado, J. M. Muñoz, J. Rodríguez-Vidal, L. M. Cáceres, J. G. Pendón, M. I. Prudêncio and M. I. Dias
Chapter 14
The Alvarado Lagoon – Environment, Impact, and Conservation Jane L. Guentzel, Enrique Portilla-Ochoa, Alejandro Ortega-Argueta, Blanca E. Cortina-Julio and Edward O. Keith
Chapter 15
Adaptive Lagoon Fishery Development through Sustainable Livelihoods Approach: A Case Study of Chilika Lagoon, India Shimpei Iwasaki
Chapter 16
Vertical Flux of Ice Algae in a Shallow Lagoon, Hokkaido, Japan Yoko Niimura, Hiroaki Saito, and Satoru Taguchi
Chapter 17
The Evaluation of Some Limnological Features of the Lagoon Lakes in European Part of Turkey Belgin Çamur-Elipek and Timur Kırgız
Index
249
279
301
333
351
371
397
417 435
457 475
PREFACE Coastal lagoons are particularly complex environments in which the transition between marine and continental waters is gradual, due to the continuity of the aquatic habitat. They are characterized by major fluctuations in chemical and physical parameters, which reflect multiple interactions between the distance to the sea, water depth, the nature of the sediment, organic matter quality, hydrodynamic turnover time, tidal currents, wind forced currents, volume lost by evaporation, and gravitational circulation. This book presents current research from across the globe in the study of lagoons, their biology, management and environmental impact. Chapter 1- There are thousands of pollutants that affect aquatic environment and their effects have long been a concern and cause of research. This number grows annually since new compounds and formulations are synthesized. At present the concept of pollution involves knowledge of environmental fate and effects of chemical pollutants and their impacts on both, ecosystems and on social and economic development. Some aquatic environments are vital because of their critical ecological and economic importance. There are numerous lakes, lagoons and coastal lagoons playing a social and economic role on adjacent human populations, as they support fishing and recreational activities, and an ecological role, as they also support a characteristic flora and fauna, becoming important habitats. Additionally, several of these fresh waters reservoirs become a vital supply of potable water. In many cases, even in sub-lethal concentrations, aquatic pollutants affect structure and normal functioning of natural populations as they can cause impacts at multiple levels of organization, including cells, tissues, organs, individuals and community level. Several aquatic species can be used to study these issues and fish has been proved to be a suitable test-organism. Fish organs, such as liver, spleen and kidney can be very helpful to understand the response mechanisms to pollutant exposure. Fish liver is the main target organ of dietary route and the central metabolic organ, where detoxification mechanisms occur; spleen is involved in development of circulating blood cells, as well as immunity; and kidney is involved with excretion and thus, with electrolyte balance and acid-base regulation. Moreover, the anterior part of kidney supports the main pool of several fish leukocyte types. Assessment of coastal and shallow lagoon waters is a top priority among environmental monitoring activities, due to high ecological and economical importance of these relevant resources. In particular in enclosed communities, such as lakes and lagoons, this issue is enhanced according to the abundance and diversity of wildlife and increased need for water quality. Fish are relatively sensitive to changes in the environment and toxic effects of
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pollutants may start to occur in the cell and in metabolic pathways, before significant alterations in behaviour or morphology can be identified. The knowledge of normal metabolic processes of these major fish organs and alterations induced by exposure to pollutants can be a tool for an early warning system in the evaluation and analysis of the wealth of a fish population and their natural environment. Chapter 2- Coastal lagoons are particularly complex environments in which the transition between marine and continental waters is gradual, due to the continuity of the aquatic habitat. They are characterized by major fluctuations in chemical and physical parameters, which reflect multiple interactions between the distance to the sea, water depth, the nature of the sediment, organic matter quality, hydrodynamic turnover time, tidal currents, wind forced currents, volume lost by evaporation, and gravitational circulation. Moreover, these ecosystems are often subjected to a great deal of anthropogenic impact, which further complicates our understanding of these habitats. Comparative studies of lagoonal environments essentially require the utilization of organisms that are distributed worldwide and occur in high density populations in most of the benthic niches. This is certainly the case for foraminifers which, as lower trophic level members, are crucial to the biological community and ideal candidates for comprehensive habitat assessment. Some widespread paralic benthic foraminiferal species are present from temperate macrotidal estuaries to tropical microtidal lagoons, thus enabling comparative studies of environmental conditions to be conducted. Since lagoons are increasingly affected by environmental stress and degradation due to pollution and other anthropogenic factors, there is a pressing need to develop a set of indicators and monitoring approaches with which to assess their health. A large number of research programs have addressed these issues within various regions, and studies of foraminiferal assemblages have produced very useful, comprehensive datasets on environmental and biotic conditions. This paper is a review of what is known about the foraminiferal assemblages living in lagoons, including their distribution according to environmental parameters and their value when it comes to assessing environmental quality in these ecosystems. Chapter 3- It is important to develop tools to get realistic predictions of how, e.g., the loading of contaminants and future climate changes may affect the structure and function of aquatic ecosystems. The CoastWeb-model presented in this work in meant as such a tool. CoastWeb is a process-based mechanistic foodweb model for coastal areas (the ecosystem scale) and includes a mass-balance model (CoastMab) for phosphorus. The model is based on ordinary differential equations and gives monthly calculations of production and biomasses for ten functional groups (phytoplankton, benthic algae, macrophytes, bacterioplankton, herbivorous and predatory zooplankton, zoobenthos, jellyfish, prey and predatory fish). CoastMab calculates in- and outflow, sedimentation, diffusion, resuspension, up- and downward mixing, biouptake and retention of phosphorus in biota. There are algorithms for, e.g., migration of fish and plankton between the given coastal area and the sea and the influence of exposure on macrophyte cover . The paper presents case-studies on eutrophication, overfishing and toxic contamination illustrating the potential of CoastWeb as a tool for sustainable coastal management. Increased nutrient loading will cause several changes to the foodweb characteristics of the studied coastal area. Some of these could be expected without a model, but here they have been quantified using a general foodweb model. The model accounts for different compensatory effects that are difficult to quantify without a
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model. The case-study on overfishing indicates that increased fishing will likely affect the studied coastal system marginally because the migration of fish from the sea is large in the studied coastal area. The case-study on toxic contamination shows that a reduction of zoobenthos biomass will have clear effects of fish production and biomass in the studied coastal area. Chapter 4- ICOLLs are considered to be one of the most ecologically productive ecosystems on earth. Similar to other coastal water bodies, ICOLLs lie at the interface of marine, freshwater and terrestrial systems and therefore represent highly dynamic transition zones between river/creek catchments and near-shore coastal waters. ICOLLs often act as net sinks of land derived sediments and nutrients; mature systems are believed to act as a source of organic material and nutrients to the adjacent sea. Suzuki et al., (1998) describes ICOLLs as having unique structural and functional characteristics as a consequence of their position in the landscape, thus having large spatial and temporal variability in their environmental and (consequently their dependant) biological variables. The focus for this chapter is micro size ICOLLs, classified as any coastal water body that has: (i) the presence of barrier beach, spit or series of barrier islands that can restrict oceanic exchange; (ii) a surface water area of less than 0.5 km2 (iii) the retention of all or the majority of the water mass within the lagoon during low tide in the adjacent sea; and (iv) the capacity of to remain brackish to fully saline either by percolation through and/or overtopping through inlet/outlet channels. ICOLLs can be viewed in a hierarchical manner, with the ocean and catchment influencing other smaller scale processes. Characteristics of the catchment and oceanic regimes influence water quality, tidal regime, stream flow, sediment delivery and seston within an ICOLL. Flow regimes and sediment loads in turn affect ICOLL morphology and sediment composition, such as nutrient status and organic matter composition. Alterations in catchment flow can either increase the residence time of water within an ICOLL increasing the susceptibility to eutrophication or decrease the residence time possibly leading to nutrient limiting conditions. In turn, these attributes determine the biological diversity and functioning of these systems. Chapter 5- Among the biological components of estuarine systems and other transitional coastal waters, waterbirds are probably the group that has been monitored more intensively and throughout longer time series, especially due to the use of citizen science. Moreover, several authors have reviewed, organized and analyzed critically the role and potential use of waterbirds as bioindicators. Recently, academic research has encouraged more intensive monitoring of waterbirds in the context of bioindication in wetlands and coastal waters. However, in the particular case of coastal lagoons, birds have received little attention compared to research efforts directed to other taxa, ignoring their important role as top predators and underestimating their contribution to various ecological processes. Few studies have included waterbirds as integral components of the food webs in lagoons, relating them to other biota. However, recent studies show that waterbirds respond to changes imposed by a variety of stressors, constituting warning signals against undesirable changes. Waterbirds can be used as bioindicators both at suborganismic and at population-community-ecosystem levels. Either approach requires that the relationships birds establish with habitats and with
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the ensemble of the lagoon‘s biocoenosis are clarified. As these relationships and the bioindicator role of waterbirds are established in more detail, stands out their usefulness as indicators of impairment in coastal lagoons of similar characteristics, subject to similar impacts with time lags. Studies on the waterbird community of the Mar Menor Lagoon (SE Spain) show the long-term response of populations to variables related to eutrophication and biological changes (proliferations of jellyfish and changes in fish stocks). Studies based on community variation in relation to internal environmental gradients of the lagoon, show spatial responses that can be mapped, and provide a basis for building indices of integrity. This is a relevant issue given the paucity of studies that explore and apply the indicator value of birds in conservation and environmental evaluation, particularly in the Mediterranean and elsewhere in temperate latitudes. Recent studies that integrate the monitoring of different physico-chemical and biotic variables of the lagoon with waterbird numbers and distribution, and research on waterbird trophic ecology based on stable isotope analysis, aim at clarifying the role of waterbirds as top-down controllers in the food webs of coastal lagoons. A role whose monitoring is also important from an applied perspective, given the potential of some waterbirds like cormorants to become conflicting species (through their interaction with fisheries). The application of these monitoring schemes to other Mediterranean lagoons emerges as a valuable tool for assessing and preventing changes in the ecological status of these systems with respect to relatively undisturbed, reference conditions. Chapter 6- The basic aim of this work has been to present a general approach to quantify how coastal systems are likely to respond to changes in nutrient loading. The conditions in most coastal areas depend on nutrients emissions from points sources, diffuse sources, river input and the exchange of nutrients and water between the given coast and the outside sea, but all these fluxes can not be of equal importance to the conditions in the given coastal area, e.g., for the water clarity, primary production and concentration of harmfull algae (such as cyanobacteria). This work describes how a general process-based mass-balance model (CoastMab) has been applied for the case-study area, the Himmerfjärden Bay on the Swedish side of the Baltic Proper. The model has previously been extensively tested and validated for salt, phosphorus, suspended particulate matter, radionuclides and metals in several lakes and coastal areas. The transport processes quantified in this model are general and apply for all substances in all aquatic systems, but there are also substance-specific parts (mainly related to the particulate fraction and the criteria for diffusion). This is not a model where the user should make any tuning or change model constants. The idea is to have a model based on general and mechanistically correct algorithms describing the transport processes (sedimentation, resuspension, diffusion, mixing, etc.) at the ecosystem scale and to calculate the role of the different transport processes and how a given system would react to changes in inflow related to natural variations and anthropogenic reductions of water pollutants. The results presented in this work indicate that the conditions in the Himmerfjärden Bay are dominated by the water exchange between the bay and the outside sea. The theoretical surface-water retention time is about 19 days, as determined using the mass-balance model for salt, which is based on comprehensive and reliable empirical data. This means that although this bay is quite enclosed, it is still dominated by the water exchange towards the sea. Local emissions of nutrients to the Himmerfjärden Bay are small compared to the nutrient fluxes from the sea. If the conditions in this, and many similar bays, are to be improved, it is very important to lower the nutrient concentrations in the outside sea.
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Chapter 7- Evidence suggests that hydraulic dredging is accompanied by considerable adverse environmental impacts on the receiving ecosystem especially on the benthos and water quality. Recently, innovative dredging is designed to minimise environmental impacts and enhance the ecological settings. Evaluations of environmental consequences of such innovative dredging are essential to quantify the ecological benefits and the associated impacts to ensure good environmental management. Congruently, innovative dredging (‗design with nature‘ principle) in a large tropical coastal lagoon in Ghana (Keta lagoon), West Africa, was assessed Before, During and After dredging operations on spatio-temporal scales to ascertain the environmental impacts on the macrobenthic fauna, shorebirds and water quality. A total of 9091 million cubic meter of sediment was removed from the 8m stretch of the lagoon for beach nourishment, land reclamation and creation of habitat islands. The macrobenthic fauna was sampled once in 2000 (Before), 2001 (During) and 2002 (After) along seven stations (A-0 to G-0 of 1-km interval) in the dredged channel. Water quality was assessed at the subsurface and bottom layers quarterly from June, 2001 to September, 2002. The shorebirds community abundance were quantified monthly from August 2000 to 2002, but only parallel data from August-December (peak periods of shorebirds abundance) of each year (2000-2002) was used for statistical analyses. The results demonstrate that dredging had initial adverse effects on numerical abundance of macrobenthic fauna but with evidence of recovery a year after the dredging (2002). Species recorded in 2001(During Dredging) and 2002 (After Dredging) were very similar in terms of composition particularly in the wet periods, suggesting the influence of seasonal environmental factors. The abundance of the species showed significant spatio-temporal variations (p<0.05). The macrobenthic fauna was dominated by opportunistic species of the family Capitellidae. Although, Nepthys lyrochaeta revealed higher frequency of occurrence (52%), there was significant (p<0.05) decrease in abundance after dredging (2002). Conversely, Notomastus cf. latericeus depicted significant (p<0.05) increase (recovery) after dredging (2002). There was no apparent impact on coastal avifauna although numerical abundance of wader group decreased from 78% in 2000; 69% in 2001 to 51% in 2002. Conversely, terns showed increased abundance from 17% in 2000, 21% in 2001 and 47% in 2002 indicating positive impact. The shorebirds placed in the ‗others‘ category experienced peak and trough between the period (6% in 2000; 10% in 2001, and 2% in 2002). In general mean numerical abundance of the shorebirds increased from 8.8% in 2000 (Before) to 81.5% in 2002 (After) of the periods. Temporal and spatial variability occurred in the physicochemical parameters measured (e.g., salinity, total dissolved solids, total suspended solids and sulfate). However, elevated turbidity occurred in localised areas along the fetch during the dredging operation. The results of the analysis presented are pertinent to several questions, such as what are the expected ecological benefits of innovative dredging and adverse impacts on the receiving ecosystem. Chapter 8- In the latest years, the environmental research has focused on studying the water quality of marine-coastal ecosystems and on the main consequences of human activities within these environments, their surroundings and catchments. Among aquatic water systems, coastal lagoons are particularly vulnerable to water-quality deterioration, due to their restricted water exchange. In addition, they are used as nursery areas for aquaculture and fisheries exploitations, which represent the main economic relevance for local inhabitants. Protection of the ecological status of worldwide lagoons has to be the key purpose of the
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International directives, as coastal lagoons are naturally stressed ecosystems which suffer from frequent environmental disturbances and fluctuations related to their geomorphologic characteristics, general hydrodynamics, abiotic and biological parameters. The main keys of ecological research studies in coastal lagoons are represented by the need to improve the general knowledge on system dynamics focusing on the leading aspects useful to develop eco-compatible management plans which allow us to preserve their productivity avoiding losses of biodiversity related to the increase of bioavailabile nutrients. The increasing number of ecosystems exhibiting frequently a progressive decline of water quality has led environmental researchers and managers to identify eutrophication as a major worldwide problem. The development of simple and not expensive well calibrated indices of eutrophication represents one of the most actual ecological fields in which researchers are involved. Many European countries have developed within the Water Framework Directive (CE 2000/60), an environmental quality classification scheme in order to assess the trophic state and water quality through the use of specific indices based on environmental factors. Our aim is to evaluate nowadays the state of knowledge related to eutrophication of worldwide lagoon ecosystems, highlighting the main fields of interest and major problems. Leading problems are related to the choise of useful indices, their calibration, their efficiency in describing dynamics of lagoons characterized by different trophic levels and the selection of the opportune pristine ecosystem as reference for lagoon classifications related to water quality. Chapter 9- A number of different approaches can be used when managing contaminated sediments depending on site-specific conditions, sediment characteristics, mix of contaminants in the sediment and local regulations. Ex situ management options can include landfill disposal or, more generally, the application of remediation treatments for beneficial reuse, which may improve the economics of management and/or be required to meet regulatory requirements. Chemical oxidation involves the use of chemical additives to remediate sediments contaminated by organic compounds. Due to electron transfers between two (or more) compounds, pollutants are degraded into less toxic or biologically available chemical forms. Chemical oxidation also changes the pH and redox conditions of the treated system, which may also alter the mobility of the target and other compounds and elements. Several different oxidizing agents are available that result in different effectiveness on different pollutants. The most commonly used oxidants are Fenton-like reagents (hydrogen peroxide catalyzed by bivalent iron ions), ozone, permanganate, and persulfate. Recent laboratory studies have also shown good results in peroxy-acid systems (an organic acid mixed with hydrogen peroxide) to degrade compounds such as Polycyclic Aromatic Hydrocarbons (PAHs). Oxidation is a non-selective process. Therefore, the oxidizable material within the sediment (natural organic matter, detritus, etc.), which may be a significant percentage of the sediment mass, can consume the oxidizing agent. Moreover, many different reactions can occur (acid/base reactions, sorption/desorption, dissolution, hydrolysis, ion exchange, oxidation/reduction, precipitation, etc.). Pollutant removal efficiency strictly depends on the contamination (pollutants, concentrations) and the sediment being treated (physical-chemical properties and composition). Laboratory tests are always necessary to evaluate the feasibility of the treatment to select the best oxidizer and the proper treatment configuration.
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This chapter reports on laboratory batch tests conducted on sediments from Porto Marghera (Italy) and New York/New Jersey Harbor (NY, USA). Porto Marghera sediments were treated with Fenton-like reagents to remove total petroleum hydrocarbons, PAHs, and polychlorinated biphenyls. Different oxidizers (Fenton-like reagents, persulfate, and peroxyacid) were used for the New York City sediments polluted by PAHs. For the latter sediments, the leachability of metals in the treated sediments and filtration resistance were also assessed to understand potential unintended consequences of treatment on metal availability and sediment dewatering operations. Chapter 10- The Gulf of Finland is a large bay in the Baltic Sea where major changes have taken place during the last 100 years. The Secchi depth has, for example, decreased from more than 7 m to about 5 m. The basic aim of this work has been to try to reconstruct the development that has taken place in this bay during the last 100 years. Since the conditions in the Gulf of Finland depend very much on both the river input of nutrients directly to the bay and the exchange of nutrients and water between the bay and the Baltic Proper, this work has focused on such interactions. The work describes how a general process-based mass-balance model (CoastMab) has been applied for the Baltic Proper and the Gulf of Finland. The model has previously been extensively tested and validated for phosphorus, suspended particulate matter, radionuclides and metals in several lakes and coastal areas. The transport processes quantified in this model are general and apply for all substances in all aquatic systems, but there are also substance-specific parts (mainly related to the particulate fraction and the criteria for diffusion). This is not a model where the user should make any tuning or change model constants. The idea is to have a model based on general and mechanistically correct algorithms describing the monthly transport processes (sedimentation, resuspension, diffusion, missing, etc.) at the ecosystem scale and to calculate the role of the different transport processes and how a given system would react to changes in inflow related to natural changes and anthropogenic reductions of water pollutants. The results presented in this work indicate that it is possible to remediate the Gulf of Finland and the Baltic Proper to the conditions that characterized the system 100 years ago. About 7000 tons of phosphorus (including 1800 tons from the tributaries to the Gulf of Finland) must then be removed on an annual basis from the present annual tributary load of about 30000 tons to the Baltic Proper. The trophic conditions in the Baltic Proper have varied relatively little during the last 25-30 years. The most marked changes in Secchi depth in the Gulf of Finland took place between 1920 and 1980. Chapter 11- This chapter illustrates some of the major issues for the management and use of coastal lagoons using two examples from the South of France. These are the mesotidal Bassin d‘Arcachon on the Atlantic coast and the microtidal Etang de Thau on the Mediterranean (see Figure 1). Oyster-farming is a major use in both lagoons. Coastal lagoons are part of a coastal landscape and are therefore typical transition zones between the continent and the sea, characterised by gradients and ecotones. Thus, it is most important to consider the coastal lagoon ecosystems in the context of the coastal zone and consider their links both with the ocean as well as with the hinterland. The latter requests a thorough knowledge of the watershed of the lagoon. Coastal areas, which are commonly defined as the interface or the transition area between land and sea, are diverse in function, form and dynamics. In general, these systems are not well defined by strict spatial boundaries and include low lands, intertidal zones, salt marshes, wetlands, lagoons and their watersheds. From the development and management point of view, the coastal areas are characterised by the economical
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activities that they support and by the impact of these activities on the environment. Accordingly, the coastal areas are characterised by i) the production of living resources, ii) highly diverse human uses including urban development, exploitation of sediments, shipping and harbours, commercial and sport fishing, aquaculture, tourism, and as a receptacle of industrial and agricultural waste, iii) their role in providing protection against flooding and by iv) their biodiversity and role in the functioning of the ecosystems at different spatial levels. Chapter 12- The Garaet El Ichkeul in Northern Tunisia has long been recognized as one of the four major wetland areas in the Western Mediterranean basin (MAB Reserve in 1977, World Heritage and Ramsar site in 1980). The Ichkeul lagoon and its marshes perform essential ecological functions which are the basis of multiple services that contribute to the wellbeing and economy of the local community. The villagers living within the core area and the buffer zone have used to make a living off the land that did not seem to pose any threat to the functions and services of these ecosystems. However, the construction of dams on the rivers which provide water for the lake and marshes, as planned by the Tunisian Ministry of Agriculture for the purposes of agricultural, urban and industrial development, has had an impact on the ecological character of the site. The Tunisian authorities, aware of the impact of these dams on the natural environment at Ichkeul, founded a National Park. Unfortunately, the Park regulations were introduced without taking properly into account the reality of the socio-economic conditions of local residents. The lack of rehabilitation measures forced the villagers to exploit the resources in a non-selective way, which in turn further aggravated the existing pressure on the Park and the precarious social conditions in which the families survive. An international multidisciplinary study of all biotic and non-biotic aspects of the National Park drew up an integrated management plan which was designed to take into account the socio-economic development of the region. Since then, a number of conservation measures have been adopted by the Tunisian authorities. They mainly take into account the flora and fauna but without consultation of the people affected by these measures – a fact that possibly explains the limited implementation of the management plan proposed by the multidisciplinary study. The question is of more than local interest, since similar problems arise throughout the Mediterranean and elsewhere, i.e. conservation measures have been introduced but the legislation is not respected in practice. When stakeholders are not involved initially or are brought into the process at a later date, without the opportunity to provide input, they are seldom supportive of the policy outcome. This is due in large part to the continued reluctance of natural scientists and developers to learn from local community practices, as opposed to management systems established on the basis of scientific facts. However, recent studies on traditional ways of living off the land claim that the local communities have developed elaborate processes for sustainably exploiting their resources. Such practices can provide an important information base for integrated resource management. The goal is: (1) to promote recognition of the traditional resource practices and the accumulated wisdom as important features within ecological research, and (2) to stimulate debate about whether their input will have significance for improving environmental management policy. Chapter 13- A multidisciplinary study of sediment cores from Doñana National Park (SW Spain), a broad region of wetlands in SW Spain, provides the base for the reconstruction of the main palaeoenvironmental changes that occurred in the Guadalquivir estuary since OIS 3. The facies analysis differentiates six main facies, deposited in freshwater pond and marsh
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(FA-1: laminated silt), brackish marsh or the periphery of a brackish lagoon (FA-2: greyish silt), a shallow lagoon (FA-3: green silt and clay), the marine connection of this lagoon (FA4: yellow silt) or sandy spit (FA-6: yellow sand), whereas FA-5 includes bioclastic silt and sand with a tsunamigenic origin. The vertical arrangement of these facies, their dates and a detailed comparison with previous works permit to delimitate ten phases in the Late Pleistocene to Holocene evolution of this lowland. In the oldest phase (OIS 3), this area was occupied by freshwater marshes. Phase 2 (OIS 2) was characterized by the alternation of freshwater and brackish marshes, partly enclosed by aeolian units. During the third phase (Early Holocene), the brackish marshes constituted the northern limit of a broad lagoon that extended along the present-day inner shelf. The sea-level highstand of the Present Interglacial (Flandrian transgression, phase 4: ~6.5 cal BP) caused the inundation of this area, occupied by an open lagoon. Between 6.5 and 4.6 cal ka (phase 5), incipient brackish marshes emerged along the margins of this lagoon and a first tsunamigenic event (5100-4800 cal BP) eroded partially the Doñana spit. The following phase (4.6-3.7 cal ka) was relatively quiet, with predominance of infilling processes. This calm scenario was interrupted by a new period of instability (phase 7: 3.7-3 cal ka), with two new high-energy events. The progressive infilling is the main feature of phase 8 (3-2.2 cal ka), with the emersion of new brackish marshes and a decreasing depth in the adjacent lagoon. The first historical tsunamis (phase 9: 2.2-1.9 cal ka) induced the creation of washover fans and bioclastic ridges overlying the previous marshes. Since 1.9 cal ka (phase 10), the growing of the Doñana spit and the fluvial-tidal sediment inputs caused an important filling of the Guadalquivir estuary (Doñana National Park), only interrupted by new tsunami records (~1.8-1.5 cal ka). Chapter 14- The Alvarado Lagoon System (ALS) in south-central Veracruz State, Mexico, is a mangrove dominated coastal wetland formed by the confluence of the Acula, Blanco, Limon and Papaloapan rivers. The ALS has a maximum width of 4.5 km, a mean surface area of 62 km2, and is connected to the Camaronera Lagoon by a narrow channel and to the Gulf of Mexico (GOM) via a 0.4 km wide sea channel. Water samples were collected during the wet (September 2005) and dry (March 2003 and 2005) seasons. Salinity ranged from 1-25.5 psu and pH was slightly alkaline (7.6-8.6). Levels of total organic carbon (TOC), total mercury (Hg), and total suspended solids (TSS) ranged from 3.9-20.9 mg C/L, 0.92-26.1 ng Hg/L, and 1-39.2 mg TSS/L, respectively. The strong correlation (R2=0.71; P=0.001) between total mercury and TSS in the water column suggests that particulate matter is a carrier phase for mercury within the Alvarado and Camaronera Lagoons. The ALS is one of the most productive estuarine-lagoon systems in the Mexican GOM. Model studies suggest that primary production by sea grasses provides more energy input to the ecosystem than detritus, which is contrary to most other Mexican GOM lagoons and estuaries. In 2004 the ALS was nominated Ramsar site no. 1355 because of its important biodiversity, ecological attributes, and high resource production. Over 100 fish species have been collected from the ALS, representing four ecological guilds: marine stenohaline, marine euryhaline, estuarine, and freshwater fishes. These assemblages have not experienced significant changes over the past 40 years, but there has been a recent decline in diversity. Antillean manatees (Trichechus manatus manatus) historically have occurred in the ALS but were reduced in the 1970s and 1980s by hunting and are now considered endangered. The rescue of 6 orphan calves between 1998 and 2000 suggests that manatees are reinhabiting the ALS as a result of conservation measures. Manatees are most commonly sighted in the
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Alvarado Lagoon, Acula River and adjacent lagoons, and are rarely sighted in the Limon River and adjacent lagoons. To protect the manatees and their habitat an educational program was developed in 1998 and an assessment of their current status and critical habitat in the ALS was conducted. Our manatee conservation efforts were recognized in 2001 when September 7th was officially declared the ―National Day of the Manatee‖ in Mexico. Almost 350 species of birds occur in the ALS, including the Mexican Duck (Anas diazi), which is undergoing a slow but marked decline due to habitat destruction and overhunting. The largest threats to the ALS include unsustainable sugar cane cultivation, cattle-ranching, coastal urban development, oil and gas exploration and exploitation, water pollution by urban waste and agricultural runoff, and increases in port and tourism industries. Despite the establishment of government policy and measures to protect the coastal wetlands of ALS, the identified threats continue to menace the important biodiversity and human well-being of the region. Chapter 15- Fishery resource in the lagoon environment is the primary form of livelihood for survival and affects lives in different ways. For centuries, fishermen used to keep a certain harmony with fishery resources in a traditional manner but they have been faced with various vulnerabilities in managing fishery resources and their related livelihoods. This chapter presents a case study of fishing communities in Chilika Lagoon (India) with emphasis on adaptive capacity to respond to changes in the lagoon environment. It explores pressing constraints and positive strengths of lagoon fishery development by applying the concept of Sustainable Livelihoods Approach (SLA). The research is based on five livelihood assets analysis developed by DFID with due consideration of vulnerability assessment and institutional contexts. Drawing on Chilika Lagoon experience, the study revealed that vulnerabilities to fishery livelihoods are affected by climatic and environmental dimensions as well as by socio-economic and cultural values. The range of pressing constraints for fishing communities covers not just fishing but also marketing, schooling, social relations, social infrastructure and environmental and disaster prevention awareness. This exposure posed grave threats in lowering the capability of people in the choice of lagoon fishery development, leading to less income generation and its associated byproducts. In contrast, the study identified several attempts to cope with the underlying root causes of failure in resource-based development. The Chilika Development Authority (CDA), for instance, implemented hydrological interventions in 2000, resulting to fisheries enhancement with a spectacular increase in fish landings. The elaborations undertaken by CDA also made great contributions to institutional arrangements for watershed management with a concept of participatory micro-watershed management that has enabled the upper communities to upgrade their socio-economic status as well as mitigate the impacts of siltation. Importantly, innovative activities which are considered to be positive strengths of lagoon fishery development have been commonly associated with the involvement of various stakeholders to adjust to the ecological-social-economic system in response to actual or expected impacts. Finally, this chapter draws some suggestions on adaptive strategies for fishery development in Chilika Lagoon and potential implications to other lagoons all over the world. The findings in Chilika Lagoon fisheries provide answers to the enquiry on holistic and integrated measures to sustain lagoon fisheries by putting forward the principle of SLA. Chapter 16- A seasonal variability in the vertical flux of ice algae was examined with a multiple sediment trap during seasonal ice coverage in SaromaKo Lagoon, Hokkaido, Japan. The multiple sediment traps were moored at 4 m below the water surface and 5 m above the
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bottom to collect suspended materials at 7 dayintervals for 64 days from February 4 to April 8, 1999. Community structure of ice algae and water column phytoplankton collected with the sediment traps was determined in terms of both cell abundance and cell volume. For the ice algal community, Odontella aurita was the most dominant in cell volume, followed by Pleurosigma spp., Achnanthes spp., Detonula confervacea, Bacteriaosira fagilis, Fragilariopsis spp., and Navicula spp. while Fragilariopsis spp. and Achnanthes spp. were dominant numerically. Water column phytoplankton were dominant in descending order of cell volume by Membraneis spp. Thalassiosira spp. Campylodiscus sp., Chaetoceros spp., Amphora spp., and Dictyocha speculum, and Alexandrium sp. Mean cell volume ratio of ice algae to total algae with one standard deviation was 0.30 ± 0.28 and highly variable although a similar ratio based on cell number was 0.72 ± 0.06. The vertical fluxes of chlorophyll a (Chl a) was estimated from the volume ratio, and the mean with one standard deviation was 0.90 ± 0.42 mg Chl a m−2 d−1. This suggests that the ecological role of ice algae in a small embayment should be considered separately from ecosystem in the high latitudes although a total release of ice algal carbon from the sea ice into a water column could be similar to one in the high latitudes and only 3 g C m2 in 65 day ice season. Even during the ice coverage, due to a lateral transport of phytoplankton through two channels from the Sea of Okhotsk, where ice coverage was always incomplete, the community structure of released ice algae under the sea ice was modified significantly. A combination of laterally transported water column phytoplankton and vertically released ice algae into the underlying water column may play a significant role in the energy transfer to the successful aquaculture of scallops and oysters as well as other benthos in the shallow coastal water ecosystem. Chapter 17- Lagoons have perfect hydrodynamic perspective and very sensitive structures. First of all, the human activities on lagoons have become a major environmental concern. Any artificial influence to these sensitive areas may cause the destruction of the natural balance of them. Turkish coasts have more than 70 lagoon lakes which are formed on about 60 000 ha. area. European part of Turkey which is also named as ―Turkish Thrace‖ is surrounded by three different seas: The Marmara Sea, The Black Sea, and The Aegean Sea. The region has a lot of lagoon lakes (such as Lakes Mert and Erikli are located on the coasts of The Black Sea in Kırklareli province; Lakes Terkos, Küçükçekmece, and Büyükçekmece are located on the coasts of The Marmara Sea in İstanbul province; and Lakes Gala, Dalyan, Taşaltı, Işık, Vakıf, and Tuzla are located on the coasts of The Aegean Sea in Edirne province) which are formed at different types. Therefore, Turkish Thrace may be considered as a rich area in terms of lagoon lakes. Furthermore, some lakes are important parts of some National Parks in Turkey. In this chapter, some limnological features of some lagoon lakes located in European part of Turkey were evaluated. With this aim, both the results of the previous limnological studies performed by different researchers (by the authors and/or the others) since 1987 in some lagoons in the region and the results of the present data on the lakes which were visited on different dates by the authors at the years 2008 and 2009 for sampling were evaluated. According to the all data (both from the previous studies and from the present study) some physicochemical features, salinity levels, some biological data of the lagoons were gathered in this chapter. Furthermore, rather roughly trophy levels of the lagoons were determined by the available features which are used to determine the trophy level of the lakes. In conclusion, this study aimed to gather all data on the lagoons in European part of Turkey by making a comparison of their former and present status.
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Consequently, the results from the previous limnological studies performed in some lagoons in the region (a review); the results from the present data on some features of some lagoons (a research); limnological evaluation on all of the lagoons in the region (an evaluation) were provided in the present chapter. Thus, it was provided the whole limnological documents which have been gathered from the lakes at separate times since 1987.
In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 1-38 © 2011 Nova Science Publishers, Inc.
Chapter 1
METABOLIC AND STRUCTURAL ROLE OF MAJOR FISH ORGANS AS AN EARLY WARNING SYSTEM IN POPULATION ASSESSMENT 1
C. Fernandes 1*, A. Afonso 2 and M.A. Salgado 2
IPB - Instituto Politécnico de Bragança, CIMO - Centro de Investigação de Montanha, Campus de Santa Apolónia, Apartado 1038, 5301-854 Bragança, Portugal 2 ICBAS - Instituto de Ciências Biomédicas de Abel Salazar, CIIMAR - Centro Interdisciplinar de Investigação Marinha e Ambiental, Rua dos Bragas, 289, 4050-123, Porto, Portugal
ABSTRACT There are thousands of pollutants that affect aquatic environment and their effects have long been a concern and cause of research. This number grows annually since new compounds and formulations are synthesized. At present the concept of pollution involves knowledge of environmental fate and effects of chemical pollutants and their impacts on both, ecosystems and on social and economic development. Some aquatic environments are vital because of their critical ecological and economic importance. There are numerous lakes, lagoons and coastal lagoons playing a social and economic role on adjacent human populations, as they support fishing and recreational activities, and an ecological role, as they also support a characteristic flora and fauna, becoming important habitats. Additionally, several of these fresh waters reservoirs become a vital supply of potable water. In many cases, even in sub-lethal concentrations, aquatic pollutants affect structure and normal functioning of natural populations as they can cause impacts at multiple levels of organization, including cells, tissues, organs, individuals and community level. Several aquatic species can be used to study these issues and fish has been proved to be a suitable test-organism. Fish organs, such as liver, spleen and kidney can be very helpful to understand the response mechanisms to pollutant exposure. Fish liver is the main target organ of dietary route and the central metabolic organ, where detoxification mechanisms * Corresponding author: E-mail:
[email protected]. Fax: +351 273 325 405.
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C. Fernandes, A. Afonso and M. A. Salgado occur; spleen is involved in development of circulating blood cells, as well as immunity; and kidney is involved with excretion and thus, with electrolyte balance and acid-base regulation. Moreover, the anterior part of kidney supports the main pool of several fish leukocyte types. Assessment of coastal and shallow lagoon waters is a top priority among environmental monitoring activities, due to high ecological and economical importance of these relevant resources. In particular in enclosed communities, such as lakes and lagoons, this issue is enhanced according to the abundance and diversity of wildlife and increased need for water quality. Fish are relatively sensitive to changes in the environment and toxic effects of pollutants may start to occur in the cell and in metabolic pathways, before significant alterations in behaviour or morphology can be identified. The knowledge of normal metabolic processes of these major fish organs and alterations induced by exposure to pollutants can be a tool for an early warning system in the evaluation and analysis of the wealth of a fish population and their natural environment.
1. INTRODUCTION There are thousands of pollutants that affect aquatic environment and their effects have long been a concern and cause of research. This number grows annually since new compounds and formulations are synthesized. At present the concept of pollution involves knowledge of environmental fate and effects of chemical pollutants and their impacts on both, ecosystems and on social and economic development. Some aquatic environments are vital because of their critical ecological and economic importance. There are numerous lakes, lagoons and coastal lagoons playing a social and economic role on adjacent human populations, as they support fishing and recreational activities, and an ecological role, as they support a characteristic flora and fauna, becoming important habitats. Additionally, several of these fresh waters reservoirs become a vital supply of potable water. Assessment of coastal and shallow lagoon waters is a top priority among environmental monitoring activities, due to high ecological and economical importance of relevant resources. In particular in enclosed communities, such as lakes and lagoons, this issue is enhanced according to the total and the diversity of wildlife and increased need for water quality. Fish, compared with invertebrates, are more sensitive to many toxicants and are the convenient test-objects for water quality assessment and toxicological effects. They are exposed to pollutants via two main routes, waterborne and dietary and, fish can develop early signs of toxic effects, even with low contamination levels. Depending on time of exposure, bioavailability and chemical speciation of pollutants in water, as well as several biotic and abiotic factors, and synergistic or antagonistic effects, aquatic pollutants can cause impacts on natural fish populations at multiple levels of organization, including cells, tissues, organs, individuals and community. Several biomarker evaluations can be used to monitor environmental activities. Toxicants body burden in fish tissues can be a helpful indicator of contaminant exposure however it depends on chemical type and speciation, and metabolic processes such as absorption, redistribution and compartmentalization into specific tissues and it is not easy to interpret,
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when there are several contaminants involved. On the other hand, the variety of highly sensitive physiologic mechanisms in fish, together with multiple contaminants exposure, may lead to an integrated stress response, beyond to their toxic effects at the cell and tissue levels. The ideal bioaccumulation marker of exposure is one that is chemical-specific, accurately measurable in trace quantities, measurable in easily sampled biological tissues or by noninvasive techniques, and correlates well with exposure history (Van der Ost, 2003). However several biomarker responses have been tested on limited number of compounds, ecosystems, and for relatively short periods of time. The complementary use of non-specific biomarkers could bring a wider range of application on environmental monitoring, related to broadspectrum of contamination. Fish organs, such as liver, spleen and kidney can be helpful to evaluate the impact and understand the response mechanisms to toxic exposure and so can be used as useful biomarkers in monitoring environmental quality. Fish liver is the main target organ of dietary route and the central metabolic organ, where detoxification mechanisms occur; spleen is involved in development of circulating blood cells, as well as immunity; and kidney is involved with excretion and thus, with electrolyte balance and acid-base regulation. Moreover, kidney is the major hematopoietic organ and its anterior part (pronefros) supports the main pool of several fish leukocyte types. The knowledge of normal metabolic processes of these major fish organs and alterations induced by exposure to pollutants can be a tool for an early warning system in the evaluation and analysis of the quality of aquatic environment and fish population wealth. Biochemical responses to contaminant exposure can include changes in hematologic parameters and in plasma electrolytes concentrations, as well as histopathologic alterations in several organs including liver, kidney and spleen. It is also useful, from both economic and public health points of view, to assess the effect of chemical pollutants on the fish immune system, and on their vulnerability to infection.
2. LIVER, ITS ROLE IN METABOLISM, ACCUMULATION AND REGULATION OF XENOBIOTIC COMPOUNDS Fish liver, the largest visceral organ, plays a major role in metabolism, namely detoxification, protein and hormone synthesis, glycogen storage and lipid metabolism. It produces bile, an alkaline compound which aids in digestion, via the emulsification of lipids. It also performs and regulates a wide variety of biochemical reactions requiring highly specialized tissues, including the synthesis and breakdown of small and complex molecules, many of which are necessary for normal vital functions (Wolf and Wolfe, 2005). Liver has also a key role in regulating vertebrate homeostasis, including reproductive cycle (Rocha et al., 2003). There are two general basic types of livers: those that contain pancreatic tissue vs. those that do not. Fish livers with exocrine pancreatic tissue are often called ―hepatopancreas‖ (Bruslé and Anadon, 1996; Rocha and Monteiro, 1999). Reports on the morphology of fish liver reflect the structural non-lobulation of the hepatic parenchyma, quite different from traditional lobulation as reported in the mammalian liver.
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The liver major vascular organization consist of afferent blood vessels entering by the hilum – hepatic artery and portal vein – and efferent veins - hepatic vein(s) - emerging at the anterior surface of the organ, which is not always a single vessel. It is consensual that hepatocytes are the main component of the fish liver and the most important structural element of the hepatic parenchyma. Covering the liver, there is a thin (Glisson) capsule that can bridge through the submesothelial connective tissue with the intrahepatic interstitial one. The more numerous liver cells are hepatocytes and usually 3 structures appear evidenced: dense bodies - that include primary and secondary lysosomes and residual bodies -, lipid droplets and glycogen. Hepatocyte morphology depends on the quantity of storage products, such as lipid and glycogen, and also on the reproductive cycle, in particular the estrogeninduced state of vitellogenesis in spawning females (Vethaak, 1993). Hepatic organization is not exactly the same in all fish species (Robertson and Bradley, 1992) and variations with age, nutritional status, temperature and sexual maturation normally occurs (Van Bohemen et al., 1981; Storch et al., 1984; Barni et al., 1985). The endocrine influences, which are strongly connected with the environmental regulation breeding status, also affect hepatic structure (Rocha and Monteiro, 1999).
Histopathology Histopathology of fish liver is a monitoring tool that can provide an assessment of the effects of environmental stressors on fish populations, and it has been considered one of the most reliable indicators of health impairment on aquatic animals due to anthropogenic activities (Hinton and Laurén 1990; Stentiford et al. 2003). Despite some morphological differences among species, liver is essentially similar in all vertebrates. There are more similarities than differences between fish and mammals in terms of their macro- and microanatomy, physiological and biochemical characteristics, and pathologic responses to hepatotoxic substances (Wolf and Wolfe, 2005). In terms of anatomical differences, fish have a relatively lower liver to body weight ratio, they have 1/4 to 1/2 less liver perfusion than mammals (Klassen and Plaa, 1967; Gingerich, 1984). But it is however, the hepatocyte architecture one of the relevant features of fish liver anatomy. The relation of hepatocytes and the blood ductules and canaliculi draining into them, make the basal and basolateral aspects of hepatocytes the only ones to be directly exposed to sinusoidal perfusion. Consequently the uptake of some chemicals may be lower. On the other hand, the blood flow through fish hepatic sinusoids is relatively slower, increasing the time of uptake, which may partially compensate for the reduced hepatocyte exposure (Hinton, et al. 2001, Gingerich, 1982). Liver histopathology has been used as an indicator of environmental stress since it provides a definite biological end-point of historical exposure (Stentiford et al. 2003), and the kind of injury is often dependent upon time of exposure to pollutants, such as metals (Yang and Chen 2003; Au 2004; Olojo et al. 2005). Although, liver histopathological alterations are not specific to pollutants, several studies have established a causal relationship between metal concentrations and fish liver lesions (Au 2004). Because the liver is so important in detoxification, exposure to contaminants can lead to an increase in liver size from hypertrophy (an increase in size), hyperplasia (an increase in
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number) of hepatocytes (Goede and Barton 1990; Hinton and Lauren 1990), or both. Significant higher Zn- and Cu-liver content associated with extensive hepatic heterogeneous parenchyma, with large spectrum of vacuolization, observed in mullet (Liza saliens) suggest that these abnormalities could be a response to metal chronic exposure (Fernandes et al., 2008c). Ultrastructural changes induced by toxicant exposure may include increased numbers of organelles such as myelinated bodies, mitochondria, glycogenosomes, peroxisomes, and lysosomes, and changes in rough endoplasmic reticulum (increased amount, vesiculation, and dilatation). Physiologic hypertrophy of hepatocytes can be observed in reproductively active female fish, or in male fish that have been exposed to exogenous estrogenic compounds, since estrogens stimulate hepatocyte metabolism for vitellogenin (yolk lipoprotein) production (Wester et al., 2003). These phenomena however can have a physiologic or toxicologic cause. Cytoplasmic and nuclear enlargement (megalocytosis), are others histologic alterations observed in cases of algal toxicity in farmed Atlantic salmon (Kent et al., 1988; Andersen et al., 1993; Stephen et al., 1993). Other types of nuclear changes, such as enlarged, binucleate, or bizarre nuclei, are seen occasionally, most often in the repair stages of toxicosis (Ferguson, 1989). A common and certainly pathologic, response of the fish liver to toxins is hepatocyte necrosis. The most characteristic reaction to toxicity is an apoptotic type of single cell death (Ferguson, 1989; Boorman et al., 1997). Typically, a random pattern of necrosis rather than a zonal pattern can be seen in fish liver, although occasionally a perivenous distribution of necrosis is observed (Casillas, et al., 1983). Necrosis of the biliary epithelium can also be induced in rainbow trout experimentally exposed to the toxin alpha-naphthylisothiocyanate (Metcalfe, 1998). Unlike mammals, cirrhosis is rarely seen in the fish liver as a sequel to hepatocellular necrosis (Ferguson, 1989). Piscine cholangiofibrosis may be accompanied by bile duct hyperplasia, increased numbers of bile ductule and/or oval cells, and nonneoplastic proliferation of the biliary epithelium (Boorman et al., 1997). Neoplasia, in fish liver collected from natural waters, has been one of the histologic biomarkers used in many research studies, to assess the hepatotoxicity of pollutants. There is now solid evidence, however, that fish should also be recognised as valid models for assessing other nonneoplastic biomarkers, in terms of both field and laboratory-based research (Wolf and Wolfe, 2005).
Glycogen and Lipid Reserves A common morphologic response of the fish liver to toxicity is a loss of hepatic glycogen and/or lipid (Ferguson, 1989). Macroscopically, affected fish have small, dark livers; microscopically, decrease of hepatocellular vacuolization, and size alterations of hepatocytes. Loss of glycogen or lipid can occur as a direct effect of intoxication, or it may occur secondary to decreased body condition, caused by inanition, stress, or concurrent disease. The latter is probably more typical. However, accumulation of fat or glycogen in the liver has also been observed in Japanese medaka (Oryzias latipes) (Wester et al., 1988) and guppies (Poecilia reticulate) (Wester and
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Canton, 1987), as a result of organotins exposure. The hypothesis to explain such results was that glycogen accumulation was due to decreased glycogen breakdown in consequence of hepatocellular toxicity. Liver of fish stores large amounts of lipids (triglyceride), but unfortunately this feature can hardly be used as a biomarker of hepatotoxicity since there are no accepted criteria for the diagnosis of hepatic lipidosis. Different percentages of lipid concentrations can be accumulated by different fish species (McLelland et al., 1995), so that the concentration above which lipid accumulation would be pathologic, would rather vary, however there are several reasons to use this alteration with some precaution as a reliable biomarker of contamination. Hepatic lipidosis in extreme may result in the fusion of the fat globules from neighbouring hepatocytes, but even though may not be detrimental or irreversible in all fish. In addition it may be nutritionally induced (Penrith et al., 1994) by an excessively energy-rich diet or caused by lipid peroxidation associated with diets rich in polyunsaturated fats and/or by the suppression of vitamin E (Ferguson, 1989). Lipid peroxidation in fish may also be toxicant-induced. The induction of hepatic lipid peroxidation caused by chronic dietary exposure to Cu was confirmed in grey mullet (Chelon labrosus) (Baker et al., 1998) and in mullet (Liza saliens) chronically exposed to Cu (Fernandes et al., 2008b). Sediment contaminated with polyaromatic hydrocarbons, polychlorinated biphenyls (PCBs), and metals have been described as lipid peroxidation inducters in channel catfish (Di Gulio et al., 1993) and in juvenile grey mullet Liza ramada exposed to atrazine (Biagianti-Risbourg and Bastide, 1995). Lipid or glycogen vacuolization can cause an increase in the size of hepatocytes; however, Hinton et al., (1992) identified 3 additional potential causes of hepatocellular enlargement: organelle proliferation (hypertrophy); the failure of sublethally-injured hepatocytes to mitotically divide (megalocytosis); and vacuolar swelling of the endoplasmic reticulum cisternae (hydropic degeneration). Hepatocyte hypertrophy was observed in rainbow trout that was simultaneously exposed to endosulfan and disulfoton (Arnold et al., 1995).
Biotransformation System of Xenobiotics In terms of physiology, the liver of fish, as the liver of mammals, is responsible for the same basic metabolic functions: processing, and storage of nutrients, enzyme and cofactors synthesis, bile formation and excretion, and the metabolism of xenobiotic compounds. A complex multienzyme family, normally referred as the biotransformation system, accomplishes the biotransformation of xenobiotics in fish. This system metabolizes both, endogenous and foreign compounds, through a series of reactions, which can be divided in two steps: Phase I that often produces reactive or toxic metabolites, and phase II where larger groups are conjugated with the oxygenated xenobiotic into polar, water-soluble and lessreactive end-products and thus can be excreted from the organism. Fish have many of the same microsomal and cytosolic enzymes as mammals (Cowey and Walton, 1989). The cytochrome P450 (CYP) monooxygenase system comprise a family of enzymes that catalyse phase I monooxygenation reactions and among them, the CYP1A,
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which can be found in hepatocytes, biliary epithelial cells, and endothelial cells (Stegeman et al., 1979; Stegeman and Hahn, 1994; Hinton et al., 2001). The activity of this enzyme has been demonstrated to vary according to the type of inducer, the exposure route, and the fish species (Hinton et al., 2001). Fish also have an enterohepatic cycling mechanism (Gingerich, 1982) to process the substances that were not metabolized during their first pass through the liver. This enterohepatic cycling may increase the efficacy of xenobiotic removal (Gingerich, 1982; deBethizy and Hayes, 2001). The induction of the CYP1A system has become an important tool for monitoring environmental exposure of fish to organic compounds (Hodson et al., 1991) and has been extensively used as a biomarker of aquatic contamination by different pollutants in freshwater as well as in marine environments (Narbonne et al., 1991; Parente et al., 2004). The CYP1A is a sensitive indicator to different environmental contaminants, such as polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and pesticides, in mammalian as well as in fish (Haasch et al., 1993). In this context, the cytochrome P450-dependent monooxygenase induction, measured as ethoxyresorufin O-deethylase (EROD) activity, has been used as an indicator of exposure to pollutants (Setegman and Lech, 1991; Stegeman and Hahn, 1994; Whyte et al., 2000; Pacheco and Santos, 2002; Ferreira et al., 2004). The expression of hepatic CYP1A and its evaluation by increases in EROD activity has been used in field and laboratory studies to assess the pollutants exposure in different fish species (Narbonne et al., 1991; Goksøyr and Förlin, 1992; Ferreira et al., 2004; Miller et. al 2004; Lee and Anderson, 2005; Bacanskas et. al, 2005). Nevertheless, there are a number of essential physiologic differences between mammalian and fish livers, some of which may affect the rate, pattern, and/or extent of toxicity that occurs in a fish following chemical exposure. One of the most important differences is that fish appear to have a relatively homogenous distribution of biotransforming enzymes in their livers (Gingerich, 1982; Schar et al., 1985; Metcalfe, 1998; Hinton et al., 2001) that is, there is generally no preferential location for these enzymes within anatomical structures, such as central veins. The significance of this dissimilarity will be addressed shortly. Another difference is that fish monooxygenases like CYP1A may be refractory to some classic cytochrome inducers such as phenobarbital (Ferguson, 1989), or variably responsive to other inducers such as 3-methylcholanthrene (Di Gulio et al., 1995) or resistant in cases where fish has been chronically exposed to heavy pollution. A PAH-resistant population of killifish has been identified in a creosoto contaminated site (Van Veld and Westbrook, 1995) However in the same site, CYP1A was environmental induced on both hepatic and extrahepatic tissues at certain times of the year. The variability in resistance among different populations of chemically impacted killifish suggests that such a resistance can occur through different mechanisms depending on the type of toxicant, and the genetic variability of the population (Bello et al., 2001). Fish liver is more tolerant to hepatotoxins than the liver of mammals, which means that the same hepatic changes are only observed in fish exposed to greater concentrations of toxicant (Gingerich, 1984). This tolerance of fish to hepatotoxins could be attributed to some of the mentioned above factors, such as the lower perfusion rate of the fish liver, the
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limitation of toxic exposure to the basal hepatocyte membrane, the homogenous distribution of biotransforming enzymes, and the fact that some enzymes are not readily inducible. Another important propensity of the fish liver is that the lesion distribution, following toxic exposure, tends to be random, without the zonal pattern that is common to sublethal intoxications in mammals (Ferguson, 1989; Boorman et al., 1997; Hinton et al., 2001). Again, this trait has been attributed to the homogenous distribution of biotransforming enzymes in the fish liver, and the fact that the zonal architecture is not apparent.
Transaminases Many enzymes of intermediary metabolism of fish as plasma transaminases are affected by exposure to chemicals. Alanine aminotransferase (AlaAT) and aspartate aminotransferase (AspAT) are indicators of liver damage. They are both mitochondrial and cytosolic and are a very sensitive measure of hepatotoxicity and histophathalogic changes that can be assessed within a shorter time (Balint et al., 1997). These intracellular enzymes are involved in catabolism of amino acids, transferring amino groups to α-keto acids. Usually they are present at very low amounts in serum or plasma. Their increase in plasma may mean liver damage, resulting in their liberation and raising plasma levels (Rao, 2006). For this reason transaminases have been used as indicators of tissue damage (Oluah, 1998, 1999; De la Torre et al. 2000; Das et al., 2004). The increase in (AlaAT), and (AspAT) activities has been observed in fish experimentally exposed to various chemicals including phenols (Hori et al., 2006), organophosphorus insecticide (Rao, 2006) and metals (Varanka et al., 2001) resulting in metabolic alterations at various levels and tissues and hepatic ultrastructure changes. In field studies, where fish has been chronically exposed to environmental metals (Cu and Zn) an increase of plasma AspAT was found suggesting a change in protein metabolism (Fernandes et al. 2008c).
Metal-Binding Proteins Metallothioneins (MTs), are cysteine-rich metal-binding proteins which are believed to play an essential role in regulating the intracellular concentration of the ionic forms of zinc and copper and in protecting cells from the deleterious effects of harmful heavy metals, such as cadmium and mercury (Kaegi et al. 1981; Kaegi and Schaffer 1988; Kaegi 1993). They have an additional role in reducing the toxicity of other metals such as Ag, Cd and Hg in contaminated environments since they also bind elements from groups Ib and IIb of the periodic table (Livingstone, 1993). The relationship between metal levels in the environment and MTs concentrations in animal tissues has led to their use for monitoring the biological effects of metal exposure (Hylland et al., 1992; Livingstone, 1993). The mechanism of metal detoxification by MTs occurs via metal-initiated transcriptional activation of MT genes, resulting in an increase in MT synthesis, and subsequent binding to the free metals (Hogstrand and Haux, 1991)
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In teleost fish, there are marked variations in the inductive response between different species and there are a number of environmental and animal conditions that influence MTs synthesis, as season, temperature, salinity, dietary status and reproductive steroids (Olsson et al., 1995, 1996; Hylland et al., 1998). Interpretation of the results and consequently its use as biomarker of environmental contamination is therefore limited (Rotchell et al., 2001).
3. THE LYMPHOHEMOPOIETIC TISSUES IN FISH In vertebrates, the hemopoietic system is one of the primary targets to several insults. As fish do not have bone marrow or lymph nodes, the hematopoiesis and lymphopoiesis must occur in different fish organs (Agius and Roberts, 2003). In teleosts, hemopoiesis is mainly located within the stroma of the spleen and in the kidney interstitium (Kranz and Peters, 1984; Fänge and Nilsson, 1985; Agius and Roberts, 2003). To a lesser extent, hemopoiesis may also occur in the peri-portal areas of the liver, in the intestinal sub-mucosa and in the thymus (Kranz and Peters, 1984; Agius and Roberts, 2003; Tort et al., 2003) and there are also reports of their occasional occurrence in gills, brain and gonads (Agius and Roberts, 2003). Teleost fish species do not have lymph nodes, thus mature lymphocytes are dependent of hemopoietic tissues, such as the spleen. The thymus, kidney and spleen are the major lymphoid organs in fish (Fänge and Nilsson, 1985; Agius and Roberts, 2003; Tort et al., 2003; Zapata et al., 2006) and, to a lesser extent, mucosa-associated lymphoid tissues can occur, including in the skin and gills (Tort et al., 2003; Huttenhius et. al., 2006). The amount of lymphoid tissue in spleen of distinct vertebrates reflects the pattern of blood circulation and/or occurrence of other peripheral lymphoid organs (Zapata et al., 1996; Agius and Roberts, 2003). Therefore, teleosts splenic lymphoid tissue is poorly developed (Zapata et al., 1996); Fänge and Nilsson, 1985), with diffuse layers of lymphoid tissue showing a tendency to accumulate around blood vessels and macrophage aggregates, as well as scattered lymphocytes within the whole spleen parenchyma (Lamers and De Haas, 1985; Fänge and Nilsson, 1985). On the contrary elasmobranchs, because they loose their renal lymphoid tissue in adult life, show an important splenic lymphoid contribution (Zapata et al., 1996). The major teleost lymphoid organs appeared in the following sequence: kidney, spleen, and thymus, as it has been earlier observed in fish, like Senegalese sole (Solea senegalensis), turbot (Scophthalmus maximus) and Japanese flounder (Paralichthys olivaceus) (Padrós and Crespo, 1996; Cunha et al., 2003), becoming soon the spleen rich in blood capillaries, red blood cells and thrombocytes (Padrós and Crespo, 1996). In freshwater species, but not in marine teleosts, the spleen is the last organ to become lymphoid (Zapata et al., 2006).
3.1. The Spleen Fish spleen is an organ with multiplicity of functions and, depending on fish species, can present high structural complexity. Spleen is surrounded by a connective tissue capsule, which is frequently a thin structure, as it has been shown in rainbow trout (Kita and Itazawa, 1994) and carp (Lamers and De
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Haas, 1985). Blood vessels organization in the spleen showed that visceral arteries originate the arterial blood supply and the hepatic portal system comprises the splenic veins (Fänge and Nilsson, 1985). The parenchyma includes grossly: blood vessels, ellipsoids, macrophages and white pulp that correspond to lymphoid tissue, showing a reticular area without definite lymphoid centers, and red pulp, showing predominantly erythrocytes (Fänge and Nilsson, 1985; Sailendri and Muthukkaruppan, 2005). However, red and white pulp is less clearly defined in poikilothermics than in the homeothermic vertebrates (Fänge and Nilsson, 1985). The ellipsoids are the terminal arterial capillaries and in carp they are surrounded by a cuff of cells (mainly macrophages) (Lamers and De Haas, 1985). Ellipsoids have been suggested to be involved in immune response, by trapping antigens, or through formation of antigenantibody complexes (Fänge and Nilsson, 1985; Lamers and De Haas, 1985). Within the spleen, macrophage aggregates usually occur close to the blood vessels and, in certain species, they are surrounded by a lymphoid sheath (Kranz and Peters, 1984; De Vico et al., 2008). The spleen of teleost fish, compared with those of elasmobranchs, is usually smaller. In teleosts spleen weight ranges 0,05-0,86 % of the body weight comparing with elasmobranchs that could range between 0,1 to 4,0 % (Fänge and Nilsson, 1985). In fish, the spleen is involved in the development of circulating blood cells, as well as immunity. Functions of fish spleen comprise blood cell formation, their storage and release, and also destruction of aged or defective blood cells and foreign agents by cells of the nonspecific immune response (Fänge and Nilsson, 1985; Spazier et al., 1992). Rapid expulsion of stored blood cells by contraction of the fish spleen can occur after severe exercise (Franklin et al., 1993; Kita and Itazawa, 1994). The spleen also serves as a filter, retaining and eliminating effete or aged blood cells and foreign particles (Fänge and Nilsson, 1985; Kita and Itazawa, 1994). The white pulp, lymphoid tissue, is mainly related to immune response, by processes involving macrophages and lymphocytes, and although species differences may exist, it has been suggested that the spleen is also involved in anti-body production. Along with other lymphohemopoietic tissues, such as the pronephros, the spleen probably is an important source of immunoglobulins in elasmobranchs and teleosts (Fänge and Nilsson, 1985).
3.2. The Kidney Fish is the oldest, largest and most variable group of vertebrates on Hearth. So, it is not surprising that this obligate aquatic animal has a multifunctional kidney, which is reflected on its complex tissue organization. Originated from mesoderm, development of kidney is a gradual process that occurs during the embryonic period and reaches various degrees of differentiation in different groups. That differentiation happens always from the head to the caudal region in a concept of a kidney triplicate organization (i.e. pronefros, mesomefros and metanefros). Because it forms within the intermediate mesoderm located in the dorsal and posterior body wall, modern fish kidney is a retroperitoneal organ (Hildebrand and Goslow, 2001; Kardong, 2002). The kidney ontogenetic development in teleost species stops at the opistonefros phase. This organ has two distinct segments: an anterior pronefretic segment (the head kidney) and a
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posterior segment mesonefretic, with contribution of some metanefros components (the trunk kidney). Although both segments hare lymphoemopoietic, it is more intense in the anterior part because this part is not involved in excretory function. The head kidney parenchyma is dispersed between the sinusoid system that is supported by the stroma. The stroma supports the hemopoietic tissue and has an important role in nonspecific immunity traping and clearance of debris and damaged cells mainly from blood (reviewed by Press and Evensen, 1999). It appears, from studies in various teleost species, that the anterior kidney is the first lymphoid organ to possess Ig+ cells during ontogenesis (Kaattari and Irwin, 1985; Castillo et al., 1993; Koumans-van Diepen et al., 1994; Breuil et al., 1997; Romano et al., 1997; Schroder et al., 1998). Moreover, Kaattari and Irwin (1985) suggested that this organ also serves as a secondary lymphoid organ. The functions assigned to each part of the organ, throughout its development, will vary and, in some cases, after a transient development, a complete regression can happen, or other function can be assigned to the remaining structures. For example, in several bony fishes the archinefretic ducts are shared in urine and sperm release. In other cases they have testicular ducts. (Hildebrand and Goslow, 2001; Kardong, 2002). Fish kidney shows morphological and physiological variations between and within groups. For example, Chondrichthyes have particular arrangements - i.e. Leydig organ(Zapata et al., 1996) and within teleosts there are aglomerular species (McDonald and Grosell, 2006). Furthermore, in contrast to higher vertebrates, most fish species hatch these organs at embryonic stage, so becoming free-living organisms. The adult fish kidney, often situated along the dorsal wall of the body cavity, is for most species an opistonefros divided into anterior pronefric region (head or cranial) and posterior (trunk or caudal) sections (Kardong 2002). The anterior kidney is one of the primary hemopoietic organ in adult teleosts (Press and Evensen, 1999). Together with the blood, anterior kidney has the largest amount and the greatest variety of fish leucocytes. In fact, anterior kidney is the larger lymphomieloid organ in most teleosts (Zapata and Cooper, 1990; Zapata et al., 1996). So, it is usually the supplier of leukocytes for in vitro studies. The interest seen over the recent few decades by the fish kidney functions is not surprising. In fact, all vertebrates have that retroperitoneal organ (the kidney) that is responsible for several vital functions. Removal of nitrogenous waste products and other circulating harmful substances is the most commonly known, because this function is general through all vertebrate groups. Osmoregulation and water balance are also vertebrate kidney general functions (Varsamos et al., 2005; Evans, 2008). The other two functions of fish kidney are reflected in the endocrine tissues, that include medullar and cortical adrenal homologs, the chromaffin tissue, or chromaffin bodies, and the interregnal tissue, or interregnal bodies, that produce catecholamines (Reid et al., 1998) and corticosteroid hormones (McCormick, 2001; Martinez-Porchas, 2009), respectively; and the last to be addressed, but not least important, is an hemopoiesis and immunological functions (Ellis 1977; 1999; Secombes 1993). Kidney plays a key role in maintaining body homeostasis, by blood filtration and critical electrolyte and acid–base balance and maintenance of intracellular fluid volume. As part of its blood filtering function, kidney remove wastes and toxicants from blood and discharges those through urine, while conserving essential ions, amino acids, and glucose. Other kidney crucial
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function is the absorption and deposition of calcium. The kidney also produces essential hormones, including renin and erythropoietin (Bernier et al., 1999).
Kidney and Its Role in Electrolyte Balance The knowledge on osmoregulation and its implications in growth is vital to understand fish survival. The water salinity has great impact in fish physiology, namely the various salinity regimes that occur in estuaries where it is of particular importance to several fish species. Freshwater environments display a diversity of low ionic types and ratios and typically have substantially lower levels of total dissolved electric charged particles (ions) than marine or brackish waters. On the other hand, in marine environment, ions occur in stable ratios, comparatively with absolute concentrations. Even though, teleosts may live in waters which exhibit wide ranges of salinity, since they are capable of maintaining relatively stable plasma and tissue ion concentrations (Evans et al., 2004; Evans, 2008). Osmoregulation is the mechanism for maintaining constant internal ionic concentrations relative to external or environmental ionic concentrations. The osmoregulatory mechanisms maintain at almost constant or only slightly variable blood osmolality, between 280 and 360 mOsm kg -1 (Varsamos et al., 2005). From the point of view of hydromineral regulation, the main function of kidney, in freshwater fish, is the excretion of large volumes of osmotically accumulated water and the elimination of surplus ions extracted from the food, mainly K+, sulfate, and phosphate. In the limit, if renal losses of valuable ions via urine occurs, intensive reabsorption of Na+, Cl–, Mg2+ and Ca2+ takes place, by transporting enzymes and exchangers in epithelial cells lining the nephronic tubules, collective tubules, and bladder (Beyenbach, 1995), depending on the external salinity. In marine environments loss of water from fish tissues is dramatic as exposure occurs over the entire body surface and the major function of fish kidney is excretion of divalent ions taken up by drinking. Water excretion has to be reduced as much as possible in a hyperosmotic environment, and this is achieved mainly by reduction of the glomerular filtration rate (Beyenbach, 1995). Few studies are available on the physiological aspects of renal hydromineral function, such as urine flow and renal ion excretion rates. Technical drawbacks as collection of such fluids require cannulation that is complicated and extremely stressful to fish, often interfering with results. Thus, a proper evaluation of the effects of toxic chemicals on the kidney is even more complicated than in others organs.
4. THE IMPACT OF WATER CONTAMINATION ON RENAL FUNCTION Because it is the main route of elimination of hydrophilic toxicant metabolites, kidney is also an important organ in toxicology. The high volumes processed in kidney lead to high levels of exposure particularly toxicants, with concomitant deposition of these toxic substances and eventual damage.
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A number of substances have been implicated in kidney damage. As Au (2004), mentioned, histochemical techniques can be used as biomarkers, of general health condition of fish and of toxic organic contaminant exposure. However, both histopathological and morphological analysis showed moderate sensitivity to pollution when compared with other techniques (Van der Oost et al., 2003). Toxicological studies have revealed extensive histopathological alterations in kidney as a result of fish exposure to heavy metals and organic chemicals. Generally, proximal tubules appear to be the first affected, but damage progresses to the posterior segments and glomeruli, following both, chronic exposure, or high concentration of the toxicant (Au, 2004; Wendelaar Bonga and Lock, 2008). Some metals, including cadmium, lead, mercury, nickel, and chromium, particularly abundant in some contaminated aquatic environments, are severely nephrotoxic. Also, halogenated hydrocarbons, including bromobenzene, chloroform, carbon tetrachloride and tetrafluoroethylene, that are transported to the kidney as cysteine S-conjugate, have nephrotoxic action (Wendelaar Bonga and Lock, 2008). The herbicide paraquat, diquat, and 2,4,5-trichlorophenoxyacetate have also toxic effects on the kidney (Parvez and Raisuddin, 2006). Histopathological effects vary from slight disruption of the proximal tubular cells, increased numbers of phagosomes and lysosomes, and abnormal mitochondria, to rupture of cell membranes, swelling and vacuolization, increased cell death by necrosis and apoptosis, and large lesions in the tubular epithelia (Hisar et al., 2009; Kosai et al., 2009; Vinodhini and Narayanan, 2009). Although kidney has been used as nonspecific cellular biomarker, for cadmium it is well known its affinity for renal tissue, as a site of accumulation, here the highest concentrations of this metal are usually found, after exposure (Bentley, 1991; McCoy et al., 1995; Van Campenhout et al., 2009). As a consequence, cadmium is able to produce severe histopathological alterations (Gill et al., 1989; Hallare et al., 2005). Copper has no specific affinity for the kidneys, but it can also produce significant structural damage to both glomeruli and renal tubules (Vinodhini and Narayanan, 2009). A study on mercury chloride effects on head kidney macrophage function and integrity of sea bass (Dicentrarchus labrax) and their dependence on macrophage activating factor(s) (MAF) for the production of reactive oxygen species (ROS), showed a decrease in ROS production as compared to cells incubated with medium alone. MAF activation of the macrophages phagocytic activity was also impaired by HgCl2 addition. Mercury chloride induced macrophages apoptosis and MAF addition prevented this effect (Sarmento et al., 2005). Among the many organic chemicals producing similar effects are paraquat (Molck and Friis, 1997), TCDD (Henry et al., 1997) and atrazine (Fischer-Scherl et al., 1991). It is clear that the lesion severity of renal functions, including hydromineral regulation, is affected by the concentration and length of exposure. Relatively few studies deals with renal functions, however inhibitory effects of silver on K+- dependent of p-nitrophenol phosphatase (Bury, 2005), of cadmium and chromium (Venugopal and Reddy, 1993), of copper and mercury (Singh and Sivalingam, 1982; Lan et al., 1993), as well as on renal tubular Na+/K+ATPase, Ca2+-ATPase, and Na+/Ca+ exchange activity were reported (Wright and Welbourn, 1993). Most organic pollutants may be responsible for a reduced activity of renal ion transport, in a less specific way. The reduction of Na+/K+-ATPase activity induced by paraquat has been
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related to the disruption of this chemical on mitochondrial electron chain transfer (Molck and Friis, 1997). Decrease in renal Na+ efflux was found in freshwater rainbow trout following exposure to waterborne copper (Li et al., 1996). As copper has a strong inhibitory action upon Na+/K+ATPase activity, the opposite effect was expected, i.e. an increased tubular reabsorption of Na+, for which Na+/K+-ATPase is a driving force. A physiological response of the kidney to compensate the impairment of branchial Na+ uptake was the explanation for this phenomenon (Grosell et al., 1998).
Endocrine Kidney Response to Stressors Fish kidney participates also through several endocrine mechanisms, during exposure to a wide range of internal and environmental stress factors. Cortisol is the principal corticoid secreted by the interrenal tissue located in the head-kidney of teleost fish. It is released by the activation of the hypothalamus-pituitary-interrenal axis (Mommsen et al., 1999). The hypothalamus releases corticotropin-releasing factor (CRF) toward blood circulation and this polypeptide further stimulates secretion of adrenocorticotropic hormone (ACTH) from the anterior pituitary gland (Fryer and Lederis, 1986), which induces the release of cortisol by the kidney interrenal tissue (Balm and Pottinger, 1995; Mommsen et al., 1999). More important in freshwater fish is prolactin, the hormone controlling the permeability to water and ions in the gills, intestine, and renal tubules (Sakamoto and McCormick, 2006). The interference of toxic agents with neuroendocrine control processes in fish involving osmoregulation has been documented (Hontela et al., 1992). Prolactin cells, adrenocorticotropic hormone (ACTH) cells and the interrenal cortisol producing cells were those that received major attention in order to investigate the potential use as biomarkers (Ramesh et al., 2009). Activation of prolactin cells has been frequently observed in fish exposed to toxic agents and has been generally interpreted as a compensatory response to the disturbance in the permeability of these epithelia by toxicants (reviewed by Wendelaar Bonga and Pang, 1989). Cortisol is one of the primary stress hormones in fish and also an important stimulator of Na+/K+- ATPase activity in gills, intestine, and kidney. The multiple functions of this hormone clearly demonstrate the intimate relationship between the stress response and osmoregulation in fish (Wendelaar Bonga, 1997; Reid et al., 1998; Barton, 2002). Endocrine dysfunction was also found in fish from water naturally contaminated with a mixture of pollutants, including heavy metals and PCBs, when compared with fish from an unpolluted reference site (Hontela et al., 1992; Hontela et al., 1997; Wendelaar Bonga and Lock, 2008). Hypothalamo–pituitary–interrenal (HPI) axis of wild brown trout is activated in fish from sites contaminated with cadmium and zinc. Histological analyses revealed that interrenal cells are more stimulated, exhibiting both hypertrophy and hyperplasia (Norris et al., 1997). These results suggest that the hypothalamo-pituitary-interrenal (HPI) axis of fish living in metal-contaminated water may be susceptible to chronic stimulation. A study of effects of endosulfan, an organochlorine pesticide, on cortisol secretion in vitro revealed that the head kidney cells of rainbow trout, (Oncorhynchus mykiss) exposed to endosulfan, decreased ACTH- or dbcAMP-stimulated cortisol secretion and cell viability in a
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concentration-dependent pattern and the doses required to disrupt cortisol secretion were significantly lower than lethal doses to the head kidney cells (Leblond et al., 2001). The interrenal tissue of yellow perch, from a site contaminated by a mixture of heavy metals and organic contaminants, secreted significantly less cortisol in response to a standardized pulse of ACTH than those from an unpolluted site (Brodeur et al., 1998) . Given the cortisol importance for osmoregulation in fish, any interference with the secretion of cortisol and its stimulant hormone (ACTH) may be expected to have an effect on osmoregulation (McDonald and Milligan, 1997); however, the actual impact of the disruptive effects of some toxic chemicals on this process remains to be established. Currently, the use of cortisol as a biomarker has to be done carefully. For proper use of cortisol as biomarker, an evaluation has to be done in each case (species, contaminant compounds and environmental conditions).
5. IMMUNE SYSTEM IN FISH The main source of pollution in aquatic environment is the growing human population and their demanding needs that may affect both, fish and human health. Degradation of environmental conditions, due to pollution, can disturb fish immune process and consequently fish health. Consequences of exposure to pollutants on fish immune system can range from suppression/inhibition or even enhancement of a specific immune response. According to Agius and Roberts (2003), fish inhabiting polluted environments can respond to environmental conditions altering the nonspecific defence activities. In fact, toxic effects on the immune system may serve as an excellent biomarker to monitor pollution and water quality, since most environmental pollutants are known to alter immune system function, even at doses that do not cause histopathological toxicity (Agbede et al., 2005).
5.1. Non-Specific Defence Mechanisms As in all jawed vertebrates, fish species possess a complex mechanisms system that provide homeostasis and fight against infection. The complexity and the type of these mechanisms led to a division in innate (non-specific) and an acquired (adaptive or specific) immunity. Indeed, the system is unique and their parts are interdependent, with several molecules and cells working together in both, innate and acquired system. Both types have the participation of both, cellular and humoral factors. However, as the term humoral was first applied to activities involving antibodies, humoral innate components are just referred as soluble components. As previously stated, the innate immunity is generally subdivided into two parts, the cellular and humoral defense responses (Köllner et al, 2002; Aoki et al., 2008). Cellular responses include physical barriers, such as mucus and epithelial tissues in skin, gills and stomach (Aoki et al., 2008), and cells, like monocytes/macrophages, and granulocytes, mainly involved in phagocytosis (Agbede et al., 2005; Aoki et al., 2008). Humoral responses involve
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a variety of proteins and glycoproteins capable of destroying or inhibiting growth of infectious microorganisms (Aoki et al., 2008). The non-specific immunity, in fish, is the primary line of defence and represents a considerable part of the immune response, since activation of leucocytes is one of the first reactions in every immune response (Agbede et al., 2005; Aoki et al., 2008). This mechanism is characterised by being non-specific and therefore not depending upon previous recognition of the invader (Tort et al., 2003). Depending on the antigen leukocyte, certain subpopulations are activated and proliferate. However, it has been shown in different fish species that some circulating sub-populations are able to act in immune defence without prior activation (Köllner et al, 2002). The nonspecific immunity in fish primarily depends on the phagocytic activity of sub-populations of monocytes/macrophages and neutrophilic granulocytes (Köllner et al, 2002; Agbede et al., 2005). Phagocytosis, killing and degradation of invading microorganisms by professional phagocytes, is a crucial process in the mechanisms of defense of vertebrates against some infections (Mackaness, 1969; Ellis, 1977; Adams and Hamilton, 1984; Edwards and Kilkpatrick, 1986; Lehrer et al., 1988; Hine, 1992; Brown, 1995). It is interesting that mammals, teleosts and other higher eukaryotes utilize two types of professional phagocytic cells -neutrophils and macrophages- in the defense against infection (Rowley and Ratcliffe, 1988; Secombes and Fletcher, 1992; Brown, 1995). Data from studies conducted on the behavior of each of the two professional mammals phagocytes in inflammation, including that due to infectious situations, can be summarized as follows (Lehrer et al., 1988; Haslett et al., 1989; Silva et al., 1989; Densen et al., 1995; Kubicka et al., 1996; van Furth 1992). Macrophages are present in all body compartments being in a quiescent state. Therefore, when superficial barriers are breached by an invading microorganism, it encounters this phagocyte. Neutrophils are present in large numbers in blood and hemopoietic organ pools as a reserve, and, under normal conditions, are rare in the tissues and body cavities. These granulocytes migrate to the infection focus just when mobilized by chemotactic molecules, including those released by macrophages (Afonso et al., 1998a; Afonso et al., 1998b). Although phagocytic system in fish involves resident macrophages present in all organs and tissues of the body (Agbede et al., 2005), spleen has an important role in this mechanism, developed by macrophages and granular leucocytes inside parenchyma. This is not surprising since it is known that phagocytosis is the principal function of macrophages in teleosts fish (Agius and Roberts, 2003; Agbede et al., 2005), and the response of splenic macrophages to foreign substances is the subsequent elimination by phagolysosomes. Therefore macrophages aggregates have been considered as metabolic dumps (Kranz and Peters, 1984).
Macrophage Aggregates Macrophages are mononuclear cells derived from circulating blood monocytes, terminally differentiated, that have been studied in a variety of fish species (Secombes and Fletcher, 1992; Enane et al., 1993; Secombes, 1993). Several distinct macrophages subpopulations seem to exist in fish (Afonso et al., 1998a; Neumann et al., 2000). Described long ago by Metchnikoff (1887), phagocytosis is one of the most ancient cellular immune mechanisms and the term ―macrophage‖ came first of these observations. Several
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immunoregulatory molecules such as macrophage-activating factor (MAF), TNF-, TGF-, -glucans, growth hormone, and neurotransmitters have been implicated in the modulation of fish macrophage phagocytosis (Secombes, 1994; Secombes et al., 1996). Temperature can affect nonspecific immune responses in fish. Studies on the effect of environmental temperature, on fish nonspecific defences, revealed greater effectiveness of phagocytosis at low environmental temperature in several species (Morvan et al., 1998). Dispersed or aggregated, macrophages are pigmented populations with particular interest. Macrophage aggregates (MAs), or melanomacrophage centers, are structures normally located in the stroma of the hemopoietic tissue of spleen and kidney, although in some fish, they are also found in liver (Fringe and Nilsson, 1985; Kranz, 1989; Montero et al., 1999; Agius and Roberts, 2003). MAs vary between the different hemopoietic organs. Splenic MAs exist in all teleosts fish (Lamers and De Haas, 1985) and for most fish species they are more abundant and larger than those in the liver (Kranz and Peters, 1984), and compared to kidney, they are more variable in pigmentation and show a closer degree of aggregation (Kranz, 1989). As stated before, polluted environments may induce changes in fish nonspecific defence activity. Macrophage aggregates have been used as nonspecific cellular biomarkers of physiological stress following exposure to chemical pollutants. Changes in MAs number and structure could be a sensitive biomarker, which could be of great value as an early sign of environmental contamination (Montero et al., 1999; Fournie et al., 2001; Agius and Roberts, 2003; Facey et al., 2005; Jordanova et al., 2006). General functions of these centres have been described as storage, destruction or detoxification of exogenous and endogenous substances, and iron metabolism and recycling (Montero et al., 1999; Agius and Roberts, 2003; Jordanova et al., 2006). They have also been implicated in the immune response, including inflammatory and humoral responses (Montero et al., 1999). MAs often exist as complex discrete centres, containing lymphocytes and macrophages, and may be primitive analogues of the germinal centres of lymph nodes of higher vertebrates (Kranz and Peters, 1984; Kranz, 1989; Agius and Roberts, 2003). It is thought that the MAs might be involved in the response of fish to infectious agents, by acting as focal depositories of resistant pathogens and also as antigen processors in immune responses (Lamers and De Haas, 1985; Agius and Roberts, 2003). Different types of pigments have been identified, frequently even within the same cell (Agius and Roberts, 2003), which seems to be species-specific (Jordanova et al., 2006). Melanin is not observed in MAs of carp, being the, hemosiderin and lipofuscin the main pigments (Lamers and De Haas, 1985). At least 3 types of pigments have been identified in the macrophages aggregates e.g. melanin, lipofuscin/ceroid and the hematogenous pigment hemosiderin (Fringe and Nilsson, 1985; Agius and Roberts, 2003; Jordanova et al., 2006). These pigments are associated to different biochemical roles, and their levels could be indicative of fish unbalance physiology.
Splenic MAs Macrophage aggregates increase in size, frequency or in pigment patterns in conditions of environmental stress and have been suggested as reliable biomarkers of water quality (Agius
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and Roberts, 2003). Furthermore, Hinton et al. (1992) have suggested MAs as histologic biomakers of contaminant exposure or environmental stress. Histochemical properties of splenic MAs vary considerably between healthy and diseased fish and increases in pigment content are suggestive of catabolic, infectious or toxic exposure (Agius and Roberts, 2003; De Vico et al., 2008). The accumulation of iron appears to be a characteristic feature of splenic MAs, but not of those in the liver, leading to conclude that one of their main functions is the digestion of degraded red blood cells (Kranz and Peters, 1984). Hemosiderin, related with iron storage and recycling (Fringe and Nilsson, 1985; Montero et al., 1999), is usually detectable in little amounts in the MAs of spleen and increased storage should be considered as a pathological event (De Vico et al., 2008). The increase hemosiderin in splenic MAs, in some infectious diseases, occurs manly due to high rates of erythrocyte destruction or/and high iron sequestering in centers to prevent them from bacterial growth (Kranz, 1989). Also Khan and Nag (1993), reported an increase in splenic hemosiderin in fish exposed to crude oil. According Agius and Roberts (2003) lipofuscin is the pigment that accumulates with age and tissue destruction and is the most widespread pigment in the MAs of many fish species. Increase of lipofuscin is derived from cell peroxidation (Kranz, 1989; Agius and Roberts, 2003). Lipofuscin in splenic MAs, has been predominantly related to high levels of tissue catabolism and degenerative chronic disorders (De Vico et al., 2008). Although changes in splenic MAs can be considered in toxicological studies as a sensitive biomarker, since they are nonspecific, their abundance and structure can be affected by many factors and so these etiologies must be considered in toxicological studies. Increase of splenic MAs has been associated with starvation (Agius and Roberts, 1981; Fänge and Nilsson, 1985), with ulcerous infection (Kranz, 1989), with parasitic infection (De Vico et al., 2008), with nutritional imbalances and high fish stocking density (Montero et al., 1999). It has also been observed that these centres increase in size and number, at least in a number of fish species, as fish grow older and tissues degenerate (Agius and Roberts, 2003). In addition, normal fluctuations occur, since MAs could undergo seasonal and breeding dependent variations. It is established that the amount of pigmented MAs in spleen was significantly increased in wild Ohrid trout females, during and/or after spawning (Jordanova et al., 2006). Thus, for biomonitoring purposes, normal fluctuations of a pollution biomarker must be excluded to achieve reliable responses. Data control could be made by comparisons between contaminated and reference sites, with fish of similar age and captured at the same season. Besides, a quantitative study, an assessment of spleen and liver MAs in broun trout (Salmo truta) during an entire gonadal cycle performed by Jordanova et al. (2006), was required since it provides a basis for future evaluation of normal versus altered levels of MAs induced by pollution, to be applied at least in the same group of fish. Although non-specific, MAs in fish has been proven to be a sensitive indicator of exposure to environmental contaminants (Au, 2004). Splenic MAs are effective biotic indicators for discrimination between fish exposed to degraded and non-degraded environments. However comparative studies, on the incidence of MAs in the spleen, kidneys and liver of fish exposed to toxic chemicals, have shown an opposite trend. A reduction in number and size of these structures in fish living in polluted water is probably due to a pollutant-induced immunosuppression (De Vico et al., 2008). The spleen of the eel (Anguilla anguilla), exposed to a chemical spill, showed alterations such as necrosis, lacking of MAs and a reduced number of macrophages dispersed throughout the reticulum, compared to
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controls (Spazier et al., 1992). Normally, the phagocytic capacity of the spleen in eel and other species is mainly associated with number and extent of MAs (Spazier et al., 1992), and according to these authors a decreased ability of macrophages phagocytic function, is possibly due to a toxicant-induced reduction of chemotactic activity. Metals may disturb ionic metabolic, balance and cell division of immunocompetent cells. It was found in vivo that copper causes, in a dose-dependent manner, a depressed phagocytic activity of catfish spleen macrophages (Saxena and Saxena, 2008). The utility of splenic MAs has been assumed as a general indicator of fish exposure to contaminated environments and has been used in monitoring programs, such as the Environmental Monitoring and Assessment Program–Estuaries (EMAP-E). This study, using image analysis, has proved that MAs densities greater than 40/mm2 can be correlated with exposure, to hypoxic conditions or chemical contamination in sediments (Fournie et al., 2001). Also, utilizing image analysis, an increase in splenic hemosiderin was observed in longhorn sculpin (Myoxocephalus octodecemspinosus), yellowfin sole (Limanda aspersa), quillback rockfish (Sebastes maliger) and kelp greenling (Hexagrammos decagrammus) exposed to crude oil (Khan and Nag, 1993). An environmental study in Calcasieu Estuary, Louisiana, showed that the frequency of MAs in spotted trout (Cynoscion nebulosus) spleen was significantly higher in contaminated sites, than reference sites (Jenkins, 2004). According to Kranz and Peters (1984), the MAs in spleen and liver of ruffe (Gymnocephalus cernua) from the polluted Elbe River, augmented during the development of several histopathological abnormalities of these organs. It also is well established an association between erythrocyte damage and spleen toxicity, after exposure to aniline and other aromatic amines. According to Monteiro et al. (2006) after 96 h of exposure to aromatic amine 3,4-dichloroaniline spleen histological alterations and deposition of hemosiderin granules, in a dose-dependent manner, were observed in juveniles of common goby (Pomatoschistus microps), compared to control groups. Besides, splenic MAs hyperplasia was generally reported in a variety of fish species inhabiting degraded environments, such as exposed to pulp mill effluent and areas with elevated levels of xenobiotic chemicals (Au, 2004). It has been shown that heavy metals exposure cause significant pathological changes in fish lymphoid organs and fish mortality. Histopathology of spleen tissues of common carp (Cyprinus carpio carpio) after metals exposure revealed congestion, haemorrhage, lymphocytic infiltration and degenerative changes with loss of cellular architecture (Saxena and Saxena, 2008). In laboratory conditions, frequency and size of splenic MAs were significantly increased in Tilapia mossambica after median lethal exposure to heavy metal cadmium chloride (Suresh, 2009). Osman et al. (2009), found splenic histopathological changes in Oreochromis nilotica under copper sulfate and lead acetate laboratory exposure. Fish spleen showed congestion of vessels, depletion of lymphoid follicles, excessive hemosiderosis and hyper activation of MAs, associated with increase of pollutants concentration and time of exposure. Also MAs sizes, in male pike (Esox lucius) and longnose sucker (Catostomus catostomus), have increased with mercury contamination (Hinck et al., 2004). A long-term effect of small concentrations of the dioxin TCDD introduced in the diet of rainbow trout (Oncorhynchus mykiss), was evaluated by Walter et al. (2000). The increased numbers of macrophages and pigmented macrophages with intracytoplasmic hemosiderin
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observed suggested a link with increased degeneration of lymphocytes and, possibly also, erythrocytes. Chronic (32 weeks) exposure of rainbow trout (O. mykiss) to sewage treatment plant (STP) effluent showed effects on spleen leucocytes and on the integrity of spleen tissue. Spleen tissue of exposed fish appeared to have less structural integrity and infiltration of stimulated monocytes/macrophages, as compared to control (Hoeger et al., 2004). These results are in agreement with the general idea that the increase in size, frequency and pigments variation on MAs of fish spleen, in conditions of environmental stress, is a reliable biomarker for water chemical pollution. In addition, utility of splenic MAs as biomarkers could be extended to evaluation of ecosystems recovery. Significant decreases in splenic MAs area were also used to suggest decreased exposure to contaminants on a fish population (Facey et al., 2005). Results of rainbow trout (O. mykiss) exposure to sublethal concentrations of the pesticide endosulfan showed splenic abnormalities, after 21 days of exposure, including exudate, necrosis and scattered MAs throughout the spleen, compared to control; whereas after 30 days of recovery, lesions were no longer seen (Altinok and Capkin, 2007). According to Jordanova et al. (2006), changes in MAs relative volume can be a nonexpensive and sensitive biomarker, which should be of great value as a first-line evaluator of early signs of aquatic environmental degradation. The histologic analyses of spleen could include the assessment of morphometric parameters, such as mean MAs profile area and number per square millimetre of spleen tissue (De Vico et al., 2008). Also, image analyses that select and quantify pigmented area are proved to be an objective way of MAs evaluation in salmonid spleen (Schwindt et al., 2006). This method is less time-consuming and was shown to be very accurate. Other studies that have used area occupied by MAs, noted increased splenic hemosiderin in several fish exposed to crude oil (Khan and Nag, 1993) and in dab with ulcers (Kranz, 1989). Using image analysis of splenic MA Fournie et al. (2001) also proved the utility of this technique as effective discriminator between fish exposed to degraded and nondegraded environments. These approaches can provide data that is easily analysed statistically, resulting in less controversial conclusions and reinforces the importance of using splenic MAs as histologic biomarker of contaminant exposure.
6. ORGANO-SOMATIC INDICES Organo-somatic indices reflect the status of organs within the whole body, which may change in size due to environmental factors more rapidly than organism weights and lengths increase or decrease. Although several factors could increase or decrease the sizes of a few organs, the organo-somatic indices have been used widely in fish health and population assessments.
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The Splenosomatic Index (SSI) Spleen size is considered a useful diagnostic factor because, as previously seen, this organ plays a highly important role in hemopoiesis and immune reactivity of fish and the use of relative spleen weight could provide information about fish health. The splenosomatic index (SSI) is the weight of the spleen expressed as a percentage of total body weight, and alterations in this index could indicate an abnormal condition in the spleen (Dethloff and Schmitt, 2000). Commitment in immune defence could be measured by spleen size, moreover the use of spleen size is also recommended in ecotoxicological studies as a standard measure of immunocompetence on fish (Šimková et al., 2008; Van der Ost et al., 2003). There is evidence that immune system of fish reacts to various environmental factors, including anthropogenic ones, and, therefore, the immune responses (either stimulation or suppression) have to be considered as an unspecific indicator of environmental stress. Phagocytic activity is an important immunological function in the study of bacterial infections in fish and contaminants can affect spleen directly and change their normal function within the immune system. These facts, together with contaminant exposure, could facilitate development of infectious and/or non-infectious diseases and in this way resulting in different disease prevalence and incidence. Pollution of the natural aquatic environment, with industrial or agricultural sewage, is an important immuno-suppressing factor, resulting in higher susceptibility of fish to infectious diseases (Köllner et al, 2002). For that reason, this issue is also of relevance for environmental monitoring programmes and useful, from both points of view, economic and public health. Enlargement of the spleen is considered to be indicative of disease or immune system problems (Dethloff and Schmitt, 2000). Parasitic infections, can lead to an increase in spleen volume (Durborow, 2003; Khan, 2009), usually by development of leucocyte reactions (Lizama et al., 2006). However, when relative spleen size is used as reflecting an immune investment against parasites or pathogens, large spleen can be interpreted either as an improving ability to respond to parasite exposure or an indication of high immunological activity from already established infection. (Šimková et al., 2008). Often the occurrence of MAs mainly around parasite larvae has been noticed in infected liver and spleen (Dezfuli et al., 2007). In rainbow trout (O. mykiss) a positive association between spleen size and resistance to bacterial disease was also found (Hadidi et al., 2008). Histological, and morphometric modifications of splenic macrophage aggregates in sea breams (Sparus aurata), infected by an ectoparasite in the gills, revealed a dramatic increase in the size and number of MAs in fish (De Vico et al., 2008). Increase splenosomatic index could be dependent on parasitic load. According to Lizama et al. (2006), the infestations in fish Prochilodus lineatus, by acantocephalan, increase SSI, while the infestation with metacercariae, due to the lower intensity of this infection, resulted in SSI decrease. Environmental alterations, due to contamination can also alter the SSI. Fish chronically exposed to a bleached Kraft mill effluent (BKME) showed a tendency for high SSI (Adams et al., 1992). Jenkins (2004) also found in black drum (Pogonias cromis), a splenosomatic index significantly higher in fish from contaminated sites than in fish from reference sites. Decrease in SSI is commonly found following contaminants exposure. Fish exposed to organic contaminants, alone or in combination with metal, have shown decrease SSI (Hinck
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et al., 2004). Exposure of fish to lead for up to 183 days was reported to produce a reduction in spleen size, with an increase in leukocyte number (Saxena and Saxena , 2008). Decreased SSI was also recorded in fish exposed to petroleum and polluted waters, with PCBs, PAHs, metals (Dethloff and Schmitt, 2000). These findings are consistent with the use of SSI as a sensitive end point biomarker. A complex pattern of effects of paper mill effluents in fish physiology was observed. Some results indicate that in-stream exposure to elemental-chlorine-free pulp and paper mill effluents the SSI decreases. An experiment of 35 days exposure to surface water of up- and downstream, from a pulp and paper mill treatment-effluent discharge, showed that SSI was significantly decreased in fish downstream, compared to fish upstream, along with a transfer from lymphocytes to neutrophils in peripheral blood (Baer et al., 2009). The effects of paper mill effluents on free-ranging and captive largemouth bass (Micropterus salmoides) were assessed by Sepúlveda et al., (2004). Fish in outdoor tank, exposed to increasing full strength effluent for 28 or 56 days, showed that SSI was not affected; whereas free-ranging bass sampled from effluent-dominated sites showed a decreased in both SSI and number of splenic macrophage aggregates, in relation to reference streams. Besides a decline on the weight of the spleen, results also showed hematological changes, such as reductions in the number of red blood cells, probably caused by alterations in the hemopoietic capacity of the spleen and/or head kidney. These authors also suggested that the decrease number of splenic MAs is due to the decreased spleen weights since bass with larger spleens and livers tend to have more MAs. Also an important issue addressed in this study is that, although many of the physiological parameters measured were statistically different from control or reference fish, they fell within normal physiological ranges when compared to reports on largemouth bass and other freshwater species. Based on that, it is evident that different responses could arise between laboratory and field biomarker assessments, and also conclusions about significant trends observed must be distinguished from normal physiological ranges. As an unspecific indicator, also certain endogenous factors are known to affect the SSI. The range of spleen sizes varies among fishes and populations of the same species. Relative spleen weight may also differ with age, gender and gonad development (Dethloff and Schmitt, 2000). Seasonal changes of the spleen size have long been known to occur in the salmon (Salmo salar) and other salmonids. Before and after spawning the spleen is large and hyperemic, but at spawning it shrinks and becomes anemic, maybe related to blood storage rather than lymphoid or hemopoietic activities (Fänge and Nilsson, 1985). However, in BEST fish monitoring program, in the Yukon River Basin, the SSI of longnose sucker (C. catostomus), was not influenced by gender (Hinck et al., 2004). Nonspecific stressors can also ending into altered spleen morphology. Several studies have shown that fish under hypoxic conditions or severe exercise, reveals spleen contraction and then decrease in size (Fänge and Nilsson, 1985; Dethloff and Schmitt, 2000). Rainbow trout, generally considered to be a hypoxia-sensitive species, showed, during hypoxia exposure, a decrease in SSI and an increase in blood hemoglobin. Splenic contraction and the subsequent red blood cell release, accounts for decrease in SSI (Lai et al., 2006). Exercise at a speed great enough to cause exhaustion also contributed to the increase in hematocrit of Pagothenia borchgrevinki (Franklin et al., 1993). Based on these considerations and according to Dethloff and Schmitt (2000), in addition to histological data, that show a relation between cellular changes in the spleen and exposure
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to contaminants, the SSI is a relevant indicator of spleen dysfunction and a useful biomarker of fish health.
The Hepato-Somatic Index (HSI) Alterations in liver size due to environmental stressors are of interest since liver plays vital functions such as energy storage and metabolism. Evaluation of the hepato-somatic index (HIS) must consider the endogenous, sometimes cyclic variations as well as the exogenous factors associated with toxicant exposure. The HSI varies with seasonal cycles (Delahunty and de Vlaming, 1980; Slooff et al., 1983; Beamish et al., 1996; Saborowski and Buchholz, 1996). Nutritional quality and regimes are main factors that affect relative liver size (Daniels and Robinson, 1986; Heidinger and Crawford, 1977; Foster et al., 1993). Gonadal development and sex of fish make the HSI to vary along the reproductive cycle (Fabacher and Baumann, 1985; Förlin and Haux, 1990; Grady et al., 1992). In females, the HSI may change due to the synthesis of vitellogenin in liver (Scott and Pankhurst, 1992). Nevertheless, the HSI is the organo-somatic index most measured to assess pollution exposure (Adams and McLean, 1985; Goede and Barton, 1990). Several investigators have suggested that relative liver enlargement in fish indicates exposure to environmental carcinogens or other toxic chemicals. Studies evaluating the relative liver size of fish from contaminated and reference sites often utilize the HSI, which expresses liver size as a percentage of total body weight (Facey et al., 1999). The rock bass Ambloplites rupestris collected from a sediment contaminated harbor showed a significant increase of splenic tissue occupied by macrophage aggregates and greater HSI than fish from reference sites (Facey, 2005). In this study macrophage aggregates and HIS were also used to evaluate the recovery of the fish population in a 7-year period after remediation has been implemented. An increase of HSI in brown bullheads (Ameiurus nebulosus) has been reported associated with polycyclic aromatic hydrocarbons (PAHs) contamination (Fabacher and Baumann, 1985; Gallagher and Di Giulio, 1989). Several other species (Atlantic cod, winter flounder, redbreast sunfish, striped bass, hard-head catfish and European plaice) exposed to different chemicals or mixtures of chemicals PAHs, PCBs, in natural or industrial waters, all had enlarged livers (Poels et al., 1980; Fletcher et al., 1982; Buckley et al., 1985; Kiceniuk and Khan, 1987; Adams et al., 1989; Everaarts et al., 1993; Secombes et al., 1995). This enlargement of fish liver seems to be due to the increase of xenobiotic metabolism rather than the increase of detoxification enzyme activities (Fabacher and Baumann, 1985; Gallagher and Di Guilio, 1989). In a coastal lagoon, contaminated with metals, condition indices (K and HSI) of mullets (Liza saliens) that bioaccumulated high concentrations of Cu and Zn in their liver were higher compared to mullets from the sea, suggesting abnormal condition in the lagoon population (Fernandes, 2008a). In contrast with these results several other studies described a decrease of liver size following exposure to contaminants (Chambers, 1979; Larsson et al., 1984; Hickie and Dixon 1987; Ruby et al., 1987; Hoque et al., 1998). The decrease of HSI may reflect glycogen loss to produce energy (Barton et al., 1987) but histopathological alterations including hepatocyte
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damage and degeneration may also result in decrease of liver size (Ram and Singh, 1988). Other explanations attribute lower HSI to altered carbohydrate metabolism (Adams et al., 1992a). The use of SSI and HSI is very challenging since they respond to several affecting factors that need to be recognized and avoided or accounted for, when possible. Organo-somatic indices should only be compared within species, or at least between similar species, of the same classes of age. In addition it is preferable a separation by gender, to avoid gender effect. The sampling procedure must be quick and effective to avoid fish handling stress that can provoke recruitment of erythrocytes from the spleen, and tissue alterations. Comparisons between polluted and natural environments must be performed with fish caught at same season. And finally, according to Dethloff and Schmitt (2000), organ size is better expressed relative to fish size excluding the gonads weight.
CONCLUSION Aquatic toxicology is part of a general trend in a world of increasing contaminant risks and it is clear that confined waters are among great concern. Coastal and shallow lagoon waters are still ecological and economical relevant resources that justify the study and development of early warning systems for evaluation of aquatic environment and fish population health. They are vital for implementation of effective recovery measures. This chapter contributes to the knowledge of liver, kidney and spleen metabolic processes and their alterations induced by pollutants exposure. The fact that contaminants usually appear in the environment as complex mixtures that can cause interactive effects, underlines the necessity of using a range of different biomarkers when attempting to evaluate environmental impact. The use of liver, kidney and spleen as an early warning system in population assessment, has the advantage of looking at different metabolic and anatomic biomarkers levels and thus offering an integrated approach of toxic effects. Biochemical responses to contaminant exposure can include changes in neuroendocrine control of osmoregulation, plasma electrolytes concentrations, EROD and plasmatic transaminases activities, metallothioneins synthesis in liver and hematologic parameters in spleen. Ultrastructural changes induced by toxicant exposure also occur in liver, kidney and spleen depending on the concentration and length of exposure. Changes in histochemical properties of splenic MAs are linked to fish exposure to contaminated environments. Besides, organo-somatic indices variations, as a measure of immune defence and as well as energy storage and metabolism, they reflect well fish toxic exposure.
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Figure 1. Diagram of the major fish organs involved in the regulation, hemopoietic, immune and detoxification processes, and the evaluation of their responses to be used as fish biomarkers of stress/injury.
The suite of methods that should be applied to each organ depends on sensitivity, costeffectiveness, the ability of the methods to detect the contaminants and requires expertise. In addition, the experimental design should take into account the potential confounding factors that may occur for each of the described biomarkers. Regarding structural aspects, the knowledge of the normal organ microanatomy is fundamental to properly evaluate abnormal physiologic and histological changes. The fact that toxic agents can act as stressors also implies that their effects are partially additive with those of other stressors. As outlined in this manuscript, the structure of the organs normally varies in direct connection with gender, age, nutritional status, or temperature. Moreover, a solid baseline data on the normal morphology and physiologic range is essential to establish associations with toxic induced changes. Concerning fish, long-term toxic exposure can instigate several adaptive responses therefore is essential to know such variations for correct discrimination between structural adaptations and lesions caused by pollutants. The weight-of-evidence for the utility of analysing these organs, as an early warning system, is that it can be useful for detecting toxic diffuse effects, such as those arising from poor accumulation in fish. Similarly, more than one autochthon fish species is useful for accurately assess the presence of environmental contaminants, given that metabolic pathways in different species can show diverse sensitivity and behavior to respond against toxic exposure. This approach contributes to a realistic understanding of the implications and extent of aquatic pollution and thus to choose wisely remediation strategies to achieve a sustainable management.
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Balint, T., Ferenczy, J., Katai, F., Kiss, I., Kraczer, L., Kufcsak, O., Lang, G., Polyhos, C., Szabó, I., Szegletes, T. & Nemcsok, J. (1997). Similarities and differences between the massive eel (Anguilla anguilla L.) devastations that occurred in lake Ablation in 1991 and 1995. Ecotoxicol Environ Saf., 37, 17-23. Balm, P. H. M. & Pottinger, T. G. (1995). Corticotrope and melanotrope pomc-derived peptides in relation to interrenal function during stress in rainbow-trout (Oncorhynchusmykiss). Gen Comp Endocrinol, 98, 279-288. Barni, S., Bernocchi, G. & Gerzelli, G. (1985). Morphohistochemical changes in hepatocytes during the life cycle of the European eel. Tissue Cell, 17, 97-109. Barton, B. A. (2002). Stress in fishes: A diversity of responses with particular reference to changes in circulating corticosteroids. Integrative and Comparative Biology, 42, 517-525. Bello, S. M., Franks, D. G., Stegeman, J. J. & Hahn, M. E. (2001). Acquired resistance to Ah receptor agonists in a population of Atlantic killifish (Fundulus heteroclitus) inhabiting a marine Superfund site: in vivo and in vitro studies on the inducibility of xenobiotic metabolizing enzymes. Toxicol Sci., 60(1), 77-91. Bentley, P. J. (1991). Accumulation of cadmium by channel catfish (Ictalurus punctatus) influx from environmental solutions. Comp Biochem Physiol C Pharmcol Toxicol Endocrinol, 99, 527-529. Bernier, N. J., McKendry, J. E. & Perry, S. F. (1999). Blood pressure regulation during hypotension in two teleost species: Differential involvement of the renin-angiotensin and adrenergic systems. J Exp Biol., 202, 1677-1690 Beyenbach, K. W. (1995). Secretory electrolyte transport in renal proximal tubules of fish. In: Cellular and molecular aproaches to fish ionic regulation. C. M. Wood, & T. J. Shuttleworth, (eds.). Academic Press, New York, 85-103. Biagianti-Risbourg, S. & Bastide, J. (1995). Hepatic perturbations induced by a herbicide (atrazine) in juvenile grey mullet Liza ramada (Mugilidae, Teleostei): an ultrastructural study. Aquat Toxicol, 31, 217-29. Boorman, G. A., Botts, S., Bunton, T. E., Fournie, J. W., Harshbarger, J. C., Hawkins, W. E., Hinton, D. E., Jokinen, M. P., Okihiro, M. S. & Wolfe, M. J. (1997). Diagnostic criteria for degenerative, inflammatory, proliferative nonneoplastic and neoplastic liver lesions in medaka (Oryzias latipes): consensus of a National Toxicology Program Pathology Working Group. Toxicol Pathol, 25, 202-10. Breuil, G., Vassiloglou, B., Pepin, J. F. & Romestand, B. (1997). Ontogeny of IgM-bearing cells and changes in the immunoglobulin M-like protein level (IgM) during larval stages in sea bass (Dicentrarchus labrax). Fish Shellfish Immunol, 7, 29-43. Brodeur, J. C., Daniel, C., Ricard, A. C. & Hontela, A. (1998). In vitro response to ACTH of the interrenal tissue of rainbow trout (Oncorhynchus mykiss) exposed to cadmium. Aquat Toxicol, 42, 103-113. Brown, E. J. (1995). Phagocytosis. BioEssays, 17, 109-117. Bruslé, J. & Anadon, G. G. (1996). The structure and function of fish liver. In Fish Morphology - Horizon of New Research. J. S. D. Munshi, & H. M. Dutta, (eds). New Delhi and Calcutta, India: Oxford & IBH Publishing, 77-93. Bury, N. R. (2005). The changes to apical silver membrane uptake, and basolateral membrane silver export in the gills of rainbow trout (Oncorhynchus mykiss) on exposure to sublethal silver concentrations. Aquat Toxicol, 72, 135-145.
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Press, C. M. & Evensen, O. (1999). The morphology of the immune system in teleost fishes. Fish Shellfish Immunol, 9, 309-318. Rao, J. V. (2006). Sublethal effects of an organophosphorus insecticide (RPR-II) on biochemical parameters of tilapia, Oreochromis mossambicus. Comp Biochem Physiol, Part C, 143, 492-498. Ramesh, M., Saravanan, M. & Kavitha, C. (2009). Hormonal responses of the fish, Cyprinus carpio, to environmental lead exposure. Afr J Biotechnol, 8, 4154-4158. Reid, S. G., Bernier, N. J. & Perry, S. F. (1998). The adrenergic stress response in fish: control of catecholamine storage and release. Comp Biochem Physiol Part C Toxicol Pharmcol, 120, 1-27. Robertson, J. C. & Bradley, T. M. (1992). Liver ultrastructure of juvenile Atlantic salmon (Salmo salar). J Morph, 21, 41-54. Rocha, E. & Monteiro, R. A. F. (1999). Histology and Cytology of Fish Liver: A Review. Ichthyology: Recent Research Advances. D. N. Saksena, (eds), New Delhi, India: Oxford & IBH Publishing Co. Pvt. Ltd. and Enfield, New Hampshire, USA: Science Publishers, Inc. 321-344. Rocha, E., Rocha, M. J. & Monteiro, R. A. F. (2003). Seasonal changes in fish hepatocytes and correlations with the endocrine system. In Fish Adaptations. B. G. Kapoor, & A. L. Val, (eds). Enfield, New Hampshire, USA, Science Publishers, Inc., Plymouth, UK, Plymbridge Distributors Ltd., 383-403. Romano, N., Abelli, L., Mastrolia, L. & Scapigliati, G. (1997). Immunocytochemical detection and cytomorphology of lymphocyte subpopulations in a teleost fish Dicentrarchus labrax. Cell Tissue Res., 289, 163-171. Rotchell, J. M., Clarke, K. R., Newton, L. C. & Bird, D. J. (2001). Hepatic metallothionein as a biomarker for metal contamination: age effects and seasonal variation in European flounders Pleuronectes flesus from the Severn estuary and Bristol Channel. Mar Environ Res., 52, 151-171. Rowley, A. F. & Ratcliffe, N.A. (1988). Vertebrate blood cells. Cambridge University Press, Cambridge - Great Britain. Sakamoto, T. & McCormick, S. D. (2006). Prolactin and growth hormone in fish osmoregulation. Gen Comp Endocrinol, 147, 24-30. Sarmento, A., Guilhermino, L. & Afonso, A. (2005). Mercury chloride effects on the function and cellular integrity of sea bass (Dicentrarchus labrax) head kidney macrophages. Fish Shellfish Immunol, 17, 489-498. Saxena, M. P. & Saxena, H. M. (2008). Histopathological changes in lymphoid organs of fish after exposure to water polluted with heavy metals. The Internet Journal of Veterinary Medicine, 5(1), ISSN: 1937-8165. Schar, M., Maly, I. P. & Sasse, D. (1985). Histochemical studies on metabolic zonation of the liver in the trout (Salmo gairdneri). Histochemistry, 83, 147-51. Schroder, M. B., Villena, A. J. & Jorgensen, T. O. (1998). Ontogeny of lymphoid organs and immunoglobulin producing cells in Atlantic cod (Gadus morhua L.). Dev Comp Immunol, 22, 507-517. Schwindt, A. R., Truelove, N., Schreck, C. B., Fournie, J. W., Landers, D. H. & Kent, M. L. (2006). Quantitative evaluation of macrophage aggregates in brook trout (Salvelinus fontinalis) and rainbow trout (Oncorhynchus mykiss). Dis Aquat Org., 68(2), 101-113.
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Secombes, C. J. (1993). Phagocytes and immunity in fish. The Nordic Symposium on Fish Immunology. The Nordic Society for Fish Immunology, Lysekil - Denmark, 9-11. Secombes, C. J. (1994). Enhancement of fish phagocyte activity. Fish Shellfish Immunol, 4, 421-436. Secombes, C. J. & Fletcher, T. C. (1992). The role of phagocytes in the protective mechanisms of fish. Ann Rev Fish Dis, 2, 73-51. Secombes, C. J., Hardie, L. J. & Daniels, G. (1996). Cytokines in fish: an update. Fish Shellfish Immunol, 6, 291-304. Segner, H., Dölle, A. & Böhm, R. (1997). Ketone body metabolism in the carp Carpinus carpio: biochemical and IH-HMR spectroscopical analysis. Comp Biochem Physiol, 116B, 257-62. Sepúlveda, M. S., Gallagher, E. P. & Gross, T. S. (2004). Physiological changes in largemouth bass exposed to paper mill effluents under laboratory and field conditions. Ecotoxicology, 13, 291-301. Singh, S.M. & Sivalingam, P. M. (1982). In vitro study on the interactive effects of heavy metals on catalase activity of Sarotherodon mossambicus (Peters). J Fish Biol., 20, 683688. Šimková, A., Lafond, T., Ondračková, M., Jurajda, P., Ottová, E. & Morand, S. (2008). Parasitism, life history traits and immune defence in cyprinid fish from Central Europe. BMC Evol Biol., 8(29). Spazier, E., Storch, V. & Braunbeck, T. (1992). Cytopathology of spleen in eel Anguilla anguilla exposed to a chemical spill in the Rhine River. Diseases of Aquatic Organisms, 14, 1-22. Stegeman, J. J., Binder, R. L. & Orren, A. (1979). Hepatic and extrahepatic microsomal electron transport components and mixed function oxidases in the marine fish (Stenotomus versicolor). Biochem Pharmacol, 28, 3431-9. Stegeman, J. J. & Lech, J. J. (1991). Cytochrome P-450 monooxygenase systems in aquatic species: Carcinogen metabolism and biomarkers for carcinogen and pollutant exposure. Environ Health Perspect, 90, 101-109. Stegema,n, J. J. & Hahn, M. E. (1994). Biochemistry and molecular biology of monooxygenases: current perspectives on forms, functions and regulation of cytochrome P450 in aquatic species. In Aquatic Toxicology (D. C. Malins, & G. K. Ostrander, eds.), 87-203. Lewis Publishers, Boca Raton. Stentiford, G. D., Longshaw, M., Lyons, B. P., Jones, G., Green, M. & Feist, S. W. (2003). Histopathological biomarkers in estuarine fish species for the assessment of biological effects of contaminants. Mar Environ Res., 55, 137-159. Stephen, C., Kent, M. L. & Dawe, S. C. (1993). Hepatic megalocytosis in wild and farmed chinook salmon Oncorhynchus tshawytscha in British Columbia, Canada. Dis Aquat Org., 16, 35-9. Storch, V., Segner, H., Juario, J. & Duray, M. (1984). Influence of nutrition on the hepatocytes of Chanos chanos (Chanidae, Teleostei). Zool Anz., 213, 151-160. Suresh, N. (2009). Effect of cadmium chloride on liver, spleen and kidney melano macrophage centres in Tilapia mossambica. J Environ Biol, 30(4), 505-508. Tort, L., Balasch, J. C. & Mackenzie, S. (2003). Fish immune system. A crossroads between innate and adaptive responses. Immunologiya, 22(3), 277-286.
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Van Bohemen, C., Lambert, J. & Peute, J. (1981). Annual changes in plasma and liver in relation to vitellogenesis in the female rainbow trout, Salmo gairdineri. Gen Comp Endocrinol, 44, 94-107. Van Campenhout, K., Bervoets, L., Redeker, E. S. & Blust, R. (2009). A kinetic model for the relative contribution of waterborne and dietary cadmium and zinc in the common carp (Cyprinus carpio). Environ Toxicol Chem., 28, 209-219. Van der Oost, R., Beyer, J. & Vermeulen, N. P. E. (2003) Fish bioaccumulation and biomarkers in environmental risk assessment: a review. Environ Toxicol Pharmacol, 13, 57-/149. Van Veld, P. A. & Westbrook, D. J. (1995). Evidence for depression of cytochrome P4501A in a population of chemicallyresistant mummichog (Fundulus heteroclitus) from a creosote- contaminated environment. Environ Sci., 3, 221-224. Varsamos, S., Nebel, C. & Charmantier, G. (2005). Ontogeny of osmoregulation in postembryonic fish: A review. Comp Biochem Physiol Part A Mol Integr Physiol, 141, 401-429. Venugopal, N. & Reddy, S. L. N. (1993). In-vivo effects of trivalent and hexavalent chromium on renal and hepatic ATPases of a fresh-water teleost Anabas-scandens. Environ Monit Assess, 28, 131-136. Vethaak, D. (1993). Diseases of flounder (Platichtys flesus) in Dutch coastal and estuarine waters, with particular reference to environmental stress factors: part 2, liver histopathology. PhD thesis, 59-81. Vinodhini, R. & Narayanan, M. (2009). Heavy metal induced histopathological alterations in selected organs of the Cyprinus carpio L. (Common Carp). International Journal of Environmental Health Research, 3, 95-100. Walter, G. L., Jones, P. D. & Giesy, J. P. (2000). Pathologic alterations in adult rainbow trout, Oncorhynchus mykiss, exposed to dietary 2,3,7,8-tetrachlorodibenzo-p-dioxin. Aquat Toxicol, 50, 287-299. Wendelaar Bonga, S. E. (1997). The stress response in fish. Physiol Rev., 77, 591-625. Wendelaar Bonga, S. E. & Lock, R. A. C. (2008). The osmoregulatory system. In The toxicology in fishes. R. T. Di Giulio, (eds). CRC Press, New York. 401-415. Wester, P. W. & Canton, J. H. (1987). Histopathological study of Poecilia reticulata (guppy) after long term exposure to bis(tri-n-butyltin)oxide (TBTO) and di-n-butyltindichloride (DBTC). Aquat Toxicol, 10, 143-65. Wester, P. W., Canton, J. H., Van Iersel, A. A. J., Kranjnc, E. I. & Vaessen, H. A. M. G. (1988). The toxicity of bis(tri-n-butyltin)oxide (TBTO) and di-n-butyltindichloride (DBTC) in the small fish species Oryzias latipes (medaka) and Poecilia reticulata (guppy). In Toxicological Pathology in Fish: An Evaluation with Two Species and Various Environmental Contaminants, 107-28. Door, The Netherlands. Wester, P. W., van der Ven, L. T. M., Brandhof, E. J. & Vos, J. H. (2003). Identification of endocrine disruptive effects in the aquatic environment: a partial life cycle assay in zebrafish. RIVM Report 6409200001/2003, 31-9. Wright, D. A. & Welbourn, P. M. (1993). Effects of mercury exposure on ionic regulation in the crayfish Orconectes propinquus. Environmental Pollution, 82, 139-142. Wyte, J. J., Jung, R. E., Schmitt, C. J. & Tillitt, D. E. (2000). Ethoxyresorufin-o-deethylase (EROD) activity in fish as a biomarker of chemical exposure. Critical Rev. Toxicol, 30 (4), 347-570.
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Wolf, J. C. & Wolfe, M. J. (2005). A Brief Overview of Nonneoplastic Hepatic Toxicity in Fish Toxicologic Pathology, 33, 75-85. Zapata, A., Diez, B., Cejalvo, T., Gutiérrez-de Frías, C. & Cortés, A. (2006). Ontogeny of the immune system of fish. Fish Shellfish Immunol, 20(2), 126-136. Zapata, A. G., Chibá, K. & Varas, A. (1996) Cells and tissues of the immune system of fish. In The fish immune system: organism, pathogen and environment. G. Iwama, T. & Nakanishi, (eds). Academic Press, USA. Zapata, A., Chibá, A. & Varas, A. (1996). Cells and tissues of the immune system of fish. In The fish immune system. G. K. Iwama, & Nakanishi, T. (eds.). Academic Press, USA, 153. Zapata, A. G. & Cooper, E. L. (1990). The immune system: Comparative histophysiology. John Wiley & Sons, Chichester.
In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 39-72 © 2011 Nova Science Publishers, Inc.
Chapter 2
BENTHIC FORAMINIFERA IN COASTAL LAGOONS: DISTRIBUTIONAL PATTERNS AND BIOMONITORING IMPLICATIONS F. Frontalini,1 E. Armynot du Châtelet2, J.P. Debenay3, R. Coccioni1 and G. Bancalà1
1
DiSUAN, Urbino University, Campus Scientifico, Localita' Crocicchia, 61029, Urbino, Italy 2 CNRS, UMR 8157, UFR des Sciences de la Terre, Laboratoire Géosystèmes, Université de Lille-1, bâtiment SN5, 59655 Villeneuve d‘Ascq cedex, France 3 IRD, Unité 182 LOCEAN, BP A5, 98848 Nouméa cedex, Nouvelle-Calédonie, France
ABSTRACT Coastal lagoons are particularly complex environments in which the transition between marine and continental waters is gradual, due to the continuity of the aquatic habitat. They are characterized by major fluctuations in chemical and physical parameters, which reflect multiple interactions between the distance to the sea, water depth, the nature of the sediment, organic matter quality, hydrodynamic turnover time, tidal currents, wind forced currents, volume lost by evaporation, and gravitational circulation. Moreover, these ecosystems are often subjected to a great deal of anthropogenic impact, which further complicates our understanding of these habitats. Comparative studies of lagoonal environments essentially require the utilization of organisms that are distributed worldwide and occur in high density populations in most of the benthic niches. This is certainly the case for foraminifers which, as lower trophic level members, are crucial to the biological community and ideal candidates for comprehensive habitat assessment. Some widespread paralic benthic foraminiferal species are present from temperate macrotidal estuaries to tropical microtidal lagoons, thus enabling comparative studies of environmental conditions to be conducted.
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F. Frontalini, E. Armynot du Châtelet, J.P. Debenay et al. Since lagoons are increasingly affected by environmental stress and degradation due to pollution and other anthropogenic factors, there is a pressing need to develop a set of indicators and monitoring approaches with which to assess their health. A large number of research programs have addressed these issues within various regions, and studies of foraminiferal assemblages have produced very useful, comprehensive datasets on environmental and biotic conditions. This paper is a review of what is known about the foraminiferal assemblages living in lagoons, including their distribution according to environmental parameters and their value when it comes to assessing environmental quality in these ecosystems.
1. INTRODUCTION A lagoon is ‗a body of shallow sea water or brackish water separated from the sea by some form of barrier‘, which excludes isolated inland saline water bodies. In reality, lagoons are complex ecotones located between continental and marine systems. They are also highly heterogeneous due to: 1) strong variations in physical, chemical and biological characteristics over space and time, and 2) multiple exchanges with the limiting continental and marine systems, the atmosphere, and sediments. Located at the transition between the continental and the marine realms, lagoons belong to paralic habitats. The term paralic was defined by Naumann (1854) for fossil environments and was first used by a sedimentary geologist. Later, the notion was adapted to apply to recent ecosystems comprising estuaries, coastal lagoons, marshes, and coastal zones under high freshwater input (Guélorget and Perthuisot, 1983, 1992). This term is more precise than the traditional phrase ‗margino marine‘ and is increasingly used to refer to modern environments. For the purpose of this study, we restricted our survey to clastic lagoons separated from the ocean by a depositional land barrier, excluding coral reef lagoons. We also used the physiography of clastic lagoons as clarified by Kjerfve (1986), who distinguished between restricted, choked and leaky lagoons (Figure 1). In particular, restricted lagoons are characterized by two or more entrance channels or inlets as well as well-defined tidal circulation.
Figure 1. Schematic representations of restricted, choked and leaky lagoons, after Kjerfve (1986)
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Like other paralic environments (e.g. marsh, mangrove, estuary, fjord and delta), lagoons exhibit a balance between an enhanced freshwater input and an evaporation loss, which determines a salinity gradient within the continuity of the aquatic habitat. Transition processes are much more complex in sheltered lagoons with high water retention times than in large well-flushed estuaries. On the basis of the triple influence of fluvial input, exchanges with the sea, and climate, the gradation can be either horizontal and/or vertical, and moves from brackish to hypersaline environments. These general conditions are complicated by a complex interplay of an array of parameters that include: (1) local climatic conditions (i.e. temperature, insolation, evaporation-rainfall balance); (2) horizontal salinity distribution, which also controls plant distribution; (3) vertical mixing between hypo- and hypersaline water, thus affecting water stratification; (4) hydrodynamic turnover time; (5) the energy of wind-forced currents and wave action; (6) the nature of the bottom; (7) the occurrence of seaweed or seagrass meadows; (8) the quality and quantity of suspended sediment (turbidity), nutrients, and dissolved and particulate organic matter; (9) the physical-chemical characteristics of the water (mainly oxygen content and pH); and (10) aperiodic crises, such as anoxia, drought, storms, or frost (Debenay et al., 2000; Debenay and Guillou, 2002). These multiple factors lead to a major internal patchiness and heterogeneity, as well as environmental fluctuations which occur at a variety of time scales ranging from daily to seasonal to years/decades, and which are further influenced by multiple impacts of anthropogenic activities. These can be the result of: pollution from industrial, domestic, agricultural, and mining work; dredging and spoil dumping; salinization; siltation and sedimentation from land clearance; forestry; and the destruction of habitat. Agricultural runoffs may be enriched in nutrients and pesticide residues, the former of which can lead to eutrophication, the deterioration of water quality and, ultimately, anoxic conditions (Wilson et al., 1993; Moss, 1996). However, nutrients are not the only chemicals affecting the ecosystems; trace elements and other organic and inorganic chemicals are also ubiquitous contaminants of the aquatic environment. There is, therefore, a need to develop a set of indicators and monitoring approaches for use in these shallow transitional waters which are increasingly affected by environmental stress that is naturally and, above all, anthropogenically induced. This requirement is made more difficult by the complexity of these environments, which can often influence and complicate the application of the most common indicators and indices of environmental quality and health status. A large number of research programs have addressed these problems within various coastal regions, and have produced extremely valuable and comprehensive datasets on the environmental and biotic conditions within these systems. A growing number of new tools and methods for assessing the health of these systems have thus emerged, and of these foraminifera are of primary importance. Foraminifera (class Foraminifera: d‘Orbigny, 1826; phylum Granuloreticulata) are single-celled organisms (protists), which play a significant role in global, biogeochemical cycles of inorganic and organic compounds, making them one of the most important animal groups on earth (Haynes, 1981; Lee and Anderson, 1991; Yanko et al., 1999). Furthermore, many foraminiferal taxa secrete a carbonate shell, which is readily preserved and so records evidence of environmental stresses and changes over time. They are commonly small and abundant compared to other hard-shelled taxa and are easy to collect, meaning that a highly reliable database for statistical analysis can be obtained, even when only small sample
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volumes are available. Because of their: widespread distribution; short life and reproductive cycles (from a few weeks for small taxa to one year for some larger forms: Boltovskoy, 1965, and Murray, 1991, 2006); high biodiversity; and specific ecological requirements, foraminifera respond rapidly to environmental changes. Benthic foraminifera are particularly sensitive, and can be successfully utilized for their value as bio-indicators of environmental change in a wide range of marine environments (e.g. Alve, 1991, 1995; Yanko et al., 1999; Coccioni, 2000; Debenay et al., 2001, 2005; Murray and Alve, 2002; Armynot du Châtelet et al., 2004; Frontalini and Coccioni, 2008; Frontalini et al., 2009, 2010; Coccioni et al., 2009; Debenay et al., 2009a; Armynot du Châtelet and Debenay, 2010). The aim of this paper is to review the recent advances and achievements when it comes to understanding the processes controlling the distribution of foraminiferal assemblages within lagoons. The main findings in relation to an array of parameters will also be summarized and emphasized. The article will also discuss the significance and influence of anthropogenic activities on benthic foraminifera in these sensitive, but environmentally valuable, areas.
2. MATERIAL AND METHODS Samples were collected either with a grab sampler or by snorkelling in subtidal environments. At intertidal stations, the samples were obtained by scraping off the upper five millimeters of sediment. The collections were made at several points over a surface of about 1 m2 using a pseudoreplication strategy (Hurlbert, 1984) to limit the bias due to patchy distribution. In such heterogeneous environments, field experience shows that the standard collection of samples over a 10 cm2 surface (e.g. Wells, 1971) does not provide reliable data, while the time consuming study of replicates (e.g. Murray, 2006) is justified only for detailed studies of living assemblages. Samples can be preserved in alcohol (ethanol), which allows Rose Bengal staining (Walton, 1952) to be used to help identify living individuals. Only superficial samples are considered because, even though foraminifera can live at depths of 30 cm in the sediment (e.g. Goldstein et al., 1995; Ozarko et al., 1997), the greatest numbers of living creatures, which produce the accumulation of living and empty tests, are found in the surface layer <1 cm (review in Alve and Murray, 2001). Collecting sediment from greater depths would also include tests deposited over a long period of time. At the laboratory, a subsample of 50 cm3 was extracted from each sample after homogenization and then washed through 315 and 50/63 μm sieves. After drying, the microfauna were separated from sand grains by flotation on trichloroethylene (d=1.465) or carbon tetrachloride (d=1.594). Observations were carried out under a stereo microscope and: (1) the total number of tests in 50 cm3 of sediment was examined; (2) 100 to 300 individuals, depending on the total number of species, were counted (Fatela and Taborda, 2002); and (3) whole samples were checked for rare species which were not found during counting. When the population density was lower than 100, all of the individuals were counted. Rose Bengal stained (living?) individuals were noted separately to provide information on living, dead and total (stained + empty tests) assemblages. However, the reliability of Rose Bengal staining for determining living individuals is still the subject of some debate (discussion in Debenay et al., 2009b, p. 253-254), and the study of living assemblages in highly dynamic environments, such as lagoons, might be more appropriate for time series studies.
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3. FORAMINIFERA LIVING IN LAGOONAL ENVIRONMENTS Complicated by tidal and seasonal cycles, the physicochemical characteristics of lagoonal environments can change drastically in relation to hydrodynamic turnover time (itself a function of freshwater input), tidal currents, wind forced currents, and volume lost by evaporation and gravitational circulation. Benthic organisms living in such environments must adapt to this instability and are generally euryhaline and eurythermal. For example, the cosmopolitan Ammonia tepida tolerates salinities ranging from 0.2 to 100 (Bradshaw, 1957; Reddy and Rao, 1984; Debenay, 1990; Almogi-Labin et al., 1992; Wennrich et al., 2007). However, only a few species can tolerate such ecological conditions, and the foraminiferal assemblages in lagoons are poorly diversified and display high levels of dominance. Despite the fact that endemic species which characterize specific areas can be found, there is an overall species similarity in lagoonal environments. The foraminiferal assemblages are generally dominated by Rotaliina in moderately restricted environments, the most cosmopolitan species being Ammonia parkinsoniana (d‘Orbigny, 1839), Ammonia tepida (Cushman, 1826), Elphidium gunteri (Cole, 1931), Haynesina germanica (Herenberg, 1840), and Quinqueloculina seminula (Linné, 1758) (Figure 2). On the other hand, the agglutinated species Ammobaculites exiguus Cushman and Brönnimann, 1984, Ammotium salsum (Cushman and Brönnimann, 1984), Arenoparella mexicana (Kornfeld, 1931), Gaudryna exilis Cushman Brönnimann, 1984, Haplophragmodes wilberti Andersen, 1953, Pseudoclavulina sp. and Trochammina spp. are the dominant species in restricted to highly restricted environments (Figure 2). Low salinity habitats are dominated by Miliammina fusca (Brady, 1870), Astrammina sphaerica (Heron-Allen and Earland, 1932) and Polysaccammina ipohalina Scott, 1976 (Figure 2). Ammonia tepida and Q. seminula are considered to be quite tolerant of environmental stress (Debenay et al., 2000; Debenay and Guillou, 2002), and these two species have been regarded as the primary pioneers in several paralic environments (Debenay et al., 2009b). For example, in the hypersaline Araruama Lagoon (Brazil) and Lake Qarun (Egypt), they comprise 70% of the total foraminiferal assemblage (Debenay et al., 2001; Abu-Zied et al., 2007). Ammonia beccarii (tepida?), which is associated with Cribroelphidium articulatum, was also reported as being present in the hypersaline Coorong Lagoon (Cann et al., 2000). It is also well represented in the Santo André Lagoon, Portugal, in association with H. germanica, Elphidium oceanensis and Q. seminula (Cearreta et al., 2002); in Lake lllawarra, Australia, where it is associated with Cribrononion sydneyensis (Yassini and Jones, 1989) and in small coastal lagoons located along the coast of West Africa (Debenay, 1990). In Croatia, A. tepida lives in low-oxygen, slightly hypersaline lagoons, typically in association with Haynesina depressula Walker and Jacob, 1798, Elphidium crispum (Linné, 1758), and Quinqueloculina spp. (Vanicek et al., 2000). However, a great deal of confusion still exists about the variety of forms and the taxonomy of the genus, despite numerous attempts to clarify these issues (e.g. Hayward et al., 2004). It is, therefore, highly probable that several different species are present in lagoons.
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Figure 2. Benthic foraminiferal species in lagoon environments: 1. Polysaccammina ipohalina, 2. Trochammina inflata, 3. Pseudoclavulina sp., 4. Ammobaculites exiguus, 5. Ammotium salsum lateral and apertural views, 6. Miliammina earlandi apertural and lateral views, 7. Miliammina fusca lateral and apertural views, 8. Caronia exilis lateral and apertural views, 9. Quinqueloculina seminula, 10. Arenoparrella mexicana spiral, apertural, and umbilical views, 11. Haplophragmoides wilberti lateral and apertural views, 12. Eponides repandus apertural and spiral views, 13. Discorbinella bertheloti spiral, umbilical, and lateral views, 14. Bolivina striatula, 15. Porosononion granosum, 16. Nonionella turgida, 17. Discorinopsis agayoi umbilical and spiral views, 18. Pararotalia cananeiaensis spiral, lateral and umbilical views, 19. Ammonia parkinsoniana umbilical view, 20. Ammonia tepida umbilical views, 21. Elphidium gunteri, 22. Cribroelphidium excavatum, 23. Haynesina germanica, 24. Haynesina depressula, 25. Elphidium crispum. Scale bars are 100µm
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The geographic distribution of these paralic species covers spectacularly wide latitudinal and longitudinal ranges (e.g. Sen Gupta, 1999; Debenay and Guillou, 2002), and their worldwide distribution supposes powerful dispersion processes. Aerial transport, over short or great distances, is often mentioned, since foraminifera may occasionally survive on the muddy feet or feathers of migratory seabirds, whose landfalls are mostly intertidal mud and sand flats (e.g. Resig, 1974; Lessard, 1980; Patterson et al., 1997; Hayward and Hollis, 1994; Almogi-Labin et al., 1995; Wennrich et al., 2007). Transport by fish is also possible if they move from one area to another during feeding and defecation (Daniels and Lipps, 1978; Langer and Lipps, 2006; Debenay et al., in press). The transplantation of marine fish or shellfish may also play a part in the introduction of new foraminifera (Arnal, 1954; Bouchet et al., 2007). Travel over short distances may similarly affect embryonic juveniles, which are easily transported thanks to a density that is similar to that of seawater (Goubert, 1997; Alve, 1999; Hayward et al., 1999). Accordingly, incoming tidal currents probably introduce many coastal species to the lagoons, but only those that can adapt, grow and reproduce in the new environment survive. In shallow paralic environments, the most successful colonizer is A. tepida in both brackish (Wennrich et al., 2007) and hypersaline (Almogi- Labin et al., 1992) waters. Indeed, during interglacial intervals in the Quaternary, it colonized lakes along the Mediterranean (Usera et al., 2002). It also populated shrimp ponds, which are associated with Q. seminula, with its fast reproduction rates rapidly increasing the density of live specimens and the accumulation of empty tests (Debenay et al., 2009b).
4. DISTRIBUTION OF FORAMINIFERA IN LAGOONAL ENVIRONMENTS 4.1. Common Pattern Numerous studies of benthic foraminiferal assemblages have been carried out in lagoons, (e.g. Closs, 1963; Closs and Madeira, 1968; Schafer and Sen Gupta, 1969; Murray, 1971; Madeira-Falceta, 1974; Suguio et al., 1975; Scott, 1976a,b; Zaninetti et al., 1977, 1979; Scott and Medioli, 1980; Zaninetti, 1982; Beurlen and Hilterman, 1983; Boltovskoy and Martinez, 1983; Debenay, 1990, 1991; Albani et al., 1991; Debenay et al., 1993; Alve and Murray, 1994a; Hayward et al., 1996; Redois and Debenay, 1996; Vanicek et al., 2000; Coccioni, 2000; Cearreta et al., 2002; Serandrei Barbero et al., 2004). A common pattern is their general distribution along a marine-continental gradient, with diverse assemblages, including calcareous forms closest to the ocean, changing landwards into oligospecific-to-monospecific assemblages in both hyposaline and hypersaline environments (Debenay et al., 2000; Debenay and Guillou, 2002). Low diversity assemblages present in the areas closest to freshwater input contain only agglutinated species (e.g. Serandrei Barbero et al., 1997; Lloyd and Evans, 2002) As stated by Nichols (1974) and reported in numerous studies, this pattern suggests that salinity is the major controlling factor for the presence of foraminiferal assemblages in paralic environments. However, their distribution is often more complex, reflecting multiple interactions between the distance to the sea, water depth, the nature of the sediment,
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hydrodynamic turnover time, tidal currents, wind forced currents, and gravitational circulation etc. It also depends on the great variety of foraminiferal behaviour, namely mode of nutrition, tolerance to oxygen depletion, steno- or euryhalinity, steno- or eurythermy, epior endofaunal mode of life, and free or attached mode of life. Among the major parameters identified as having a strong influence on foraminiferal distribution are: exposure during tidal cycles (Hayward and Hollis, 1994; De Rijk, 1995; Horton et al., 1999); pH (Wang, 1992); organic matter content; and grain size of the sediment (Scott et al., 1979; Zaninetti, 1982; Petrucci et al., 1983; Albani et al., 1991; Jennings and Nelson, 1992; Coccioni 2000). Consequently, foraminiferal assemblages may change considerably from one lagoon to another, depending on local characteristics. As a result of the complexity of interpreting entire assemblages, biocenotic indices, such as the diversity index or the dominance index, are often used for the characterization of the community structure and, subsequently, environmental conditions. However, attempts to use the Fisher diversity index revealed that values vary irregularly between 2 and 8 inside the lagoons, without any clear ecological significance (Zaninetti et al., 1977; Debenay, 1990; Debenay et al., 1998). This is probably the result of a replacement of fauna (hyaline species replaced by agglutinated ones), rather than a simple faunal change. Moreover, biocenotic indices neither take into account the role of the species in the community, nor their potential interest as bioindicators. Accordingly, they are of lesser value than the methods based on the presence/absence of bioindicator species (Caquet and Lagadic, 1998). Instead of such biocenotic indices, the ―Confinement Index‖, or Ic, which is based on the relative abundance of species identified as being characteristic of environmental conditions, has been defined in the estuaries and lagoons of West Africa (Debenay, 1990). It was later adapted, with slight modifications, for utilization in Brazilian lagoons (Debenay et al., 1996), a Mediterranean lagoon (Debenay et al., 2005), and in the Mekong estuary (Debenay and Luan, 2006). The species used for the calculation of the Ic are listed in Table 1. The following selected examples were studied separately by one of us. They are grouped together here to illustrate the particular conditions that can prevail in some representative lagoonal environments.
Figure 3. Locations map of some of the presented lagoons
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Table 1. The Confinement Index and the species considered for its calculation in different worldwide areas Group A, species related to strong marine influence: Mediterranean (Kalloni)
Vietnam (Mekong delta)
Elphidium crispum, Gavelinopsis praegeri, Lobatula lobatula, Nonionella turgida, Quinqueloculina stelligera, Rosalina bradyi, R. floridensis, R. globularis, Triloculina adriatica Asterorotalia dentata, Asterorotalia pulchella, Brizalina striatula, Cribroelphidium cf. incertum, Rosalina sp.
Group B, species from paralic environments subjected to noticeable marine influence: Aubignyna planidorso, Brizalina striatula, B. variabilis, Eggerelloides scaber, Elphidium jenseni, Porosononion granosum Ammonia spp., Brizalina cf. variabilis, Haynesina sp., Miliammina spp., Quinqueloculina seminula
Brazil (coastal lagoons)
Bolivina striatula, Elphidium gunteri, Pararotalia sp., Rosalina spp.
Ammonia spp., Bolivina variabilis, Elphidium galvestonense, Haynesina germanica, Quinqueloculina seminula, Quinqueloculina poeyana
Africa (coastal lagoons and estuaries)
Elphidium fichtelianum, Pararotalia sp., Bolivina striatula, Rosalina spp.
Eggerelloides scaber, Quinqueloculina poeyana, Q. seminula, Haynesina germanica, Elphidium gunteri, E. limosum, Bolivina variabilis, Ammonia spp.
Western coast of France
Brizalina strialula, Brizalina variabilis, Cribroelphidium excavatum, Elphidium pulvereum, Quinqueloculina stelligera, Rosalina spp.
Ammonia tepida, Elphidium gunteri, Haynesina germanica, Quinqueloculina seminula
Group C, euryhaline species living in more restricted areas: Ammonia tepida, A. convexa, Cribroelphidium translucens, Haynesina depressula simplex, Haynesina sp., Quinqueloculina seminula
Ammobaculites formosensis, Ammotium cf. salsum, Arenoparrella asiatica, Haplophragmoides wilberti, Jadammina macrescens, Siphotrochammina lobata, Trochammina spp. Ammobaculites exiguus, Ammotiumsalsum, Arenoparrella mexicana, Gaudryina exilis, Haplophragmoides wilberti, Miliammina spp., Trochammina spp., Siphotrochammina spp. Ammobaculites exiguus, Ammotium salsum, Arenoparella mexicana, Gaudryina exilis, Haplophragmoides wilberti, Miliammina spp., Trochammina spp., Siphotrochammina lobata Jadammina macrescens, Miliammina spp., Paratrochammina spp., Trochammina spp.
Ic = (C /(B + C) - A /(A + B) + 1)/2Ic = 1 if assemblage III is the only one represented (A + B = 0); Ic = 0 if assemblage I is the only one represented (B + C = 0). Ic<0.4 indicates low confinement; 0.4
0.9 indicates an extreme confinement
4.2. Choked Stratified Lagoon Example: Lagoa da Conceição, Brazil, latitude ≈ 27°3 S (Debenay et al., 1998; Figures 3 and 4).
Morphology The lagoon is elongated, about 13.5 km in length, with a total surface area of about 19 km2 (Knoppers et al., 1984; Muehe and Caruso-Gomes, 1989). It communicates with the sea via a narrow, 2 m deep and 2 km long channel (Odebrecht and Caruso-Gomes, 1987; Sierra de Ledo and Klingebiel, 1993). The lagoon is longitudinally divided into three zones, with a maximum water depth of about 8 m, and is separated by shallows and/or narrowings. The
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dunes extend into shallow sandbanks on the east side, while a deep channel is present on the west side (Figure 4).
Hydrodynamics The long and shallow entrance channel reduces water exchanges with the ocean, while fresh water enters the lagoon through runoff from the western granitic reliefs, the João Gualberto River discharge in the northern zone, and groundwater seepage from the sand dunes in the southern zone (Odebrecht and Caruso-Gomes, 1987). During the rainy season, the high freshwater input is responsible for strong water stratification, with brackish superficial water (≈18‰) and saline bottom waters (> 30‰) being trapped in the depressions and becoming anoxic. During the dry season, the stratification is weakened and the bottom waters can be renewed. Sediments The sediments in the depressions are organic-rich muds, while fine to medium grained sands, with numerous fragments of euryhaline Pelecypods, make up the sand banks.
Figure 4. Conceição Lagoon on Santa Catarina island. A. Horizontal distribution of the main foraminiferal species showing the dominance of agglutinated species on sand banks while hyaline species dominate in deeper areas; B. Vertical distribution of the main foraminiferal species showing the impact of the halocline on the dominant species. C. Distribution of Ic values with depth showing the impact of the halocline on foraminiferal assemblages (after Debenay et al., 1998)
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Foraminiferal Assemblages The density of tests in 50 cm3 of sediment (D50) varies from zero to 800 inside the lagoon, reaching 5000 in the outer part of the entrance channel. Thirty-three species are found. The assemblages reveal little horizontal change, except for a higher percentage of Miliammina (70%), which is under the direct influence of freshwater input. Vertically, they change abruptly at about the halocline: shallow sand banks (<1.5 m) are dominated by agglutinated species, mainly Ammotium salsum, which is associated with A. exiguus, Pseudoclavulina sp., G. exilis, and Miliammina earlandi. Depressions, on the other hand, are characterized by less restricted foraminiferal taxa, such as A. tepida and E. gunteri (Figure 4 A-B). This deeper microfauna only develops during periods of bottom water renewal (dry season), while only empty tests are found during anoxic conditions (rainy season). Pararotalia cananeiaensis, which is characteristic of a stronger marine influence, is found only in the outer part of the channel. The diagram of the Ic vs. depth clearly shows the distribution of the two assemblages, which are separated from each other at the depth corresponding to the halocline (Figure 4C). The Ic index, which is between 0.4 and 0.7 in most parts of the depressions, indicates a moderate confinement, while a strong confinement is suggested in the shallow areas. Stratification is also observed in the choked, hyposaline Ebrie Lagoon (Ivory Coast; Debenay et al., 1987). Ammotium salsum is the dominant species, and is associated with A. tepida near the entrance channel. A high proportion of Miliammina spp. occurs near the mouth of the main tributary. Neither foraminifera nor other microorganisms are found in the deep anoxic depressions.
4.3. Restricted Lagoon with Salt Wedge Example: Cananéia-Iguape Lagoon, Brazil, latitude ≈ 25° S (Eichler et al., 1995; Debenay et al., 1998; Figures 3 and 5)
Morphology The Cananéia-Iguape Lagoon is made up of channels that run parallel to the coastline and are separated from the sea by a sand spit, which is more than 70 km long. The study area in the south-eastern part of the lagoon consists of two channels that are 6 to 10 m deep (Mar de Cubatão and Mar de Cananéia), and are connected southwards with the Baia de Trapandé (10 m deep), which is wide open to the sea through a 13 m deep inlet (Figure 5). Mangroves are well developed on the edges of the lagoon. Hydrodynamics The characteristics of the mixohaline waters depend on sea-water inputs during semidiurnal microtidal tides (mean amplitude about 0.8 m) and seasonal cycles of freshwater input from small coastal rivers (Miyao et al., 1986). The resulting pattern is an inclined salinity gradient (salt wedge), which is related to gravitational circulation (Kjerfve, 1986; Kjerfve and Magill, 1989) (Figure 5B).
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Figure 5. Cananéia-Iguape Lagoon. A. Horizontal distribution of the main foraminiferal species showing changes from hyaline species near the inlet to agglutinated species landward. B. Distribution of salinity values with depth and distance to the sea showing the salt wedge. B. Distribution of Ic values with depth and distance to the sea where the influence of the salt wedge can be seen. Anomalous values of Ic are found in areas subjected to pollution (after Eichler et al., 1995; Debenay et al., 1998)
Sediments The sediments are mostly muddy sands, with mud in restricted areas, sand near the inlet where the tidal currents are stronger, and coarse sand and gravel in estuaries where there are strong currents during the rainy season. Foraminiferal Assemblages The density (D50) varies from 20 to 3000, reaching a maximum at Baia de Trapandé. The microfauna are comprised of about 100 species. Near the lagoon entrance, under marine influence, the assemblage is dominated by calcareous species, particularly P. cananeiaensis, which is associated with Brizalina striatula, E. gunteri, and Pseudononion atlanticum (Figure 5A). This assemblage progressively changes landwards, with an increasing proportion of agglutinated species, such as A. salsum and G. exilis, becoming dominant in restricted areas. In low salinity areas, the assemblages become oligospecific, with the M. earlandi predominating. The progressiveness in the transition means that it is not possible to subdivide the lagoon into clearly distinct zones.
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The Ic index increases progressively landwards, reflecting the gradual transition in foraminiferal assemblages. It increases more rapidly in the shallow waters (Ic D 0:4 about 10 km from the sea) than in the deep bottom waters of the channel (Ic D 0:4 about 18 km from the sea), revealing a weaker marine influence in the shallower areas in relation to the salt wedge (Figure 5C).
4.4. Choked Non-Stratified Hypersaline Lagoon Example: the Lagoon of Araruama, Brazil, latitude ≈ 23° S (Debenay et al., 2001, Figures 3 and 6)
Morphology The Lagoon of Araruama is one of the largest hypersaline lagoons in the world (Kjerfve et al., 1996). It is about 47 km long, with a surface area of 210 km2 and an additional 65 km2 of adjacent salt-producing ponds. Its average depth is about 3 m up to a maximum of 17 m. It has only limited water exchanges with the sea through a narrow and shallow entrance channel (less than 4 m deep) located at its eastern extremity. Sand spits, constructed by wind driven circulation cells, extend into sand banks and partially divide the lagoon into several basins. Hydrodynamics The deficit in the water balance: average rainfall ≈700 mm/y, average evaporation ≈1400 mm/y (Kjerfve et al., 1996), results in permanently hypersaline conditions. The mean salinity may exceed 65‰ (average 52‰; André et al., 1979), lowering only in the entrance channel and the eastern-most basin. In the salt-producing ponds it exceeds 100‰. Only two tributaries, located in the north-western part of the lagoon, have permanent runoffs. Other freshwater inputs result from rainfall, runoffs, small river occasional discharges, and domestic sewage, which are estimated to be 0.7 m3/s (Kjerfve et al., 1996). The increase in the superficial water density, which results from intense evaporation, induces mixing in the water column and prevents water stratification. The tidal range (0.8 m to 1.3 m in the open ocean) rapidly weakens in the lagoon, where it becomes negligible (14 km inside) (Lessa, 1990). The circulation processes are dominated by clockwise wind driven circulation cells. Sediments The input of fluvial sediments is noticeable in the western part of the lagoon where fine organic rich sediments accumulate (Azevedo, 1984; Barroso, 1987). The finest sediments, which are comprised of up to 98% of silt and clay, are mainly present in the deepest, central part of the lagoon and in the shallow, eastern-most lagoon cell. They are black and reduced, except for a thin surface layer. The sediments of the shallower northern and southern parts of the lagoon are shelly sands with a thick oxidized layer. The western-most lagoon cell often has accumulations of organic remains (plant fragments, dead fish or various domestic effluents). The maximum concentrations of organic carbon, phosphorus, and nitrogen are found near to human activities (Campos et al., 1979; Debenay et al., 2001).
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Figure 6. Araruama Lagoon. The dominance of Ammonia tepida is related to enrichment in anthropogenic nutrients along the northern shore and eastern part of the lagoon assemblages (after Debenay et al., 2001)
Foraminiferal Assemblages The density (D50) varies from 50 to about 50,000 inside the lagoon, reaching 500,000 in adjacent areas. A total of seventy-four species are found, with the species richness of the samples ranging between 5 and 27. Very few specimens were alive. The D50 is highest along the northern coast and in the central part of the lagoon, while it is less than 1000 near to the main urban areas, Araruama City and Cabo Frio. In the entire lagoon, the assemblages are dominated by three species: A. tepida, Q. seminula (first identified as Triloculina oblonga) and the less abundant Cribroelphidium excavatum var. selseyense. Ammonia tepida is dominant (50%-92% of the assemblages) along the northern shore and at the eastern end of the lagoon, while Q. seminula is dominant at the other stations (Figure 6). This has been attributed to the input of wastewaters and the enrichment in anthropogenic nutrients along the northern shore and eastern part of the lagoon. Only a few species that are indicative of marine influence are present in the outermost stations of the entrance channel (e.g. Eponides repandus, Discorbinella bertheloti, Pseudononion atlanticum, Quinqueloculina lamarckiana and P. cananeiaensis). In adjacent areas, Q. seminula is frequently dominant, and is associated with A. tepida and species that are absent or rare in the lagoon, such as Discorinopsis aguayoi. Textulariidae are nearly absent, even in the hyposaline estuaries of the tributaries. No correlation was observed between the abundance of common species and any of the sedimentary parameters. The Ic index is about 0.5 in almost the entire lagoon, except near the entrance and in the estuaries of the tributaries.
4.5. Restricted, Non-Stratified Lagoon, with Roughly Normal Saline Waters Example: Gulf of Kalloni, Lesvos Island, Greece, latitude ≈ 39°05‘ N, longitude ≈ 26°10‘ E (Debenay et al., 2005; Figures 3 and 7)
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Morphology The Gulf of Kalloni is essentially a lagoon that is about 20 km long, with a surface area of about 130 km2. It communicates with the sea through a narrow inlet, which is less than 2 km wide, at its south-western end. The depth of about 25 m at the inlet decreases steadily north-eastwards, while the gulf progressively widens, ending up in a wider and shallower north-eastern part. Hydrodynamics During the dry season (May-September), weak freshwater input and strong wind-induced evaporation lead to higher salinity (38‰) in the north-eastern end of the gulf. During the rainy season (October-April), freshwater input from small intermittent rivers lowers the salinity, the seasonal range being about 5‰ (Lefebvre, 1993). No vertical salinity stratification was observed, other than temporary stratification during strong rainfalls. According to Kjerfve and Magill (1989), the horizontal salinity gradient demonstrates that the flushing rate is relatively long in the north-eastern part of the gulf. Water exchange with the Aegean Sea depends on tidal flow (maximum tidal range of 23 cm) and wind-forced currents (Millet and Lamy, 2002; Debenay et al., 2005). When northern winds dominate (June to September), the marine waters penetrate through the central part of the gulf, reaching its north-east end in less than five days; the ebb tidal flow moves along the shores. In contrast, when the southern winds blow (October to March), the marine waters penetrate along the shores, particularly the southern shore. The seawards ebb tidal flow moves through the central part of the gulf. North-westerly and south-easterly winds, which only blow for limited periods, induce clockwise gyratory currents that limit the inflow of marine water to the south-western part of the gulf and enhance the confinement in the northeastern part (Millet and Lamy, 2002). Sediments The bottom sediments are sand, muddy sand or sandy mud, with a greater proportion of mud (up to 93%) in the low energy, deepest areas. These are mostly of terrigenous origin, with a greater contribution of carbonate biogenic production in the shallower sandy areas. They are enriched in organic matter near a fish farm and a small town to the south. The concentration of Cu is low in most of the gulf (around 14 ng/g), revealing the absence of noticeable chemical contamination, except in the vicinity of the town of Skala Kalloni (53 ng/g) (Angelidis et al., 2001). Foraminiferal Assemblages The density (D50) varies from 160 to about 40,000, with the maximum being near the inlet. The lower values are in the central axis of the gulf and in two areas of high organic input near a fish farm and a town. A total of 147 species is found, which is quite high compared to the shallow choked lagoons of the western Mediterranean (69 in the Thau Lagoon, France (Kurk, 1961) and 47 in the Prévost Lagoon, France) (Favry et al., 1998), but considerably lower than in Mediterranean open gulfs: 222 species in the Gulf of Policastro, Italy (Sgarrella et al., 1985) and 366 in the Gulf of Naples (Sgarrella and Moncharmont-Zei, 1993). With respect to foraminiferal assemblages, the Gulf of Kalloni has an intermediate position between choked lagoons and the gulfs that are wide open to the sea. The species
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richness ranges between 11 and 81, with decreasing values from the inlet towards the northeastern end of the gulf and from the shores towards the deeper, central part. The six dominant species are Haynesina sp., Aubignyna planidorso, A. beccarii, A. tepida, Porosononion granosum and Nonionella turgida. Ammonia tepida and Haynesina sp. achieve their maximum relative abundances in the north-eastern part of the gulf and in the two areas of high organic input. A. planidorso and P. granosum reach their highest relative abundance along the central axis of the gulf, where water energy is lower in the depression of the southern axial zone, and in the centre of the gyratory currents affecting the north-eastern part of the gulf. The lower density and species richness in the two areas of high organic input may result from low-oxygen stress. At these two stations the dominant species A. tepida and Haynesina sp. Owing to the weak freshwater influence, the agglutinated species used for calculating the Ic in previous studies are extremely rare or are not found in the Gulf of Kalloni The distribution of the Ic reflects the decreasing marine influence north-eastwards; values are higher than 6.5 in the north-eastern part of the gulf (Figure 7), indicating more restricted conditions. The values of the Ic are also high in the two areas of high organic input, highlighting that organic matter accumulation can have the same impact on this index as decreasing marine influence does.
Figure 7. Gulf of Kalloni. Values indicated on this figure were measured in September 1993. The Ic values show increasing confinement with distance to the sea and the impact of both the fish farm and the town of Skala Polychnitos. The density of foraminiferal assemblages shows a decrease with increasing distance to the sea, mainly in the central part of the gulf. The species diversity is higher along the southeastern shore of the lagoon indicating the penetration of marine water along the shore during most of the year (after Debenay et al., 2005)
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4.6. Choked Hyposaline Lagoon Example: Lake Nokoué, Bénin, latitude ≈ 6°26‘ N, longitude ≈ 2°27‘ E (Debenay et al., 1993; Figures. 3 and 8)
Morphology This coastal lagoon extends over about 160 km2 (20 km long from west to east). It is closed by a sand spit, which is about 5 km wide, and is directly connected to the sea via a narrow channel through Cotonou. Another connection to the sea exists to the east of the lagoon, through a channel and the lagoons of Nigeria. The Cotonou channel can close during low-water periods. The south coast is sandy while the north coast, where the main tributaries flow into the lagoon, is marshy. The lagoon is shallow (<3 m) except near the entrance channel (9 m). Hydrodynamics The main water circulation pattern is a general clockwise, wind driven current around the lagoon, with several smaller circulation cells (Colleuil, 1984; Millet et al., 1991). Tidal currents are sensitive only during low water periods, and are mainly located near the entrance channel. Freshwater inputs are generally produced by rain and runoffs during the great rainy season (March - July) and by the main tributary, the Oueme River, during the small rainy season (September – November). When the Oueme River is in spate (September – December), almost the entire lagoon is filled with fresh water, with a salinity of about 0.2‰. At the beginning of the low water period, oceanic waters penetrate the lagoon through the Cotonou channel and are pushed westwards by the clockwise current, inducing a west-east zonation. Maximum salinity can then reach 33‰. Later, the entrance channel closes naturally, due to long-shore sediment input, and the salinity lowers, with a gradient from 10‰ (west) to 5‰ (east). No vertical water stratification was observed. Sediments The sediments are of terrigenous origin, and are typically organic rich muds, with some sand banks deposited by the wind driven currents. Foraminiferal Assemblages The foraminiferal assemblages collected in Lake Nokoué are poor and dominated by the euryhaline A. salsum. However, near the Cotonou channel, and under oceanic influence, they are more diversified, with A. parkinsoniana, A. tepida and E. gunteri present. The samples collected from the organic-rich-sediment in the estuaries of the tributaries contain A. mexicana and H. wilberti, while the brackish eastern area contains M. earlandi and M. fusca. The distribution of the confinement index, the Ic, fit well with the hydrological characteristics of the area (Figure 8). Values lower than 0.4 are limited to the vicinity of the Cotonou channel, highlighting the weakness of the marine influence. Both the westwards extension of the area, where the Ic is less than 0.7, and its north-eastern extension are the result of the combined effects of: i) freshwater input from the Ouémé River; and ii) the clockwise rotation of the water masses. The south-eastern extension of this area is probably due to the influence of the eastern channel.
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Figure 8. Lake Nokoué. The distribution of the confinement index Ic is related to the input of marine water through the entrance channel and to the circulation of these waters pushed by wind-forced currents assemblages (after Debenay et al., 1993)
4.7. Generalization Living at the bottom of areas of water, benthic foraminifera are subjected to all kinds of changes in the characteristics of water masses, ranging from the scale of the tidal to seasonal cycles. They therefore represent the average conditions prevailing at the site of sampling, which is of primary interest in these highly changing environments. The selected examples of coastal clastic lagoons reveal that the main distribution pattern of foraminiferal assemblages is primarily related to the balance between marine and continental influence, thus reflecting the various water masses. The sensitivity of foraminifera is such that they can indicate the influence of salt wedges, such as in the Cananéia-Iguape Lagoon. The impact of marine water has often been emphasized in the literature, and a good example is the Santo André coastal lagoon, where Cearreta et al. (2002) reported that the absolute abundance of foraminiferal assemblages greatly increases when the inlet periodically opens. Salinity certainly plays a prominent role in the impact of the balance between marine and continental water masses, as is attested to by the presence of foraminifera in inland saline lakes. The selected examples also reveal that the gradient of marine influence is not necessarily a direct function of the distance to the inlet, and that this primary distributional pattern may be complicated by secondary parameters, such as water stratification. Consequently, a simple horizontal mapping of foraminiferal assemblages has no significance in a stratified lagoon, such as the Lagoa da Conceiçao, and could lead to misinterpretations. In areas of almost stable salinity, the assemblages are controlled by secondary parameters, which are no longer obscured by the marine/continental balance. In the Araruama Lagoon, for example, local conditions, such as anthropogenic inputs, clearly affect the foraminiferal assemblages. Albani (1978) reported the same phenomenon in estuarine environments, where assemblages reflected the marine and fluvial water masses in areas of
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variable conditions, while in areas of more stable salinity the major parameters became water depth and tidal activity. In the study examples, no clear relationship could be established between foraminiferal assemblages and the nature of the sediment. However, such a link could be evidenced in Lake lllawarra, Australia (Yassini and Jones, 1989), and in the Bassin d'Arcachon, a restricted lagoon on the Atlantic coast of France, where Le Campion (1970) recognized a number of sub-environments with different foraminiferal assemblages related to the nature of the sediment. Generally, muddier sediments, usually accompanied by higher nutrient conditions, tend to contain a greater density of foraminifera than sandier sediments, as seen in the Gippsland Lakes, Australia (Apthorpe, 1980) and the Goro Lagoon, Italy (Coccioni, 2000). The agglutinated species collected in the selected lagoons are always related to low salinity and are always associated with low pH conditions. However, when considering these species and their significance for environmental conditions, it is necessary to make the distinction between organic-cemented species, which mainly live in low salinity and low pH conditions, and calcite-cemented species, which are abundant in fully marine reefal environments and coral reef lagoons. The species that lives in the less saline areas is M. fusca, and is always found near fluvial input sites. This species is often reported to be present in the same type of environments and also seems to prefer the quieter conditions prevailing in shallow, subtidal sheltered waters (Lewis, 2006). The great variety of lagoonal functioning illustrated by the selected examples reveals that it is impossible to establish a universal model for foraminiferal distribution in lagoons. However, these assemblages may be used as a key indicator in lagoonal environments, either for understanding the functioning of the lagoon, as was the case in Lagoa da Conceiçao (Debenay et al., 1998), or for exploring the favourable, average conditions for man‘s activity, such as aquaculture. For example, it was demonstrated in the Nokoue Lagoon that the distribution of the confinement index, the Ic, fits well with macrobenthic zonation (Debenay et al., 1993). The Ic index is also a powerful tool for comparing various lagoonal environments and other paralic habitats, typically estuaries. Moreover, the Ic also gives a helpful indication of organic matter input and serves as a useful tool for a quick characterization of the environment, including the detection of any anthropogenic impact.
5. USING FORAMINIFERA FOR ASSESSING WATER AND SEDIMENT QUALITY IN LAGOONS 5.1. Use of Foraminifera Coastal areas have traditionally been places of human settlement, with the accompanying development of cities, industries and other human-related activities possibly having an impact on aquatic ecosystems and modifying their health quality and local biota. Although humaninduced disturbances may take many forms, the most deleterious impact typically occurs in paralic environments, where the effects generally overlap with the stress conditions which tend to be induced by drastic changes in water characteristics. At present, there is clearly an increasing need to monitor the ecosystem response to different types of disturbance. Despite the complex interplay of natural vs. anthropogenic induced stress, biological organisms like
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foraminifera can be used to provide an early warning of the presence or absence of pollution (biological monitoring). Like the biotic indices that have already been developed for macrofaunal organisms, foraminiferal monitoring procedures are also beginning to be formalized, and considerable effort has been made to develop new methodologies for the biological monitoring of different contaminants. Moreover, because of our increased knowledge of the biology of foraminifera, it is clear that benthic foraminifera have great potential as indicators of stress, thereby providing one of the most sensitive and inexpensive markers of environmental strain in both naturally and anthropogenically stressed locations (Murray and Alve, 2002). Benthic foraminifera generally respond to adverse ecological conditions, mainly by undergoing: i) local extinctions; ii) compositional biocenosis changes; iii) assemblage modifications, which include changes in abundance and diversity; iv) dwarfism (Lilliput effect); v) prolocular morphology; vi) reproduction capability; and vii) the development of test abnormalities (e.g. Alve 1991, 1995; Yanko et al., 1994; Geslin, 1999; Frontalini et al., 2009). Over the last few years, many studies of benthic foraminiferal assemblages have been carried out in different parts of the world in areas exposed to different kinds of marine pollution, which has generally included a) increased organic matter, b) hydrocarbons-oil and c) trace elements.
5.2. The Effect of Organic Matter on Benthic Foraminifera The input of organic matter has deleterious effects on marine ecosystems and their benthic community by inducing high nutrient levels which can ultimately lead to oxygen deficiency. The influence of organic material on the benthic community is not only controlled by its quantity, but also by its quality. Although organic matter is composed of a wide range of compounds, it can be divided into two main groups. The first includes the material that is more easily biodegradable and ―naturally‖ produced. This encompasses organic compounds from agriculture (e.g. fertilizers) and aquaculture, as well as domestic sewage, which is readily metabolized by marine organisms. In contrast, the effluents of pulp/paper mills, which are composed primarily of cellulose, lignin and other wood fibers, are rather resistant and difficult to metabolize. According to Alve (1995), the increase in organic matter from both sources in the socalled defined ―hyper-trophic‖ zone may stimulate the growth of large populations of benthic foraminifera. However, an excess of organic material may negatively influence the benthic community. In fact, most studies have revealed that around areas of organic matter supply (e.g. outfall and pipe), an abiotic zone might occur in response to the development of anoxic conditions. Changes in density are not the only response by benthic foraminifera to organic matter, with a lowering in species diversification also being documented in the vicinity of many outfalls (e.g. Resig, 1960; Schafer, 1973). Although the Index of confinement (Ic) is used to define a marine-to-confined water gradient, it can be also utilized to unravel the influence of freshwater discharges and detect anthropogenic impact (Debenay et al., 1998, 2005). This is the case in the Cananéia-Iguape Lagoon, which exhibits salinity gradients due to the mixing of freshwater input from local
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rivers with marine waters, and where anomalous values of the Ic and the dominance of Miliammina spp., in correspondence with freshwater input, have been documented by Debenay et al. (1998). Although the environmental quality of the Gulf of Kalloni has been reported as good, higher organic matter contents have been noted in the vicinity of a fish farm and in correspondence to the town of Skala Polychnitos (Figure 7). This is due to local pollution sources, which include urban effluents and agricultural land runoffs (Panayotidis et al., 1999). The enhanced organic matter input appears to be responsible for a lowering in density and species diversity as well as a higher Ic index and abundances of A. tepida and Haynesina sp. (Debenay et al., 2005). In the hypersaline Lagoon of Araruama, the strong contrast of foraminiferal assemblage distributions between the north-eastern part of the lagoon, which is dominated by A. tepida, and the southern part, where T. oblonga dominates (Figure 6), has been related to organic-rich wastewater input along the north-eastern coast of the lagoon (Debenay et al., 2001). Ammonia tepida has usually been found in shallow marine environments, lagoons and deltaic zones (Jorissen, 1988; Almogi-Labin et al., 1992; Coccioni, 2000; Abu-Zied et al., 2007; Frontalini et al., 2009), and is known for its great tolerance to chemical and thermal pollution, fertilizing products, and hydrocarbons (e.g. Yanko and Flexer, 1991; Coccioni, 2000). It was even capable of supporting very polluted environments and high concentrations of trace elements (e.g. Ferraro et al., 2006). Yanko et al. (1994) found that megalospheric forms of A. tepida were dominant at stations where toxic trace metal pollution was prevalent. Similarly, H. germanica has been regarded by Stubbles (1993) and Armynot du Châtelet et al. (2004) as a species that is tolerant to pollution, and its increasing dominance is an indicator of stressed environmental conditions. Enrichments of organic matters have also been considered to be responsible for increasing the proportions of abnormal tests (FAI). In particular, in shrimp ponds in New Caledonia, Debenay et al. (2009a) documented a strongly positive correlation between the FAI and (1) the quantity of easily oxidized material (EOM) deposited at the bottom of the ponds, and (2) the sediment oxygen demand. This is corroborated by the poorly diversified assemblages that are mainly dominated by A. tepida and Q. seminula, indicating very restricted conditions and major environmental stress. It has also been suggested that a very high FAI could be a potential indicator of great accumulations of native organic matter, leading to a high sediment oxygen demand. In their multi-proxy study on intertidal estuaries in New Zealand, Hayward et al. (2004, 2006) found that stepwise shifts in dominance from calcareous to agglutinated forms, which are usually related to increasing continental influence, were also associated with the arrival and establishment in the area of humans. These major faunal changes probably resulted from the increased freshwater runoffs associated with forest clearance and an increase of nutrient inputs. Clear foraminiferal faunal zones have been documented by Takata et al. (2006) in the organic-rich brackish-water Lagoon of Saroma (Japan). This faunal distribution appears to be controlled by the dissolved oxygen content of the bottom water and a combination of organic enrichment and mud content in the substrate in front of river mouths. In particular, these authors reported a river-mouth fauna dominated by Elphidium excavatum, which is probably adapted to organic-rich sediment. Previous studies have reported the presence of E. excavatum in highly organic substrates; Schafer (1973) noted that the Elphidium incertum/Elphidium clavatum Group (probably related to E. excavatum) was particularly abundant around sewage outfalls in Chaleur Bay, Canada, while Alve and Murray (1999) inferred that E. excavatum can live in substrates characterized by highly variable grain size
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and TOC content. Major changes in foraminiferal assemblages over both time and space have also been reported in the Osaka Bay (which can be regarded as a restricted lagoon) by Tsujimoto et al. (2006a, b). Using living foraminiferal assemblages, these researchers documented an inner area of the bay which was mainly related to eutrophication and dominated by agglutinated forms (Trochammina hadai and Eggerella advena). Moreover, they also highlighted marked foraminiferal assemblages present over the past 50 years, where the dominance of agglutinants, which was linked to the increase of eutrophication from the 1960s to the 1970s, was followed by a decrease of these forms in response to the imposition of improved environmental regulations. A similar approach has been used in the northern sector of the Lagoon of Venice by Albani et al. (2007), who compared foraminiferal assemblages from samples collected in 1983 and 2001, thus documenting unchanged conditions for 50% of the lagoon. On the basis of these results, these authors have been able to document both the effectiveness of the purification plant, which has been operating since 1980s, and improvements in the water quality in the area near Porto Marghera.
5.3. The Effect of Hydrocarbon-Oil on Benthic Foraminifera The effect of hydrocarbons on benthic foraminiferal assemblages in field and experimental studies has been the subject of only a few papers (e.g. Vénec-Peyre, 1981; Yanko et al., 1994; Alve, 1995; Bernhard et al., 2001; Morvan et al., 2004; Ernst et al., 2006; Sabean et al., 2009). Increased mortality and abnormality and decreased density and diversity are among the effects on benthic foraminiferal assemblages induced by hydrocarbon pollution. In particular, and in order to address the response of benthic foraminifera to pollution as a result of the ―Erika‖ oil spill, Morvan et al. (2004) evaluated a site situated on the tidal mudflat along the southern Bay of Bourgneuf (France) at monthly/bimonthly intervals. Although a clear link between FAI and oil pollution was not found, impoverished fauna in terms of density and species richness was highlighted, confirming the potential sensitivity of foraminifera to this pollutant, and suggesting a direct impact either by the oil spill itself or by the strong disturbance of the environment resulting from cleaning activities.
5.4. The Effect of Trace Elements on Benthic Foraminifera Although most trace elements are biologically essential at very low concentrations, they become potentially toxic to marine and estuarine organisms above a specific threshold (Kennish, 1992). Over the last four decades, many studies from different environmental settings have focused on the response of benthic foraminifera to pollution by trace elements (Alve, 1991, 1995; Sharifi et al., 1991; Yanko et al., 1994 1998, 1999; Coccioni, 2000; Geslin et al., 2000, 2002; Samir, 2000; Samir and El-Din, 2001; Elberling et al., 2003; Armynot du Châtelet et al., 2004; Coccioni et al., 2003, 2005, 2009; Coccioni and Marsili, 2005; Ferraro et al., 2006; Frontalini and Coccioni, 2008; Frontalini et al., 2009, 2010). Most of these studies documented a lowering in species diversity and density, and a high incidence of abnormality, megalospheric and dwarfed forms, and changes in assemblage composition.
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The benthic foraminiferal response to trace element pollution was investigated by Samir (2000) in two Egyptian Nile Delta lagoons (Manzalah and Edku). The high level of pollution reported in the Manzalah was believed to be lethal to foraminifera and, indeed, only one species of Ostracoda (Cyprideis torosa) was found to be able to survive in this environment. On the other hand, the Edku Lagoon, which had trace element concentrations close to the natural baseline level, yielded living foraminifera. On the basis of total assemblages, the Manzalah Lagoon exhibited lower foraminiferal diversification and higher percentages of both megalospheric forms of A. tepida and abnormality. A similar response, in terms of very impoverished foraminiferal assemblages, has been documented in different Italian lagoons (e.g. Santa Gilla, Venice, Orbetello and Lesina) by Frontalini et al. (2009, 2010) and Coccioni et al. (2009). In particular, reduced foraminiferal diversification and high percentages of abnormal forms have been reported close to the most polluted industrial zone of Porto Marghera (Coccioni et al., 2009). The same authors reported a biocenosis (living assemblages) dominated by A. tepida, H. germanica and E. oceanensis. These assemblages are comparable to the Ammonia associations with H. germanica that are characteristic of lagoons along the Mediterranean coast (see Murray, 1991, 2006). High concentrations of trace elements (e.g. Hg values up to 10 times higher than the background level) were found in the Santa Gilla lagoon, the innermost part of which is comprised of the industrial complex at Macchiareddu. Indeed, the trace element concentration values were generally higher than the USEPA ER–L and ER-M levels (Frontalini et al., 2009). The same authors documented an oligotipic assemblage and the occurrence of abnormalities, particularly in the innermost part of the lagoon, testifying to an important chemical stress in this area. In contrast, higher diversity values and lower percentages of abnormalities were recognized in the outermost part, which is probably favoured by faster water renewal and the reduced influence of urban discharge. This reflects a limited influence of trace element concentrations in the sediment. On the basis of trace element analysis of the biogenic carbonate of porcelanaceous foraminifera, Frontalini et al. (2009) also found higher concentrations than those reported in unpolluted environments. The same results were achieved by Madkour and Youssef Ali (2008), who found high concentrations of Fe and Mn in benthic foraminiferal tests from several Egyptian Red Sea lagoons (e.g. Umm al-Huwayat).
7. CONCLUSION Lagoons, like other transitional marine environments, are areas where biological, chemical, and physical processes overlap over both time and space. Our understanding of them might be improved by knowledge of the behaviour of the organisms evolving and living in these complex systems. Benthic foraminifera are highly suitable and sensitive biological organisms through which our comprehension of lagoon environments can be further explored. Since the early 1900s, plenty of studies have documented the ability of benthic foraminifera to synthetically reflect a great variety of complex processes. Despite of the general conditions are complicated by a complex interplay of an array of parameters in lagoon environments, this work highlights that foraminiferal assemblages are distributed along major gradients (i.e., salinity). Benthic foraminifera have been also proven to be particularly sensitive
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microrganisms and they have been successfully utilized for their value as bio-indicators of environmental change in a wide range of marine environments including lagoon ecosystems. In this context, the ―Confinement Index‖ gives a helpful indication of organic matter input and serves as a useful tool for a quick characterization of the environment, including the detection of any anthropogenic impact. Although the separation of natural and anthropogenically-induced stress is sometimes hampered by environmental complexity, benthic foraminifera are ideal and reliable candidate for environmental monitoring program and management of lagoonal ecosystems.
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In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 73-117 © 2011 Nova Science Publishers, Inc.
Chapter 3
COASTWEB, A FOODWEB MODEL BASED ON FUNCTIONAL GROUPS FOR COASTAL AREAS INCLUDING A MASS-BALANCE MODEL FOR PHOSPHORUS Lars Håkanson* and Dan Lindgren Department of Earth Sciences, Uppsala University, Uppsala, Sweden
ABSTRACT It is important to develop tools to get realistic predictions of how, e.g., the loading of contaminants and future climate changes may affect the structure and function of aquatic ecosystems. The CoastWeb-model presented in this work in meant as such a tool. CoastWeb is a process-based mechanistic foodweb model for coastal areas (the ecosystem scale) and includes a mass-balance model (CoastMab) for phosphorus. The model is based on ordinary differential equations and gives monthly calculations of production and biomasses for ten functional groups (phytoplankton, benthic algae, macrophytes, bacterioplankton, herbivorous and predatory zooplankton, zoobenthos, jellyfish, prey and predatory fish). CoastMab calculates in- and outflow, sedimentation, diffusion, resuspension, up- and downward mixing, biouptake and retention of phosphorus in biota. There are algorithms for, e.g., migration of fish and plankton between the given coastal area and the sea and the influence of exposure on macrophyte cover . The paper presents case-studies on eutrophication, overfishing and toxic contamination illustrating the potential of CoastWeb as a tool for sustainable coastal management. Increased nutrient loading will cause several changes to the foodweb characteristics of the studied coastal area. Some of these could be expected without a model, but here they have been quantified using a general foodweb model. The model accounts for different compensatory effects that are difficult to quantify without a model. The case-study on overfishing indicates that increased fishing will likely affect the studied coastal system marginally because the migration of fish from the sea is large in the studied coastal area. The case-study on toxic contamination shows that a reduction of *
Corresponding author: Email: [email protected]., tel: +46 184713897; fax: +46 184712737.
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Lars Håkanson and Dan Lindgren zoobenthos biomass will have clear effects of fish production and biomass in the studied coastal area.
Keywords: coastal areas, eutrophication, foodweb modelling, functional groups, massbalance modelling, overfishing, phosphorus, toxic contamination, climate change
INTRODUCTION At any modelling scale, the complexity of natural ecosystems always exceeds the complexity and size of any model, so simplifications are always needed. The ultimate goal in achieving predictive power and general validity for a model is to find the most appropriate simplifications (Monte, 1995, 1996; Monte et al., 1999; Peters, 1991). Different models for biota focus on different targets and scales. Fundamentally different approaches may be used in, e.g., physiological models, models for individual species and models for functional groups, approaches using different time scales (hours to years), different spatial scales (from sites to ecosystems), different driving variables (climatological data or map parameters) and approaches using statistical methods or models based on ordinary differential equations (box models) or partial differential equations (2- or 3-dimensional models), see Monte (1996), Mace (2001). The CoastWeb-model presented in this work is meant as a tool for coastal sciences and management to study how changes in nutrient inflow, fishing, water temperature and contamination by toxins could influence the structure and function of coastal ecosystems. CoastWeb is basically a combination of a foodweb model for lakes (LakeWeb, Håkanson and Boulion, 2002), a process-based dynamic mass-balance model for phosphorus (CoastMab, Håkanson and Eklund, 2007) and several adjustments needed to bring these two models together into a comprehensive unit. An important feature of this model, and a pre-requisite for its practical use, is that it can be run by a few driving variables readily accessible from standard maps and monitoring programs. CoastWeb is based on ordinary differential equations, works at the ecosystem scale and gives monthly predictions, but it does not address the finer details related to individual species or changes among sites within coastal systems. LakeWeb, has been positively tested against comprehensive empirical data for lakes and by sensitivity and uncertainty analyses (Håkanson and Boulion, 2002). LakeWeb was used for the Baltic Sea as a tool to set fish quotas (Håkanson and Gyllenhammar, 2005) by calculating the fish production potential and how it depends on environmental conditions (salinity, temperature and phosphorus loading) as well as on fishing and overfishing. Håkanson and Gyllenhammar (2005) compared LakeWeb with other models, e.g., Ecopath/Ecosim (Christensen et al., 2000; Walters et al., 1997, 2000; Sandberg et al., 2000; Harvey et al., 2003) and that comparison will not be repeated here. However, it should be stressed that CoastWeb provides a new dimension to understand and simulate the factors regulating aquatic ecosystem structure, including the fish production. Ecopath/Ecosim and CoastWeb/LakeWeb are complementary and both can calculate production and biomasses, but CoastWeb/LakeWeb has a separate sub-model to calculate inflow, outflow and internal processes (sedimentation, resuspension, etc.) of nutrients so that the nutrient concentration can be related to the nutrient loading and used to
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calculate chlorophyll (phytoplankton biomass). Ecopath/Ecosim is designed to handle more detailed foodweb interactions than CoastWeb/LakeWeb. Most of the algorithms used in the mass-balance model for phosphorus (CoastMab) have been critically tested and shown to predict well, but only for coastal areas within a fairly limited salinity range. It would be very interesting to test CoastWeb/CoastMab for more saline systems, e.g., in the Mediterranean, along the Atlantic coast or in the Black Sea. The case-studies presented here merely illustrate the potential use of this modelling related to eutrophication, toxic contamination and overfishing – each case-study could easily grow into a large book. So, this paper is ―not the end, nor the beginning of the end, but rather the end of the beginning‖.
Figure 1. Illustration of the steps to define the boundary lines of a coastal area (step 1) at the topographical bottlenecks defined by the ratio between the section area (At) and the enclosed coastal area (A) where the exposure (Ex) attains a minimum value. Once the boundary lines for the coastal area are defined, steps 2 and 3 illustrate how to calculate important coastal parameters (such as morphometric size, form and special parameters, the theoretical surface and deep water retention times and where areas of fine sediment accumulation prevails)
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Lars Håkanson and Dan Lindgren The text has been divided into the following parts: First, the basic structure of the foodweb model is described, including the approach to define the geographical boundary conditions for coastal areas, the approach to define ―normal‖ biomasses for the functional groups, migration into and out from coastal areas and an outline of the new sub-model for jellyfish. Then, there is a section related to the different roles of macrophytes in coastal systems and how these roles and functions can be modelled using CoastWeb. The third main part gives results related to the three case-studies and how CoastWeb may be used as a tool to analyse how very complicated and important environmental problems may be handled in a structured and quantitative manner. The appendix gives a list of minor modifications done to transform the lake model into a model for coastal areas.
METHODS – THE MODELLING APPROACH Coastal Ecosystem Boundaries It is easy to define what a lake is or a stretch of river. It is more difficult to draw the borderlines toward the sea and/or adjacent coast to define a given coastal area. The positions of such borders are essential for mass-balance calculations since arbitrary borderlines generate arbitrary volumes, which reduce the predictive power of the mass-balance model (Håkanson, 1999). CoastWeb requires that the coastal area is defined according to the topographical bottleneck approach (Figure 1). The boundaries should be drawn at the topographical bottlenecks using Geographical Information Systems (GIS) techniques so that the exposure (Ex = 100·At/A) attains a minimum value when different alternatives for defining the boundary lines are tested (At = section area; A = enclosed coastal area; Pilesjö et al., 1991). Once the coastal area is defined, other key variables for mass-balance calculations may also be defined, such as the water volume. This method also makes it possible to use simple models to estimate the theoretical surface-water retention time (Persson et al., 1994), the deep-water exchange (Håkanson and Karlsson, 2004) and the bottom dynamic conditions (Håkanson, 2006) from morphometrical parameters. Such simple models are important since establishing an empirical value of the theoretical water retention time from field measurements can be costly. CoastWeb may be used for the main coast types, tidal coasts, open coasts, archipelago coasts and bays (Håkanson, 2000).
The Foodweb Model The main aim of the LakeWeb-model is to quantitatively describe characteristic foodweb interactions so that production, biomasses and predation can be determined for the functional groups in the model: the three primary producers, phytoplankton, benthic algae and macrophytes, the five secondary producers, herbivorous zooplankton, predatory zooplankton, zoobenthos, prey fish and predatory fish, and one decomposer, bacterioplankton. Jellyfish is
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added as a functional group to adapt the model to coastal conditions. The group ―predatory fish‖ does the work of eating ―prey fish‖, which in turn eats zooplankton (herbivorous and predatory) and zoobenthos. Other organisms, like benthic bacteria and fungi are not treated individually but are included in the flux called ―zoobenthos production from other sediment sources‖. Such simplifications are necessary to keep the model as small as possible, to keep the driving variables as few and as accessible as possible and to be able to critically test the model using empirical data. The idea is not to include everything, but to focus on key functional groups and fundamental abiotic/biotic relationships (see Figure 2 for an overview of the LakeWeb model). CoastWeb is meant to cover a wide range in temperature, water basin morphometry, trophic state and salinity. Since the model can be run from few and readily accessible driving variables (see Table 1), it is evident that the aim is to model general conditions. This modelling is intended to handle feedbacks among the functional groups, but biotic/abiotic feedbacks also are included. Table 1. Data needed to run the CoastWeb-model for the studied coastal areas (data from Wallin et al., 1992 and Håkanson et al., 2007). The water exchange between Ringkobing Fjord and the sea is regulated by a sluice Area
Country
Lati- Water CatchDmax Dm At Chl SalCaCTP Sec tude area ment area inity conc. # (°N) (km2) (km2) (m) (m) (km2) (µg/l) (mg/l) (µg/l) (m) Ringkobing Denmark 56 300 3 500 5.1 1.9 sluice 52/9,1* 7.8/9.6 30 130/56 0.6/1.6 Ronneby S. Swed. 56 11.0 633 17.6 4.3 0.0176 2.1 6.5 25 21 4 Gräsmarö C. Swed. 58 13.8 0 46.9 14 0.0825 2.6 6.6 15 17 4.3 Haverö Finland 61 2.3 0 22.5 8.6 0.0172 2.1 6.5 15 27 3.4 Gävle N. Swed. 61 17.1 2 600 17.0 8.4 0.0063 3.5 4.2 9 23 3.6
Dmax = maximum depth; Dm = mean depth; At = section area; Chl = concentration of chlorophyll-a; CTP = TP-concentration; Sec = Secchi depth; *) mean values from all existing data 1990/93 and 2000/2003, respectively; #) estimated values Predatory fish
Secondary producers
Prey fish
Jellyfish Predatory zooplankton
Zoobenthos Herbivorous zooplankton Sediments Benthic algae Macrophytes
Primary producers
Phytoplankton
Bacterioplankton
Decomposer Figure 2. Illustration of a coastal foodweb including ten groups of organisms (phytoplankton, bacterioplankton, benthic algae, macrophytes, herbivorous zooplankton, predatory zooplankton, jellyfish, zoobenthos, prey fish and predatory fish)
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Figure 3. Illustration of general and fundamental transport processes to, within and from coastal systems used in the mass-balance model for phosphorus in the CoastWeb-model. ―ET-sediments‖ in the figure refer to erosion and transportation areas where fine sediments and particulate forms of nutrients are resuspended. ―Active A-sediments‖ are biologically active sediment areas where fine sediments are continuously being deposited (accumulation areas)
Mass-balance modelling of nutrients is important in aquatic ecology (Vollenweider, 1968; OECD, 1982) and by including a mass-balance model for nutrients in the foodweb model, it is possible to calculate the uptake and retention of phosphorus in biota. Basically, CoastWeb consists of two parts: the foodweb model, which is driven by chlorophyll and calculates production (kg ww/month) and biomass (kg ww) of the functional groups, and the mass-balance model for phosphorus (CoastMab; Håkanson and Eklund, 2007) based on transport processes that appear in most systems (Figure 3) and apply to most substances (nutrients, suspended particulate matter (= SPM), radionuclides, etc.). Key concepts in this modelling are (Table 2): (1) Consumption rates - ―how large a fraction of the prey biomass is consumed per time unit by the predator?‖ (2) Metabolic efficiency ratios for each compartment - ―how much of the food consumed will increase the biomass of the consumer?‖ (3) Turnover or retention rates for each compartment - ―how long is the mean, characteristic lifespan of the group?‖ (4) Food choices - ―if there is a food choice, how much is consumed of each food type?‖ (5) Migration rates - ―how large a fraction of the group will leave and enter the system per unit of time?‖ These concepts will be described briefly below for jellyfish. Håkanson and Boulion (2002) give more information on the different concepts. This modelling uses a simple general system to assign weights to food choices and adjust the consumption to the number of food choices. Figure 4 gives an overview of the food choice panel. If there are more than two food choices, they are first differentiated by a distribution coefficient (DC1) that separates between the primary and the other food types. A second distribution coefficient (DC2) separates the second most popular food type from the rest, etc.
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Table 2. Metabolic efficiency ratios for key functional groups (MER = PR/CON, dimensionless). The MER-value is calculated from the mass-balance equation, CON = PR + RES + FAE, where CON = consumption, PR = production, RES = respiration, FAE = unassimilated food (faeces), all dimensionless, and T = turnover time (= BM/PR, days; BM = biomass). The actual consumption rate constant, CR, expresses reduction of prey organism biomass per unit of time. The jellyfish values on PR, RES and FAE are from Schneider (1989) while the corresponding values for the other functional groups mainly are from Winberg (1985) and Håkanson and Boulion (2002) Zooherb
CON 100
PR 24
RES 36
FAE 40
MER 0.24
T 6.0
CR 0.17
Zoopred
100
32
48
20
0.32
11.0
0.091
Zoobenthos
100
15
35
50
0.15
65
0.015
Prey fish
100
16
64
20
0.16
300
0.016
Predatory fish Jellyfish
100
25
55
20
0.25
450
100
22
56
20
0.22
120
0.00130.02 0.008
Consumes Phytopl., Bacteriopl.Zoo pred, Zooherb Macrophytes, Benthic algae Zoobent., Zooherb, Zoopred Prey fish Zoopred, Zooherb
DC = 1
Zoobenthos DC = 0.5 Benthic plants DC = DC = 0.25 0.75 Benthic Macroalgae phytes
Secchi depth and morphometry
DC = 0.5 Organic sediments
Prey fish
DC = 0.5·Ysec Zooplankton
DC = 0.75 Pred. zooplankton
DC = 0.25 Herb. zooplankton
DC = 0.5 Phytoplankton
Phosphorus
Jellyfish
DC = 0.5
DC = 0.5
DC = 0.5 Bacterioplankton
SPM
Figure 4. Food choice panel for the default set-up used for the CoastWeb-model
Table 3. Gives a compilation of abbreviations used in this modelling.
Prey fish, Jellyfish Prey fish Pred. fish Pred. fish None
Predatory fish
DC = 1-0.5·Ysec
Consumed by Prey fish, Jellyfish
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Table 3. Abbreviations and dimensions of the most commonly used concepts and variables in this modelling. Note that we have tried to use as simple and self-explanatory abbreviations as possible. Greek letters have been banned A. Organisms BA = Benthic algae BE = Zoobenthos BP = Bacterioplankton JE = Jellyfish MA = Macrophytes PD = Predatory fish PH = Phytoplankton PY = Prey fish ZH = Zooplankton, herbivours ZP = Zooplankton, predators B. Driving variables Area = Coastal area (m2) Dm = Mean depth (m) Dmax = Maximum depth (m) SWT = Surface-water temperature (°C) TP = Total phosphorus (μg/l) C. Foodweb interactions BM = Biomass (kg ww), e.g., BMBP CON = Consumption (kg ww/week), e.g., CONPHZH (of PH eaten by ZH) CR = Actual consumption rate (1/week), e.g., CRZPPY (ZP eaten by PY) EL = Elimination (kg ww/week), e.g., ELZP IPR = Initial production (kg ww/week), e.g., IPRZHZP (ZH eaten by ZP) NBM = Normal biomass (kg ww), e.g., NBMBE NCR = Normal consumption rate (1/week), e.g., NCRPY MER = Metabolic efficiency ratio (dim. less), e.g., MERPYPD (PY eaten by PD) NR = Number of first order food choices (dim. less), e.g., NRZH PR = Production (kg ww/week), e.g., PRPD (PR defined by the ratio BM/T) T = Turnover time (weeks), e.g., TPH D. Mass-balance for phosphorus (= CoastMab) ASec = Area above Secchi depth (m2) BL = Biota with long turnover times BS = Biota with short turnover times C = Concentration, e.g., of phosphorus CTP (μg/l) DF = Dissolved fraction of phosphorus (dim. less) DP = Dissolved phosphorus (μg/l) DR = Dynamic ratio (dim. less) ET = Areas of fine sediment erosion and transport (dim. less) F = Flux of phosphorus (g/week), e.g., FETA (from ET to A) M = Mass of phosphorus (g), e.g., MET PF = Particulate fraction of phosphorus (dim. less) R = Rate (1/week) SW = Surface water Vd = Volume development (= form factor, dim. less)
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Table 3. (Continued) Y = Dimensionless moderator E. Other abbreviations Chl = Chlorophyll-a concentration (μg/l) dw = Dry weight IG = Sediment organic content (= loss on ignition, % dw) PrimP = Primary phytoplankton production Prec = Mean annual precipitation (mm/yr) SPM = Suspended particulate matter (mg/l) Sec = Secchi depth (m) W = Sediment water content (% ww) ww = Wet weight
Table 4. Many biological variables, whose determination normally require extensive and expensive field and laboratory work, may be estimated from lake TP (in µg/l = mg/m3). From Håkanson and Peters (1995) and Håkanson and Boulion (2002). PrimP = primary production (in g ww / m2 yr), Maccov = Macrophyte cover of lake bed (in % lake area), SecMV = mean annual Secchi depth (in m), Dm = mean lake depth (in m), Col = lake colour (mg Pt/l), DC = distribution coefficient (dimensionless), n = number of lakes used in the regression, ww = wet weight and dw = dry weight y-value
Equation
Equations based on phosphorus used as norms in LakeWeb: Chlorophyll =0.28·TP0.96 (summer mean) Chlorophyll =0.64·TP1.05 (summer max.) Max. prim. prod. =20·TP-71 (TP>10) Max. prim. prod. =0.85·TP1.4 (TP<10) Mean prim. prod. =10·TP-79 (TP>10) Mean prim. prod. =0.85·TP1.4 (TP<10) Phytoplankton =30·TP1.4 Bacterioplankton =0.90·TP0.66 Zooplankton, =0.77·38·TP0.64 herbivores Zooplankton, =0.23·38·TP0.64(the distr. coeff. is predators 0.77) Zoobenthos =810·TP0.71 Fish =590·TP0.71 Fish yield =7.1·TP Other equations used as norms in LakeWeb: Bacterioplankton =10(0.973·(0.27·log(Chl)+0.19)-0.438)
r2
n
Units
2.5-100
0.77
77
mg ww/m3
2.5-100
0.81
50
mg ww/m3
7-200
0.95
38
mg C/m3·d
Range for x
mg C/m3·d 7-200
0.94
38
m C/m3·d
0.88 0.83 0.86
27 12 12
mg ww/m3 mill./ml mg ww/m3
mg C/m3·d 3-80 3-100 3-80
mg ww/m3 3-100 10-550 8-550
0.48 0.75 0.87
38 18 21
mg ww/m2 mg ww/m2 mg ww/m2·yr mg ww/m3
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Equation =0.0023·PrimP0.9
Range for x 170-14 000
r2
n
Units
0.64
66
mg ww/m2·yr mg ww/m2 mg ww/m2 %
Prey fish =DC·fish biomass (default DC=0.73) Predatory fish =(1-DC)·fish biomass Macrophyte = 0.50·( SecMV/Dm) 229 cover Macrophytes =1.37·log(Maccov)+3.58 g ww/m2·yr 0.86 Zooplankton, =0.15·(PrimP·1000) 13-15 000 0.61 42 g ww/m2·yr herbivores Zooplankton, =0.076·(PrimP·1000)0.84 2-3 000 0.43 42 g ww/m2·yr predators Examples of local, regional and general relationships that may be used in the CoastWeb-model to predict chlorophyll-a concentrations from TP Local (for Chl = Ringkobing SMTH(((SWT+0.1)/9),12,60)·10^(Fjord): 1.86+1.72·log(CTP)) Regional (Baltic Chl = ((SWT+0.1)/20)·10^(coastal areas): 1.59+1.56·log(CTP)) General: Chl = (1/YCa)·YDRchl·Ytemp·Ysal·(0.28·CTP·0.56 /PF)0.96
Predictions of Normal Biomasses In LakeWeb and CoastWeb ―normal‖ (= norms = characteristic) biomasses of all functional groups are needed for calculations of consumption and migration. All normal biomasses and production values for the functional groups should ideally be calculated from empirical regressions yielding a high coefficient of determination (r2). Such general regressions are not, to the best of our knowledge, available for coastal areas, but many such empirical regressions are available for lakes (see Table 4). This is a major problem, not just to obtain good predictive power using CoastWeb, but also more generally in coastal ecology, to know what the ―normal‖ conditions are, given a set of standard abiotic regulating variables, such as TP-concentration for lakes. For coastal areas, the salinity is important for the Secchi depth (see Håkanson, 2006) and also for the relationship between chlorophyll and nutrient concentrations (Figure 5). Since there are no empirical relationships available for coastal areas that predict normal biomasses (norms), and since normal biomasses are essential in this modelling, the approach here is to modify and adjust the normal biomasses used in the LakeWeb-model and given in Table 4. Salinity influences the relationship between Chl and TP – the higher the salinity the lower chlorophyll relative to TP (Figure 5). If the primary production becomes lower at higher salinities, so will the secondary production. Hence, the first step in the approach to estimate coastal norms is to calculate a correction factor (Ychl) that describes the difference between chlorophyll in lakes (Chllake) and in coastal areas (Chlcoast) at the same TP, eq. 1.
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50 45
Chlorophyll-a concentration (µg/l)
40 35 30 25
1. Lakes, mean summer values; salinity = 0 2. Brackish coastal areas, salinities 2- 20; mean salinity - 11 3. Marine coastal areas, mean salinity - 23.5 4. Marine sites, mean salinity - 36 Chl=(1/YCa)·YDRchl·Ytemp·Ysal·(0.28·TP·0.56/PF)^0.96 If Ca-conc. < 10 mg/l then YCa =1 else YCa = (1+0.23·(Ca/10-1)) If DR > 2.45 then YDRchl=1 else YDRchl=DR/2.45 Ytemp = ((SWT+0.1)/20); SWT = surface-water temperature; °C Ysal = (1-0.75·Sal/36); Sal = salinity PF = the particulate fraction of P (calculated in the CoastWeb-model)
20
1
2
15
3 10
4
5 0 0
10
20
30
40
50
60
TP-concentration (µg/l)
70
80
90
100
Figure 5. The relationship between median total phosphorus concentrations (TP) in surface water and median concentrations of chlorophyll-a from the summer period (months 6, 7 and 8) for lakes, brackish water systems, marine coastal areas and open marine sites covering a salinity range from 0 to 36. DR is the dynamic ratio = √Area/Dm (Area = coastal area in km2; Dm = mean depth in m) (modified from Håkanson et al., 2005)
Ychl = Chlcoast/Chllake
(1)
Chlcoast may be calculated from a regression between TP and Chl as explained in Figure 5; Chllake is derived from Table 4. Hence, Ychl is 1 for lakes and less than 1 for coastal areas that have lower Chl-values than lakes at the same TP. To get the norms for the different functional groups, the corresponding norms in LakeWeb (Table 4) are multiplied with this correction factor. The normal biomasses for herbivorous zooplankton (NBMZH), predatory zooplankton (NBMZP), prey fish (NBMPY) and predatory fish (NBMPD) are calculated as: NBMZH = Ychl·(DCZHZP)·10-6·Vol·38·CTP0.64
(2)
DCZHZP is set to 0.77 as a default value (Håkanson and Boulion, 2002); Vol is the coastal volume (m3). NBMZP = Ychl·(1-DCZHZP)·10-6·Vol·38·CTP0.64 The normal biomass for fish (prey plus predatory fish) is given by:
(3)
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(4)
NBMPY = (DCPYPD)·SMTH(NBMfish,TPY,NBMfish)
(5)
NBMPD = (1-DCPYPD)·SMTH(NBMfish,TPD,NBMfish)
(6)
TPY and TPD are the turnover times for prey and predatory fish. The smoothing function (SMTH; see Håkanson, 1999, for more information on smoothing function) is used to adjust the temporal variability in TP to the turnover time of prey fish. The distribution coefficient regulating the fraction of prey fish is given by eq. 7. The more eutrophic the system, the higher the fraction of prey fish. This means that in relatively low-productive systems with TP = CTP = 15 µg/l, DCPYPD = (15/(15+22))0.4 = 0.70; and 70% of the fish biomass would be prey fish. DCPYPD = (CTP/(CTP +22))0.4
(7)
In LakeWeb, the normal biomass of zoobenthos (NBMZB) is calculated from Table 4 as 810·(CTP0.71). In CoastWeb, this has been modified to take into account that the biomass of zoobenthos primarily should depend on the sedimentation of organic matter and the bottom area above the Secchi depth, which regulate the production of benthic algae and macrophytes. The approach to predict NBMZB in CoastWeb is: If CTP < 100 µg/l then NBMZB = YChlZB·10-6·Area·810·(CTP0.71) else NBMZB = YChlZB·10-6·Area·810·(CTP0.71)·(1-0.5·(CTP/100-1))
(8)
Area is the coastal area (m2), CTP is the modelled TP-concentration. The normal biomass of phytoplankton is given by: NBMPH = Ychl·(10-6)·Vsec·(30·CTP1.4)
(9)
(30·TP1.4) is the normal biomass of phytoplankton in lakes (Table 4) and Vsec (or VsecSW) the water volume above the Secchi depth (Sec), calculated from: Vsec = V-(A-Asec)·Vd·(Dmax-Sec)/3
(10)
Vd is the form factor (Vd = 3·Dm/Dmax) and Asec is the bottom area shallower than the Secchi depth. The normal biomass of benthic algae (NBMBA) is calculated from the normal production of benthic algae (NPRBA) and the turnover time of benthic algae (TBA) by: NBMBA = NPRBA·TBA
(11)
NPRBA = 0.63·(Asec/A)·PRPH·(YsalSW)
(12)
Where
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Asec/A is the part of the bottom area shallower than the Secchi depth; PRPH is the production of phytoplankton (PRPH = BMPH/TPH). The equation in CoastWeb is the same as in LakeWeb, except for YsalSW, which is a salinity moderator for how the salinity influences the water clarity, which in turn influences the production of benthic algae (if SalSW < 1 then YsalSW = 1 else YsalSW = SalSW/1). The normal biomass of bacterioplankton (NBMBP) is estimated from a lake regression based on TP and Chl (Table 4), and modified by a moderator for SPM (YSPMBP) – the higher the amount of degradable organic suspended matter, the higher the normal biomass of bacterioplankton. NBMBP =YSPMBP·0.001·Vol·10(0.973·(0.27·log(Chl)+0.19)-0.438)
(13)
YSPMBP is given by: YSPMBP = SPMSWcoast/SPMSWlake
(14)
So, if there is a difference in SPM between a coast and a similar lake, this would influence the normal biomass of bacterioplankton in the coast. The SPM-concentrations in the surface water in the coast (SPMSWcoast) and in a corresponding lake (SPMSWlake) are calculated from the respective TP-concentrations and the regression between TP and SPM (from Håkanson, 2006). The same approach is used to estimate normal biomasses of the functional groups in the sea outside the given coastal area (NBMsea), which are used to calculate immigration. NBMsea is estimated from: NBMsea = NBMcoast·Ychlsea
(15)
Ychlsea is Chlsea/Chlcoast. For phytoplankton in the sea outside the given coastal area, the normal biomass is: NBMPHsea = Ychlsea·(30·CTPsea1.4)
(16)
For herbivorous and predatory zooplankton, the normal biomasses in the sea (NBMZHsea and NBMZPsea) are calculated as Ychlsea·NBMZH and Ychlsea·NBMZP. This is also the case for the normal biomasses for prey and predatory fish (Ychlsea·NBMPY and Ychlsea·NBMPD). For bacterioplankton, we have: NBMBPsea = NBMBP·YSPMsea
(17)
YSPMsea is SPMsea/SPMcoast and SPMsea is calculated from (SPMsea = 10(1.56·log(TPsea)-1.64)). The TP-concentration in the sea outside the given coast (TPsea = CTPsea in µg/l) is an obligatory driving variable. Immigration and emigration are not calculated for benthic algae, macrophytes and zoobenthos since these groups are assumed to be largely stationary. Migration of the other functional groups is described in the following section. We will be show how these algorithms work using data from real coastal areas.
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Table 5. Compilation of equations used to quantify immigration and emigration of predatory fish, prey fish, jellyfish, predatory zooplankton, herbivorous zooplankton, phytoplankton and bacterioplankton. There is no in- and emigration for benthic algae or zoobenthos (or macrophytes) in the model Ychlsea = Chlsea/Chlcoast The chlorophyll concentration in the sea and the coast may be given either by empirical data or by local, regional or global regressions based on TP and SWT (SWT = surface-water temp, °C) Predatory fish (PD); immigration: If BMPD/NBMPD < 1 then FinmigPD = Yseason ·RmigPD·NBMPDsea else FinmigPD = 0.5·Yseason ·RmigPD·NBMPDsea Migration rate: RmigPD = (1/TSW) [this is the theoretical surface water retention rate] Dimensionless seasonal moderator for migration: Yseason If (YseasonA -YseasonB) ≥ 0 then Yseason = ((YseasonA+YseasonB)/2)·(Lat/63) else Yseason = ((YseasonA+YseasonB)/2)·(63/Lat, where YseasonB = SMTH(YsaeasonA, AV, 0.12) NBMPDsea = NBMPDlake ·Ychlsea Ychlsea = Chlsea/Chlcoast Predatory fish (PD); emigration If BMPD/NBMPD < 1 then FoutmigPD = 0.5·Yseason ·RmigPD·BMPD else FoutmigPD = Yseason ·RmigPD·BMPD Prey fish (PY) immigration: If BMPDY/NBMPY < 1 then FinmigPY = Yseason ·RmigPY·NBMPYsea else FinmigPY = 0.5·Yseason ·RmigPY·NBMPYsea Migration rate: RmigPY = (0.33·1/TSW) NBMPYsea = NBMPYlake ·Ychlsea Prey fish (PY); emigration If BMPY/NBMPY < 1 then FoutmigPY = 0.5·Yseason ·RmigPY·BMPY else FoutmigPD = Yseason ·RmigPD·BMPD Jellyfish (JE) Migration rate: RmigJE = RmigPY Immigration: FinmigJE = RmigJE·NBMJEsea NBMJEsea = NBMJE ·Ychlsea NBMJE (kg ww) is assumed to be 10 times the normal biomass of predatory zooplankton (NBMZP, see below). Emigration: FoutmigJE = RmigJE·BMJE Predatory zooplankton (ZP) Migration rate: RmigZP = 1/TSW Immigration: FinmigZP = RmigZP·NBMZPsea NBMZPsea = NBMZPlake ·Ychlsea Emigration: FoutmigZP = RmigZP·BMZP Herbivorous zooplankton (ZH) Migration rate: RmigZH = RmigZP Immigration: FinmigZH = RmigZH·NBMZH
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Table 5. (Continued) NBMZHsea = NBMZHlake ·Ychlsea Emigration: FoutmigZH = RmigZH·BMZH Phytoplankton (PH) Migration rate: RmigPH = 0.5·RmigZP Immigration: FinmigPH = RmigPH·NBMPHsea NBMPHsea = NBMPHlake ·Ychlsea Emigration: FoutmigPH = RmigPH·BMPH Bacterioplankton (BP) Migration rate: RmigBP = RmigPH Immigration: FinmigBP = RmigBP·NBMBPsea NBMBPsea = NBMBPlake ·Ychlsea Emigration: FoutmigBP = RmigBP·BMBP
Migration LakeWeb accounts for immigration and emigration of fish. Coastal areas have a much more dynamic exchange of water than lakes (a typical theoretical surface-water retention time for Baltic Sea coastal areas is 4-6 days; and a typical water retention time for a lake is about 1 year; see Håkanson, 2000), which affects the immigration and emigration of fish to and from the area. Migration of fish is a complicated issue (Levinton, 2001), but it has to be quantified in CoastWeb where the aim is to obtain realistic predictions of fish biomass. Not only prey and predatory fish migrate, but also jellyfish, zooplankton, bacterioplankton and phytoplankton. New algorithms for immigration and emigration are used for all these functional groups (Table 5). They are based on the following principles: 1. The migration rate (Rmig, per month) in LakeWeb is related to the surface water (SW) retention rate (Rmig =1/TSW). This is meant to account for the physical possibilities for the organisms to migrate: if there is no inflow or outflow of water, no organisms will migrate in and out of the system. This approach is also used in CoastWeb for plankton that travel with the water rather than in the water, but not for fish and jellyfish. Plankton is mainly transported by water currents, as given by the SWexchange (TSW). The deep-water (DW) exchange is generally smaller than the SWexchange and the focus here is on the water exchange for the productive SW-layer. 2. It is assumed that big predatory fish will move more than smaller prey fish (the default assumption is that the migration rate is a factor of 3 lower for prey fish than for predatory fish, all else being constant); jellyfish and prey fish are assumed to have similar migration rates but jellyfish is likely to drift more passively in the water than prey fish. Vertical movements of jellyfish are achieved through contraction of the bell (Moen and Svensen, 2004). 3. Fish can migrate in and out of coastal areas for a number of reasons: as a part of their life cycle, to spawn, mate, etc. (Levinton, 2001) or more seasonally in search for food. This behaviour is different for different species. Knowledge of the dominating species in a region should be used to define an optimum migration behaviour for the
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Lars Håkanson and Dan Lindgren prey and predatory fish in the given region. For example, in Baltic Sea systems, Baltic herring (Clupea harengus) is likely to migrate into the coast in great numbers during the spawning in the spring (Axenrot and Hansson, 2004), which implies that the predatory fish feeding on herring also will migrate into the coast, and that the fish biomass in the coast will increase. To account for such regional migration patterns, CoastWeb uses a dimensionless moderator (Yseason), which could be adjusted to the prevailing conditions in different regions. This moderator is multiplied with the default migration rate (Rmig). As in LakeWeb, it is also assumed that the immigration or emigration of fish depend on the relationship between the actual biomass in the coastal area and the normal biomass (the BM/NBM-ratio). The migration may also sometimes be temperature dependent. Fish eat and grow faster in species-specific temperature ranges (Larsson and Berglund, 2005). This temperature influence could also be accounted for in the Yseason-moderator. An algorithm has been added to take into account that the latitude (Lat in °N) probably influences the seasonal migration patterns for fish. One should expect a more pronounced seasonal variation in light and temperature at high latitudes than at low latitudes and hence also in migration of fish searching for food. This has been handled in the following manner: If Lat > 63°N then AV = 1 else AV = (63-Lat); AV is an averaging function used in the smoothing function (SMTH) below: YseasonB = SMTH(YsaeasonA, AV, 0.12)
(18)
YseasonA is the seasonal moderator used for all coasts at latitudes ≥ 63°N (for which AV = 1; this is an assumed boundary latitude for the given algorithm). At lower latitudes, the function will smooth this curve (Figure 6A). The general moderator for migration is given by: If (YseasonA -YseasonB) ≥ 0 then Yseason = ((YseasonA+YseasonB)/2)·(Lat/63) else Yseason = ((YseasonA+YseasonB)/2)·(63/Lat)
(19)
Yseason is the default dimensionless moderator. It is shown in Figure 6A for four different latitudes (≥ 63, 56, 45 and 35°N). With this setup, the moderator attains high values in the spring at high latitudes reflecting regions with strong migrations related to the spawning and feeding of the dominating fish species. This is a suggestion for a general approach that can be used if no information is available on regional migratory patterns of fish. If such information is available, it should preferably be used. 4. It would require a very extensive sea-model (similar to and compatible with CoastWeb) to predict the amount of fish or plankton available for immigration outside any given coastal area. CoastWeb estimates the potentially available fish biomass for immigration using an estimated normal fish biomass in the sea outside the given coastal area, which is calculated from chlorophyll in the sea outside the coastal area. The immigration of predatory fish is then calculated as: If BMPD/NBMPD < 1 then FinmigPD = Yseason·RmigPD·NBMPDsea else FinmigPD = 0.5·Yseason·RmigPD·NBMPDsea
(20)
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RmigPD is the default migration rate for predatory fish (= 1/TSW). If the theoretical SW-retention time, TSW, is 6 days, the surface water is exchanged 5 times each month. Since there are no general migration rates to/from coastal areas available in the literature (to the best of our knowledge), the value of the default migration rate is our estimate based on calibrations using information from the studied coastal areas. To quantify this more accurately is an important task for the future. NBMPDsea is the normal biomass of predatory fish in the sea outside the given coastal area calculated from the normal biomass of predatory fish in lakes, NBMPDlake (Table 4) and a chlorophyll moderator, Ychlsea. Figure 6B illustrates the migration rate (Rmig) for predatory and prey fish for the Ronneby coastal area (latitude 56°N; Table 1). An Rmig-value of 0.75 means that 75% of the fish biomass may migrate either in or out of the coastal area. 5. Emigration of predatory fish is calculated in a similar way, i.e.: If BMPD/NBMPD < 1 then FoutmigPD = 0.5·Yseason·RmigPD·BMPD else FoutmigPD = Yseason·RmigPD·BMPD
(21)
Figure 6. A. Illustration of the seasonal moderator for immigration and emigration, Yseason, for four different latitudes (≥ 63, 56, 45 and 35 °N) and B. The default migration rates for prey and predatory fish (RmigPY and RmigPD, respectively) using data for the Ronneby coastal area (latitude 56 °N)
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Table 5 gives a compilation of all equations quantifying immigration and emigration. It shows that the basic set-up is applied to all functional groups. Note that CoastWeb does not account for cannibalism (feeding within the functional group). Cannibalism exists in aquatic systems among fish (Menshutkin, 1971), but to gain simplicity, the model calculates net production of fish (and zooplankton and zoobenthos). Table 6 gives all calculated monthly fluxes of predatory fish, i.e., immigration and emigration, initial production (IPR), production (BM/T), fishing and elimination, for the Ronneby coastal area (Table 1). Table 6 and the following four tables give results exemplifying the magnitude of these fluxes. Evidently, uncertainties in major fluxes are more decisive for the predictions than uncertainties in minor fluxes. So, it is important to identify the major fluxes and use algorithms that quantify these as correctly as possible. One can note: The biomass of predatory fish in this coast varies between 2.5 and 4 t wet weight during the year. The initial production is relatively high during summer and fall with a yearly total of 3.2 t/y; the production values are about 3 t/y. Immigration and emigration are significant; immigration 16 t/y and emigration 10 t/y. So, there is a net immigration of predatory fish to this area. The annual fishing of predatory fish under default conditions is 5 t/y. The loss of predatory fish (death, etc.) is 4 t/y. Table 7. gives the corresponding values for prey fish. The biomass of prey fish is about a factor 5 times higher than for predatory fish; the biomass varies between 12 and 20 t during the year. The initial production is 63 t/y and the production about 20 t/y. Immigration is 12 t/y and emigration 25 t/y, which means a significant net outflow of prey fish. Table 6. Calculated monthly and annual values of predatory fish biomass and fluxes of predatory fish in the Ronneby coastal area (southern Baltic Proper) Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Biomass (BMPD) (kg ww) 3 811 3 646 3 187 2 647 3 426 3 606 3 828 4 030 4 155 3 977 4 002 3 977 Annual values:
IPRPD (kg ww/m)
ElimPD (kg ww/m)
294 277 240 166 178 229 264 308 329 319 306 304 3 214
365 348 318 260 285 332 347 369 383 381 374 375 4 137
FishingPD (kg ww/m) 128 283 653 1 442 1 010 303 121 91 385 331 139 147 5 033
InmigPD (kg ww/m)
OutmigPD (kg ww/m)
513 622 798 2 096 3 329 2 056 1 422 1 222 1 798 1 060 772 661 16 349
480 432 525 1 100 1 434 1 470 995 869 1 234 846 539 468 10 392
Production (BMPD/TPD) (kg ww/m) 258 246 215 179 231 244 259 272 281 269 270 269 2 993
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3 906 3 946 4 063 3 907 4 573 5 902 7 147 7 502 6 767 5 912 5 172 4 291 63 088
17 29 43 52 95 150 151 130 102 67 36 14 886
12 18 24 28 56 94 100 84 65 37 21 10 549
1 177 1 107 960 663 713 916 1 056 1 233 1 315 1 278 1 222 1 216 12 856
2 447 2 316 2 136 1 776 1 752 1 911 2 198 2 566 2 738 2 696 2 644 2 569 27 749
287 627 1 460 3 282 2 088 582 256 211 916 783 326 336 11 154
318 341 438 1 782 3 236 1 586 1 041 882 1 241 676 457 379 12 377
1 161 1 252 1 552 2 539 2 533 2 887 2 288 2 179 3 230 2 479 1 673 1 372 25 145
Production (BMPY/TPY) (kg ww/m)
OutmigPY (kg ww/m)
InmigPY (kg ww/m)
FishingPY (kg ww/m)
ElimPY (kg ww/m)
From PY to PD (kg ww/m)
IPRZPPY (kg ww/m)
17 024 16 057 14 516 12 025 12 900 14 338 16 979 19 388 19 366 18 823 18 643 17 845 Annual values:
IPRZHPY (kg ww/m)
Biomass (BMPY) (kg ww)
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
IPRZBPY (kg ww/m)
Month
Table 7. Calculated monthly and annual values of prey fish biomass and fluxes in the Ronneby coastal area
1 727 1 628 1 472 1 220 1 308 1 454 1 722 1 966 1 964 1 909 1 891 1 810 20 071
Zoobenthos is the most dominating and important food for prey fish. The prey fish production from zoobenthos consumption is 63 t/y, compared to 1 t/y from consumption of herbivorous zooplankton and 0.5 t/yr from consumption of predatory zooplankton. The annual fishing of prey fish is 11 t/y. The loss of prey fish (death, etc.) is 28 t/y. Table 8. gives the results for predatory zooplankton. The biomass varies very much during the year, from 120 kg ww during the winter to almost 1.6 t during the summer. The initial production from eating herbivorous zooplankton is over 27 t/yr and the production about 21 t/yr. Immigration is 49 t/y and emigration 40 t/y, i.e., a net inflow from the sea. The elimination is 29 t/y. Table 9 shows the same results for zoobenthos, which feed on benthic algae (430 t/y), macrophytes (24 t/y), but most of all on ―sediments‖ (1000 t/y) since zoobenthos mainly are detrivores. The biomass of zoobenthos varies between 45 and 100 t during the year and is about a factor of 6 higher than the biomass of prey fish. Immigration and emigration are zero (zoobenthos are largely stationary within the given coastal area). The elimination of zoobenthos is about 1000 t/y.
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Lars Håkanson and Dan Lindgren Table 8. Calculated monthly and annual values of biomass and fluxes for predatory zooplankton in the Ronneby coastal area Month
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Biomass (BMZP) (kg ww) 117 160 252 340 607 1 159 1 594 1 285 917 681 347 146 Annual values:
IPRZP (kg ww/m)
ElimZP (kg ww/m)
135 150 300 527 933 3 224 6 769 6 676 4 399 2 787 1 051 464 27 415
456 501 790 1 134 1 569 3 309 5 568 5 617 4 182 3 037 1 750 987 28 900
From ZP to JE (kg ww/m) 0 0 0 0 0 0 0 0 0 0 0 0 0
From ZP to PY (kg ww/m) 147 165 259 350 399 814 1 375 1 466 1 222 944 540 306 7 987
InmigZP (kg ww/m) 1 066 1 248 1 926 2 600 3 455 5 994 8 249 7 808 6 376 5 125 3 307 1 983 49 137
OutmigZP (kg ww/m) 626 688 1 084 1 556 2 153 4 542 7 641 7 709 5 739 4 168 2 402 1 355 39 663
Production (BMZP/TZP) (kg ww/m) 323 442 696 940 1 678 3 203 4 405 3 551 2 534 1 882 959 403 21 017
Table 9. Calculated monthly and annual values of biomass and fluxes for zoobenthos in the Ronneby coastal area Month Biomass (BMZB) (kg ww) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
45 501 48 373 53 841 64 705 80 396 100 518 103 515 90 509 77 495 69 738 57 531 47 569 Annual values:
IPRBAZB (kg ww/m) 6 284 10 099 15 137 22 908 49 432 78 805 84 256 68 794 49 825 28 632 15 390 6 157 435 719
IPRsedZB (kg ww/m) 73 156 75 203 76 514 77 983 84 312 91 251 95 216 96 027 94 897 89 079 81 274 73 798 1 008 710
IPRMAZB (kg ww/m) 1 034 1 001 1 069 1 260 1 723 2 510 3 247 3 298 2 876 2 371 1 862 1 280 23 531
From ZB to PY (kg ww/m)
ElimZB (kg ww/m)
24 374 24 720 26 935 33 436 52 251 66 358 75 697 71 336 60 968 40 650 34 077 27 314 538 116
58 168 58 711 60 316 57 851 67 525 86 086 104 025 109 788 99 645 87 189 76 656 63 882 929 844
Production (BMZB/TZB) (kg ww/m) 10 808 11 490 12 789 15 369 19 096 23 876 24 588 21 499 18 407 16 565 13 665 11 299 199 451
These simulations indicate that zoobenthos is an important food for fish in this coastal area and that threats to the production of zoobenthos would be serious to the fish production. Immigration and emigration of fish and zooplankton are important processes. There is generally no jellyfish in the Ronneby coastal area. The next section focuses on jellyfish.
An Outline of the Sub-Model for Jellyfish Jellyfish (JE) can appear in great numbers and are able to consume substantial amounts of mainly zooplankton, which can influence on fish production (Schneider and Behrends, 1994;
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Brodeur et al., 2002; Purcell, 2003). This makes them an important part of coastal foodwebs and they have been included as a secondary production unit in CoastWeb for areas where the salinity is high enough (the default threshold value in this model is set to 10; Lucas (2001) gave a value of 14 for a common jellyfish, Aurelia aurita). Jellyfish is a predatory zooplankton and could belong to the predatory zooplankton group in the model. However, the medusae-stage, i.e., what we generally mean by jellyfish, is so different compared to other predatory zooplankton concerning size, abundance, etc. that it has been assigned its own group in CoastWeb. Figure 7 illustrates the jellyfish sub-model and Table 10 gives all equations. Although this is a new sub-model, it is built in the same way as all other sub-models. This section will give an outline of this building block. Since jellyfish mainly eat zooplankton (Larson, 1987; Mills, 1995; Hansson, 2006), there is only one food choice between predatory and herbivorous zooplankton. So, the number of first order food choices for jellyfish is NRJE = 2, separated by DCZPZH. Jellyfish are also known to consume ichthyoplankton (fish eggs and larvae; Cowan et al., 1996; Suchman and Brodeur, 2005). However, this is not considered in the model since ichthyoplankton is not included as a functional group. Table 10. Basic differential equation for production and biomass of jellyfish (JE) BMJE(t) IPRZHJE IPRZPJE InmigJE ElimJE OutmigJE FZHJE FZPJE Ychlsea CRJE DCZPZH MERZP RmigJE NJE NBMJE NCRJE SalSW TJE YsalJE Ytemp
= BMJE(t - dt) + (IPRZHJE + IPRZPJE + InmigJE - ElimJE - OutmigJE)·dt = YsalJE· (1- DCZPZH)·FZHJE· MERZP·Ytemp0.5 [initial production of JE from eating ZH] = YsalJE· DCZPZH·FZPJE· MERZP·Ytemp0.5 [initial production of JE from eating ZP] = RmigJE·NBMJEsea [immigration of JE] = BMJE·1.386/TJE [elimination of JE] = RmigJE·BMJE [emigration of JE] = BMJE·CRJE [flux from ZH to JE] = BMJE·CRJE [flux from ZP to JE] = Chlsea/Chlcoast [correction factor for biomasses in the sea and in the coast related to chlorophyll] = (NCRJE+NCRJE·(BMJE/NBMJE-1)) [consumption rate for JE; if NBMJE = 0, then CRJE = 0] = 0.5 [distribution coefficient for JE eating ZP or ZH] = 0.32 [metabolic efficiency ratio for JE eating ZP or ZH] = RmigPY = RmigPD·0.33 [basic migration rates for PY, JE and PD] = 2 [number of first order food choices] = 10·NBMZP = 50·Ychlsea·(1-DCZHZP)·10-6·SMTH((V·38·CTP 0.64),TZP,(V·38·CTP 0.64)) [normal biomass of JE] = NJE/TJE [normal consumption rate for JE] = Surface-water salinity [= 6.5 in the Ronneby coastal area] = 120/30.42 [turnover time for JE in months] = if SalSW < 10 then 0 else 1 [assumed threshold salinity for JE production] = (SWT+0.1)/9 [dimensionless moderator for temperature influences on bioproduction]
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Lars Håkanson and Dan Lindgren Outline of the sub-model for jellyfish From ZH to JE, FZHJE MERZP
YSWT
T JE
IPR ZHJE
InmigJE
Jellyfish biomass BMJE Elim JE
RmigJE IPR ZPJE
From ZP to JE, FZPJE
OutmigJE CRJE
DCZPZH NCR JE
YsalJE
NJE NBM ZP
NBM JE
SalSW
Figure 7. An outline of the new sub-model for jellyfish
The consumption of biomass from grazing is calculated in kg ww/month. The total consumption is given by FZPJE = BMZP·CRJE. BMZP is the available biomass of predatory zooplankton and CRJE is the actual consumption rate (jellyfish eating its prey): CRJE = (NCRJE+NCRJE·(BMJE/NBMJE-1))
(22)
NCRJE is the normal consumption rate, BMJE is the actual biomass of jellyfish and NBMJE is the normal biomass. This means that the model quantifies changes in the actual consumption of the prey unit related to changes in the biomass of the consumer: more animals in the secondary unit (higher BMJE) means a higher actual consumption rate, CRJE. If the actual biomass of the predator is equal to the normal biomass of the predator, BMJE/NBMJE = 1, and CRJE = NCRJE. If the actual biomass of the predator is twice the normal biomass, then CRJE = 2·NCRJE. So, the model gives a linear increase in consumption with increase in biomass of the secondary unit. Lacking reliable empirical data, it is assumed that NBMJE may be set to be 10 times higher than the normal biomass of predatory zooplankton and depend on salinity. This gives: NBMJE = 10·NBMZP·YsalJE
(23)
By using a boundary condition, NBMJE can never be less than 0. The normal consumption rate, NCRJE, is NCRJE = 2/TJE. TJE is the turnover time of jellyfish (i.e., of the medusae stage). According to Lucas (2001), medusae of the common jellyfish, Aurelia aurita,
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generally live for 4 to 8 months. In the model, 120 days is used as a default value of turnover time for Jellyfish. The initial production (IPR) of jellyfish (JE) from eating predatory zooplankton (ZP) is given by: IPRJE = YsalJE·DCZPZH·FZPJE·MERZP·Ytemp0.5
(24)
The distribution coefficient, DCZPZH, gives the fraction of predatory zooplankton versus herbivorous zooplankton consumed by jellyfish. The MER-value is the amount of the total consumption (FZPJE) that will increase the biomass of the consumer, here jellyfish. The jellyfish digestion/consumption of its prey is temperature dependent (Martinussen and Båmstedt, 1999). This is accounted for by a dimensionless moderator Ytemp0.5 (Ytemp = ((SWT+0.1)/9); SWT = the SW-temperature in °C). YsalJE is a salinity moderator, which works in the following way: If the SW-salinity (salSW) is lower than 10, then YsalJE = 0 else YsalJE = salSW/10. Jellyfish can in some cases be consumed by fish and turtles (Legović, 1987) and they can also be consumed by other jellyfish (Martinussen and Båmstedt, 1999). However, this is not accounted for in the default set-up of the model. Jellyfish are removed from the coastal system by two processes: elimination, related to the turnover time of jellyfish and emigration. Immigration and emigration of jellyfish are calculated from: FinmigJE = RmigPY·NBMJEsea·YsalJE
(25)
FoutmigJE = RmigPY·BMJE
(26)
The migration rate for jellyfish is set equal to the migration rate for prey fish and the normal biomass of jellyfish in the sea outside the given coastal area is calculated from NBMJEsea = NBMJE·Ychl. The actual biomass of jellyfish in the coastal area, BMJE, is calculated automatically in the model and Ychl is defined by eq. 1. Elimination, i.e. the loss of biomass (ELJE) is given as: ELJE = BMJE·1.386/TJE
(27)
Where 1.386 is the halflife constant (-ln(0.5)/0.5 = (0.693/0.5; see Håkanson and Peters, 1995).
THE ROLE OF MACROPHYTES Macrophyte Cover The sub-model used in LakeWeb to predict the macrophyte cover is shown in eq. 28. MAcovlake = (10.49+1.502·(Sec /Dm)-1.993·(90/(90-Lat))-0. 422·(√Dmax)+0.490·log(A1·10-6))2
(28)
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In CoastWeb, it has been modified by an energy factor (Yex1) taking into account that coasts are open and affected by wind/wave action from the sea. This moderator quantifies that in coasts, where the wind/wave energy is high and the water exchange fast, it would be more difficult for the roots of the macrophytes to develop which would lower the macrophyte cover (MAcov in % of the coastal area). The macrophyte cover is calculated as: MAcov = MAcovlake· (1/Yex10.75)
(29)
If Ex < 0.003 (lower boundary condition for the exposure; see Figure 1) then Yex1 = 1 else Yex1 = (Ex/0.003)0.25 If Ex > 10 (upper boundary condition for the exposure) then Yex1 = 10 else Yex1 = (Ex/0.003)0.25 So, if the exposure (Ex) is very limited (< 0.003), the equation will calculate the same macrophyte cover as for a lake. If Ex is very high (> 10) for open coasts, (1/Yex10.75) will be 0.18 and the macrophyte cover will be only 18% of the corresponding value for a lake. A typical Ex-value for Baltic coastal areas is about 0.1 (Håkanson, 2006) which gives Yex = 0.52 and a macrophyte cover that is 52% of what would be expected in a lake with the same Secchi depth (Sec in m), the same area above a water depth of one meter (A1 in km2), the same mean depth (Dm in m) and maximum depth (Dmax in m). The macrophyte cover is used to calculate macrophyte production and biomass; the higher the macrophyte cover, the higher the fish biomass (if everything else is constant), since the macrophytes provide a protected environment for small fish (Sogard and Able, 1991). Different macrophyte species prefer different salinities (Boston et al., 1989; King and Garey, 1999) and have different tolerance to changes in salinity (Rout and Shaw, 1998, 2001). A relatively constant salinity is desirable for the macrophytes to abound. Figure 8 shows that the increase in salinity in the middle of the 1990s in Ringkobing Fjord (see Table 1) likely caused the observed reduction in macrophyte cover. There has been a slight change in dominance from sago pondweed Potemogeton pectinatus towards the more salt tolerant ditch grass Ruppia cirrhosa in recent years. This example is included to stress that Coast Web does not include any consideration to the fact that there can be changes in the abundance of single macrophyte species with a higher or lower tolerance to changes in salinity. The overall correspondence between the predicted values for the macrophyte cover during the period when the salinity was lower than 9.5 is good (see Håkanson, 2006), but when the salinity reached a threshold value of 9.5 (Håkanson et al., 2007), there was an initial reduction in macrophytes, which is not captured by the model. This is because when the salinity increases, the Secchi depth will also iincrease, which means that the model will predict an increased macrophyte cover. However, Figure 8 shows that the opposite has happened in Ringkobing Fjord. This indicates that the effect of the changes in salinity on single macrophyte species is even more pronounced than indicated by looking just at the macrophyte cover for the initial period. The actual change should be related to the curve predicted by CoastWeb since these predictions describe what would normally be expected under given conditions related to the factors accounted for in CoastWeb (eq. 28).
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Figure 8. Illustration of how the mean annual macrophyte cover and the mean annual salinity have varied in Rinkobing Fjord between 1980 and 2004, and how the macrophyte cover is predicted by the modified CoastWeb-model
Macrophytes and Macroalgae and Their Influence on Fish Production Macrophytes and macroalgae constitute a good environment for some species of predatory fish, e.g., for pike to make an ambush (Savino and Stein, 1989). The beds of macrophytes constitute a ―nursery‖ for young fish (Sogard and Able, 1991), which help to sustain a high fish biomass. Macrophytes and macroalgae are generally not important food for most fish (Barnes and Hughes, 1988; except for herbivores), but they provide shelter (Persson and Eklöv, 1995; Duarte, 2000) and can reduce the predation pressure (Nelson and Bonsdorff, 1990; Winfield, 2004), especially on small fish. In LakeWeb, this is handled by a dimensionless moderator, YMA: YMA = (1-0.2·(Maccov/25-1))
(30)
Maccov is the macrophyte cover (%). Macroalgae are expected to play a larger role in saline systems than in lakes for two reasons. Firstly, when the water clarity increases, the depth of the photic zone increases. This increases the production of benthic algae and macrophytes, which can cause a shift from a dominance of pelagic primary production to benthic primary production. Secondly, in marine systems such a shift would likely lead to a higher percentage of large macroalgae compared to smaller benthic algae. These macroalgae will influence the structure of the coastal ecosystem in ways similar to the macrophytes. In LakeWeb, the macrophytes influence the fish production mainly by providing a safe haven for the small fish. This is accounted for by lowering the predation pressure (from man, mammals or birds) on the fish. In CoastWeb, the influence of macroalgae and macrophytes on production and survival of prey and predatory fish is accounted for by a modification of the dimensionless moderator (YMA) in eq. 30. This gives a new moderator YMAcoast, eq. 31, that should reduce the predation pressure on prey and predatory fish in the same manner as YMA does in LakeWeb.
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(31)
YBAmacro is the ratio between the actual biomass of benthic algae in coastal areas and the normal biomass of benthic algae in lakes (YBAmacro = BMBA/NBMBAlake). This ratio reflects the prevalence of macroalgae in coastal areas compared to lakes and is generally higher than 1. In LakeWeb, the loss of prey fish from fishing and predation, is given by a constant default rate. In CoastWeb, the corresponding default rate is modified by two dimensionless moderators meant to make the loss of prey fish from fishing more realistic. The loss of prey fish from fishing is given by FfishPY (in kg ww/month): FfishPY = YMAcoast·BMPY·RfishPY
(32)
BMPY is the biomass of prey fish and RfishPY is the fishing rate of the prey fish. RfishPY is defined as: RfishPY =Ysec·Yseason ·0.5
(33)
0.5 (1/month) is a default fishing rate used in LakeWeb (derived from extensive calibrations), which is affected by two dimensionless moderators that account for influence of Secchi depth (Ysec) and seasonal migration pattern to and from the coastal area (Yseason). If empirical data are available on fishing of prey fish, such data should be used instead of the default fishing rate of 0.5. If the Secchi depth in a corresponding lake (Seclake) is larger than the Secchi depth in the coast (Seccoast = Sec), then Ysec =1 else Ysec = Sec/Seclake. So, if the water clarity in the coast is larger than in a corresponding lake, the predation pressure on prey fish is assumed to be higher than in a lake. This is quantified by this simple dimensionless moderator. Yseason is the dimensionless moderator for seasonal migration (see eq. 19). The loss from all types of predation on predatory fish (FfishPD in kg ww/month) is given in a similar way by: FfishPD = YMAcoast·BMPD·2·RfishPY
(34)
The default assumption is that the rate for fishing and predation is higher for predatory fish than for prey fish based on the fact that large fish are more attractive for professional and recreational fishermen (given by the factor 2). Figure 9 illustrates how the prey fish biomass, the predatory fish biomass and the elimination of prey fish depend on the new algorithm given in eq. 31. In these simulations, the new algorithm was used after month 26, before the algorithm in eq. 30 was used. One should note the effects that the macroalgae would have on the predation of prey fish (Figure 9C). The effect is due to an increase in prey fish biomass, which is compensated for by a significant increase in the food available for predatory fish and hence also in predation pressure of predatory fish on prey fish. The net effect is a relatively small change in prey fish biomass (Figure 9B) and in predatory fish biomass (Figure 9A).
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Figure 9. Simulations to illustrate the role of macroalgae for the fish production and biomass in coastal areas. In these simulations, the dimensionless moderator expressing how macroalgae influence elimination of prey fish was used from month 26 (the curves ―Accounting for macroalgae‖) compared to a situation when this moderator is not used. Using data from the Ronneby coastal area, S. Sweden, (A) gives the results for predatory fish, (B) for prey fish and (C) for the predation/fishing of prey fish
RESULTS This section presents case-studies to illustrate the potential use of CoastWeb to quantify how three major threats to coastal systems are likely to influence the structure and function of coastal foodwebs and this section will also give results from sensitivity analyses to illustrate how the model works along a latitude/temperature gradient and a salinity gradient. The first case-study focuses on eutrophication, the second on overfishing and the third on toxic contamination.
Eutrophication The idea here is to study how hypothetical stepwise (3-year steps) increases in TP in the sea outside a coast would likely influence the coast. Here, data from the Haverö coastal area are used (Finland; Table 1). The results are presented in Figure 10. The actual (default) TPconcentration in the sea is 24 µg/l, and tests have been done of how values of 0.75·24, 24, 1.5·24 and 2·24 would change modelled values of TP in the coastal water (A), chlorophyll (B), Secchi depth (C), the oxygen saturation in the deep-water zone, O2Sat (D), the normal and actual biomasses of zoobenthos (E), herbivorous zooplankton (F), prey fish (G) and predatory fish (H). Modelled values of TP, chlorophyll, Secchi depth and O2Sat are also
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compared with empirical data and uncertainty bands for the empirical data. The main results and conclusions of the simulations are: There is generally good correspondence between modelled and empirical data for the TPconcentration (Figure 10A), chlorophyll (Figure 10B), Secchi depth (Figure 10C) and O2Sat (Figure 10D). Note that the empirical chlorophyll value is a mean value for the entire summer period. There is also a close and logical correspondence between the actual and normal biomasses for zoobenthos, herbivorous zooplankton, prey fish and predatory fish. Note that the actual biomasses accounts for seasonal variations and predation more realistically than the normal biomasses, which are basically empirical reference values. The increased hypothetical eutrophication of the sea outside the coastal area will drastically increase TP also in the coast (which is logical because the water retention time in this area is 3-5 days, Persson et al., 1994) (Figure 10E). This leads to higher Chl-values (Figure 10B), reduced Secchi depths (Figure 10C) and lower O2Sat (Figure 10D), which will influence zoobenthos (Figure 10E) living in the sediments more than zooplankton in the more oxygenated surface water (Figure 10F). Since there is much more zoobenthos in the system than zooplankton (about 50 t ww compared to about 3-5 t ww), zoobenthos is an important source of food for omnivorous prey fish and changes in zoobenthos will have clear effects on the prey fish (Figure 10G), and changes in prey fish biomass will in turn influence the predatory fish who feed on prey fish (Figure 10H). The zoobenthos within the accumulation areas (A-areas) will die if O2Sat is lower than 20%, but the oxygenation of the sediments on the erosion and transport areas (ETareas) will maintain a low biomass of zoobenthos in the more shallow parts of the coastal area. To conclude: The increased eutrophication in the sea will imply several changes to the water quality and foodweb characteristics of the studied coastal area. Many of these changes could be expected without a model, but the point here is that they have been quantitatively predicted using a general comprehensive foodweb model which includes a dynamic massbalance model for phosphorus. This modelling accounts for many abiotic and biotic interactions and feedbacks and it is meant to give the ―normal‖ response of the system to the given change in the TP-concentration in the sea. The model accounts for different types of compensatory effects (such as increasing eutrophication leading to a higher primary phytoplankton production, which leads to more suspended particulate matter in the water and a lower Secchi depth, which leads to a smaller depth of the photic zone, which leads to a lower primary phytoplankton production). Such effects are difficult to quantify without a model. As stated, CoastWeb simulates functional groups and hence does not include responses related to single species.
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Figure 10. Case-study on coastal eutrophication using data from the Haverö coastal area. There are changes in 3-year steps in the TP-concentration in the sea adjacent to the coastal area. The default TPconcentration in the sea is 24 µg l-1 and this value has been set to 0.75·24, 24, 1.5·24 and 2·24 (i.e., 18, 24, 36 and 48 µg l-1) and the consequences calculated for (A) the TP-concentration in the given coastal area, (B) chlorophyll, (C) Secchi depth, (D) oxygen saturation in the deep-water zone (all compared to empirical mean values and inherent uncertainties in the mean values; the chlorophyll mean value is for the summer period) and actual and normal biomasses of (E) zoobenthos (F) herbivorous zooplankton, (G) prey fish and (H) predatory fish. MV: Mean values, SD: Standard deviation
Overfishing Extensive fishing or fishing more than the permitted quota, is, unfortunately, a common practice in most parts of the world and an issue of intensive debate in many countries (Eagle
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and Thompson Jr., 2003; Hilborn et al., 2003). The idea with this case study is to illustrate how CoastWeb can be used to address this issue. Here, data from the Gävle coastal area (northern Sweden; Table 1) have been used. We will show how changes in fishing would influence the structure of this coastal ecosystem. The scenario is defined in Figure 11A. First, there is a ―normal‖ period of three years, then a period of one year when ten times the normal amount of prey and predatory fish is taken out of the system, followed by a recovery period of two years, then another period of intensive fishing with 20 times the default fishing for a period of two years, followed by a recovery period. Note that this is also a sensitivity analysis since no other changes than fishing have been made. In Figure 11, the consequences for TP-concentration (A), Secchi depth (B), chlorophyll (C) and the actual biomasses with and without this extensive fishing for herbivorous and predatory zooplankton (D, E), zoobenthos (F), prey fish (G) and predatory fish (H) are presented. The main results and conclusions of the simulation are: Also for this coastal area, there is generally a good correspondence between modelled and empirical data for TP (Figure 11A), Secchi depth (Figure 11B) and chlorophyll (Figure 11C). One can also note from these three figures that the changes in fishing in this coastal area would not affect the three water variables very much. There are no clear changes for herbivorous zoolankton (Figure 11D), but increases in the biomass of predatory zooplankton as a response to the lower predatory pressure from a declining biomass of prey fish related to the extensive fishing (Figure 11E and 11G). The lower predation pressure on zoobenthos from a reduced biomass of benthivorous prey fish is evident (Figure 11F). Note that this coastal system will recover quickly. As long as there is fish in the sea outside the coast, immigration of fish will continue, and the system will return to a dynamic steady state, as given by the algorithms for migration in the model. To conclude: The increased fishing will likely only affect the given coastal system marginally and mostly so during the period of the intensive fishing. The immigration of fish from the sea, especially in the springtime, is very large. However, if this kind of fishing were done also in the outside sea, the results would be different. This scenario also shows that it is essential to use as accurate values as possible on immigration and emigration in the model.
Toxic Contamination The final case-study concerns the effects of toxic substances. Our aim is to demonstrate the potential of CoastWeb for making calculations to obtain realistic expectations of the consequences that contaminants can have on the coastal foodweb. We will examine what might happen if a hypothetical contaminant would drastically reduce the biomass of a functional group. Large ecosystem effects should be expected if there are major changes in groups with large biomasses. For that reason, zoobenthos have been selected and data from the Ronneby coastal area have been used. There is also another reason to focus on zoobenthos, related to the fact that many toxic substances show a high affinity for particles in
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aquatic systems (Håkanson, 1999; Mackay, 2001). This means that high concentrations of such substances may appear in sediments, the habitat for zoobenthos.
Figure 11. Case-study on extensive fishing (or overfishing) using data from the Gävle coastal area. First there is a tenfold increase in the default fishing/predation rate on prey and predatory fish for one year, and then the fishing rate is increased by a factor of 20 for two consecutive years (see Figure A). The consequences of these events are calculated for (A) TP-concentration, (B) Secchi depth and (C) chlorophyll (all compared to empirical data, mean values and uncertainties in the mean values; the chlorophyll mean value is for the summer period). Figures D to H gives a comparison of how this extensive fishing would influence the actual biomasses of (D) herbivorous zooplankton, (E) predatory zooplankton, (F) zoobenthos, (G) prey fish and (H) predatory fish. MV: Mean values, SD: Standard deviation
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Figure 12. Case-study on toxic contamination using data from the Ronneby coastal area. It is assumed that there is first a contamination that eliminates 90% of the zoobenthos months 7 and 8, then a contamination that kills 99% of the zoobenthos for a whole year, and, finally, total extinction of zoobenthos (see Figure A). The consequences of these events are calculated for the actual and normal biomasses of (B) phytoplankton, (C) benthic algae, (D) bacterioplankton, (E) herbivorous zooplankton, (F) predatory zooplankton, (G) prey fish and (H) predatory fish. MV: Mean values, SD: Standard deviation
Figure 12A presents the scenario. First, 90% of the zoobenthos biomass is reduced (killed by contamination) months 7 and 8, year 4. Then, after a two year recovery period, 99% of the zoobenthos biomass is reduced for an entire year. Finally, after another period of recovery, all zoobenthos are killed. Figure 12 shows how this would influence the actual and normal biomasses of zoobenthos (A), phytoplankton (B), benthic algae (C), bacterioplankton (D), herbivorous zooplankton (E), predatory zooplankton (F), prey fish (G) and predatory fish (H).
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Initially, there is a good correspondence between actual and normal biomasses also in this area for all the eight functional groups shown in Figure 12. The changes in zoobenthos (Figure 12A) will not affect phytoplankton (Figure 12B), benthic algae (Figure 12C) and bacterioplankton (Figure 12D). Since there is much more zoobenthos in the system than herbivorous and predatory zooplankton (about 100 t ww compared to about 5 and 1 t ww, respectively), zoobenthos is an important food source for omnivorous prey fish and reductions or changes in zoobenthos will have clear effects on prey fish and hence also on predatory fish (compare Figure 12A to Figure 12G and H). To conclude: This case-study shows that a reduction of zoobenthos biomass will have clear effects of fish production and biomass in the given coastal area. This scenario may not be realistic in the sense that nothing but zoobenthos has been affected by the contamination. However, more realistic simulations can be made with the model. The model can, e.g., also be used to simulate non-lethal effects of toxic substances, such as reduced production. The idea here is just to briefly demonstrate its potential.
Sensitivity Analysis – Latitude/Temperature This section first presents a sensitivity analysis along a latitude (temperature) gradient. The latitude for the Gräsmarö coastal area (see Table 1; latitude = 58°N) has been changed in 3-year steps to 40, 50, 58 and 70°N. Results are given in Figure 13 for Secchi depth, TP, O2Sat, chlorophyll (using the general approach in Table 4) and actual and normal biomasses of benthic algae, zoobenthos, prey fish and predatory fish. Figure 13A gives the driving variable, the latitude gradient. The main results and conclusions of the simulation are: The change in latitude will cause clear changes in predicted surface-water temperatures (Figure 13A). There is a good correspondence between modelled and empirical chlorophyll (Figure 13B); the figure gives empirical mean values (MV) and MV plus two standard deviations (SD). There is a good correspondence also between modelled values for sedimentation on accumulation areas and empirical data, as determined from sediment traps (Figure 13C). Figure 14D to H give values of the actual and normal biomasses for phytoplankton, benthic algae, bacterioplankton, zoobenthos and predatory fish. The actual biomasses should give representative values since these values account for predation and several factors that are not included in the calculation of the normal biomasses. In general, however, there is a good correspondence between the two measures indicating that the model works as expected. It is also interesting to compare the biomasses: in this test, the biomass of benthic algae (Figure 13E) is higher than the biomass of bacterioplankton (Figure 13F), which is higher than the biomass of phytoplankton (Figure 13D); the biomass of zoobenthos
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Figure 13. Testing the model along a latitude gradient using data from the Gräsmarö coastal area. The default latitude (58°N) has been changed in 3-year steps by 40, 50, 58 and 70°N and the consequences have been calculated for (A) the surface-water temperature, (B) chlorophyll-a, (C) sedimentation on accumulation areas (as compared to empirical maximum and minimum data from sediment traps), and modelled actual and normal biomasses of (D) phytoplankton, (E) benthic algae, (F) bacterioplankton, (G) zoobenthos and (H) predatory fish. MV: Mean values, SD: Standard deviation
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Sensitivity Analysis - Salinity This section presents a sensitivity analysis along a salinity gradient. Figure 14 uses data from the Ronneby coastal area (see Table 1). The default salinity inside and outside this area has been increased in 3-year steps from 6.5 to 13, 19.5 and 26 and the consequences calculated for all functional groups and bioindicators while all other factors have been kept constant at the default conditions. Figure 14 gives results for Secchi depth, TP, O2Sat, chlorophyll (using the general approach in Table 4) and actual and normal biomasses of benthic algae, jellyfish, prey fish and predatory fish. Figure 14A gives the driving variable, the salinity gradient. The main results and conclusions are: The increase in salinity will cause a distinct increase in Secchi depth and in water clarity (Figure 14A). There is a good correspondence between modelled and empirical Secchi depths also in this coastal area. Whenever data are available, Figure 14 also gives empirical mean values (MV) and standard deviations for the empirical data (SD) as a measure of the inherent uncertainty in the empirical data. There is a good correspondence between modelled and empirical TP. TP will decrease somewhat along the salinity gradient (Figure 14B). There is also a fine correspondence between modelled and empirical O2Sat, which will decrease with increasing salinity because a high salinity will increase flocculation and sedimentation of suspended particulate matter and particulate phosphoprus. In this open and shallow area, the deep-water turnover time is about 6 days and the deep-water volume is small. This means that the coastal area is well oxygenated (Figure 14C). There is also a relatively good correspondence between modelled and empirical chlorophyll (Figure 14D). Chlorophyll decreases with increasing salinity (see Figure 5) and with lower TP. The biomass of benthic algae (Figure 14E) increases along the salinity gradient because a higher salinity means an increased water clarity and therefore photosynthetic activity. Also the Jellyfish biomass increases (Figure 14F). However, there are no empirical data on biomasses available for comparison. Also the biomass of zoobenthos increases, meaning more food for prey fish and a higher biomass of prey fish along the salinity gradient. More prey fish also means more food for the predatory fish and an increase in predatory fish biomass (Figure 14G and H). The changes in salinity would also influence the migration of fish and the consumption rates since the salinity influences the normal biomasses of both prey and predatory fish. In reality, individual species can be sensitive to changes in salinity and would not survive the big changes in salinity that was used in this example. However, the model does not simulate individual species, but functional groups and a salinity that is non-optimal for one species may be optimal for another species in the same functional group.
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Figure 14. Testing the CoastWeb-model using data from the Ronneby coastal area along a salinity gradient. The default salinity (6.5) has been increased in 3-year steps by a factor of 1, 2, 3 and 4 and the consequences calculated for (A) Secchi depth, (B) TP-concentration, (C) oxygen saturation in the deepwater zone, (D) chlorophyll-a concentration using the general model (all compared to empirical mean values and inherent uncertainties in the mean values; the chlorophyll mean value is for the summer period) and actual and normal biomasses of (E) benthic algae, (F) jellyfish, (G) prey fish and (H) predatory fish
DISCUSSION AND COMMENTS The overall framework for this modelling is that science and management need practical, operational tools to predict how coastal ecosystems would likely respond to
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different threats so that the best possible remedial actions can be taken. The model presented in this work in meant as a tool to address such issues. This is exemplified by the case-studies and sensitivity analyses discussed in this paper We have presented a first version of CoastWeb, a coastal foodweb model that simulates ten functional groups and includes a mass-balance model for phosphorus. CoastWeb is an adaptation of a foodweb model for lakes and its underlying structure and main algorithms have been extensively tested. However, this is a first adaptation of the model to coastal conditions and there are several parts that could and should be improved if, and when, better data become available from more coastal areas covering a wide functional domain. At present, the lack of data is most evident for more saline coastal areas. A major deficiency in CoastWeb compared to LakeWeb concerns the empirical models to predict normal biomasses for the functional groups. In this respect, limnology, where good empirical models exist for almost all functional groups, is ahead of coastal ecology. This highlights the importance of getting better data and knowledge on the role of the salinity to predict chlorophyll from phosphorus and/or nitrogen in costal areas. It is also important to seek better knowledge on the processes regulating nitrogen fluxes in marine systems to be able to include a mass-balance model of nitrogen in CoastWeb in the future. In CoastWeb, jellyfish has been introduced as a functional group. The model structure for this group is the same as for all other functional groups. Empirical data have been used for jellyfish model parameterisation, when available. However, in this first version, several estimates have been used that may need to be changed when more and better data become available in the future. Mass occurrence (blooms) of jellyfish also needs to be addressed in future versions of CoastWeb. Due to the high variability that coastal fish show concerning food habits, migratory patterns, etc., it is difficult to develop general algorithms for fish that give good predictions over a wide range of areas. The regional seasonal moderator (Yseason) that handles migration of fish used in this work is only meant as a template and is mainly intended to reflect prevailing conditions in Baltic Sea coastal areas. Similar regional moderators should be developed for other coastal regions. This is especially important since the performed tests show that migration of fish is of major importance for coastal fish biomasses. It is essential to stress that the model simulates functional groups and not individual species. In the presented sensitivity analyses and case-studies, several water variables show good correspondence with existing and available empirical data. The calculated biomasses seem reasonable, but no or few empirical biomasses data have been available to perform independent validations. This is desirable for the future, although it is very hard to get comprehensive, time- and area compatible data on biomasses and abiotic variables from the same area for functional groups of organisms.
ACKNOWLEDGMENTS This work has been carried out within the framework of the Thresholds-project, an integrated EU project (no., 003933-2), and we would like to acknowledge the financial support from EU and the constructive cooperation within the project. Special thanks to prof. Carlos Duarte, the scientific coordinator of the project.
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APPENDIX: MINOR MODIFICATIONS 1. Salinity is of paramount importance for the number of different species: freshwater species dominate at salinities lower than 5 (psu), brackish water species at salinities from 5 to 20 and saltwater species at higher salinities than 20 (Remane, 1934). The salinity also influences the settling velocity of SPM, and hence water clarity (Secchi depth): the higher the salinity, the greater the aggregation, and the higher the sedimentation (Kranck, 1973, 1979). In CoastMab, this is expressed by a dimensionless moderator for salinity (Ysal) operating on the settling velocity. The effect of salinity is of special importance in estuaries where fresh and saltwater meet and a zone of maximum turbidity occurs (Gebhardt et al., 2005). A new algorithm relating the Secchi depth to SPM and salinity (from Håkanson, 2006) has also been incorporated into CoastWeb. 2. SPM-values are used to calculate the Secchi depth, which in turn is important to predict macrophyte cover and production of benthic algae. In the original CoastMabmodel for total phosphorus (TP) (Håkanson and Eklund, 2007), SPM is calculated by a dynamic SPM-model. For simplicity, and because there is a close relationship between SPM and TP, this version of CoastWeb has omitted the dynamic SPMmodel and uses a regression to predict SPM from dynamically modelled TPconcentrations (Figure 15). It is based on annual data from 51 systems (data from Lindström et al., 1999; Håkanson, 2006) and gives a high coefficient of determination (r2 = 0.895). However, this regression is based on data from systems with salinities lower than 15 so it may provide limited predictive power for systems with higher salinities. y = 1.561x - 1.639; r2 = 0.895; n = 51; p < 0.001 1.75 1.5 1.25
log(SPM) [mg l-1]
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log(TP) [µg l-1] Figure 15. The regression between annual SPM and TP-concentrations based on data from 51 coastal areas and lakes
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3. The chlorophyll-a concentration (Chl) is important in CoastWeb since Chl is needed to predict phytoplankton biomass. If the aim is to use only CoastWeb, the simplest approach is to use empirical data of Chl. However, if the aim is to study how changes in phosphorus loading affect the foodweb, CoastMab should be linked to CoastWeb. Calculating chlorophyll from nutrients is a fundamental concern in aquatic sciences. Generally, Chl-values are predicted from temperature or light and nutrient concentrations (Dillon and Rigler, 1974; Smith, 1979; Riley and Prepas, 1985; Evans et al., 1996). In this work, regressions relating monthly TP to monthly chlorophyll are used. A local relationship (Håkanson et al., 2007) between chlorophyll and TP has been used for Ringkobing Fjord, Denmark (see Table 4 and Figure 16, with and without a smoothing function SMTH; see Håkanson, 1999). Note that modelled values are not compared to the empirical mean values, but to uncertainty bands calculated as median monthly values ± the uncertainty in the mean empirical value. The regional regression in Table 4 is from Håkanson and Eklund (2007); (SWT+0.1)/20) is the temperature moderator where 20°C is the summer mean temperature for this regression. If no local or regional relationships are available, the general approach in Table 4 may be used. This is an adaptation of a basic regression for lakes [(0.28·CTP)0.96; from OECD (1982)], which is modified by a four moderators. The calcium moderator (YCa) takes into account that systems with Caconcentrations > 10 mg/l are likely to have lower Chl-values relative to TP than systems with lower Ca-concentrations (Håkanson et al., 2005). The morphometry moderator, YDRchl, quantifies how the dynamic ratio (DR = √Area/Dm; Area in km2 and mean depth, Dm, in m) influences the relationship between TP and Chl. Systems with DR > 2.45, are dominated by resuspension events of fine sediments (Håkanson and Jansson, 1983). In such systems, benthic algae may be resuspended and included in the water sample used for the chlorophyll analysis. YDRchl is given by: If DR < 2.45 then YDRchl = 1 else YDRchl = DR/2.45
(35)
The temperature moderator [Ytemp= ((SWT+0.1)/20)] has already been mentioned. The salinity moderator, Ysal, takes into account that the salinity influences the distribution coefficient between dissolved and particulate P in a similar way as calcium: the higher the salinity the lower the slope of the regression line between TP and chlorophyll (Figure 5; Håkanson et al., 2007). The relationship between Chl and phosphorus is also affected by the particulate fraction of phosphorus (PF). In LakeWeb, monthly PF was set to 0.56 as a reference value (Håkanson and Eklund, 2007), but in CoastWeb PF is affected by the biouptake and retention of phosphorus in functional groups, eq. 36. If SWT > 9 °C then PF = 0.56·(MSW + Mshort + Mlong)/MSW else PF = 0.56·MSW/(MSW+ Mshort + Mlong)
(36)
MSW, Mshort, Mlong are the amounts of TP [g] in the surface water, in functional groups with short turnover times and with long turnover times. So, in CoastWeb,
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The previous expression works well for systems where the DW-zone has the form of a cone, but for systems that are more U-shaped with Vd-values higher than 1, the correction using the form factor (Vd = 3·Dm/Dmax) will provide a more realistic estimate of VDW. 5. The moderator, YEh1, is used to express the oxygen stress on zoobenthos in LakeWeb. In CoastWeb, it has been replaced by a more tested approach, which is also used to quantify diffusion of phosphorus from sediments (Håkanson and Eklund, 2007): If O2Sat > 50% then YEh1 = (2-1·(O2Sat/50-1)) else YEh1 = (2-3000·(CTPA/1)·(O2Sat/50-1))
(38)
Figure 16. Modelling chlorophyll in Ringkobing Fjord, from modelled monthly TP-concentrations (actual data and smoothed data) using the CoastMab-model (within CoastWeb) and the regression given in eq. 2, compared to uncertainty bands based on median monthly values ± the uncertainty in the empirical annual mean values (see Håkanson et al., 2007)
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CTPA is the modelled TP-concentration is accumulation-area (A) sediments. If CTPA is higher than 1 mg/g dw, the dimensionless amplitude value (3000) increases, and hence also the diffusion; if CTPA is lower than 1, the amplitude value decreases. The following smoothing function has also been applied to provide realistic temporal changes in the moderator for zoobenthos: YEh = SMTH(1/YEh1, TZB, 1/YEh1)
(39)
TZB is the turnover time for zoobenthos (Table 2). YEh is never permitted to attain values < 0. 6. The dimensionless moderator expressing how low oxygen saturation in the DW-zone (O2Sat in %) would influence the survival of zoobenthos in areas of erosion and transport (ET-areas) has been modified from YEh10.25 to YEh10.5. This means that a low O2Sat will more clearly reflect lower oxygen conditions also in the surface water. 7. The distribution coefficient regulating the prey fish consumption of either zooplankton or zoobenthos has been changed from 0.5 in LakeWeb to DCZPZB = 0.5·Ysec0.2. For coasts, which generally have a higher water clarity than lakes, the basic DC-value is modified by a Secchi depth moderator (Ysec;, eq. 40), that compares the Secchi depth in the coast Secchicoast with that of a corresponding lake, Secchilake. If Secchilake > Secchicoast then Ysec = 1 else Ysec = Secchicoast/Secchilake
(40)
Which, e.g., gives 0.5·20.2 = 0.57 (a diet of 57% zooplankton and 43% zoobenthos consumed by prey fish) if Ysec is 2. The power (0.2) has been derived by calibration. 8. The moderator used in LakeWeb to reduce the predation pressure in very turbid lakes (Yfish) has been set to 1, since Secchi depths lower than 1 m are rare in coastal areas on a monthly basis (the ecosystem scale). 9. The amount of food (―sediment pool‖, FsedZB in kg ww/month) available for the zoobenthos is not calculated in the same manner as in LakeWeb, but from sedimentation of particulate phosphorus recalculated into sedimentation of organic matter as food for the zoobenthos. This is done accordingly: FsedZB = FAET·(1000/2)·1000·(100/(1-W))·0.67
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FAET is the sedimentation of TP on ET- and A-areas in g dw/month (calculated automatically in CoastMab from eq. 42). FAET is calculated from a function which gives an annual smoothing of the monthly sedimentation on ET-areas and A-areas (FSWET and FDWA in g TP/month): FAET = SMTH((FSWET+FDWA), 12, (FSWET+FDWA))
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From Håkanson (2006) it is assumed that SPM deposited on ET- and A-areas on average has a TP-concentration of 2 mg/g dw. Multiplication with 1000 gives SPM in kg dw/month. W is the water content of SPM (= 100·(g ww-g dw)/g ww) of SPM
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(43)
When the fraction of ET-areas is 15%, W is 75% which is used as the default water content of ET- and A-sediments in coastal areas (Håkanson et al., 1984). If the fraction of ET-areas (with coarser materials), is higher, the calculated water content of the SPM should be lower, which is given by eq. 43. If ET is 0.9, W is 61%.
REFERENCES Axenrot, T. & Hansson, S. (2004). Seasonal dynamics in pelagic fish abundance in a Baltic Sea coastal area. Estuar. Coast. Shelf Sci., 60, 541-547. Barnes, R. S. K. & Hughes, R. N. (1988). An introduction to marine ecology, 2nd ed. Blackwell Scientific Publications, Oxford, 351. Boston, H. L., Adams, M. S. & Madsen, J. D. (1989). Photosynthetic strategies and productivity in aquatic systems. Aquat. Bot., 34, 27-57. Brodeur, R. D., Sugisaki, H. & Hunt, G. L. Jr., (2002). Increases in jellyfish biomass in the Bering Sea: implications for the ecosystem. Mar. Ecol. Prog. Ser., 233, 89-103. Christensen, V., Walters, C. J. & Pauly, D. (2000). Ecopath with Ecosim: A User‘s Guide. Fisheries Centre, Univ. of British Columbia, Vancouver, 130. Cowan, J. H., Jr, Houde, E. D. & Rose, K. A. (1996). Size-dependent vulnerability of marine fish larvae to predation: an individual-based numerical experiment. ICES J. Mar. Sci., 53, 23-37. Dillon, P. J. & Rigler, F. H. (1974). The phosphorus-chlorophyll relationship in lakes. Limnol. Oceanogr, 19, 767-773. Duarte, C. M. (2000). Marine biodiversity and ecosystem services: an elusive link. J. Exp. Mar. Biol. Ecol., 250, 117-131. Eagle, J. & Thompson Jr., B. H. (2003). Answering Lord Perry‘s question: dissecting regulatory overfishing. Ocean Coast. Manag., 46, 649-679. Evans, M. S., Arts, M. T. & Robarts, R. D. (1996). Algal productivity, algal biomass, and zooplankton biomass in a phosphorus-rich, saline lake: deviations from regression model predictions. Can. J. Fish. Aquat. Sci., 53, 1048-1060. Gebhardt, A. C., Schoster, F., Gaye-Haake, B., Beeskow, B., Rachold, V., Unger, D. & Ittekkot, V. (2005). The turbidity maximum zone of the Yenisei River (Siberia) and its impact on organic and inorganic proxies. Estuar. Coast. Shelf Sci., 65, 61-73. Hansson, L. J. (2006). A method for in situ estimation of prey selectivity and predation rate in large plankton, exemplified with the jellyfish Aurelia aurita (L.). J. Exp. Mar. Biol. Ecol., 328, 113-126. Harvey, C. J., Cox, S. P., Essington, T. E., Hansson, S. & Kitchell, J. F. (2003). An ecosystem model of food web and fisheries interactions in the Baltic Sea. ICES J. Mar. Sci., 60, 939-950.
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Håkanson, L. (1999). Water pollution - methods and criteria to rank, model and remediate chemical threats to aquatic ecosystems. Backhuys Publishers, Leiden, 299. Håkanson, L. (2000). Modelling radiocesium in lakes and coastal areas - new approaches for ecosystem modelers. A textbook with Internet support. Kluwer Academic Publishers, Dordrecht, 215. Håkanson, L. (2006). Suspended particulate matter in lakes, rivers and marine systems. The Blackburn Press, New Jersey, 331. Håkanson, L., Blenckner, T., Bryhn, A. C. & Hellström, S. S. (2005). The influence of calcium on the chlorophyll-phosphorus relationship and lake Secchi depths. Hydrobiologia, 537, 111-123. Håkanson, L. & Boulion, V. V. (2002). The Lake Foodweb - modelling predation and abiotic/biotic interactions. Backhuys Publishers, Leiden, 344. Håkanson, L., Bryhn, A. C. & Eklund, J. M. (2007). Modelling phosphorus and suspended particulate matter in Ringkobing Fjord in order to understand regime shifts. J. Mar. Syst., 68, 65-90. Håkanson, L. & Eklund, J. M. (2007). A dynamic mass balance model for phosphorus fluxes and concentrations in coastal areas. Ecol. Res., 22, 296-320. Håkanson, L. & Gyllenhammar, A. (2005). Setting fish quotas based on holistic ecosystem modelling including environmental factors and foodweb interactions – a new approach. Aquat. Ecol., 39, 325-351. Håkanson, L. & Jansson, M. (1983). Principles of lake Sedimentology, Springer, Berlin, 316. Håkanson, L. & Karlsson, M. (2004). A dynamic model to predict phosphorus fluxes, concentrations and eutropications effects in Baltic coastal areas. In: M. Karlsson, Predictive modelling – a tool for aquatic environmental management. Thesis, Department of Earth Sciences, Uppsala University, 108. Håkanson, L., Kulinski, I. & Kvarnäs, H. (1984). Vattendynamik och bottendynamik i kustzonen. SNV PM 1905, Solna, 228. (in Swedish). Håkanson, L. & Peters, R. H. (1995). Predictive limnology. Methods for predictive modelling. SPB Academic Publishing, Amsterdam, 464. Hilborn, R., Branch, T. A., Ernst, B., Magnusson, A., Minte-Vera, C. V., Scheuerell, M. D. & Valero, J. L. (2003). State of the Worlds Fisheries. Annu. Rev. Environ. Resour., 28, 359399. King, G. M. & Garey, M. A. (1999). Ferric Iron Reduction by Bacteria Associated with the Roots of Freshwater and Marine Macrophytes. Appl. Environ. Microbiol, 65, 4393-4398. Kranck, K. (1973). Flocculation of suspended sediment in the sea. Nature, 246, 348-350. Kranck, K. (1979). Particle matter grain-size characteristics and flocculation in a partially mixed estuary. Sedimentology, 28, 107-114. Larson, R. J. (1987). Daily ration and predation by medusae and ctenophores in Saanich inlet, B.C., Canada. Neth. J. Sea Res., 21, 35-44. Larsson, S. & Berglund, I. (2005). The effect of temperature on the energetic growth efficiency of Arctic charr (Salvelinus alpinus L.) from four Swedish populations. J. Therm. Biol., 30, 29-36. Legović, T. (1987). A recent increase in Jellyfish populations: A predator-prey model and its implications. Ecol. Model., 38, 243-256. Levinton, J. S. (2001). Marine biology: function, biodiversity, ecology, 2nd Ed. Oxford University Press, New York, USA, 515.
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indström, M., Håkanson, L., Abrahamsson, O. & Johansson, H. (1999). An empirical model for prediction of lake water suspended matter. Ecol. Model, 121, 185-198. Lucas, C. H. (2001). Reproduction and life history strategies of the common jellyfish, Aurelia aurita, in relation to its ambient environment. Hydrobiologia, 451, 229-246. Mace, P. M. (2001). A new role for MSY in single-species and ecosystem approaches to fisheries stock assessment and management. Fish and Fisheries, 2, 2-32. Mackay, D. (2001). Multimedia Environmental Models. The Fugacity Approach, 2nd ed. Lewis Publishers, Boca Raton, FL, USA, 272. Martinussen, M. B. & Båmstedt, U. (1999). Nutritional ecology of gelatinous planktonic predators. Digestion rate in relation to type and amount of prey. J. Exp. Mar. Biol. Ecol., 232, 61-84. Menshutkin, V. V. (1971). Mathematical modelling of populations and communities of aquatic animals. Leningrad (in Russian). Mills, C. E. (1995). Medusae, siphonophores, and ctenophores as planktivorous predators in changing global ecosystems. ICES J. Mar. Sci., 52, 575-581. Moen, F. E. & Svensen, E. (2004). Marine fish and invertebrates. AquaPress, Essex, 608. Monte, L. (1995). A simple formula to predict approximate initial contamination of lake water following a pulse deposition of radionuclide. Health Phys., 68, 397-400. Monte, L. (1996). Collective models in environmental science. Sci. Total Env., 192, 41-47. Monte, L., Brittain, J. E., Håkanson, L. & Gallego, E. (1999). MOIRA models and methodologies for assessing the effectiveness of countermeasures in complex aquatic systems contaminated by radionuclides. ENEA, RT/AMP, 150. Nelson, W. G. & Bonsdorff, E. (1990). Fish predation and habitat complexity: are complexity thresholds real? J. Exp. Mar. Biol. Ecol., 141, 183-194. OECD. (1982). Eutrophication of waters. Monitoring, assessment and control. OECD, Paris, 154. Persson, J., Håkanson, L. & Pilesjö, P. (1994). Prediction of surface water turnover time in coastal waters using digital bathymetric information. Environmetrics, 5, 433-449. Persson, L. & Eklöv, P. (1995). Prey refuges affecting interactions between piscivorous perch and juvenile perch and roach. Ecology, 76, 70-81. Peters, R. H. (1991). A Critique for Ecology. Cambridge Univ. Press, Cambridge, 366. Pilesjö, P., Persson, J. & Håkanson, L. (1991). Digital sjökortsinformation för beräkningar av kustmorfometriska parametrar och ytvattnets utbytestid. National Swedish Environmental Protection Agency (SNV) Report no. 3916, Solna, Sweden, 76. (in Swedish). Purcell, J. E. (2003). Predation on zooplankton by large jellyfish, Aurelia labiata, Cyanea capillata and Aequorea aequorea, in Prince William Sound, Alaska. Mar. Ecol. Prog. Ser., 246, 137-152. Remane, A. (1934). Die Brackwasserfauna. Verh. Dtsch. Zool. Ges., 36, 34-74. Riley, E. T. & Prepas, E. E. (1985). Comparison of the phosphorus-chlorophyll relationships in mixed and stratified lakes. Can. J. Fish. Aquat. Sci., 42, 831-835. Rout, N. P. & Shaw, B. P. (1998). Salinity tolerance in aquatic macrophytes: probable role of proline, the enzymes involved in its synthesis and C4 type of metabolism. Plant Sci., 136, 121-130. Rout, N. P. & Shaw, B. P. (2001). Salt tolerance in aquatic macrophytes: possible involvement of the antioxidative enzymes. Plant Sci., 160, 415-423.
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Sandberg, J., Elmgren, R. & Wulff, F. (2000). Carbon flows in Baltic Sea food webs – a reevaluation using a mass balance approach. J. Mar. Syst., 25, 249-260. Savino, J. F. & Stein, R. A. (1989). Behavioural interactions between fish predators and their prey: effects of plant density. Animal Behav, 37, 311-321. Schneider, G. (1989). Estimation of food demands of Aurelia Aurita medusae populations in the Kiel Bight/Western Baltic. Ophelia, 31, 17-27. Schneider, G. & Behrends, G. (1994). Population dynamics and the trophic role of Aurelia aurita medusae in the Kiel Bight and western Baltic. J. Mar. Sci., 51, 359-367. Smith, V. H. (1979). Nutrient dependence of primary productivity in lakes. Limnol. Oceanogr, 24, 1051-1064. Sogard, S. M. & Able, W. (1991). A comparison of eelgrass, sea lettuce macroalgae, and marsh creeks as habitats for epibenthic fishes and decapods. Estuar. Coast. Shelf Sci., 33, 501-519. Suchman, C. L. & Brodeur, R. D. (2005). Abundance and distribution of large medusae in surface waters of the northern California Current. Deep-Sea Res., II 52, 51-72. Vollenweider, R. A. (1968). The scientific basis of lake eutrophication, with particular reference to phosphorus and nitrogen as eutrophication factors. Tech. Rep., DAS/DSI/68.27, OECD, Paris, 159. Wallin, M., Håkanson, L. & Persson, J. (1992). Belastningsmodeller för närsaltutslepp i kustvatten – speciellt fiskodlingars miljöpåverkan. Nordiska ministerrådet, 1992, 502, Copenhagen, 207 (in Swedish). Walters, C. J., Christersen, V. & Pauly, D. (1997). Structuring dynamic models of exploited ecosystems from trophic mass-balance assessments. Rev. Fish Biol. Fish., 7, 139-172. Walters, C. J., Christersen, V., Pauly, D. & Kitchell, J. F. (2000). Representing density dependent consequences of life history strategies in aquatic ecosystems: Ecosim II. Ecosystems, 3, 70-83. Winberg, G. G. 1985). Main features of production process in the Naroch lakes. Ecological system of Naroch lakes. Minsk, 269-284 (in Russian). Winfield, I. J. (2004). Fish in the littoral zone: ecology, threats and management. Limnologica, 34, 124-131.
In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 119-151 © 2011 Nova Science Publishers, Inc.
Chapter 4
FORM AND FUNCTIONING OF MICRO SIZE INTERMITTENT CLOSED OPEN LAKE LAGOONS (ICOLLS) IN NSW, AUSTRALIA
1
W. Maher1, K. M. Mikac2, S. Foster1, D. Spooner1 and D. Williams1
Ecochemistry Laboratory, Institute for Appled Ecolgy, University of Canberra, Bruce, ACT, Australia. 2 Institute for Conservation Biology and Environmental Management, University of Wollongong, Wollongong, NSW, Australia.
ABSTRACT ICOLLs are considered to be one of the most ecologically productive ecosystems on earth. Similar to other coastal water bodies, ICOLLs lie at the interface of marine, freshwater and terrestrial systems and therefore represent highly dynamic transition zones between river/creek catchments and near-shore coastal waters. ICOLLs often act as net sinks of land derived sediments and nutrients; mature systems are believed to act as a source of organic material and nutrients to the adjacent sea. Suzuki et al., (1998) describes ICOLLs as having unique structural and functional characteristics as a consequence of their position in the landscape, thus having large spatial and temporal variability in their environmental and (consequently their dependant) biological variables. The focus for this chapter is micro size ICOLLs, classified as any coastal water body that has: (i) the presence of barrier beach, spit or series of barrier islands that can restrict oceanic exchange; (ii) a surface water area of less than 0.5 km2 (iii) the retention of all or the majority of the water mass within the lagoon during low tide in the adjacent sea; and (iv) the capacity of to remain brackish to fully saline either by percolation through and/or overtopping through inlet/outlet channels.
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W. Maher, K. M. Mikac, S. Foster et al. ICOLLs can be viewed in a hierarchical manner, with the ocean and catchment influencing other smaller scale processes. Characteristics of the catchment and oceanic regimes influence water quality, tidal regime, stream flow, sediment delivery and seston within an ICOLL. Flow regimes and sediment loads in turn affect ICOLL morphology and sediment composition, such as nutrient status and organic matter composition. Alterations in catchment flow can either increase the residence time of water within an ICOLL increasing the susceptibility to eutrophication or decrease the residence time possibly leading to nutrient limiting conditions. In turn, these attributes determine the biological diversity and functioning of these systems.
1. INTRODUCTION AND DEFINITION Intermittently Closed and Open Lake Lagoons (ICOLLs) are a common feature of the NSW coastline, occupying approximately 92 % of all New South Wales estuarine waters (Williams et al., 1998). ICOLLs are coastal bodies of saline water (Figure 1), either wholly or partially separated from the adjacent sea, by one or more restricted inlets (Bird, 1967a, b, 1994; Mee, 1978). They are characterised as having largely varying salinities e.g. hyposaline to hypersaline (Kjerfve, 1986, 1994; Bamber, 1998), and often as being stagnant and brackish (ie: 5-20ppt) in nature (Ward and Ashley, 1989; Tagliapietra et al., 2009). ICOLLs are considered to be one of the most ecologically productive ecosystems on earth (Boynton et al., 1996). Similar to other coastal water bodies, ICOLLs lie at the interface of marine, freshwater and terrestrial systems and therefore represent highly dynamic transition zones between river/creek catchments and near-shore coastal waters (Edgar and Barrett, 2000). ICOLLs often act as net sinks of land derived sediments and nutrients; mature systems are believed to act as a source of organic material and nutrients to the adjacent sea (Kjerfve and Magill, 1989; Cognetti and Maltagliati, 2000). Suzuki et al., (1998) describes ICOLLs as having unique structural and functional characteristics as a consequence of their position in the landscape, thus having large spatial and temporal variability in their environmental and (consequently their dependant) biological variables. On the south eastern coast of NSW they provide a habitat for commercially important fish stocks (Griffiths, 2001), and are sanctuaries for many migrating demersal nektonic species (e.g. shrimps, crabs, spots, flounders) that depend on shallow lagoonal habitats as nursery areas for early development (Boynton et al., 1996). Of all the systems that are inherent to the coastal environments, ICOLLs have the greatest potential to become eutrophic (Comin and Valiela, 1993; Boynton et al., 1996; Menendez and Comin, 2000). Reduced flushing, shallow waters, and often silt/clay sediment composition all contribute to accelerate eutrophication. NSW coastal lakes are under immense pressure, and almost all have been modified with approximately 60% classified as degraded and in need of comprehensive or significant protection (HRC, 2002). One of the main problems associated with this assessment was the lack of data for micro size ICOLLs along the south coast of NSW, which highlight the requirement for future research priority. To provide the focus for this chapter a micro size ICOLL will be classified as any coastal water body that has:
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 121 (i) the presence of barrier beach, spit or series of barrier islands that can restrict oceanic exchange; (ii) a surface water area of less than 0.5 km2 (iii) the retention of all or the majority of the water mass within the lagoon during low tide in the adjacent sea; and (iv) the capacity of to remain brackish to fully saline either by percolation through and/or overtopping through inlet/outlet channels.
Figure 1. Morphology and sediment facies of micro-size ICOLLs. A: Brackish Creeks (Wimbie Creek); B: Broad Basins (Kianga Lake); C: Floodplain brackish creeks (Congo Creek)
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Figure 2. Hierarchical effects in ICOLLs
ICOLLs can be viewed in a hierarchical manner; with the ocean and catchment influencing other smaller scale processes (see Figure 2). Characteristics of the catchment and oceanic regimes influence water quality, tidal regime, stream flow, sediment delivery and plankton within an ICOLL (Kench 1999; Loneragan and Bunn 1999; Roshanka and Pattiaratchi 1999; Cooper 2001; Roy et al. 2001). Flow regimes and sediment loads in turn affect ICOLL morphology and sediment composition, such as nutrient status and organic matter composition (Harris 2001b). In turn, these attributes determine the biological diversity and functioning of these systems. Alterations in catchment flow can either increase the residence time of water within an ICOLL increasing the susceptibility to eutrophication or decrease the residence time possibly leading to nutrient limiting conditions (Cooper 2001).
2. PHYSICAL FEATURES ICOLLs are located at the transitional zone between rivers and oceans and often act as net sinks of land derived sediment and nutrient inputs (Kennish, 1986; Kjerfve, 1994). ICOLLs may have one or multiple entrances to the sea that are intermittently open or closed to the ocean (Kench, 1999). These shallow systems are often found behind barrier islands and sand spits and are conspicuous physiographic features of continental land margin around the world (Boynton et al., 1996). The movement of sediment into these water bodies is part of an evolutionary process and changes the morphology and bathometry of the ICOLL basin (Kennish, 1986). Accelerated
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 123 infilling caused by increased catchment sediment loads can sometimes ‗in fill‘ coastal ICOLLs, although the isolation of the water body from the ocean is the true cause of their demise (Hodgkin, 1998). The different stages of isolation of ICOLLs to the ocean have also been attributed to differences in ICOLL volume and varying catchment discharges (i.e. sporadic or consistent) (Hodgkin, 1998). The location of the ICOLL entrance in relation to the inherent coastal features that shelter them from prevailing wind and ocean waves is also an important physical aspect of ICOLLs (Hodgkin, 1998). The formation of the barrier that restricts oceanic exchange is reliant on shoreline drift of marine sands that accumulate at the entrance of the ICOLL (Kennish, 1986). During high river discharges the barrier can be breached allowing tidal inflow and exchange. Understanding of the ecological and hydrological consequences of these breaches within south eastern Australian ICOLLs are limited (Pollard, 1994; Wiecek and Floyd, 2006; Gale et al., 2007). In Australia, ICOLLs are found where high wave energy, microtides (ie: tidal amplitude <2 m), low fluvial discharge and low coastal relief dominate (Bayly, 1971; Digby et al., 1999). These oceanographic and terrestrial forces act synchronously to produce ICOLLs (Bird, 1967a, 1994; Digby et al., 1999). In Australia, ICOLLs are noticeably absent on coastlines characterised by high retreating cliffs e.g. Great Australian Bight, and where macrotides dominate e.g. Northern Australia (Bird, 1994; Digby et al., 1999). Bird (1967a) demonstrated that ICOLLs are well represented throughout the southern seaboard of Australia, and although a great variation in lagoon morphology occurs, similar general physico-chemical and biological processes operate in most south eastern Australian ICOLLs.
3. MORPHOLOGY ICOLLs display high morphological variability (Figure 1 and 3), and have been previously described as either brackish creeks (Stanton et al. 1999), or barrier lagoons (Bird 1994; Kjerfve 1994; Cooper 2001). Brackish creeks are typically narrow creeks with a single entrance to the ocean, usually with a sand bar built up to around the high tide level (Stanton et al. 1999). Brackish creeks are also usually narrow shallow channels that have a small surface area (Stanton et al. 1999; Mikac et al. 2007). Barrier lagoons on the other hand can have single or multiple entrances with a narrow entrance opening out to a larger shallow lagoon/lake (Kjerfve 1994). Digby et al. (1999) and Gregory and Petrie (1994) described numerous physical characteristics that can be easily measured to define the morphology of estuaries, some of which are pertinent to ICOLLs (e.g. Haines et al. 2006). The morphological features that best classify micro sized ICOLLs on the south east coast of New South Wales are: Cross sectional ratio – ratio of average width of the ICOLL to the average width of the mouth. Describes the general shape of the lagoon i.e. values <1 indicate a narrow entrance opening out into a wide lagoon, whereas values >1 indicate a wide entrance narrowing toward the back. ICOLLs with a value <1 would tend to restrict tidal flow when open while ICOLLs with values >1 would facilitate tidal flushing (Gregory and Petrie 1994).
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W. Maher, K. M. Mikac, S. Foster et al. ICOLL surface area (km2) – Measurement of the surface area of the ICOLL (Digby et al. 1999). Length to width ratio – length to width ratio is an indicator of the geometry of the ICOLL i.e. long and narrow to short and wide (Gregory and Petrie 1994). Fluvial flow – Fluvial flow is a ratio of mean annual rainfall runoff to the volume of the lagoon. Fluvial flow is an indication of the ICOLLs buffering capacity i.e. ICOLLs with low fluvial flow have smaller volumes of water entering from the catchment in comparison with the ICOLLs volume therefore, expected changes in the water characteristics (salinity) would be attenuated (Digby et al. 1999). Fluvial flow is calculated using the equation: FF = (P × A × Ceff) ÷ V
Figure 3. Cross sections of the berm (entrance channel), middle and basin in ICOLLs. A: Brackish Creeks (Wimbie Creek); B: Broad Basins (Kianga Lake); C: Floodplain brackish creeks (Congo Creek).
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 125 Where FF is fluvial flow; P is the mean annual precipitation; A is the area of the catchment under a single land use; Ceff is the rainfall runoff coefficient for the land use; V is the volume of the ICOLL. Three main morphologies are present in ICOLLs of the southeastern coast of NSW, and have been classified based on their physical features as brackish creeks, lake lagoons and floodplain lagoons (Figure 1). The morphology of ICOLLs is a reflection of the topography of the catchment. Brackish creeks characteristically have high cross sectional ratios and high fluvial flows, which together with their small water volumes have little capacity to attenuate inputs from the catchment or the ocean. Brackish creeks have pronounced boom bust cycles and are highly variable environments in respect to their water quality (Foster, 2002; Mikac et al. 2007). Brackish creeks tend to occur in coastal environments with steep catchments with little to no flood plain, these are the most common type of ICOLL occurring on the south east coast of NSW. Lake lagoons characteristically have large surface areas and high length to width ratios and low fluvial flows. Lake lagoons are the most stable type of small ICOLL (i.e. <0.5 km2) in respect to their water quality as they have greater buffering capacity due to their large water volumes, which acts to attenuate inputs (i.e. smaller oceanward openings in relation to their body and low fluvial inputs in relation to their volume). Lake lagoons typically occur in moderately sloped catchments with some flood plain development. Floodplain lagoons occur in large catchments with low catchment slopes and moderate fluvial flows. These ICOLLs are long and sinuous along their length and have well defined floodplains. Floodplain lagoons tend to be flanged with the seaward opening larger than the ICOLL body, causing greater tidal influence when the ICOLL is open to the ocean. Many of the processes involved in the geomorphological evolution of ICOLLs are similar to the processes involved in river systems (i.e. floodplain development) (Vannote et al. 1980). Lake lagoon ICOLLs would be classified as being in the early to middle stages of geomorphological evolution and flood plain ICOLLs in the latter stages (Digby et al. 1999). It would be difficult to place brackish creeks into a geomorphological class due the lack of floodplain development and depositional features (Digby et al. 1999). Cooper (2001), agues that scouring during flood events would result in the removal of much of the accumulated sediments “thus resetting the evolutionary clock”. It can be expected that flood events will occur with more frequency in steeper catchments (i.e. greater fluvial flow), it would be anticipated that brackish creeks would tend not to follow the accepted hypothesis of shallowing with age (Roy et al. 2001).
4. CATCHMENT CHARACTERISTICS AND HYDROLOGICAL PROCESSES 4.1. The Influence of Catchment Characteristics on ICOLLs Catchments can be viewed as functional geographic units that integrate a variety of environmental processes and anthropogenic effects on the landscape (Post and Jakeman 1996; Aspinall and Pearson 2000). Both Edgar and Barrett (2000) and Harris (2001b) found that changes in land-use within coastal catchments affected both the quantity and quality of material entering estuaries. Estuaries form the terminal point in a catchment where all water
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leaves the river system and enters the ocean (Frissell et al. 1986). In this respect estuaries form the interface between the terrestrial and oceanic environments (Edgar and Barrett 2000; Cooper 2001). ICOLLs are often separated from the ocean by a barrier of sand, and during periods of freshwater input from the catchment, act as sinks for all the products exported (e.g. sediment, organic matter, nutrients and pollutants) (Kench 1999). As such, catchment exports play a vital role in the health and function of ICOLLs (Heap and Harris 2002). Changes in the amount of sediment, organic matter and nutrients will affect the functioning of these ecosystems, by altering their physical, chemical and biological nature (Hopkinson Jr and Vallino 1995; Harris 2001a, b; Cooper 2001). The physical features of a catchment such as slope, land cover, soils types, drainage density, shape and size of the catchment, as well as urban infrastructure govern the movement of water and associated constitutes (i.e. sediment, nutrients and organic matter) through the catchment (Calow and Petts 1994; Post and Jakeman 1996; Harris 2001b; Jennings and Jarnagin 2002). The volume and velocity of water through the catchment is crucial in determining the morphology of ICOLLs, such as the shape of the water body, entrance morphology, internal depositional characteristics and the opening and closing regimes of the ICOLL (Bell and Edwards 1980; Sklar and Browder 1998; Cooper 2001, Roy et al. 2001).
4.2. Catchment Hydrology Australia is the driest inhabited continent, with a large variation in runoff compared to the rest of the world. Many of Australia‘s rivers and streams are ephemeral. Hydrographs often show a rapid rise in stream level followed by a sharp decline with long periods of little or no flow (Croke and Jakemen 2001). ICOLLs receive most of their freshwater input during high rainfall events (Pollard 1994). As a result of their small catchment areas, ICOLL inlets are often blocked for extended periods by sand deposited by wave action. They are only open when there is a sufficiently large storm where storm water inflow raises the water level such that the berm is breached or when there are large waves overtopping the berm. The unpredictable nature of rainfall on the South Coast of NSW results in erratic opening of ICOLLs. The frequency and magnitude of rainfall events determines the frequency of entrance opening. Under low stream flow conditions, water inputs are balanced by water losses through evaporation and seepage and the entrance remains closed (Figure 4a). Wave energy will maintain the berm and over washing will top up lagoons and maintain brackish water conditions. Storm events of sufficient magnitude will incise a channel and cause the berm to breach (Figure 4b). The depth of incision will determine how much of the ICOLL is drained. Wave action will normally re-establish the berm within 1-2 weeks and the lagoon water level will remain low unless refilled by runoff or tidal exchange (Figure 4c). Streams and rivers serve as rapid conduits for water and anthropogenic nutrients to estuarine and coastal marine environments (McMahon, 1998; Smith, 1999). Slope determines the velocity of the surface runoff that governs the erosive potential and the transport capacity of the flow (Lepisto et al., 1995; Croke and Jakeman, 2001). Hill slope erosion across Australia has increased 100-fold in historical times as a result of catchment clearing and agricultural land use (Prosser, 2001). Smaller catchments are often steeper which tends to
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 127 induce greater sediment movement and subsequent sediment yield. During periods of high rainfall and runoff, exports of sediment, nutrients and organic matter tend to be higher (Harris 2001a, b). This often causes characteristic sediment plumes from the river into the ocean from estuaries, however, as ICOLLs are closed for the majority of the time, these sediments and associated material are trapped within the ICOLL and can have a great affect upon the water quality and sediment composition within the ICOLL.
Figure 4. ICOLL hydrology. A: ICOLL full; B: Berm breeched; C: Berm rebuilt, ICOLL drained (Wimbie Creek)
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5. PHYSIOCHEMICAL FEATURES The physicochemical composition of ICOLLs is highly variable (Figure 4) depending on runoff, wave action and whether the ICOLL entrance is open or closed (Mikac, 2001; Foster, 2002). The period of closure will also influence water composition (Wiecek and Floyd, 2006; Scanes et al., 2007).
5.1. Salinity and pH Salinity regimes within ICOLLs depend on the ratio of fresh water inflow, overtopping, tidal exchange and evaporation. If the entrance is closed and stream flow is low, ICOLLs are generally brackish (15-25 % S) and increase in salinity over time if evaporation exceeds the fresh water input. ICOLLs can also be stratified with a denser saline layer (36 % S) in deeper areas. Increased stream flow can result in a surface layer of fresh water or a reduction in salinity. It is common to find a lens of nearly fresh water (8-10 % S) over a deeper layer of brackish water (16-25 % S). Once the berm is breached, the ICOLL can become completely fresh although saline layers in deeper areas will persist. Depending on how long the entrance is open, tide height and storm activity, salinity can vary from brackish to sea water due to over washing and tidal exchange. pH will also change with variations in storm water inflows and salinity. Fresh water pH varies between 5.5-6.5 while brackish water tends to have a similar pH to sea water (pH 8).
5.2. Temperature The temperature of the bulk of ICOLL water generally reflects the ambient air temperature and varies seasonally from 5 - 40 oC. However, overtopping or filling by seawater can substantially modify water temperature depending on the ambient seawater temperature. Seawater temperature along the South Coast varies from to 11 -21 oC and doesn‘t follow a seasonal pattern. Thus ICOLL water temperature will be highly dependent on if the ICOLL is open or closed. the period of closure and prevailing sea water temperature. Similarly, water temperature of the deep saline layer, if present, will be also depend on the ambient seawater temperature. These deep saline layers can be warmer than the overlying water depending on the seawater temperature, ambient air temperature and decomposition of organic matter, which generates heat.
5.3. Dissolved Oxygen Dissolved oxygen concentration is also highly variable depending on the source of the water, ambient temperature, water stratification and biological activity. Normally if ICOLLs are open or surface flow is occurring, dissolved oxygen concentrations are 40-100% saturation. Over washing of seawater raises the oxygen levels, as seawater is generally 100% saturated with oxygen. Catchment runoff brings water in that is oxygen saturated but also
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 129 brings in organic matter that through respiration lowers oxygen concentrations. On closure, ICOLLs oxygen concentrations can vary from 0-140 % saturation. Over a 24 hour period, oxygen concentrations can drop to 0 % saturation at night especially if a deep stratified saline layer is present, and depending on the presence of algae recover to 50-80 % saturation during day light hours. Prolonged deoxygenation will led to the mortality of organisms while hypoxia (< 10% saturation) will effect growth, feeding and metabolic rates (Gray et al. 2002). Many ICOLLs have extensive mats of benthic attached algae during summer. In shallow, non turbid ICOLLs, oxygen concentrations can become supersaturated (100-140%) due to algae photosynthesis.
5.4. Nutrients As most nutrients enter ICOLLs bound to suspended particulates, the concentration of dissolved phosphorus (< 1 g/l), dissolved nitrogen (5-10 g/L) and ammonia (2-10 g/L) are normally low (Mikac, 2001; Foster, 2002; Mikac et al., 2007). Inputs of dissolved nutrients from septic sewage systems and sewer overflows during periods of high rainfall can result in short lived elevation of nutrient concentrations (P: 3-5 g/L; N: 20-30 g/L) especially ammonia (20-90 g/L). Low water column nutrient concentrations limit phytoplankton growth such that attached benthic algae are the most common algae growth (Nozais et al. 2001).
5.5. Colour During periods of low flow, ICOLLs are generally non-turbid and highly coloured from the release of tannins from decomposing organic litter. Together with the low soluble nutrient concentrations, tannins may limit phytoplankton growth. We have shown in our laboratory that the growth of algae species such as Chaetamorpha, Oscillatoria and E. ralfsii are inhibited by highly coloured water derived from tannins (Dalton et al. unpublished).
6. SEDIMENT COMPOSITION 6.1. Grain Size Patterns of sedimentation in coastal water bodies are highly heterogeneous and vary according to hydrological processes e.g. river discharge, tidal flow and catchment inputs (Dyer, 1979). Bird (1994) proposed a general sedimentation model for ICOLLs. This model suggested that coarser material e.g. sand and gravel, is deposited as the river/creek enters the lagoon, while the finer sediment e.g. silt/ clay, is carried out into the lagoon and deposited throughout the central basin. Sediments enter coastal lagoons from oceanic and fluvial sources (Bird 1967b; Kennish 1986). The terrestrial and coastal geology influence the types of sediments available for transport (Thornton et al. 1995). A number of factors can affect the transport and spatial
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distribution of sediments in ICOLLs e.g. salinity, surface runoff, tidal influence (Dyer 1979; Thornton et al. 1995; Kench 1999). In general, coarse sediments of fluvial sands and gravel are deposited where the river meets the lagoon, the finer sediments of silt and clay are carried further and, through the process of flocculation, deposited within the central basin, with wave action carrying oceanic sand into the mouth of the lagoon (Dyer 1979; Bird 1994). Sediments are a depository for organic matter, nutrients and contaminants (Thornton et al. 1995). The sediments in microsize ICOLLs consisted mainly of sand at the seaward end with increasing silt upstream (Figure 1). This is typical of south eastern Australian coastal lagoons (e.g. Allan et al., 1985) from which marine sand is transported (and eventually deposited) into ICOLLs by ocean currents and wave action (Owen, 1978). However, Mikac et al. (2007) found that the ICOLLs in catchments dominated by urban development had greater % silt/clay. Silt/clay is a covariate of urbanisation, where % silt/clay increases as urbanisation increases (Edgar and Barrett, 2000). Hume and McGlone (1986) have shown that the deforestation of catchments for urban development increases the peakedness and frequency of catchment high flows and results in an increase in the loads of fine sediment deposited into coastal water bodies. Once the catchment is developed the soil is stabilised, however, the peakedness of flows increases further because of the development of sealed areas and stormwater systems (Hume and McGlone, 1986). Stormwater systems, of urbanised areas in particular, are known to carry large quantities of fine sediment, organic material, nutrients and contaminants to coastal water bodies (Dennison and Abal, 1999). In addition, Mikac et al. (2007) found that an increase in the % silt/clay of sediments was associated with an increase in sediment total organic carbon, nutrient (total nitrogen and phosphorus) and trace metal concentrations (lead, copper, cadmium and zinc). It should be noted that concentrations of these nutrients and trace metals did not exceed benchmark levels as recommended by Australian water and sediment quality guidelines (ANZECC/ARMCANZ, 2000). Rather, silt and clay have a large sorption capacity and thus locations with greater % silt/clay have a greater potential to bind and scavenge organic matter, nutrients and trace metals (Kennish, 1986; Arakel, 1995). In particular, fine sediments have an immense sorption capacity because of their large surface area to volume ratio and high surface charge to mass ratio (Arakel, 1995). The effects of ICOLL opening and closing on the sediments of the system are vast. If an ICOLL is closed for extended periods, the system will be subjected to greater influence of land derived sediments (usually fine sediments) that accumulate in the absence of diurnal tidal scouring and near coast sand deposition.
6.2. Nitrogen and Phosphorus Phosphorus and nitrogen are considered macronutrients, as they are essential for biological processes (Deeley and Paling 1999). Typically in uncontaminated ICOLLs, nitrogen and phosphorus concentrations vary from 20-100 and 5-80 g/g respectively with higher concentrations in silt than sand. Nutrients enter ICOLLs attached to sediments, humic material or in organic matter, either through catchment runoff, inputs from the ocean, precipitation or the decomposition of biota (Kennish 1986; Thornton et al. 1995). Most nutrients entering ICOLLs are found in the finer sediments of silt and clay (Thornton et al. 1995; Harris 2001b). Nutrients can be reintroduced into the water column by chemical,
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 131 physical and biological processes such as changes in pH and redox, bioturbation and bioirrigation (See Section 6.4; Thornton et al. 1995). Under oxic conditions, phosphorus is usually bound with iron (Fe) in the sediments and nitrate converted to nitrogen gas through the process of denitrification (Aston 1980; Heggie et al. 1999). Under low pH and/or anoxic conditions phosphorus can be liberated from sediments and nitrogen released into the water column as ammonia (Figure 5 and 6) (Aston 1980; Hatcher 1994; Thornton et al. 1995; Heggie et al. 1999). ICOLLs are generally nitrogen limited, with increases in nitrogen shown to stimulate algal growth (Harris 2001b). Nutrient concentrations within ICOLLs sediments have been shown to be highly seasonal and ICOLL specific (e.g. Schallenberg et al., 2010).
6.3. Organic Matter Organic matter enters estuaries both internally through the decay of fauna and fauna and externally through inputs from the catchment (leaf litter fall, leaching of soils) and ocean (seaweed, biota) (Kennish 1986). Typically in uncontaminated ICOLLs, organic carbon concentrations vary from <0.01-10 % respectively with higher concentrations in silt relative to sand. Large quantities of organic matter can enter ICOLLs during periods of high fluvial inputs (Day 1981) and in some ICOLLs the extensive accumulation of dead seaweed also occurs. Within estuaries organic matter is the primary food source for many benthic organisms (Morrisey 1995). Large quantities of organic matter can adversely affect water quality by producing anoxic conditions leading to sulphate reduction and the production of hydrogen sulphide gas (H2S) (Burton 1976). Hydrogen sulphide per se, should not be viewed as a problem as some polychaete species eg Capitella sp. require hydrogen sulphide as a settlement cue (Cuomo, 1985).
6.4. Biogeochemical Nutrient Cycles Benthic sediments in shallow coastal embayments (i.e. ICOLLs) are the primary site for the mineralisation of organic matter (Fisher et al., 1982; Jorgensen and Revsbech, 1989; Heggie, 1999). These processes are primarily mediated by bacteria and contribute, together with catchment discharges, to the nutrient concentrations in the water column.
6.4.1. Nitrogen Inorganic nitrogen species NO3- and NH3+ are the most important because they are readily available for biological uptake (Herbert, 1999). Currently, the consensus is that denitrification ie the release of nitrogen as nitrogen gas, in closed systems with restricted oceanic exchange, plays a vital role in regulating, or removing, nitrogen out of the aquatic cycle (Figure 5). This is especially apparent in shallow Australian coastal systems where denitrification is primarily a sedimentary based process (Heggie et al., 1999).
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Figure 5. Nitrogen cycling in response to organic carbon loading
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Figure 6. Phosphorus cycling in response to organic carbon loading
During the cooler months of the year, or when labile organic matter is unavailable, bacterial metabolic activity is low, and the water column is well oxygenated. This situation promotes deep penetration of oxygen into benthic sediments that is utilised by bacteria to oxidize organic matter (ammonification), which is then oxidized further by nitrifying bacteria
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to nitrate (nitrification). In the anoxic microzones, which are vertically and horizontally distributed throughout the sediment profile, denitrifying bacteria reduce the nitrate to nitrogen gas that is released to the atmosphere (denitrification) (Figure 5a). Under these conditions biologically available nitrogen concentrations in the water column remain stable, and often limit phytoplankton and microphyte production. Once water temperatures increase and a source of organic carbon is available, the metabolic activity of heterotrophic bacteria increases and oxygen in the sediment profile is restricted to the surficial zone. Under these conditions, ammonification and nitrification is reduced and denitrification ceases (Figure 5b). Alternate electron acceptors are employed by the bacteria to mineralize the organic matter, and sulphate is the most likely source. Sulphate reduction of organic matter releases ammonia to the water column, which is directly available for biological uptake (Figure 5c). Large fluxes of ammonia to the overlying water column occur that support algal blooms and cause fish kills.
6.4.2. Phosphorus Organic carbon inputs also control the mobilisation of phosphorus from ICOLL sediments into overlying water. During the cooler months of the year, or when labile organic matter is unavailable, bacterial activity is low, and the water column is well oxygenated and little phosphorus is released. Sediments are oxidised and phosphorus complexes with iron. Thus phosphorus is effectively trapped in sediments (Figure 6a). When ‗fresh‘ labile organic matter is deposited to marine sediments oxygen is consumed and phosphorus is released from organic matter and iron oxide phases (Figure 6b). Under anoxic conditions H2S is formed and reacts with iron-phosphorus complexes. The capacity of the sediment to retain the phosphorus is drastically reduced and a larger phosphate fluxes occurs (Figure 6c). The mineralisation of organic matter and desorption from inorganic complexes have been identified as major sources of phosphorus for phytoplankton production in coastal marine environments (Nixon, 1981; McComb, 1998).
7. BIOLOGICAL FEATURES 7.1. Food Webs The biota of brackish ICOLLs comprises relatively few species when compared to stable marine habitats (Hammond and Synnot, 1994). Salinity is the prime factor in determining the types of organisms within ICOLLS. Organisms within ICOLLs need to cope with varying salinity and usually are opportunists such as polychaetes and shrimps, adapted to exploit space and resources following disturbances ie opening and closing regimes (Boesch, 1977). Generally, food webs in micro size ICOLLs are detritus based relying on allochthonous inputs from both terrestrial and marine sources (Hadwen and Arthington, 2006), as phytoplankton abundance is low because of low water column nutrient concentrations and tannins (see Section 5.4 and 5.5). Benthic communities dominate micro size ICOLLs with attached algae, microphytobenthos (Figure 7) and meso- and macro invertebrates being the dominant organisms (Figure 8). Fish that are mobile and efficient osmoregulators also thrive in ICOLLs (Figure 9) (Hadwen and Arthington, 2006).
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Figure 7. Typical algae and plants in ICOLLs
7.2. Algae and Plants As ICOLLs are relatively unstable environments and considerable redistribution of sand and sediment occurs, it is rare to find extensive seagrass beds or mangroves within microsize ICOLLs. Where these do occur in ICOLLs, it is in stable areas in which sand or sediment has accumulated and not remobilised. Fringing vegetation tends to be salt tolerant terrestrial species such as sedge, Juncus and Salt Bush (Atriplex). As mentioned in Section 5, phytoplankton abundance is normally low because of the low water column nutrient concentrations (Nozais et al. 2001) and the presence of tannins. Phytoplankton abundance tends to be higher in winter months than in summer months. Phytoplankton species abundance will be a function of ICOLL pH. Although some species grow well over a wide range of pH (6-10), some species growth rates are significantly
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influenced by pH (Hinga, 2002) with pH changes of 0.1 units causing observable changes in phytoplankton community structure. Any freshwater phytoplankton carried into ICOLLs die at salinities greater than 8% S (McLusky, 1989). Also in some ICOLLs it has been found that phytoplankton growth is governed by the opening and closing regimes of the system, with some ICOLLs experiencing greater phytoplankton chlorophyll a concentrations during closure with the opposite being found for others (Schallenberg et al., 2010). Nitrogen and phosphorus limitation and/or light limitation were other factors that were found to alter phytoplankton growth in ICOLLs (Everett et al., 2007; Schallenberg et al., 2010). Benthic attached filamentous algae such as Enteromorpha sp. form extensive mats in warmer months and decline in autumn. Microphytobenthos have been reported in the literature to exhibit strong seasonal fluctuations and not to be inhibited by low water column nutrient concentrations or light availability (Nozais et al 2001). Large populations of microphytobenthos (diatoms and other micro algae) also occur in silty-sandy sediments up to depths of 20 cm. These algae play an important role in maintaining the surface of sediments and overlying water in an oxygenated state (Peckol and Rivers, 1996) and are an important food source for macroinvertebrates. Little information is known about algal recruitment, competition or predation, the effects of disturbances and changes in pH, salinity and temperature in micro size ICOLLs. All of these factors are known to cause changes in the distribution and abundance of phytoplankton, filamentous algae and microphytobenthos (Hamilton et al. 2000). Processes are likely to be different in different ICOLLs.
7.3. Soft Sediment Macrofauna Soft-sediment macrofauna are marine invertebrates that live within the sediment bed that are retained on 1 or 0.5 mm sieves (Snelgrove and Butman, 1994). It has been suggested that the soft-sediment macrofauna when coupled with an assessment of their habitat parameters may be used as reliable indicators of anthropogenic or natural disturbance (e.g. Warwick, 1986, 1993; Deeley and Paling, 1999). In the microsize ICOLLs of southeastern Australia, Mikac et al. (2007) found a total of 20, 253 individuals belonging to 12 marine invertebrate families (Figure 8). The macrofaunal communities of the five ICOLLs examined consisted of polychaetes (Capitellidae, Nereididae, Sabellidae, Spionidae and Serpulidae), gastropods (Haminoeidae and Hydrobiidae), bivalve molluscs (Galeommatidae and Mytilidae) an amphipod (Melitidae) and isopod crustaceans (Cirolanidae and Sphaeromatidae). The macrofaunal assemblages of the microsize ICOLLs examined by Mikac et al. (2007) were typical of meso and macrosize ICOLLs in Australia (e.g. Hodgkin and Clark, 1988; Platell and Potter, 1996; Edgar et al., 2000b). The soft-sediment macrofaunal abundance and composition of an ICOLL is usually a function of its size and opening and closing regime (Hutchings, 1999). Although not directly examined by Mikac et al. (2007), opening and closing regimes are acknowledged as having a significant effect on overall taxa richness and assemblage composition. In that, the opening and closing regime is known to affect the habitat parameters (salinity, dissolved oxygen, sediment grain size and organic carbon content) of the macrofauna and therefore have an indirect effect. This is supported by Platell and Potter (1996) who show that not only does the
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 137 closure of Wilson‘s Inlet (a mesosize ICOLL in south-western Western Australia) prevent recruitment of macrofaunal larvae into the system but also determines the salinity regime of the water body.
Figure 8. Typical benthic macrofauna in ICOLLs
It is difficult to determine which specific abiotic variable is responsible for the pattern of macrofaunal assemblages in micro size ICOLLs, however, the habitat parameters found to best explain soft-sediment macrofaunal composition in large south eastern Australian ICOLLs include water quality (salinity, dissolved oxygen) and physico-chemical sediment variables (grain size, organic carbon content) (Weate and Hutchings, 1977; Hutchings et al., 1978; Powis and Robinson, 1980; Atkinson et al., 1981; Poore, 1982; Robinson et al., 1982; Gibbs, 1986). More recent work conducted by Platell and Potter (1996) and Mikac et al. (2007) have attempted to single out the habitat parameters of the macrofauna in micro- and meso- sizel ICOLLs. Platell and Potter (1996) found that a greater number of macrofaunal species were associated with sediment composition and also the biomass of an aquatic macrophyte Ruppia megacarpa. In turn, Mikac et al. (2007) found that the macrofauna of five microsize ICOLLs examined was largely a function of sediment composition. Where fine sediment and sandy substrata dominated, opportunistic polychaete taxa e.g. spionids, capitellids, nereids, and
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mollusc taxa e.g. hydrobiids and mytilids were numerically dominant. It is possible that these opportunistic macrofaunal taxa occur in disturbed locations because of their ability to reproduce quickly in unrestricted conditions afforded by new unexploited environments (Grassle and Grassle, 1974; Pearson and Rosenburg, 1978; Barnes, 1989). In ICOLLs, where large variability in abiotic variables is common, usually due to unpredictable opening and closing regimes, it is not surprising to find taxa that have life history characteristics e.g. rselected species, that enable them to exploit such environments. Mikac et al. (2007) demonstrated that microsize ICOLLs in NSW have similar macrofaunal taxanomic assemblages as larger Australian ICOLLs. The macrofaunal assemblages are also governed by opening and closing regimes, either directly, through macrofaunal recruitment when ICOLLs are connected to the sea or indirectly, through the effect opening and closing exerts on abiotic variables (i.e. water quality and physico-sediment quality) or macrofaunal habitat parameters within these systems.
7.4. Fish To date there are no publications on the ichthyofauna of micro size ICOLLs in south eastern Australia. However, the ichthyofauna of meso size ICOLLs have been investigated by Pollard (1994) and Griffiths (1999) and (2000). Both Pollard (1994) and Griffiths (1999) found similar species in the six ICOLLs examined by the authors. Both authors show that greater taxa richness and abundance of fishes occurred in the larger and more open of the ICOLLs examined. Pollard (1994) studied Lake Conjola, Swan lake and Lake Wollumboola (meso sized coastal lagoons) and found that the larger of these and the ICOLL that was open the most (i.e. Lake Conjola) had the most species and also the greatest abundance of these species. Pollard (1994) found species composition in the ICOLLs examined were similar to permanently open estuaries in eastern Australia. Griffiths (1999) found that fish abundance and taxa richness was a function of size and opening and closing regimes. In addition, the larger of the ICOLLs examined by Griffith (1999; i.e. Lake Illawarra), which was connected to the ocean more often, had a greater abundance of commercial and non-commercial species than the smaller and less frequently open ICOLL examined. The most common fish found by Griffiths (1999) in the three ICOLLs examined were Ambassis jacksoniensis (Lake Illawarra); Pseudogobius olosium (Shellharbour Lagoon); and Atherinosoma microstoma (Werri Lagoon). In addition, the commercially important species Mugil cephalus, Acanthopognus autralis and Myxus elongatus were also found. As well, both Pollard (1994); Griffiths (1999; 2001) showed that ICOLLs are important nursery areas for juvenile fish of both commercial and non-commercial significance. ICOLLs are also refugia as juvenile fish are protected from open ocean predators during ICOLL closure. Griffiths (1999) discusses the consequences of opening and closing of ICOLLs and suggests that although the consequences of such events are poorly documented in Australian ICOLLs (regardless of size), there is evidence that species composition and abundance are a function of the duration, frequency and time of ICOLL opening that may coincide with the recruitment period of a wide range of species and randomly increase the chance of other species entering the ICOLLs. As discussed in section 1.1, near shore and land based coastal processes determine the opening /closing regimes of ICOLLs. If these processes coincide
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 139 with recruitment periods of various fish species then ICOLLs that are connected to the sea are available to be recruited into. This is supported by Griffiths (2001) who found that the recruitment of Acanthopagrus australis occurred in marked phases when the ICOLL examined was connected to the adjacent sea.
Figure 9. Typical fish species in ICOLLs
Consequently the spatial and temporal variability of fish assemblages and their abundances within ICOLLs is often large because the patterns of assemblages in ICOLLs are a function of the opening and closing regimes. Not only does an intermittent opening and closing regime effect recruitment into the lagoon itself but also effects the general water quality of the lagoon. That is, when the ICOLL is closed from the adjacent sea for extended periods and freshwater versus saltwater inputs are greater, the resulting changed salinity
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profile of the ICOLL will favour euryhaline species and be detrimental to stenohaline species. The inherent variability in opening and closing regimes in ICOLLs is recognised as the driving force that determines the fish assemblages of ICOLLs, regardless of size, in south eastern Australia.
8. ANTHROPOGENIC CHANGES ICOLLs are not isolated ecosystems but intimately connected or nested within adjacent or larger systems (e.g. Frissell et al., 1986, See Section 4). ICOLLs represent systems that form part of a continuum from rivers and creeks to lagoons; from lagoons to the sea; and from the sea to the ocean (e.g. Vannote et al., 1980). These systems are inherently linked and thus a natural or anthropogenic disturbance or perturbation at one level inevitably has an effect at various other temporal and spatial scales within the system (Glasby and Underwood, 1996). Human activity in coastal catchments has been directly correlated with increased rainfall runoff and sediment loads (Hume and McGlone 1986; Harris 2001b; Jennings and Jarnagin 2002). Water carries particulate and soluble material through the catchment, into the coastal zone (Petts 1984). Alterations in the physical nature of the catchment can increase or decrease the amount of particulate and soluble material moving through the catchment, however, increased movement of material normally occurs (Petts 1984). The physical variability in ICOLLs is influenced by numerous factors whose effects coincide with different catchment characteristics that drive this variability (Cooper 2001). The morphology of ICOLLs increases the susceptibility of ICOLLs to changes in land-use (Heap and Harris 2002). Due to the presence of a barrier, ICOLLs lack tidal flushing (Cooper 2001; Heap and Harris 2002). This can lead to the build up of nutrients, sediments and other contaminants, which in turn can affect the ecological function of the ICOLLs through reduced sediment and water quality (Heap and Harris 2002). The morphology of an ICOLL can have a profound effect on the symptoms associated with eutrophication. The position of the entrance in relation to the shoreline drift can influence the opening regime; the estero can influence the exchange kinetics between the ICOLL and the adjacent ocean. Water residence time within the ICOLL influences the accumulation of organic matter, high water residence time often correspond to increased potential for eutrophication symptoms. Unlike permanently open estuaries which are flushed diurnally (Kennish, 1986), ICOLLs are usually closed off from the adjacent sea and thus susceptible to changes in land use practices in their catchments (Zann, 1995; Inglis and Cross, 2000; Mikac et al., 2007). It is widely accepted that anthropogenic activities effect estuarine ecosystems and in numerous instances have resulted in large-scale alterations of their natural communities (Edgar et al., 1998; Edgar and Barrett, 2000). Bucher and Saenger (1991) showed that 70 % of the 738 coastal water bodies dominating the Australian coastline have deforested catchments and associated poor water quality, yet they represent habitats with moderate to high fisheries and conservation value. More alarming is the recent trend in ICOLL degradation (Edgar et al., 2000; Edgar and Barrett, 2000). Zann (1995) and Hutchings (1999) reported that mesosized ICOLLs of the densely populated south eastern and western Australian coastlines are under immense threat from the adverse effects of urbanisation.
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8.1. Changes in Catchment Land-Use, Hydrology and Water Quality It is well established that deforestation associated with urban or commercial development increases the peakedness and frequency of catchment high flows and fine sediment runoff to estuaries (Hume and McGlone, 1986). Once the catchment is developed the soil is stabilised and although sediment runoff decreases, the peakedness of flows increases further because of the development of sealed areas and stormwater systems (Hume and McGlone, 1986). This is supported by numerous authors who have demonstrated that changes in land use have effects, usually considered to be adverse, on the receiving system‘s physical, chemical and biological components (Loughran et al., 1986; Hogg and Norris, 1991; Arakel, 1995; Zann, 1995; Stromberg et al., 1998; Dennison and Abal, 1999; Foster and Lees, 1999; Harris, 1999). Stormwater and sewage discharges from urbanised catchments contain fine sediments, nutrients, organic material, heavy metals, pesticides, oils and hydrocarbons (Deeley and Paling, 1999). Elevated concentrations of trace metals, toxic to fauna, are readily stored in the sediments and act as an intermittent source of contamination (Arakel, 1995; Birch, 1996, 2000). Trace metals such as cadmium, lead, copper and zinc have become serious contaminants throughout Australian coastal water bodies (Birch, 2000). Physical alterations to catchments as a result of commercial, urban or industrial development e.g. impervious surfaces, drainage systems etc., are exacerbated by urban non-point source discharges which aid in the rapid deterioration of water and physico-chemical sediment quality (Aelion et al., 1997; Corbett et al., 1997; Wahl et al., 1997; Dennison and Abal, 1999).
8.2. Changes in Biological Communities Both natural and anthropogenic disturbances may affect the overall pattern of macrofaunal assemblages temporally and spatially in an ICOLL. The habitat parameters found to explain soft-sediment macrofaunal composition in south eastern Australian ICOLLs include a combination of water quality and physico-chemical sediment variables (Weate and Hutchings, 1977; Hutchings et al., 1978; Powis and Robinson, 1980; Atkinson et al., 1981; Poore, 1982; Robinson et al., 1982; Gibbs, 1986; Mikac et al., 2007). As indicated in previous sections of this chapter, the water quality and physico-chemical sediment variables of ICOLLs are a function of opening and closing regimes and catchment activities i.e. land use. Numerous biotic indices may be used to summarise the response of organisms to anthropogenic/natural disturbance and stress. Biotic indicators of anthropogenic or natural stress or disturbance include ecological measures such as taxa richness, relative taxa abundance, taxa diversity, biomass and size strata (Deeley and Paling, 1999). Indices of biotic integrity are most popular for assessing anthropogenic disturbance/stress or ecosystem health and three biotic metrics are commonly used: (1) taxa richness and composition including indicator taxa e.g. capitellids, nereids and spionids are usually indicative of disturbed/ contaminated locations; (2) trophic composition or the proportion of taxa belonging to different feeding groups e.g. the proportion of suspension feeders compared to deposit feeders; and (3) mean abundance of individuals belonging to a particular taxonomic grouping or feeding guild (Deeley and Paling, 1999). In microsized ICOLLs in southeastern Australia,
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Mikac et al. (2007) reported a significant increase in spatial heterogeneity/variability of macrofauna between control and impact (urban) locations. The author found that in impacted locations there was a shift towards more opportunistic taxa e.g. polychaetes, compared to the less opportunistic/conservative taxa found at control locations. Others have found that in anthropogenically disturbed locations opportunistic polychaete e.g. spionids, capitellids, nereids, mollusc e.g. hydrobiids (Pearson and Rosenburg, 1978) and mytilid taxa (Grassle and Grassle, 1974; Desrosiers et al., 1990), numerically dominate. The combined effects of urban/commercial/industrial development on the macrofauna of coastal water bodies have been difficult to determine (Edgar and Barrett, 2000; Inglis and Kross, 2000). However, numerous correlative and descriptive publications have provided convincing evidence to demonstrate a direct link between changes in community composition e.g. increase in opportunists usually deposit feeding polychaetes, and reduced water and physico-chemical sediment quality e.g. organic contamination (Grassle and Grassle, 1974; Pearson and Rosenburg, 1978) and trace metal contamination (Inglis and Kross, 2000). The observed decline in suspension feeders and the increase of deposit feeders in organic and/or contaminant rich sediments is widely accepted (Pearson and Rosenburg, 1978; Warwick, 1986; Clarke and Warwick, 1994; Inglis and Kross, 2000). That is, there is a change from large bodied, long-lived, iteroparous k- selected species to r-selected species (MacArthur and Wilson, 1967; Pianka, 1970). The later are characteristically small bodied, short-lived species that are able to reproduce quickly and readily colonise disturbed locations (MacArthur and Wilson, 1967; Pianka, 1970). The spatial distribution of environmental variables and contaminants within coastal water bodies is variable, with the foci of accumulation occurring near major sources of contamination or in depositional environments where fine sediments and organic matter accumulate (Morrisey et al., 1994; Inglis and Kross, 2000). Inglis and Kross, (2000) proposed that if contaminants are haphazardly distributed, changes in the soft-sediment macrofauna will be characterised by an increase in the spatial variability of assemblages from degraded sites. This tenet is based on work conducted by Caswell and Cohen (1991) who demonstrated that in patchy environments, disturbance can generate heterogeneity both spatially and temporally in local macrofaunal community structure (Caswell and Cohen, 1991). In the absence of disturbance the once patchy and heterogeneous habitats converge to form a uniform landscape (Caswell and Cohen, 1991). This is supported by Warwick and Clarke (1993) who found a marked increase in variability among macrofaunal samples from disturbed/stressed treatments. Therefore, the possible detection of habitat degradation, identified as increased spatial variability, may be achieved using spatially nested experimental designs that incorporate measures of variance within and among the effected locations or habitats (Underwood, 1997, 2000; Krebs, 1999).
9. MANAGEMENT 9.1. Flood Management Many ICOLLs are surrounded by urban areas and when development was approved often no consideration of possible inundation during extreme rainfall events was considered.
Form and Functioning of Micro Size Australian Intermittent Closed Open Lake… 143 Consequently some ICOLLS are artificially opened to prevent flooding of houses and infrastructure such as roads and sewage pumping stations (Wiecek and Floyd, 2006). In these situations, ICOLLs would probably have opened naturally, thus artificial opening will make little difference to the ecology of ICOLLs. As well, flora and fauna found in ICOLLs are often species that can tolerate natural or anthropogenic disturbances (artificial openings).
9.2. Water Quality Changed land use in catchments will inevitably lead to increases in suspended solids, nutrients and altered carbon inputs (see section 8 and 9.3). Most nutrients (excluding sewage inputs) will be attached to or incorporated into particles and deposited in sediments. Micro sized ICOLLs, even after severe storm events have low water column dissolved nutrient concentrations and do not experience many phytoplankton blooms. Sediments are already relatively rich in nutrients, thus the addition of nutrient rich sediment is unlikely to alter the natural ecosystem balance. Potentially the greatest threat to ICOLLs is nutrient and reactive carbon inputs from untreated sewage from leaking septic tanks and sewage overflows. Reactive organic matter will interfere with the natural nutrient cycling processes in ICOLLs. Denitrification (see Section 6.4.1) can cease and ammonia released to the water column. As well, phosphorus can also be released to the water column (see Section 6.4.2). Consequently dissolved nutrient concentrations will be increased and phytoplankton growth favoured over the growth of benthic attached algae (Schallenberg et al., 2010). Ammonia is also toxic to marine organisms especially fish. Deoxygenation caused by decomposition of reactive organic matter can also lead to fish kills. Most ICOLLs have periods of being odorous due to hydrogen sulphide production. This is a natural phenomenon, a result of naturally high sulphide concentrations from sea water inputs and periods of anoxia. Sewage inputs would lead to longer periods of anoxia and longer periods of excessive hydrogen sulphide production. Erosion in catchments and mobilisation of sediment is also a threat to ICOLLs as smothering of habitats and infilling may occur. However, as scouring of ICOLLs often occurs when ICOLLs open, sediments are probably not as greater a threat as in poorly flushed marine lake and barrier estuaries. ICOLLs are highly variable in their water quality even when they are the same type of ICOLL and located in the same geographic area/region, therefore it is imperative that each ICOLL be managed as a single entity rather than a series of lagoons from a particular location (Scanes et al., 2007; Chuwen et al., 2009; Schallenberg et al., 2010).
9.3. Conservation A potential problem of deforestation of catchments and urbanisation is that the amount and composition (from eucalypts to introduced grasses and other plant species) of organic matter entering ICOLLs changes. Detritus based ecosystems such as ICOLLs are adapted to specific types of organic matter thus fundamental changes in ecology may occur. Broad scale clearing in catchments should be avoided and revegetation with native species encouraged preventing drastic changes in organic carbon inputs and composition. Riparian vegetation
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forms an important habitat in ICOLLs. Urbanisation leads to loss of riparian vegetation with many ICOLLs having houses built within 5-10 metres of the water body. Reestablishment and restoration of riparian buffer strips would aid in conserving biodiversity and prevent erosion of banks and channel widening. As ICOLLs are breeding grounds and refugia for fish, artificial opening of ICOLLs should be avoided as protection from open water marine predators is a feature of ICOLLs. Fish seem to survive and thrive in closed ICOLLs as long as ICOLLs do not become totally devoid of oxygen.
9.4. Amenity As described in Section 9.2, odours due to hydrogen sulphide formation are often a problem in ICOLLs. Odours are a natural phenomenon and exacerbated by anoxic conditions. However, some hydrogen sulphide is required as a settlement cue for polychaetes (Cuomo, 1985). Opening the mouth of ICOLLs to allow flushing to occur can alleviate odours. However, as mentioned above ICOLLs as refugia can be compromised. The community probably should be educated as to why odours occur and the trade off between alleviating odours and compromising biodiversity and breeding habitats. While ICOLLs are closed they may look like they are in poor condition because of scum build up and algae growth. This is a natural phenomenon and not a symptom of deterioration. Again, education is needed as to what the natural states of ICOLLs are.
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In: Lagoons: Biology, Management and Environmental Impact ISBN: 978-1-61761-738-6 Editor: Adam G. Friedman, pp. 153-183 © 2011 Nova Science Publishers, Inc.
Chapter 5
WATERBIRDS AS BIOINDICATORS IN COASTAL LAGOONS: BACKGROUND, POTENTIAL VALUE AND RECENT RESEARCH IN MEDITERRANEAN AREAS Francisco Robledano Aymerich* and Pablo Farinós Celdrán Department of Ecology and Hidrology, University of Murcia, Espinardo, Spain
ABSTRACT Among the biological components of estuarine systems and other transitional coastal waters, waterbirds are probably the group that has been monitored more intensively and throughout longer time series, especially due to the use of citizen science. Moreover, several authors have reviewed, organized and analyzed critically the role and potential use of waterbirds as bioindicators. Recently, academic research has encouraged more intensive monitoring of waterbirds in the context of bioindication in wetlands and coastal waters. However, in the particular case of coastal lagoons, birds have received little attention compared to research efforts directed to other taxa, ignoring their important role as top predators and underestimating their contribution to various ecological processes. Few studies have included waterbirds as integral components of the food webs in lagoons, relating them to other biota. However, recent studies show that waterbirds respond to changes imposed by a variety of stressors, constituting warning signals against undesirable changes. Waterbirds can be used as bioindicators both at suborganismic and at population-community-ecosystem levels. Either approach requires that the relationships birds establish with habitats and with the ensemble of the lagoon‘s biocoenosis are clarified. As these relationships and the bioindicator role of waterbirds are established in more detail, stands out their usefulness as indicators of impairment in coastal lagoons of similar characteristics, subject to similar impacts with time lags. Studies on the waterbird community of the Mar Menor Lagoon (SE Spain) show the long-term response of populations to variables related to eutrophication and biological *
Corresponding author: E-mail: [email protected]
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Francisco Robledano Aymerich and Pablo Farinós Celdrán changes (proliferations of jellyfish and changes in fish stocks). Studies based on community variation in relation to internal environmental gradients of the lagoon, show spatial responses that can be mapped, and provide a basis for building indices of integrity. This is a relevant issue given the paucity of studies that explore and apply the indicator value of birds in conservation and environmental evaluation, particularly in the Mediterranean and elsewhere in temperate latitudes. Recent studies that integrate the monitoring of different physico-chemical and biotic variables of the lagoon with waterbird numbers and distribution, and research on waterbird trophic ecology based on stable isotope analysis, aim at clarifying the role of waterbirds as top-down controllers in the food webs of coastal lagoons. A role whose monitoring is also important from an applied perspective, given the potential of some waterbirds like cormorants to become conflicting species (through their interaction with fisheries). The application of these monitoring schemes to other Mediterranean lagoons emerges as a valuable tool for assessing and preventing changes in the ecological status of these systems with respect to relatively undisturbed, reference conditions.
1. INTRODUCTION Among the biota of estuarine systems and other transitional coastal waters (TW), waterbirds are probably the group that has been monitored more intensively and throughout longer time series (Crivelli et al., 1996; Delany et al., 1999; Gilissen et al., 2002; Wetlands International, 2008). The use of citizen science has been crucial in this respect (Kushlan, 1993). However, the application of such datasets to ecological monitoring or bioindication has been much more limited. Waterbirds have been the main criterion -and for a long time, virtually the only available- for the designation of internationally 