The Biogeochemistry of Submerged Soils

The Biogeochemistry of Submerged Soils

The Biogeochemistry of Submerged Soils Guy Kirk  2004 John Wiley & Sons, Ltd ISBN: 0-470-86301-3

The Biogeochemistry of Submerged Soils Guy Kirk National Soil Resources Institute Cranfield University, UK and formerly International Rice Research Institute, Philippines

Copyright  2004

John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England Telephone (+44) 1243 779777

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Contents

Preface

ix

Acknowledgements

xi

1 Introduction 1.1 Global Extent of Submerged Soils and Wetlands 1.2 Biogeochemical Characteristics 1.3 Types of Submerged Soil 1.3.1 Organic Soils 1.3.2 Mineral Soils 1.3.3 Relation between Soils and Landform

1 1 3 9 9 10 12

2 Transport Processes in Submerged Soils 2.1 Mass Flow 2.2 Diffusion 2.2.1 Diffusion Coefficients in Soil 2.2.2 Propagation of pH Changes Through Soil 2.3 Ebullition 2.4 Mixing by Soil Animals

17 19 22 22 35 38 39

3 Interchange of Solutes between Solid, Liquid and Gas Phases A. WATER 3.1 Composition of the Water 3.1.1 Acid and Bases 3.1.2 Speciation 3.1.3 Equilibrium Calculations 3.2 pH Buffer Capacity 3.3 Equilibrium with the Gas Phase 3.3.1 Floodwater CO2 Dynamics 3.4 Gas Transport Across the Air–Water Interface 3.4.1 CO2 Transfer Across the Air–Water Interface B. SOIL 3.5 The Solid Surfaces in Soils 3.6 The Solid Surfaces in Submerged Soils 3.6.1 Organic Matter in Submerged Soils 3.7 Solid–Solution Interactions 3.7.1 Adsorption

45 45 45 46 47 50 53 54 56 58 61 65 65 69 74 76 76

vi

Contents

3.7.2 3.7.3 3.7.4 3.7.5 4

5

Precipitation Co-Precipitation in Solid Solutions Inhibition of Precipitation Equations for Solid—Solution Interactions

Reduction and Oxidation 4.1 Thermodynamics and Kinetics of Redox Reactions 4.1.1 Electron Activities and Free Energy Changes 4.1.2 Redox Potentials 4.1.3 Relation between pe and Concentration of Redox Couples 4.1.4 pe–pH Diagrams 4.1.5 Energetics of Reactions Mediated by Microbes 4.2 Redox Conditions in Soils 4.2.1 Changes with Depth in the Soil 4.2.2 Changes with Time 4.2.3 Calculated Changes in pe, pH and Fe During Soil Reduction 4.2.4 Measurement of Redox Potential in Soil 4.3 Transformations of Nutrient Elements Accompanying Changes in Redox 4.3.1 Transformations of Carbon 4.3.2 Transformations of Nitrogen 4.3.3 Transformations of Sulfur 4.3.4 Transformations of Phosphorus 4.4 Oxidation of Reduced Soil 4.4.1 Kinetics of Fe2+ Oxidation 4.4.2 Simultaneous Diffusion and Oxidation in Soil Biological Processes in the Soil and Floodwater 5.1 Microbiological Processes 5.1.1 Processes Involved in Sequential Reduction 5.1.2 Nitrate Reduction 5.1.3 Iron and Manganese Reduction 5.1.4 Sulfate Reduction 5.1.5 Methanogenesis 5.1.6 Aerobic Processes 5.2 Macrobiological Processes 5.2.1 Net Primary Production and Decomposition 5.2.2 The Floodwater–Soil System 5.2.3 Floodwater Properties 5.2.4 Floodwater Flora 5.2.5 Fauna 5.3 Is Biodiversity Important?

79 82 85 87 93 93 93 97 97 99 102 106 107 109 113 116 119 120 120 122 124 127 128 131 135 135 136 141 142 143 144 147 150 150 151 152 154 159 163

Contents

vii

6 Processes in Roots and the Rhizosphere 6.1 Effects of Anoxia and Anaerobicity on Plant Roots 6.1.1 Adaptations to Anoxia 6.1.2 Armstrong and Beckett’s Model of Root Aeration 6.2 Architecture of Wetland Plant Root Systems 6.2.1 Model of Root Aeration versus Nutrient Absorption 6.2.2 Root Surface Required for Nutrient Absorption 6.3 Nutrient Absorption Properties of Wetland Plant Roots 6.3.1 Ion Transport in Roots 6.3.2 Ion Transport in Wetland Roots 6.4 Root-Induced Changes in the Soil 6.4.1 Oxygenation of the Rhizosphere 6.4.2 The pH Profile Across the Rhizosphere 6.5 Consequences of Root-induced Changes 6.5.1 Nitrification–Denitrification in the Rhizosphere 6.5.2 Solubilization of Phosphate 6.5.3 Solubilization of Zinc 6.5.4 Immobilization of Cations 6.6 Conclusions

165 165 167 170 171 172 177 180 180 184 190 191 194 196 196 197 200 200 202

7 Nutrients, Toxins and Pollutants 7.1 Nutrient and Acidity Balances 7.1.1 Nutrient Balances in Ricefields 7.1.2 Acidity Balances in Ricefields 7.1.3 Peat Bogs 7.1.4 Riparian Wetlands 7.1.5 Tidal Wetlands 7.2 Toxins 7.2.1 Acidity 7.2.2 Iron Toxicity 7.2.3 Organic Acids 7.2.4 Salinity 7.3 Trace Elements 7.3.1 Global Cycling of Trace Elements 7.3.2 Transport Through Soil and into Plant Roots 7.3.1 Mobilities of Individual Trace Elements

203 203 203 208 210 210 211 212 212 214 215 216 218 218 218 220

8 Trace Gases 8.1 Methane 8.1.1 Global Budget 8.1.2 Processes Governing Methane Emissions from Rice 8.1.3 Modelling Methane Emission

233 233 233 234 237

viii

Contents

8.2

8.3

8.4

8.5

8.1.4 Estimating Emissions at the Regional Scale 8.1.5 Possibilities For Decreasing Emissions Nitrogen Oxides 8.2.1 Global Budget 8.2.2 Processes Governing Nitrous and Nitric Oxide Emissions from Rice 8.2.3 Differences between Rice Production Systems Ammonia 8.3.1 Global Budget 8.3.2 Processes Governing Ammonia Emissions from Rice Sulfur Compounds 8.4.1 Global Budget 8.4.2 Emissions from Ricefields Carbon Sequestration

244 246 247 247 249 250 252 252 254 256 256 256 258

References

259

Index

283

Preface

This book is about the movements and transformations of energy and matter in soils that are continuously or intermittently submerged with water. Submerged soils cover a huge area, from 5 to 7 per cent of the Earth’s land surface, and they are undoubtedly of great practical importance: in local, regional and global element cycles, as habitats for plants and wildlife, and in food and fibre production. The submerged soils in ricefields, for example, produce the basic food of more than 2 billion people, a third of the world population. But submerged soils are also inherently interesting scientifically, and that is the main theme of the book. When a soil is submerged, air is excluded and the soil quickly becomes anoxic. A submerged soil is therefore an open, anoxic chemical system, surrounded by oxic systems with very different characteristics. Energy enters through photosynthesis, and inorganic matter enters with percolating water and by gas exchange. Chemical reactions occur through a complicated interchange between solid, liquid and gas phases, largely mediated by biological processes. Further, because plants are the main conduits for gas exchange between the soil and overlying atmosphere, they have a particularly important influence. Submerged soils therefore provide a unique natural laboratory for studying a great range of physical, chemical and biological processes that are important in environmental systems. They form under a wide range of hydrological, geological and topographical conditions, but because of the overriding influence of anoxia, the soils and plants and microbes adapted to them have various characteristics in common. The book describes the physical, chemical and biological processes operating in submerged soils and links them to the dynamics of nutrients, toxins, pollutants and trace gases. Far less research has been done on these topics for submerged soils than for dryland soils, in spite of their importance. But knowledge and understanding of them have increased substantially in the past few decades. Much of the research has been on rice soils, particularly at the International Rice Research Institute (IRRI) which has been involved in research on submerged soils since it was founded in 1960. But there is also much in the ecological and environmental literatures concerned with natural wetlands. In preparing the book I have aimed to deal with generic principles relevant to both natural and artificial wetlands with the aim of serving audiences for both.

Acknowledgements

I thank the following friends and colleagues for their help in planning the book and reviewing draft chapters: Dave Bouldin, Roland Buresh, Ralph Conrad, Achim Dobermann, Dennis Greenland, Peter Nye, Bill Patrick, John Sheehy, Siobhan Staunton, Dick Webster and Oswald van Cleemput. I am indebted to the Director General of IRRI, Ron Cantrell, for the award of a consultancy to write the book and for his encouragement throughout. Most of the writing was done during a sabbatical in the Department of Plant Sciences, University of Cambridge, and I am grateful to the Head of Department, Roger Leigh, and member of the Department for their hospitality. The book was completed during my first months at the National Soil Resources Institute, Cranfield University, and I am indebted to the Director, Mark Kibblewhite, for his encouragement and forbearance. For help with the artwork I am grateful to Edwin Javier, Ely Tabaquero and Gene Hettel, all of IRRI.

1 Introduction

Submerged soils behave and affect the environment in substantially different ways to dryland soils. This chapter discusses the main characteristics and environmental effects of submerged soils and the wetlands they support, and their extent across the globe. 1.1 GLOBAL EXTENT OF SUBMERGED SOILS AND WETLANDS For the purposes of the book I define wetlands as lands that are intermittently or permanently inundated with water to a depth of no more than a few metres. Depending on the precise definition applied, estimates of the total global wetland area range from 700 to 1000 Mha (Aselmann and Crutzen, 1989; Scharpenseel, 1997; Mitsch and Gosselink, 2000). Figure 1.1 shows their approximate distribution and Table 1.1 the extents of different types distinguished by hydrology, vegetation and soil characteristics. The largest areas are the bogs and fens in polar and boreal regions in North America and Russia (34 % of total area); tropical swamps, especially in East Africa and South America (14 % of total area); tropical floodplains, especially of the Amazon and the rivers of South East Asia (10 %); and temperate and tropical ricefields (4 and 12 %, respectively). Almost half the global wetland area is in the tropics. There has been considerable loss of wetlands in many parts of the world over the past 200 years as a result of conversion to agricultural and aquacultural uses. In the US for example, it is estimated that the area has declined from 89 Mha in the 1780s to 49 Mha in the 1980s (Mitsch and Gosselink, 2000). A special class of wetland is the lowland ricefield, which accounts for almost a fifth of the wetland area worldwide. Much of our knowledge and understanding of submerged soils has been gained from research on rice soils. The success of rice as a food crop stems from its origins as a wetland plant and its ability to withstand soil submergence with the attendant improvements in water and nutrient supplies. A corollary is that rice is more sensitive to water deficiency than most other crops, and the critical factors in its productivity are the supply of water to the soil, from rain, river, reservoir or groundwater, and the ability of the soil to retain water. Hence most rice is produced and the highest yields attained on the alluvial deposits associated with major rivers and their deltas. More than 90 % of the production is in Asia, distributed unevenly over four rice The Biogeochemistry of Submerged Soils Guy Kirk  2004 John Wiley & Sons, Ltd ISBN: 0-470-86301-3

2

Introduction

40°

20°

0° Equator 20°

40°

Major Wetland Area Area with Abundant Wetlands

160° 140° 120° 100° 80°

60°

40°

20°

0°

20° 40°

60°

80° 100° 120° 140° 160°

Figure 1.1 Global distribution of wetlands (Mitsch and Gosselink, 2000). Reproduced by permission of Wiley, New York Table 1.1

Global extent of wetlands of different types Area (Mha)

Bogs Fens Swamps Marshes Floodplains Shallow lakes Ricefields Total

Polar

Boreal

Temperate

Tropical

Total

21 54 — — — — — 75

104 62 1 — — — — 167

42 32 10 17 8 1 29 139

20 — 102 10 74 11 80 297

187 148 113 27 82 12 109 678

Definitions of wetland types: Bogs are raised peat-producing wetlands formed in wet climates where organic material has accumulated over long periods. Because they are raised, water and nutrients are entirely derived from the atmosphere, and they are therefore nutrient deficient and acid. Sphagnum moss is the main vegetation, though other types of vegetation are also present in tropical regions. Fens are peat-producing wetlands that receive water and nutrients through inflow from neighbouring land. They are generally less acid than bogs and may be alkaline, and tend to be dominated by grasses and sedges. Because of their better nutrient status they are generally more prolific than bogs. Swamps are forested, freshwater wetlands on submerged soils in which little peat accumulates. This is the US definition; elsewhere the term also includes non-forested wetlands with reeds. Swamps tend to form in warmer climates. Marshes are herbaceous freshwater, non-peat-producing wetlands dominated by grasses, sedges or reeds. The distinction between swamps and marshes may be blurred. Floodplains are periodically inundated areas along rivers or lakes. Their vegetative cover is variable. Shallow lakes are open water bodies a few metres deep. Only considered foe temperate and tropical regions; in polar and boreal regions it is difficult to separate shallow lakes from bogs and fens. Ricefields exclude upland rice. The physical area is calculated from the sum of irrigated rice (51 Mha of which 47 % is double- or triple-cropped with rice and 33 % under rice–wheat rotation), rainfed lowland rice (54 Mha) and deepwater rice (4 Mha). The riceland of China is taken to be all temperate. Sources: Aselmann and Crutzen (1989); Huke and Huke (1997); IRRI (2002).

3

Biogeochemical Characteristics Table 1.2

Rice ecosystems in the main rice-producing countries in Asia Harvested area (kha) Irrigated WSa

DSa

India 15 537 4123 China 20 490 9146 Indonesia 2963 2963 Bangladesh 351 2267 Thailand 274 665 Vietnam 1630 1630 Myanmar 1812 1386 Philippines 1175 1029 Pakistan 2125 0 Cambodia 140 165 Nepal 706 24 Korea, Rep. of 776 0 Sri Lanka 377 251 Total 49 211 24 003

Rainfed lowland 0–30b

30–100b

11 985 1990 2872 3271 6382 1963 2033 911 0 1069 406 326 213 34 056

4447 0 1006 2873 1778 651 478 341 0 349 166 0 26 12 131

Flood-prone

Upland

Total

1364 0 2 1220 342 177 362 0 0 152 118 0 0 3737

5060 499 1209 697 203 322 214 165 0 24 68 1 0 8853

42 516 32 125 11 015 10 679 9644 6373 6285 3621 2125 1899 1488 1103 867 13 1991

a

Wet/dry season. Depth of floodwater (cm). Definitions of ecosystem types: Irrigated. Grown in levelled, bunded fields with good water control. Crop is transplanted or direct seeded in puddled soil, and a shallow floodwater is maintained on the soil surface so that the soil is predominantly anoxic during crop growth. Rainfed lowland. Grown in level to gently sloping, bunded fields that are flooded for at least part of the cropping season. Water depths exceed 100 cm for no more than 10 consecutive days. Crop is transplanted in puddled soil or direct seeded on puddled or ploughed dry soil. During season soil alternates between oxic and anoxic conditions of variable duration and frequency. Flood-prone. Distinguished from rainfed lowland rice by extent and duration of flooding. Fields are flooded to at least 100 cm and often much more for at least 10 consecutive days in the growing season. Crop is transplanted in puddled soil or direct seeded on ploughed dry soil; soil may alternate between oxic and anoxic conditions during season. Upland. Grown in level to steeply sloping fields that are rarely flooded. No effort is made to impound water as for other rice ecosystems. Crop is direct seeded on ploughed dry soil or dibbled in wet, non-puddled soil. Source: IRRI (2002). Reproduced by permission of IRRI.

b

‘ecosystems’ distinguished by land and water characteristics and adaptations of the rice plant to them. These are defined in Table 1.2 together with their extents in the main rice-producing countries in Asia.

1.2 BIOGEOCHEMICAL CHARACTERISTICS Wetlands are intermediate between upland systems and true aquatic systems, both in terms of their hydrologies, being intermittently to permanently flooded, and in terms of their biogeochemistries, being sources, sinks and transformers of

4

Introduction

nutrients and carbon, whereas uplands tend to be sources and aquatic systems sinks. Three types of wetland are distinguished based on hydrology (Figure 1.2): a. fluxial, which receive water wholly or in part from surface flow, such as in runoff or streams; b. phreatic, which receive water from groundwater that rises to the soil surface for at least part of the year; and c. pluvial, which receive water entirely from rainfall. In fluxial wetlands water flowing in from neighbouring upland brings with it sediment and nutrients which are only slowly lost to deepwater areas downslope, and may be supplemented by seasonal inflow from deepwater areas. Because of the net inflow of nutrients, the abundance of water, and beneficial changes in the soil resulting from chemical reduction under anoxia, fluxial wetlands are among the most productive ecosystems on Earth. By contrast pluvial wetlands rely on nutrients brought in by rainfall or fixed biologically from the atmosphere, and they therefore tend to be much less productive. Phreatic wetlands are intermediate. As sources, sinks and transformers of matter and energy, wetlands have important roles in element cycles at local, regional and global scales. They contribute to the global stability of carbon dioxide, methane and sulfur in the atmosphere and of available nitrogen and phosphorus in surface waters, and they are important regionally as sinks for organic and inorganic pollutants released into them accidentally or otherwise. These topics are introduced in the following sections; all are returned to in greater detail later in the book. Carbon Balances in Wetlands Table 1.3 shows the net primary production of different wetlands compared with upland and aquatic ecosystems. The generally greater productivity of wetlands is evident. Net primary production (NPP) is the gross rate of carbon fixation in photosynthesis less the rate of loss in plant respiration. The chief factors governing NPP are radiation, temperature, water, nutrients and toxins. Hence for a given type of wetland, NPP tends to increase from polar to tropical regions as incident radiation and day length increase; correspondingly nutrients and temperature become increasingly limiting. There are of course interactions between these changes. For example, the greater productivity of temperate compared with tropical ricefields on a per crop basis shown in Table 1.3 arises because of interactions between radiation and temperature: in temperate rice areas with high radiation during the growing season, low night-time temperatures result in lower respiratory losses compared with tropical areas and hence greater net productivity. Because of their often high biological productivity and low rates of decomposition under anoxia, wetlands are one of the largest terrestrial sinks for carbon. They account for about a third of the soil carbon globally (Table 1.4). However there are large differences between wetland types. Organic wetland soils tend

Figure 1.2

Net import

Net export or import, and transformation

Net export

Generally low

Permanently deeply flooded

Intermittently -permanently flooded

Dry

Generally high

…… … …… … …… …

…… … …… ……

Low to medium

Aquatic

Wetland

Upland

Upland

Wetland

Generally medium to high

Net import and transformation

Intermittently -permanently flooded

…… …… ……… … … …

(b) Phreatic

Wetlands in (a) fluxial, (b) phreatic and (c) pluvial landscapes

Energy conversion

Nutrient regime

Water regime

(a) Fluxial Upland

Upland

(c) Pluvial Wetland

Generally low

Transformation

Intermittently -permanently flooded

… …… …… …

Upland

5

6 Table 1.3

Introduction Net primary production of wetlands compared with other ecosystems Net primary production (g C m−2 year−1 )

Wetlands Bogsa Fensa Swampsa Marshesa Floodplainsa Shallow lakesa Wetland riceb Others Forestc Grasslandc Arabled Desertc

Polar

Boreal

Temperate

Tropical

100–300 100–300

300–700 400–700 500–1000

400–800 400–1200 700–1500 800–2000 800–1800 400–600 850

600–1200

430

650 320 750 <100

1500–3000 1500–4000 1500–2500 500–800 1050 620 (dry), 800 (humid) 450 600 <100

Source: a Aselmann and Crutzen (1989). b Irrigated rice, assuming temperate mean grain yield = 8 t ha−1 , tropical mean grain yield = 5 t ha−1 × 2 crops year−1 , harvest index = 0.5, root mass/above-ground mass = 0.2, mass of C/plant mass = 0.44. c Houghton and Skole (1993). d Based on data of Evans (1993) for wheat and maize yields and harvest indices.

to be confined to cold regions and are rare in tropical regions where decomposition is accelerated by higher temperatures and seasonal wetting and drying of the soil because of the seasonal rainfall pattern. Decomposition is particularly accelerated in wetland rice soils for reasons connected with their fertility and particular ecology, and they therefore tend not to have large organic matter contents in spite of their very large productivities. Mineral wetland soils cover about 5 % of the Earth’s land surface and account for 18 % of soil carbon; organic wetland soils account for 12 % of soil carbon though less than 3 % of the land surface. Countering their value as a carbon sink, wetlands are also the largest single source of atmospheric methane accounting for nearly 50 % of global emissions. Wetlands may also be sources of particulate carbon for aquatic systems downstream. Salt marshes especially are important carbon sources for adjacent estuaries where in situ biological production may be limited by nutrient supplies. Small differences in climate, water and nutrient regimes, and land use can markedly change the delicate carbon balance in wetlands. Nitrogen Nitrogen occurs in several oxidation states under Earth-surface conditions, from +V to −III, and its fixation from and loss to the atmosphere depend on transformations between these states. Because wetlands are the main reducing system

7

Biogeochemical Characteristics Table 1.4 Estimates of organic carbon in wetland and other soils compared with other global carbon pools Pool

Area (Mha)

Soil Wetland minerala,b Wetland organica,b Wetland ricec Forestd Grasslanda Arablea Desert Total Otherse Atmosphere Land Short-lived biota Long-lived biota Litter Sea Surface water Deep water Fossil fuel Sediments

Carbon stocks (Pg)

670 350 109 4200 3000 1400 3750 13 500

Annual change (Pg year−1 )

380 260 10 790 500 140 10 2090 770

+3

130 700 60

−1 to −2

725 37 675 5000–10 000 108

−5

Source: a Scharpenseel (1997). b Armentano and Verhoeven (1990). c IRRI (2002) (2 % C to 30 cm depth). d Dixon et al. (1994). e Bolin and Cook (1983) (atmosphere adjusted to 2003).

in most landscapes and maintain the widest range of redox conditions of any ecosystem, they have a central role in the global nitrogen cycle. Nearly 20 % of natural N2 fixation occurs in wetlands (Table 1.5) because of the favourable water and nutrient status for N2 fixing organisms (Buresh et al., 1980; Bowden, 1987). Wetlands are also important sinks for nitrate which under anoxic conditions is reduced to N2 by microbes in denitrification: 5CH2 O + 4NO3 − + 4H+ −−−→ 2N2 + 5CO2 + 7H2 O Table 1.5 shows the importance of denitrification in wetlands on a global scale. Further, agricultural wetlands are important sources of NH3 which is emitted by volatilization of ammoniacal-N in the floodwater: NH4 + −−−→ NH3 + H+

8 Table 1.5

Introduction Nitrogen fixation and denitrification in wetlands N fixation Mean rate (g m−2 year−1 )

Temperate Bogs/fens Floodplains Tropical Bogs Swamps Floodplains Ricefields Total Total terrestrial

Denitrification

Total (Tg year−1 )

Mean rate (g m−2 year−1 )

Total (Tg year−1 )

1.0 2.0

3.0 6.0

0.4 1.0

1.2 3.0

1.0 3.5 3.5 3.5

0.5 7.8 5.2 5.0 27.5 139

0.4 1.0 1.0 7.5

0.2 2.2 1.5 10.8 18.9 43–390

Source: after Armentano and Verhoeven (1990).

The floodwater often has a high pH as a result of CO2 removal by photosynthesizing organisms, favouring NH3 volatilization. As a result of gaseous losses, and in spite of biological N2 fixation, N is often the most limiting nutrient in wetlands together with P. It is also often one of the most limiting nutrients in coastal waters, so the extent of denitrification of NO3 − in coastal wetlands has a particular significance. Pollution with excess NO3 − causes hypoxia in coastal waters and lakes worldwide (Mitsch and Gosselink, 2000). Currently atmospheric N2 is fixed artificially for N fertilizers at more than double the rate of natural biological N2 fixation, so the return of N to the atmosphere through denitrification in wetlands is an important brake on excess NO3 − .

Sulfur Like nitrogen, sulfur occurs in several oxidation states in submerged soils and its transformations are microbially mediated. Sulfate washed into wetlands or deposited from the atmosphere is largely reduced to S2− in reactions mediated by sulfate reducing bacteria. Subsequent precipitation of S2− with metals, especially Fe2+ , results in more or less permanent removal of the S from the global S cycle. Wetlands are therefore a potentially important sink for excess S released in fossil fuel burning. Some of the S2− may be emitted as H2 S in organic soils, but in submerged mineral soils the concentration of Fe2+ is usually sufficient to prevent this. Hence measured emissions of H2 S and other forms of volatile S from wetlands are generally modest, and in general wetlands are a net sink for S. The concentrations and availability of S in wetland soils rarely limit biological production.

Types of Submerged Soil

9

Phosphorus Though orthophosphate itself is generally not reduced in submerged soils, reduction of ferric iron compounds and changes in the electrochemical properties of the surfaces with which orthophosphate reacts strongly affect its solubility and dynamics. In agricultural wetlands with a history of P fertilization, submergence often results in enhanced availability of P to plants, and responses to additions of further fertilizer in ricefields are often weak. However in natural wetlands, P concentrations are much smaller and P washed into the soil becomes strongly sorbed on the surfaces of reduced soil constituents. Phosphorus brought in with sediment may also be effectively filtered out of water passing through wetlands. Phosphorus retention is therefore a highly valuable attribute of wetlands receiving diffuse pollution. However, the net primary productivity of most natural wetlands, particularly freshwater wetlands, is limited by deficiency of P.

Metals and Other Pollutants Heavy metals, toxic organics and other pollutants have often frequently been added to wetlands both accidentally and on purpose, exploiting their buffering and storage capacities. The chemistry of submerged soils and sediments is such that pollutants may be effectively removed from the percolating water in redox, sorption and precipitation reactions. But the effects of long-term accumulation of pollutants on nutrient cycles and other wetland functions are not well understood.

1.3 TYPES OF SUBMERGED SOIL The principal distinguishing feature of wetland soils is that they develop under predominantly anoxic conditions. Although anoxia is also sometimes found in other ecosystems, it prevails in wetlands and dominates soil properties. Because of the very large organic matter content of some wetland soils, a rough separation into organic and mineral types based on organic matter content is a useful delineation. 1.3.1 ORGANIC SOILS The USDA (1999) defines organic wetland soils as having an organic carbon content of at least 12 % if the mineral fraction has no clay, 18 % if ≥ 60 % clay, or 12–18 % if < 60 % clay. Further differentiation is based on the botanical origin of the organic matter–whether mosses, herbaceous plants, or woody plants–and its state of decomposition: fibrists contain predominantly recognizable, littledecomposed plant debris, saprists predominantly well-decomposed plant debris,

10

Introduction

and hemists are intermediate. Equivalent terms in other classifications are peats, mucks and mucky-peats, respectively. By virtue of being unconsolidated and structureless in comparison with mineral soils, organic soils have much smaller bulk densities, greater porosities and water contents (>80 %), and smaller load-bearing capacities. These factors make their artificial management highly problematic. Organic wetland soils also tend to be poor chemically. Organic soils tend to form under nutrient deficient conditions, which limit organic matter decomposition. This occurs particularly in pluvial wetlands where the only nutrient inputs are from rainfall and biological fixation from the atmosphere. Although the organic material may have a high cation exchange capacity by virtue of the charged functional groups on its surfaces, the exchange capacity tends to be dominated by H+ ions and the soil is acid. The acidity is an inevitable consequence of the circumstances in which organic soils form. By contrast, mineral wetland soils tend to have pHs near neutral as a result of electrochemical changes accompanying soil reduction.

1.3.2 MINERAL SOILS The most productive wetlands are on mineral soils, often developed on alluvial deposits in fluxial wetlands. Nutrients and fertile sediments seasonally flow into these areas under high rainfall and surface water flow. Under prolonged submergence, mineral soils develop so-called redoximorphic features associated with anaerobic soil metabolism (Figure 1.3). As oxygen is excluded by submergence, soil organisms must use other soil constituents as their oxidizing agents in deriving energy from organic matter. This typically occurs in the sequence: nitrate ions to nitrogen, manganic manganese to manganous, ferric iron to ferrous, and then sulfate ions to sulfide. Subsequently organic matter is decomposed by methanogenic bacteria to carbon dioxide and methane. This sequence is predicted by thermodynamics. The most visible change associated with this process is the reduction of the red and brown compounds of ferric iron to blue-grey compounds of ferrous iron. Subsequent translocation of soluble ferrous iron to zones where oxygen enters the soil–such as at the soil surface or near plant roots–produces reddish-brown mottles of insoluble ferric iron. Likewise there may be movement and re-oxidation of manganous manganese forming black manganic compounds. These changes produce the characteristic redoximorphic features of submerged mineral soils. The soil profile that develops under prolonged submergence is sensitive to the nature of the water saturation. In very wet areas where the soil is perennially saturated, the profile may be largely reduced throughout with little development of distinct pedogenic horizons. Such conditions arise in tidal marshes, lake margins, floodplains or in wet footslope areas. In better-drained areas where the flooding

11

Types of Submerged Soil

Ofw

Layer of standing water occupied by micro and macro-fauna and -flora

Apox

Oxic floodwater−soil interface, a few mm to a few cm thick depending on floodwater aeration, soil reducing conditions, mixing by soil animals and percolation

10

Apg

Anoxic soil layer in which pe+pH is below the range at which Fe(III) is reduced, except in the rhizosphere

20

B

Subsoil properties vary with the type of water saturation. In aquic moisture regimes the whole horizon is largely reduced throughout; in epiaquic regimes, where the water table is perched, the horizon generally remains oxic and is mottled along wide pores

Depth (cm)

0

30

40

Figure 1.3

Schematic profile of a submerged soil with redoximorphic features

is more intermittent, there may be more-distinct layers in the soil with different redoximorphic features. The transition between these soil types in partially drained wetlands may occur in a matter of decades. At the boundary between uplands and wetlands there is, in some circumstances, an interaction between organic matter accumulation in sediments and the development of wetland conditions. Some level of organic matter accumulation is required to drive anaerobic metabolism. But also, because, in general, welldecomposed organic matter improves the water holding capacity of mineral soils, particularly in medium to coarse textured sediments, and particularly if the clay mineralogy is dominated by low activity kaolinitic clays, there is a feedback between organic matter accumulation and the extent and duration of water saturation. Particular modifications of these patterns occur in wetland rice soils. Repeated working of the soil for rice often results in permanent changes that mask the soil’s original character. Gross changes are caused by levelling, terracing and puddling the soil for rice, which destroys the soil structure. Over time a ‘traffic’ pan of compacted soil often develops, 5–10 cm thick at 10–40 cm depth. This has a greater bulk density and is less permeable than the overlying surface soil,

12

Introduction

but has similar texture. Over time the surface soil often becomes more coarsetextured, possibly because of weathering of clay under alternate flooding and drainage (Brinkman, 1970; Moormann and van Breemen, 1978). Clay may also be lost from the surface during puddling by movement downslope with surface water. But equally clay may be added from upslope. Freely drained soils that are repeatedly flooded and puddled for rice may show downward movement of reduced Fe and Mn and their subsequent accumulation in oxidized forms at the boundary with oxic subsoil. However this is rarely seen in naturally hydromorphic, finer textured soils. Because of rice’s origins as a wetland plant, it is more sensitive to water deficiency than most other crops. But provided sufficient water is supplied to periodically inundate the land and the soil is able to retain the water, rice will thrive on almost any type of soil. The productivity of rice land therefore often depends more on position in the landscape and soil physical properties than on the finer attributes of the soil. Nonetheless, subtle differences in properties distinguish productive and ‘problem’ soils and affect the behaviour of the soil in the environment.

1.3.3 RELATION BETWEEN SOILS AND LANDFORM Most of the landforms in which wetlands form can be seen in tracing a river from its source in hilly or mountainous areas to its outflow in coastal floodplains and the sea. The main landforms are inland valleys, alluvial fans or fan complexes, meander or lacustrine floodplains, and alluvial terraces (Figure 1.4), and each of these is associated with particular soils as illustrated for ricelands in Asia in Table 1.6. This section gives a brief description of these associations. More complete descriptions are given in Moormann and van Breemen (1978), Driessen and Moormann (1985) and Richardson and Vepraskas (2001). Following these authors I use the USDA (1999) soil classification.

Inland Valleys Wetlands occur on the valley floors and the lower slopes. The soils vary widely with parent materials and other factors, but there are some general patterns. On the valley floors, slopes decrease from the top to the bottom and the age and texture of the deposits vary accordingly. Where deposition is most active, the soils are young and have little profile development. These are Entisols. But most soils in the valley bottoms show at least some profile development and are Inceptisols or Alfisols where there is a pronounced dry season. Where the valley slopes have been terraced for rice and the soil has remained in situ for a long time–hundreds of years–there may be inherited clay illuviation leading to man-made Alfisols and Ultisols. Artificial Entisols may occur where

13

Types of Submerged Soil Inland valleys

Inland valley Terrace

Inland valley Terrace

Alluvial fan Terrace Coastal

Plain

Meander

Floodplain

Tidal

Sea

land

Marine sediments

Riverine sediments

Figure 1.4 Major wetland land forms (Moorman and van Breemen, 1978). Reproduced by permission of IRRI

terracing has completely disturbed the original soil profile and also on valley bottoms that have been perennially irrigated with muddy water. Alluvial Fans The soils again vary greatly with the age and origin of sediments, from young Entisols to well-developed Alfisols and Ultisols. There are some common trends. The deposits are often coarsest and youngest near the apex of a fan and they become finer and older towards the more gently sloping base. There are corresponding differences in hydrology with seepage of water from the better-drained upper parts and accumulation in the lower resulting in marshland to develop where fans meet adjacent floodplains. Entisols and Inceptisols are common in the upper fans; Alfisols in the lower fans or Ultisols where the surrounding uplands are highly weathered. Active Floodplains The main wetland areas are in the river basins. Levee deposits become increasingly fine textured with distance downstream and distance away from the river. The soils are mostly Entisols and Inceptisols, and, where levees grade into basins, Alfisols or Ultisols. Soils in the basins are typically fine-textured and wet but many types occur due to differences in parent materials, rates of deposition,

++ ++ + + +

Aquents na ++ ++ ++ +

Fluvents

Entisols

++ ++ ++ ++ +

Aquepts + + ++ ++ ++

Tropepts/ Ochrepts

Inceptisols

+ + ++ ++ ++

Aqualfs − + + ++ ++

Ustalfs/ Udalfs

Alfisols

− + + + ++

Aquults

− + + + ++

Ustults/ Udults

Ultisols

USDA (1999) soil classification. na, not applicable; −, absent or rare; +, common; ++, abundant. Explanation of soil categories (FAO (1999) equivalents in parentheses): Histosols (Histosols) have high organic matter throughout the profile. Entisols show no evidence of soil-forming processes leading to profile development: Aquents (Gleysols, pt; Fluvisols, pt) are formed in continuously or near-continuously wet environments; Fluvents (Fluvisols, pt) in recent alluvium in areas that are frequently flooded by rivers depositing new sediment. Inceptisols show weak profile development: Aquepts (Gleysols, pt; Thionic Luvisols, pt) are water-saturated for at least part of the year and show gray or rusty mottling; Tropepts (Cambisols, pt) are well-drained and occur in warm regions with only slight annual temperature changes; Ochrepts (Cambisols, pt) occur in regions with greater annual temperature changes. Alfisols show marked clay translocation down the profile without excessive depletion of bases: Aqualfs (Gleyic Luvisols) are water-saturated for part of the year; Ustalfs (Luvisols, except Gleyic, pt; Eutric Nitosols, pt) are seasonally dry; Udalfs (Luvisols, except Gleyic, pt; Eutric Nitosols, pt) are continuously moist. Ultisols show marked clay translocation with intensive leaching and depletion of bases: Aquults (Gleyic Acrisols; Plinthic Acrisols, pt; Dystric Plansols, pt), Ustults (Acrisols, pt; Dystric Nitosols) and Udults (Acrisols, pt; Dystric Nitosols) as for Alfisols. Source: after Driessen and Moorman (1985). Reproduced by permission of IRRI.

++ + − − −

Histosols

The main wetland soils in riverine and coastal landforms

Coastal plains Inland valleys Alluvial fans Floodplains Alluvial terraces

Table 1.6

14

Types of Submerged Soil

15

relic riverbeds, and other factors: Entisols and Inceptisols in young deposits and Alfisols and Ultisols in older. More humic soils, Mollisols, occur locally in depressions in richer floodplains and Vertisols (swelling clay soils that are ‘selfmulching’ as a result of seasonal shrinking and cracking) in basins receiving base-rich water from adjacent higher areas.

Alluvial Terraces Terraces vary in age, parent material, height above the base drainage and topography. Within a given river system, the lower terraces are the youngest and the main soils are Inceptisols with Alfisols in poorly drained areas. Higher, older, Pleistocene terraces have soils reflecting their age and degree of pedogenesis. The relatively low Pleistocene terraces accompanying many rivers in Southeast Asia are important rice areas and the soils are Ultisols and to a lesser extent Alfisols. The highest, oldest Pleistocene terraces are often so dissected and highly weathered that they are not suitable for rice.

Coastal Plains Rapidly aggrading coastal plains are all wet and young and many of the soils are Entisols with no distinct profile development. Upon ripening, whether through drainage or further accretion of sediment, they may develop into Inceptisols. Further inland, soils are increasingly older and profile development more conspicuous. The groundwater is shallow and the soils are grayish with mottling reflecting seasonal fluctuations in the water table. Similar soils occur in slowly aggrading or stationary coastal plains, but the greater extent and duration of mangrove vegetation and more intense tidal influence often cause accumulation of pyrite leading to potential ‘acid sulfate’ soils. Upon drainage and aeration these become extremely acid and are notoriously difficult to manage (Section 7.2). Where the land is protected from direct intrusion by the sea by beach ridges, and sedimentation is minimal, Histosols may develop. Typically these areas have a domed relief with raised central portions where the peat-forming forest vegetation grew, grading into Entisols close to the rivers and sea.

2 Transport Processes in Submerged Soils

The properties of submerged soils are, to a large extent, determined by transport processes controlling the fluxes of solutes and gases through the soil or through plants growing in it. For example, the reason the soil rapidly becomes anoxic following submergence is the much slower transport of oxygen through the waterfilled pores of submerged soil than through the air spaces of well-drained soil. Diffusion coefficients in the liquid phase are four orders of magnitude smaller than those in the gas phase. It therefore makes sense to start with an account of the various transport processes that operate in submerged soils. Transport processes in plants are considered in Chapter 6. Because of the central importance of transport, and because there is a wellestablished theory and mathematics of transport processes in soils, submerged soils lend themselves well to mathematical modelling. Models necessarily give only a crude picture, particularly of the biological processes. But some form of modelling is essential to unravel the complex interactions taking place. Most models involving transport processes in soils are based on the ‘continuity equation’ which relates the change in mass of a substance in a small volume of soil over a small time to the fluxes of the substance into and out of the volume. I here explain the basis of the continuity equation and then describe the transport equations derived from it that are used later in the book. For an introduction to the mathematics of transport processes in environmental systems see Crank et al. (1981). Considering the mass balance of a solute moving in soil between two planes of unit cross-section at distances x and x + δx, the rate of change in mass is equal to the rate of entry across the plane at x less the rate of removal across the plane at x + δx. Hence
 
∂C ∂F δx ≈ (Fx − Fx+δx )t ≈ −δx (2.1) ∂t x ∂x t where Fx and Fx+δx are the fluxes across x and x + δx and C is the amount of solute per unit volume of soil. In the limit δx → 0,
 
∂C ∂F = − (2.2) ∂t x ∂x t This is the continuity equation in one dimension. The Biogeochemistry of Submerged Soils Guy Kirk  2004 John Wiley & Sons, Ltd ISBN: 0-470-86301-3

18

Transport Processes in Submerged Soils

If the movement is solely by diffusion, then from Fick’s first law,
F = −D

∂C ∂x

 (2.3) t

where D is the solute diffusion coefficient. If the soil solution is also moving, then the solute will also be carried by mass flow, and F = −D ∗

∂C + vCL ∂x

(2.4)

where v is the water flux in the x direction, CL is the concentration of the solute in the soil solution and D ∗ is the dispersion coefficient which differs from the diffusion coefficient because the movement of the solution itself causes some dispersion of the solute. The continuity equation for combined diffusion and mass flow is obtained by combining Equations (2.2) and (2.4): ∂C ∂ = ∂t ∂x


D

∗ ∂C

∂x

 − vCL

(2.5) t

This is an expression of Fick’s second law. The concentration of the solute may also change as a result of processes occurring within the volume δx. This is allowed for by adding a term R(C, x, t) to Equation (2.2) to give ∂ ∂C = ∂t ∂x




D∗

∂C − vCL ∂x

 + R(C, x, t)

(2.6)

t

Note that R can be positive or negative. Generally conditions in submerged soils are strongly affected by the vegetation present, which acts as the main conduit for gas transfer between the soil and overlying atmosphere. The effects of vegetation can be allowed for in the R term, suitably modified with depth in the soil and time. Time-dependent reactions, microbially mediated reactions and other reactions adding or removing the solute can be represented with additional R terms. The equivalent equation for movement normal to a cylinder, such as a plant root, is 
1 ∂ ∂C ∗ ∂C = r D − vCL + R(C, x, t) (2.7) ∂t r ∂r ∂r t where r is the radial distance from the axis of the cylinder. In simple cases these equations can be solved analytically but more often numerical solutions are necessary.

19

Mass Flow

2.1 MASS FLOW Submergence greatly alters a soil’s hydraulic properties. Following submergence, air trapped in the pores inside aggregates becomes compressed. Further compression develops as volatile products of respiration accumulate in the pores and as 2:1 type clays swell. As a result, large aggregates tend to rupture. Further rupture occurs as a result of the dissolution of organic matter and oxides, which act as cementing agents within aggregates (Greenland, 1981). Hence in the first few days following submergence, the permeability of the soil increases as gases accumulate in the pores. But as the soil begins to disaggregate, the permeability gradually declines. The decline accelerates as pores become clogged with dispersed clay and other debris. Allison (1947) found the decrease in permeability was less if the soil was sterilized, indicating that the effects of microbes were important, presumably because of increased disruption of aggregates with the accumulation of respiratory gases and dissolution of cementing agents. The extent of disaggregation varies greatly between soils and with the quality of the water. In pure layer silicate systems with high pH or sodium saturation, the disintegration of aggregates and dispersion of clays can be near complete. Whereas in highly structured soils with large contents of organic matter or hydrous oxides, aggregation may be little affected, although it may be easily disrupted by subsequent application of force. In wetland rice cultivation, further disaggregation is caused by the process of tilling the soil when wet, which is an integral part of the land preparation prior to transplanting. Wet tillage results in near complete destruction of water-soluble aggregates and dispersion of fine clay particles. The aim is to reduce losses of water through percolation, both to conserve water and to control weeds, and to facilitate transplanting. Some flow through of water should be maintained so that the soil does not become entirely anoxic. Also, if the structure is completely destroyed the soil will dry only very slowly following the rice crop, and this will delay the establishment of a following dryland crop. Table 2.1 shows the effect of puddling on percolation rates in a range of flooded soils measured Table 2.1 Soil

Psamment Fluvent Aquept Aqualf Ustox Andept

Effect of puddling on percolation rates in a range of flooded Philippine soils Mineralogy

Siliceous Mixed Montmorillonitic Montmorillonitic Kaolinitic Allophanic

Clay (%)

9 24 30 40 64 46

Source: Sanchez (1976). Reproduced by permission of Wiley, New York.

Percolation rate (cm day−1 ) Unpuddled

Puddled

267 215 183 268 155 214

0.45 0.17 0.05 0.05 0.05 0.31

20

Transport Processes in Submerged Soils

Table 2.2 Effect of cultivation at different soil-water states on components of percentage porosity in a Vertic Tropaquept clay soil Sampling state

Total porosity

>50 µm

0.5–50 µm

<0.5 µm

66 61

26 5

6 15

31 41

62

3

16

43

1

1

1

1

Before cultivation After moist cultivation After saturated cultivation SE

Source: Reprinted from Painuli et al. (1988) with permission from Elsevier Science.

under laboratory conditions. Puddling decreases percolation rates by up to three orders of magnitude. Among the soils in the table, the sandy Entisol and clayey Andept were difficult to puddle and consequently had greater percolation rates. However, the low percolation rates in the other soils are comparable to rates in most rice soils under field conditions. Puddling generally leads to an increase in total porosity because the destruction of aggregates decreases intra-aggregate pores but increases inter-aggregate and inter-domain pores, as shown in Table 2.2. The percolation rate also depends on the depth of water standing on the soil surface. Consider the submerged soil shown in Figure 2.1. The soil overlies a compacted traffic layer caused by repeated working for wetland rice cultivation, beneath which the soil may be saturated or unsaturated depending on its properties and the depth of the ground water. The flux of water through the soil is related to the gradient in water potential by Darcy’s law: v = −K

dψ dz

(2.8)

where v is the flux in direction z, K the hydraulic conductivity and ψ the water potential. If v and K are constant in a given layer in Figure 2.1, as they generally ψ 0

floodwater

z1 puddled layer

z2 z3

compacted layer

Figure 2.1 Changes in water potential with depth in a puddled flooded soil

21

Mass Flow

will be, then v = −K

ψ z

(2.9)

and for steady-state flow of water through the soil, v = −Kp

ψ 2 − ψ1 ψ3 − ψ2 = −Kc z2 − z1 z3 − z2

(2.10)

where subscripts 1, 2 and 3 refer to the indicated depths in Figure 2.1 and Kp and Kc are the conductivities of the puddled and compacted layers, respectively. Rearranging Equation (2.10) and substituting Lp and Lc for the depths of the puddled and compacted layers gives v=

ψ1 − ψ3 Lp /Kp + Lc /Kc

(2.11)

Equation (2.11) shows how the flow increases with increasing depth of the floodwater and decreases with increasing impermeability of the compacted layer. The effect of percolation on transport of solutes through the soil is quantified as follows. If there is a concentration gradient of a solute through the soil, from Equation (2.4) the net flux due to mass flow and diffusion is F = −D

dC + vC dz

(2.12)

Mass flow and diffusion act together and cannot be separated. However an idea of their relative contributions to the net flux can be obtained by estimating the distance the solute would be transported if each process acted independently. If in time t mass flow transports the solute a distance z1 = vt the mean distance moved by diffusion would be √ z2 = Dt and the ratio of the two would be

 t z1 =v z2 D

(2.13)

(2.14)

(2.15)

This equation indicates that, for a constant flow rate and diffusion coefficient, the distance transported by mass flow will exceed that by diffusion after a certain time has elapsed, i.e. mass flow eventually becomes more important than diffusion. However note that z2 is only the mean distance moved; some of the solute will have diffused beyond this. Equation (2.15) can be used to calculate the relative importance of mass flow and diffusion under conditions in ricefields. From the discussion above, rates of

22

Transport Processes in Submerged Soils

percolation in puddled submerged soils are generally less than a few mm day−1 , that is ≤ 2 × 10−7 dm s−1 . Solute diffusion coefficients in submerged soils are of the order of 5 × 10−8 dm2 s−1 (next section). Therefore the time taken for the distance moved by mass flow to exceed the mean distance moved by diffusion would be 14 days.

2.2 DIFFUSION The rates of many important processes in submerged soils are governed by rates of diffusion. A comprehensive theory of diffusion in soils exists, allowing the development of mechanistic models of soil processes involving diffusion. I briefly describe this theory in this section; more complete treatments are given in Nye (1979) and Tinker and Nye (2000). Diffusion results from the random thermal motion of particles. If there is a concentration gradient of a substance through a medium in which it is mobile, the net amount of substance crossing a unit section in unit time is given by Fick’s first law (Equation 2.3):
 dC F = −D (2.16) dx where F is the flux of the substance, dC/dx is its concentration gradient across the section, and D is the diffusion coefficient, which is defined by this relation.

2.2.1 DIFFUSION COEFFICIENTS IN SOIL In submerged soils there is no continuous gas phase through which volatile solutes can diffuse. Hence we are mainly concerned with the liquid and solid phases. If the concentration of a volatile solute in the liquid becomes sufficiently large for an appreciable amount to come out of solution, the resulting gas bubbles will rise through the soil by the process of ebullition, partly becoming entrapped beneath soil particles until they are dislodged by mechanical forces. Ebullition is discussed in Section 2.3. For diffusion in the liquid and solid phases, the same principles apply as for non-submerged soils though there are some additional effects, which I shall describe. Most solutes in soils are to some extent adsorbed on the soil solid; only a small fraction is in the solution in the pores. However some adsorbed solutes, particularly exchangeable cations, can have considerable mobility on soil surfaces (see below), so it is important to consider the solid phase pathway as well as the solution. Because the diffusing solute passes rapidly between the solid and solution, the two pathways partly act in series. In such a heterogeneous medium as soil it is not realistic to account for the mobilities and concentration gradients of solutes in all the constituent parts. But if the soil volumes and reaction times

23

Diffusion

considered are large enough to average microscale variations, the soil can be treated as quasi-homogeneous and Fick’s first law can be applied to the system as a whole. The term C in Equation (2.16) is then the concentration of the diffusate in the whole soil system; that is, ‘all those ions or molecules that are in or pass through a mobile phase during a period that is short in comparison with the time of the diffusion process’ (Nye, 1979). Solutes that do not interchange completely between the solid and solution within this time frame, i.e. a matter of hours, are treated as having a rate of reaction and are dealt with by adding a source or sink term to the appropriate form of the continuity equation. Following from this definition, the diffusive flux of a solute through the solution and solid in the x direction is given by (Tinker and Nye, 2000, Equation 4.17) F = −DL fL θL

dCL dCS − DL fS θS dx dx

(2.17)

where DL is the diffusion coefficient of the solute in free solution, θL is the fraction of the soil volume occupied by solution, θS is the fraction of the soil volume occupied by soil solid, fL and fS are the impedance factors for the liquid and solid phase, respectively, and CL and CS are the amounts of solute per unit volume of liquid and solid phase, respectively. The first term on the right-hand side of Equation (2.17) represents diffusion exclusively in solution; the second term represents the additional diffusion that occurs as a result of mobility on the soil solid. The concentration of the solute in the solid is expressed in terms of the amount per unit weight of solid, SS , by θS CS = ρSS where ρ is the weight of dry solid per unit soil volume. By definition, F = −DdC/dx. Substituting for F and θS CS in Equation (2.17) and rearranging gives
 dSS dCL (2.18) D = DL fL θL + fS ρ dCL dC In the following sections I discuss the components of the diffusion coefficient so defined in turn. Note all the components of D are altered by flooding the soil. As well as increasing the cross-sectional area for diffusion, represented by θL , flooding affects the geometry and tortuosity of the soil pore network, represented by fL and fS , and solute sorption on the soil solid, represented by dCL /dC. The Diffusion Coefficient in Free Solution, DL Table 2.3 gives the self-diffusion coefficients of some important ions in submerged soils and Figure 2.2 shows the values for the elemental ions plotted against ionic potential (|z|/r where |z| is the absolute ionic charge and r the crystal ionic radius). As the ionic potential increases the hydration layer of water molecules around the ion increases, and therefore the mobility tends to decrease. Also, at the same ionic potential, cations diffuse faster than anions. The mobilities

24

Transport Processes in Submerged Soils Table 2.3 Self-diffusion coefficients of ions in aqueous solution at 25 ◦ Ca D0 (dm s × 10−7 )

Cations H3 O+ Li+ Na+ K+ Rb+ Cs+ NH4 + Mg2+ Ca2+ Sr2+ Ba2+ Mn2+ Fe2+ Ni2+ Cu2+ Zn2+ Cd2+ Pb2+ a

from Landolt et al. (1960). Robinson and Stokes (1959).

2 −1

OH− F− Cl− Br− I− HS− SO4 2− NO2 − NO3 − HCO3 − CO3 2− H2 PO4 − HPO4 2− H2 AsO4 − HCOO−b CH3 COO−b CH3 CH2 COO−b

9.31 1.03 1.33 1.96 2.06 2.07 1.98 0.70 0.79 0.79 0.85 0.69 0.72 0.68 0.73 0.72 0.72 0.95

Calculated with the relation D 0 =

D0 (dm s × 10−7 )

Anions

2 −1

5.27 1.47 2.03 2.08 2.04 1.73 1.06 1.91 1.90 1.18 0.92 0.85 0.73 0.91 1.45 1.09 0.95

RT λ0 using values of the limiting equivalent conductivity, λ0 , |z|F 2

b

2.5 Cs+ + Rb NH4+ I− − K+ Cl Br −

D 0 (dm2 s−1 × 10−7)

2.0

1.5

F−

Na+ Li+

1.0 Ba2+ 0.5

0.0 0.0

0.5

1.0

1.5

Pb2+ Sr2+

2+ 2+ Ca2+ Fe , Zn Ni2+

2+ Cd2+ Mn2+ Cu2+ Mg

2.0

2.5

3.0

3.5

|z |/r (nm−1)

Figure 2.2 Self-diffusion coefficients at 25 ◦ C plotted against ionic potential (after Li and Gregory, 1974). Reprinted with permission from Elsevier Science

25

Diffusion

of H3 O+ and OH− are anomalously large because they move by a proton jump mechanism in which protons are passed between favourably orientated water molecules (Glasstone et al., 1941). However, in bulk diffusion, ions cannot move independently of each other because electrical neutrality must be maintained. Consequently there is an electric potential between diffusing ions such that the faster ions tend to be slowed down by the slower ones and vice versa. The flux of a particular ion is therefore the sum of the diffusion due to its own concentration gradient and that due to the gradient of the diffusion potential arising from differences in the mobilities of the ions present. This is expressed by the Nernst-Planck equation along the x-axis:
 dCLA ZA CLA F  dψ FLA = −DLA + (2.19) dx RT dx where F  is the Faraday, ZA is the charge of ion A and ψ is the potential. If A is present in only small concentrations, the diffusion potential term is much less important than the concentration gradient term, and can be ignored. However, if A is a large part of the total ionic strength, and ions are present with differing mobilities, the diffusion potential will be important. Vinograd and McBain (1941) used the condition of no net flux of charge: Zi FLi = 0

(2.20)

where subscript i refers to a particular species and Zi is its charge, to express the term dψ/dx in terms of the ionic concentrations gradients, giving FLA = −DLA

dCLA DLi dCLi /dx + ZA CLA DLA dx Zi 2 DLi CLi

(2.21)

Equation (2.21) shows that the greater ZA , CLA and DLA , and the smaller dCLA /dx, the greater will be the effect. But the effect is small for ions with similar mobilities and for ions whose concentrations are small compared with the total solution concentration. A further point is that a significant proportion of many of the cations in solution in submerged soils may be complexed with organic ligands (Chapter 3). The diffusion coefficients of the complexed ions will be smaller than the corresponding free ions. Table 2.4 compares self-diffusion coefficients of chelated and unchelated Fe3+ and Zn2+ . Table 2.5 gives the diffusion coefficients in aqueous solution of other uncharged solutes important in submerged soils, and diffusion coefficients in air. The Soil Moisture Content, θL and Bulk Density, ρ In submerged soils there tends to be a gradient of bulk density with depth as a result of the settling of disturbed sediment. As a result, the bulk density is

26

Transport Processes in Submerged Soils Table 2.4 Diffusion coefficients of chelated ions at 25 ◦ C D(dm2 s−1 ) 8.8 × 10−8 a 6.8 × 10−8 a 6.2 × 10−8 b 3.9 × 10−8 b 4.2 × 10−8 b 5.4 × 10−8 b

Zn2+ ZnEDTA Fe3+ FeEDTA FeDTPA FeEDDHA

Source: a Elgawhary et al. (1970). b O’Connor et al. (1971).

Table 2.5 Diffusion coefficients of gases in air and water at 25 ◦ C and 1 atm D(dm2 s−1 )

O2 CO2 CH4 H2 S N2 NH3 N2 O NO

in air

in water

2.05 × 10−3 1.55 × 10−3 2.20 × 10−3 1.66 × 10−3 2.04 × 10−3 2.19 × 10−3 1.55 × 10−3 2.04 × 10−3

2.26 × 10−7 1.93 × 10−7 1.73 × 10−7 2.00 × 10−7 2.02 × 10−7 2.49 × 10−7 1.98 × 10−7 2.55 × 10−7

Source: Lerman (1979).

near zero at the boundary between the soil and overlying water and gradually increases over the upper 0.5 to 1 cm of soil or deeper. The cross-sectional area for diffusion and ion interchange with the soil solid are altered correspondingly. The Impedance Factor for the Liquid Phase, fL The impedance factor is strictly empirical, accounting primarily for the geometry of the soil pore network but also for ion exclusion by negative adsorption from narrow pores, and for the increased viscosity of water near charged surfaces. It is similar for all simple ions and molecules. It can be measured by following the self diffusion of a nonadsorbed ion, such as Cl− , for which C = θL CL and hence D = DL fL . Discontinuities in the liquid pathway and the effects of anion exclusion from narrow pores and of viscosity near charged surfaces are important at low moisture contents. The value of fL therefore approaches zero in very dry soil and the

27

Diffusion 0.6 30a

Impedance factor, fL

0.5 0.4 0.3 0.2

24 23

15 6

16 19 37

5 4

53 38

33

26

17b

0.1 0.0 0.0

0.1 0.2 0.3 0.4 0.5 Volumetric water content, qL

0.6

Figure 2.3 Relation between diffusion impedance factor, fL , and moisture content, θL , in a range of soils. Numbers shown are % clay contents. a Mean of six soils; b volcanic ash soil. (After Tinker and Nye, 2000; Olesen et al., 2001). Reproduced by permission of Oxford University Press

relation between fL and θL is curvilinear. Figure 2.3 shows relations between fL and θL in a range of soils given by Nye (1979); Olesen et al. (2001) give further values. The figure shows that, at a given moisture content, fL is smaller in clay soils than in sandy soils, probably because a greater proportion of the soil water is in fine pores. But at a given water potential, fL is larger in clayey than sandy soils because they hold more water (So and Nye, 1989). Effects of Flooding and Redox Conditions on fL . As well as increasing the crosssectional area for diffusion through the soil pores, flooding affects fL because the anoxic conditions that develop result in dissolution and re-precipitation of the soil solid and changes in its electrical properties. Kirk et al. (2003) investigated these effects in four soils with contrasting properties. Figure 2.4 shows the relation between fL and bulk density in the soils under water-saturated conditions. The relation is linear with similar slopes but different intercepts in the four soils. As bulk density increases, porosity decreases, and the pathway for diffusion becomes more tortuous. The dotted line in Figure 2.4 shows the theoretical relation between fL and ρ for a mixture of spherical particles of various sizes: fL = θL 0.5 = (1 − ρ/ρP )0.5 where ρP is the particle density, taken as 2.65 g cm−3 (Nye, 1979, Section V.B). The values of fL for the more coarse-textured soil, Iloilo, come closest to this line, but the values are progressively far from it for the more clayey soils, and they are not parallel to it in any of the soils. There are several reasons for this. In soils electrostatic and viscosity interactions between diffusing solutes and solid surfaces are important and tend to diminish fL at a

28

Transport Processes in Submerged Soils 0.9

Impedance factor, f L

0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.7

Iloilo Maahas N. Ecija Tarlac 0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

Bulk density, r (g cm−3)

Figure 2.4 Relation between diffusion impedance factor, fL , and bulk density, ρ, in four water-saturated rice soils. Dotted line is the theoretical relation between fL and ρ for a mixture of different-sized spherical particles (Kirk et al., 2003). Iloilo: Epiaquult; clay 21 %; org C 1.04 %; pH 3.93. Maahas: Haplaquoll; clay 54 %; org C 1.83 %; pH 5.89. Nueva Ecija: Epiaquert; clay 35 %; org C 1.57 %; pH 5.25. Tarlac: Tropaquept; clay 33 %; org C 1.06 %; pH 6.02. Reproduced by permission of Blackwell Publishing

given ρ. These interactions increase as ρ increases and an increasing proportion of the pores are fine, and as clay content increases. Hence the regression lines are steeper than the theoretical line and farther from it with increasing clay content. Also the approximation of spherical shape is increasingly invalid with increasing clay content because small surface irregularities become an increasing proportion of the whole. Figure 2.5 shows the effects of changes in redox conditions on fL in the four soils with time following flooding. In three of the soils, fL decreases during the first few weeks following flooding but then gradually returns to its initial value. Since ρ and θL were constant over this period, the changes in fL were evidently due to changes in chemical and biological conditions in the soils following flooding. This is explained as follows. Following flooding O2 entrapped in the soil is rapidly consumed in aerobic microbial respiration, and then other inorganic electron acceptors are used in microbial respiration in the sequence NO3 − , Mn(IV), Fe(III), SO4 2− (Chapter 4). Concomitantly, organic matter is oxidized, dissolved CO2 accumulates, and the pH of acid soils tends to increase and that of alkaline soils to decrease, stabilizing in the range 6.5 to 7. Figure 2.6 shows the changes in EH , pH, the concentration of HCO3 − in solution and cation exchange capacity (CEC) in the four soils following flooding, and Figure 2.7 shows the corresponding changes in soil Fe. In all four soils, Fe(III) is the main inorganic reductant and large concentrations of Fe2+ develop in the soil solution in the weeks following flooding as Fe(III) is

29

Diffusion 0.7 Iloilo (r = 1.21 ± 0.01) 0.6

0.5

0.4 0.7 Maahas (r = 0.80 ± 0.01)

Impedance factor, f L

0.6

0.5

0.4 0.7 Nueva Ecija (r = 1.00 ± 0.02) 0.6

0.5

0.4 0.7 Tarlac (r = 0.98 ± 0.02) 0.6

0.5

0.4

0

20 40 60 Time after flooding (days)

80

Figure 2.5 Changes in fL with time following submergence of the four soils in Figure 2.4 (Kirk et al., 2003). Reproduced by permission of Blackwell Publishing

30

Transport Processes in Submerged Soils 300

Soil EH (mV)

200

Iloilo

100

Nueva Ecija

0

Tarlac

−100 −200 Maahas

−300

Soil pH

7

Maahas

6

Tarlac

Nueva Ecija 5 Iloilo 4

[HCO3−] in solution (mM)

25 20

Maahas

15

Nueva Ecija

10 Iloilo 5 Tarlac

0

CEC (mmolc kg−1)

250 200 Nueva Ecija

150

Tarlac

100 50 0

Maahas

Iloilo 0

20

40

60

80

Time after flooding (days)

Figure 2.6 Changes in EH , pH, HCO3 − and CEC with time in the experiment in Figure 2.5 (Kirk et al., 2003). Reproduced by permission of Blackwell Publishing

31

Diffusion

4 [Fe2+] / mM

[Fe2+] in solution (mM)

0.4 0.3 Nueva Ecija

0.2

3 2 1 0

Iloilo 0

80

Maahas

0.1

Tarlac

NH4OAc-extractable Fe(II) (mmol kg−1)

0.0 6 5

Iloilo

Maahas

4 3 2 1

Tarlac

Nueva Ecija

0

Ferrozine-extractable Fe(II) (mmol kg−1)

8 Nueva Ecija

Iloilo

6 4

Maahas 2 Tarlac 0

HCl-extractable Fe(II) (mmol kg−1)

100 80

Nueva Ecija

Maahas

60

Iloilo

40 20 0

Tarlac 0

20

40

60

80

Time after flooding (days)

Figure 2.7 Changes in soil Fe(II) with time in the experiment in Figure 2.5 (Kirk et al., 2003). Reproduced by permission of Blackwell Publishing

32

Transport Processes in Submerged Soils

reduced and dissolves. The increases and subsequent decreases in Fe2+ in solution coincide with the increases and decreases in HCO3 − , suggesting that insoluble ferrous carbonates are formed. The ion activity products of well-known ferrous carbonates and hydroxides are exceeded up to 10-fold in the four soils in the early stages following flooding. Evidently precipitation of these compounds is inhibited, probably as a result of adsorption of foreign solutes, such as dissolved organic matter, on nucleation sites. However, once a sufficient supersaturation has been reached, amorphous solid phases are precipitated, and these later reorder to more crystalline forms. The changes in Fe(II) in the solid phase are consistent with this, the more soluble pools showing peaks roughly matching Fe2+ in solution but the HCl-extractable Fe(II) continuing to increase over time. Mixed Fe(III)–Fe(II) compounds form initially upon flooding with a progressively greater proportion of Fe(II) as reduction proceeds. In the Maahas, Nueva Ecija and Tarlac soils, which contain 2:1 clays, some of the Fe is structural in clay lattices. Reduction of this structural Fe causes a net increase in the negative surface charge on the clay, resulting in increased CEC and decreased clay swelling and surface area (Stucki et al., 1997). Further, in soils that undergo intermittent reduction and oxidation, as all the soils here do, a large part of the easily reducible Fe is present as coatings of oxyhydroxides on clay surfaces (Brinkman, 1985), and these are dissolved during soil reduction. Where positively charged oxyhydroxides neutralize negatively charged sites on the clay, dissolution of the coatings will cause the net surface negative charge and hence CEC to increase (Roth et al., 1969). The rapid increase in CEC in the early stages of reduction and its subsequent stabilization (2.7) are consistent with the changes in pH and Fe. The changes in fL in the four soils following flooding roughly parallel the changes in CEC and Fe. Increased CEC will cause increased anion exclusion from narrow pores, decreasing fL . Decreased clay swelling and interlayer space with reduction of structural Fe will also increase anion exclusion and exacerbate the decrease in fL . There will also be changes in pore geometry with dissolution of ferric oxyhydroxides coatings, but these will be complicated by subsequent reprecipitation in initially amorphous but later crystalline forms. Poorly crystalline compounds lining soil pores should increase the tortuosity of the diffusion pathway, but as they revert to more crystalline forms with smaller specific surfaces, fL should increase. Although the changes in diffusion impedance due to changes in redox are smaller than the changes due to water content per se, they will be important in some soils.

The Impedance Factor for the Solid Phase, fS In Equation (2.18) fS is defined in relation to DL : it takes account of all factors decreasing the mobility of the sorbed solute from the mobility it would have in free solution. This includes the binding of the solute to the surface and the limited thickness of the layer of water molecules associated with the surface,

Diffusion

33

in which the sorbed solute diffuses. It can be measured by assuming that the solution pathway is the same as that for a nonabsorbed ion, and then deducing the movement in the solid from the excess movement not accounted for by the solution pathway. While fS is negligible for strongly sorbed anions, such as phosphate, which are covalently bound to the surface, it is often substantial for exchangeable cations (Staunton and Nye, 1983, 1987; Staunton, 1990; Nye and Staunton, 1994). Although the values of fS are much smaller than those of fL , the flux on the surface may exceed that in solution because a much larger proportion of the cations are held on the surface. Staunton (1990) measured fS for different exchangeable cations (Na+ , Ca2+ , Rb+ and Cs+ ) in soils with a range of clay contents and mineralogies, and found that fS decreased as the degree of binding to the surface, measured by the ratio SS /CL , increased. Thus the two tend to offset each other and as a result the contribution of surface diffusion to D is variable. For the cations and soils considered by Staunton the contribution of surface diffusion to D ranged from 27 to 97 %. There was no correlation between fS and soil mineralogy or clay content. Staunton and Nye studied alkali and alkaline earth cations sorbed in freely exchangeable forms, over reaction times of a few hours. More strongly sorbed cations, such as those of transition and heavy metals at trace concentrations, are likely to have less surface mobility. A consequence of high surface mobility is that equilibrium between inter- and intra-aggregate pores is maintained more easily. Thus Pinner and Nye (1982), for Cl− , and Staunton and Nye (1983, 1987), for exchangeable cations, found no evidence of slow equilibration between inter- and intra-aggregate pores for diffusion in naturally structured soils, and the soil pore network behaved homogeneously to the diffusant. However for solutes with little surface mobility, such as strongly sorbed anions, access to exchange sites through narrow access pores is likely to limit equilibration between inter- and intra-aggregate pores. It is important to consider this in defining continuity equations and in measuring rates or reaction. Effects of Flooding and Redox Conditions on fS . I know of no published data on this. But it is likely that the nature of particle surfaces in intermittently flooded soils would restrict surface mobility. For ions to diffuse freely on the surface there must be a continuous pathway of water molecules over the surface and uniform cation adsorption sites. But in intermittently flooded soils the surface typically contains discontinuous coatings of amorphous iron oxides on other clay minerals, and on flooding reduced iron is to a large extent re-precipitated as amorphous hydroxides and carbonates as discussed above, resulting in much microheterogeneity with adsorption sites with disparate cation affinities. The Derivative dCL /dC This derivative is the reciprocal of the buffer power and describes the distribution of the diffusing solute between the soil solid and solution. Its value varies by

34

Transport Processes in Submerged Soils

several orders of magnitude for different solutes in a given soil and to a lesser extent for the same solute in different soils. For nonadsorbed solutes, such as the Cl− ion, C = θL CL and therefore θL dCL /dC = 1. Hence in Equation (2.18), D = DL fL . For a strongly sorbed ion, such as H2 PO4 − , dCL /dC may be 1000 and the value of D correspondingly small. Values of dCL /dC are also sensitive to the method by which they are measured. This must therefore be as close as possible to the conditions under which the diffusion coefficient is to be applied. The difficulties in measuring dCL /dC correctly are discussed by Tinker and Nye (2000, pp. 84–88). Effects of Flooding and Redox Conditions on dCL /dC . Reductive dissolution reactions of the sort indicated in Figures 2.6 and 2.7 will affect the amount of a solute in diffusible forms in the soil and the distribution of the diffusible forms between the soil solid and solution. These processes are discussed in detail in Chapter 3. I here exemplify their effects by reference to a study of phosphate diffusion in a soil under different water regimes. Huguenin-Elie et al. (2003) measured the diffusion of P to a resin sink placed in contact with a soil that was either moist, flooded or flooded then moist, and derived values of the diffusion coefficient of P in the soil by fitting to the results the equation for diffusion from a semi-infinite medium to a planar sink:  DP t Mt = 2C∞ (2.22) π where Mt is the amount of P accumulated in the resin at time t, C∞ is the concentration of diffusible P in the soil bulk, measured independently, and DP is the diffusion coefficient of P. The results are shown in Figure 2.8. They then

P accumulated in resin, M t (µmol dm−2)

1.4

M t = 14.96 × 10−10 × √t

1.2 1.0 0.8

M t = 4.93 × 10−10 × √t

0.6 0.4

M t = 4.60 × 10−10 × √t

0.2 0.0

0

2

4

6 Time (days)

8

10

Figure 2.8 Amounts of P absorbed by a planar resin sink in contact with columns of soil that was flooded (circles), moist (triangles) or flooded then moist (squares). Lines are fits to Equation (2.22) (Huguenin-Elie et al., 2003). Reproduced by permission of Blackwell Publishing

35

Diffusion

calculated values of dCL /dC from the values of DP so obtained using measured values of θL and fL and Equation (2.18). Flooding increased θL fL from 0.12 to 0.21, C∞ from 199 to 352 µmol dm−3 (whole soil), and dCL /dC from 1/2220 to 1/1330. Drying previously flooded soil to the original θL fL value decreased C∞ to 149 µmol dm−3 and dCL /dC to 1/1430. The changes were consistent with changes in soil Fe upon flooding and drying. Equations for Sorption. The following two simple equations often adequately describe the relation between the amount of an anion or a cation sorbed on the soil solid and its concentration in solution: Freundlich equation CS = a CL b (2.23) Tempkin equation CS = a ln CL

(2.24)

where CS is the concentration in the solid, CL the concentration in solution, and a and b are coefficients (b < 1). Log-log transformations of the Freundlich equation are linear and linear-log transformations of the Tempkin are linear. These equations correspond to mechanisms by which sorption is progressively inhibited by the accumulation of sorbed solute on the solid. However, as applied to heterogeneous soil systems they are empirical and more precise mechanisms than this cannot be inferred. 2.2.2 PROPAGATION OF pH CHANGES THROUGH SOIL An important application of the theory of solute diffusion in soil is Nye’s (1972) theory of how pH changes are propagated by acid–base transfer. Sources of pH changes in submerged soils are legion and the resulting pH gradients through the soil have important effects on soil processes. Examples are diurnal changes in floodwater pH caused by algae and pH changes in the rhizosphere induced by roots. I here give a summary of the theory. Changes in pH are propagated by the movement of protons. But because free protons do not exist they must move by transfer between proton donors and acceptors, i.e. Bronsted acids and bases: acid (proton donor) = base (proton acceptor) + H+

(2.25)

The main acid–base pairs in soils are H3 O+ –HCO3 − and H2 CO3 –HCO3 − . In particular cases other pairs, such as NH4 + –NH3 , H2 PO4 − –HPO4 2− and H2 S–HS− , may also be important. When a pH gradient exists in a soil, acids and bases will move in the soil solution between the solid surfaces: acids from zones of low pH to high and bases in the opposite direction. The acid arriving in a portion of soil will react with it, and a local acid–base equilibrium will be established. Thus the

36

Transport Processes in Submerged Soils

acidity of the solution is buffered. Electrical neutrality is maintained by the co- and counter-diffusion of the other cations and anions present. Nye derives equations of the transfer of protons through the soil as follows. Consider the balance of acid, HS, between two imaginary planes of unit crosssection at x and x + δx in the soil. The general reaction of the acids and bases with the soil may be written HB + MS = HS + M+ + B−

(2.26)

where HB is an acid and B− its conjugate base. In unit time the increase in HS will be the result of all reactions of this type and will equal the loss by reaction of acids HB within the region. This loss must equal the sum of the fluxes of all acids entering across the plane at x less those leaving across the plane at x + δx. If M+ and H+ do not move in the solid phase, then by analogy with Equations (2.5) and (2.18),
 ∂[HB] ∂ ∂[HS] = θL fL DLHB (2.27) ∂t ∂x ∂x where DLHB is the diffusion coefficient of HB in free solution, [HB] is the concentration of acid in solution and [HS] is the concentration of acid soil, i.e. of proton donating groups as measured by the amount of strong base consumed by unit volume of soil in raising the equilibrium pH to a standard pH. (Since only differences in [HS] arise it is not necessary to define this pH.) It is assumed that the impedance factor, fL , is the same for all mobile acids and bases. It is also assumed that the solid equilibrates rapidly with the adjacent solution; in cases where it does not, terms for the rates of reaction can be added to the equation. The term ∂[HB]/∂x in Equation (2.27) is expressed in terms of ∂[HS]/∂x as follows. The pH buffer power of each acid–base pair is defined as: bHB =

d[B− ] d pH

(2.28)

However, because in general there is no net flux of component B, d[B− ] = −d[HB] and d[HB] (2.29) bHB = − d pH Likewise the pH buffer power of the soil is bHS = −

d[HS] d pH

bHS is often fairly constant over a wide range of pH.

(2.30)

37

Diffusion

Since [HB] and [HS] are both functions of pH, and pH is a function of x, ∂[HB] ∂[HS] d[HB] d pH bHB ∂[HS] = = ∂x ∂x d pH d[HS] bHS ∂x Hence substituting in Equation (2.27),  
 ∂[HS] ∂[HS] ∂ θL fL bHB DLHB = ∂t ∂x bHS ∂x

(2.31)

where the term in parentheses is the soil acidity diffusion coefficient, DHS . If bHS is constant, then by substituting for d[HS] from Equation (2.30), Equation (2.31) may be written
 ∂pH ∂pH ∂ = DHS (2.32) ∂t ∂x ∂x For a soil in which the only important acid–base pairs are H3 O+ –H2 O and H2 CO3 –HCO3 − , Nye (1972) shows that: DHS =

2.303θL fL (DLH [H3 O+ ] + DLC [HCO3 − ]) bHS

(2.33)

The relative contribution of the pairs H3 O+ –H2 O and H2 CO3 –HCO3 − to the overall soil acidity diffusion coefficient is given by the term in parentheses in Equation (2.33) and is plotted at different pHs in Figure 2.9(a). The figures shows

DLqLfLbHB /bHS (dm2 s−1 × 10−9)

1.0

H2CO3---HCO3−

H3O+---H2O

1.0

PCO2 = 1 kPa

0.8

(b)

0.1 0.6

0.03

DHS (dm2 s−1 × 10−9)

(a)

0.6 0.4 0.2 0.0

0.4

PCO2 = 0.05 kPa

0.8

3

4

5

6

7

8

pH 0.2

0.0

4

5

6 pH

7

8

Figure 2.9 (a) Contributions of acid–base pairs H3 O+ –H2 O and H2 CO3 –HCO3 − to the soil acidity diffusion coefficient over a range of pH; θL fL = 0.3, bHS = 0.05 mol dm−3 pH−1 (after Nye, 1972). (b) Observed and calculated soil acidity diffusion coefficients (Nye and Ameloko, 1986). Reproduced by permission of Blackwell Publishing

38

Transport Processes in Submerged Soils

that the soil acidity diffusion coefficient passes through a minimum in the pH range in which H3 O+ and HCO3 − are both low: in this pH range a flux of acid or base through the soil results in steep pH gradients. This has been corroborated experimentally over a wide range of soil pHs by Nye and Ameloko (1986), as shown in Figure 2.9(b). The data in Figure 2.9(b) were obtained from profiles of pH measured in two blocks of soil of different initial pHs placed in contact.

2.3 EBULLITION Ebullition is the process by which gas bubbles form from volatile solutes in solution and rise to the surface and atmosphere. Bubbles form spontaneously when a solution becomes supersaturated with a volatile solute. Rates of formation of bubbles and ebullition depend on the volatility of the particular solute as well as its concentration in solution. In a soil producing methane, for example, although CH4 and CO2 may be generated in equal proportions (Chapter 5), gas bubbles will contain a large excess of CH4 over CO2 because CH4 is about 20 times more volatile than CO2 . Bubbles form when the sum of the partial pressures of the volatile solutes exceeds the hydrostatic pressure. For a water column containing dissolved N2 , CO2 and CH4 , the condition for formation of a bubble is therefore (Morel and Herring, 1993, Equation 142) PN2 + PCO2 + PCH4 + PH2 O > Pz (2.34) where Pz is the hydrostatic pressure at depth z (= Patm + ρgz). This inequality may be met either because of accumulation of dissolved gases or because of changes in pressure, as for example when a core of mud is brought up from an anaerobic sediment. In flooded soil or sediment, bubbles form through heterogeneous nucleation at the surface of solid particles, rather than by homogeneous nucleation in free solution. Because of this, bubbles form easily and the sum of the partial pressures of volatile solutes tends to be maintained at or near the hydrostatic pressure. Therefore, for a methanogenic sediment, PN2 + PCO2 + PCH4 + PH2 O = Patm + ρgz

(2.35)

This equation can be used to calculate the composition of bubbles and rates of ebullition from rates of gas formation and the volatility of the different species. Thus for a methanogenic sediment in which rates of CH4 and CO2 generation are balanced by their rates of loss to the atmosphere above by diffusion and ebullition, we have for each volatile solute (cf. Morel and Herring, 1993, Equations 144–146)

 CZ − C0 CZ /KH D +ε −R =0 (2.36) Z Patm + ρgZ

39

Mixing by Soil Animals

FE = 2.9

FD = 2.1

FE = 0.3

FD = 4.7

FE = 0.8

FD = −0.8

Depth in overlying water (cm)

0 10

CH4

CO2

N2

20 30 40 50 0.0 0.3 0.6 0.9 0.0 0.3 0.6 0.9 1.2 1.5 1.8 2.1 2.4 0.0 0.3 0.6 Concentration of dissolved gas in water (mM)

Figure 2.10 Concentrations and fluxes of CH4 , CO2 and N2 in anoxic acidic marsh (after Morel and Herring, 1993). FE and FD are the fluxes by ebullition and diffusion, respectively Reproduced by permission of Wiley, New York

where Z is the depth of overlying water, D is the diffusion coefficient of the solute in water, CZ and C0 are the concentration of dissolved solute at sediment surface and water surface, respectively, ε is the rate of ebullition of all gases together, KH is Henry’s law constant and R is the rate of generation of the solute in the sediment. An equation of this type can be written for N2 , CH4 and CO2 and combined with Equation (2.35) and the resulting equation solved to obtain the rates of ebullition and the concentrations of each gas at the sediment surface given the ambient atmospheric concentrations, the rate of methanogensis and the depth of the water. Figure 2.10 compares the relative contributions of ebullition and diffusion to fluxes of CH4 , CO2 and N2 in an anoxic marsh so calculated. The figure shows that CO2 escapes mainly by diffusion whereas more than half the CH4 escapes by ebullition. The bubbles contain 69 % CH4 , 19 % N2 , 5 % H2 O and only 7 % CO2 . In practice gas bubbles may become entrapped under irregularly shaped soil particles, and so the simple steady state described by Equation (2.36) does not hold. The rate of ebullition is then sensitive to mechanical disturbances, induced for example by wading animals or by the action of wind on plants in the sediment. This is discussed further in Chapter 8. 2.4 MIXING BY SOIL ANIMALS The upper few centimetres of the soil are subject to mixing by invertebrates burrowing through the soil and ingesting soil particles. If populations are sufficiently

40

Transport Processes in Submerged Soils

dense, this may have a large effect on solute transfer between the soil and overlying water. Oligochaete worms are often present in submerged soils in populations exceeding several thousand per m2 with burrows extending to several centimetres (Chapter 5). Once the burrows are constructed, the worms remain in them feeding with their heads downward and their posterior ends upward in the overlying water. By waving their posteriors and moving their bodies in a peristaltic motion they cause the water in the burrows to be mixed with the overlying water. Solid particles also fall into the burrows and are mixed. Hence solutes diffusing into a burrow will be rapidly transferred to the surface, and vice versa. The ecology of tubificids and other organisms in the soil and floodwater are discussed in Chapter 5. I here discuss approaches to modelling their effects on solute transfer between the soil and floodwater. Three approaches have been taken to the analogous problem of mixing by invertebrates in marine sediments (Aller, 1980a; Berner, 1980). The simplest approach has been to lump together all the processes involved and to assume that mixing is random and complete to a specified depth. This has been applied successfully to the long-term mixing of sediments under the combined action of invertebrates and waves or currents, but is inappropriate for less perturbed systems and short times. A second approach has been to express the effect of burrowing as increased effective diffusion coefficients of solutes in the pore water, derived by fitting diffusion equations to empirical data (Aller, 1980a; Berner, 1980; van Rees et al., 1996). But the physical basis of this approach is doubtful. A third approach was developed by Aller (1980a, b) who studied solute fluxes in near-shore marine sediments showing seasonal variation. In this approach, the geometry of the burrow–sediment system is allowed for explicitly and transport in the sediment between the burrows is described with appropriate diffusion equations. It is assumed that the burrows are oriented normal to the sediment surface and distributed uniformly or randomly in the horizontal plane (Figure 2.11). Thereby a cylindrical zone of influence is ascribed to each burrow with a radius

burrow (radius = r1)

zone of influence (radius = r2 = 1/√πN)

Figure 2.11 Distribution of worm burrows and cylinders of influence represented by boundary conditions for Equation (2.37)

41

Mixing by Soil Animals

such that the whole sediment volume is accounted for. The water in a burrow is assumed to mix instantaneously with the overlying seawater, and solutes diffuse radially between the burrow and the sediment surrounding it as well as vertically between the sediment and overlying water. The corresponding continuity equation for transport in the sediment influenced by a particular burrow is

 ∂C ∂ ∂C 1 ∂ ∂C = D + rD +R (2.37) ∂t ∂z ∂z r ∂r ∂r where z is the distance from the sediment surface, r is the radial distance from the centre of the cylinder and R is the rate of production or consumption of solute in the sediment. In Equation (2.37), the first term on the right-hand side accounts for diffusion in the vertical direction; the second term accounts for radial diffusion across the cylinder. The following boundary conditions apply. At the sediment–water and sediment–burrow interfaces, the concentrations are the same as in the overlying water: z = 0 C = C0 r = r1

C = C0

At the boundary between adjacent cylinders, there is effectively no transfer of solute: r = r2 dC/dr = 0 √ where the radius of the cylinder, r2 , = 1/ πN , where N is the density of worms per unit sediment surface area. At the bottom of the cylinder, the flux of solute is constant: z = L dC/dz = B The value of B is specified from empirical observations. Aller (1980b) shows that if the mean distance between burrows is small compared with their length, then a steady state (∂C/∂t = 0) will be attained rapidly, and he provides an analytical solution of Equation (2.37) for the steady state subject to the above boundary conditions. (The solution is complicated, involving Bessel functions, and is not reproduced here.) The mean concentration at a particular depth is found by integrating the concentration across the cylinder of sediment at that depth:  r2

2πrC.dr r Cz = 1

(2.38)

r2

2πr.dr r1

Aller uses the model to explain seasonally fluctuating profiles of NH4 + concentration in sediments in Long Island Sound. In this system NH4 + is produced

42

Transport Processes in Submerged Soils

in anoxic decomposition of organic matter in the sediment at a rate decreasing exponentially with depth, R = R0 exp(−αz) + R1

(2.39)

and it is removed by nitrification in the overlying water and in worm burrows. The rate of NH4 + formation and the density of the worms vary with seasonal temperature changes. Figure 2.12 shows concentration profiles of NH4 + in the sediments measured over 2 years and the corresponding profiles predicted by the model using independently measured parameter values. It shows that the main features of the profiles and their seasonal dynamics are satisfactorily predicted. By comparison, a model using the same parameter values but only allowing for diffusion in the vertical direction over-predicted the concentrations several fold. Aller found similar good agreement between observed and predicted profiles and fluxes of SO4 2− and Si in the sediments. He concluded that the model accounted satisfactorily for the important processes operating. The application of this approach is illustrated in Figures 2.13 and 2.14, which show the effects of tubificid worms on the movement of P between a submerged Concentration of NH4+ in solution (µM)

Depth (cm)

0

0

100 200 300 400

0

0

100 200 300 400

0

5

5

5

10

10

10

15

15

0

100 200 300 400

November 1974 0

0

100 200 300 400

March 1975 0

5

5

5

10

10

10

15

15

15

July 1975

100 200 300 400

15

July 1974 0

0

October 1975

0

100 200 300 400

March 1976

Figure 2.12 Concentration profiles of NH4 + at different times in sediments in Long Island Sound. Points are measured data; lines are predicted with Equations (2.37) and (2.39) using independently measured parameter values (after Aller, 1980a). Reprinted with permission from Elsevier

43

Mixing by Soil Animals

0.0

0

Concentration of P in solution (µM) 100 200 300 400 500 600

Depth (cm)

0.5 1.0

N= 30 000

1.5

15 000 5000

2.0 2.5

1000 3.0

0.8

L = 5 cm

0.6

3 0.4 1.5 0.2 0.0

0

10 000 20 000 N (m−2)

30 000

Ratio of soil surface flux to total

P flux (mmol m−2 day−1)

Figure 2.13 Effect of mixing of pore water by tubificid worms on profiles of P concentration in submerged soil calculated with Equations (2.37) and (2.40). Numbers on curves are densities of tubificids

1.0 0.8 0.6 1.5 0.4 3 5

0.2 0.0

0

10 000

20 000

30 000

N (m−2)

Figure 2.14 Effect of mixing by tubificids on flux of P between soil and floodwater calculated with Equations (2.37) and (2.40). Numbers on curves are depths of mixing

soil and overlying floodwater. The primary productivity of the floodwater, including the fixation of N by photosynthetic aquatic organisms, is often limited by the supply of P from the soil. So enhanced P transport resulting from tubificid activities can be important. Figure 2.13 shows calculated concentration profiles of P in the soil near the floodwater for realistic densities of tubificids (see Chapter 5) and other parameters, and Figure 2.14 shows the corresponding fluxes from the soil into the floodwater. Following Aller (1980b) for Si desorption in marine sediments, the rate of P desorption from the soil is calculated with the formula R = k(Ceq − C)

(2.40)

44

Transport Processes in Submerged Soils

where k is a rate constant and Ceq an apparent equilibrium P concentration. Values of k = 10−6 s−1 and Ceq = 0.5 mm were used for the calculations in Figures 2.13 and 2.14. The values of the other parameters used were θL = 0.6, √ fL = 0.4, b = 100, B = 0, r1 = 0.5 mm, r2 = 1/ πN , where the values of N are given in the figures and L = 3 cm. It will be seen that the tubificids have a large effect and the flux of P to the floodwater increased several fold for realistic numbers and dimensions. For comparison, the fluxes of P from the soil required to sustain typical rates of primary production in the floodwater in ricefields are in the range 0.05–0.25 mmol m−2 day−1 , calculated from measured primary production and the P contents of likely photosynthetic organisms given by Roger (1996). Because the tubificids depend upon the photosynthetic organisms for their carbon, there will be a positive feedback between mixing by tubificids and net primary production in the floodwater. Note that the sensitivity of the net flux between the soil and water to the worms’ activities depends on the relation between the rate R and the solute concentration. For the calculations in Figures 2.13 and 2.14, R varies linearly with concentration as specified in Equation (2.40), and the flux is sensitive to worm activity. But where the rate is independent of concentration, as for NH4 + formation in Equation (2.39), the net flux, which in this case is roughly R0 /α + LR1 , is necessarily independent of worm activity, though the distribution of the flux between burrows and the sediment surface and the concentration profile are not. In practice the rate will always depend to some extent on concentration. But the predictions here for the idealized steady state indicate the expected sensitivities.

3 Interchange of Solutes between Solid, Liquid and Gas Phases

This chapter is concerned with how ions and uncharged solutes in the water and soil solution in submerged soils interchange between the solid, liquid and gas phases present. This is a large topic. I give here the bare essentials needed to understand the transport and transformation processes discussed elsewhere in the book, and I give references to more detailed treatments where appropriate. The water and atmosphere overlying the soil are dealt with first and then the additional complexities in the soil. A. WATER 3.1 COMPOSITION OF THE WATER The water contains: • dissolved matter – free ions; – inorganic and organic complexes; – uncharged molecules. • particulate matter – large organic and inorganic polymers; – oxides; – clay minerals; – organic matter. Because of their large surface areas, charged particles are very efficient scavengers of ions from solution, and where the sediment load is large the concentration of adsorbed ions may greatly exceed the concentration in solution. Similarly for ions that form complexes with organic or inorganic ligands, their total concentration in solution may be far greater than the concentration of the free ion. Complexation and sorption are especially important in regulating the concentrations of trace metals in natural water systems. The interactions between ions and charged particles are discussed in the sections on soil. The Biogeochemistry of Submerged Soils Guy Kirk  2004 John Wiley & Sons, Ltd ISBN: 0-470-86301-3

46

Interchange of Solutes between Solid, Liquid and Gas Phases

3.1.1 ACIDS AND BASES The concentrations of dissolved species in natural waters depend ultimately on the dissolution of basic rocks–carbonates, silicates and aluminosilicates–induced by the action of weak acids in the water derived from dissolved gases–e.g. H2 CO3 derived from CO2 . Anions produced in acid–base reactions balance cations produced in dissolution reactions. The charge balance is:
m[cationm+ ] =
n[anionn− ]

(3.1)

Table 3.1 shows the main weak acids present in natural waters and typical concentration ranges. Table 3.2 shows the corresponding equilibrium constants. Table 3.1 shows that carbonic acid is by far the dominant acid with concentrations typically of the order of several mM. It arises from the dissolution of carbonate rocks and atmospheric CO2 , and from the respiration of aquatic and soil organisms. The concentrations of dissolved silica are 5–10 times smaller, and those of ammonium and orthophosphate smaller again, although NH4 + concentrations in the mM range may arise in the water in ricefields following fertilizer applications. The hydrolysis products of certain metals, such as Fe(III) and Al(III), also behave as weak acids and may be important under particular circumstances. Dissolved amino, organic and humic acids are rarely a large part of the charge balance in solution but may be important as metal ligands. The distributions of different acid–base pairs with pH are shown in Figure 3.1. Bicarbonate (HCO3 − ) is the dominant carbonate species at near neutral pH; silicic acid (H4 SiO4 ) is essentially undissociated at all pHs of interest; and the ammonium ion (NH4 + ) is the dominant form of ammoniacal-N at pHs below about 8. Orthophosphate and sulfide have acidity constants near neutral pH. For a given concentration of a particular dissolved acid, the proportions of the component species in the equilibrium solution will depend on the alkalinity of the solution; that is, the balance of cations and non-dissociating anions present. This can be calculated as shown in Table 3.3 for the aqueous carbonate equilibria Table 3.1

Concentrations of weak acids and bases in natural waters Global mean for freshwatera

Range in water

Range in submerged soil solutions

0.97 mM 0.22 mM 0–10 µM 0.7 µM — — —

0.01–10 mM 0.1–0.5 mM 0.001–1 mM 0.5–25 µM Trace Trace 0.001–1 mM

5–100 mM 0.1–1.5 mM 0.001–1 mM 0.5–100 µM 0.01–10 µM 0.1–10 µM 0.1–10 mM

Carbonate Silicate Ammonium Phosphate Sulfide Amino acids Organic acids Source: a Morel and Herring (1993).

47

Composition of the Water Table 3.2 Equilibrium constants for acid–base equilibria at 25 ◦ C, I = 0 Equilibrium

− log K

H2 O = H+ + OH− CO2 (g) + H2 O = H2 CO3 ∗ H2 CO3 ∗ = H+ + HCO3 − HCO3 − = H+ + CO3 2− H4 SiO4 = H+ + H3 SiO4 − H3 SiO4 − = H+ + H2 SiO4 2− NH3 (g) = NH3 (aq) NH4 + = H+ + NH3 (aq) H3 PO4 = H+ + H2 PO4 − H2 PO4 − = H+ + HPO4 2− HPO4 2− = H+ + PO4 3− H2 S(g) = H2 S(aq) H2 S(aq) = H+ + HS− HS− = H+ + S2− CH2 NH2 COOH = H+ + CH2 NH2 COO− CH3 COOH = H+ + CH3 COO−

14.0 1.46 6.35 10.33 9.86 13.1 −1.76 9.24 2.15 7.20 12.35 0.99 7.02 13.9 9.78 4.76

with the equilibrium constants in Table 3.4. Similar calculations can be made for the other dissolved acids. Table 3.3 gives the equilibria in a closed system in which the total carbonate concentration, CT , is fixed. In an open system, such as the water on the surface of a submerged soil, CT is variable and the resulting changes in pH depend on the balance of charge between the non-carbonate anions and cations present. Likewise if a quantity of strong acid, HX, or base, MOH, is added to the solution, the equilibria will adjust so as to neutralize part of the H+ or OH− added and so buffer the change in pH. The changes in [H+ ] with alkalinity or dissolved CO2 can be found from (see Equation 9, Table 3.3): CB − CA = [HCO3 − ] + 2[CO3 2− ] + [OH− ] − [H+ ]

(3.2)

where CA is the concentration of non-carbonate anions after the addition of acid HX and CB is the concentration of cations after addition of base MOH. If CB > CA , the difference CB − CA is the alkalinity of the solution; if CA > CB , the difference CA − CB is the mineral acidity. 3.1.2 SPECIATION Many ions and uncharged molecules are present in solution as more than one species, depending on the concentrations of ligand ions and molecules and the

48

Interchange of Solutes between Solid, Liquid and Gas Phases (a)

HCO3−

H2CO3*

CO32−

(b)

H4SiO4 H3SiO4− H2SiO42−

log activity (arbitrary units)

H2CO3

(c)

NH4+

NH3

(d)

H2PO4−

HPO42− PO42−

H3PO4

(e)

(f)

HS−

H2S

CH3COO−

CH3COOH

S2−

4

5

6

7

8

9

10

11

4

5

6

7

8

9

10

11

pH

Figure 3.1 Distribution of dissolved acid–base species at constant total concentration in solution (after Morel and Herring, 1993). Reproduced by permission of Wiley, New York

solution pH and ionic strength. Complexation of metals with ligands can result in the total concentration of the metal being far greater than the concentration of the free ion. This topic is covered in detail by Morel and Herring (1993), Stumm and Morgan (1996) and, for chelation by humic substances, by Tipping (2002). A complex is a species in which a metal atom or ion is attached by coordinate bonds to one or more ligand ions or uncharged molecules. The complex may itself be positive, negative or uncharged. In forming a coordinate bond the ligand donates a pair of electrons to the metal. In so doing the ligand is acting as a

49

Composition of the Water Table 3.3

Equilibria in aqueous carbonate solutions

Species CO2 (g), CO2 (aq), H2 CO3 , HCO3 − , CO3 2− , H+ , OH− , M+ , X− [H2 CO3 ∗ ]a = [CO2 (aq)] + [H2 CO3 ] Equilibriab [CO2 (aq)]/[CO2 (g)] = H c [H2 CO3 ∗ ]/pCO2 = KH [CO2 (aq)]/[H2 CO3 ] = K [H+ ][HCO3 − ]/[H2 CO3 ] = KH2 CO3 [H+ ][HCO3 − ]/[H2 CO3 ∗ ] = K1

(0) (0a) (1) (2) (2a)

[H+ ][CO3 2− ]/[HCO3 − ] = K2 [H+ ][OH− ] = KW Ionization fractions for constant total carbonate concentration, CT

(3) (4)

CT = [H2 CO3 ∗ ] + [HCO3 − ] + [CO3 2− ] ∗

−

[H2 CO3 ] = α0 CT [HCO3 ] = α1 CT [CO3 ] = α2 CT 
K1 K2 −1 K1 α0 = 1 + + + + 2 [H ] [H ] −1
+ [H ] K2 +1+ + α1 = K1 [H ]
+2 −1 [H ] [H+ ] + +1 α2 = K1 K2 K2 Electrical neutrality condition [H+ ] + [M+ ] = [HCO3 − ] + 2[CO3 2− ] + [OH− ] + [X− ] The ‘apparent’ concentration of H2 CO3 since [CO2 (aq)]  [H2 CO3 ]. Equilibrium constants are defined at constant ionic strength. Dimensionless Henry’s law constant, in which [CO2 (g)] = PCO2 /RT . Source: Stumm and Morgan (1996). Reproduced by permission of Wiley, New York.

a b c

Table 3.4 Equilibrium constants for carbonate equilibria at 25 ◦ C, I = 0 Equilibrium CO2 (g) + H2 O = H2 CO3 H2 CO3 ∗ = H+ + HCO3 − HCO3 − = H+ + CO3 2− H2 O = H+ + OH− a

PCO2 in kPa.

Constant ∗

(5)

2−

− log K

a

KH K1

3.47 6.35

K2 KW

10.33 14.0

(6) (7) (8)

(9)

50

Interchange of Solutes between Solid, Liquid and Gas Phases

Lewis base and the metal as a Lewis acid. A characteristic of ligands is that they have a lone pair of electrons which they can donate to empty electron orbitals on the metal. Some ligands also have empty p- or d-orbitals and can produce complexes in which a double bond is formed with the metal: a sigma bond by donation of the lone pair from the ligand to the metal and a pi bond by back donation of electrons on the metal to empty d-orbitals on the ligand. The term chelate is reserved for species involving polydentate ligands that form a ring of atoms including the metal. Inorganic and organic ligands contain the following electron donor atoms from Groups IVB to VIIB of the Periodic Table: C

N O F P S Cl As Se Br Te I

Formation of coordination complexes is typical of transition metals, but other metals also form complexes. The tendency to form complexes is a function of the metal’s electron configuration and the nature of its outer electron orbitals. Metal cations can be classified into types A and B based on their coordination characteristics, as shown in Table 3.5. A-type cations, which tend to be from the left side of the Periodic Table, have the inert-gas type electron configuration with largely empty d-orbitals. They can be imagined as having electron sheaths not easily deformed under the influence of the electric fields around neighbouring ions. B-type cations have a more readily deformable electron sheath. In consequence, A-type cations form complexes preferentially with the fluoride ion and ligands having oxygen as their electron donor atom. They are attracted to H2 O more strongly than to NH3 or CN− , and they do not form sulfides because OH− ions readily displace HS− or S2− ions. They tend to form sparingly soluble precipitates with OH− , CO3 2− and PO4 3− . By contrast, B-type cations coordinate preferentially with ligands containing I, S or N as electron donors. They may bind NH3 more strongly than H2 O and CN− more strongly than OH− , and they tend not to form complexes with the main functional groups in organic matter, which have O as electron donor. They form insoluble sulfides and soluble complexes with S2− and HS− . Table 3.6 shows the major inorganic species expected in a solution with a composition typical of natural fresh water. Some calculations for organic ligands in submerged soil solutions are given in Section 3.7.

3.1.3 EQUILIBRIUM CALCULATIONS Complete calculations of chemical equilibria in natural waters and soil solutions are complicated because such a large number of solutes, solids and gases are

51

Composition of the Water Table 3.5

Classification of metal ions

A-type metal cations

Transition-metal cations

B-type metal cations

Electron configuration of inert gas, low polarizability, ‘hard spheres’

One to nine outer shell electrons, not spherically symmetric

Electron number corresponds to Ni0 , Pd0 and Pt0 (10 or 12 outer shell electrons), low electronegativity, high polarizability, ‘soft spheres’

(H+ ), Li+ , Na+ , K+ , Be2+ , Mg2+ , Ca2+ , Sr2+ , Al3+ , Sc3+ , La3+ , Si4+ , Ti4+ , Zr4+ , Th4+

V2+ , Cr2+ , Mn2+ , Fe2+ , Co2+ , Ni2+ , Cu2+ , Ti3+ , V3+ , Cr3+ , Mn3+ , Fe3+ , Co3+

Cu+ , Ag+ , Au+ , Tl+ , Ga+ , Zn2+ , Cd2+ , Hg2+ , Pb2+ , Sn2+ , Tl3+ , Au3+ , In3+ , Bi3+

Ligands F > O > N = Cl > Br > I>S OH− > RO− > RCOO−

Ligands S > I > Br > Cl = N > O > F

CO3 2−  NO3 − PO4 3−  SO4 2−  ClO4 − Source: Stumm and Morgan (1996). Reproduced by permission of Wiley, New York.

involved. However general computer programs are available to perform such calculations using successive approximation (Melchior and Bassett, 1990; Mangold and Tsang, 1991; Sposito, 1994). WHAM (Tipping, 1994, 2002) gives particular attention to reactions involving humic substances. An important component of equilibrium calculations is the conversion between ion activities, which equilibrium constants refer to, and ion concentrations, which mass balance and electrical neutrality equations refer to. The conversion is made with activity coefficients defined by the relation: ai = γi Ci

(3.3)

Various empirical relations are available for calculating individual ion activity coefficients [discussed by Stumm and Morgan (1996) for natural waters and Sposito (1984a, b), for soil solutions]. In the calculations in this book I used the Davies equation:  √  I log γ = −AZ 2 √ − 0.3I 1+ I

(3.4)

where I is ionic strength (= 12
Ci Zi 2 ), Z is ionic charge and A = 1.82 × 106 (εT )−1.5 , where ε is the dielectric constant (A ≈ 0.5 for water at 25 ◦ C). This relation is valid for I < 0.5 m.

52

Interchange of Solutes between Solid, Liquid and Gas Phases

Table 3.6

Major inorganic species in representative natural water

Condition

Element

Major species

Fresh water [Mn+ /MT ]

B(III)

H3 BO3 , B(OH)4 −

V(V)

HVO4 2− , H2 VO4 −

Hydrolysed,

Cr(VI)

CrO4 2−

anionic

As(V)

HASO4 2−

Se(VI)

SeO4 2−

Mo(VI)

MoO4 2−

Si(IV)

Si(OH)4

Li Na

Li+ Na+

1.00 1.00

Mg K

Mg2+ K+

0.94 1.00

Ca

Ca2+

0.94

Predominantly free aquo ions

2+

Sr Cs

Sr Cs+

0.94 1.00

Ba

Ba2+

0.95

Be(II) Al(III)

BeOH+ , Be(OH)2 0 Al(OH)3 (s), Al(OH)2 + , Al(OH)4 −

1.5 × 10−3 1 × 10−9

Ti(IV) Mn(IV) Fe(III)

TiO2 (s), Ti(OH)4 0 MnO2 (s) Fe(OH)3 (s), Fe(OH)2 + , Fe(OH)4 −

2 × 10−11

Co(II)

2+

Co , CoCO3

0

0

2+

0.5 2+

Ni(II)

Ni , NiCO3 (Ni , NiCl)

0.4

Complexation with

Cu(II)

CuCO3 0 , Cu(OH)2 0

0.01

OH− , CO3 2− ,

Zn(II)

Zn2+ , ZnCO3 0 (Zn2+ , ZnCl)

0.4

Ag(I)

Ag+ , AgCl0 (AgCl2 − , AgCl)

0.6

−

HCO3 , Cl

−

0

2+

Cd(II) La(III)

Cd , CdCO3 (CdCl2 ) LaCO3 + , La(CO3 )2 −

0.5 8 × 10−3

Tl(I), Tl(III)

Tl+ , Tl(OH)3 0 , Tl(OH)4 −

2 × 10−21

Hg(II)

Hg(OH)2 0 (HgCl4 2− )

1 × 10−10

Pb(II) Bi(III)

0

+

PbCO3 (PbCl , PbCO3 ) Bi(OH)3

5 × 10−2 7 × 10−16

Fresh water conditions: pH = 8, Alk = 2 mM, [SO4 2− ]T = 0.3 mM, [Cl− ] = 0.25 mM, [Ca2+ ]T = 1 mM, [Mg2+ ]T = 0.3 mM, [Na+ ]T = 0.25 mM, O2 at saturation with air, I = 5 mM. Source: Stumm and Morgan (1996). Reproduced by permission of Wiley, New York.

53

pH Buffer Capacity

3.2 pH BUFFER CAPACITY The extent to which the pH of a solution is buffered against additions or removals of protons is measured by the solution’s pH buffer capacity. This is defined as the amount of strong acid or base required to produce unit change in pH. The buffering depends on the transfer of protons between donors and acceptors, i.e. Bronsted acids and bases, which form conjugate acid–base pairs. The pH buffer capacity of a solution is calculated from the buffer capacities of the individual acid–base pairs present. Consider a generic acid–base pair HX–X− representing the various acid–base pairs in a solution. The pH buffer capacity of the HX–X− pair is defined as bHX =

d[X− ] d pH

(3.5)

The total concentration of the pair is [HX] + [X− ] = [Xtotal ] and from the acidity constant, K, [HX] = [H+ ][A]/K, hence [X− ] =

[Xtotal ] [H ]/K + 1

(3.6)

+

Substituting in Equation (3.5) for [X− ] from Equation (3.6)   d 1/ [H+ ]/K + 1 bHX = [Xtotal ] d pH Hence bHX

(3.7)

  d[H+ ] d 1/ [H+ ]/K + 1 K[H+ ] = 2.303[Xtotal ]  = [Xtotal ] 2 + d pH d[H ] K + [H+ ]

or bHX = 2.303

[HX][X− ] [HX] + [X− ]

(3.8)

The total buffer capacity of the solution is equal to the sum of the buffer capacities of the individual acid–base pairs present, each given by an equation like Equation (3.8). In an aqueous solution of acid HA, three acid–base pairs are present: HA–A− , H3 O+ –H2 O and H2 O–OH− . Because [H3 O+ ] and [OH− ] are both negligible compared with [H2 O], in Equation (3.8) [X− ] = ([HX] + [X− ]) for H3 O+ –H2 O and [HX] = ([HX] + [X− ]) for H2 O–OH− . Hence bH3 O+ = 2.303[H3 O+ ] −

bOH− = 2.303[OH ] Therefore


[HA][A− ] bsolution = 2.303 [H3 O+ ] + [OH− ] + [HA] + [A− ]

(3.9) (3.10)

(3.11)

54

Interchange of Solutes between Solid, Liquid and Gas Phases

If other acid–base pairs are present the buffer capacity is 
[HB][B− ] [HA][A− ] + − + + .... bsolution = 2.303 [H3 O ] + [OH ] + [HA] + [A− ] [HB] + [B− ] (3.12) Polyprotic acids can be treated as a mixture of monoprotic acids. For example, consider the diprotic acid H2 C which forms the acid–base pairs H2 C = HC− + H+ and HC− = C2− + H+ . The acidity constants are K1 = [H+ ][HC− ]/[H2 C] and K2 = [H+ ][C2− ]/[HC− ], respectively. The total buffer capacity of the solution is therefore   − − 2− [HC C][HC ] ][C ] [H 2 + bsolution = 2.303 [H3 O+ ] + [OH− ] + [H2 C] + [HC− ] [HC− ] + [C2− ] (3.13) For example, for a solution buffered by the CO2 –H2 O–H2 CO3 –HCO3 − system, application of Equation (3.13) gives bsolution = 2.303{[H3 O+ ] + [OH− ] + [α1 (α0 + α2 ) + 4α2 α0 ] CT }

(3.14)

where α0 , α1 and α2 are ionization fractions defined in Table 3.3. This equation predicts that the buffer capacity will pass through minima at pH 4–4.5 where [H3 O+ ] and [HCO3 − ] are both low, at pH 8.3 where [H2 CO3 ] and [CO3 2− ] are low, and at pH 10.5–11 where [HCO3 − ] and [OH− ] are low. At these pH ranges, changes in the concentrations of acids or bases in the solution will cause large pH changes.

3.3 EQUILIBRIUM WITH THE GAS PHASE The equilibrium distribution of a volatile solute between gas and liquid phases is described by Henry’s law. For the equilibrium A(l) = A(g) in a dilute solution at low gas pressure, [A(l)] = KH pA (3.15) where [A(l)] is the concentration of the dissolved gas in solution, pA is the partial pressure in the gas phase and KH is the Henry’s law constant. (At high concentrations or gas pressures, [A(l)] and pA are replaced by the corresponding activities and fugacities.) The constant is also sometimes expressed in dimensionless form, H, such that [A(l)] = H [A(g)] (3.16) where [A(g)] is the concentration in the gas phase. Hence H = RT KH

(3.17)

55

Equilibrium with the Gas Phase Table 3.7 Henry’s law constants for important gases in submerged soils at 25 ◦ C and typical partial pressures in the atmosphere Typical partial pressure

KH (M kPa−1 )

(kPa)

−6

6.52 × 10 1.24 × 10−5 3.35 × 10−4 1.27 × 10−5 5.63 × 10−1 1.04 × 10−3 9.87 × 10−5 1.88 × 10−5 2.54 × 10−5

N2 O2 CO2 CH4 NH3 H2 S NO2 NO N2 O

78 21 3.5 × 10−2 1.7 × 10−4 0.1–5 × 10−7 < 2 × 10−8 1–5 × 10−7 1–5 × 10−8 3 × 10−5

where R is the gas constant (= 8.314 kPa L mol−1 K−1 ) and T is the temperature (K). Values of KH for important gases in submerged soils are given in Table 3.7. For some volatile solutes, slow reactions influence the rate of equilibration between the gas and liquid phases. Generally the rate of gas transfer across the liquid–gas interface is the rate-limiting step, as discussed in Section 3.4. But there may also be slow hydration or other reactions in solution that must be allowed for. An important example is the hydration of CO2 , whose half-life may be comparable to rates of transfer of CO2 across the air–water interface. Kinetics of CO2 Hydration The kinetics of the hydration and dehydration reactions are slow in comparison with some processes in the water. The reactions are kf 1

−− −− → CO2 + H2 O − ← − H2 CO3

(3.18)

kb1

and

kf 2

− + −− −− → CO2 + H2 O − ← − HCO3 + H

(3.19)

kb2

and the corresponding rate law is −

   d[CO2 ]  = kf 1 [CO2 ] − kb1 [H2 CO3 ] + kf 2 [CO2 ][OH− ] − kb2 [HCO3 − ] dt (3.20)

56

Interchange of Solutes between Solid, Liquid and Gas Phases

Substituting from Table 3.3 for the equilibrium constant for dissociation of H2 CO3 , which is fast, −

   d[CO2 ]  = kf 1 + kf 2 [CO2 ] − kb1 + kb2 KH2 CO3 [H2 CO3 ] dt

or −

d[CO2 ] kH CO = kCO2 [CO2 ] − 2 3 [H+ ][HCO3 − ] dt KH2 CO3

(3.21)

(3.22)

where kCO2 = kf1 + kf2 and kH2 CO3 = kb1 + kb2 KH2 CO3 . Equation (3.22) corresponds to the simplified scheme kCO2

fast

+ − −− −− → −− −− → CO2 + H2 O − ← − H2 CO3 − ← − H + HCO3

(3.23)

kH2 CO3

That is, the hydration reaction is first order with respect to dissolved CO2 . The rate constant kCO2 = 0.025–0.04 s−1 (25 ◦ C) and activation energy ≈63 kJ mol−1 . For the dehydration reaction, kH2 CO3 = 10–20 s−1 (20–25 ◦ C) and activation energy ≈67 kJ mol−1 . 3.3.1 FLOODWATER CO2 DYNAMICS The pH of the water on the surface of a submerged soil often depends on the activity of photosynthetic organisms. Photosynthesis by aquatic plants and algae removes dissolved CO2 during the day, but at night the net respiratory activity of the organisms returns CO2 to the water and the concentration of dissolved CO2 and acidity increase: photosynthesis

−−− −− −− −− −− −− → CO2 + H2 O ← − CH2 O + O2

(3.24)

respiration

where CH2 O is organic matter produced in photosynthesis or consumed in respiration. As a result the pH may rise as high as 10 during the day but fall by two or three pH units at night. Figure 3.2 shows measured diurnal changes in pH and carbonate species in the floodwater of a ricefield. The relations between pH, alkalinity and carbonate equilibria are described by Equation (3.2). Equation (3.24) shows that photosynthesis and respiration do not affect the alkalinity of the water per se. The pH increases or decreases with the change in CT at constant alkalinity. The change in pH depends on the alkalinity as it affects the initial pH and the consequent acid–base system operating. At pHs below pK1 (= 6.3), CO2 (aq) is the dominant species and there is little change in pH with CT . Between pK1 and + pK2 (= 10.3)HCO− 3 is the dominant species and roughly 1 mol of H is consumed − + per C fixed in photosynthesis (HCO3 + H → CH2 O + O2 ), with a correspondingly greater pH change. At pHs above pK2 , CO3 2− is the dominant species and roughly 2 mol of H+ are consumed per C fixed (CO3 2− + 2H+ → CH2 O + O2 ),

57

Equilibrium with the Gas Phase 10 60

90

50 pH 40

80 15

10

30

20

Free CO2 2−

5

H2CO3

CO3

9

8

pH

HCO3−

Free CO2 content (mg L−1)

Percent mole fraction of H2CO3, HCO3− and CO32−

100

7

10

0 0 600 800 1000 1200 1400 1600 1800 2000 2200 Time

6

Figure 3.2 Diurnal changes in pH and concentrations of carbonate species in the floodwater in a ricefield (Mikkelsen et al., 1978). Reproduced by permission of Soil Sci. Soc. Am.

and the pH change is correspondingly larger again. Figure 3.3 shows calculated changes in pH for a sinusoidally varying floodwater [H2 CO3 ∗ ] over the day for two different alkalinities. The dissolved CO2 concentrations are the same in Figure 3.3(a) and (b); only the alkalinities differ. In principle, the alkalinity of the water will also be affected by the balance of nutrient ions consumed and released by organisms in the water. But in practice these have a minor affect compared with CO2 . The average composition of the algal biomass in natural waters is given by the Redfield formula (Redfield, 1934) as C106 H263 O110 N16 P. Therefore for the complete stoichiometry of algal photosynthesis and respiration, we have with NO3 − as the source of N 106CO2 + 16NO3 − + H2 PO4 − + 122H2 O + 17H+ = C106 H263 O110 N16 P + 133O2 and with NH4 +

(3.25)

106CO2 + 16NH4 + + H2 PO4 − + 106H2 O = C106 H263 O110 N16 P + 106O2 + 15H+

(3.26)

The corresponding changes in alkalinity are +17/106 = +0.16 molc per mol C fixed for NO3 − nutrition and −15/106 = −0.14 molc per mol C fixed for NH4 + nutrition. More significant changes in the alkalinity of ricefield floodwater are

58

Interchange of Solutes between Solid, Liquid and Gas Phases (a) [Alk] = 10 mM 1.0 Free CO2

0.8

40 HCO3−/C T

8.5 30

pH

8.0

0.6 20 0.4

7.5 7.0

2−/C

H2CO3*/C T

CO3

10 6.5

T

0.0

0

(b) [Alk] = 0.5 mM 1.0

40

Free CO2

0.8

HCO3−/C T 30

6.0 pH

0.2

Free CO2 (mg L−1)

Ratio of H2CO3*, HCO3− or CO32− to C T

9.0

9.0 8.5 8.0

0.6 pH

20

7.5

0.4 7.0 H2CO3*/C T

0.2 0.0

10 6.5

6

8

10 12 14 16 18 Time (h past midnight)

20

0 22

6.0

Figure 3.3 Calculated diurnal changes in the pH and concentrations of carbonate species in ricefield floodwater for sinusoidally varying [H2 CO3 ∗ ] with (a) [Alk] = 10 mM, (b) [Alk] = 0.5 mM. The free CO2 concentrations are in mg L−1 to be consistent with Figure 3.2

caused by additions of nitrogenous fertilizers. Effects on pH again depend on initial pH and corresponding buffer systems operating. 3.4 GAS TRANSPORT ACROSS THE AIR–WATER INTERFACE The floodwater is for the most part not in equilibrium with the atmosphere because rates of production of volatile solutes in the water exceed rates of gas exchange across the air–water interface. In particular, during the day, rates of CO2 consumption and O2 production by photosynthesizing organisms are generally sufficient to cause undersaturation of CO2 and supersaturation of O2 . Conversely, at night, respiration causes depletion of O2 and supersaturation of CO2 . The underlying soil is also a large sink for O2 and source of CO2 . The resulting diurnal changes in dissolved CO2 can cause large changes in floodwater pH, often from near neutral at night to pH 10 during the day.

59

Gas Transport Across the Air–Water Interface turbulent bulk air

still air layer

dzG

still water layer

dz L

turbulent bulk water

Figure 3.4

The air–water interface

Two main approaches have been taken to modelling the air–water interface in natural systems so as to calculate rates of volatilization and dissolution (Liss and Slater, 1974; Frost and Upstill-Goddard, 1999; McGillis et al., 2001). In the simpler the interface is viewed as two thin still layers, one in the air and one in the water, separating well-mixed bulk phases (Figure 3.4). Transport across the still layers is by diffusion. The still layers arise because of the increased viscosity of the air and water near the interface. Their thicknesses depend on such factors as wind speed and surface roughness. Under turbulent conditions, the thickness of the still layers is reduced and rates of gas transport correspondingly increased. At steady state the fluxes across the layers are equal. Therefore, if the gas undergoes no reactions, we have from Fick’s first law F =−

DG DL (CG0 − CG ) = − (CL − CL0 ) δzG δzL

(3.27)

where subscripts G and L indicate the gas and liquid phases, respectively, and subscript 0 indicates the interface. The alternative approach considers that turbulent eddies periodically mix the surface layers with the bulk fluids. The flux across the interface is related to the concentration difference by a transfer coefficient equal to the square root of the diffusion coefficient divided by a characteristic time, τ , representing the frequency of mixing. Thus   DG DL F =− (CG0 − CG ) = − (CL − CL0 ) (3.28) τG τL Neither model accounts completely for the processes operating in the interface, and they provide similar fits to empirical data (Frost and Upstill-Goddard, 1999). However the first model has the advantage of conceptual simplicity and I use it in the following sections.

60

Interchange of Solutes between Solid, Liquid and Gas Phases

If the gas obeys Henry’s law, then CL0 = H CG0

(3.29)

where H is the dimensionless Henry’s law constant. Eliminating CG0 between Equations (3.27) and (3.29) gives F =

1 1 (CG − CL0 /H ) = (CL0 − CL ) kG kL

(3.30)

where kG (= DG /δzG ) and kL (= DL /δzL ) are transfer coefficients for the gas and liquid phases, respectively. Hence CL0 can be eliminated to obtain the following equation for the flux through the water film F =

1 (CG − H CL ) 1/kL + H /kG

(3.31)

In Equation (3.31), 1/kL is the resistance to transfer through the liquid film and H /kG is the resistance to transfer through the gas film. The relative importance of these resistances is given by the ratio resistance in gas phase kL =H resistance in liquid phase kG

(3.32)

Table 3.8 gives values of this ratio for important gases in submerged soils. Most of the gases are sparingly soluble, and the resistance in the liquid phase is much greater than that in the gas. This is because diffusion coefficients in water are two orders of magnitude smaller than those in air and because, for these gases, H is small. But for very soluble gases, such as NH3 , resistance in the gas phase may be limiting. Solubility varies much more between different gases than the diffusion coefficients and is therefore the main determinant of whether gas or liquid phase resistance is limiting. If H is less than about 5, transport in the Table 3.8 Relative importance of resistances in air (rG ) and in water (rL ) to gas transfer across an air–water interface at 25 ◦ C and 1 atm (Equation 3.32)

O2 CO2 CH4 H2 S N2 NH3 N2 O NO a

DG (dm2 s−1 )

DL (dm2 s−1 )

H

rG /rL a

2.05 × 10−3 1.55 × 10−3 2.20 × 10−3 1.66 × 10−3 2.04 × 10−3 2.19 × 10−3 1.55 × 10−3 2.04 × 10−3

2.26 × 10−7 1.93 × 10−7 1.73 × 10−7 2.00 × 10−7 2.02 × 10−7 2.49 × 10−7 1.98 × 10−7 2.55 × 10−7

3.08 × 10−2 8.29 × 10−1 3.16 × 10−2 2.57 1.62 × 10−2 1.39 × 103 6.29 × 10−2 4.65 × 10−2

3.40 × 10−6 1.03 × 10−4 2.48 × 10−6 3.09 × 10−4 1.59 × 10−6 0.159 8.03 × 10−6 5.81 × 10−6

For δzL = δzG and assuming gases do not react with water.

Gas Transport Across the Air–Water Interface

61

liquid phase is limiting; if it is greater than about 500, transport in the gas phase is limiting. However, this simple picture only applies to gases that do not undergo reactions in the boundary layers. For gases that do react, for example through hydration and acid–base reactions, the net flux depends on the simultaneous movement of all the solutes involved, and the flux will not be the simple function of concentration expressed in Equation (3.25). An example is CO2 , which reacts with water to form carbonic acid and carbonate species–H2 CO3 , HCO3 − and CO3 2− . The situation is complicated because the exchange of H+ ions in the carbonate equilibria results in a pH gradient across the still layer, and it is therefore necessary to account for the movement of H+ ions across the still layer as well as the movement of carbonate species. The situation is further complicated in the case of CO2 by the kinetics of hydration and dehydration, which may be slow in comparison with transport. 3.4.1 CO2 TRANSFER ACROSS THE AIR–WATER INTERFACE Under equilibrium conditions, the bulk of the dissolved CO2 is present as HCO3 − or CO3 2− or both if the pH is greater than about 6. Therefore, where a gradient of CO2 concentration exists across a solution, the net flux of CO2 will be greatly increased if there is rapid equilibration between the dissolved CO2 and carbonate species. Consequently, most plants and animals have evolved enzyme systems to catalyse the hydration–dehydration equilibria and the enzyme responsible—carbonic anhydrase—is present in most plant and animal cells. It is likely that this enzyme will often be present extracellularly in natural waters. This is because many aquatic plants use HCO3 − for photosynthesis under low CO2 conditions by catalysing the conversion of HCO3 − to CO2 outside the plasma membranes of leaf cells. The mechanism involves catalysis by extracellular carbonic anhydrase in conjunction with H+ extrusion across the plasma membrane (Graham et al., 1984; Tsuzuki and Miyachi, 1989). Since at least some forms of the enzyme are soluble, appreciable concentrations should arise in the water under intense algal growth, though the stability of the enzyme under high light and O2 conditions is unknown. The presence of carbonic anhydrase or similar enzymes catalysing CO2 hydration has been demonstrated in seawater with corresponding differences in rates of CO2 exchange (Berger and Libby, 1969). The following calculations show the range of effects from infinitely slow hydration–dehydration to infinitely fast. Emerson (1975) and Kirk and Rachhpal-Singh (1992) and have made calculations allowing for the kinetics of the uncatalysed hydration–dehydration reactions, giving intermediate results. We have for the flux of CO2 across the still air layer an equation of the type FG = −

DG (CG − CL0 /H ) δzG

(3.33)

62

Interchange of Solutes between Solid, Liquid and Gas Phases

At steady state the flux of CO2 gas must equal the net flux of dissolved CO2 and carbonate species, therefore FGC = FLC = FLH2 CO3 ∗ + FLHCO3 − + FLCO3 2−

(3.34)

where H2 CO3 ∗ represents CO2 (aq) + H2 CO3 . The fluxes of the uncharged solutes, CO2 and H2 CO3 , are given by equations of the type DLA FLA = − (CLA − CLA0 ) (3.35) δzL The fluxes of charged solutes depend on the diffusion potential arising from differences in the mobilities of individual ions, as well as on an ion’s own concentration gradient (Equation 2.21). The effect of diffusion potentials will be important if the carbonate species are a large part of the total ion concentration, as they often will be. Therefore we have for the net flux of ion B FLB = −DLB

dCLB
DLi dCLi /dz + ZB CLB DLB dz
Zi 2 DLi CLi

(3.36)

where subscript i refers to all the co- and counter-ions in solution and ZB and Zi are the ionic charges. This gives FLB ≈ −

DLB ZB (CLB + CLB0 )DLB Φ (CLB0 − CLB ) + δzL 2

(3.37)

where Φ=


DLi dCLi /dz
Zi 2 DLi CLi

There is an equation of this type for each of the ions present. The principal cations and anions in floodwaters are generally Ca2+ , Cl− , 2− − HCO− 3 , CO3 and OH . Therefore we have five equations of type (3.37) for the fluxes of the five charged species, Equation (3.33) for CO2 gas and Equation (3.35) for H2 CO3 ∗ . These seven equations contain six unknowns—the concentrations of H2 CO3 ∗ and the five ions in solution at the interface—and these are found with the following six equations: Equation (3.34), Equations (1)–(3) in Table 3.3, and FLCa2+ = 0 and FLCl− = 0—i.e. no net flux of Ca2+ and Cl− across the interface, their concentration gradients being balanced by their diffusion potential gradients. Note that charge balance between the diffusing ions is inherent in Equation (3.37). Note also that the movement of H+ ions formed in the carbonate equilibria is allowed for in the movements of the various conjugate acid–base pairs present: H2 CO3 –HCO3 − , HCO3 − –CO3 2− and H2 O–OH− . For each mol of CO2 entering or leaving the water, 1 mol of H+ is added or removed at the

63

Gas Transport Across the Air–Water Interface

interface and transferred to or from the bulk solution by the diffusion of conjugate acid–base pairs. Thus FGC = FLH2 CO3 ∗ − FLCO3 2− − FLOH−

(3.38)

which is inherent in the mass and charge balances. Figure 3.5 shows calculated concentration profiles in the still water layer for realistic conditions in ricefields. In figure 3.5(a) the CO2 pressure is large, the pH in the bulk solution correspondingly low (pH 6.7), and the movement of dissolved CO2 to the interface primarily as H2 CO3 ∗ . The loss of CO2 raises the pH at the interface (to pH 8.2), tending to offset the depletion of HCO3 − and the gradient of HCO3 − concentration is small. In figure 3.5(b) the CO2 pressure is small, the pH in the bulk solution correspondingly high (pH 10.6), and the movement of dissolved CO2 away from the interface is primarily as HCO3 − . Dissolution of CO2 lowers the pH at the interface (to pH 8.3) and there is therefore a gradient of decreasing OH− towards the interface. The gradient of CO3 2− is also negative. Since the mobility of OH− is about five times that of HCO3 − and CO3 2− , there is therefore an excess negative potential at the interface and as a result Ca2+ diffuses to the interface and Cl− away. (a) 0.00 0.0

Concentration (mM) 0.50 0.75

0.25

Depth (mm)

Cl−

1.00

1.25

HCO3−

Ca2+

OH− H2CO3*

0.1 (b) 0.0 Cl−

Ca2+

Depth (mm)

H2CO3*

HCO3−

2−

CO3

OH−

0.1

Figure 3.5 Profiles of CO2 , HCO3 − , etc. across still water layer. Still layer thickness both = 1000 µm, [Ca2+ ]L∞ = 0.5 mM, [Cl− ]L∞ = 0.15 mM, PCO2 L∞ = 1 kPa (a), 2.5 × 10−5 kPa (b)

64

Interchange of Solutes between Solid, Liquid and Gas Phases

CO2 flux (kg C ha−1 h−1)

15

10 with CO2 hydration 5

0 without −5 −10 0.01

0.1

1 10 100 1000 CO2 pressure (Pa)

Figure 3.6 Flux of CO2 as a function of CO2 pressure with and without carbonate equilibria

Figure 3.6 shows how the flux of CO2 across the interface varies with CO2 pressure in the bulk solution, with and without equilibration between CO2 and carbonate species in the boundary layer. A positive flux indicates dissolution and a negative flux volatilization. The figure shows that the effect of the carbonate equilibria is very marked at small CO2 pressures, but insignificant at large pressures where transport across the boundary layer is primarily as H2 CO3 ∗ . At small CO2 pressures the rate of dissolution is enhanced many fold by the carbonate equilibria, the effect increasing as the CO2 pressure decreases and the pH of the bulk solution correspondingly increases. An important practical problem in ricefields is the loss of N fertilizer through volatilization of NH3 from the floodwater. Loss of NH3 is sensitive to the pH of the floodwater, and hence is intimately linked to the dynamics of dissolved CO2 (Bouldin and Alimago, 1976). To quantify this it is necessary to consider the simultaneous transfers of CO2 and NH3 across the air–water interface and their coupling through acid–base reactions. There is an equation of type (3.33) for the flux of NH3 across the still air layer and, as for the dissolved CO2 and carbonate species, the flux across the still water layer is FGN = FLN = FLNH4 + + FLNH3 + FLNH4 OH

(3.39)

The acid–base pairs involved are NH4 + –NH3 and NH4 + –NH4 OH, in addition to those listed above, and we have FGC − FGN = FLH2 CO3 − FLCO3 2− − FLNH3 − FLNH4 OH − FLOH

(3.40)

Equation (3.40) is inherent in the mass and charge balances. These equations can be solved as before to calculate the simultaneous fluxes of CO2 and NH3 across the air–water interface.

The Solid Surfaces in Soils

65

B. SOIL In addition to the factors considered for water, we need to consider for soil: (a) the far greater importance of interactions with solid surfaces and the buffering of ions in solution by ions adsorbed on the surfaces; and (b) the more-strongly reducing conditions that develop in soil because of the greater sink for O2 , resulting in transformations of soil surfaces as well as of species in solution. Figure 3.7 shows the concentrations of cations in solution following submergence of four representative rice soils; the corresponding changes in EH , pH, HCO3 − , CEC and soil Fe are shown in Figures 2.6 and 2.7. The main anion in solution is HCO3 − derived from CO2 together with Cl− : any NO3 − ions present before submergence are rapidly consumed in reduction and consequently their concentration is generally negligible after the initial stages, and SO4 2− ions are also reduced though more slowly. These unadsorbed anions determine the overall strength of the soil solution and balance cations derived from exchange, dissolution and redox reactions involving the soil solid. Redox processes are discussed in detail in Chapter 4. The rest of this chapter deals with solid–solution interactions, firstly for soils in general and then for submerged soils. Recent reviews of solid–solution interactions in soils include Sposito (1994), Sparks (2003) and the relevant chapters of Sumner (2000).

3.5 THE SOLID SURFACES IN SOILS The main surfaces with which ions interact are clay-sized particles of layer silicates and Al, Fe and Mn oxides, and organic matter bound to clay particles. Their interactions with ions depend on their functional groups. These are analogous to the functional groups on molecules in solution but differ in that they are held a fixed distance apart and their charge characteristics may be strongly influenced by the neighbouring functional groups.

Layer Silicates The layer silicates comprise tetrahedral sheets of silica and octahedral sheets of aluminium and magnesium hydroxide, with varying amounts of the Si, Al and Mg replaced by cations of lower valence giving the lattice a net negative charge. Two basic combinations occur: 1 tetrahedral sheet with 1 octahedral (e.g. kaolinite, halloysite), and 2 tetrahedral with 1 octahedral (e.g. smectite, vermiculite, illite). 1:1 Type. The tetrahedral and octahedral sheets are bound together because they share an oxygen atom, and the resulting layers are bound together by hydrogen bonds between the oxygens of the tetrahedral sheet and the hydroxyls of the adjacent octahedral sheet. The structure is therefore rigid. Pure kaolinite, formula

66

Interchange of Solutes between Solid, Liquid and Gas Phases 7 Iloilo

6

Fe2+

5 4 Ca2+

3

Mg2+

NH4+

2

Na+

1

K+

Mn2+

0 16 Maahas

14 Concentration in soil solution (mmolc L−1)

12 10

Ca2+

8 Mg2+

6 4

Na+

Fe2+

2 0 20

Nueva Ecija 15 Ca2+ 10 Mg2+ 5

Na+ Fe2+

0 6 5

Ca2+

Tarlac

4 3

Mg2+

2

0

Na+

Fe2+

1 0

20

40

60

80

Time after flooding (days)

Figure 3.7 Changes in the concentrations of cations in solution following flooding of four rice soils (Kirk et al., 2003). The corresponding changes in EH , pH, HCO3 − , CEC and soil Fe are shown in Figures 2.6 and 2.7. Reproduced by permission of Blackwell Publishing

67

The Solid Surfaces in Soils Table 3.9

Structural charge and surface area of layer silicates

Group

Layer structure

Typical formulaa

Structural Specific negative surface charge area −1 (molc kg−1 ) (m2 kg )

Kaolinite 1:1 [Si4 ]Al4 O10 (OH)8 0–0.01 0–0.01 Halloysite 1:1 [Si4 ]Al4 O10 (OH)8· 4H2 O Illite 2:1 M1.4 – 2 [Si6.8 Al1.2 ]Al3 Fe0.25 Mg0.75 O20 (OH)4 1.9–2.8 Vermiculite 2:1 M1.2 – 1.8 [Si7 Al]Al3 Fe0.5 Mg0.5 O20 (OH)4 1.6–2.5 Smectite 2:1 M0.5 – 1.2 [Si8 ]Al3.2 Fe0.2 Mg0.6 O 20 (OH)4 0.7–1.7 Chlorite 2:1:1 (Al(OH)2.55 )4 [Si6.8 Al1.2 ]Al3.4 Mg0.6 O20 (OH)4 Variable a

0.5–3 1–4.5 8–15 30–50 60–80 2.5–15

M = monovalent cation.

Si4 Al4 O10 (OH)8 , has no structural charge, but moderate structural charge (< − 10 mmolc kg−1 ) arises in most natural kaolinites as a result of substitution of Mg2+ for Al3+ or Al3+ for Si4+ (Table 3.9). More important is the pH-dependent charge that arises as a result of adsorption and desorption of protons by the –OH and –O groups at the lattice edges. This is in the range +10 to −50 mmolc kg−1 over the usual range of soil pHs, with zero charge at about pH 4.6. 2:1 Type. The tetrahedral sheets of adjacent layers cannot form hydrogen bonds with each other, lacking –O groups, but are held together by electrostatic forces arising from their charge. In illites the interaction is strong because the lattice charge is neutralized by K+ ions, which effectively glue the sheets together. In smectites and vermiculites water molecules and solutes can enter between the layers, increasing the layer spacing. Swelling clay minerals have a moderate proportion of substituted atoms and hence a relatively low charge density (Table 3.9). The cations that compensate the permanent charge are therefore bound to the surface by relatively weak purely electrostatic forces. They form a broad diffuse layer in the solution near the surface. Non-swelling 2:1 clay minerals have a much larger proportion of substituted atoms and therefore greater charge density (Table 3.9). As a result the chargecompensating cations may form covalent or ionic bonds with the surface, as well as being held electrostatically. Certain ions, e.g. K+ and NH4 + , fit neatly in holes in the clay structure and produce a rigid stack of clay layers. Only the cations held on outer surfaces and, to a variable extent, on imperfectly fitting layers within the clay structure are then exchangeable with cations in the soil solution. 2:1:1 Type. The interlayer spaces of 2:1 silicates may be blocked by poorly ordered sheets of Al hydroxy polymers, such as [Al(OH)2.5 0.5+ ]n (n ≥ 6). Such Al interlayers neutralize a considerable part of the surface charge and restrict swelling, and effectively convert 2:1 clays into materials similar to kaolinite.

68

Interchange of Solutes between Solid, Liquid and Gas Phases

Even moderate Al interlayering greatly affects clay properties. Such materials are important in submerged soils that have become ferrolysed (Section 7.1). Amorphous Aluminosilicates. These occur in soils influenced by volcanic activity and are associated with very high moisture retention and anion fixation, and low to very high pH-dependent CEC. They may also bind organic matter tightly, protecting it against decomposition. Examples are allophane and imogolite. Oxides Being widespread in the lithosphere and insoluble in the usual range of soil pH, oxides and hydroxides of Al, Fe and Mn are common in soil clays. Red or yellow coloration of soils is apparent at Fe oxide contents of only 0.1 % or less, especially if the Fe is amorphous and coats other minerals. The most visible change occurring when soils are submerged is the conversion of the red and yellow compounds of Fe(III) to the bluish-grey compounds of Fe(II). Metal oxides and hydroxides have little or no structural charge but develop pH-dependent charge as the hydroxyl groups at the lattice edges gain or lose protons. The surface charge is a function of both pH and the concentration of salts in the solution, as these affect the dissociation of the –OH groups. However the pH at which the surface negative charge is equal to the surface positive charge—the point of zero charge (pzc)—is independent of the salt concentration if the salt does not react with the surface. The point of zero charge is an important characteristic of the surface. Table 3.10 gives pzc values for common soil materials. Values are large for metal oxides and hydroxides but small for silica and soil organic matter. In real soils where oxides, layer silicates, organic matter and other materials are present in intimate mixtures, with the oxides and organic matter often coating the surfaces of the other materials, the different functional groups interact with Table 3.10 Points of zero charge (pzc) of oxides and aluminosilicates Material α-Al(OH)3 γ -AlOOH α-FeOOH γ -Fe2 O3 Amorphous Fe(OH)3 MgO δ-MnO2 SiO2 Feldspars Kaolinite Montmorillonite

pzc 5.0 8.2 7.8 6.7 8.5 12.4 7.2 2.0 2–2.4 4.6 2.5

The Solid Surfaces in Submerged Soils

69

each other and so the distinction between permanent and pH-dependent charge is blurred. Organic Matter Soil organic matter is a weak acid and becomes negatively charged by losing protons. The main functional groups are carboxylates and, to a lesser extent, phenols, which are weaker acids. Their acid–base behaviour is complicated because of their heterogeneity and because of the effects of neighbouring functional groups on soil surfaces. With increasing dissociation, the build up of negative charge on the surface tends to inhibit further dissociation. Thus a plot of the extent of dissociation of organic functional groups versus pH tends to be steeper than the equivalent plot for simple monoprotic acids, and it approaches a straight line over the usual pH range in soils. This leads to the following rough empirical relation for the negative charge on soil organic matter as a function of pH (McBride, 1994): SOM charge(mmolc g−1 organic C) = −0.6 + 0.5 pH

(3.41)

As a rule of thumb, at near neutral pH, each g of organic C per kg of soil increases the surface negative charge by about 3 cmolc kg−1 soil. A further complication is that soil organic matter becomes more soluble at higher pH as dissociation increases the surface negative charge. Also, organic matter may form coordination complexes with some metals involving covalent bonds. 3.6 THE SOLID SURFACES IN SUBMERGED SOILS Many submerged soils are developed in recent in alluvium and are often young or only weakly weathered (Section 1.3). The overall composition of the clay fraction is therefore often close to that of the parent sediment. Hence the following generalizations can be made for rice soils in the humid tropical lowlands (Kyuma, 1978; Binkman, 1985) • Soils derived from marine alluvial sediments tend to be dominated by montmorillonitic 2:1 clays whereas those from riverine sediments have vermiculitic 2:1 clays with mixtures of 1:1 clays and metal oxides, the sediment being developed under more strongly weathered conditions. • Soils developed in positions higher in the landscape tend to be dominated by more-weathered material. • Soils derived from basic volcanic ejecta, metamorphic rocks and granitic rocks have corresponding mineralogies. Various changes in mineralogy are induced by seasonal flooding. The first factor in this is the change in base status of the soil due to the flow of water

70

Interchange of Solutes between Solid, Liquid and Gas Phases

through and across it. Depending on the alkalinity of the water entering and leaving, the soil may be enriched with bases or depleted. Large quantities of bases are liberated in soil reduction following flooding and may be leached. The balance will depend on the topological and hydrological situation of the soil, and in general soils low in the landscape will accumulate bases and those higher will be depleted. There may be biological fixation of bases, for example by aquatic snails in fields receiving base-rich interflow water or irrigation. For example, after 15 years of intensive irrigation of ricefields at the International Rice Research Institute (Laguna, Philippines) with base-rich water (4 mmolc L−1 Na+ and 1 mmolc L−1 Mg2+ ), there was a marked accumulation of CaCO3 in snail shells and the aerobic soil pH increased from 5.6–6.0 to 6.5–7.0 (Moormann and van Breemen, 1978). The reverse process—decalcification—may also occur. For example, in the calcareous soils of the Ganges and Megha sediments, Bangladesh, where the ricefields are rainfed and the rainwater tends to be acid, Brammer (1971) reported losses of 1 % of the CaCO3 in 25 years from sediments that originally contained 5–10 % CaCO3 . The calcite is dissolved by acids in the rain and CO2 formed during soil reduction, and Ca(HCO3 )2 is leached out of the soil. The second factor is the changing redox state of the soil. Generally iron is the most abundant redox species present. Table 3.11 shows total iron contents of a range of rice soils across Asia. From 20 to 80 % of the iron is present as free Fe(III) oxides and often from 1 to 20 %—and sometimes as much as 90 %—of the free Fe(III) is reduced to soluble and exchangeable Fe(II) following submergence (see for example Figure 2.8). Some of the exchangeable Fe(II) is subsequently reprecipitated as mixed Fe(II)Fe(III) compounds of uncertain composition. There may also be reduction of structural Fe(III) to Fe(II) within clay minerals. These changes take place over a matter of weeks. Upon subsequent drying and re-oxidation, the exchangeable and amorphous Fe(II) are rapidly converted to ferric hydroxides, initially in amorphous forms that recrystallize only very slowly (Figure 3.8). As a result, amorphous ferric hydroxides and similar materials tend to accumulate in the soil at the expense of more stable Table 3.11 Total iron contents (mg Fe g−1 ) of rice soils Country

Mean

Min.

Max.

n

Bangladesh Burma Cambodia India Indonesia Malaysia Philippines Sri Lanka Thailand Japan

40.1 39.7 32.2 72.3 20.8 20.8 54.1 37.4 25.2 42.0

8.0 5.9 0.0 9.0 1.7 1.9 28.8 5.0 0.0 —

66.1 65.5 80.1 117.6 50.3 50.3 86.7 149.6 90.0 —

53 16 16 73 44 41 54 33 80 155

Source: Kyuma (1978).

71

The Solid Surfaces in Submerged Soils Slow reduction

Crystalline Fe(III) oxides

Fast oxidation

Amorphous Fe(III) oxides

Fe(II)

Fast reduction Slow crystallization

Figure 3.8 Accumulation of amorphous Fe(III) compounds under alternating reduction and oxidation (after Moormann and van Breemen, 1978). Reproduced by permission of IRRI

ferric oxides. In turn, the amorphous materials are more easily reduced during soil flooding and over time the iron compounds reach a steady state in which easily reducible amorphous materials are combined with more recalcitrant minerals. The proportion of amorphous and crystalline materials will be influenced by the hydrological regime and climate. Concomitantly there are short- and long-term changes in soil organic matter. Changes in Surface Properties Following Submergence For the most part, the overall composition of the clay fraction in soils is determined by long-term processes and does not change rapidly with changes in conditions. However the properties of the clay surface can change rapidly and the surface is often not in equilibrium with the rest of the solid phase. Thus alternating reduction and oxidation under variable water regimes cause rapid but transient changes in surface properties, as well as more persistent changes in the overall composition of the solid phase. The changes in surface properties following soil submergence are as follows. Dissolution of Oxide Coatings. The net negative charge on the soil solid may increase following reduction as a result of dissolution of oxide and oxyhydroxide coatings on clay surfaces. The pzc of oxides and oxyhydroxide are at or above neutral pH (Table 3.10), and so the coatings on clays are positively charged in neutral and acid soils and neutralize some of the clay’s negative charge. Their dissolution therefore results in an increase in the net negative charge on the surface. Hence, for example, an oxide with composition Fe(OH)2.5 0.5+ , is reduced according to the half reaction [soil—2Fe(OH)2.5 ] + 5H+ + 2e− −−−→ [soil—]− + 2Fe2+ + 5H2 O

(3.42)

where e− represents an electron transferred in the reduction. If the corresponding oxidation of soil organic matter is (Chapter 4) CH2 O + H2 O −−−→ CO2 + 4H+ + 4e−

(3.43)

72

Interchange of Solutes between Solid, Liquid and Gas Phases

then the overall reaction is 2[soil—2Fe(OH)2.5 ] + CH2 O + 6H+ −−−→ 2[soil—]− + 4Fe2+ + CO2 + 9H2 O (3.44) In Reaction (3.44), for each mol of Fe reduced the surface negative charge increases by 0.5 molc and 1.5 mol of H+ are consumed. Roth et al. (1969) found increases in surface negative charge equivalent to 10–60 % of the initial charge for a range of soils and soil clays. The change could be attributed quantitatively to the removal of the positively charged oxide coatings and was reversed by re-oxidizing the samples. Changes in charge with reductive dissolution of oxides have been demonstrated using chemical reducing agents (Roth et al., 1969) and microbial reducing agents (Bloomfield, 1951; Ottow, 1973; Lovley, 1991), and under field conditions (Favre et al., 2002). Dissolution and reduction of crystalline Fe(III) minerals is accelerated by chelation with carboxylate ligands in the presence of Fe(II) (Zinder et al., 1986; Blesa et al., 1987; Phillips et al., 1993; Kostka and Luther, 1994). Therefore as soil reduction proceeds and carboxylates formed in oxidation of organic matter accumulate in solution together with Fe2+ , dissolution and reduction of crystalline Fe(III) will commence. Dissolution of oxyhydroxide coatings will therefore lag behind the initial reduction of Fe(III). Reduction of Structural Fe. There may also be changes in charge due to reduction of structural Fe(III). Virtually all soil clay minerals contain some iron in their crystal structures and reduction of this structural Fe by chemical or microbial reducing agents, with the iron remaining octahedrally coordinated in the clay structure, is well documented (Stucki, 1988; Stucki et al., 1997). The extent of reduction, whether by microbes or chemical reducting agents, can be as much as 90 % of the octahedral Fe(III) in a few days (Kostka et al., 1999). The rate is enhanced by the presence of organic chelating agents that commonly occur in sediments and flooded soil solutions, and under such conditions Fe(III) reduction may lead to partial dissolution of the clay (Kostka et al., 1999). As structural Fe(III) is reduced, the negative charge on the clay will increase. It is found experimentally that the increase in negative charge is not directly equivalent to the amount of Fe(III) reduced, and the more reduced the clay is the smaller is the change in charge. An example is shown in Figure 3.9. The mechanism behind this is uncertain but involves dehydroxylation of the clay structure during reduction and sorption of metal cations from the solution (Stucki et al., 1997; Drits and Manceau, 2000). The extent of dehydroxylation and sorption varies with the extent of reduction, hence the change is nonlinearly related to the amount of Fe reduced. For example, for a nontronite: M[Si7 Al]Fe(III)4 O20 (OH)4 + mM+ + nH+ + pe− −−−→ M1+m [Si7 Al]Fe(III)4−p Fe(III)p O20 (OH)4−n + nH2 O

(3.45)

73

The Solid Surfaces in Submerged Soils

Surface charge (mmolc g−1)

1.5 1.4 1.3 1.2 1.1 1.0 0.9 0.8 0.7 0.0

0.5

1.0

1.5

2.0

Amount of Fe(III) reduced (mmol g−1)

Figure 3.9 Relation between surface charge and reduction of structural Fe in a dioctahedral smectite. Points are experimental data; lines are theoretical relations discussed in the text (Drits and Manceau, 2000). Reproduced by permission of Clay Minerals Society

where M is a sorbed cation and m, n and p are coefficients. The solid line in Figure 3.9 shows the fit to Equation (3.45) and the dotted line shows the expected relationship if only dehydroxylation occurs. If the generic reaction is simplified to [clay—Fe(III)OH] + nH+ + e− −−−→ [clay—Fe(II)OH1−n ](1−n)− + nH2 O (3.46) then using the upper value n = 0.75 (Figure 3.9), the complete reaction with simultaneous oxidation of organic matter (as for Reaction 3.44) is: 4[clay—Fe(III)OH] + CH2 O −−−→ 4[clay–Fe(II)OH0.25 ]0.25− + H+ + CO2 + H2 O

(3.47)

In Reaction (3.47), for each mol of Fe reduced the surface negative charge increases by 0.25 molc and 0.25 mol of H+ are released. For moderate reduction the changes are completely reversible but they are progressively less so with more thorough reduction (Stucki et al., 1984; Komadel et al., 1995; Gates et al., 1996). There are concomitant changes in the clay’s physical and chemical properties, including its surface area, swelling behaviour, and capacity to sorb cations. Changes in pH-dependent Charge. Changes in pH with soil reduction will cause changes in the charges on inorganic –OH functional groups and organic matter. From Equation (3.41), the increase due to organic functional groups will be approximately 0.5 mmolc g−1 organic C per unit pH increase, or, for a soil with 1 % organic C, 5 mmolc kg−1 soil. This is small compared with the changes due to dissolution of oxide coatings and reduction of structural Fe, which are of the order of several tens of mmolc kg−1 soil. But it may be important in highly

74

Interchange of Solutes between Solid, Liquid and Gas Phases

weathered soils with low cation exchange capacity. The changes due to edge –OH groups on kaolinites will be of a similar magnitude. The increase in oxide charge per unit increase in pH will be of the order of 5 mmolc kg−1 oxide at the ionic strength and pH of typical flooded soil solutions. However, if the surface oxide coatings dissolve in the process of reduction, this will be of no consequence. Formation of New Solid Phases. Once a sufficient concentration of dissolved constituents has been reached following submergence and soil reduction, new solid phases will precipitate. The nature of these compounds is discussed in detail in Chapter 4. In neutral soils with smectite or vermiculite in the clay fractions, the changes in redox and bases status following soil flooding may cause synthesis of materials similar to smectite with Fe2+ in the octahedral sheet. Other cations, e.g. Zn2+ , may also become entrapped. In acids soils, particularly those with kaolinite clay minerals, soluble Fe2+ concentrations tend to rise to high levels because of low CEC and because conditions do not favour precipitation of Fe(II) oxides or carbonates or synthesis of silicates. When a reduced soil is re-oxidized, Fe2+ changes into Fe(OH)3 . The original Fe oxides are thus distributed differently, generally with a higher specific surface and activity. In high-activity clay soils, this may increase the stability of the structure established just before flooding. In low-activity clay soils the effects of alternate reduction and oxidation are less clearly beneficial, partly because of leaching of nutrients.

3.6.1 ORGANIC MATTER IN SUBMERGED SOILS In general the organic matter in soils tends towards a steady state in which additions from net primary production balance the various processes removing it, and the organic matter attains a level and composition characteristic of the prevailing conditions. As discussed in Chapter 1, net primary productivity of wetlands is in general far greater than that of uplands and rates of organic matter loss due to decomposition, run-off, leaching and erosion tend to be less. In general, the yield of energy per unit of carbon oxidized is smaller in anaerobic fermentation than in aerobic respiration, and so, other things being equal, rates of decomposition are less. Hence in the temperate zone wetland soils often have large organic matter contents or are peaty. However, in the tropics, peat bogs and fens are rare (Table 1.1) and wetland rice soils tend not to have particularly large organic matter contents. In data assembled by Greenland (1997), the mean level of organic carbon in the topsoils of wetland rice soils from across tropical Asia was 2 %, and after excluding acid peaty soils the mean was 1 %. This compares with a range of 1.27–1.81 % for Oxisols and Ultisols of the Cerrado region of Brazil (Sanchez,

75

The Solid Surfaces in Submerged Soils

1981) and 2.78–4.80 for Oxisols and Ultisols of the humid tropical forest zone of Sumatra (van Noordwijk et al., 1997). Under intensive multiple-rice cropping, the soil organic mater may increase until a new steady state level is reached after some years. Table 3.12 gives an example for a rice–rice system over five crops in 2 years compared with a maize–rice system. However, very large soil organic matter contents do not develop. Evidently rates of decomposition are greater than expected for simple anaerobic decomposition. Figure 3.10 shows comparable rates of organic matter decomposition in soils that were kept continuously flooded or well-drained under otherwise similar, tropical conditions for 3–4 years (Neue and Scharpenseel, 1987). Clearly, Table 3.12 Carbon balances for rice–rice and maize–rice cropping systems over five consecutive crops in 3 years at IRRI, Laguna, Philippines. Except for short stubble all straw was removed from the fields and no organic manures were applied. Values are t C ha−1 ± SEs Cropping system

Rice–rice

N fertilizer (kg ha−1 ) a

Initial SOC Final SOC Change in SOC (% change) C from crop residues C mineralized (% of crop residues)

Maize–rice

0–0

190–100

0–0

190–100

19.13 ± 0.83 20.97 ± 0.49 +1.84 ± 0.44 (+10) 4.93 ± 0.18 3.09 ± 0.56 (63)

19.41 ± 0.27 22.15 ± 0.54 +2.74 ± 0.67 (+14) 7.72 ± 0.21 4.98 ± 0.47 (64)

19.22 ± 0.79 19.01 ± 0.40 −0.22 ± 0.50 (−1) 4.15 ± 0.28 4.37 ± 0.56 (105)

19.38 ± 0.97 19.83 ± 0.43 +0.46 ± 0.96 (+2) 7.09 ± 0.18 6.63 ± 0.87 (94)

a

SOC, soil organic carbon. Source: Witt et al. (2000). Reproduced with kind permission of Kluwer Academic Publishers.

(a) well drained

(b) submerged 100 Tropept Tropept Humult

30

10

Aquept Aquoll Aquult

30

10

14C

remaining (%)

100

3

0

10

20

3 0 10 20 30 40 50 Time (months after straw incorporation)

30

40

50

Figure 3.10 Decomposition of 14 C-labelled rice straw in (a) well-drained upland soils and (b) continuously submerged lowland soils under tropical conditions (adapted from Neue and Scharpenseel, 1987). Reprinted with permission from Elsevier

76

Interchange of Solutes between Solid, Liquid and Gas Phases

other factors are at work. In addition to temperature and aeration, and the quantity and nature of organic matter inputs, other factors influencing decomposition include the soil pH, which may be more favourable following submergence; the level and balance of nutrients, which may also be more favourable; and the communities of micro- and macro-fauna that together bring about the decomposition. Submerged soils are never wholly anoxic and contain aerated zones at the interfaces between the soil and floodwater and the soil and plant roots. Burrowing oligochaete worms transport fresh and partially decomposed organic matter between the soil and floodwater, and the activities of organisms in the soil and floodwater are thereby linked. Hence the soil–floodwater system as a whole behaves quite differently from its component parts in isolation. Decomposition processes are discussed further in Chapter 5. Studies by Olk and others of long-term (≤ 30 years) changes in organic matter in soils under intensive wetland rice cultivation have shown a gradual accumulation of less humified and more phenolic material (Olk et al., 1996, 1998, 1999; Mahieu et al., 2000a, b, 2002). These authors compared the chemical composition of organic matter from four soils with different histories of cropping and submergence: (a) one crop of upland rice annually without soil submergence; (b) one wetland rice crop and one soybean crop annually; (c) two wetland rice crops annually; and (d) three wetland rice crops annually. With increasing intensity of wetland rice cropping there were large increases in the proportions of less humified material in the soil organic matter, measured as diester P, amide N and phenolic C in nuclear magnetic resonance spectra. There were also positive correlations with visible light absorption and concentrations of free radicals, both of which are indices of humification, and negative correlations with the concentration of H, a negative index of humification. The authors speculate that slower lignin decomposition under restricted O2 supply in submerged soil leads to incorporation of phenolic compounds into young soil organic matter as it is turned over. Since phenolic compounds can react strongly with nitrogenous compounds, they further speculate that the mineralization and immobilization of N in intensively cropped rice soils may be adversely affected by accumulation of phenolic material.

3.7 SOLID–SOLUTION INTERACTIONS 3.7.1 ADSORPTION Adsorption depends on the interaction of ions and uncharged solutes with the functional groups on soil surfaces. It is in some ways analogous to complexation of ions with ligands in solution (Section 3.1), with the difference that the surface functional groups are stationary and their properties depend to a greater extent on interactions with neighbouring groups. Two types of surface complex are distinguished:

77

Solid–Solution Interactions

(a) inner-sphere complexes in which the adsorbed species is bound directly to the surface functional group, with no intervening water molecules; and (b) outer-sphere complexes in which at least one water molecule remains between the absorbed species and the surface. In inner-sphere complexes the bonding is covalent or ionic and the reactivity of the surface is altered by the interaction; in outer-sphere complexes the bonding is largely electrostatic and the reactivity of the surface is largely unaltered. Innersphere complexation is usually slower than outer-sphere and is often not readily reversible. It can occur regardless of the net surface charge and is little influenced by the ionic strength of the external solution. If an ion is adsorbed without forming a surface complex, neutralizing surface charge in only a delocalized way, then it is said to be part of the diffuse ion swarm. Such ions are free to move about in the soil solution near the surface. Figure 3.11 shows surface complexes on an inorganic hydroxyl surface. It shows the distinction between inner- and outersphere complexes, depending on the presence of water molecules between the surface and complexed species. The region of the diffuse ion swarm begins at the outer edge of the water molecules solvating ions in outer-sphere complexes. There are a number of more loosely defined terms for different types of adsorption that are related to the form of surface complexation. Specifically adsorbed ions are held in inner-sphere complexes whereas non-specifically adsorbed ions are in outer-sphere complexes or the diffuse-ion swarm. Readily exchangeable Oxygen Metal Inner-sphere complexes

H X

e.g. M = Zn, Pb, Cd X = P, As, Si M

H+ Outer-sphere complexes e.g. M = K, Ca, Mg, Fe X = Cl, NO3, HCO3

X−

H Water molecules

H M+ Solid−water interface

Figure 3.11 Complexes formed between solutes and hydroxyl groups on oxides and layer silicate edges (adapted from Sposito, 1984b). Reproduced by permission of Oxford University Press

78

Interchange of Solutes between Solid, Liquid and Gas Phases

ions are those that can be replaced easily by leaching with an electrolyte solution. This is an empirical definition, but only fully solvated ions can be readily exchangeable and therefore must be either in the diffuse-ion swarm or in outersphere complexes. Adsorption interacts strongly with complexation in solution. Table 3.13 indicates the range of complexes between metal ions and inorganic and organic ligands in soil solutions. In a submerged soil the organic ligands present include acetate, formate and propionate at concentrations of 10–40 mM in the early stages following submergence though less than 1 mM after 3–4 weeks. In addition concentrations of amino acids, phenolic acids and larger molecular weight humic acids may reach a few hundred µM, though transiently. Figure 3.12 shows the calculated effects of realistic concentrations of acetate, formate, propionate, glutamate, glycine, benzoate and phenylacetate on Fe(II), Mn(II) and Zn(II) species. The figure shows that for Fe(II) and Mn(II) the free ion dominates at all pHs, except for Fe above pH 9 where hydroxy complexes are important. Complexes with acetate are also significant at pHs above about 5, and FeHCO3 + above pH 6 and MnGlu above pH 5. Complexes with formate, propionate or either of the phenolic acids are unimportant at all pHs. The picture is more complicated for Zn(II) with many more significant species. The free ion dominates at pH ≤ 7.5 but complexes with acetate, HCO3 − , glutamate and especially CO3 2− are important at various pHs. Hydroxy complexes are only important at pH>9. Figure 3.13 shows the solubility of Zn2+ in soil at four Zn levels and different pHs. The figure shows that the soil solution is under-saturated with respect to likely pure Zn precipitates up to high pHs, and there is a marked minimum in solubility at near neutral pH. The explanation involves cation exchange and specific adsorption reactions, trace amounts of Zn2+ being sorbed preferentially over the main exchanging cations, and complexation reactions between Zn2+ and organic ligands in solution. The negative charge on soil surfaces increases as the pH increases, tending to increase sorption of Zn2+ on variable-charge surfaces. But at near neutral pH the concentration of dissolved organic matter in solution Table 3.13 The main species of trace metals in soil solutions Metal Mn(II)

Acid soils

Alkaline soils Mn2+ , MnSO4 0 , MnCO3 0 , MnHCO3 +

Mn2+ , MnSO4 0 , Orga 0

2+

+

Fe(II)

Fe , FeSO4 , FeH2 PO4

Ni(II)

Ni2+ , NiSO4 0 , NiHCO3 + , Org Org, Cu

Zn(II)

Zn2+ , ZnSO4 2+

NiHCO3 0 , NiHCO3 + , Ni2+ CuCO3 0 , Org

2+

Cu(II)

FeCO3 0 , Fe2+ , FeHCO3 + , FeSO4 0

ZnHCO3 + , ZnCO3 0 , Zn2+ , ZnSO4 0

+

Cd(II)

Cd , CdSO4 , CdCl

Pb(II)

Pb2+ , Org, PbSO4 0 , PbHCO3 +

Cd2+ , CdCl+ , CdSO4 0 , CdHCO3 + PbCO3 0 , PbHCO3 + , Pb(CO3 )2 2− , PbOH+

a Org, organic complexes, e.g. with fulvic acids. Source: adapted from Sposito (1983). Reproduced by permission of Elsevier.

79

Solid–Solution Interactions 10−2 Fe2+ 10−3

FeAc

10−4

FeHCO3+

Fe(OH)3− +

FeOH

10−5

Fe(OH)2 FeGly

10−6

Concentration (M)

10−3

Mn2+

10−4

MnGlu MnAc

10−5 MnHCO3+ MnOH+

10−6 10−7 10−7 Zn2+ ZnAc

−8

10

ZnHCO3+

ZnCO3

ZnProp ZnForm 10−9 ZnGlu

10−10

ZnOH+

ZnGly 10−11

4

Zn(OH)2 Zn(OH)3− 5

6

7 pH

8

9

10

Figure 3.12 Distributions of Fe(II), Mn(II) and Zn(II) species in a simulated flooded soil solution. Total concentrations in mM are Fe(II) = 2.5, Mn(II) = 0.25, Zn(II) = 0.0001, CT = 20, acetate = 10, formate = 1, propionate = 1, glutamate = 0.1, glycine = 0.1, benzoate = 0.1, phenylacetate = 0.1. Species accounting for <1 % of total not shown

increases appreciably and so complexation of Zn2+ in solution increases. There is also the possibility of co-precipitation in solid solutions that are much less soluble than pure precipitates (see below). 3.7.2 PRECIPITATION Adsorption is the process by which a net accumulation of a substance occurs at the boundary between two phases (e.g. gas—solid as well as liquid—solid),

80

Interchange of Solutes between Solid, Liquid and Gas Phases O 3) 2 ) (C 6 ) (OH OH 2 Zn 5 Zn(

3

4

pZn

morp

H) 2 (a

Zn (O

ZnCO 3

5

hous)

6 10 ppm Zn 20 ppm Zn 40 ppm Zn 70 ppm Zn 7

3

4

5

6

7

8

9

10

pH

Figure 3.13 Solubility of Zn2+ versus pH in soil at four Zn levels. The straight lines indicate the solubilities of possible precipitates at atmospheric CO2 pressure (McBride, 1994). Reproduced by permission of Oxford University Press

whereas precipitation is the process by which a substance accumulates to form a new solid phase. Both imply a net removal of solute from solution, but one is inherently two-dimensional and the other three-dimensional. However the distinction is blurred because similar types of chemical bond are often involved. Figure 3.14 shows the formation of a precipitate on the surface of an oxide or layer silicate in an analogous way to the formation of inner-sphere complexes in Figure 3.11. In practice there is a continuum between the two ranging from extremely insoluble inner-sphere complexes to precipitates that are much more soluble. In general when the concentration of a sorbed species is small surface complexation dominates and when it is large precipitation dominates. In submerged soils very large concentrations of dissolved ions and gases develop following anaerobic metabolism and reductive dissolution of solid phases, and so precipitation reactions often dominate. Precipitation is generally much slower than adsorption. Table 3.14 compares rates of precipitation with rates of adsorption and other surface phenomena in soil systems. Rates vary greatly between precipitating compounds. They are also often subject to inhibition and catalysis by other solutes and solid phases present.

81

Solid–Solution Interactions Oxygen Metal H

H Precipitated metal

H

H

Solid−water interface

Figure 3.14 Fig. 3.11)

Precipitation on the surface of an oxide or edge of a layer silicate (cf.

Table 3.14 Rates of solid-solution interactions in soils Process Complexation in solution Adsorption Desorption Dissolution Redox reactions in solution Redox reactions on surfaces Solid solution formation Cluster formation Heterogeneous nucleation and precipitation Homogeneous nucleation and precipitation Recrystallization into pure phases Diffusion on surfaces Diffusion in crystals

Time scale (h) 10−8 –10 10−8 –10 10−6 –104 1–104 10−6 –108 0.1–104 0.1–10 10−2 –1 1–102 0.1–104 104 –108 10–108 105 –108

Thus rate laws for precipitation reactions tend to be complicated, even in pure solutions. Mixed precipitates can be inhomogeneous solids with one component restricted to a thin outer layer because of slow diffusion. New solid phases can precipitate homogeneously onto the surfaces of existing solid phases. Weathering solids may provide host surfaces onto which more stable phases may precipitate. At least three potentially rate-limiting steps can be distinguished: the diffusion of the reacting solutes to the site of precipitation; their reaction to form the insoluble compound; and accumulation of the compound as a solid phase. In

82

Interchange of Solutes between Solid, Liquid and Gas Phases

general, in water systems rates of diffusion are much greater than the rates of reaction and are rarely rate limiting. However in soils diffusion may be much slower, for example where a reaction is catalysed by sorption on inaccessible surfaces, and so diffusion is often rate limiting. The formation of the solid phase then has three stages. First a critical cluster of the constituent solutes must form from a supersaturated solution. Spontaneous crystal growth may then occur. In effect the solubility of the nuclei that are initially formed is greater than that of the larger crystallites that grow from them. The difference arises from the much greater surface energy of the nuclei compared with the crystallites. In the third stage large crystals form slowly from crystallites through the process known as ripening. Nucleation may occur homogeneously from a pure solution that is sufficiently supersaturated. But in soil systems it is more likely to occur heterogeneously with the surfaces of soil particles acting as catalysts. If the surface matches the precipitating phase well, the interfacial energy between the two solids is less than that between the precipitate and the solution, and the energy barrier for nucleation is therefore decreased. Consequently the degree of supersaturation necessary for precipitation to start is smaller. For example, soil solutions are often highly supersaturated with respect to gibbsite, but it will precipitate from similar solutions containing smectite. The particular combinations of ions and molecules that will form precipitates in a given solution can be predicted from equilibrium thermodynamics. However, this often gives a misleading picture because there are kinetic limitations or there is inhibition, particularly in soil solutions. There may also be isomorphous substitution of one cation for another in the precipitate, resulting in a solid solution with a different solubility to the pure compound.

3.7.3 CO-PRECIPITATION IN SOLID SOLUTIONS In general the solid phases formed under natural conditions are not simple pure compounds but contain foreign ions isomorphously substituted in crystal lattices. The activity of the solid phase is thereby decreased. This may have little effect on the solubility of the major component, but it may greatly decrease the solubility of the minor component compared with its pure form. This process differs from adsorption or occlusion in that it represents the equilibrium state of the system. A requirement is that the foreign ion can diffuse freely during precipitation and that there is a high structural compatibility between the two pure phases. Hence the radii of the ions involved must be similar and the minor component should become uniformly distributed through the solid. As discussed earlier rates of precipitation tend to be slower than rates of adsorption; rates of solid solution formation are intermediate between rates of adsorption and precipitation (Table 3.14). Solid solutions seem likely to form in submerged soils because reductive dissolution reactions generate large concentrations of dissolved ions over short times, and so there are opportunities for mixed precipitates to form.

83

Solid–Solution Interactions

Consider a two-phase system with components AY and BY in which some of the BY(s) becomes dissolved in AY(s): BY is the solute and AY the solvent. If the resulting solid solution is homogeneous, that is, it contains no concentration gradient, the equilibrium distribution of A and B between the liquid and solid is AY(s) + B+ = BY(s) + A+

(3.48)

and the equilibrium constant is XBY fBY (A+ ) KSP(AY) (BY(s))(A+ ) = =K + + = (AY(s))(B ) XAY fAY (B ) KSP(BY)

(3.49)

where the ratio of the activities of the solids is replaced by the ratio of the mole fractions [XAY = nAY /(nAY + nBY ) and XBY = nBY /(nAY + nBY )] multiplied by activity coefficients, and KSP(AY) and KSP(BY) are the solubility products of pure AY and BY. Pure AY and BY are the ‘end members’ of the solid solution series. This equation shows that the dissolution of BY in solid AY is a function of: (a) the ratio of the solubility products of AY and BY (K); (b) the solution composition with respect to A+ and B+ ; (c) a solid solution factor equal to the ratio of the activity coefficients of the solid solution components (fAY /fBY ). Assuming as a first approximation fAY /fBY = 1 (an ideal solid solution) and that the activity ratio of the species in solution can be replaced by the concentration ratio, then XBY [B+ ] (3.50) =K + XAY [A ] As an example, consider a solid solution of 5 % ZnCO3 in MgCO3 (95 %) in equilibrium with Mg2+ , Zn2+ and [CO3 2− ] = 10−5 M (realistic conditions for many submerged soils). We have K=

KSP(MgCO3 ) 10−7.46 = −10.0 = 347 KSP(ZnCO3 ) 10

Assuming the solubility of MgCO3 is little altered, then [Mg2+ ] = 3.47 × 10−3 M and from Equation (3.49) [Zn2+ ] = [Mg2+ ]

1 XZnCO3 = 5.26 × 10−7 M K XMgCO3

This compares with [Zn2+ ] = 10−5 M for equilibrium with pure ZnCO3 . If K is very large or small, the solid solution cannot be homogeneous because A or B will be selectively scavenged from the liquid as the solid precipitates. In this case A or B will be occluded within the solid and will only be desorbed back into solution very slowly. This mechanism provides a means by which toxic or

84

Interchange of Solutes between Solid, Liquid and Gas Phases

essential metals may become buried in forms largely inaccessible to desorption, so they may accumulate over time. Examples in Soil Systems Solid solutions will only form between ions with similar radii (±15 %). Table 3.15 shows the radii in crystal lattices of divalent cations that might form solid solutions in soils. Hence, for example Mn2+ , Fe2+ and Cd2+ might be expected to form solid solutions in CaCO3 , but Cu2+ and Zn2+ would not. However, soils do not necessarily behave the same as pure systems. Thus there is little evidence for strong association of Cd2+ or Pb2+ with calcite (CaCO3 ) in soil systems, despite having similar radii to Ca2+ (McBride, 1994). However Cd2+ and Pb2+ are both commonly associated with hydroxyapatite (Ca10 (PO4 )6 (OH)2 ), and hence may contaminate phosphate fertilizers. Also Cu2+ , Zn2+ , Ni2+ and Co2+ are excluded from haematite during its crystallization but substitute into magnetite (Fe(III)2 Fe(II)O4 ). Small divalent cations such as Zn2+ , Cu2+ and Mg2+ often react with Al hydroxide to form solid solutions called hydrotalcites of general formula [M2+ 1−x Alx (OH)2 ]x+ Xn− x/n , where Xn− is an anion. These are noted for their permanent positive charge and hence anion exchange capacity. Features of metal sorption in soils that indicate—but do not prove—solid solution formation include (McBride, 1994): sorption capacities that increase over time; decreasing reversibility of sorption with time; selectivity for metals based largely on ionic radii; and solubilities well below those predicted from the solubility products of pure systems. The cycles of reduction and oxidation of Fe and Mn oxides in intermittently submerged soils provide opportunities for co-precipitation with trace metals. In most natural systems it is the rate of dissolution of the solid phase that limits solid solution formation rather than thermodynamics, so conditions in submerged soils are highly conducive to formation of solid solutions. Table 3.15 Radii of divalent cations in crystal lattices Cationa

Ionic radius (nm)

2+

Mg Ca2+ Mn2+ Fe2+ Co2+ Ni2+ Cu2+ Zn2+ Cd2+ Pb2+ a

In six-fold coordination.

0.072 0.100 0.083 0.078 0.075 0.069 0.073 0.074 0.075 0.119

Solid–Solution Interactions

85

3.7.4 INHIBITION OF PRECIPITATION Rates of precipitation in soil are sensitive to inhibition by organic and inorganic ligands that may be sorbed on soil surfaces and thereby interfere with nucleation and crystal growth. This is particularly important in submerged soils because large concentrations of organic and inorganic ligands develop in the soil solution following submergence. Inskeep and Bloom (1986) measured inhibition of calcite precipitation by organic ligands in simulated soil solutions prepared from CaCl2 , KHCO3 and seeds of CaCO3 , and maintained at constant pH and CO2 pressure. The data fitted the rate equation: R = ks[(Ca2+ )(CO3 2− ) − KSP ]

(3.51)

where R is the rate of CaCO3 precipitation, k is the rate constant, s is the surface area of CaCO3 seeds, and KSP is the solubility product of pure CaCO3 . The value of k was 117 dm6 mol−1 m−2 s−1 and it decreased to zero in the presence of 0.15 mM water-soluble soil organic matter or 0.028 mM fulvic acid. However, rates of precipitation in soil systems may be quite different from those in solutions because: precipitation is catalysed by adsorption of the reacting solutes onto soil surfaces; the nature of the solid phases formed may be different; and sorption may also alter the effects of inhibitors. There are very few data in the literature on these effects actually measured in soils. Figure 3.15 shows data of Huang (1990) for calcite precipitation in three soils incubated with urea. Precipitation was induced as the pH increased during urea hydrolysis: CO(NH2 )2 + 3H2 O −−−→ 2 NH4 + + HCO3 − + OH−

(3.52a)

Soil2 —Ca + 2 NH4 + + HCO3 − + OH− −−−→ 2Soil—NH4 + CaCO3 (s) + H2 O (3.52b) Simultaneously, in all the soils the concentrations of P and dissolved organic carbon (DOC) in the soil solution increased as the pH increased, and this will have inhibited CaCO3 precipitation. By analysing the combined data by multiple regression, Huang (1990) developed a rate equation for the three soils allowing for inhibition by P and DOC. The rate equation was developed from an earlier equation developed from studies in solution systems: R = kw0.379 [(Ca2+ )(CO3 2− )/KSP ]

(3.53)

where R is the rate of precipitation in mol dm−3 soil solution s−1 , k is the rate constant and w is the weight of newly formed CaCO3 in kg dm−3 soil solution, which is a surrogate for the surface area term in Equation (3.51), surface area being unmeasurable in soil. The rates calculated with this equation are comparable to those with Equation (3.51). The modified equation for soil systems is: R = kw0.379 ea[PL ] eb[CL ] ec[PL ][CL ] [(Ca2+ )(CO3 2− )/KSP ]

(3.54)

86

Interchange of Solutes between Solid, Liquid and Gas Phases

CaCO3 precipitated (mmol kg−1 soil)

120 A A B B C C

100 80 60

0.5 0.7 0.3 0.5 0.3 0.5

40 20 0 9.5 9.0

pH

8.5 8.0 7.5 7.0

P concentration (mmol dm−3 solution)

5 4 3 2 1 0

DOC concentration (mmol dm−3 solution)

500 400 300 200 100 0

0

20

40

60 80 Time (h)

100

120

Figure 3.15 Precipitation of calcite in three soils (A, B, C) as pH increases during hydrolysis of urea, and simultaneous changes in pH, P and dissolved organic C (DOC) in the soil solution. Moist soil was incubated with CaCl2 and urea at constant CO2 pressure. Numbers with symbols are initial concentrations of urea (M). Data of Huang (1990). Reproduced by permission

87

Solid–Solution Interactions

where [PL ] is the concentration of P in the soil solution, [CL ] is the concentration of DOC in the soil solution, a, b, c are coefficients and k is the rate constant, which is soil specific. The values of k were 0.18, 1.98 and 1.16 × 10−6 (mol dm−3 s−1 basis) for Soils A, B and C in Figure 3.15, respectively. These values are more than four times k for the solution system. The values of the inhibition coefficients–a = −1686, b = 6.13, c = 3854—were smaller than in the solution system. As a result the concentrations of P and DOC required to halve the rate of precipitation were 10 times those in the solution system. Also the interaction between [PL ] and [CL ] was negligible in the solution system but important in the soils. Figure 3.16 shows plots of Equation (3.54) for different values of [PL ] and [CL ] and w = 0.75 g dm−3 . For the values used, which are realistic for submerged-soil solutions, the combined inhibitory effect of P and DOC was such that an order of magnitude greater degree of supersaturation [(Ca2+ )(CO3 2− )/KSP ] is necessary to produce the same rate of precipitation as in the absence of inhibitors. This sensitivity of precipitation in soil to organic ligands and other inhibitors explains why the soil solutions of submerged soils may be as much as a hundredfold over-saturated with respect to solid phases in the first few weeks following submergence (Chapter 4). 3.7.5 EQUATIONS FOR SOLID—SOLUTION INTERACTIONS In the initial few weeks following submergence, the properties of the soil surface change markedly as a result of reductive dissolution and precipitation reactions. But in time, a steady- or quasi-steady-state is reached, and then the same rules govern the distributions of exchangeable ions between the soil solid and

Rate of CaCO3 precipitation (µmol dm−3 s−1)

9 8

0, 0

7 6 5 0, 200

4

0.5, 200

3

0.5, 0

2 1 0

20

40 60 Saturation index

80

100

Figure 3.16 Inhibition of calcite precipitation by P and water-soluble organic matter calculated with Equation (3.54) derived using the data in Figure 3.15. Numbers on curves are concentrations of P and DOC in the soil solution (mM)

88

Interchange of Solutes between Solid, Liquid and Gas Phases

solution as in non-submerged soils. The first consideration is the concentration of non-adsorbed anions in solution because this determines the total strength of the solution. In submerged soils the principle anion is generally HCO3 − . The next consideration is what proportions of the exchangeable cations balance the anions in solution, and for this some form of empirical relation is necessary. There have not been many attempts to apply ion exchange equations to submerged soils (Pasricha and Ponnamperuma, 1976, 1977). But in principle the same equations should apply as for non-submerged soils. Considering the monovalent–divalent exchange reaction soil—B + 2A+ = soil—2A + B2+

(3.55)

and applying the law of mass action: (soil—2A)(B2+ ) = KE (soil—B)(A+ )2

(3.56)

where KE is the equilibrium constant for the reaction and the terms in parentheses are activities. Rearranging Equation (3.56) gives (soil—2A) (A+ )2 = KE 2+ (soil—B) (B )

(3.57)

Because there is generally a large reserve of exchangeable cations on the solid, a small change in A+ results in little change  in the ratio on the left-hand side. Hence the ‘reduced activity ratio’ (A+ )/ (B2+ ) tends to remain constant. The activity coefficients for the ions in solution can be evaluated with Equation (3.3). Because of the complexity of soils, there are no general relations between the proportions of two cations on the exchange complex and their reduced activity ratio in solution. But two equations are commonly used: the Gaines and Thomas NA (A+ ) (3.58) = KGT  √ NB (B2+ ) and the Gapon

(A+ ) NA = KG  NB (B2+ )

(3.59)

where NA and NB are equivalent fractions of the total exchange capacity and KGT and KG are exchange constants. When there are three or more competing ions, as there generally will be, it is not practical to determine the exchange isotherms for all possible combinations of the ions. However Bond and Verburg (1997) have shown that ternary and higher order exchanges can be predicted from the binary exchange isotherms of the component ions.

89

Solid–Solution Interactions

Calculated Changes in Exchangeable Cations Following Soil Reduction. We can use these equations to calculate how the exchangeable cations and the composition of the soil solution will change following soil reduction. As we have seen, precipitation of insoluble reduced compounds is often inhibited until a large supersaturation is reached. Therefore for simplicity I assume no precipitation; the effects of precipitation are considered in Chapter 4. The major changes in the soil solid affecting exchangeable cations are: reduction and dissolution of Fe oxyhydroxide coatings (cf. Equation 3.44): 2[soil—2Fe(OH)3−m ] + CH2 O + (8 − 4 m)H+ −−−→ 2[soil—]2m− + 4Fe2+ + CO2 + (11 − 4 m)H2 O

(3.60)

in which, for each mol of Fe reduced, the change in surface negative charge is 0.5 m molc and 2 − m mol of H+ are consumed; reduction of structural Fe in clay lattices (cf. Equation 3.47): 4[clay—Fe(III)OH] + CH2 O −−−→ 4[clay—Fe(II)OH1−n ](1−n)− + 4(1 − n)H+ + CO2 + (4n − 1)H2 O

(3.61)

in which, for each mol of Fe reduced, the surface negative charge increases by 1 − n molc and 1 − n mol of H+ are released; and changes in the charge on organic matter and variable-charge clays due to the changes in pH. If ψ is the ratio of structural Fe reduced to total Fe reduced, the total changes in surface negative charge and acidity are [Z] =
[cations]S + [HS]S = {(1 − ψ)0.5 m + ψ(1 − n)} [Fe(III)] (3.62) and [HS] = −{(1 − ψ)(2 − m) − ψ(1 − n)} [Fe(III)] (3.63) where
[cations]S and [HS]S are the changes in exchangeable cations and acidity in the soil solid. The latter is related to [HS] by [HS]S = [HS] − θ/ρ( [H+ ]L − [HCO3 − ]L )

(3.64)

It is often found empirically that the change in soil pH for a given addition of acid or base is constant over a wide range of pH and this relation is not greatly altered by soil reduction. Hence the pH buffer power, bHS , is constant and pH = − [HS]/bHS

(3.65)

Hence [H+ ]L and [HCO3 − ]L in Equation (3.64) can be found from [HS]. We therefore have the basis for the calculation. Consider the effect of Reactions (3.60) and (3.61) on the composition of a soil solution containing exchangeable cations A+ and B2+ balanced by the anion X− . As Fe2+ and CO2 are formed and H+ consumed:

90

Interchange of Solutes between Solid, Liquid and Gas Phases

(a) the strength of the soil solution increases, with the additional cations balanced by HCO3 − ; (b) the CEC of the soil solid increases; (c) some A+ and B2+ are displaced from the exchange complex by Fe2+ . Given the values of [Fe(III)], CT , [Z] and [HS], we have nine unknowns: the concentrations of A+ , B2+ , Fe2+ , H+ and HCO3 − in the soil solution, and the concentrations of A+ , B2+ , Fe2+ and HS in the soil solid. These may be found from the following nine equations: (1) from Equation (3.65) [H+ ]L = 10−(pH− [HS]/bHS )

(3.66)

(2) from the carbonate equilibria, [HCO3 − ]L =

CT [H ]L /KC1 + 1 +

(3.67)

(3) from the requirement of electrical neutrality in the solution, [A+ ]L + 2[B2+ ]L + 2[Fe2+ ]L + [H+ ]L = [HCO3 − ]L + [X− ]L + [OH− ]L (3.68) (4) from the requirement of electrical neutrality in the solid, [A+ ]S + 2[B2+ ]S + 2[Fe2+ ]S = [A+ ]S0 + 2[B2+ ]S0 + [Z] − { [HS] − θ/ρ( [H+ ]L − [HCO3 − ]L )} (3.69) where subscript 0 indicates initial values; (5) from monovalent–divalent cation exchange equilibria, 

[A+ ]L [B2+ ]L + [Fe2+ ]L

= KE1

[A+ ]S [B2+ ]S + [Fe2+ ]S

(3.70)

(6) from divalent–divalent cation exchange equilibria, [B2+ ]S [B2+ ]L = K E2 [Fe2+ ]L [Fe2+ ]S

(3.71)

and (7), (8), (9) from conservation of mass there are three equations of the type θ/ρ[A+ ]L + [A+ ]S = [A+ ]

(3.72)

These equations can be solved simultaneously to obtain the new composition of the soil solution. Assume KE1 and KE2 constant in spite of reductive dissolution reactions.

91

Solid–Solution Interactions 7.00

20

25

HCO3−

CO2 pressure

6.75 20

15

6.50 pH

10

Fe2+

10 6.25

A+

5 0

0

20

40 60 Fe(III) reduced (mmol kg−1)

15

B2+

80

CO2 pressure (kPa)

25

30

pH

Concentration in soil solution (mmolc L−1)

30

5 6.00 100

0

Figure 3.17 Calculated changes in a soil solution upon reduction of Fe(III) oxide coatings on soil surfaces and structural Fe(III) in clay lattices without re-precipitation of Fe(II). A+ and B2+ are exchangeable cations. Parameter values in Equations (3.60)–(3.72): [A+ ] = 0.1[B2+ ], CEC0 = 100 mmol kg−1 , [X]L = 5 mmolc L−1 , pH0 = 6, bHS = 50 mmol pH−1 kg−1 , KE1 = 1, KE2 = 1, ψ = 0.5, m = 0.5, n = 0.75, θ/ρ = 0.7

Figure 3.17 shows changes in the composition of a simulated soil solution so calculated. The proportions of Fe reduced in oxide coatings and structural Fe are equal. The figure shows that as Fe2+ accumulates and the CEC, pH and [HCO3 − ]L increase, the concentrations of Fe2+ and B2+ in solution increase, but the concentration of the monovalent A+ in solution changes less because it is more poorly buffered by the exchange complex. With a greater proportion of structural Fe reduced, less Fe2+ accumulates and the increase in pH is smaller but nonetheless the CEC increases and so the increases in B2+ in solution with oxide dissolution and accumulation of HCO3 − is smaller.

4 Reduction and Oxidation

The characteristics of submerged soils depend above all on the reduction and oxidation (redox) reactions that take place as a result of oxygen being excluded from the soil. With few exceptions, redox reactions on the Earth’s surface are driven by the redox disequilibrium caused by photosynthesis. In photosynthesis green plants use solar energy to reduce inorganic carbon to strongly reduced organic compounds, and simultaneously water is oxidized to O2 . Non-photosynthetic organisms tend to restore equilibrium by catalysing the oxidation of the organic compounds back to inorganic compounds in energy-yielding reactions. The bulk of this oxidation takes place in soil. In aerated soils, the preferred oxidizing agent is O2 itself. However where O2 is not available, as for example in submerged soils, alternative oxidants must be used. These may be organic, in which case the process is fermentation, or inorganic, in which case it is anaerobic respiration, though this term is often used to cover fermentation as well. In this chapter I give an overview of the thermodynamics of redox reactions and their kinetics in natural systems, and I then discuss the particular redox processes that occur in submerged soils. 4.1 THERMODYNAMICS AND KINETICS OF REDOX REACTIONS 4.1.1 ELECTRON ACTIVITIES AND FREE ENERGY CHANGES In the same way that acid–base reactions involve the transfer of protons between proton donors and proton acceptors, redox reactions involve the transfer of electrons between electron donors, called reducing agents or reductants, and electron acceptors, called oxidizing agents or oxidants. Thus when a redox reaction takes place, a reductant loses electrons and is oxidized to its conjugate oxidant: Red1 −−−→ Ox1 + ne−

(4.1a)

and simultaneously an oxidant gains electrons and is reduced to its conjugate reductant: Ox2 + ne− −−−→ Red2 (4.1b) where e− represents the electron. Equations (4.1a) and (4.1b) are redox half reactions or couples, and together they constitute a complete redox reaction. The Biogeochemistry of Submerged Soils Guy Kirk  2004 John Wiley & Sons, Ltd ISBN: 0-470-86301-3

94

Reduction and Oxidation

Which redox couple in a redox reaction has the oxidizing role and which the reducing role depends on the relative abilities of the two couples to accept or donate electrons. For example O2 has a greater affinity for electrons than other potential oxidants in natural systems, and is therefore reduced preferentially. The means of quantifying the relative abilities of redox couples to accept or donate electrons and the corresponding free energy changes is as follows. Just as free protons do not exist in solution in acid–base reactions, there are no free electrons in redox reactions. However it is possible to define the activity of electrons relative to a specified standard state and thereby treat electrons as discrete species in equilibrium calculations in the same way as ions and molecules. The standard state of electron activity for this purpose is by convention defined with respect to the redox couple made by hydrogen ions and hydrogen gas: H+ + e− = 12 H2 (g)

(4.2)

By convention the standard free energy change,
Go , for this reaction is set at zero, i.e. since
Go = −RT ln K: K=

(H2 (g))1/2 =1 (H+ )(e− )

(4.2a)

The thermodynamic relations of any particular redox couple can therefore be calculated from the values for the reaction between the couple of interest and the hydrogen ion—hydrogen gas couple. Thus for the reduction of oxidant Ox to its conjugate reductant Red, we have: Ox + ne− = Red and 1 nH2 (g) 2

= nH+ + ne−

(4.3a) (4.3b)

and the full reaction is Ox + 12 nH2 (g) = Red + nH+

(4.3c)

If K1 , K2 and K are the equilibrium constants for Reactions (4.3a), (4.3b) and (4.3c), then (Red) (4.4) K = K1 K 2 = K1 = (Ox)(e− )n i.e.




1 (Red) (e ) = K (Ox) −

1/n (4.5)

or, on a logarithmic scale, pe = − log(e− ) =


 (Red) 1 log K − log n (Ox)

(4.6)

95

Thermodynamics and Kinetics of Redox Reactions

Writing (1/n) log K = peo , pe = pe0 −

1 (Red) log n (Ox)

(4.7)

and since
G = −2.303RT log K,
Go (4.8) 2.303nRT peo is the electron activity with all the components of the redox couple at unit activity, with unit activity of gases taken as a partial pressure of 1 atm. Table 4.1 gives values of peo for important redox couples in natural systems expressed in terms of unit electron transfer (i.e. n = 1 and peo = log K). The pe of a solution indicates its relative tendency to accept or donate electrons in the same way that pH indicates the tendency to accept or donate protons. In a strongly reducing solution the tendency to donate protons and the corresponding electron activity are large, and the pe is low. Likewise an acid solution has a low pH. Table 4.1 shows that the pe values and hence equilibrium constants of many redox reactions are very large or very small, which means that the reactions proceed to completion in one direction or the other and the free energy changes involved are large. The values of peo and
Go for any particular redox half reaction can be calculated from the values for complete redox reactions or combinations of reactions having the half reaction in common. For example, the oxidation of glucose by oxygen, 1 glucose + O2 (g) = CO2 (g) + H2 O (4.9) 6 peo = −

is equivalent to the two half reactions 1 O (g) 2 2

and 1 glucose 6

+ 2H+ + 2e− = H2 O

(4.9a)

+ H2 O = CO2 (g) + 4H+ + 4e−

(4.9b)

The change in free energy for the glucose—CO2 half reaction can be found from
Go for the full reaction less that for the O2 –H2 O half reaction = −477.7 − 2 × (−236.6) = −4.5 kJ mol−1 . The values of peo and
Go can also be calculated from the standard free energies of formation,
Gof , of each of the reactants and products in a redox half reaction. For example, for the reduction of ferrihydrite [amorphous Fe(OH)3 ] the half reaction is Fe(OH)3 (s, amorph) + 3H+ + 2e− = Fe2+ + 3H2 O −1

(4.10)

are between −699 and −712 kJ mol for amorphous and the values of −1 Fe(OH)3 , −78.87 kJ mol for Fe2+ and −711.54 kJ mol−1 for H2 O. Therefore
Gor = 
Gof products −
Gof reactants = −91 to −78 kJ mol−1 , and peo = (log K)/n = −
Gor /2.303nRT = 16.0 to 13.7. Values of
Gof and other
Gof

96

Reduction and Oxidation Table 4.1 Equilibrium constants of important reduction half-reactions in natural systems at 25 ◦ C peo = log K H H+ + e− O 1 O (aq) + H+ + e− 4 2 N 1 N + 43 H+ + e− 6 2 1 NO3 − + H+ + e− 2 1 NO2 − + 43 H+ + e− 6 1 NO3 − + 54 H+ + e− 4 1 NO3 − + 65 H+ + e− 5

= 12 H2 (g)

0.00

= 12 H2 O

20.75

= = = = =

1 NH4 + 3 1 NO2 − + 12 H2 O 2 1 NH4 + + 13 H2 O 6 1 N O(g) + 58 H2 O 8 2 1 N (g) + 35 H2 O 10 2

4.63 14.15 15.14 18.81 21.05

= = = =

1 SO3 2− + 12 H2 O 2 1 HS− + 12 H2 O 8 1 S O 2− + 58 H2 O 8 2 3 1 H S(g) + 12 H2 O 8 2

−1.65 4.25 4.85 5.25

S 1 SO4 2− 2 1 SO4 2− 8 1 SO4 2− 4 1 SO4 2− 8

+ H+ + e− + 98 H+ + e− + 54 H+ + e− + 54 H+ + e−

Mn 1 MnO2 (s) + 2H+ + e− 2 MnOOH(s) + 3H+ + e− 1 Mn3 O4 (s) + 4H+ + e− 2

= 12 Mn2+ + 2H2 O = Mn2+ + 2H2 O = 32 Mn2+ + 2H2 O

21.82 25.33 30.79

Fe Fe3+ + e− α-FeOOH(s) + 3H+ + e− Fe(OH)3 (s) + 3H+ + e−

= Fe2+ = Fe2+ + 2H2 O = Fe2+ + 3H2 O

13.00 11.31 16.54

C 1 CH2 O + H+ + e− 2 1 CH2 O + H+ + e− 4 1 CO2 (g) + 12 H+ + e− 2 1 CO2 (g) + H+ + e− 4 1 CO2 + H+ + e− 6 1 CO2 (g) + H+ + e− 8 1 CO2 (g) + 78 H+ + e− 4 1 CO2 (g) + H+ + e− 5 1 CO2 (g) + H+ + e− 6 1 CO2 (g) + H+ + e− 6 1 CO2 (g) + 11 H+ + e− 4 12 3 9 + CO2 (g) + 10 H + e− 10 1 CO2 (g) + H+ + e− 4

= = = = = = = = = = = = =

3.99 6.94 −5.22 −1.20 0.50 2.87 1.27 0.99 1.52 1.34 0.68 0.05 −0.20

1 CH3 OH(aq) 2 1 CH4 (g) + 14 H2 O 4 1 HCOO− 2 1 HCHO(aq) + 12 H2 O 4 1 CH3 OH(aq) + 16 H2 O 6 1 CH4 (g) + 14 H2 O 8 1 CH3 COO− + 14 H2 O 8 1 3 CH3 CHO(g) + 10 H2 O 10 1 1 CH CH OH(aq) + H O 3 2 12 4 2 1 1 C H (g) + H O 12 2 4 4 2 1 1 (lactate) + H O 12 4 2 1 3 (pyruvate) + H O 10 10 2 1 1 (glucose) + H O 24 4 2

Source: Morel and Herring (1993) and Stumm and Morgan (1996).

Thermodynamics and Kinetics of Redox Reactions

97

thermodynamic properties of common chemical species in natural systems are given in Stumm and Morgan, 1996 (Appendix 3). 4.1.2 REDOX POTENTIALS An alternative approach to quantifying redox equilibria is to treat them as electrode reactions and to calculate the electric potential that would exist if the couple of interest formed a half cell with an inert electrode. The standard reference point for this is again taken as the hydrogen half reaction, the electrode potential for which is set at zero, which is equivalent to setting
Go equal to zero. This approach lacks the simplicity of the system based on electron activities and is not so well suited to equilibrium calculations. However it has historical precedence and is widely used so must be mentioned. Also, the electrode potentials of many redox couples can be measured directly. An inert electrode, such as platinum metal, is placed in a solution containing the redox couple of interest and linked via an external circuit to a hydrogen half cell comprising an inert electrode in a solution in equilibrium with H2 gas at 1 atm and having unit activity of H+ ions. The potential is measured with a voltmeter. The standard electrode potential, EHo , in which the suffix H indicates that the potential is on the H2 –H+ scale, is derived as follows. We have
G = −nF EH

(4.11)

where F is the Faraday. Combining Equation (4.11) with Equation (4.8) gives EH =

2.303RT pe F

Substituting for pe from Equation (4.6) in Equation (4.12) gives
 (Red) 2.303RT 1 EH = log K − log F n (Ox) or EH = EHo −

2.303RT (Red) log nF (Ox)

(4.12)

(4.13)

(4.14)

where EHo = (2.303RT /nF ) log K. This is the Nernst equation. At 25 ◦ C, 2.303RT /F = 0.059 V, therefore EH = 0.059 pe

(4.15)

4.1.3 RELATION BETWEEN pe AND CONCENTRATION OF REDOX COUPLES If one redox couple in a redox reaction is present at a much greater concentration than the other, then the concentration of the reduced and oxidized species in this

98

Reduction and Oxidation

couple are little influenced by the advancement of the reaction towards equilibrium and the equilibrium electron activity is effectively that of the dominant redox couple. This is given by the appropriate form of Equation (4.7) for the dominant couple: (Red) 1 pe = peo − log (4.16) n (Ox) (Note that this equation can be expressed in terms of the concentrations of Red and Ox by dividing the activities by the appropriate activity coefficients.) The pe of a solution will therefore be ‘poised’ at the pe determined by the dominant couple until that couple is exhausted. The pe of all other redox couples operating will tend to adjust to this electron activity. For example, in oxic natural waters the principal oxidant is O2 and in agreement with expectations the pe of such waters is generally poised in the range expected for the O2 –H2 O couple (Morel and Herring, 1993). Thus for water at pH = 7 in equilibrium with atmospheric PO2 (= 10−0.7 atm), the half reaction is 1 O (g) 4 2

+ H+ + e− = 12 H2 O

therefore pe = peo − log

1 1/4 PO2 (H+ )

peo = 20.75 = 13.58,

(4.17)

which agrees well with the typical range of pe in oxic natural waters; pe = 12 to 14. Equation (4.17) indicates the pe varies as log (H+ ) but only as 14 log PO2 . Thus the pH has a large effect on pe but the concentration of O2 has only a minor effect and small concentrations of O2 maintain water in an oxidized state. A further informative example is the organic matter—CO2 couple, which is the principal reductant in natural systems. Consider a solution in equilibrium with atmospheric CO2 at neutral pH and containing 10 µM ‘CH2 O’, where CH2 O represents average organic C in natural systems, whose composition is similar stoichiometrically to that of carbohydrates. The half reaction is 1 CO2 (g) 4

+ H+ + e− = 14 CH2 O + 14 H2 O

therefore pe = peo − log

(CH2 O)1/4 PCO2 (H+ ) 1/4

peo = −1.20

= −7.83

(4.18)

Such very low pe values do not generally occur in natural systems because oxidizing couples such as O2 –H2 O or Fe(OH)3 –Fe2+ are usually present in much greater concentrations. However pe values this low may occur in bacterial cells where organic matter is being oxidized in the absence of large concentrations of inorganic oxidizing couples, providing strongly reducing microenvironments which may be linked to redox couples in the external environment via intermediaries passing across the cell wall.

99

Thermodynamics and Kinetics of Redox Reactions

Notice that, as in Equation (4.17), pe in Equation (4.18) is sensitive to pH but not to the concentrations of the redox species. The sensitivity to the concentration of the redox species depends on the reaction stoichiometry. For the Fe(OH)3 –Fe2+ couple, for example, the half reaction is Fe(OH)3 (s) + 3H+ + e− = Fe2+ + 3H2 O

peo = 16.54

giving pe = peo − log

(Fe2+ ) (H+ )3

(4.19)

and thus pe is sensitive to both the Fe2+ concentration and pH, and pe falls as the reduction of Fe(OH)3 proceeds and Fe2+ accumulates. 4.1.4 pe–pH DIAGRAMS Most redox reactions consume or produce protons and the stoichiometry is often such that pe is very sensitive to pH, as the examples in the previous section show. A simple method for determining which species will predominate under particular conditions of pe and pH in an unknown redox system is to construct ‘pe–pH diagrams’. This is done as follows. Consider the following redox half reaction involving H+ : Ox + mH+ + ne− = Red We have pe = peo −

(Red) m 1 log − pH n (Ox) n

(4.20)

(Ox) (Red)

(4.21)

i.e. n(pe − peo ) + mpH = log

If n(pe − peo ) + mpH > 0 then (Ox) > (Red) and the oxidant is the dominant species, and vice versa. Hence a plot of pe versus pH with (Ox) = (Red) has slope m/n and intercept pe, and for points above the line the oxidant is dominant and for points below the reductant is dominant. pe is taken as the dependent variable, plotted on the ordinate, because pH is often controlled by processes in addition to redox reactions and is therefore more properly the independent variable. Figure 4.1 gives examples for biological redox couples important in natural systems. Figure 4.1(a) shows the diagram for the H2 O–O2 and H2 O–H2 couples. The respective lines are pe = 20.75 − 14 log PO2 − pH with PO2 = 1 atm, and pe = − 14 log PH2 − pH with PH2 = 1 atm. These are upper limits for the partial pressures of O2 and H2 in natural waters. For points above the upper line, H2 O is an effective reductant, producing O2 ; for points below the lower line H2 O is an effective oxidant, producing H2 . The region between the lines, where O2 acts as an oxidant and H2 as a reductant, covers most circumstances in natural systems.

−10

−5

0

5

10

15

4 5 6 7 8 9 10

PH2 > 1 atm

H2O

PO2 > 1 atm

(b)

NH3

4 5 6 7 8 9 10

NH4+

N2

NO3−

(c)

NO2−

4 5 6 7 8 9 10 pH

NH4+

NH3

NO3−

(d)

HS−

4 5 6 7 8 9 10 11

H2S

S(s)

SO42−

(e)

CO32−

HCO3−

4 5 6 7 8 9 10 11

CH4

CO2

Figure 4.1 pe–pH diagrams for important biological redox couples in natural systems. (a) H2 O–O2 . (b) The nitrogen system considering only stable equilibria: the only oxidation states involved are (−III), the elemental state and (+V). (c) The nitrogen system treating NH4 + , NH3 , NO3 − and NO2 − as metastable with respect to N2 which is treated as redox-inert. (d) The SO4 2− –S(s)–H2 S(aq) system, [total soluble S] = 10−2 M. (e) The carbon system ignoring elemental C. After Stumm and Morgan (1996). Reproduced by permission of Wiley, New York

pe

(a) 20

100

101

Thermodynamics and Kinetics of Redox Reactions

Figure 4.1(b) shows the diagram for the stable equilibria in the nitrogen system. According to this diagram N2 should be largely oxidized to NO3 − in most natural waters. The fact that it is not and N2 is known to persist in oxic waters indicates that a complete redox equilibrium does not exist; only a partial equilibrium is attained under the mediation of microbes. Figure 4.1(c) shows the diagram for the nitrogen system with N2 treated as redox-inert and NH4 + , NH3 , NO3 − and NO2 − as metastable with respect to N2 . This diagram more correctly represents conditions in natural systems, with NH4 + as the stable species under mildly reducing conditions and NO3 − under oxic conditions. This example illustrates the difficulty in choosing the correct redox couples to represent real systems in pe–pH diagrams. Some independent insight into the system is generally required to choose the correct couples. Figure 4.1(d) and (e) show diagrams for sulfur and carbon systems. The situation is further complicated for redox reactions involving several solid phases. An example is the Fe–CO2 –H2 O system shown in Figure 4.2. This shows that ferrihydrite, Fe(OH)3 , can be formed over a wide range of pe and pH, though the pe range is increasingly restricted under increasingly acid conditions, and Fe2+ is then the stable form. Siderite, FeCO3 , and the hypothetical Fe(II) hydrous oxide Fe(OH)2 may be formed under moderately reducing conditions but only at pH > 7. Elemental Fe is only stable under very strongly reducing conditions, outside the range in which water is stable. In real systems the situation

25 FeOH2+

20 Fe3+

PO2 > 1 atm

15

Fe(OH)4−

pe

10 Fe2+

5

Fe(OH)3(amorph, s)

0

PH2 > 1

−5 −10 −15

FeCO3(s) Fe(OH)2(s)

Fe(s) 0

2

4

6

8 pH

10

12

14

Figure 4.2 pe–pH diagram for the Fe–CO2 –H2 O system. [Fe(II)] = 1 mM, [Fe(III)] = 0.01 mM, CT = 5 mM. Amorphous Fe(OH)3 is ferrihydrite, FeCO3 siderite, and Fe(OH)2 a hypothetical Fe(II) hydrous oxide. The details of the construction of this diagram are explained in Stumm and Morgan (1996, Chapter 8). Reproduced by permission of Wiley, New York

102

Reduction and Oxidation

may be complicated by the presence of other redox species with which Fe reacts, such as sulfide, and by the slow kinetics of redox and precipitation reactions and the need for microbial mediation. Thus for example siderite is rarely found in soils though in many cases it is the thermodynamically favoured phase as shown in Figure 4.2. These points are discussed further in later sections. Because of the sensitivity of pe to pH it is often convenient to compare peo values ‘corrected’ to pH 7 and termed peo∗ , where: peo∗ = peo −

1 (Red) m log −7 n (Ox) n

(4.22)

As discussed earlier, the concentration-dependent term in Equation (4.22) will often be small in comparison with the pH term and can be ignored. For couples in which the concentration term is more important, such as Fe(OH)3 –Fe2+ , peo∗ values can be calculated for representative concentrations. Table 4.2 gives peo∗ values for important redox couples in natural systems arranged in order of decreasing peo∗ with strong oxidants at the top and strong reductants at the bottom. From such a table it is possible to infer which couples will react when present together and which will have the oxidizing role and which the reducing role. The table shows for example that Fe(OH)3 can readily oxidize organic matter ‘CH2 O’ to form CO2 and Fe2+ but it cannot oxidize N2 to NO3 − . However note that the peo∗ value for the Fe(OH)3 –Fe2+ couple is sensitive to the value of (Fe2+ ).

4.1.5 ENERGETICS OF REACTIONS MEDIATED BY MICROBES Most redox reactions in vitro reach equilibrium only extremely slowly with half times of the order of months or years, even though they may be highly favoured thermodynamically. This is illustrated by the persistence of N2 in oxic systems even though its oxidation to NO3 − is strongly favoured (Table 4.1). However, microbes in soil and water are capable of catalysing particular reactions from which they obtain energy for metabolism. The half times of such microbially catalysed reactions are of the order of hours or days. The amounts of energy consumed or produced in redox reactions, and hence the efficiency with which they can be exploited by microbes, can be calculated from thermodynamic data. This gives surprisingly good insights into the dynamics of microbial communities in natural systems without detailed knowledge of the biochemical and physiological pathways involved. For example, the sequence of reduction reactions that occur in submerged soils following exclusion of O2 matches the order of decreasing free energy change for the corresponding redox reactions. Note that organisms cannot carry out gross reactions that are thermodynamically impossible: they do not oxidize substrates or reduce oxidants per se, but merely catalyse the process by mediating the electron transfers occurring. The energy produced or consumed in a given redox reaction is calculated as follows.

103

Thermodynamics and Kinetics of Redox Reactions Table 4.2

Equilibrium constants of reduction half-reactions at pH 7 and 25 ◦ C

1 O (aq) + H+ + e− 4 2 1 NO3 − + 65 H+ + e− 5

= 12 H2 O

1 NO3 − + 54 H+ + e− 4 1 MnO2 (s) + 2H+ + e− 2 1 Mn3 O4 (s) + 4H+ + e− 2 + −

=

=

1 N (g) + 35 H2 O 10 2 1 N O(g) + 58 H2 O 8 2

= 12 Mn2+ + 2H2 O

peo

peo∗

20.75

13.75

21.05

12.65

18.81

10.06

21.82

9.67a

= 32 Mn2+ + 2H2 O

30.79

8.33

MnOOH(s) + 3H + e

= Mn2+ + 2H2 O

25.33

8.02a

1 NO3 − 2 1 NO3 − 8 1 NO2 − 6

+ H+ + e −

= 12 NO2 − + 12 H2 O

14.15

7.15

14.90

6.15

15.14

5.82

1 CH2 O 4

6.94

−0.06

16.54

−1.46a

3.99

−3.01

5.25

−3.50

4.25

−3.63

2.87

−4.13

4.63

−4.70

11.31

−6.69a

+ +

5 + H 4 4 + H 3 +

−

+e

=

+ e−

=

−

=

+H +e

+

−

1 NH4 + 8 1 NH4 + 6

+ +

1 CH4 (g) 4 2+

Fe(OH)3 (s) + 3H + e

= Fe

1 CH2 O + H+ + e− 2 1 SO4 2− + 54 H+ + e− 8

= 12 CH3 OH

1 SO4 2− + 98 H+ + e− 8 1 CO2 (g) + H+ + e− 8

=

+ 43 H+ + e−

=

1 N 6 2

+

α-FeOOH(s) + 3H + e

= = −

H+ + e − 1 CO2 (g) 4 1 CO2 (g) 4

3 H O 8 2 1 H O 3 2

+

1 H O 4 2

+ 3H2 O

1 H S(g) + 12 H2 O 8 2 1 HS− + 12 H2 O 8 1 CH4 (g) + 14 H2 O 8 1 NH4 + 3

= Fe

2+

+ 2H2 O

= 12 H2 (g) +

+ H + e−

=

+ H+ + e−

=

1 (glucose) + 14 H2 O 24 1 CH2 O + 12 H2 O 4

0.00

−7.00

−0.20

−7.20

−1.20

−8.20

For reductive dissolution of Mn and Fe oxides peo∗ values are calculated with (Mn2+ ) = 0.2 mM and (Fe2+ ) = 1 mM to represent conditions in submerged soil solutions; in other couples reactants are given unit activities.

a

Consider the reaction Ox1 + Red2 = Red1 + Ox2 for which the reduction half reactions are: Ox1 + ne− = Red1 Ox2 + ne− = Red2 with equilibrium constants K1 and K2 , i.e. pe1 = 1/n log K1 and pe2 = 1/n log K2 . Therefore
Go = −2.303RT log K = −2.303RT log

K1 = −2.303RT n(peo1 − peo2 ) K2 (4.23)

104

Reduction and Oxidation

The free energy change for the reaction is
G =
Go + 2.303RT log

(Ox2 )(Red1 ) (Ox1 )(Red2 )

Combining Equations (4.23) and (4.24) gives 
(Ox2 )(Red1 ) o o
G = −2.303RT n(pe1 − pe2 ) − log (Ox1 )(Red2 )

(4.24)

(4.25)

As discussed earlier, the dependence of pe on the concentrations of reductants and oxidants is often small in comparison with its dependence on pH. The term in the square brackets in Equation (4.25) can therefore be replaced by peo∗ terms giving for the approximate standard free energy change: o∗
Go∗ ≈ −2.303RT n(peo∗ 1 − pe2 )

(4.26)

Figure 4.3 shows oxidation and reduction reactions used by microbes as energy sources on a scale of peo∗ (data from Table 4.1). The free energy changes for the different complete reactions can be read from the
Go∗ scale, in accordance with Equation (4.26). The energy expended by microbes in elaborating carbon, for example through fixation of CO2 , and other elements, for example nitrogen through fixation of atmospheric N2 , can be calculated in a similar way. Such calculations indicate the maximum energy available from a reaction or the minimum required to carry it out. The true gain to a microbe is smaller, or the cost larger, because of the energy required for cell maintenance and reproduction and other processes. The energetic efficiencies of biochemical processes are typically of the order of 30–40 %. Nonetheless the ecological succession of microbes in response to the stepwise oxidation of reduced compounds and exhaustion of oxidants can be predicted from such calculations. Thus the succession of aerobic organisms, denitrifiers, manganese reducers, iron reducers, sulfate reducers and methanogenic bacteria following submergence of a soil directly matches the order of decreasing peo∗ for the corresponding redox couples in Figure 4.3(b): O2 –H2 O, NO3 − –N2 , MnO2 (s)–Mn2+ , Fe(OH)3 (s)–Fe2+ , SO4 2− –HS− and CH2 O–CH4 . Microorganisms and organisms in general can be classified according to the principal sources of their energy, carbon and electrons. A hierarchical classification is not possible because all combinations of these three occur. Thus all three can be separate, as for green plants which obtain their energy from sunlight, carbon from CO2 and electrons by oxidizing water to O2 ; and all three can be the same, as for the majority of bacteria which use organic compounds as their sources of energy, carbon and electrons. Organisms that obtain their carbon from inorganic compounds, mainly CO2 , are called autotrophs. They are subdivided into photoautotrophs which obtain energy from sunlight—for example, green plants and photosynthetic bacteria—and chemoautotrophs which obtain energy from chemical processes—for example, in Figure 4.3(a), nitrifying bacteria, which oxidize NH4 + to NO3 − , sulfur oxidizing

130

120

H2 H+

H2S SO42−

100

110

Fe2+ Fe(OH)3

NH4 NO2

−

+

NO2 NO3

−

−

90

80

70

60

50

40

30

20

10

Oxidations 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 −1 −2 −3 −4 −5 −6 −7 −8 −9 −10 O2 H2O

Reductions

(b)

CH2O CO2

Oxidations 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 −1 −2 −3 −4 −5 −6 −7 −8 −9 −10 NO3 NO2

−

H+ H2

CO2 CH4

SO42− HS−

CH2O CH3OH

Fe(OH)3 Fe2+

NO3− NH4+

−

MnO2 Mn2+

NO3− N2O

NO3− N2

O2 H2O

Reductions

10

20

30

40

50

60

70

80

90

100

110

120

130

−∆Go* (kJ mol−1)

peo*

peo*

Figure 4.3 Free energy changes in redox reactions mediated by microbes. (a) Oxidation of reduced inorganic compounds linked to reduction of O2 . (b) Oxidation of organic matter ‘CH2 O’ linked to reduction of various organic and inorganic oxidants. pH = 7 and unit oxidant and reductant activities except (Mn2+ ) = 0.2 mM and (Fe2+ ) = 1 mM

−∆Go* (kJ mol−1)

(a)

105

106

Reduction and Oxidation

bacteria, which oxidize reduced S compounds to SO4 2− , and Mn(II) and Fe(II) oxidizing bacteria, which produce insoluble Mn and Fe oxides, though it is not certain that useful energy is derived from this. Examples of autotrophs using different electron sources in fixing CO2 are green plants which derive electrons from the oxidation of water, sulfide oxidizers which oxidize H2 S(g) to colloidal S, and ammonium oxidizers which oxidize NH4 + to NO2 − . Organisms that obtain carbon from ingested organic compounds are called heterotrophs, and most also derive their energy and electrons from these organic compounds. Examples are fungi, protozoa and most bacteria. A wide range of organic and inorganic oxidants are used as end electron acceptors in oxidizing the organic compounds, as in the reactions shown in Figure 4.3(b). Also a wide range of organic compounds are oxidized. The resulting free energy changes may differ substantially from those in Figure 4.3(b) for oxidation of the average compound ‘CH2 O’. For example the oxidation of glucose yields about 54 kJ more energy per mole of C than oxidation of acetate. This makes an increasingly significant difference the lower the peo∗ of the oxidizing couple. Thus it makes only a small difference for O2 or NO3 − reduction (12 and 15 %, respectively), but a large difference for SO4 2− reduction (69 %). An important component of the overall efficiency of energy production by microbes is the location of the linked couples and the resulting need to transport reactants and products across cell membranes. In denitrification and SO4 2− reduction, because all of the NO3 − and to a lesser extent the SO4 2− are dissolved in the soil solution, they are readily imported into the cell and their reduction linked directly to the oxidation of organic compounds via electron transfer systems. But in Mn and Fe reduction, the oxides are only sparingly soluble, and so the concentrations of Mn(III, IV) and Fe(III) in solution are small, even when large concentrations of the solid oxides are present. This presented a problem in establishing that Mn and Fe reduction was directly linked to microbial respiration in natural systems, rather than being an indirect effect through abiotic reactions involving side products of respiration. The evidence for the direct involvement of microbes is discussed in Chapter 5. 4.2 REDOX CONDITIONS IN SOILS This topic has a long history of research (Harrison and Aiyer, 1920; Sturgis, 1936; Pearsall and Mortimer, 1939; Shioiri, 1943; De Gee, 1950; Takai, 1952; Ponnamperuma, 1955; Baas-Becking et al., 1960; Jeffrey, 1961; Patrick, 1966; Ponnamperuma, 1972; Yu, 1985; Kyuma, 2003). The following factors result in conditions differing from those in simple aquatic systems: • The soil has a structure and contains a network of pores filled to a varying extent with water, and the soil is overlain by a layer of standing water of varying depth and degree of oxygenation. The filling and emptying of the pores is often very dynamic changing from complete saturation to near emptiness

Redox Conditions in Soils

•

• •

•

107

and vice versa within a matter of days. Redox conditions are correspondingly dynamic. Transport of solutes and gases through the soil is much slower than through soilfree water because of the restricted cross-sectional area for transport through the soil pore network and because of adsorption and reaction on soil surfaces (Chapter 2). Redox conditions are therefore closely linked to transport processes. Mineral surfaces have a much greater influence through sorption and precipitation of solutes and direct mediation of redox reactions. The soil contains organic matter which is humified to a varying extent and inputs of fresh organic matter are often much larger than in aquatic systems because of greater net primary productivity. The organic matter both provides substrates for microbial processes and participates in sorption and other reactions. The micro- and macrobiological ecologies are different.

In this section the redox conditions developing in soils following submergence are described and the processes governing these conditions are analysed in terms of the soil chemistry and microbiology discussed so far. 4.2.1 CHANGES WITH DEPTH IN THE SOIL The floodwater standing on the soil surface is usually sufficiently shallow, well mixed by wind and thermal gradients, and oxygenated by photosynthetic organisms that it is essentially aerobic. However transport of O2 into the underlying soil is too slow for more than a thin layer to be aerobic. In this layer the concentrations of Mn2+ , Fe2+ and other reduced species are negligible, and CO2 is the main end product of microbial respiration. In the underlying anaerobic soil, only a few millimetres away, the concentrations of Mn2+ , Fe2+ and the various organic products of anaerobic respiration can be very large. Thus conditions change dramatically over a very short distance. The distribution of reduced species with depth follows a characteristic pattern reflecting the succession of terminal electron acceptors used by microbes—O2 , NO3 − , Mn(III, IV), Fe(III), SO4 2− and organic C in fermentation reactions. Sorption, precipitation and dissolution reactions also influence the distribution. Figure 4.4 shows profiles of EH and extractable Mn2+ , Fe2+ and S2− in soil columns following flooding, illustrating some of these effects. A steady state develops over time and the profiles of the reduced species in the soil then reflect the profile of EH being progressively deeper for the less-easily reduced species. Thus the profile of Mn2+ in the figure extends closest to the surface, Mn reduction taking place at the highest EH , and the S2− profile extends least close to the surface. The depth to which O2 penetrates the soil, as indicated by the depth at which EH begins to decrease, is about 10 mm under the conditions of the figure. This depth depends on such factors as the oxygenation of the floodwater, the

25 −100 0

20

15

10

5

13 wk

4 wk

1 day

100 200 300 400 500 0 EH (mV)

10 wk

2 wk

2

10

1 wk

4 6 8 [Mn2+] (µmol g−1)

1 day

13 wk

8 wk

6 wk

10 wk

2 wk

0

4 wk

6 wk

10 20 30 [Fe2+] (µmol g−1)

1 day

1 wk

2 wk

13 wk

40

8 wk

7 wk

10 wk

0

3 wk

8 wk 11 wk

250 500 750 100012501500 [S2−] (cpm g−1)

2 wk

13 wk

5 wk

Figure 4.4 Depth distribution of EH , Mn2+ , Fe2+ , S2− at different times following flooding (Patrick and DeLaune, 1972). Reproduced by permission of Soil Sci. Soc. Am.

Depth in soil (mm)

0

108

109

Redox Conditions in Soils

amount and quality of organic matter present, and the concentrations of easily reducible Fe(III) and other reductants. I now summarize the changes in electrochemical conditions that occur in the soil with time following submergence as they affect the profiles and dynamics of redox species. 4.2.2 CHANGES WITH TIME Reduction of a submerged soil proceeds roughly in the sequence predicted by thermodynamics: O2 + CH2 O −−−→ CO2 + H2 O −

+

4NO3 + 5CH2 O + 4H −−−→ 2N2 + 5CO2 + 7H2 O 2MnO2 + CH2 O + 4H+ −−−→ 2Mn2+ + CO2 + 3H2 O +

4Fe(OH)3 + CH2 O + 8H −−−→ 4Fe and

2+

+ CO2 + 11H2 O

(4.27) (4.28) (4.29) (4.30)

SO4 2− + 2CH2 O + 2H+ −−−→ H2 S + 2CO2 + 2H2 O

(4.31)

2CH2 O −−−→ CH4 + CO2

(4.32)

Typically O2 becomes undetectable within a day of submergence and then NO3 − is reduced. Reduction of NO3 − will not occur until the O2 concentration reaches a very small value. Likewise, whilst NO3 − is being reduced, the pe is poised in the range 3–6 and reduction of Mn and Fe are prevented. However NO3 − will be exhausted within a matter of days and then reduction of Mn and Fe may proceed. In the absence of O2 Fe(III) is generally the main oxidant in the soil, its concentration typically exceeding concentrations of NO3 − , Mn(III, IV) or SO4 2− by at least an order of magnitude (Chapter 3). Between 1 and 20 % and sometimes as much as 90 % of the free Fe(III) in the soil is reduced to Fe(II) over 1–2 months of submergence (Ponnamperuma, 1972; van Breemen, 1988). Some of the structural Fe(III) in soil clays is also reduced (Stucki et al., 1997). The course of soil reduction and the changes in pe and pH are therefore generally dominated by the reduction of Fe(III). Changes in pe, pH and Alkalinity It is difficult to obtain reliable measurements of EH and hence pe in soils. Strictly, only measurements made with the electrodes in soil solution extracts rather than directly in soil are thermodynamically meaningful, and these are also subject to various errors, particularly due to the presence of mixed redox systems. Nonetheless it is a useful parameter and is the only single electrochemical property that can distinguish submerged soils from well-drained ones. Figure 4.5 shows changes in pe, pH and Fe2+ in the soil solution of four representative soils following flooding (IRRI, 1964). The figure shows that in all the soils there is a minimum in pe after a few days followed by an increase,

−1

0

1

2

3

4

5

6

0

2

4

6

8

10 21 26 30

1.67 2.78 0.30 1.2

10 12 14 16

1.5 4.1 1.5 5.1

Soil Org C Active (%) Fe (%)

5.2

5.4

5.6

5.8

6.0

6.2

6.4

6.6

6.8

7.0

7.2

0

4

6

8 10 12 14 16

Time (weeks after flooding)

2

[Fe2+] in solution (mM)

pH

0

2

4

6

8

10

12

0

2

4

6

8

10 12 14 16

Figure 4.5 Changes in pe, pH and Fe2+ in soil solutions of various soils following submergence at 25 ◦ C. pe values are calculated from measured EH (V) values in soil solutions. Data from IRRI (1964). Reproduced by permission of IRRI

pe

7

110

111

Redox Conditions in Soils

and this is characteristic of most soils following flooding (Ponnamperuma, 1972). The minimum can be less than zero and can be accompanied by evolution of H2 gas. It is due to fermentation reactions starting as soon as O2 and NO3 − are used up but before populations of Mn and Fe reducing bacteria are established. As discussed in Section 5.3, the low solubility of Mn(III, IV) and Fe(III) oxides may initially limit the rate of their reduction. Organic acids produced in fermentation reactions will help dissolve Mn(III, IV) and Fe(III) from oxide particles and thereby facilitate the establishment of the Mn and Fe reducers. As Mn and Fe reduction then proceed, the pe will increase to values corresponding to the Mn and Fe couples involved, and then gradually decline. Simultaneously H+ ions are consumed in Reactions (4.28)–(4.31) and the pH tends to increase. Initially the pH of aerobic soils may decrease following submergence because CO2 formed in aerobic respiration escapes from the soil only very slowly, and it therefore accumulates. As CO2 continues to accumulate during anaerobic respiration and fermentation, large partial pressures develop, typically in the range 5 to 20 kPa. The accumulation of CO2 lowers the pH of alkaline soils and curbs the increase in pH of acid soils. As a result the pHs of all soils tend to converge following submergence in the range 6.5–7. As the partial pressure of CO2 increases, the concentration of HCO3 − in the soil solution increases and therefore the concentrations of balancing cations in solution increase. Changes in alkalinity and concentrations of cations in solution following submergence are shown in Figure 4.6. The NH4 + , Mn2+ and especially Fe2+ ions formed in soil reduction displace exchangeable cations into solution.

25 Concentration in soil solution (mmolc L−1)

Alkalinity 20 Ca2+ + Mg2+ + NH4+ + Na+ + K+

15

Fe2+ + Mn2+

10

5

0

0

2 4 6 8 10 12 14 16 Time (weeks after submergence)

Figure 4.6 Changes in alkalinity and concentrations of cations in the soil solution following submergence (Ponnamperuma, 1972)

112

Reduction and Oxidation

Also, the changes in pH will cause changes in the charges of variable-charge clays and organic matter, thus the cation exchange capacity of acid soils will tend to increase and that of alkaline soils decrease.

Changes in Fe Large concentrations of Fe2+ develop in the soil solution in the weeks following flooding, often several mM or tens of mM (Figure 4.5). Calculations with chemical equilibrium models show that the ion activity products of pure ferrous hydroxides, carbonates and other minerals are often exceeded 100-fold (Neue and Bloom, 1989). Evidently precipitation of these minerals is inhibited, probably as a result of adsorption of foreign solutes, such as dissolved organic matter and phosphate ions, onto nucleation sites (Section 3.7). However, once a sufficient supersaturation has been reached there is a rapid precipitation of amorphous solid phases, which may later re-order to more crystalline forms. Only a small part of the Fe(II) formed in reduction remains in solution; the bulk is sorbed in exchangeable forms or, eventually, precipitated. The identities of the solid phases that form remain a mystery. Direct identification is difficult because Fe(II) and Mn(II) solid phases are readily oxidized by O2 and it is therefore necessary to maintain scrupulously anoxic conditions to ensure that the material examined actually represents that in anoxic soil. An alternative is to make indirect assessments through measurements of pe, pH and [Fe2+ ] in solution, but these too are difficult (see section on measurement of redox potential in soil). Some of the well-known solid phases that might form are shown in Table 4.3. None of these appears to be quantitatively important, at least in the first few Table 4.3 at 25 ◦ C

Some possible mineral phases in reduced soils and their equilibrium constants

Compound Mn(II) hydroxide Rhodocrosite Hauerite Fe(II) hydroxide Fe(II)Fe(III) hydroxide Siderite Vivianite Pyrite Source: a Calculated from
Gof values. b Stumm and Morgan (1996). c Lindsay (1979). d Arden (1950).

Equilibrium

log K

Mn(OH)2 (s) + 2H+ = Mn2+ + 2H2 O MnCO3 (s) = Mn2+ + CO3 2− MnS2 (s) = Mn2+ + S2 2− Fe(OH)2 (s) + 2H+ = Fe2+ + 2H2 O Fe3 (OH)8 (s) + 2H+ = Fe2+ + 2Fe(OH)3 + 2H2 O FeCO3 (s) = Fe2+ + CO3 2− Fe3 (PO4 )2· 8H2 O(s) = 3Fe2+ + 2H2 PO4 − + 8H2 O FeS2 (s) = Fe2+ + S2 2−

15.13a −10.39b −14.79c 11.67a −10.60d −10.45b 3.11c −26.93c

Redox Conditions in Soils

113

weeks or months following submergence. The large increases in CO2 pressure as dissolved Mn(II) and Fe(II) accumulate would suggest Mn and Fe carbonates should be precipitated. However it is unlikely that simple Mn and Fe carbonates are formed because Mn2+ and Fe2+ ions have similar radii (0.083 and 0.078 nm, respectively) and can readily substitute for each other in crystal lattices. Rhodocrosite (MnCO3 ) and siderite (FeCO3 ) are end members of a continuous series of solid solutions of Fe(II)–Mn(II) carbonates (Deer et al., 1992). Iron–manganese minerals also readily incorporate Mg2+ (radius 0.072 nm) and to a lesser extent Ca2+ (0.1 nm) and other divalent cations. It is therefore likely that various solid solutions are formed. There is evidence that mixed Fe(II)–Fe(III) hydroxides are formed. These can be produced easily in vitro by partial oxidation of pure Fe(II) hydroxy salts and they have some of the observed properties of the solid phase Fe(II) found in reduced soils, including the grayish-green colours characteristic of reducing conditions in soils. This material is ‘green rust’ and has the general formula Fe(II)6 Fe(III)2 (OH)18 with Al3+ partly substituted for Fe3+ and Cl− , SO4 2− and CO3 2− substituted for OH− . Once precipitation begins, a quasi-steady state will eventually be attained in which the soil pe and pH are poised by the redox and precipitation equilibria operating. In the transition to the steady state, protons will be provided by dissociation of acids in the soil solution—e.g. H2 CO3 derived from CO2 –and by reactions with the soil exchange complex. The course of reduction and the eventual steady state will depend on these reactions and it is therefore necessary to allow for them in predicting what the steady state conditions will be. In the following section I describe a simple model for calculating the changes in pe, pH and concentrations of inorganic reductants during soil reduction, allowing for the effects of pH buffering and cation exchange, and the characteristics of the mineral phases formed. The approach is based on that of van Breemen (1988) for partial redox equilibrium in soil without pH buffering and cation exchange. 4.2.3 CALCULATED CHANGES IN pe, pH AND Fe DURING SOIL REDUCTION Consider an idealized soil containing ferric hydroxide and readily decomposable organic matter. The following conditions hold: • the soil is initially saturated with the atmospheric partial pressure of O2 but otherwise closed to exchange of O2 ; • the partial pressure of CO2 is constant; • the soil exchange complex is initially saturated with divalent cations M2+ , i.e. H+ is treated as non-exchangeable and there are no other monovalent cations; • the soil reaches a steady state following reduction in which the soil solution is in equilibrium with Fe(OH)3 and Fe3 (OH)8 .

114

Reduction and Oxidation

Following flooding, O2 dissolved in the soil solution is consumed according to Reaction (4.27). There is no pH change, the CO2 pressure being constant, and pe is poised by the O2 –H2 O couple: O2 (aq) + 4H+ + 4e− = H2 O i.e. pe = 21.45 + 14 log[O2 ]L − pH

(4.33)

Once all the O2 has been used up Fe(OH)3 is reduced according to Reaction (4.30) and the pe is poised by the Fe(OH)3 –Fe2+ couple: Fe(OH)3 (s) + 3H+ + e− = Fe2+ + 3H2 O i.e. pe = 16.54 − log[Fe2+ ]L − 3pH

(4.34)

Once pe falls sufficiently, precipitation of Fe3 (OH)8 commences and Fe3 (OH)8 is formed at the expense of Fe(OH)3 according to the reaction 3Fe(OH)3 + CH2 O + 8H+ → Fe3 (OH)8 + CO2 + 11H2 O The pe is now poised by the Fe(OH)3 –Fe3 (OH)8 half reaction: 3Fe(OH)3 (s) + H+ + e− = Fe3 (OH)8 + H2 O i.e. pe = 1.46 − pH

(4.35)

Hence for a given generation of Fe2+ in Fe(OH)3 reduction, and for a specified initial soil CEC and concentration of non-carbonate anions in the soil solution ([X− ]L ), we have five unknowns: the soil pH and the concentrations of Fe2+ and M2+ in the soil solid and solution; and these can be found from the following five equations: (1) Equation (3.69) for the electrical neutrality of the solution, with [HCO3 − ] found from pCO2 and pH; (2) Equation (3.70) for the electrical neutrality of the solid, with changes in acidity in the solid related to changes in pH with the soil pH buffer capacity; (3) Equation (3.72) for divalent–divalent cation exchange; and (4) and (5) two equations like Equation (3.73) for conservation of M2+ and Fe2+ . These equations can be solved simultaneously with Equations (4.33)–(4.35) to obtain values of pe, pH, [O2 ] and [Fe2+ ] over the course of reduction. Figure 4.7 shows results for realistic flooded soil conditions, expressed in terms of the amounts of CH2 O oxidized in the different reactions. Figure 4.7(a) gives results in the absence of pH and cation buffering by the soil; Figure 4.7(b)–(d) gives results for different values of bHS , CEC and [X− ]L .

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0

2

O2

4

6

8 10 12 14 16

pe

pH

Fe2+

bHS = 0, CEC = 0, [X−]L = 0

0

(b)

2

4

O2 6

0

(c)

2

4

O2 6

8 10 12 14 16

pe

pH

Fe2+

bHS = 50, CEC = 35, [X−]L = 20

CH2O oxidized (mmol kg−1)

8 10 12 14 16

pe

Fe2+

pH

bHS = 15, CEC = 35, [X−]L = 20

0

(d)

2

O2 4

6

pe

pH

−2

0

2

4

6

8

10

12

14

16

18

8 10 12 14 16

Fe2+

bHS = 50, CEC = 10, [X−]L = 10

4.0

4.5

5.0

5.5

6.0

6.5

7.0

7.5

8.0

pH pe

Figure 4.7 Calculated changes in pe, pH, [O2 ] and [Fe2+ ] in an idealized soil during reduction. Mineral phases Fe(OH)3 and Fe3 (OH)8 . Parameters for pH buffering and cation exchange differ between (a)–(d) as indicated. Units of bHS (soil pH buffer power), mmol kg−1 pH−1 ; CEC (initial cation exchange capacity), cmolc kg−1 ; and [X− ]L (concentration of non-carbonate anions), mM. CO2 pressure = 10 kPa, θ = 0.6, ρ = 1.0, initial pH = 4.5

[Fe2+], [O2] in solution (mM)

(a)

115

116

Reduction and Oxidation

It will be seen that pe is initially buffered at about 15 until the O2 is exhausted, and it then falls rapidly to the point where it is buffered by the Fe(OH)3 –Fe2+ couple. Ferrous ions are now released into the solution and protons removed from it, and the changes in pe and pH now depend on the buffering of Fe2+ and H+ by the soil solid. As a result of buffering, the increases in Fe2+ and pH as Fe(OH)3 is reduced are more gradual. Comparing Figure 4.7(b) and (c), for which the CEC and [X− ]L are the same but bHS different, the effect of increasing bHS is to further slow the increase in pH, and the pH at the steady state when Fe3 (OH)8 is formed is smaller and the pe and concentration of Fe2+ in solution correspondingly larger. Also a much larger quantity of CH2 O is consumed in reaching the steady state. From the stoichiometry of Reaction (4.30), the amount of exchangeable Fe2+ formed in mmolc kg−1 is roughly four times the amount of CH2 O oxidized. The effect of varying CEC can be seen by comparing Figure 4.7(c) and (d). With decreasing CEC at constant bHS , [X− ]L and PCO2 , the concentration of Fe2+ at steady state is increased and the pH correspondingly decreased and pe increased. In summary, the calculations predict that: (1) O2 will disappear rapidly after flooding; (2) dissolved Fe2+ will appear in the soil solution and its concentration increases to a constant steady-state level; (3) an initially low pH will increase to between 6.5 and 7 at the steady state; (4) pe will decrease from about 15 to near 0; (5) the rates of change in Fe2+ , pH and pe and their steady-state values, and the amounts of organic matter oxidized in reaching the steady state, depend on pH buffering and cation exchange by the soil. These predictions can be compared with the results for real soils shown in Figure 4.7. In the real soils the ranges of pe and pH are similar and a steady state is attained in which the concentrations of Fe2+ in solution are similar to those predicted with the model. However the large peak in Fe2+ concentrations in some soils before the steady state is reached is not predicted. The peak occurs because precipitation of ferrous carbonate is slow and may be inhibited by interfering solutes in the soil, resulting in supersaturation with respect to the expected solid phases. Note that although the pe–pH–[Fe2+ ] relationships shown in Figure 4.7 are consistent with control by the Fe(OH)3 –Fe3 (OH)8 system, in fact various other reduced Fe solid phases are possible and as discussed above it is difficult to establish unequivocally which phase controls Fe2+ solubility in reduced soils. 4.2.4 MEASUREMENT OF REDOX POTENTIAL IN SOIL In principle the redox potential provides a simple means of gauging a soil’s redox status. However in practice it is difficult to make reliable measurements.

Redox Conditions in Soils

117

Stumm and Morgan (1996) discuss the problems for simple aquatic systems and van Breemen (1969), Ponnamperuma (1972), McBride (1994) and Patrick et al. (1996) discuss the additional problems for soil systems. I here give the main points. Measurements of EH are usually made with a platinum electrode placed in the soil solution together with a reference half cell electrode of known potential. The platinum electrode transfers electrons to and from the soil solution without reacting with it. Reducing half reactions in the soil tend to transfer electrons to the platinum electrode and oxidizing half reactions to remove them. At equilibrium no electrons flow and the electric potential difference between the half cell comprising the platinum electrode and the soil solution and the half cell comprising the reference electrode is recorded. The first problem to mention is that thermodynamically meaningful measurements of EH must be made on soil solution extracts and not directly on the soil itself. Although EH values measured in soil following reduction may show the expected qualitative trends and expected differences between soils, they are not satisfactory for quantitative interpretation. Hence duplicate measurements of EH in soil can vary by as much as 100 mV and values are generally far too low in terms of the Fe2+ and Mn2+ concentrations measured (IRRI, 1964). This is firstly because the measurement indicates the potential in the immediate vicinity of the electrode and not that of the whole soil, and there may be large microscale variations in EH especially near the surfaces of bacterial cells. Secondly they are subject to liquid junction potential errors. It is therefore necessary to make measurements in solution withdrawn from the soil ensuring the minimum of gas exchange during sampling. It is particularly important that no O2 is allowed to enter the solution and that no CO2 is lost. This may be achieved by withdrawing the solution through porous tubing into previously evacuated tubes. Apart from these sampling errors there are a number of intrinsic errors in the measurement of EH in soil solutions. The measurement depends on there being no net flow of current through the circuit made by the platinum electrode and reference electrode. However the current in one direction, called the exchange current, i0 , is not zero. Its value for each half-reaction varies with the electrode potential and with the concentrations of the oxidant and reductant. Figure 4.8 shows this schematically for the Fe2+ –Fe3+ couple. As can be seen from the figure, an infinitesimal shift in the electrode potential from its equilibrium value will make the half reactions proceed in one direction or the other and a net current will flow through the circuit. The equilibrium potential of the system can be found from the potential at which no net current flows. How precisely and reproducibly this measurement indicates the equilibrium potential depends on how steeply the net current deviates from zero near the equilibrium potential. The greater the exchange current, i0 , the more steeply the net current varies with the potential. This in turn depends on the redox couple operating and its concentration. Modern instruments will give reliable measurements for i0 values greater than about 0.1 µA. Figure 4.8 shows that for the Fe2+ –Fe3+ couple, i0 ≈ 100 µA

118

Reduction and Oxidation net current

(a) −100

(b) −100

Fe3+→ Fe2+ −i 0

−50

−50 Fe3+→ Fe2+

← Potential (mV) 525 Current (µA)

net current

0

0 475

500

525

475 Fe2+→ Fe3+

+i 0

50

Fe2+→ Fe3+

50

100

100

(c) −50

−i 0

0 525 50

net current

Fe3+→ Fe2+

475

500

450 +i 0 425

+i 0 Fe2+→ Fe3+

Figure 4.8 Electrode current versus electrode potential curves for the Fe2+ –Fe3+ couple in water at pH 2 with (a) [Fe3+ ] = [Fe2+ ] = 1 mM; (b) [Fe3+ ] = [Fe2+ ] = 0.1 mM; (c) [Fe3+ ] = 0.1 mM, [Fe2+ ] = 1 mM. Electrode area = 1 cm2 (Stumm and Morgan, 1996). Reproduced by permission of Wiley, New York

for [Fe3+ ] = [Fe3+ ] = 10−3 M (Figure 4.8a). If the concentration of both ions is 10-fold smaller, i0 and the slope are 10-fold smaller (Figure 4.8b). However if the concentration of only one of the ions is decreased the drop in i0 is not as great (Figure 4.8c); note also that the equilibrium potential is shifted. If [Fe3+ ] = [Fe3+ ] = 10−7 M, i0 ≈ 0.1 µA and measurements are no longer reliable. In practice the limiting concentration is nearer 10−5 M because of the effects of trace impurities. The value of i0 will increase with the surface area of the electrode. However the benefit of this tends to be offset by greater effects of impurities. In the case of the O2 –H2 O couple, the net current is virtually zero over a wide range of electrode potentials as shown in Figure 4.9(a). This makes it extremely difficult to determine the equilibrium potential for the O2 –H2 O couple, and so EH measurements in aerated soils are not reliable. A further problem, particularly in soil systems, is that several redox systems may be present, in which case the apparent equilibrium potential may be the result

119

Transformations of Nutrient Elements Accompanying Changes in Redox (a)

(b) H2O→H2

−1

Current (mA)

O2→H2O

O2→H2O Fe3+→ Fe2+

0

0 +1 H2O→O2

1

0 −1 Potential (V)

Em

Eeq

Potential (V)

Fe2+→ Fe3+

Figure 4.9 Electrode current versus electrode potential curves for solutions containing O2 : (a) in otherwise pure water; (b) in the presence of Fe2+ . In (a) the net current is close to zero over a wide range of potential, so it is difficult to locate the equilibrium potential. In (b) the measured equilibrium potential is a mixed potential, Em , obscuring the true equilibrium potential of the system, Eeq (Stumm and Morgan, 1996). Reproduced by permission of Wiley, New York

of the combined exchange currents of two or more redox couples. Figure 4.9(b) illustrates this for the Fe2+ –Fe3+ system in the presence of trace concentrations of dissolved O2 . The measured equilibrium potential, Em , at which the net current is zero may be the potential at which the rate of reduction of O2 at the electrode equals the rate of Fe2+ oxidation. This would be likely if the concentration of Fe2+ greatly exceeded that of Fe3+ , as in general it will in submerged soils. The two couples are not in equilibrium with each other and the measured potential is termed a mixed potential. The mixed potential does not represent either of the individual couples operating and is therefore difficult to interpret. Many redox couples do not react reversibly at electrode surfaces. Examples are CO2 –CH4 and NO3 − –N2 . This too complicates interpretation. These factors rather constrain the usefulness of EH measurements in soil solutions. Inferences about the thermodynamics of redox processes in soils that rely heavily on measurements of redox potential should be treated with caution. Nonetheless soil EH measurements provide a ready measure of redox status, for example in experiments in which constant EH and pH are required (Patrick et al., 1973). 4.3 TRANSFORMATIONS OF NUTRIENT ELEMENTS ACCOMPANYING CHANGES IN REDOX These are briefly discussed here in the context of redox chemistry. More complete discussions are given in Chapters 5–8.

120

Reduction and Oxidation

4.3.1 TRANSFORMATIONS OF CARBON In broad terms the decomposition of organic matter under anaerobic conditions is expected to be slower than under aerobic conditions because the free energy changes for the reactions involved are much smaller (Table 4.1 and Figure 4.3). For example, for the aerobic decomposition of ‘CH2 O’, 1 ‘CH2 O’ 4

+ 14 O2 = 14 CO2 (g) + 14 H2 O


Go = −119 kJ mol−1 at pH 7, whereas for its anaerobic decomposition in methanogenesis, 1 ‘CH2 O’ = 14 CO2 (g) + 14 CH4 (g) 4
Go = −17.7 kJ mol−1 at pH 7. Consequently the microbes mediating the decomposition derive less energy and produce fewer cells per unit of carbon metabolized. The accumulation of organic matter in marshes and peat bogs illustrates this point. (But note the rarity of tropical wetland soils with large organic matter contents, discussed in Section 3.7.) The most striking difference between anaerobic and aerobic decomposition is in the nature of the end products. In aerobic decomposition the main products are CO2 , NO3 − , SO4 2− and resistant residues; in anaerobic decomposition they are CO2 , H2 , CH4 , N2 , NH4 + , H2 S and various partially decomposed and humified residues. The decomposition proceeds in two stages. The first involves formation of organic acids, particularly acetic, propionic and butyric, plus various aliphatics and phenolics, some of which are toxic to plants. The second involves conversion of organic acids to gaseous products and follows a characteristic pattern. In the first few days, H2 formed in fermentation reactions may be evolved together with CO2 . Nitrogen gas is also evolved, formed in denitrification of NO3 − . As inorganic redox couples then begin to buffer the redox potential, H2 evolution ceases and CO2 is the main end product of carbohydrate metabolism. This continues until the pe and pH reach values at which methanogenesis is possible, typically 1 or 2 weeks after submergence. The concentration of CH4 in the soil solution and in gas bubbles then exceeds the concentration of CO2 several-fold as a result of solubility and precipitation effects. Although there is wide variation in the composition of gases formed between soils, this general pattern is always seen. At higher temperatures, CO2 and CH4 are formed sooner and at greater rates. Also, at higher temperature and pH, the ratio of CH4 to CO2 in the soil gases changes in favour of CH4 because of solubility and precipitation effects and the higher optimal temperatures for methanogens. 4.3.2 TRANSFORMATIONS OF NITROGEN The main transformations of N are summarized in Figure 4.10. In the absence of oxygen, mineralization of organic N proceeds only as far as NH4 + , and NH4 +

121

NO2

+3 +2

NO2− NO

+1

N2O

0

N2 N fixation

−3

NH4+

pe

Oxidation

+4

12

Reduction

NO3−

nitrification

+5

denitrification

Oxidation state of N

Transformations of Nutrient Elements Accompanying Changes in Redox

−4

immobilization Organic N mineralization

Figure 4.10 Nitrogen transformations in submerged soils on a redox scale (McBride, 1994). Reproduced by permission of Oxford University Press

accumulates in the soil solution and exchange complex. Because of the low N requirement of anaerobic metabolism, subsequent immobilization by microbes tends not to be important, or, if it occurs—as when organic matter with a wide C:N ratio is present—the immobilization is temporary. Further transformations of N take place at the oxic interfaces between the soil and floodwater and root and soil where NH4 + diffusing in from the neighbouring anoxic soil may be nitrified to NO3 − . Subsequently, NO3 − diffusing out into the anoxic soil may be denitrified to N2 . This process results in significant losses of N from wet soils but its importance in submerged soils is unclear (Section 5.3). Under strongly reducing conditions (pe < −4) reduction of N2 to NH4 + is thermodynamically possible. The net reaction is 1 N (g) 6 2

+ 13 H+ + 14 ‘CH2 O’ = 13 NH4 + + 14 CO2 (g)


Go = −14.3 kJ mol−1 at pH 7. However this reaction has a very large activation energy because of the energy required to break the N≡N triple bond (942 kJ mol−1 ). Therefore only highly specialized ‘nitrogen fixing’ organisms are capable of maintaining sufficiently reducing conditions in their cells to mediate the reaction. The niches in submerged soils in which nitrogen fixers may operate are discussed in Chapter 5. Most of the mineralizable N in the soil is converted to NH4 + within a few weeks of submergence if the temperature is favourable and the soil not strongly acid or deficient in other nutrients. The concentration of NH4 + in the soil solution typically reaches 0.1 to 5 mM buffered by from 5 to 20 times this concentration

122

Reduction and Oxidation

Concentration of P in soil solution (µM)

(c)

(b) 8

6 25 18 23

4

21 29 28 1

2

27 0

0

2

4

6

8

Concentration of SO42− in soil solution (mM)

Concentration of NH4+ in soil solution (mM)

(a)

10 12 14 16

12 16.5 mM at 0.5 wk

10

39 8 6 1

4

23

21 2 14

26

0

0

2

4

6

8

10 12 14 16

140 120 Soil

pH

1 14 18 21 23 25 26 27 28 29 39

7.6 4.8 5.6 4.6 5.7 4.8 7.6 6.6 4.9 5.8 8.1

Org C Active (%) Fe (%)

100 1 80 60 25 40 20 0

0

26 27 14 2 4 6 8 10 12 14 16 Time (weeks after flooding)

2.3 2.8 6.0 4.1 8.0 4.4 1.5 2.0 2.9 7.7 2.0

0.18 2.13 0.27 2.78 0.47 0.18 0.30 1.60 4.70 1.80 -

Figure 4.11 Changes in (a) NH4 + , (b) SO4 2− and (c) P in the soil solution of various soils following flooding (modified from IRRI, 1964, 1965). Reproduced by permission of IRRI

of NH4 + on the soil exchange complex. Figure 4.11 shows changes in NH4 + in solution following submergence of a range of soils.

4.3.3 TRANSFORMATIONS OF SULFUR The stable form of sulfur under moderately strong reducing conditions (pe < −3) is hydrogen sulfide, H2 S, which is readily soluble and under non-acid conditions

Transformations of Nutrient Elements Accompanying Changes in Redox

123

dissociates to HS− (pK = 7.02). For the reduction of SO4 2− the net reaction is 1 ‘CH2 O’ 4

+ 18 SO4 2− + 18 H+ = 14 CO2 (g) + 18 HS−

and
Go = −20.5 kJ mol−1 at pH 7. H2 S and HS− are also produced in the hydrolysis of the S-containing amino acids. The HS− formed further dissociates to S2− (pK = 13.9). However in most submerged soils the concentration of Fe2+ in the soil solution is sufficient that virtually all S2− is precipitated as amorphous ferrous sulfide and very small concentrations of H2 S and HS− remain in solution. The relations between the SO4 2− –HS− and Fe(OH)3 –Fe2+ systems at neutral pH are shown in Figure 4.12. Amorphous ferrous sulfide may gradually crystallize as mackinawite (FeS). Under some circumstances pyrite is then formed, e.g. FeS(s) + S(s) → FeS2 (s), leading to potential acid sulfate soils (Section 7.3). There may be a cycling of S compounds of different oxidation state between anaerobic and aerobic zones in the soil, such as at the soil—floodwater interface. In reduced lake and marine sediments this leads to accumulation of insoluble sulfides as SO4 2− carried into the sediment from the water above is immobilized. Such deposits function as sinks for heavy metals. Plants absorb S through their roots as SO4 2− ; H2 S is toxic to them. Therefore HS− must be oxidized to SO4 2− in the rhizosphere before it is absorbed. Figure 4.12 shows changes in the concentration of SO4 2− in the soil solution following submergence of a range of soils. In neutral and alkaline soils concentrations of SO4 2− greater than 10 mM may decrease to 0 within 6 weeks of submergence. In acid soils the concentration of SO4 2− in solution may initially increase following submergence and then slowly decline over several months. FeS

FeCO3

Fe(OH)3

log concentration (M)

0 −2

H2S + HS−

SO42−

−4 −6 −8

Fe2+

−10 −12 −8

−6

−4

−2

0

2

4

6

8

10

pe

Figure 4.12 Concentration–pe diagram for FeS, FeCO3 and Fe(OH)3 at pH = 7, CT (total carbonate carbon) = 5 mM and [SO4 2− ] + [H2 S(aq)] + [HS− ] = 1 mM (modified from Stumm and Morgan, 1996). Reproduced by permission of Wiley, New York

124

Reduction and Oxidation

The initial increase occurs because SO4 2− sorbed on variable charge clays and oxides is desorbed as the pH increases. The rate of subsequent reduction will be low if the pH remains below 5.5, the optimal range of pH for SO4 2− reducing bacteria being greater than this.

4.3.4 TRANSFORMATIONS OF PHOSPHORUS Phosphorus is often the most limiting nutrient in natural wetlands. Because of its association with soil Fe, its solubility changes markedly during reduction and oxidation. In general it is not itself reduced and remains in the +5 oxidation state, though production of phosphine gas (PH3 ; +3 oxidation state) at rates ≤ 6.5 ng m−2 h−1 has been reported in laboratory experiments with brackish and saline marsh soils (Devai and Delaune, 1995). Review articles on transformations of P in submerged soil include Patrick and Mahapatra (1968), Kirk et al. (1990a) and Willett (1991). Typically when a soil is submerged the concentrations of water- and acidsoluble P increase, reach a peak or plateau, and then decrease (Figures 4.11c and 4.13). For the soils shown in the figures, the peak P concentrations in solution were smallest for acid soils high in active Fe and greatest for a sandy soil low in Fe. The increases in acid-soluble P were greatest in an alkali soil low in active

Concentration of acid-soluble P in soil (mmol kg−1)

1.2

1.0

26

0.8

0.6

27 18

0.4

21 0.2

28 14

0.0

0

2 4 6 8 10 Time (weeks after submergence)

12

Figure 4.13 Changes following flooding in the concentration of P soluble in an acetate buffer at pH 2.7. Numbers next to curves identify soils; properties given in table in Figure 4.11 (modified from Ponnamperuma, 1985). Reproduced by permission of IRRI

Transformations of Nutrient Elements Accompanying Changes in Redox

125

Fe, intermediate in sandy loams high in organic C and low in active Fe, and least in acid clays high in active Fe. The increases in soluble P are particularly linked to the transformations of Fe and changes in pH. The main processes are: • reduction of Fe(III) compounds holding P on their surfaces and within their crystal lattices; • dissolution of Ca-P compounds in alkaline soils as the pH decreases and desorption of P held on variable-charge surfaces in acid soils as the pH increases; • displacement of sorbed P by organic anions and chelation of metal ions that would otherwise immobilize P; and • mineralization of organic P. Subsequent decreases in solubility may be due to re-sorption or precipitation on clays and oxides as soil conditions continue to change, and decomposition of organic anions chelating P or chelating Al and Fe with which it would otherwise react. Following submergence soils often release more P to solutions low in P but adsorb more P from solutions high in P. This apparent paradox can be explained by the reduction of Fe(III) oxides to poorly ordered gel-like Fe(II) compounds with large surface areas. Phosphorus solubilized in soil reduction is sorbed on the amorphous surfaces and desorbed when P is removed from the soil solution; but fresh P added to the soil is removed from solution by sorption onto the Fe(II) surfaces. Consequently many soils do not show significant increases in P solubility during flooding (Willett, 1991), and with prolonged flooding the P may become re-immobilized in less soluble forms. Gradual immobilization of P with prolonged anaerobicity is shown in Figure 4.14, which gives change in labile P over 3 years of double rice cropping of a perennially wet soil (B¨ucher, 2001). The labile P declines even in plots that received sufficient P fertilizer to more than off-set crop removals. Periodic drying of the soil during the fallow periods tended to increase labile P in the soil, but not in years when the soil remained anaerobic during the fallow (following the 1998 and 1999 wet season crops). The effect was greatest when tillage was delayed until the end of the fallow, resulting in more-reducing conditions in the soil, and it carried through to the succeeding rice crop. Supporting laboratory and greenhouse studies showed that changes in soil Fe with reduction and oxidation were responsible for the changes in P. Rapid drying and oxidation of the soil can also result in the P becoming very insoluble (Brandon and Mikkelsen, 1979; Willett, 1979; Sah et al., 1989; Huguenin-Elie et al., 2003). Re-oxidized Fe(II) compounds may be precipitated in poorly crystalline forms with large specific surface areas, on and in which P becomes immobilized. Hence upland crops grown in rotation with rice frequently suffer P deficiency even though crops on similar soils not used for rice grow healthily. The problem is in part also due to disruption of mycorrhizal networks during flooding (Ilag et al., 1987; Ellis, 1998; Miller, 2000).

NK plots

1999 DS

End of fallow 2 Dat Time

Fallow

1999 WS Fallow 2000 DS

63 Dat Harvest

21 Dat End of fallow

2 Dat Mid-fallow

63 Dat Harvest

42 Dat

21 Dat

End of fallow 2 Dat Mid-fallow

63 Dat Harvest

42 Dat

21 Dat

Mid-fallow

4 Dat

Resin-extractable P (mg kg−1 dry soil)

Figure 4.14 Changes in labile soil P (extractable with HCO3 − -form anion exchange resin) during 3 years of wetland rice cropping as affected by timing of tillage (early, late = start, end of fallow), incorporation of previous crop’s straw, and application of P (20 kg ha−1 in NPK plots). The overall P balances over 3 years were +37 and +7 kg P ha−1 in the NPK plots with and without straw, and −90 and −115 kg P ha−1 in the PK plots. DS, WS, dry, wet season; DAT, days after transplanting (B¨ucher, 2001). Reproduced by permission

0

5

10

0 15

Harvest

5

21 Dat

Early tillage, no straw

Late tillage, Late tillage, with straw no straw

Mid-fallow

10

42 Dat

Early tillage, with straw

Fallow

42 Dat

1998 WS

End of fallow 2 Dat

15

NPK plots

63 Dat

Fallow

21 Dat

1998 DS

42 Dat

20

Fallow

63 Dat Harvest

25

126

127

Oxidation of Reduced Soil

4.4 OXIDATION OF REDUCED SOIL When a spadeful of wet, anaerobic soil is brought to the surface and allowed to dry, air enters through drying cracks and the soil tends to become uniformly oxidized and turn a uniform brown. Whereas when oxidation occurs without drying—as, for example, near a root releasing O2 into wet soil—it is far less uniform and reddish-brown ferric oxide deposits form on and near the oxidizing source. The difference depends on the relative rates of movement of O2 into the soil and of ferrous iron and other reductants in the opposite direction, and the rates of reaction. Figure 4.15 indicates the range of rates of O2 consumption in different soils. Oxygen is consumed in oxidation of inorganic reductants, such as Fe(II), as well as in oxidation of organic matter by microbes. Bouldin (1968) and Howeler and Bouldin (1971) compared measured rates of O2 movement into anaerobic soil cores with the predictions of various models, and obtained the best fits with a model allowing for both microbial respiration and abiotic oxidation of mobile and immobile reductants; abiotic oxidation accounted for about half the O2 consumed. The kinetics of the abiotic reactions are complicated. They often depend on the adsorption of the reductant on solid surfaces as, for example, in

[O2]/[O2]initial

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42.3 39.6 33.6 18.9 26.9 5.3 16.5

40 Time (h)

60

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Figure 4.15 Rates of oxygen consumption by shaken suspensions of anaerobic soils. Points are measured data, lines are fits to two first-order rate equations. The apparent rate constant for the initial reaction is common to all soils; that for the main reaction varies 30-fold between the soils and is well correlated with [Fe2+ ] (Reddy et al., 1980). Reproduced by permission of Soil Sci. Soc. Am.

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the autocatalysis of Fe2+ oxidation by adsorption of Fe2+ on ferric hydroxide formed in the reaction. The adsorption is likely to be pH-dependent, a decrease in pH tending to decrease sorption and increase the concentration of Fe2+ in solution. Hence there may be complex interactions between the mobility of Fe2+ , the rate of oxidation, and pH changes caused by the reaction. Such interactions can produce banded distributions of iron around an O2 source, as found, for example, by Saleque & Kirk (1995) for the distribution of iron near rice roots and calculated by Kirk et al. (1990) with a model of the coupled diffusion and reaction of O2 , Fe2+ and acidity in soil. This is an example of the Liesegang phenomenon (Stern, 1954; Keller, 1980). 4.4.1 KINETICS OF Fe2+ OXIDATION Aqueous Solution The reaction between Fe2+ and O2 to form insoluble ferric hydroxide can be written 4Fe2+ + O2 + 10H2 O = 4Fe(OH)3 + 8H+ (4.36) Equation (4.36) shows that two H+ ions are produced for each mole of Fe2+ oxidized, i.e. the reaction is accompanied by acidification. In aqueous solution, the rate is found to be very sensitive to pH and at near neutral pH the reaction is accelerated 100-fold if the pH is raised by one unit. The following empirical rate law applies in the pH range 5–8 (Stumm and Lee, 1961; Wehrli, 1990) −d[Fe(II)]/dt = k[O2 ][OH− ]2 [Fe(II)]

(4.37)

where k ≈ 2 × 1014 mol3 dm−9 s−1 at 25 ◦ C and [Fe(II)] is the sum of the concentrations of Fe(II) species present—Fe2+ and its hydroxy complexes, FeOH+ and Fe(OH)2 , for which the formation constants are 10−4.5 mol−1 dm3 and 10−7.4 mol−2 dm6 , respectively. Therefore [Fe(II)] ≈ [Fe2+ ], but the pH dependence of the rate is due to the parallel oxidation of the three species. At [O2 ] = 0.28 mM (i.e. in equilibrium with atmospheric PO2 ), the half time for the reaction is 0.34 h at pH 7 and 143 days at pH 5. As discussed in Section 4.1, most redox reactions reach equilibrium only slowly if they are not catalysed. Oxidation of Fe2+ is catalysed by adsorption of Fe2+ onto Fe(OH)3 formed in the reaction, so Equation (4.36) only holds for the initial rates of reaction. Tamura et al. (1976) studied the oxidation of a solution of Fe2+ at different controlled pHs near neutral and with varying additions of Fe(OH)3 . The reaction obeyed the rate law −d[Fe2+ ]/dt = k[O2 ][OH− ]2 [Fe2+ ] + kS [O2 ][Fe2+ ]ad

(4.38)

where [Fe2+ ] is the concentration in solution, [Fe2+ ]ad the concentration adsorbed on Fe(OH)3 and kS the rate constant for oxidation of adsorbed Fe2+ (= 73 mol−1

Oxidation of Reduced Soil

129

dm3 s−1 , with all concentrations in mol dm−3 suspension). Adsorption is described by [Fe2+ ]ad /[Fe2+ ] = K[Fe(III)]/[H+ ] (4.38a) where [Fe(III)] is the concentration of Fe(OH)3 and K = 10−14.3 . Other metal oxidation reactions catalysed by sorption onto oxide surfaces are described in Section 7.3.

Soil A similar catalysis occurs on soil surfaces. Ahmad and Nye (1990) and Kirk and Solivas (1994) studied the kinetics of Fe2+ oxidation in soil suspensions by measuring changes in extractable Fe2+ in the whole soil and in solution during oxidation at constant [O2 ]. They found that 75 % of the initial Fe2+ was oxidized rapidly (t1/2 ≈ 2 h) and the remainder only very slowly (t1/2 ≈ 8 days). In the soils studied, the pH fell from near neutral to less than 5 over the course of the fast reaction. Measurements of the fast reaction at constant pH (Figure 4.16) showed that the oxidation of adsorbed Fe2+ was much faster than solution Fe2+ , and that the adsorbed Fe2+ was oxidized at a rate that was nearly independent of pH. Figure 4.16 shows that the overall rate of oxidation is more dependent on the concentration of sorbed Fe2+ ([Fe2+ ]S ) than the concentration in solution ([Fe2+ ]L ). Thus, although at pH 6.5 [Fe2+ ]L drops to one-tenth of its initial value within 1 h, d[Fe2+ ]/dt does not decrease to nearly the same extent. The figure also shows that oxidation of sorbed Fe2+ , indicated by the slopes of the lines in Figure 4.16(c), is surprisingly little influenced by pH and roughly follows first-order kinetics. The overall rate equation at constant pH is therefore −d[Fe2+ ]/dt = RkL [O2 ]L [Fe2+ ]L + kS [O2 ]L [Fe2+ ]S

(4.39)

where kL and kS are the rate constants for the reactions in the solution and solid and R the solution to solid ratio. Values of kS , calculated from the data in Figure 4.16(c) range from 0.19 mol−1 dm3 s−1 at pH 6.5 to 0.15 mol−1 dm3 s−1 at pH 5. Initially, most of the readily oxidizable Fe(II) is sorbed on the soil exchange complex. As the soil is oxidized, the Fe(OH)3 formed provides fresh sorption sites, as well as possibly blocking some of the original sites. Ahmad and Nye (1990) estimated the importance of the freshly formed Fe(OH)3 in sorbing Fe2+ compared with the original soil exchange complex, and found that the importance of the freshly formed Fe(OH)3 was much greater at higher pH, consistent with the expected greater pH-dependence of sorption on Fe(OH)3 surfaces. They also found that the oxidation of Fe2+ when sorbed on a mixture of soil exchange and Fe(OH)3 sites was much slower than on Fe(OH)3 in the absence of soil, described by Equations (4.38) and (4.38a).

130

Reduction and Oxidation (b) 100

(a) 100 90

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Figure 4.16 Changes in concentrations of Fe2+ in (a) whole soil, (b) soil solution and (c) soil solid during oxygenation of reduced soil suspensions at different pHs. [Fe2+ ]S was calculated from [Fe2+ ]–R[Fe2+ ]L (Kirk and Solivas, 1994). Reproduced by permission of Blackwell Publishing

A possible explanation is that access of O2 to the exchange or Fe(OH)3 sites where the Fe2+ is adsorbed is restricted. Possibly Fe(OH)3 is precipitated between clay lamellae at the oxidation sites and it partially blocks the original exchange sites. This mechanism would also imply a wide range of reaction rates between soils, with kS values ranging by perhaps an order of magnitude, as in Figure 4.15. In summary, the reaction can be represented by the following simplified scheme: kS

Fe2+ L   Fe2+ S −−−→ Fe(OH)3

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Oxidation of Reduced Soil

in which the exchange of Fe2+ between the solid and liquid is rapid and the overall rate depends only on the approximately first-order oxidation of sorbed Fe2+ . Although this rate is independent of pH, the distribution of Fe2+ between the solid and liquid is not and it is therefore necessary to allow for pH changes in calculating the rate.

4.4.2 SIMULTANEOUS DIFFUSION AND OXIDATION IN SOIL Kirk et al. (1990b) and Kirk and Solivas (1994) used the above understanding of oxidation kinetics to develop a model of soil oxygenation. The model allows for the diffusion of O2 into the soil, the diffusion of Fe2+ towards the oxidizing surface, the rate of formation and concentration profile of the Fe(OH)3 formed, and the diffusion by acid–base transfer of the acidity formed: H3 O+ diffusing away from the zone of acidification and HCO3 − (derived from CO2 ) towards it. The principal equations are as follows, expressed in planar geometry so as to be able to test the predictions against experimentally measured reactant profiles. (1) For the diffusion and reaction of O2 :   ∂ ∂[O2 ]L ∂[O2 ] = DLO θf − 14 S1 − S2 ∂t ∂x ∂x

(4.40)

where [O2 ] and [O2 ]L are the concentrations of O2 in the whole soil and solution, respectively, S1 is the rate of Fe2+ oxygenation, S2 is the rate of O2 consumption in microbial respiration, and the other parameters are as defined in Chapter 2. (2) For the diffusion and reaction of Fe2+ :   ∂[Fe2+ ] ∂ ∂[Fe2+ ]L = DLI θf − S1 (4.41) ∂t ∂x ∂x where [Fe2+ ] and [Fe2+ ]L are the concentrations of mobile Fe2+ in the whole soil and solution, respectively. (3) For the diffusion and reaction of soil acidity (Section 2.2)   ∂[HS] ∂ ∂pH − + =− 2.303θf (DLH [H3 O ]L + DLC [HCO3 ]L ) + 2S1 ∂t ∂x ∂x (4.42) where [HS] is the concentration of titratable soil acid. Applying Equation (4.39) to the structured-soil system, and ignoring the slow oxidation of Fe2+ in solution, gives S1 = ρkS [O2 ]L [Fe2+ ]S

(4.43)

0

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Figure 4.17 Profiles of (a) Fe(II), (b) Fe(III) and (c) pH in columns of reduced soil exposed to O2 at one end for different times. Points are experimentally measured; lines are predicted using the model described in the text with independently estimated parameter values (Kirk and Solivas, 1994). Reproduced by permission of Blackwell Publishing

[Fe(II)] (mmol kg−1)

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(a) 80

132

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Oxidation of Reduced Soil

where ρ is the soil bulk density. The rate of microbial O2 consumption is described by a Michaelis–Menten type equation: S2 = ρvmax [O2 ]L /(KM + [O2 ]L )

(4.44)

Kirk and Solivas (1994) measured profiles of Fe(II) and Fe(III) concentrations and pH in columns of reduced soil exposed to O2 at one end and compared the results with the predictions of the model using independently measured parameter values. The agreement between the observed and calculated results, shown in Figure 4.17, is good. The measured profiles of [Fe(II)] (Figure 4.17a) are scattered, probably because of the spatial variability inherent in soil reduction and the clustering of microbes around favourable microsites. There was much less scatter in the Fe(OH)3 and pH profiles which are the result of abiotic reactions. The zone of Fe(II) depletion extends further than the zone of Fe(OH)3 accumulation, as expected because Fe2+ is mobile but Fe(OH)3 is not. As a result, Fe(OH)3 accumulated in the oxidation zone close to the source of O2 , as shown in the inset in Figure 4.17(b). The good agreement between observed and calculated results and the fact that the model contains no arbitrary fitting parameters show that the important processes are well understood and that the model provides a satisfactory description of the system. It can therefore be used to explore other conditions through a sensitivity analysis (Figure 4.18). The figure shows that over the range of parameter values expected for submerged soils, substantial amounts of iron are transferred towards the O2 -exposed surface leading to a well-defined zone of Fe(OH)3 accumulation. For a given soil Fe(II) content, the accumulation is sensitive to the soil Fe2+ buffer power, the oxidation rate constant and the soil bulk density. The fall in pH in the oxidation zone is sensitive to the initial soil pH, the soil pH buffer power, and the partial pressure of CO2 . By contrast if the soil dries to any extent resulting in partially air-filled pores, the penetration of O2 increases dramatically: for an air-space of just 1 % of total 5.5 5.0

4 [Fe]

3 r 2 1 0 0.01

bHs

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6

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Multiple of standard parameter value

Figure 4.18 Sensitivity of the model used for the calculations in Figure 4.17 to its parameters: [Fe] is the initial concentration of mobile Fe2+ , bFe is the soil Fe2+ buffer power, bHS is the soil pH buffer power, kS is the Fe2+ oxidation rate constant and ρ is the soil bulk density. Standard values as for calculations in Figure 4.17

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porosity, Kirk et al. (1990b) calculated a four-fold increase in the penetration of O2 . There is then little accumulation of iron in the oxidation zone because the O2 diffuses so much faster than the Fe2+ that almost no Fe2+ can move towards the oxidation front before it is oxidized. The generation of acidity is correspondingly dispersed through the soil. These conclusions are discussed further in Chapter 6 in relation to the rhizospheres of wetland plants.

5 Biological Processes in the Soil and Floodwater

The soil and floodwater in wetlands are busy with life, and this drives the biogeochemistry. The remarkable long-term productivity of wetland rice systems depends on the fixation of carbon and nitrogen from the atmosphere by organisms in the soil and water, for which conditions are optimal. For example, in a long-term experiment at the International Rice Research Institute in the Philippines in which three crops of rice have been grown each year for 30 years without additions of fertilizers or manures and with complete removal of the rice straw, grain yields have remained nearly constant at 3 to 3.5 t ha−1 per crop or a total of 9 to 10 t ha−1 per year (Dobermann et al., 2000). No other intensive agricultural system without artificial inputs of nutrients comes close to this level of productivity. The accumulation of nitrogen by crops in this experiment has remained constant at about 50 kg N ha−1 per crop, largely due to additions from biological fixation in the floodwater and floodwater–soil interface (Ladha et al., 2000). Comparable rates of nitrogen fixation are attained in other fluxial wetland systems (Table 1.5). This chapter describes the important micro- and macrobiological processes in submerged soil and the overlying floodwater. Processes in plants and their rhizospheres are discussed in Chapter 6. The microbiological processes are discussed first and then the additional complexities caused by macrobiological processes and the particular ecology of the floodwater–soil system. 5.1 MICROBIOLOGICAL PROCESSES Descending through the soil from the floodwater there is a gradient of redox potential and a sequence of zones characterized by progressively more-reduced electron acceptors. Figure 5.1 shows hypothetical concentration profiles of redox species with depth. At sufficient depth the only electron acceptors are CO2 and H+ , and this zone is dominated by fermentation and methanogenesis. At intermediate depths there are successive zones of sulfate reduction, iron reduction, manganese reduction and denitrification. The microbes mediating these processes are largely prokaryotic; populations of fungi and other eukaryotes that are important in digesting organic matter under aerobic conditions are much less significant in anaerobic soil. The Biogeochemistry of Submerged Soils Guy Kirk  2004 John Wiley & Sons, Ltd ISBN: 0-470-86301-3

136

Biological Processes in the Soil and Floodwater Concentration O2 NO3−

NH4+

Depth

Mn2+ Fe2+

CH4

Figure 5.1 Indicative concentration profiles of redox species with depth in submerged soil

5.1.1 PROCESSES INVOLVED IN SEQUENTIAL REDUCTION The sequence of reactions by which organic matter is oxidized following submergence loosely follows the predictions of thermodynamics—i.e. in the order of decreasing free energy change—as described in Chapter 4. However, rates of reduction vary greatly between soils and there are complicated interactions between the microbial processes involved. Hence it is difficult to predict a priori, for example, how long after submergence a given soil will become methanogenic and what the rate of methane production will be. The free energy change for a particular redox reaction varies with pe, pH, and the concentrations of reductants and oxidants according to Equation (4.26):
 (Ox2 )(Red1 ) 0 0
G = −2.303RT n(pe1 − pe2 ) − log (Ox1 )(Red2 ) In this equation, the value of (Red) is a function of the nature of the reductant, its solubility, the crystallinity of solid phases containing it, effects of solubilizing agents, transport limitations, and other factors. Likewise the value of (Ox) is a function of various factors. As discussed in the previous chapter, most redox reactions are very slow and the prevailing conditions are therefore sensitive to catalysis. Three types of catalysis are involved: • Abiotic, for example by adsorption of reactants onto mineral surfaces, distinguished from biotic catalysis by the absence of a temperature optimum.

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137

Abiotic catalysis is generally less important than biotic but may be important. Examples are Mn(III,IV) and Fe(III) reduction by microbial metabolites, and Fe(II) oxidation which is catalysed by sorption onto soil particles. • Abiontic, involving free extracellular enzymes or solubilizing agents, enzymes bound to soil surfaces, enzymes within dead or non-proliferating cells, or enzymes associated with dead cell fragments. Extracellular enzymes are important in the initial stages of organic matter oxidation, in which polysaccharides and proteins are hydrolysed to soluble compounds that can be absorbed by microbial cells and further oxidized in biotic processes. • Above all, biotic catalysis by microbes is important. Biotic catalysis is complicated. Different communities of microbes deal with different parts of the sequence of processes degrading organic matter. Anaerobic decomposition involving organic electron acceptors (i.e. fermentation) generally occurs concurrently with respiration involving inorganic electron acceptors, and both produce intermediates that act as both oxidants and reductants. There are often syntrophic relationships between microbes in which the metabolisms of two or more organisms are linked and mutually beneficial. For example, in methanogenesis, oxidation of fatty and amino acids to H2 , CO2 and acetate is endergonic under standard conditions (i.e. PH2 = 1 atm), but a sufficiently small concentration of H2 is maintained locally by methanogens that utilize H2 (Conrad et al., 1986; Zehnder and Stumm, 1988; Krylova and Conrad, 1998). Likewise there are antagonisms between microbes, for example where one microbe maintains the concentration of a substrate below the threshold of a competitor, such as in the inhibition of methanogens by SO4 2− reducers competing for H2 (Achtnich et al., 1995). There are also specific inhibitory effects through particular metabolites, such as in the inhibition of methanogens by denitrifiers (Roy and Conrad, 1999). Hence the initial microbial populations, growth rates and community structures may all be important in the overall course of reduction. The main pathways of organic matter oxidation in anaerobic soil are as follows. In the initial stages, fermenting bacteria excrete extracellular enzymes that hydrolyse polysaccharides and proteins to soluble compounds. These may then be absorbed by microbial cells and converted to alcohols, fatty acids and H2 . If inorganic electron acceptors are available, the alcohols and fatty acids are completely oxidized to CO2 in sequential reduction reactions. If inorganic electron acceptors are not available—whether because they have been exhausted or because they are otherwise inaccessible—communities of fermenting bacteria decompose the alcohols and fatty acids to acetate, H2 and CO2 . These then serve as substrates for methanogenic archaea. Sugar monomers may also be directly converted to acetate by homacetogenic bacteria. Likewise proteins are hydrolysed to amino acids by extracellular enzymes, and the amino acids then ultimately oxidized to acetate, H2 , NH4 + and CO2 . Figure 5.2 shows the sequential reduction of inorganic electron acceptors and production of CO2 , CH4 and intermediaries in two representative soils from a

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Figure 5.2 Sequential reduction of electron acceptors and accumulation of CO2 and CH4 in two rice soils. The soils were submerged and incubated at 30 ◦ C in sealed bottles (Yao et al., 1999). Reproduced with kind permission of Kluwer Academic Publishers

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sample of 16 rice soils studied by Yao et al. (1999). Three distinct phases can be distinguished: (1) an initial reduction phase lasting 19–75 days in the 16 soils, during which most of the inorganic electron acceptors are depleted and the rate of CO2 production, given by the slope of the CO2 accumulation line in the figure, is maximal; (2) a methanogenic phase starting after 2–87 days and lasting 38–68 days, during which the rate of CH4 production is maximal; and (3) a pseudo steady-state phase during which rates of CH4 and CO2 production and concentrations of H2 and acetate are roughly constant. The line of H2 accumulation in the figure is informative because H2 is turned over rapidly as it is produced in fermentation and consumed in Fe(III) and SO4 2− reduction and methanogenesis. Hence there are peaks in H2 pressure in the early stages of Fe(III) and SO4 2− reduction and again at the transition from Fe(III) and SO4 2− reduction to methanogenesis. Because consumption tends to increase with the concentration of H2 but production is independent of it, there is a point at which consumption equals production, characterized by H2 concentrations in the nM range. Acetate is also produced in fermentation and consumed in methanogenesis, but its turnover is slower and larger concentrations build up. Figure 5.3 compares the quantities of electrons consumed in reduction of inorganic electron acceptors and methanogenesis in the 16 soils with those donated in the oxidation of organic matter to CO2 . At the end of the initial reduction phase, the former exceeded the latter in nine of the soils, probably in part because CO2 was precipitated in carbonates and in part because some of the organic carbon was converted to forms more oxidized than that in CO2 . However by the end of the incubation the electron balance was zero in all but three of the soils. At the end of the incubation, only 6–17 % of the organic carbon in the soils was released as gases: 61–100 % as CO2 , <0.1–35 % as CH4 and <5 % as non-methane hydrocarbons. Most of the CO2 was produced in Fe(III) reduction during the initial reduction phase. Yao and Conrad (1999) calculated the free energy changes in methanogenesis during the three phases above. During the initial reduction and while redox potentials were still positive (360–510 mV), acetate and H2 concentrations allowed exergonic methanogenesis with
G < −30 kJ mol−1 CH4 . After about 4 days CH4 accumulation slowed and ceased in most soils. At this time CH4 partial pressures were still small (about 10–100 Pa), but H2 depleted by Fe or S reduction and
G increased to −10 kJ mol−1 CH4 , indicating that methanogenesis was not possible. At the end of Fe and S reduction,
G decreased to < − 25 kJ mol−1 CH4 and CH4 production resumed. Vigorous CH4 production continued until the pseudo steady state was reached. In a few soils the initial CH4 production was not interrupted by an intermediate increase of
G so CH4 was released throughout the experiment, resulting in the highest maximum CH4 production rates.

140

Biological Processes in the Soil and Floodwater No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

pH 7.7 6.0 5.1 7.4 6.3 6.7 7.6 5.9 5.1 6.2 6.8 6.0 6.7 5.8 6.1 6.0

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10.4 16.8 18.5 13.4 11.5 13.5 9.5 19.7 16.5 21.4 26.2 15.1 10.7 13.9 8.1 15.5

79.5 582.7 713.9 376.5 424.3 477.3 265.4 818.7 575.2 331.1 319.0 200.4 118.0 272.3 405.9 422.0

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Figure 5.3 Calculated electron balance between CO2 produced and electron acceptors reduced during anaerobic incubation of 16 rice soils (a) after the initial reduction phase and (b) after 120 days (Yao et al., 1999). Reproduced with kind permission of Kluwer Academic Publishers

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Microbiological Processes

5.1.2 NITRATE REDUCTION Figure 4.1 shows that NO3 − is the stable form of nitrogen over the usual range of pe + pH in aerobic environments. The fact that most of the N2 in the atmosphere has not been converted to NO3 − therefore indicates that the biological mediation of this conversion in both directions is inefficient. Hence NO3 − reduction to N2 occurs by indirect mechanisms involving intermediaries. Dissimilatory reduction of NO3 − (i.e. where the nitrogen oxide serves as an electron acceptor for the cell’s metabolism but the N reduced is not used by the microbes involved) potentially occurs by two processes: denitrification, NO3 − −−−→ NO2 − −−−→ NO −−−→ N2 O −−−→ N2 and reduction to NH4 + , NO3 − −−−→ NO2 − −−−→ NH4 + Assimilatory NO3 − reduction might also occur. But because concentrations of NH4 + and organic N are in general large in anaerobic environments, it is suppressed and insignificant. The literature on NO3 − reduction is reviewed by Tiedje (1988). In most submerged soils dissimilatory reduction to NH4 + is much less important than denitrification because reduction to NH4 + is a strictly anaerobic process and any NO3 − entering the soil or formed in oxic zones is denitrified before it reaches a sufficiently reduced environment (Buresh and Patrick, 1981). The importance of dissimilatory reduction depends on the ratio of available carbon to electron acceptors. Reduction to NH4 + produces more electrons per unit NO3 − reduced (8 compared with 5), but less energy. It therefore dominates in continuously anaerobic environments with a high ratio of available carbon to electron acceptors, such as the rumen, whereas denitrification dominates in environments with a low ratio of available carbon to electron acceptors, such as in most submerged soils and in anaerobic microsites in otherwise aerobic soils. Buresh and Patrick (1981) found 15 % of NO3 − reduction was to NH4 + in unplanted submerged sediment, and Buresh et al. (1989) found the equivalent figure for rice soils was less than 5 %. Carbon acts as the electron donor for denitrification. The availability of carbon often limits denitrification in anaerobic microsites in non-submerged soils. As a result, the reaction does not go to completion and the intermediaries NO2 − and N2 O accumulate. Completion of the reaction may also be hindered by low pH. But under uniformly anaerobic conditions NO3 − as electron acceptor is more likely to be limiting than carbon as electron donor because NO3 − is not regenerated. Therefore the rate of denitrification is limited by the supply of NO3 − rather than carbon, and proceeds almost completely to N2 .

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Biological Processes in the Soil and Floodwater

These general features of NO3 − reduction in submerged rice soils are born out by field observations. Buresh et al. (1993b) found that from 60 to 75 % of 15 N-labelled NO3 − applied on the surface of flooded ricefields was lost by denitrification over 2–3 weeks, as measured by the 15 N not recovered in the soil, floodwater and plants. The recovery of (N2 + N2 O)-15 N in chambers placed over the floodwater was less than the estimated denitrification loss because gas bubbles became entrapped in the soil. More N2 + N2 O was recovered when the chambers were placed over the rice plants showing that some of the gas escaped through the plants. The 15 NO3 − not lost by denitrification was presumed to have been immobilized following absorption by the plants and algae; denitrification losses increased when algicides were applied.

5.1.3 IRON AND MANGANESE REDUCTION Iron reduction has been studied more intensively than manganese because of the greater abundance of iron in the natural environment. However, because of their broadly similar chemistries, the processes involved are probably similar. Until recently it was thought that microbes were not directly involved in Fe and Mn reduction but only indirectly through abiotic reactions involving end products of their metabolism. Common metabolites such as H2 S and various organic acids can reduce Mn and Fe chemically, especially at low pH. However, it is now clear, at least for Fe, that the reduction is directly linked to microbial metabolism (Lovley, 1997; Straub et al., 2001). The main obstacle in establishing this was the insolubility of Fe and Mn oxides, which prevents easy absorption of Fe and Mn into microbial cells so that their reduction can be linked directly to oxidation of organic compounds via cellular electron transfer systems. It is now established that electrons are transferred out of microbial cells to extracellular Fe(III) using cytochromes and quinones or similar compounds, and that some species of Fe reducers can solubilize Fe(III) in oxides by excreting chelating agents. Nevin and Lovley (2002) have shown that microbes can reduce Fe(III) in iron oxide without being in direct contact with the oxide. They incorporated poorly crystalline iron oxide into porous alginate beads and incubated the beads with cultures of the Fe reducing bacterium Geothrix fermentans, which is found in the Fe(III) reduction zone of anoxic sediments. Ferric iron from the solid oxide was reduced and the concentration of dissolved Fe(III) in the solution increased to as much as 250 mM. Since the pores in the beads were too fine for entry of the bacteria, and the amount of Fe(III) reduced was far greater than the amount in oxides on exposed surfaces of the beads, this demonstrates that extracellular excretions from the bacteria both solubilized Fe(III) and shuttled electrons to it. Further experiments in which Fe(III) in iron oxides was reduced by filtered suspensions of cultures of G. fermentans confirmed that the electron shuttling was extracellular. In contrast, the Fe reducer Geobacter metallireductans is not

Microbiological Processes

143

capable or reducing Fe(III) without direct contact with the oxide. Ecological interactions between these and other species of Fe reducers in natural anoxic sediments reflect these and other mechanisms (Snoeyenbos-West et al., 2000; Stein et al., 2001). Demonstrating that Mn(III,IV) is reduced microbially is complicated by the rapid abiotic reduction of Mn(III,IV) by Fe2+ and other reductants. Lovley and Goodwin (1987) obtained indirect evidence for microbial mediation of Mn(III,IV) reduction in experiments in which they follows the consumption of H2 by anoxic sediment. Addition of MnO2 caused H2 to decrease to smaller concentrations than possible under Fe reducing conditions, suggesting that Mn reduction was out competing Fe reduction for H2 in the same way that Fe reduction out competes SO4 2− reduction and methanogenesis.

5.1.4 SULFATE REDUCTION Widdel (1988) gives a comprehensive review of the microbiology and ecology of sulfate reduction in natural environments. Dissimilatory reduction of SO4 2− is carried out by certain heterotrophic bacteria, which use SO4 2− as the terminal electron acceptor in their respiration. The main genera are Desulfovibrio, Desulfomaculum and Desulfobacter. The bacteria are obligate anaerobes, and being heterotrophs their activity is sensitive to the supply of carbon. Various organic substrates are used with some preferences among species: lactate is the preferred substrate for many species but there are also acetate oxidizing sulfate reducers. Lactate oxidizers in particular will also grow well on H2 . Competition for H2 and acetate results in inhibition of methanogens by sulfate reducers. Figure 5.2 shows that SO4 2− reduction commences well before Fe(III) reduction is complete, in spite of the lower redox potential required. The onset of SO4 2− reduction coincides with a rapid decline in concentrations of H2 and acetate, for which the sulfate reducers compete with Fe(III) reducers. The overlap between Fe and SO4 2− reduction is explained by clustering of sulfate reducers in microsites within which they generate more strongly reducing conditions than in the surrounding soil. They are able to do this because the SO4 2− and organic substrates on which they subsist are mobile in the soil solution and can therefore diffuse to the microsites where the colonies of sulfate reducers develop. Iron reducers cannot do this because they depend on access to immobile Fe(III) in the soil solid. Hence the horizontal distribution of sulfate reducers in submerged soils is generally found to be contagious (Watanabe and Furusaka, 1980). The degree of clustering increases as the mean number of cells present increases, confirming that the clustering is self-induced. The distribution with depth follows the profile of redox potential with a peak at an intermediate depth, below the zone dominated by Fe reduction and above the zone of methanogenesis. Except in some coastal soils, histosols, acid sulfate soils, and soils artificially amended with sulfate, the total amount of sulfate present is usually small in

144

Biological Processes in the Soil and Floodwater

comparison with the amount of reducible Fe. Hence SO4 2− reduction generally does not exert a dominant influence on the soil ecology. Artificial amendment with sulfate has been proposed as a means of ameliorating methane emissions (Chapter 8).

5.1.5 METHANOGENESIS While sufficient inorganic oxidants are present, CO2 is the main end product of organic matter decomposition. But after the inorganic oxidants are used up, methanogenesis is obligatory and the proportion of CH4 in the respiratory gases increases. Methane is produced mainly by disproportionation of acetate to CO2 and CH4 or by reduction of CO2 with H2 (see review articles by Conrad, 1989; Kiene, 1991; Zinder, 1993). The relative proportions of the two pathways and the resulting ratio of CH4 to CO2 produced depend on the balance of electrons among the reactants and products. Hence for organic matter whose average oxidation state is zero—for example carbohydrates, which have an average composition CH2 O—complete oxidation produces equal quantities of CH4 and CO2 . But if the organic products are more oxidized or more reduced than the original compounds, the ratio of CH4 to CO2 produced will be less or greater than one. Yao and Conrad (2000) have used this principle to analyse organic matter turnover in methanogenic soils. Because the rate of turnover is slow, and the corresponding changes in the organic matter small and therefore difficult to measure accurately, this approach is potentially very useful. Yao and Conrad’s method is now outlined. Once the inorganic oxidants have been used up and methanogenesis established, the soil enters a pseudo steady state in which the gross composition of the organic matter is little altered by decomposition and the rates of CO2 and CH4 production are roughly constant (cf. Figure 5.2). A simple model of the electron balance during the pseudo steady state is as follows. Decomposition of soil organic matter (SOM) from SOM0 to SOM1 plus CO2 and CH4 occurs through the following reactions: SOM0 + aH2 O −−−→ SOM1 + bCH3 COOH + cH2 + dCO2

(5.1)

CH3 COOH −−−→ CH4 + CO2

(5.1a)

and 4H2 + CO2 −−−→ CH4 + 2H2 O

(5.1b)

where a, b, c and d are coefficients, normalized for the flux of C (i.e.
C = 2b + d = 1). In the pseudo steady state, Reaction (5.1) is rate limiting and CO2 abundant. It follows that the net rates of CH4 and CO2 production are VCH4 = (b + c/4)V and VCO2 = (b − c/4 + d)V

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Microbiological Processes

where V is the rate of Reaction (5.1), and the ratio of these rates is φ=

VCH4 4b + c = VCO2 4b − c + 4d

(5.2)

Similarly the fractions of CH4 produced in Reactions (5.1b) and (5.1a) are RH2 =

c 4b and RAc = 1 − RH2 = 4b + c 4b + c

and the ratio of these fractions is ψ=

RH2 c = RAc 4b

(5.3)

If the composition of SOM0 is SOM0 = xC + yH + zO then SOM1 = (x − 2b − d)C + (y + 2a − 4b − 2c)H + (z + a − 2b − 2d)O Taking O to be in oxidation state −2, H in state +1 and ignoring all other SOM elements, the charges on SOM0 C and SOM1 C are therefore Z0 = 2z − y and Z1 = 2z − y + 2c − 4d and the change in total SOM C charge per mole of C consumed,
Z, is
Z = Z1 − Z0 = 2c − 4d

(5.4)

These equations can be combined to give
Z in terms of φ(= VCH4 /VCO2 ):
Z = 4

φ−1 φ+1

(5.5)

This relation is plotted in Figure 5.4(a). Negative values of
Z indicate a deficit of electrons in the gaseous products of SOM decomposition and that SOM1 is more reduced than SOM0 ; positive values indicate a surplus of electrons in the gaseous products and that SOM1 is more oxidized than SOM0 . Substituting for c from Equation (5.3) and for d from d = 1 − 2b in Equation (5.2) gives the following expression for b in terms of φ and ψ: b=

φ (1 + φ)(1 + ψ)

(5.6)

Here b is the number of moles of acetate produced per mole of SOM carbon decomposed. From Equation (5.3), the number moles of H2 produced is c = 4bψ =

4φψ (1 + φ)(1 + ψ)

(5.7)

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Biological Processes in the Soil and Floodwater

0 −1 −2 −3 −4 0.0

0.4

0.8

1.2

1.6

(c)

0.5 0.4 0.3

y = 0 0.2 0.4 0.6 0.8 1

0.2 0.1 0.0 0.0

0.4

0.8

1.2

1.2 mol H2 per mol C (c )

(b) 1 mol acetate per mol C (b )

Charge transferred per mol of C (∆Z)

(a)

1.6

y=1

1.0

0.8

0.8

0.6 0.4 0.2

0.6 0.4 0.2 0.0 0.0

0.4

0.8

1.2

1.6

CH4 produced/CO2 produced (f)

Figure 5.4 Calculated (a) electron balance (Equation 5.5), (b) production of acetate (Equation 5.6) and (c) production of H2 (Equation 5.7) as functions of the ratio of CH4 to CO2 produced (φ) during anaerobic decomposition of soil organic matter. Numbers on curves are ratios of CH4 produced from H2 + CO2 to CH4 produced from acetate (ψ)

These relations are plotted in Figure 5.4(b) and (c), showing how the amounts of H2 and acetate produced per mole of C consumed vary with the ratio of CH4 to CO2 produced. Finally, from Equation (5.4) the rate of change in Z is dZ/dt = (2c − 4d)V1 = 2VH2 − 4(VCO2 − VAc + VH2 /4)

(5.8)

where VAc = (1 − RH2 )VCH4 and VH2 = 4RH2 VCH4 , giving dZ/dt = 4(VCH4 − VCO2 )

(5.9)

Yao and Conrad (2000) measured rates of CO2 and CH4 production (VCH4 and VCO2 ) and the proportion of CH4 produced from H2 + CO2 (RH2 ) in a range of submerged rice soils under pseudo steady-state conditions, and calculated the electron balance using Equation (5.9). The results are shown in Figure 5.5. The figure shows that in the majority of the soils there was a net deficit of electrons, indicating that the SOM became more reduced during decomposition. The ratio φ = VCH4 /VCO2 varied from 0.39 to 0.96 in six of the soils, and from 1.24 to 1.36 in the remaining two. Also a fairly small proportion of the CH4 was produced from reduction of CO2 with H2 ; most was produced from disproportionation of acetate. The ratio ψ = RH2 /RAc varied from 0.27 to 0.54. There are various possible explanations for the decrease in oxidation state of the SOM carbon in most of the soils. One is that the SOM comprises different pools of organic matter with carbon in different oxidation states, and Z decreases as a result of preferential oxidation of more-oxidized pools of SOM, leaving a greater proportion of the more-reduced forms in the residue. The more oxidized SOM would include compounds in the original SOM and also compounds generated in the course of reduction, for example as a result of chemical oxidation by Fe(III) and other metal oxides. Alternatively, part of the organic matter could

147

Microbiological Processes CO2 consumed CH4 produced CH4 produced CO2 produced from H2 + CO2 from acetate from acetate by H2

CO2 produced from SOM

Soil No. 16 15 12 8 6 5 3 Net surplus or deficit of e−

2 −3

−2

−1

e− deficit (µmol g−1 day−1)

0

0

1 2 e− surplus (µmol g−1 day−1)

3

Figure 5.5 Electron balances during anoxic decomposition of soil organic matter to CH4 and CO2 in eight rice soils. Soil properties given in Figure 5.3 (Yao and Conrad, 2000). Reproduced by permission of Blackwell publishing

have been acting as an electron acceptor, itself becoming reduced and allowing more of the SOM to be oxidized to CO2 rather than reduced to CH4 . The latter mechanism is consistent with the observed small proportion of CH4 produced from H2 and CO2 because an electron sink in addition to CO2 would suppress the concentration of H2 . The results imply that the average oxidation state of SOM carbon should decrease under continuous reducing conditions. This agrees with the observed long-term changes in the composition of SOM and accumulation of phenolic compounds with prolonged flooding of rice soils (Chapter 3). However the field situation differs from Yao and Conrad’s experiments in that the soil receives continuing inputs of living organic matter from growing plants or other sources, with mean oxidation state zero, and the fields are periodically drained and oxidized for some part of the year. Therefore general conclusions cannot be drawn. 5.1.6 AEROBIC PROCESSES The floodwater and uppermost part of the soil are oxygenated by photosynthetic organisms, and the rhizosphere is oxygenated by leakage of O2 from plant roots.

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Biological Processes in the Soil and Floodwater

The penetration of the O2 into the soil depends on its rate of consumption in aerobic processes and its rate of transport by mass flow and diffusion, and in the floodwater–soil interface, mixing by burrowing invertebrates. Various aerobic processes take place in these oxygenated zones. Nitrification Depending on the population and growth rates of nitrifying bacteria, the meeting of O2 from the floodwater or roots and NH4 + from the anaerobic bulk soil will lead to production of NO3 − . Subsequent movement of the NO3 − into the anaerobic soil will lead to rapid loss by denitrification. The importance of this process will be sensitive to the various factors affecting oxygenation of the interface and transport through the soil. Measurements of denitrification in ricefields have in fact failed to find very high rates of loss (De Datta and Buresh, 1989). An important point is that conditions favouring high rates of oxygenation of the floodwater–soil interface through algal activity during the day will also favour volatilization of NH3 because of the concomitant increase in floodwater pH (Section 3.2). Therefore NH3 volatilization may out-compete nitrifiers for NH4 + in the soil surface. Figure 5.6 shows profiles of NO3 − concentration measured with microsensors in soil cores taken from ricefields by Revsbech and co-workers (Liesack et al., 2000). During illumination of the cores, O2 generated in the floodwater penetrated to a depth of 2–3 mm and a clear peak of NO3 − was apparent, produced in nitrification. However in the dark, entry of O2 from the floodwater diminished, nitrification ceased, and NO3 − moving into the soil from the floodwater was rapidly consumed in denitrification. The rates of nitrification were slow and all fields investigated had similar rates. Nitrification in the rice rhizosphere may be more important (Chapter 6). 2 Dark Light

Depth (mm)

1 0 −1 −2 −3

0

1 2 3 Concentration of NO3− (µM)

4

Figure 5.6 Concentration profiles of NO3 − in soil cores from a ricefield, illuminated and not illuminated (Liesack et al., 2000). Reproduced with permission from Elsevier Science

149

Microbiological Processes

CH4 Oxidation Again depending on the population and growth rates of methane oxidizing bacteria, methane diffusing in from the anaerobic soil may be oxidized in the floodwater–soil interface or oxygenated rhizosphere. Figure 5.7 shows profiles of O2 and CH4 measured with microelectrodes in the same way as for Figure 5.6. The rate of oxidation is again sensitive to diurnal changes in oxygenation by algae in the floodwater. But nonetheless, averaged over the day, of the order of 80 % of CH4 diffusing towards the floodwater will be oxidized (Conrad and Frenzel, 2002). Oxidation of CH4 in the rhizosphere is rather less efficient (10–30 %) because of the greater competition with alternative O2 sinks (Section 8.1.3). Because diffusion of CH4 through the soil to the floodwater is slow, and oxidation in the (a) illuminated 4 2 0 −2 −4

oxygen methane

−6 Depth (mm)

−8 −10 (b) not illuminated 4 2 0 −2 −4 −6 −8 −10

0

200

0

50

400 600 800 1000 1200 1400 Concentration of O2 (µM) 100 150 200 250 Concentration of CH4 (µM)

300

Figure 5.7 Concentration profiles of O2 and CH4 in soil cores from a ricefield (a) illuminated and (b) not illuminated (Damgaard et al., 1998). Reproduced by permission of American Society for Microbiology

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Biological Processes in the Soil and Floodwater

floodwater-soil interface efficient, diffusion through the floodwater is a much less important conduit for CH4 emission from ricefields than escape by ebullition or by passage through the plant (Section 8.1).

5.2 MACROBIOLOGICAL PROCESSES Superimposed on the microbiological processes are processes driven by the macroflora and -fauna in the soil and floodwater. These are responsible for the net primary production of the system, which ultimately drives the biogeochemistry. Organic matter produced by photosynthetic organisms is the source of energy and nutrients for grazing organisms, populations of which can be very large. Many of the invertebrate species found in wetlands create burrows through the soil which provide conduits for the movement of oxygen, nutrients and carbon. Hence rates of interchange between aerobic and anaerobic zones can be much greater than expected from simple physical transport processes. For discussion of the ecology of wetland soils and water see Mitsch and Gosselink (2000) for natural wetlands, Roger (1996) for wetland ricefields, and Catling (1992) for the additional niceties of deepwater ricefields.

5.2.1 NET PRIMARY PRODUCTION AND DECOMPOSITION The net primary production is often far greater in wetlands than in drylands in similar climate zones (Chapter 1). In a given climate, NPP depends on hydrological conditions—the frequency and duration of submergence and the rate of water flow—and on the concentrations of nutrients and toxins. Hydrological conditions regulate primary producers and decomposers in the soil by limiting the availability of oxygen for aerobic respiration and by affecting supplies of nutrients and toxins. In general the frequency of inundation is more important than the duration, and the more open the system the greater the NPP because periodic inundation brings in oxygen and nutrient-rich sediment and flushes out toxins. Likewise decomposition is faster under a fluctuating water regime and the accumulation of organic matter is greatest in wetlands with prolonged inundation and stagnant water (Moore and Bellamy, 1974; Mitsch and Gosselink, 2000). Maximum productivity occurs under intermediate periods of inundation. In many wetlands NPP and decomposition are most limited by the availability of nutrients, especially N and P. For example, in a review of published data on nutrient limitations in North American bogs, fens, marshes and swamps, Bedford et al. (1999) found that a large proportion of the wetlands were either P limited or limited by both N and P, especially those occurring on organic soils. Only marshes had N:P ratios in both live tissues and soils that consistently indicated N limitation, though the soil data suggested that the majority of swamps were also

Macrobiological Processes

151

N limited. Nutrient availability also affects the composition of plant communities: species richness and the presence of rare species often decline as nutrient availability increases beyond some threshold (Bedford et al., 1999). In addition to the inflow of nutrients with the water and sediment, there are complicated interactions between hydrology and nutrient availability that affect productivity and decomposition. Transformations of N and P under anaerobic conditions are discussed in Section 4.3. 5.2.2 THE FLOODWATER–SOIL SYSTEM Five zones can be distinguished: the floodwater standing on the soil per se, the floodwater–soil interface, the anaerobic bulk soil, the rhizosphere, and the subsoil. These are to some extent continuous with each other, and they are certainly linked so that the function of the system as a whole is greater than the sum of its parts. But they provide convenient boundaries for discussion. The floodwater is photic and aerobic. It contains photosynthetic and chemosynthetic producers of fixed carbon–bacteria, algae and aquatic weeds—and invertebrate and vertebrate consumers that graze on the producers. The community of producers and consumers provides organic matter to the underlying soil and recycles inorganic nutrients. The floodwater–soil interface is also photic and aerobic. The boundary with the overlying water is diffuse and the bulk density increases from near zero to 1 g cm−3 or more in the underlying anaerobic soil. The depth to the underlying soil varies from a few mm to a few cm, depending on the aeration of the floodwater, reducing conditions in the soil, rates of percolation, and mixing by invertebrates. Nitrate, Mn(III,IV), Fe(III), SO4 2− and CO2 are stable and algae and aerobic bacteria predominate. In the early stages of land preparation for rice, algae develop on the wet soil surface and support populations of grazers. As organic matter accumulates during the crop, populations of benthic filters and deposit feeders develop. The activities of the invertebrates affect nutrient cycling both directly through their excretions and indirectly by moving soil particles and organic matter. The anaerobic soil is non-photic and reduction processes predominate. The value of pe + pH is generally below the range at which Fe(III) is reduced, unless organic substrates are limiting or there are large concentrations of more oxidized reductants such as Mn(III,IV). Microbial activity is concentrated within waterstable aggregates containing organic matter, and produces NH4 + , S2− , organic acids and CH4 . Decomposing organic matter in the anaerobic soil sustains populations of aquatic oligochaete worms and chironomid larvae. The subsoil at greater depths may be aerobic in well-drained soils with a perched water table owing to an impermeable layer—such as the traffic pan in ricefields; or anaerobic in soils that are poorly drained throughout. It may provide significant quantities of nutrients to plants growing in the soil if their roots can reach them.

152

Biological Processes in the Soil and Floodwater

Plants shade the floodwater and soil surface, and lower the temperature and concentration of CO2 above the floodwater during the day. These effects increase as the plant canopy develops during a growing season, with corresponding changes in the ecology of the soil and water. Plants also act as substrate for epiphytic growths—for example for nitrogen-fixing cyanobacteria—and they provide mechanical support for animals, for example allowing animals to escape high temperatures in the floodwater during the day. Plant roots support a partially oxic rhizosphere. The rhizosphere is non-photic, but root-derived carbon provides substrate for microbial growth. The thickness of the oxic rhizosphere is only a few tenths of a millimetre, but because the roots can occupy a large part of the anaerobic soil layer, a significant proportion of it may be oxic (Chapter 6).

5.2.3 FLOODWATER PROPERTIES Temperature and Radiation Under submerged conditions, temperatures in the soil and water depend on the depth of the water and on the density of the plant canopy, as well as on meteorological conditions. The water transmits incident short-wave radiation to the soil but it also insulates the soil against emission of long wave radiation. The full plant canopy transmits 90 % of the short-wave infrared radiation (i.e. half the total short-wave). Hence there is a ‘greenhouse’ effect and consequently the soil and water temperatures tend to be higher than the air temperature. Evaporative cooling reduces the surface water temperature and drives convection currents, so the water tends to be well mixed. Figure 5.8 shows temperatures in the air, water and soil in a tropical ricefield over a year. For the conditions in Figure 5.8, the water and the top 2 cm of soil were 2–5 ◦ C warmer than the maximum air temperatures and they continued to rise for some weeks after the annual peak air temperature. The 2–10 cm layer of soil is 2–3 ◦ C cooler than the top 0–2 cm. Because of the greenhouse effect, diurnal changes in soil and floodwater temperatures tend to be smaller than the changes in air temperature. However the effects depend on the depth of the floodwater and its source. Under continuous flowing irrigation, water temperatures tend to be lower than air temperatures in hot areas and vice versa in cool areas. Sediment load and algal cover also have effects. Incident radiation varies with season, cloud cover and latitude, and the fraction reaching the floodwater varies with the density of the plant canopy and with the presence of floating macrophytes and plankton and floodwater turbidity. Algae use different wavelengths of light to green plants, and this may in part compensate for shading by plants. Nonetheless the intensity of photosynthetically active radiation at the floodwater surface becomes deficient at some point during the season. Figure 5.9 shows the decline in light intensity at the floodwater surface as the canopy of a rice crop develops. Within 6 weeks of transplanting,

153

Macrobiological Processes

Temperature ( °C)

40 Air Water Soil 0-2 cm Soil 2-10 cm

35

30

Rice crop 25

0

100

Rice crop 200

300

Day of year

Figure 5.8 Temperatures in ricefields over a year, IRRI, Laguna, Philippines. Values are means over a month; air temperature is maximum; water and soil temperatures were taken at 1400 h (Roger, 1996). Reproduced by permission of IRRI

Fractional light penetration

1.0 0.8 0.6 0.4 0.2 0.0

0

20 40 60 80 Time after transplanting (days)

100

Figure 5.9 Decrease in light penetration to the floodwater as a typical rice crop develops (J. Sheehy, IRRI, unpublished data)

only 10 % of the incident photosynthetically active radiation reaches the floodwater. Similar changes occur in natural wetlands as plants become established following inundation. Dissolved O2 and CO2 and pH Oxygen is produced by photosynthetic organisms in the water and consumed in respiration and other oxidative processes. Often the concentration varies from super-saturation during the day to near zero at night. Because the partial pressures

154

Biological Processes in the Soil and Floodwater

of CO2 and O2 are inversely related, the pH and O2 concentration in the floodwater tend to be positively correlated. Diurnal variations of floodwater CO2 and pH are discussed in Section 3.3.

Inorganic Nutrients The supply of nutrients in the floodwater depends on the composition of the water arriving in the field and on the nutrient status and transport properties of the underlying soil. As discussed above, P is most often the most limiting nutrient in natural wetlands and also in ricefields (Roger, 1996). Concentrations in irrigation and flood waters are generally small (≤10 µM) and diffusion from the soil into the floodwater is slow, particularly if P is adsorbed to a large extent on iron oxides in the oxic floodwater–soil interface. The effect of turbation by animals burrowing into the soil may therefore be important. The calculations in Chapter 2 show that the flux of P into the floodwater increases several fold with realistic tubificid populations and soil parameters.

5.2.4 FLOODWATER FLORA The photosynthetic aquatic biomass comprises cyanobacteria (formerly called blue-green algae), planktonic, filamentous and macrophytic algae, and vascular macrophytes. The net productivity of the floodwater depends on the level of primary production by the photosynthetic biomass versus its consumption by grazing animals, particularly cladocerans, copepods, ostracods, insect larvae and molluscs. Their role will change as the canopy develops and at a leaf area index of about 6–7 there will be no more photosynthetically active radiation available to them. The cyanobacteria and algae are confined to the water and upper few mm of soil, whereas the macrophytes may be either floating—for example, in ricefields the water fern Azolla –or rooted in the soil to depth. Planktonic and filamentous algae move up and down in the water column over the day as their buoyancy changes with photosynthetic O2 production. Table 5.1 compares the compositions of cyanobacteria and aquatic macrophytes obtained from ricefields. The data show that cyanobacteria have lower dry matter contents and higher N contents than the macrophytes. Aquatic macrophytes notably have much smaller dry matter contents than terrestrial plants and greater ash contents as % of dry matter. The P contents of the cyanobacteria and aquatic macrophytes in Table 5.1 are in both cases smaller than critical values for deficiency (about 1 %), which indicates that in these ricefields P was the limiting nutrient. Information on the productivity of the floodwater is scarce. Data compiled for ricefields by Roger (1996) give an average of 0.35 t dry wt ha−1 of cyanobacteria,

155

Macrobiological Processes Table 5.1 Compositions of N2 -fixing cyanobacteria and aquatic macrophytes in ricefields. Data are means with ranges in parentheses

Dry matter (% fresh wt) Ash (% dry wt) C (% dry wt ash-free) N (% dry wt ash-free) C:N ratio P (% dry wt ash-free)

Cyanobacteria

Aquatic macrophytes

4.0 (0.9–7.0) 45.0 (27–71) 40.0 (37–47) 5.0 (3.8–7.4) 8 (5–12) 0.2 (0.05–0.39)

8.0 (4.5–12.0) 20.0 (12–50) – 2.1 (1.3–2.9) 24 (18–47) 0.3 (0.1–0.6)

Source: Roger (1996). Reproduced by permission of IRRI.

algae and macrophytes in the field during a cropping season (range 0.1–0.6 t ha−1 ). For freshwater bodies and irrigation canals the average was 4.5 t ha−1 (range 1–13 t ha−1 ). In experimental plots of rice under a range of fertilizer treatments, values for cyanobacteria were 177 kg dry wt ha−1 , 28 kg C ha−1 and 4 kg N ha−1 . Net primary production in ricefield floodwater may reach 1 to 2 g C m−2 day−1 but more usually it ranges between 0.2 and 1 g C m−2 day−1 . The total production over a season is equivalent to 10–15 % of the carbon accumulated by the rice crop.

Factors Affecting Primary Production Climate. The principal variable is light intensity, which affects both the total biomass and its composition. Generally the algal biomass increases following flooding until shading by the rice canopy becomes limiting. In general green algae prefer high light intensity, cyanobacteria prefer low light, though not in all cases, and diatoms are indifferent. This results in a characteristic succession of species over the growing season. The effect of light is moderated by temperature, and both low and high temperatures can be inhibitory. Dessication and re-wetting of the soil are also inhibitory and affect the proportions of species present. Enhanced mineralization of soil N following drying and re-wetting favours algae over cyanobacteria. Soil. Soil pH and the content of available P have the most consistent effect (Roger, 1996). Overall algal growth increases as pH increases and higher pH favours N2 -fixing cyanobacteria over eukaryotic algae. Liming of acidic soils increases the proportion of cyanobacteria in the biomass, and the proportion of cyanobacteria may increase as the soil pH increases during reduction. Applications of mineral fertilizers and organic manures have large effects on algal growth and succession. Effects of changes in acidity and availabilities of N

156

Biological Processes in the Soil and Floodwater

and P are particularly important. Herbicides have direct effects and insecticides have indirect effects through grazers. Biotic Factors. Cyanobacteria appear to be ubiquitous in ricefields and attempts to increase biological N2 fixation by inoculating with improved strains developed in laboratory cultures have not been successful (Roger, 1996). Certain bacteria, fungi and viruses have been shown to be pathogenic to cyanobacteria and algae under laboratory conditions, but this has yet to be confirmed under field conditions. Likewise antagonistic effects have been observed between different species of cyanobacteria and algae, and between algae and macrophytes, and vice versa, but there is not much information on the importance of these effects under field conditions. Invertebrates such as cladocerans, copepods, ostracods, insect larvae and snails are common grazers of algae in ricefields and their population dynamics often mirror those of algae with a lag of a week or two (below).

Dynamics Over the Crop Cycle The plethora of variables affecting algal growth and succession mean that complicated dynamics are expected. Figure 5.10 shows a generalized succession for the dry season flora and fauna in unfertilized ricefields (Grant et al., 1986). The main points are (Roger, 1996): • Eukaryotic algae develop first but are quickly succeeded by non-colonial, heterocystous cyanobacteria, shown by the increase in chlorophyll a in the figure. The bloom of cyanobacteria produces a bloom of ostracods and molluscs, which graze on the cyanobacteria. The resulting collapse of the cyanobacteria population is followed by collapses of the ostracods and molluscs. • About 4 weeks after transplanting a population of slow-growing, mucilaginous, colonial cyanobacteria develops, which is resistant to grazing. This continues to grow until the soil is drained for the harvest of the rice crop. • Primary production typically exceeds net respiration (P:R > 1) over the first month, leading to accumulation of organic matter and hence a decrease in the ratio to low values. • There is a peak of N2 fixation coincident with the early cyanobacterial bloom, shown by the increase in acetylene reducing activity in the figure. Nitrogen fixation by the colonial cyanobacteria is slower but lasts longer.

Biological Nitrogen Fixation in the Floodwater–Soil System The water column and soil surface are often the main sites of biological nitrogen fixation in wetland systems (Buresh et al., 1980; Roger 1996). Biological nitrogen fixation is the process by which atmospheric N2 is reduced to NH4 + and the

157

Macrobiological Processes Chlorophyll a (mg m−2) and Ostracods (no. m−2 × 102)

12

Chlorophyll a

3 2 1 0 10

20

ARA (µmol C2H2 m−2 h−1)

8

150

6

100

4

50

2

0

0

40

50

60

DAT

10 200

30

ARA

Ostracods

1000

Colonial cyanobacteria

500 2000 100

Molluscs

0

10

20

30 40 50 60 70 Days after transplanting

1000

Harvest 50

80

90

1500

0 100

500 0

Molluscs (no. m−2)

P:R

14

Colonial algae (g m−2)

Figure 5.10 Generalized fluctuations of algae, acetylene-reducing activity (ARA), and grazers in floodwater of unfertilized ricefields. P:R is the ratio of primary production to net respiration (Grant et al., 1986). Reproduced by permission of AB Academic Publishers

NH4 + incorporated into organic compounds. The reduction requires a pe less than about −4.5 at pH 7 (Section 4.3). This is less negative than the pe required for reduction of CO2 to CH2 O, hence cyanobacteria (blue-green algae) and certain other photosynthetic bacteria are able to mediate the reduction at the negative pe levels generated in photosynthesis. Non-photosynthetic N2 fixers require anoxic conditions or must exclude O2 from site of fixation. Because of the large activation energy required to break the N≡N triple bond, there is a kinetic barrier to be overcome, and this is achieved in N2 fixing organisms through the enzyme nitrogenase. In wetlands N2 fixation can occur in the water column, in the aerobic water–soil interface, in the anaerobic soil bulk, in the rhizosphere, and on the leaves and stems of plants. Phototrophic bacteria in the water and at the water–soil interface are generally more important than non-photosynthetic, heterotrophic bacteria in the soil and on plant roots (Buresh et al., 1980; Roger 1996). The phototrophs comprise bacteria that are epiphytic on plants and cyanobacteria that are both free-living and epiphytic. A particularly favourable site for cyanobacteria is below the leaf surface of the water fern Azolla, which forms a very efficient symbiosis with the cyanobacterium Anabaena azollae. This symbiosis and those in various leguminous plants have been exploited in traditional rice production systems to sustain yields of 2 to 4 t ha−1 of grain without fertilizer for hundreds of years.

158

Biological Processes in the Soil and Floodwater

There has been much research aimed at developing N2 fixing systems for greater yield levels. For practical reasons, such systems cannot entirely substitute for mineral N fertilizers, and there is the difficult dilemma that N2 fixation within the ricefield is inhibited by additions of mineral N. Table 5.2 gives estimates of N2 fixed by various agents in wetland ricefields and Table 5.3 gives estimates of total fixation in ricefields from a review of 211 N balances in field and pot experiments by Roger and Ladha (1992). The values range from 0 to 100 kg N ha−1 per crop with averages of 30 kg N ha−1 in plots without N fertilizer, 8 kg N ha−1 in plots with N fertilizer broadcast in the floodwater, and 12 kg N ha−1 in plots where the fertilizer was placed at depth in the soil. The beneficial effect of the presence of plants on BNF is evident, and also the effect of illumination, especially without inorganic N, indicating that the N2 fixing agents are phototrophic. Rates of comparable magnitude and variability are found in natural freshwater and coastal wetlands (Buresh et al., 1980; Bowden, 1987). Not all of the nitrogen fixed finds its way into the vegetation. The recovery will depend on rates of decomposition of the material containing the fixed N, rates of Table 5.2 ricefields

Estimates of biological nitrogen fixation (BNF) by various agents in wetland BNF (kg N ha−1 crop−1 )

Heterotrophic bacteria in the rhizosphere Heterotrophic bacteria in the rhizosphere and bulk soil Heterotrophic and phototrophic bacteria on added straw Free-living cyanobacteria Azolla/Anaebena azollae in experimental plots Azolla/Anaebena azollae in ricefields Legumes as green manures

1–7 1–31 20–40 for 10 t straw 0–80 20–150 10–50 50–100 in 50 days

Source: adapted from Roger and Ladha (1992). Reproduced with kind permission of Kluwer Academic Publishers.

Table 5.3 studies

Estimates of nitrogen fixed in rice systems from N balance

Factor No inorganic N With inorganic N Planted Unplanted Soil and water light Soil and water dark No N, soil and water light No N, soil and water dark

No. observations

Mean ± SD (kg N ha−1 crop−1 )

166 45 193 18 197 14 152 14

29.7 ± 25.4 4.0 ± 47.6 26.5 ± 30.7 −0.5 ± 46.2 25.0 ± 33.9 13.2 ± 13.8 31.2 ± 25.7 13.2 ± 13.8

Source: adapted from Roger and Ladha (1992). Reproduced with kind permission of Kluwer Academic Publishers.

159

Macrobiological Processes

loss, especially by volatilization of NH3 from the floodwater, and how well the decomposition matches the dynamics of plant growth. Recoveries seldom exceed 60 % of the N and may be less than 25 %.

5.2.5 FAUNA Table 5.4 lists invertebrates commonly found in the soil and floodwater of different wetland types. Insect larvae, molluscs and, particularly, oligochaete worms of the order Tubificidae are abundant on and in the soil surface. Table 5.5 lists invertebrates common in ricefields. In a survey of 32 ricefields in the Philippines, Simpson et al. (1993a) found that oligochaetes were the only macro-invertebrates present in significant numbers in all the fields. The dominant species were Limnodrilus hoffmeisteri (81 % of the population on average) and Branchiura sowerbyi (13 %). Their distribution within fields was contagious and ranged from 0 to 35 000 m−2 , averages 5000 to 10 000 m−2 . The fresh weight ranged from 0 to 630 kg ha−1 . The average population at a site was positively correlated with soil Table 5.4 Invertebrates commonly found in the soil and floodwater of different types of wetland Meiofauna (63–500 µm diameter) Freshwater Marsh/fen Swamp forest Deepwater Alluvial

Estuarine Tidal marsh Freshwater Brackish Salt Mangrove forest

Macrofauna (>500 µm diameter)

Amphipods, copepods

Chironomid insect larvae, gastropods, isopods

Nematodes, amphipods, copepods, oligochaetes

Crayfish, clams, oligochaetes, gastropods, isopods, midge larvae Oligochaetes including earthworms, crayfish

Nematodes, oligochaetes, ‘terrestrial’ invertebrates (mitesacari, springtailscollembola)

Nematodes, amphipods, oligochaetes Nematodes, amphipods, oligochaetes Nematodes, amphipods, oligochaetes Nematodes, amphipods, copepods, oligochaetes, polychaetes

Oligochaetes, polychaetes, midge larvae Oligochaetes, fiddler crabs, snails, mussels Oligochaetes, fiddler crabs, mud crabs, periwinkles, snails, mussels, oysters, clams Fiddler crabs, oysters, barnacles

Source: adapted from Craft (2001). Reproduced by permission of Lewis Publishers.

160

Biological Processes in the Soil and Floodwater

Table 5.5 Invertebrates in ricefield soil and floodwater Densities (number m−2 )

Microcrustacea Ostracods

Copepods Cladocerans Insect larvae Chironomids Mosquitoes Molluscs Snails

Oligochaetes Tubificids

Min.

Max.

Mean

0

98 000

6000

Comments

              

Stimulated by factors that increase primary production, such as N and P fertilizer. Filter bacteria and algae from water

0 0

40 000 33 000

33 000 900

0

10 000

600

 

0

7000

170



0

1000

200

Inhibited by high acidity, N fertilizer and pesticides; stimulated by high organic matter. Graze on epipelic and floating algae, and on algae epiphytic on plant stems

0

40 000

10 000

Stimulated by factors that increase primary production and bacterial decomposers; inhibited by high soil bulk density

Feed on epipelic algae at soil surface and on floating algae

Source: Roger (1996), Simpson et al. (1993a, 1994a,b).

organic matter and applications of N fertilizer, presumably through the effects of these on primary production and bacterial decomposers on which oligochaetes feed. Populations of insect larvae and molluscs are successional over the season following the cycles of algal populations. But no general trends have been established for the dynamics of oligochaetes, though this may reflect the paucity of data (Roger, 1996). The effects of macrofauna on the soil biogeochemistry can be summarized (Aller, 1994): • manipulation of particles: exposure of substrate resulting in increased decomposition; • grazing: consumption of microbes, stimulation of microbial growth, increased mineralization; • excretion of substrate and nutrients: stimulation of microbial growth, increased mineralization;

Macrobiological Processes

161

• construction of burrows: synthesis of refractory or inhibitory structural products; • irrigation of burrows: increased transfer of soluble oxidants and nutrients, increased re-oxidation and mineralization; • transport of particles: transfer between major redox zones, increased re-oxidation and mineralization. Bioturbation Oligochaetes feed with their heads downward in the burrow and posterior ends upward in the water. They ingest fine soil particles, extract carbon and minerals, and deposit residues in faeces on the soil surface. The faeces may subsequently fall into the burrow and be mixed. The net effect is a loosening and mixing of the soil to depth. The burrows of the species found in ricefields may be several centimetres deep and a millimetre or so in diameter. Deeper and wider burrows are formed by species found in other wetlands (Table 5.4). Once the burrows are constructed, the worms tend to remain in them and maintain a supply of oxygen from the overlying water by waving their posteriors in the water and moving their bodies in a peristaltic motion. Thereby the water in the burrows is mixed with the overlying water and solutes diffusing into a burrow are rapidly transferred to the surface and vice versa. The calculations in Section 2.4 show the great sensitivity of solute transport and mixing to the geometry, density and activity of the burrowing animals. The effects of oligochaetes on the soil or sediment depend on the particular circumstances. Limnologists and oceanographers consider oligochaetes to be agents of aeration, increasing the depth of the oxidized layer and stimulating mineralization and nitrification–denitrification (Fry, 1982; Aller, 1994). For example, Davis (1974) found that the oxidized layer (EH > 200 mV) in profundal lake sediments was increased by 0.3–1.6 cm by tubificid populations of 800 m−2 . By contrast in ricefields, where primary production and the amounts of organic matter in the floodwater may be much greater, the effect can be to enhance the incorporation of organic matter into the soil and so to make the surface soil on average more reduced, in spite of oxygenation of the solution in the burrows. Kikuchi and colleagues (Kikuchi et al., 1975; Kikuchi and Kurihara, 1977, 1982) found that with realistic densities of tubificids and organic matter in ricefields, the oxidized layer at the soil surface disappeared altogether. They found that weed growth was diminished because seeds were moved to a depth at which the O2 concentration was too low for germination, and as a consequence oxygenation of the soil by weeds decreased and populations of aerobes in the soil decreased and anaerobes increased. The concentrations of NH4 + , ortho-P and acid soluble Fe in the floodwater increased and the concentration of NO2 − + NO3 − decreased (Figure 5.11). In practice redox conditions in the burrows will oscillate as the oxygenation of the floodwater varies over the diurnal cycle. Aller (1994) found in a wide range of organic matter-rich sediments containing burrowing invertebrates that

162

Biological Processes in the Soil and Floodwater

NO3− + NO2− (µM)

NH4+ (µM)

600 with tubificids without

400 200 0 500 400 300 200 100

acid soluble Fe (µM)

ortho P (µM)

0 10 8 6 4 2 0 750 600 450 300 150 0 150

175

200

225

250

Day of year

Figure 5.11 Effects of tubificids on concentrations of N species, P and Fe in the floodwater of unplanted microplots in ricefields. Species B. sowerbyi, density 1000 m−2 (Kikuchi and Kurihara, 1982). Reproduced with kind permission of Kluwer Academic Publishers

solid particles constantly cycled between oxic and anoxic zones but typically spent 10- to 100-times longer under anoxic than oxic conditions. Cyclic redox patterns were also common within individual burrows and were accompanied by rapid switching of metabolic processes. Even brief, periodic re-exposure of organic matter to O2 resulted in more complete decomposition than under constant conditions or unidirectional redox change. Redox oscillation apparently results initially in net remineralization of existing microbial biomass followed by stimulated renewed synthesis. Aller (1994) found that some properties, such as the accumulation of P in the sediment, were comparable under fully oxic and oscillating redox conditions but differed under continuously anoxic conditions. This is another mechanism by which the operation of the floodwater–soil system as a whole is not a simple sum of its component parts.

Is Biodiversity Important?

163

5.3 IS BIODIVERSITY IMPORTANT? Submerged and non-submerged soils have huge biological diversity and contain orders of magnitude more biological species than above ground habitats and aquatic systems (Liesack et al., 2000; Conrad and Frenzel, 2002; Usher et al., 2004). The origins of this diversity are in the physical and chemical heterogeneity of soils at micro- and macro-scales, and intense competition for substrate. In submerged soils there are extreme gradients of redox potential from oxic to anoxic zones due to the slow transport of O2 through the soil, and gradients of substrate from rich to poor zones due to the non-uniform distribution of plant debris and root exudates. Heterogeneity also arises from soil physical structure and the labyrinthine network of soil pores which constrain the movements of both organisms and substrates. Although submerged soils have weak macro-structure, especially rice soils that have been deliberately puddled, they retain considerable micro-structure in water-stable micro-aggregates and a corresponding network of pores. These factors in combination result in a near infinite combination of opportunities and constraints for different organisms. But does all this biodiversity have any consequences for soil processes at the macro-scale? This is a seemingly straightforward question, but the answer has been surprisingly elusive. Progress has been hampered by the absence of suitable experimental methods for analysing biological diversity and its relation to soil functions. Three types of method are used (Ritz, 2004): (1) genotypic analysis, which assesses the basic genetic information about the community of microbes present; (2) phenotypic analysis, which assesses the expression of the genetic information, i.e. the living form of the microbial community; and (3) functional analysis, which assesses the processes that the microbial community is actively or potentially engaged in. The greatest diversity is revealed in genotypic analysis, but there is a corresponding lack of discrimination. Analyses of soil DNA often do not show clear differences between soils from widely differing environments, including in submerged soils (Liesack et al., 2000; Reichardt et al., 2000). Phenotypic analysis, such as by assaying membrane-bound phospholipids from living microbes, is more discriminatory, and there is now good evidence for phenotypic ‘signatures’ in soil microbial communities, modified by the environment the microbes are operating in, including for submerged soils (Reichardt et al., 1996). In functional analysis, the actual or potential activities of the microbial community are measured. Techniques for this have been developed based on the ability of soil communities to utilize different C-containing compounds using Biolog plates. The results often match phenotypic analysis and the expected effects of soil and environmental differences. However the method is biased towards those microbes that thrive under the particular conditions of the assay in vitro (Preston-Mafham

164

Biological Processes in the Soil and Floodwater

et al., 2002). A solution is to measure the utilization of substrates added directly to soil, and practical methods for doing this are being developed (Degens and Harris, 1997). Through such techniques evidence is emerging for the importance of biodiversity for macro-scale soil processes (Usher et al., 2004). Though there is evidently a great deal of redundancy in most microbial populations, there are threshold levels of biodiversity below which important soil functions are impaired. For example, the decomposition of recalcitrant organic matter can only be achieved by consortia of organisms operating together, such as in the anaerobic decomposition of organic matter in submerged soils in sequential reduction reactions mediated by microbes (Section 5.1.1). Also the growth and activity of individual organisms is necessarily constrained by the nature of the prevailing community, which is important, for example in the persistence of rare organisms in the soil and management of soil-borne diseases. Given that biodiversity is important, it is important to understand how soil management affects it. But as yet there is not much information on this. It has been assumed that intensification of rice production and more widespread use of fertilizers and pesticides in the past few decades will have diminished the diversity of microbes and invertebrates in ricefields compared with those under traditional practices. Roger et al. (1991) compared the diversity of arthropods in farmers’ fields in the Philippines and at the International Rice Research Institute, and found the greatest diversity in fields at the Institute, where there has been heavy use of fertilizers and pesticides for many years, and the least in fields in the Ifugao rice terraces at Banaue, where there has been little use of fertilizers and pesticides. This goes against the often hypothesized trend of intensification reducing biodiversity. Simpson et al. (1993b, 1994a, b) measured the effects of fertilizer and pesticides on populations of algae and invertebrates in ricefields, and found complicated interactions. Whereas N fertilizer inhibits N2 fixation by cyanobacteria, P fertilizer stimulates it, and the overall productivity of the floodwater is generally increased by fertilization. Likewise pesticides have various effects. Part of the community of organisms responsible for mineralizing organic matter may be killed by pesticide, but the subsequent collapse of predators may allow other mineralizing organisms to bloom. Several insecticides reduce the numbers of ostracods that graze on N2 -fixing cyanobacteria, and so N2 fixation is enhanced.

6 Processes in Roots and the Rhizosphere

Though wetland plants have the advantage of an assured water supply, they must contend with various difficulties that their dryland counterparts are largely spared. First, because of the very slow diffusion of respiratory gases through water and submerged soil compared with dryland soil, the roots must aerate themselves internally by forming internal gas channels to the air above. Second, the roots must exclude toxic products of anaerobic metabolism in the soil, such as organic acids and ferrous iron, or tolerate large concentrations of these toxins internally. Third, they must contend with the altered forms and solubilities of nutrients in the soil under anaerobic conditions, for example the predominance of ammonium rather than nitrate as the plant-available form of nitrogen. That wetland plants are capable of surmounting these difficulties is shown by the great productivity and biodiversity of wetland systems. This chapter discusses the various processes and mechanisms involved in this. 6.1 EFFECTS OF ANOXIA AND ANAEROBICITY ON PLANT ROOTS Generally, in plant cells well supplied with O2 , energy is provided for growth and metabolism by the oxidation of glucose in the three stages shown in Figure 6.1: (1) glycolysis, in which 1 mol of glucose is converted to 2 mol of pyruvate yielding 2 mol of ATP (the main form in which energy is transported and utilized in plants) and 2 mol of NADH2 (reduced NAD which acts as a universal reducing agent in non-green plant tissues); (2) the Krebs cycle, in which 1 mol of pyruvate is completely oxidized to CO2 yielding 1 mol of ATP and 5 mol of NADH2 ; and (3) the mitochondrial cytochrome chain, in which 1 mol of NADH2 generates 3 mol of ATP. The net result is that complete aerobic respiration of 1 mol of glucose yields 38 mol of ATP. However in the absence of O2 , anaerobic glycolysis—fermentation—produces only 2 mol of ATP per mol of glucose consumed. In the absence of O2 the mitochondrial cytochrome chain ceases to operate and as a result NADH2 accumulates The Biogeochemistry of Submerged Soils Guy Kirk  2004 John Wiley & Sons, Ltd ISBN: 0-470-86301-3

166

Processes in Roots and the Rhizosphere

(a)

2 ATP

2 ADP

Glucose

2 PGA

2 (1,3-Diphosphoglycerate) 2 ADP

2 NAD

2NADH2

2 Ethanol

2 ATP

3 2 Acetaldehyde

2 PEP 2 ADP 1 2 ATP 2 Pyruvate

2 Lactate 2 2 CO2

Krebs cycle (b)

Isocitrate

Pyruvate NAD

CO2 a-Ketoglutarate NAD, ADP

Citrate NADH2

CO2 Acetyl-CoA

Oxaloacetate

NADH2

ATP e

ADP FP

e

FPH2

Malate

NAD ADP

NADH2, ATP CO2 Succinate FP Fumarate

NADH2

(c)

NAD NADH2

cytb

ATP e

cytc

ADP e

cyta

ATP e

O2

cyta3 OH−

Figure 6.1 Pathways involved in glucose oxidation by plant cells: (a) glycolysis, (b) Krebs cycle, (c) mitochondrial cytochrome chain. Under anoxic conditions, Reactions 1, 2 and 3 of glycolysis are catalysed by lactate dehydrogenase, pyruvate decarboxylase and alcohol dehydrogenase, respectively. ATP and ADP, adenosine tri- and diphosphate; NAD and NADH2 , oxidized and reduced forms of nicotinamide adenine dinucleotide; PGA, phosphoglyceraldehyde; PEP, phosphoenolpyruvate; Acetyl-CoA, acetyl coenzyme A; FP, flavoprotein; cyt, cytochrome; ε, electron. (Modified from Fitter and Hay, 2002). Reprinted with permission from Elsevier

and the Krebs cycle is suppressed. This leads to an accumulation of acetaldehyde—the first end-product of fermentation (Figure 6.1a); synthesis of alcohol dehydrogenase catalysing the conversion of acetaldehyde to ethanol; and consumption of NADH2 as acetaldehyde is reduced to ethanol and hence continuing production of ATP and pyruvate. So fermentation can continue to generate ATP

Effects of Anoxia and Anaerobicity on Plant Roots

167

for as long as carbohydrate reserves last. However, because the efficiency of this process is much less than the efficiency of aerobic respiration—only 2 mol of ATP are produced per mol of glucose consumed compared with 38—the rate of fermentation must increase sharply under anoxia if the cell energy supply is to be maintained. This can lead to rapid exhaustion of plant reserves under prolonged anoxia. In addition anoxic cells must contend with toxic products of fermentation, particularly ethanol and lactate. Hence the plant will go to some lengths to avoid anoxia in its active tissues.

6.1.1 ADAPTATIONS TO ANOXIA The most important adaptation plants make to anoxic soil conditions is the development of highly porous tissue in the root cortex called aerenchyma (Figure 6.2) (Jackson and Armstrong, 1999). The development of aerenchyma may occur both through closely regulated separation and expansion of cells, or, more usually, through programmed cell death, also under tight regulation in response to external stimuli. The result is a continuous pathway of gas channels between the base of the root and the tip. This both permits gas transport between the plant’s aerial parts and respiring root tissues, and lessens the amount of respiring tissue per unit root volume. In addition, the root wall layers become partially suberized along part of the root length, resulting in decreased permeability to gases and hence less loss of O2 to the anaerobic soil outside. The mechanisms by which the aerenchyma remains gas-filled rather than waterfilled are not fully understood but appear to involve metabolic control (Raven, 1996). The gas-filled state is favoured by inward gradients of water potential created by evapo-transpiration and by barriers to water movement in the apoplasm such as exodermis (van Noordwijk and Brouwer, 1993). Thus the root acts as a moderately gas-tight pipe conveying O2 down from the shoots to the elongating and actively respiring tip and venting CO2 and other respiratory gases in the opposite direction. Figure 6.3 shows changes in root porosity and respiration rate along the length of maize roots grown in anoxic media. Metabolic adaptations in the root to provide alternative respiratory pathways are far less important. Where these do occur, they are only of short-term use. Indeed, in plants that tolerate prolonged soil submergence, root tissues are often particularly sensitive to anoxia (Vartapetian and Jackson, 1997). Without morphological adaptations and a continuous supply of O2 to the root tip, survival is limited. That said, some rice genotypes will survive several days of anoxia resulting from complete submergence of the plant following flash flooding, which is a widespread phenomenon in rainfed rice systems. The tolerance appears to depend on (a) the water being sufficiently clear and with a sufficient dissolved CO2 content that the plants can continue to photosynthesize and produce carbohydrates; (b) cessation of growth so as to preserve carbohydrates for maintenance processes; and (c) increased alcoholic fermentation to maintain glycolysis, NAD

168

Processes in Roots and the Rhizosphere (a)

(b) P

E

CC

SC

CC

0.1 mm

RH (c)

0.1 mm (d)

CC P

P

AE

branch roots aerenchyma

central cylinder

E 0.1 mm

SC

0.1 mm

crack

br

an

ch

ro

ots

(e)

aerenchyma 0.1 mm

Figure 6.2 Cross-sections of primary rice roots. (a) Radial section close to tip showing intercellular spaces (I), central cylinder (CC), and rhizodermis (RH). (b) and (c) Radial sections of younger (39 days) and older (72 days) basal parts showing exodermis (E), schlerenchymatous cylinder (SC), parenchymatous or cortical cells (P) and aerenchyma (AE). (d) and (e) Axial sections of mature root (72 days) showing break through of lateral roots (Butterbach-Bahl et al., 2000). Reproduced by permission of verlag

recycling and ATP synthesis (Setter et al., 1997). However these adaptations would not serve a vigorously growing root system in normal circumstances. Transport of gases through the aerenchyma may occur by diffusion and, where pressure gradients develop, by convection. Pressurized flow is important in wetland plants with root systems permitting a throughflow of gases, but is insignificant in other plants (Beckett et al., 1988; Skelton and Alloway,

169

Effects of Anoxia and Anaerobicity on Plant Roots 60

250

Aerenchyma

200

40

150

Stele

Wall (estimated)

30

Total

100 50 0

50

Cortex 0

20 10

Cortex wall

100

200

Aerenchyma (%)

Respiration rate (ng O2 mL−1 s−1)

300

300

400

0 500

Distance from apex (mm)

Figure 6.3 Aerenchyma development and changes in respiration rate along the length of maize roots grown in anoxic media (adapted from Armstrong et al., 1991a). Reproduced by permission of Backhuys publishers

1996). In throughflow systems atmospheric gases are driven or sucked into the above-ground parts of the plant and then vented from some other point on the above-ground parts as an O2 -depleted and CO2 -enriched exhaust. There are various possible sources of positive pressure—e.g. humidity-induced diffusion and thermal transpiration—and of negative pressure—e.g. wind (Venturi forces), the greater solubility of CO2 than O2 (140-fold at 25 ◦ C and pH 7), differences in gas velocities, and thermo-osmosis (references in Jackson and Armstrong, 1999). Resistance to pressure flow is inversely proportional to the fourth power of the radius of the conducting vessel, and so large pore-diameters in the diaphragm partitions of leaf sheath, stem and rhizome are an essential prerequisite for efficient pressurized flow. A well known example of a pressurized flow system is the water lily (Dacey, 1980, 1981). Pressurized flow could in principle occur in a non-throughflow root system, such as that of rice, driven by dissolution of respiratory CO2 produced from gaseous O2 . However, Beckett et al. (1988) have shown that convection by this means will always be subordinate to diffusion in non-throughflow systems and will only ever have a minor effect. Hence diffusion is the principle means of gas transport. The effectiveness of the internal O2 transport by diffusion or convection depends on the physical resistance to movement and on the O2 demand. The physical resistance is a function of the cross-sectional area for transport, the tortuosity of the pore space, and the path length. The O2 demand is a function of rates of respiration in root tissues and rates of loss of O2 to the soil where it is consumed in chemical and microbial reactions. The O2 budget of the root therefore depends on the simultaneous operation of several linked processes and these have been analysed by mathematical modelling (reviewed by Armstrong

170

Processes in Roots and the Rhizosphere

et al., 1991b, 2000). In the following section I describe the model developed by Armstrong and Beckett (1987). This accounts for the most important processes within the root and has been corroborated for various wetland species using measurements of O2 gradients within roots with microelectrodes.

6.1.2 ARMSTRONG AND BECKETT’S MODEL OF ROOT AERATION To summarize, the main factors influencing the O2 budget of a non-throughflow root in anoxic soil are as follows. (1) The extent of aerenchyma development by the degradation of the primary root cortex. (2) Rates of respiration in different root tissues. The formation of aerenchyma decreases the respiratory O2 demand per unit root volume because there is less respiring root tissue. Also, some plants can tolerate a degree of anoxia in parts of the root, which substantially reduces the O2 demand per unit root volume. (3) The permeability of the root wall to gases. Sub-apical parts of the root can have permeabilities several orders of magnitude smaller than those in the region of the tip. (4) The proportion of fine lateral roots branching off the primary root. Having high surface area to volume ratios, laterals tend to be O2 -leaky. For simplicity, the effects of lateral roots are not dealt with explicitly in Armstrong and Beckett’s model, but they are dealt with in Section 6.2. In the model, the internal structure of the root is described as three concentric cylinders corresponding to the central stele, the cortex and the wall layers. Diffusivities and respiration rates differ in the different tissues. The model allows for the axial diffusion of O2 through the cortical gas spaces, radial diffusion into the root tissues, and simultaneous consumption in respiration and loss to the soil. A steady state is assumed, in which the flux of O2 across the root base equals the net consumption in root respiration and loss to the soil. This is realistic because root elongation is in general slow compared with gas transport. The basic equation is

 d[O2 ]G d[O2 ]L 1 d d (6.1) DG θG fG + rDL − Rroot − Rsoil = 0 dz dz r dr dr where the first term represents axial diffusion through the cortical gas spaces, the second term radial diffusion through root tissues, and the third and fourth terms the rates of O2 consumption in tissue respiration and loss to the soil, respectively. Here DG and DL are the diffusion coefficients of O2 in air and water, respectively, θG is the gas content of root by volume, fG is the impedance factor for diffusion in the cortical gas spaces, r is the radial distance, z is the axial distance and [O2 ]G

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171

and [O2 ]L are the concentrations of O2 in the gas space (mol per unit volume gas space) and in root tissue (mol per unit volume root), respectively. The boundary conditions for solving Equation (6.1) are: (a) at the root base, [O2 ]G is the ambient value in the atmosphere; and (b) at the root apex, [O2 ]G is the minimum value required for root respiration [≈ 30 µmol dm−3 (gas space)]. The equations are solved numerically. 6.2 ARCHITECTURE OF WETLAND PLANT ROOT SYSTEMS In dryland plants the size of the root system compared with the shoot system is generally governed by the plant’s water requirements except under quite severe nutrient deficiency (Tinker and Nye, 2000). However, in wetland plants in submerged soil, the free availability of water means that the size of the root system is more often likely to be governed by nutrient requirements. The length densities of wetland root systems may be comparable to those of dryland plants: length densities of rice roots are typically 20–30 cm cm−3 in the topsoil (Matsuo and Hoshikawa, 1993). A large proportion of the length may be as fine roots. In rice in submerged soil short fine laterals, 1–2 cm long and 0.1–0.2 mm in diameter, develop as branches along the primary roots once the primary roots are a few cm long. These are much less aerenchymatous than the primary roots (porosities of 1–2 % compared with ≤50 %) and they do not develop secondary thickenings in their walls to the same extent (Matsuo and Hoshikawa, 1993). They may themselves be branched producing up to sixth order laterals. They account for a small part of the root mass but the bulk of the external surface, and they are plumbed directly into the main water and solute transport vessels in the stele of the primary root (as can be seen in Figure 6.2). The structure of the rice root is therefore apparently dominated by the need for internal gas transport. On the face of it, this structure may conflict with the needs for efficient nutrient absorption (Kirk and Bouldin, 1991). The development of gas-impermeable layers in the root wall seems likely to impair the ability of those parts of the root to absorb nutrients, and the disintegration of the cortex might impair transport from the apoplasm to the main solute transport vessels in the stele, though these points are uncertain (Drew and Saker, 1986; Kronzucker et al., 1998a). It seems likely that the short fine lateral roots are responsible for the bulk of the nutrient absorption by the root system and compensate for any impairment of nutrient absorption by the primary roots as a result of adaptations for internal aeration. The question arises: what combination of fine laterals and aerenchymatous primary roots provides the greatest absorbing surface for a given root mass? Not having impermeable wall layers and having a large surface area to volume ratio, the laterals will leak O2 more rapidly than the adjacent primary root. A related question is therefore how the O2 budget of the root system is affected by the combination of primary roots and laterals. Armstrong et al. (1990, 1996) modelled O2 release from adventitious and lateral roots of the rhizomatous wetland

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species Phragmites australis, and found that for the appropriate combination of root types, properties and dimensions, and a large but realistic soil O2 demand, the ratio of O2 consumption in root respiration to that in loss to the soil was 13:1 for adventitious roots but 0.15:1, i.e. reversed, for laterals. Evidence for preferential loss of O2 from laterals in rice includes measurements of Fe oxide coatings on roots placed in deoxygenated agar containing Fe(II) (Trolldenier, 1988); changes in redox potential as roots grew across rows of Pt electrodes in anaerobic soil (Flessa and Fischer, 1993); and the abundance of methane oxidizing bacteria, which are obligate aerobes, along rice lateral roots in anaerobic soil (Gilbert et al., 1998). Although O2 leakage compromises the root’s internal aeration, some leakage is desirable for a number of purposes. These include oxidation of toxic products of anaerobic metabolism in submerged soil such as ferrous iron (van Raalte, 1944; Bouldin, 1966; van Mensvoort et al., 1985); nitrification of ammonium to nitrate, there being benefits in mixed nitrate–ammonium nutrition (Kronzucker et al., 1999, 2000); and mobilization of sparingly soluble nutrients such as P (Saleque and Kirk, 1995) and Zn (Kirk and Bajita, 1995) as a result of acidification due to iron oxidation and cation–anion intake imbalance.

6.2.1 MODEL OF ROOT AERATION VERSUS NUTRIENT ABSORPTION Kirk (2003) has developed a simple model to compare root requirements for aeration with those for efficient nutrient acquisition in rice. The main features of the rice root system are summarized in Figure 6.4. The model considers roots in the anoxic soil beneath the floodwater—soil interface, receiving their oxygen solely from the aerial parts of the plant. Structure of the Root System The distribution of primary roots beneath a hill of plants is approximately hemispherical with the individual roots randomly distributed with respect to the vertical and horizontal directions. Thus if there are N primary roots per hill, the length of primary roots per unit soil volume, LVP , at any distance r from the centre of the hill is dN/dr N LVP (r) = (6.2) = dV /dr 2πr 2 About each primary root there is a cylinder of laterals, increasing in density with distance from the root base (Figure 6.5). The laterals may develop up to sixth-order branches. A simple equation to describe this is: LVL (r) = LVL max

r2 (k + r)2

(6.3)

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Superficial roots in floodwater and oxic soil Floodwater Oxic surface soil Primary roots (with laterals) in anoxic soil Anoxic soil

Fine roots penetrating plough pan Plough pan Oxic subsoil

Figure 6.4 Root system of the rice plant (Kirk, 2003). Reproduced by permission of Blackwell Publishing

where LVL is the length density of laterals in the cylinder of soil occupied by them, k is a coefficient, equivalent to the distance at which LVL (r) = 0.25LVL max , and r0 < r ≤ rlat . If the cylinder has outer radius x and inner radius aP (i.e. the radius of the primary root), and x and aP are constant along the root length, then the total length density of primary and lateral roots at distance r from the centre of the hill is   r2 N 2 2 1 + π(x (6.4) LV (r) = − a )L VL max P 2πr 2 (k + r)2 Equation (6.4) gives reasonable fits to measured profiles of LV with depth in the field. Structure of an Individual Root and its Laterals The porosity of the cortex, permeability of the root wall and the coverage of the root with laterals vary along the root length, with a much smaller porosity,

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Processes in Roots and the Rhizosphere radius of hill

zone of laterals

r0

rlat r1

r2 rmax

zone of decreasing porosity zone of root tip

Figure 6.5 Idealized primary root and its cylinder of laterals. The parallel lines indicate the increasing length density of laterals along the primary root. The branching of the laterals is not represented (Kirk, 2003). Reproduced by permission of Blackwell Publishing

more-permeable wall and no laterals in the region of the tip. Where the laterals emerge from the primary root, there are generally cracks in the epidermis a few µm wide and apparently directly connected to the primary root aerenchyma (Butterbach-Bahl et al., 2000). It seems likely these will be important in gas transfer, though there are no direct measurements showing this. In practice leakage of O2 from the cracks and axial gradients of O2 within laterals will lead to gradients of O2 release along laterals. However, for the intended purpose of the model an elaborate treatment of these effects is not necessary; it is sufficient that the loss of O2 increases with the density of laterals and a constant leakage along the length of laterals is assumed. Figure 6.5 defines for the purposes of the model the distances at which the porosity and coverage with laterals change. It is assumed that, because of the changes in wall permeability along the root, nutrients are only absorbed by the primary root in the zones beyond the laterals (rlat < r < rmax ) and by the laterals. This is also the surface across which O2 leaks.

Architecture of Wetland Plant Root Systems

175

Transport and Consumption of O2 in the Roots and Losses to the Soil To avoid unduly complicating the model, radial diffusion within the root is not allowed for. Equation (6.1) therefore reduces to:
 d d[O2 ]G DG θG fG − Rroot − Rsoil = 0 (6.5) dr dr where r is the distance from the root bases (not the radial distance across the root as in Equation 6.1). Rroot at a particular distance along the root is the sum of the respiration in the primary root and in any laterals emerging from it. Hence, if the rate of respiration per unit root mass is Q, Rroot = ρ(1 − θG )Q +

ρ(1 − θG2 )QπaL2 π(x 2 − aP2 )LVL πaP2

(6.6)

Likewise Rsoil at a particular distance is the sum of the rates of loss from the primary root and from the laterals. Hence, if FO2 is the flux across unit root surface, Rsoil =

2πaP FO2 2πaL FO2 π(x 2 − aP2 )LVL + πaP2 πaP2

(6.7)

It is assumed that the primary root wall is completely impermeable to O2 in the zone covered with laterals. In fact the root wall is not completely impermeable in this zone but the resulting flux is small compared with that from the rest of the root system and no serious error arises from ignoring it. It is also assumed that the flux from the laterals and the primary root in the zone beyond the laterals is constant. In fact the sink for O2 in the surrounding soil will vary in a complicated way with soil conditions and time, and there will be differences along the root length. However to some extent these differences cancel each other (Kirk, 2003) and the additional complexity involved in allowing for them is unjustified. The same boundary conditions apply as for Armstrong and Beckett’s model, and the equations are solved numerically.

Model Calculations Figure 6.6 shows results for a realistic set of standard parameter values. The maximum primary root length is 27.3 cm declining to 17.7 dm as the coverage with laterals increases from <5 to 80 % of the root length. Although the maximum root length decreases as the coverage with laterals increases, the absorbing root surface per unit root mass increases more than two-fold as the coverage with

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Processes in Roots and the Rhizosphere (c) 120

30 Absorbing root surface (AR, cm2)

Maximum primary root length (r max, cm)

(a) 28 26 24 22 20 18 16 14 0.0

Porosity of cortex 0.6 0.7 0.8 0.2 0.4 0.6 Fraction of r max with laterals

60 40 20

(d) 280

0.6

240

0.5

Loss to soil (FO2AR, nmol s−1)

Absorbing root surface/mass (AR/WR, cm2 g−1)

80

0 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 O2 respired and lost (nmol s−1)

0.8

(b)

100

200 160 120 80 0.0

0.2

0.4

0.6

Fraction of r max with laterals

0.8

0.4 0.3 0.2 0.1 0.0 2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

Net root respiration (nmol s−1)

Figure 6.6 Effect of cortical porosity of primary root and fraction of root covered with laterals on (a) maximum primary root length, (b) absorbing root surface per unit root mass, and (c) absorbing root surface per primary root as a function of net O2 consumption, and (d) O2 consumed in root respiration and loss to the soil. Numbers on curves are porosities; other parameters have standard values (Kirk, 2003). Reproduced by permission of Blackwell Publishing

laterals increases from <5 to 80 %. The net O2 consumption in root respiration and loss to the soil decreases as the coverage with laterals increases above about 50 %, in spite of the larger surface releasing oxygen. Figure 6.6(d) shows that root respiration is the main sink for O2 , accounting for more than 30 times the O2 loss to the soil at the minimum coverage with laterals, though less than five times the loss to the soil at the maximum coverage with laterals. Respiration in the lateral roots exceeds that in the primary root by four-fold at the maximum coverage with laterals. These values compare with ratios of respiration to loss of 13:1 in adventitious roots of Phragmites australis and 0.15:1 in laterals estimated by Armstrong et al. (1990) with a somewhat larger FO2 than here. The results broadly tally with experimental findings for rice. The maximum length of primary root required to sustain a plant depends on soil conditions and planting density. Typically the depth to the plough pan in a puddled ricefield is less than 2 dm, and a typical spacing between plant hills is 25 cm × 25 cm

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though this varies with rice variety, soil fertility and other factors. The maximum primary root length required to explore this volume of soil would be 26.7 cm, which is within the range calculated with the model. Note that some roots with a greater coverage of laterals could be shorter than this, exploring the soil at shallower depths. In summary, the model shows that a system of coarse, aerenchmymatous primary roots with gas-impermeable walls conducting O2 down to short, fine, gas-permeable laterals provides the best compromise between the need for internal aeration and the need for the largest possible absorbing surface per unit root mass. Though the model assumes a fairly simple picture of the root architecture and the changes in gas-permeability across the roots, this is the basic system in most current rice genotypes. The significance of rates of loss of O2 to the soil of the magnitude calculated is considered in Sections 6.4 and 6.5.

6.2.2 ROOT SURFACE REQUIRED FOR NUTRIENT ABSORPTION Having explored in the last section the limits that the need for internal aeration places on the size of the root system and its optimal architecture, we may now consider what root surface is required for nutrient absorption in submerged soil. I consider the case of nitrogen because it is the nutrient required in the greatest amounts. In fertile moist soil, the main plant-available form of N is usually the NO3 − ion, and because NO3 − is largely not adsorbed on soil surfaces and is all in the soil solution, its rate of delivery to absorbing root surfaces does not limit the rate of uptake. In submerged soil, however, the principle form of N is the NH4 + ion which is adsorbed and therefore diffuses through the soil more slowly. In quantifying the rate-limiting step in uptake and the root surface required we therefore need to allow for the rate of transport through the soil and the rate of transfer across the root surface. The main transport processes involved are shown in Figure 6.7. In essence these are the same as in a non-flooded soil: there is a dynamic equilibrium between solutes in the soil solution and those sorbed on the immediately adjacent Liquid

Root

rapid exchange

Soil

diffusion and mass flow

very slow diffusion Solid

Figure 6.7 Solute transport processes near an absorbing root (Tinker and Nye, 2000). Reproduced by permission of Oxford University Press

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soil surfaces. As solutes are removed from the soil solution by root uptake, the sorbed solutes tend to buffer the soil solution against the resulting changes in concentration. The influx across the root surface, F in moles per unit area per unit time, is related to the concentration in solution at the root surface with a ‘root absorbing power’, α, such that F = αCLa

(6.8)

To calculate the inflow, CLa must be found from the concentration in the soil bulk taking into account rates of transport through the soil. Kirk and Solivas (1997) have done this for N uptake by rice growing in flooded soil and used the resulting model to assess the relative importance of root uptake properties and transport through the soil. Their results are summarized in the following. Kirk and Solivas measured the time course of N uptake by soil-grown rice plants and the simultaneous changes in soil solution NH4 + and root length density, and then compared the results with the calculated minimum root length densities required to explain the uptake. The calculation was based on the following picture of events. (1) All the N is absorbed as NH4 + . (2) The rate of uptake per unit root length for a given concentration of NH4 + at the root surface is maximal, as indicated by a Michaelis–Menten relation derived from measurements with plants grown hydroponically under moderate N-deficiency (Section 6.3). (3) The concentration of NH4 + in the soil solution at root surfaces is related to the mean concentration in the bulk soil solution by an equation for steadystate diffusion through the soil. The diffusion coefficient of NH4 + in the soil was measured. The corresponding equations are as follows. For roots uniformly or randomly distributed in volume V of soil at density LV (length per unit volume), the rate of uptake is dU/dt = 2πaF LV V = 2πaαCLa LV V (6.9) where a is the mean root radius. For steady-state diffusion across a cylinder of depletion around a root of radius x, the concentration maintained at the root surface is (from Tinker and Nye, 2000, Equation 10.24) CLa = 

CL  1 x 2 (αa/Db) x 1 − (αa/Db) + ln 2 (x 2 − a 2 ) a

(6.10)

where CL is the mean concentration in solution in the soil around the root, D the diffusion coefficient of NH4 + in the soil and b the buffer power for NH4 + . The assumptions inherent in this equation are discussed by Kirk and Solivas. The

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Architecture of Wetland Plant Root Systems

√ value of x increases as x = 2 Dt + a until it coincides with the boundary with √ the equivalent cylinders around adjacent roots, at which point, x = 1/ πLV . In the experiments, N as urea was mixed into the soil so that the concentration in the floodwater was negligible. The urea N was all hydrolysed to NH4 + within a few days. The results are shown in Figure 6.8. They indicate that it would have been necessary for the whole of the measured root length to have been active in uptake to achieve the measured uptake rates, even though very large root length densities developed—up to 30 cm cm−3 , which is near maximal values for the upper 10 cm of soil under field conditions (Matsuo and Hoshikawa, 1993, Chapter 2, Section 2), and uptake per unit root length was near maximal. This is somewhat surprising: in dryland crops the total root length is generally far larger than necessary to account for N uptake. An important difference is that, as a result of NH4 + adsorption on the soil solid, unlike for NO3 − , the concentration of NH4 + in the soil solution is less than Km for high affinity NH4 + transporters in the root and so V < Vmax and a larger root length is required. (b) 10

Solution NH4+ (mM)

N uptake (mmol plant−1)

(a)

8 6 4 2

1.5 1.0 0.5 0.0

0 (d) 5000

Root density (dm dm−3)

(c) Root density (dm dm−3)

2.0

−N

1000 500 100 20

30

40

5000

+N

1000 500 100

50 20 30 Time (days after germination)

40

50

Figure 6.8 The time-course of (a) N uptake, (b) soil solution NH4 + , and (c) and (d) root length density in pots of flooded soil planted with rice with ( ) and without ( ) added N. In (a), lines are fitted logistic curves, slopes of which give values of dU /dt in Equation (6.10). In (b), solid horizontal lines are CL ; broken lines CLa calculated with Equation (6.11). In (c) and (d), the lines indicate the minimum root length densities required to explain uptake calculated with the measured CL values ± SE (full lines) and CL derived from exchangeable NH4 + values ± SE (Kirk and Solivas, 1997). Reproduced by permission of Blackwell Publishing

Ž

ž

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Processes in Roots and the Rhizosphere

However the calculations indicate an unlikely lack of margin for error in the root length. A possible explanation is that N species other than NH4 + are also being absorbed—such as NO3 − or amino acids—as discussed in Section 6.3. Transport of NH4 + to the roots in Kirk and Solivas’ experiment was mainly by diffusion. The additional transport resulting from mass flow of soil solution in the transpiration stream would have increased the influx across the roots by about 100ava /0.5bD % where va is the water flux (Tinker and Nye, 2000, pp. 146–148), or about 4 % in Kirk and Solivas’ experiment. A sensitivity analysis showed that rates of diffusion will generally not limit uptake in well-puddled soils, but they may greatly limit uptake in puddled soils that have been drained and re-flooded and in unpuddled flooded soils. Note that the above conclusions refer to uptake of soil N by the main body of the rice root system in the anoxic soil beneath the soil–floodwater interface. Uptake of fertilizer N broadcast into ricefield floodwater and absorbed by roots in the floodwater or soil near the floodwater is not likely to be limited by root uptake properties or transport (Kirk and Solivas, 1997).

6.3 NUTRIENT ABSORPTION PROPERTIES OF WETLAND PLANT ROOTS 6.3.1 ION TRANSPORT IN ROOTS Taiz and Zeiger (2002) give a full account of this topic. Mineral ions absorbed from solution outside the root surface must be transported across the root to the main long-distance transport vessels in the xylem, through which they reach the shoot. This process is highly specific for different ions and molecules and is closely regulated. The regulation is in part a function of the anatomy of the various root tissues and in part a function of active transport processes in root cells. The pathways and transport processes are affected by root adaptations to anoxia. Molecules and ions move across the root through both extracellular and intracellular pathways (Figure 6.9). The extracellular route exists because all cells have walls containing solution separated from the cytosol by plasma membranes, and there is therefore a continuous ‘apoplastic’ pathway through which solutes can diffuse from one cell wall to the next without crossing a plasma membrane. There is also a continuous intracellular ‘symplastic’ pathway because the cytosols of neighbouring cells are connected by cylindrical pores called plasmodesmata, 20–60 nm in diameter, through which ions and molecules that have been taken up into the cytosol may diffuse. In tissues where significant intracellular transport occurs there may be up to 15 plasmodesmata per square µm of cross-section. An ion entering a root may immediately enter the symplast by crossing the plasma membrane of an epidermal cell, or it may remain in the apoplasm and diffuse through cell walls. It may subsequently enter the symplasm by crossing

181

Nutrient Absorption Properties of Wetland Plant Roots XYLEM CORTEX EPIDERMIS

ENDODERMIS PAREN- TRACHEARY CHYMA

EXTERNAL SOLUTION

Apoplasm Cytoplasm Nucleus Vacuole

Plasma Tonoplast Plasmo- Casparian membrane desmata strip

Figure 6.9 Idealized structure of a root showing apoplastic and symplastic pathways for solute transport to the xylem

the plasma membrane of a cortical cell, and thence continue to the xylem. But it cannot reach the xylem entirely through the apoplasm because its passage is blocked by a suberized layer of endodermal cells called the Casparian strip. These effectively block entry of water and mineral ions into the stele via the apoplasm. They also prevent back diffusion of solutes from the xylem apoplast to the cortical apoplast. Finally the ion must leave the symplast of the xylem and be loaded into the xylem’s long-distance conducting vessels. The mechanism of xylem loading apparently involves both passive and active transfer from the xylem parenchymal cells. The immediate means of regulating ion transport and hence absorption into the root is through the control of active uptake across plasma membranes. Changes in root anatomy in response to changes in nutritional or other external conditions are necessarily slower. Membrane Transport Processes The cell plasma membrane separates the cell cytoplasm from the external medium. The composition of the cytoplasm must be tightly controlled to optimize cellular processes, but the composition of the external medium is highly variable. The membrane is hydrophobic and impedes solute diffusion. But it also facilitates and regulates solute transfers as the cell absorbs nutrients, expels wastes and maintains turgour.

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When concentration gradients of solutes exist across a membrane the solutes will diffuse according to their individual concentration gradients. Because of differing mobilities, an electric potential exists between diffusing ions—the diffusion potential (Section 2.2)—and as a result the faster ions speed up the slower ones and vice versa, so that electrical neutrality is maintained everywhere in the solution. Thus the rates of transfer of negative and positive charges are equal. However an electric potential difference across the membrane persists and is measurable. Plant cells have several internal compartments separated by plasma membranes. The main compartments controlling the ionic relations of the cell are the cytosol and vacuole. The vacuole occupies more than 90 % of the cell volume and so contains the bulk of the ions. Many different ions permeate the membranes, but in general K+ , Na+ and Cl− have the greatest concentrations and permeabilities. Studies of ion relations in plant cells have led to the following conclusions: • K+ is accumulated in both the cytosol and vacuole by passive diffusion, except when the external concentration is small in which case its is actively taken up; • Na+ is actively pumped out of the cytosol into the apoplasm and vacuole; • H+ generated in metabolic processes in the cell is also actively pumped out of the cytosol to maintain a neutral pH; as a result the pH in the apoplasm and vacuole may be two units lower; • Cl− and all other anions are actively taken up into the cytosol. All the ions also diffuse passively according to their electrochemical gradients. It is possible to calculate the resulting diffusion potential across the membranes. Typically the diffusion potential expected from the movements of K+ , Na+ and Cl− is in the range −80 to −50 mV. But measured membrane potentials are generally much more negative, often −200 to −100 mV, indicating that the membrane potential has a second component. The excess potential is generated by electrogenic H+ -ATPases in the plasma membrane which pump H+ ions out. The energy provided by hydrolysis of ATP is used to pump out H+ against its electrochemical gradient. This drives the movements of other ions and molecules across the membrane via various transporters which both enhance and regulate the transfers. Three types of membrane transporter are found: channels, carriers and pumps (Figure 6.10). Channels are transmembrane proteins that function as selective pores through which ions or uncharged molecules can diffuse passively. Their selectivity for solutes depends on the size of the pore and the density of surface charges lining it. These are altered in response to external and internal stimuli in the plant, so regulating the transport. Carriers consist of proteins that extend completely across the membrane. A solute being transported is initially bound to external sites on the carrier protein; subsequent changes in the conformation of the protein result in the transfer of the bound solute across to the other side of the membrane where it dissociates.

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Nutrient Absorption Properties of Wetland Plant Roots Symporters

Energy dissipated by movement of H+ back into cell coupled to transport of one molecule of substrate in

+

K H2PO4− NO3−

H+ Na+

Zn2+ Fe2+ sucrose + H+ Mn2+ H

H+

Antiporters

hexose H+

Na+

+

H+ H+

sucrose H+

H

ATP

sucrose

Mg2+

Ca2+

ATP ADP + Pi

H+

ADP + Pi H+

H+ Efflux carrier

Cd2+

H+

Na+

CYTOSOL

H+ pumps H+

Antiporter Energy dissipated by movement of H+ back into cell coupled to active transport of substrate out

H+

H+ NH4+

Energy from ATP hydrolysis used to pump H+ out against electrochemical gradient

amino acid + H

ATP

ADP + Pi

H+ ADP pumps + Pi

ATP 2Pi

VACUOLE H+ anions, cations

H+

Ca2+

PPi Tonoplast Plasma membrane

ABC transporter ATP PC-Cd2+ ADP + Pi ADP + Pi Ca2+ ATP Ca2+ pump

anions (malate2−, Cl−, NO3−) Channels

K+

Inward rectifying K+ Outward rectifying Channels

Inward rectifying Ca2+

Cl− Outward rectifying

Transmembrane pores: selectivity for solutes depends on biophysical properties that are actively regulated

Figure 6.10 The main transport processes across the plasma membrane and tonoplast of plant cells (adapted from Taiz and Zeiger, 2002). Reproduced by permission of Sinauer Associates

The binding is highly selective and allows transport of a wide range of both organic and inorganic solutes. The transport may be either passive, down an electrochemical gradient, or, unlike for channels, active. If active, the carrier must couple the energetically uphill transfer of solute to a separate energy-yielding process. The coupling may be direct, for example to ATP hydrolysis as in H+

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Processes in Roots and the Rhizosphere

and Ca2+ pumps; or it may be secondary with the membrane potential generated by H+ pumps dissipated by reuptake of one or more H+ ions coupled to the transport of a different ion or molecule. The solute may be transported into the cell—symport—or out of it—antiport. Thereby H+ ions circulate across the plasma membrane, outward through primary active transport proteins and inward through secondary transport proteins. A particular ion or uncharged molecule can be transported by different transporters depending on its concentration. For example NH4 + may be absorbed by a passive low-affinity uptake system when its external concentration is large and by an active high-affinity system when its external concentration is small. Figure 6.10 summarizes the main transport processes on the plasma membrane and tonoplast of plant cells.

6.3.2 ION TRANSPORT IN WETLAND ROOTS Of wetland plants, rice has been studied the most extensively, and nitrogen has been the most extensively studied element. In this section the rates at which rice roots can absorb nitrogen are discussed and whether this is affected by the morphological and physiological adaptations to anoxic soil conditions.

Experimental Systems for Measuring Absorption Kinetics The aim is to measure the influx of the nutrient into a root for a given concentration of the nutrient in the soil solution at the root surface. This is a seemingly simple matter. But there are well-known difficulties in obtaining unequivocal information (Marschner, 1995; Tinker and Nye, 2000). The main problem is that the influx of the nutrient is closely regulated by the plant and depends sensitively on the current nutrient content of the plant as well as the external concentration the root is exposed to. Over time the plant will adjust its intake to the new external concentration, so the measured influx will be a function of how long the plant has been exposed to the new concentration. Measurements should therefore be made as rapidly as possible following exposure to the new concentration. Currently the best available technique for this for N absorption by roots uses the short-lived tracer 13 N. This is a strong γ -emitter and so can be assayed very accurately and rapidly in fresh root tissue and thereby N fluxes across root membranes measured rapidly and non-destructively. Wang et al. (1993a, b) and Kronzucker et al. (1998a, b, 1999, 2000) have used this technique to study NH4 + and NO3 − absorption by rice roots. In the following sections I discuss these results at some length. In brief the procedure is as follows. Plants were grown for 3 to 4 weeks in hydroponic cultures with different concentrations of N, then exposed briefly (<10 min) to solutions containing 2 to 1000 µM of N labelled with 13 N, and the kinetics of influx deduced from the accumulation of 13 N in the

185

Nutrient Absorption Properties of Wetland Plant Roots

plants. In other experiments the kinetics of 13 N efflux out of previously labelled roots were followed, and from the results the partitioning of the 13 N between different subcellular compartments was inferred.

Effects of External and Internal Nutrient Concentrations Wang et al. (1993a, b) studied the kinetics and regulation of NH4 + absorption by rice roots using 13 N. In common with other plants and ions, this revealed at least two transport systems for NH4 + influx: one active and operating at low external concentrations of NH4 + (<1000 µM); the other passive and operating at higher concentrations and associated with a significant efflux of NH4 + into the external solution. Figure 6.11 shows results for the high affinity concentration range with plants grown for 3 weeks at three different NH4 + concentrations. The data for the different concentrations fitted Michaelis–Menten-type equations: V =

Vmax CLa Km + CLa

(6.11)

NH4+ influx (µmol g−1 FW h−1)

where Vmax is the maximum influx in moles per unit root fresh weight per unit time, Km a constant and CLa the concentration in solution at the root surface. Table 6.1 gives the values of Vmax and Km ; Vmax was four-fold larger and Km six-fold smaller for plants grown in 2 µM NH+ 4 solutions than for those in 1000 µM solutions. It is apparent that the roots have considerable flexibility in their response to the external N concentration. Influx of NH4 + is ‘up-regulated’ as the plant’s internal N status decreases, but suppressed as the N status increases. Hence there 16 2 µM 12 100 µM

8

1000 µM

4

0

0

200 400 600 800 [NH4+] in external solution (µM)

1000

Figure 6.11 Concentration dependence of steady-state NH4 + influx into rice roots grown at a range of external NH4 + concentrations. Prior to the influx measurements, the plants were grown in solutions at the concentrations indicated on the curves (Wang et al., 1993b). Reproduced by permission of the American Society of Plant Biologists

186

Processes in Roots and the Rhizosphere Table 6.1 Parameters for Michaelis–Menten equations fitted to NH4 + absorption data in Figure 6.11 Initial [NH4 + ] (µM) 2 100 1000

Vmax (µmol g−1 fresh wt h−1 )

Km (µM)

12.8 8.2 3.4

32.2 90.2 122.1

Source: Wang et al. (1993b). Reproduced by permission of the American Society of Plant Biologists.

is unused capacity in the root transporters in plants that are not very low in N. Furthermore there is considerable efflux of absorbed NH4 + back out of the roots, implying a futile cycling of N across the root membrane. From studies of the kinetics of efflux of 13 NH4 + out of the roots, during a 30 min exposure to 13 NH4 + of plants grown in 100 µM NH4 + , 20 % of the 13 N was assimilated, 20 % sequestered in the vacuole, 40 % retained in the cytoplasm and 20 % lost through efflux (Wang, 1993b). Concentrations of NH4 + in the cytoplasm were large—15 to 20 mM—with no sign of toxicity. These results indicate it may be possible to improve the efficiency of absorption and assimilation by altering the process of regulation. However the mechanisms governing regulation are poorly understood. It is not known whether the regulation is linked to the concentration of NH4 + or NO3 − itself or to the concentrations of products of N assimilation ‘downstream’ from NH4 + or NO3 − , such as particular amino acids. Nor is it known what the targets of the resulting feedback mechanisms are. Effects of Anoxia The above studies were made in aerated growth media. To simulate anoxic conditions in submerged soil, Kronzucker et al. (1998a) grew plants for 3 weeks in aerated nutrient solutions and then transferred the plants to solutions bubbled with N2 –O2 mixtures to give O2 concentrations from 100 to 15 % of air-saturation. They found that the capacity for NH4 + absorption remained large, even at very small external O2 concentrations. In the early stages of exposure to hypoxia, NH4 + absorption actually increased, but subsequently it declined reaching a steady state after a few days (Figure 6.12). Thus as the plants adapted to hypoxia influx of NH4 + into the roots was both up-regulated and down-regulated. At steady state, the maximum influx (Vmax ) varied with the degree of hypoxia but the affinity for NH4 + (Km ) was constant (Table 6.2). The rate and extent of these changes are consistent with metabolic adaptations to hypoxia rather than impairment of uptake due the changes in root morphology. Thus Kronzucker et al. (1998a) argue that the initial up-regulation of NH4 + influx was a response to cytoplasmic acidosis involving decarboxylation of N

187

Nutrient Absorption Properties of Wetland Plant Roots

Influx of NH4+ (µmol g−1 FW h−1)

7 6 5 4 3 2 1 0

0

1 2 3 4 5 6 Duration of hypoxia (days)

7

Figure 6.12 Effect of hypoxia on influx of NH4 + into rice roots. Seedlings were cultivated in nutrient solutions containing 100 µM NH+ 4 , aerated for 3 weeks then at 15 % O2 for indicated times (Kronzucker et al., 1998a). Reproduced by permission of the American Society of Plant Biologists Table 6.2 Effect of hypoxia on Michaelis–Menten parameters for NH4 + absorption by rice. Plants were grown in nutrient solutions containing 100 µM NH+ 4 , aerated for 21 days and then exposed to hypoxia for 7 days O2 pressure (% of air-saturated)

Vmax (µmol g−1 fresh wt h−1 )

Km (µM)

5.22 8.21 5.41 4.69

31.8 38.9 32.6 46.9

100 50 35 15 Source: Kronzucker et al. (1998a).

compounds to neutralize acidity, and the subsequent down-regulation of influx is as a result of restrictions in ATP supply. Though they did not measure the changes in root morphology in response to hypoxia, other work shows that within 7 days aerenchyma formation and other changes would have occurred (Kronzucker, unpublished). But since influx was at steady state after 4 days at about 50 % of the pre-hypoxia level this had no very dramatic effect on the capacity for NH4 + absorption. Ammonium versus Nitrate Absorption Kronzucker et al. (1999, 2000) have found that lowland rice (cv IR72) grown hydroponically is exceptionally efficient in absorbing NO3 − , raising the possibility that rice growing in flooded soil may absorb significant amounts of NO3 − formed by nitrification of NH4 + in the rhizosphere. This is important because (a) this NO3 − is otherwise lost through denitrification in the soil bulk (Reddy

188

Processes in Roots and the Rhizosphere

et al., 1989), and (b) plant growth and yield are generally improved when plants absorb their nitrogen as a mixture of NO3 − and NH4 + compared with either on its own (Layzell and Turpin, 1990; Taiz and Zeiger, 2002). Previous field research has shown the large potential for losses of NO3 − but not the potential advantages of NO3 − nutrition. Because NO3 − is rapidly reduced in the plant, and there are no simple methods for measuring NO3 − fluxes into the plant, it is difficult to quantify the extent of NO3 − absorption under field conditions. Three lines of evidence from Kronzucker et al., suggest unusually efficient NO3 − absorption. First, steady-state influx of NO3 − and NH4 + followed Michaelis–Menten kinetics over the relevant concentration range (Figure 6.13a), and Vmax for NO3 − was some 40 % larger than that for NH4 + and Km 50 % smaller. Second, induction of the root NO3 − transporters following its re-supply to plants deprived of NO3 − for 24 h was exceptionally rapid, peaking within 2 h (Figure 6.13a). For comparison, in white spruce, which is not well adapted to using NO3 − , full induction takes several days, and in barley, which is considered one of the most efficient NO3 − users, full induction takes up to 24 h (references in Kronzucker et al., 2000). Third, subcellular pool sizes and fluxes, estimated from the kinetics of 13 N efflux out of labelled roots indicated highly efficient NO3 − use: while similar proportions of incoming NH4 + and NO3 − were channelled into assimilation and to the vacuole, the proportion of NO3 − translocated to the shoot was larger and that lost through efflux out of the roots smaller (Figure 6.14). (a)

(b) 9

N influx (µmol g−1 FW h−1)

8

NO3−

7 4 wk 6 5 4

NH4+

3 3 wk

2 1 0

0 100 200 300 400 500 [N] in external solution (µM)

0

5

10

15

20

25

Time after exposure to NO3− (h)

Figure 6.13 Influx of N into roots of intact rice plants grown on 100 µM N as either NO3 − or NH4 + : (a) concentration dependence of NO3 − and NH4 + influx in 4-week-old plants; (b) induction of NO3 − uptake in 3- or 4-week-old plants deprived of N for 24 h before re-supply at 100 µM for the indicated periods (Kronzucker et al., 2000). Reproduced by permission of Blackwell Publishing

189

Nutrient Absorption Properties of Wetland Plant Roots 9 8

0.83 NO3− = 0.32 0.09 NH4+ = 0.51 0.07

assimilation/vacuole xylem efflux

N flux (µmol g−1 h−1)

7 6

0.52

4.19 NO3− = 1.37 0.19

5 2.28

4

NH4+ = 2.82 0.17

0.99 1.05

3

2.86 NO3− = 1.12 0.08

2 3.18

2.04

1

NH4+ = 1.74 0.11

0 NO3−

NH4+

NO3− + NH4+

Figure 6.14 Fluxes of NO3 − and NH4 + within rice roots measured by analysing 13 N + efflux kinetics. Plants were grown on 100 µM NO− or NH4 NO3 (i.e. [NO3 − ] 3 , NH4 + = [NH4 ] = 50 µM) for 3 weeks. Efflux kinetics were measured following 60 min exposure of roots to 13 N-labelled solutions of the same composition (data from Kronzucker et al., 1999)

When NO3 − and NH4 + were provided together in the nutrient solution at the same total N concentration (100 µM, i.e. [NO3 − ] = [NH4 + ] = 50 µM), NO3 − influx, accumulation and metabolism were repressed (Figure 6.14). However, plasma membrane fluxes of NH4 + , NH4 + accumulation in the cytosol and NH4 + assimilation were larger than with solely NH4 + at 100 µM, and NH4 + efflux was smaller. Because very little free NH4 + is translocated to the shoot, enhanced translocation of 13 N derived from 13 NH4 + in the presence of NO3 − indicates that NH4 + assimilation was stimulated by NO3 − . As a result, net N acquisition and translocation to the shoot were much larger than when NO3 − or NH4 + was provided alone. The extent of NO3 − absorption by soil-grown plants will depend on its rate of formation and loss in the rhizosphere (this is considered in Section 6.5). Transporters for amino acids have also been found in plant roots, and concentrations of amino acids in the soil solution in flooded soils can be appreciable. Therefore it seems likely that some N is also absorbed as amino acids, but as yet we do not have the necessary data to quantify this. Prospects for Improving the Efficiency of Absorption These results suggest various possibilities for increasing the efficiency of N absorption and assimilation. The fact that the NH4 + and NO3 − transport systems

190

Processes in Roots and the Rhizosphere

are down-regulated for the most part indicates that there is no need to incorporate additional transporters. Rather, efforts should focus on manipulating the regulation of influx or decreasing efflux or both. Depending on the specific N compounds that trigger down-regulation, and on their subcellular location, it might be possible to dampen down-regulation by directing N to different biochemical pathways or subcellular compartments or both, and, as necessary, to store the additional N taken up in cell vacuoles. The rate of assimilation of NH4 + , which must to a large extent occur in the root, may be limited by the supply of carbon skeletons. The extent to which carbon skeletons are limiting will depend on the C:N ratio of the amino acid or amide used to transport N to the shoot, and this may be manipulable. In addition any process that led to a lowering of cytoplasmic NH4 + concentrations would presumably lower efflux. 6.4 ROOT-INDUCED CHANGES IN THE SOIL The following root-induced changes in the soil occur as an inevitable consequence of the nature of submerged soils and plant adaptations to them. (1) Organic compounds are released from the root into the soil. As for dryland plants, this may account for up to 10–15 % of the photosynthate, depending on the plant’s nutritional status and other factors. It includes microbial substrate, as exudate or sloughed-off material; extracellular enzymes, actively or passively released; and complexing agents, also actively or passively released. (2) Oxygen diffusing down through the root’s internal aerenchyma leaks out into the soil, which has a lower O2 concentration. (3) Mobile inorganic reductants in the soil are oxidized, particularly Fe2+ which is precipitated as Fe(OH)3 on or near the root. As a result the concentration of Fe2+ near the root falls and more Fe2+ diffuses in from the bulk soil. This is then oxidized resulting in a zone of Fe(OH)3 accumulation near the root. (4) The oxidation of inorganic reductants generates H+ : 4Fe2+ + O2 + 10H2 O = 4Fe(OH)3 + 8H+ so the pH in the oxidation zone tends to fall. (5) Because the main form of plant-available N in anaerobic soil is NH4 + , the root absorbs an excess of cations (NH4 + , K+ , Na+ , Ca2+ , Mg2+ ) over anions (H2 PO4 − , Cl− , SO4 2− ). Consequently H+ is released by the root to maintain electrical neutrality, tending to further decrease the soil pH. Note that if any N is taken up as NO3 − as a result of nitrification of NH4 + in the rhizosphere, the net acid–base change is the same because, although the root exports 2 mol less H+ for each mol of NO3 − replacing a mol of NH4 + , 2 mol of H+ are formed in the nitrification of each mol of NH4 + . Note also that Si, which is taken up in large quantities by rice plants, crosses the root as the uncharged H4 SiO4 molecule (pK1 = 9.46 at 25 ◦ C).

Root-Induced Changes in the Soil

191

(6) Because very large concentrations of dissolved CO2 develop in submerged soil, in spite of root respiration the CO2 pressure outside the root may be greater than that inside it, resulting in a flow of CO2 from the soil to the atmosphere through the aerenchyma. Net removal of CO2 by the root decreases the concentration of the acid H2 CO3 near the root, and this may offset the acidity produced in oxidation and excess cation uptake. The net effects of these processes will depend on their rates versus the rates at which the resulting changes are buffered by processes in the soil. In the following sections I give available information for different soil conditions. 6.4.1 OXYGENATION OF THE RHIZOSPHERE The extent to which wetland roots oxygenate their rhizospheres is a matter of contention. There is little doubt that some O2 is released: reddish-brown ferric oxide deposits are frequently observed on the surfaces of wetland roots. But the magnitude of release is debated and measured rates of release vary by more than two orders of magnitude (Bedford et al., 1991; Sorrell and Armstrong, 1991; Kirk and Le van Du, 1997). The flux of O2 across a particular portion of the root depends not only on the rate of O2 transport through the root—which is itself complicated by the effects of root type, age and condition—but also on the strength of the sink presented by the external medium. In soil, the strength of the sink depends on the rate of O2 diffusion into the soil, its rate of consumption by microbes and reaction with mobile reductants such as Fe2+ , and the rate of Fe2+ diffusion towards the oxidation zone. There are also differences along the root length. As a root grows through a portion of soil, a zone of Fe2+ depletion arises where oxidation is intense in the region of the root tip, but is rapidly filled in when the O2 supply decreases as the root grows passed. Re-reduction of Fe(III) is slow compared with oxidation of Fe(II). Hence the root tips are generally white and free of ferric oxide deposits, whereas the older parts are coloured orange-brown. The calculations in Section 6.2 indicate that the root system as a whole can sustain considerable rates of O2 loss to the rhizosphere without compromising their internal O2 requirements. The standard O2 flux in the calculations in Section 6.2 was 0.5 nmol dm−2 (root) s−1 for the parts releasing O2 . For rice roots grown in soil, Begg et al. (1994) obtained values of 0.1–1.2 nmol dm−2 (root) s−1 from rates of Fe2+ oxidation and Fe(III) accumulation near planar layers of rice roots in anaerobic soil, and Kirk and Bajita (1995) obtained 0.1–0.2 nmol dm−2 (root) s−1 with the same experimental system but a soil with a smaller ferrous iron content. These values probably underestimate the total O2 release because they did not allow for O2 consumed by soil microbes. Revsbech et al. (1999) obtained values of 1–3 nmol dm−2 (root) s−1 from measurements of O2 gradients made with a microelectrode near rice roots in the soil used by Kirk and Bajita (1995). These values are in the middle of the range described above.

192

Processes in Roots and the Rhizosphere

Figures 6.15 and 6.16 give the profiles of Fe(II) and Fe(III) concentration and pH measured by Begg et al. (1994) and Kirk and Bajita (1995). Blocks of reduced soils were placed in contact with planar layers of rice roots, with the roots separated from the soil by fine nylon mesh which they could not penetrate. 0.25

7.0 3 days

0.20 pH

0.15

6.5 6.0 5.5

0.10

Fe(III)

0.05

4.5

0.00

4.0

0.25

7.0 5 days

0.20

6.5 6.0

0.15 5.5

pH

[Fe(II)], [Fe(III)] (mol kg−1)

5.0 Fe(II)

0.10 5.0 0.05

4.5

0.00

4.0 7.0

0.25 10 days 0.20

6.5 6.0

0.15 5.5 0.10 5.0 0.05 0.00

4.5

0

2

4 6 8 10 Distance from root plane (mm)

4.0 12

Figure 6.15 Profiles of ferrous and ferric iron and pH in blocks of two reduced soils in contact with planar layers of rice roots for indicated times in Iloilo soil. Iloilo soil is a highly weathered sandy loam, org C = 1.2 %, aerobic pH = 3.4, reducible Fe = 80 mmol kg−1 (Begg et al., 1994). Reproduced by permission of Blackwell Publishing

193

Root-Induced Changes in the Soil 0.18

7.4

0.15 7.3 0.12 pH

Fe(III)

0.09

7.2

0.06

Fe(II) 7.1

0.03 3 days 0.00

7.0

0.18

7.4

0.15 7.3 0.12 0.09

7.2

pH

[Fe(II)], [Fe(III)] (mol kg−1)

6 days

0.06 7.1 0.03 0.00

7.0

0.18

7.4 12 days

0.15

7.3 0.12 0.09

7.2

0.06 7.1 0.03 0.00

0

2

4 6 8 10 Distance from root plane (mm)

7.0 12

Figure 6.16 As Figure 6.15 but with Maahas soil. Maahas soil is a dark humic clay, org C = 18 %, aerobic pH = 5.9, reducible Fe = 30 mmol kg−1 (Kirk and Bajita, 1995). Reproduced by permission of Blackwell Publishing

Over 2 weeks of root–soil contact, Fe2+ close to the roots was oxidized by O2 from the roots, and substantial quantities of iron were transferred towards the root plane producing a well-defined zone of Fe(OH)3 accumulation. The pH in the oxidation zone fell. In both the soils studied, the amount of H+ formed in

194

Processes in Roots and the Rhizosphere

Fe(II) oxidation was comparable to that released from the roots to balance excess cation uptake. But in both soils the H+ generated in these two processes exceeded the acidification calculated from the pH profile and the soil pH buffer powers. This was possibly because of CO2 uptake by the roots and, in the Maahas soil, where acidity diffusion was fast because of the high pH and high CO2 pressure, because the acidification spread beyond the zone of soil analysed. 6.4.2 THE pH PROFILE ACROSS THE RHIZOSPHERE The pH profile across the rhizosphere resulting from the above processes depends on the rate at which acidity is generated versus the rate at which the resulting pH change is propagated away through the soil. In the Iloilo soil (Figure 6.15), which is a highly weathered sandy loam, the pH at the root surface fell by more than 2 units, whereas in the Maahas soil (Figure 6.16), a less-weathered humic clay, it fell by only 0.2 units. Apart from differences in the rate of acidity generation, the Maahas soil had a greater initial pH and a greater organic C content resulting in a greater CO2 pressure when flooded. These together result in faster acidity diffusion through the soil. The continuity equation for diffusion of acidity in the soil surrounding a root is (Equation 2.32 expressed in radial coordinates)
 ∂pH d pH 1 ∂ = rDHS (6.12) ∂t r ∂r dr where DHS is the soil acidity diffusion coefficient, given by: DHS =

2.303θL fL (DLH [H3 O+ ] + DLC [HCO3 − ]) bHS

(6.13)

The explanation of Equation (6.13) is that a small portion of soil near the root may gain acidity either by access of H3 O+ (S— + H3 O+ = S—H+ + H2 O) or by dissociation of CO2 and removal of HCO3 − though the soil solution (S— + H2 CO3 = S—H+ + HCO3 − ) (Section 2.2). Since [H3 O+ ] and [HCO3 − ] are both sensitive to pH, the rate at which pH changes are propagated is also sensitive to pH and passes through a minimum in the pH range 4.5–6.0 where [H3 O+ ] and [HCO3 − ] are both small. In this pH range, therefore, a flux of acid or base through the soil causes steep pH gradients. Figure 6.17 shows pH profiles calculated with Equations (6.12) and (6.13) with parameters appropriate for a rice root in anaerobic soil. The pH change at the root surface is small at pHs above neutral because DHS is large, and it increases towards the pH at which DHS is minimal. Because of this, the combined effect of the two sources of acidity in the rice rhizosphere is greater than the sum of their effects in isolation. So in spite of θL fL and the CO2 pressure both being large in submerged soils, if the rate of generation of acidity is sufficiently large there may be substantial pH changes at the root surface. These effects are summarized

195

Root-Induced Changes in the Soil 7.5 7.0 6.5

pH

6.0 5.5 5.0 4.5 4.0 0.0

0.5

1.0

1.5

2.0

2.5

3.0

Distance from root surface (mm)

Figure 6.17 Calculated pH profiles around a rice root exporting acid into anaerobic soil at different initial pHs. Other parameter values: H+ flux across root = 2.5 nmol dm−2 s−1 , root radius = 0.2 mm, pH buffer power = 0.05 mol dm−3 pH−1 , CO2 pressure = 1 kPa, θL = 0.7, fL = 0.4, time = 12 days (after Nye, 1981)

Change in pH at root surface

0.00 initial pH

−0.25

flux of H+

−0.50

pH buffer power

−0.75 −1.00 CO2 pressure

−1.25 −1.50

6.0

6.5

7.0

7.5

initial pH 0.00

0.02

0.04

0.06

0.08

0.10

pH buffer power (mol kg−1 pH−1) 0.0

0

0.5

1

1.0 1.5 CO2 pressure (kPa) 2

3

2.0

4

5

flux of H+ across root (nmol dm−2 s−1)

Figure 6.18 Sensitivity of pH change at root surface to important variables, varied individually. Standard values as in Figure 6.17 with initial pH = 6.75

196

Processes in Roots and the Rhizosphere

in Figure 6.18, which shows the sensitivity of the pH change at the root surface to the flux of H+ across the root and the important soil variables. 6.5 CONSEQUENCES OF ROOT-INDUCED CHANGES Effects of the root-induced changes on the general microbiology of submerged soils are discussed in Chapter 5 and effects on methane production and consumption are discussed in Chapter 8. I here discuss specific effects on plant nutrients. 6.5.1 NITRIFICATION–DENITRIFICATION IN THE RHIZOSPHERE As we have seen in Section 6.4, wetland rice is particularly efficient at absorbing NO3 − . Kirk and Kronzucker (2000) developed a model to calculate the extent to which rice growing in submerged soil can capture NO3 − formed in the rhizosphere before it diffuses away and is denitrified in the soil bulk. The model allows for the following processes. (1) Transport of O2 away from a root and its consumption in microbial processes—in addition to nitrification—and oxidation of mobile reductants such as Fe2+ . Microbial O2 consumption is described with Michaelis–Menten kinetics and Fe2+ oxidation with first-order kinetics with respect to both [O2 ] and [Fe2+ ]. (2) Transport of NH4 + towards the root and its consumption in nitrification and uptake at the root surface. Nitrification is described with dual Michaelis– Menten kinetics allowing for [O2 ] and [NH4 + ]. (3) Transport of NO3 − formed from NH4 + towards the root and its consumption in denitrification and uptake by the root. Denitrification is described with Michaelis–Menten kinetics with an inhibition function related to [O2 ]. Uptake of NH4 + and NO3 − into the root are described by Michaelis–Menten relations with the parameter values discussed in Section 6.3. Figure 6.19 shows the concentration profiles of O2 , Fe2+ , NH4 + and NO3 − near a root calculated with this model for realistic flooded soil conditions and realistic rates of O2 release (last section); Figure 6.20 shows the corresponding fluxes of O2 out of the root and NH4 + and NO3 − in. The amount of N denitrified in 10 days in the calculations corresponds to about 10 % of the NH4 + initially in the volume of soil influenced by the root. This is of the order of maximum rates of denitrification reported in the literature for rice in flooded soil, indicating that the model parameter values are indeed realistic. The calculations indicate that quite large amounts of NO3 − may be absorbed by rice in flooded soils, perhaps as much as a third of the total N absorbed if soil conditions and water management prevent very thorough soil reduction. This may explain, for example, the benefit of the elaborate water management

197

Consequences of Root-Induced Changes

Solution O2, NH4+, NO3− conc. (µM)

NH4+

60

990 Fe2+

980

40 970

O2 20

960

Solution Fe2+ conc. (µM)

1000

80

NO3− 0

0

1 2 Distance from root surface (mm)

3

950

1.2 O2 1.0

+,

−

Flux of O2 out or NH4 NO3 or N in (nmol dm−2 s−1)

Figure 6.19 Calculated concentration profiles of O2 , NO3 − , NH4 + and Fe2+ in a flooded soil near a rice root after 10 days of root–soil contact. The parameter values used in the calculations are realistic for a healthy root growing in an unexceptional lowland rice soil (Kirk and Kronzucker, 2000). Reproduced by permission of IRRI

0.8 0.6 N

0.4

+

NH4 NO3−

0.2 0.0

0

2

4

6

8

10

Time (days)

Figure 6.20 Calculated fluxes of O2 , NO3 − and NH4 + across the root over time. Parameter values as in Figure 6.19

schemes practiced for rice in parts of China and Japan, involving intermittent drainage of water from the fields during the season (Section 7.2 and Figure 7.4). But further research is needed to quantify how far mixed NH4 + –NO3 − nutrition operates under field conditions and its benefits to rice growth. 6.5.2 SOLUBILIZATION OF PHOSPHATE Deficiency of P is often the main nutrient limitation in natural wetlands, though it is rarely important in wetland rice soils that have at least some history of P

198

Processes in Roots and the Rhizosphere

fertilization. Phosphate tends to be solubilized by the electrochemical changes following soil submergence, but with prolonged submergence it may become re-immobilized as reduced phases are precipitated (Section 4.3). Some of this P might be re-solubilized by root-induced oxidation of the rhizosphere soil. On the other hand, precipitation of amorphous Fe(OH)3 close to and on rice roots might be expected to immobilize P from the soil solution, impeding its access to the roots. Saleque and Kirk (1995) measured concentration profiles of P and other rootinduced changes near planar layers of rice roots growing in a highly weathered P-deficient soil to which different amounts of P had been added (Figure 6.21). In both P-fertilized and -unfertilized soil, the quantity of readily plant-available P was negligible, so it was necessary for the plants to solubilize P. Some 90 % of the P taken up was drawn from acid-soluble pools, probably associated with Fe(II) carbonates and hydroxides. There were also narrow zones of P accumulation in an alkali-soluble pool which coincided with zones of Fe(OH)3 accumulation near the roots. The zone of P depletion coincided with a zone of acidification, caused by the processes discussed in Section 6.4. Kirk and Saleque (1995) showed with a model of this system that the acidification and the Psolubilizing effect of acidity in the soil were sufficient to account for the P mobilized and absorbed by the roots. Solubilization accounted for at least 80 % of the P taken up in both the P-unfertilized and -fertilized soil, though only about half the P solubilized was absorbed because the rest diffused away from the roots. The amount of P solubilized greatly exceeded the amount immobilized on Fe(OH)3 precipitated near the roots. This is an extreme example, involving particularly large pH changes, but it indicates the magnitude of the effects that are possible. By contrast, when a submerged soil is dried and oxidized, immobilization of P on the ferric oxide formed may be the dominant process and plants may become severely P deficient (Section 4.3). Huguenin-Elie et al. (2003) investigated the mechanisms by which rice growing in alternately submerged and drained soils extract P by measuring uptake from moist, flooded or flooded then moist soils and comparing the results with model calculations allowing for solubilization by various means. In all three water regimes the plants relied on solubilization for most of their P. The roots were not mycorrhizal, as they will often not be in intermittently flooded soils. In the moist soil, the uptake was only a third of that in the flooded soils and was consistent with solubilization by organic anion excretion from the roots, which appears to be the mechanism by which upland rice in aerobic soil extracts P (Kirk et al., 1999; Trolove, 2000). In the submerged then moist soil, uptake declined sharply as the soil dried because P became immobilized. The final uptake was similar to that in the continuously moist soil, indicating that some of the immobilized P was re-solubilized by roots, possibly by excretion of organic anions.

199

Consequences of Root-Induced Changes

1.2

P50 2.0

P50 P15

0.8

1.6 P15

P0

0.4

1.2 P0

0.0

0.8

P extracted (µmol g−1)

2.0

0.7 Alkali-Po

Acid-2-P

1.9

P50

0.6

1.8

P15

0.5

1.7 0.4

P0

1.6 1.5

0.3 85 75

Fe(II)

25

65

15

55

5

P0

5.5 5.0

P15

pH

Fe(III)

35

6.0 Fe(III) (µmol g−1)

45 Fe(II) (µmol g−1)

P extracted (µmol g−1)

2.4

Alkali-Pi

Acid-1-P

P extracted (µmol g−1)

P extracted (µmol g−1)

1.6

4.5

P50

4.0

45 0

2

4

6

8

10

3.5 0

2

4

6

8

10

mm from root plane

Figure 6.21 Profiles of P, Fe and pH near a planar layer of rice roots in contact with flooded soil fertilized containing 0, 15 or 50 mg P kg−1 for 6 weeks. The P pools measured sequentially were: readily available P extracted by anion-exchange resin (negligible at all P levels and therefore not shown); readily acid-soluble P (Acid-1-P), extracted by anion-exchange resin + H+ -form cation-exchange resin; alkali-soluble inorganic P (Alkali-Pi ), by 0.1 M NaOH; alkali-soluble organic P (Alkali-Po ), by digesting the previous extract and subtracting the alkali-soluble inorganic P; the more recalcitrant acid-soluble P (Acid-2-P), by 1 M HCl + 1 M H2 SO4 . (Differences between P levels not significant for Fe and Alkali-Po ) (Saleque and Kirk, 1995). Reproduced by permission of Blackwell Publishing

200

Processes in Roots and the Rhizosphere

6.5.3 SOLUBILIZATION OF ZINC Zinc is often highly insoluble in submerged soils and Zn deficiency is an important constraint to rice production throughout Asia (Chapter 7). In similar experiments to those in the last section, Kirk and Bajita (1995) measured changes in Zn pools near rice roots in anaerobic soil (Figure 6.22) and simultaneous changes in Fe(II), Fe(III) and pH (Figure 6.16). As for P in the soil in Figure 6.21, the concentration of easily extractable Zn in the soil was negligible following flooding and it was necessary for the plants to solubilize Zn to meet their requirements. Zinc was mobilized from highly insoluble forms in the soil and re-precipitated with Fe(OH)3 and organic matter within 4–5 mm of the roots. The accumulation continued over time but simultaneously there was a substantial depletion of the accumulated fractions within 2 mm of the roots. The zones of accumulation and depletion coincided with zones of Fe(III) accumulation and soil acidification. The authors concluded that Fe oxidation released Zn from highly insoluble forms and that this Zn was re-adsorbed on Fe(OH)3 and on organic matter in forms that were acid-soluble and therefore accessible to the plants. An additional benefit of acidification of the soil close to the root may be to lower the concentration of HCO3 − in solution. High HCO3 − impairs Zn absorption (Dogar and Hai, 1980), its translocation to the shoot (Forno et al., 1975), root growth (Yang et al., 1994), or all three. The modest decrease in pH near the roots in Figure 6.16 (from pH 7.35 to 7.1) is equivalent to a two-fold increase in H+ concentration and if the CO2 pressure is constant a two-fold decrease in HCO3 − concentration. There may also be effects via the concentrations of competing cations at the root surface. In studies of short-term uptake of 65 Zn by rice from nutrient solutions containing realistic Zn2+ concentrations, Giordano and Mortvedt (1974) found uptake was inhibited by various metabolic inhibitors and by Fe2+ , Mn2+ , Ca2+ and Mg2+ as Cl− salts at typical concentrations in flooded soil solutions. Translocation of absorbed Zn was also inhibited by Fe2+ and Mn2+ but not by Ca2+ or Mg2+ . Cayton et al. (1985) also found antagonistic effects of competing cations on Zn uptake. Absorption involves preferential binding of Zn2+ at cation exchange sites in the root cell walls prior to active uptake across the plasma membrane. Preferential binding concentrates Zn2+ at the sites of active uptake, and would be sensitive to the concentrations of competing cations. But it is not clear whether competition for exchange sites or for transporters in the plasma membrane is the more important (Reid et al., 1996). 6.5.4 IMMOBILIZATION OF CATIONS Metal cations in the soil solution may be immobilized by sorption onto iron ‘plaque’ on root surfaces in submerged soils, in the same way that solubilized Zn2+ was re-adsorbed on ferric oxide in the experiments in Figure 6.22. Sequestering of metals on the external surfaces of wetland roots in this way limits uptake

0.0

0.1

0.2

0.3

0.4

0

2

4

CBD

CuAc Acid NH4Ox

6

KCl

8

10

0 days

12

0

(b)

2

6

8

mm from root plane

4

Hypothetical profile if no uptake

10

6 days

12

0

(c)

2

4

6

8

10

12 days

12

Figure 6.22 Profiles of Zn fractions in anaerobic soil near a planar layer of rice roots after indicated times of root–soil contact. The dashed lines are the hypothetical profiles if no Zn had been removed by the plants, estimated by interpolation of the lines beyond the depletion zones. Corresponding profiles of Fe(II), Fe(III) and pH are in Figure 6.16 (Kirk and Bajita, 1995). Reproduced by permission of Blackwell Publishing

[Zn] in indicated pool (mmol kg−1)

(a)

201

202

Processes in Roots and the Rhizosphere

of metal pollutants into the vegetation (Otte et al., 1989; St-Cyr and Crowder, 1990; Ye et al., 1997a, b; Hansel et al., 2001). In soils with small pH buffer powers, root-induced acidification may also impede access of cations to roots, though it may diminish sorption onto oxides as the surface negative charge decreases (Razafinjara, 1999). This is because the overall concentration of the soil solution in a submerged soil depends largely on the concentration of HCO3 − , buffered by dissolved CO2 . Therefore, if the pH close to the root decreases below about 6.0, the concentration of anions in solution also decreases and so the concentration of cations in solution and hence their rate of diffusion to roots must decrease [Bouldin (1989) gives calculations of this effect]. This may happen, for example, in ‘iron toxic’ soils which develop large concentrations of Fe2+ in solution. High rates of Fe2+ oxidation and associated H+ generation result in a low pH in the rhizosphere, especially if the soil is already acid or has a small pH buffer power. Hence the need to exclude toxic Fe2+ from the root by oxidizing it in the rhizosphere may impair the absorption of nutrient cations by the root. Consistent with this the symptoms of iron toxicity are often alleviated by applications of K salts. A further complication is that the lowering of the rhizosphere pH and consequent depression of HCO3 − means that any Fe2+ entering the root will be accompanied by a proportion of Cl− or SO4 2− rather than HCO3 − . When Fe2+ enters with HCO3 − , the acidity generated in Fe2+ oxidation in the plant is neutralized by conversion of HCO3 − to CO2 , which is assimilated or lost. However when Fe2+ enters with a non-volatile anion, Fe2+ oxidation will produce the equivalent amount of free H+ in the plant, with damaging effects on plant tissues (van Mensvoort et al., 1985). 6.6 CONCLUSIONS This chapter has shown the complexity of the chemical and biological processes around wetland plant roots and the effects of the extreme electrochemical gradient between the root surface and surrounding soil. Models of nutrient uptake by plants in aerobic soil, which treat the root as a simple sink to which nutrients are delivered by mass flow and diffusion but the root not otherwise influencing the surrounding soil, work reasonably well for the more soluble nutrient ions. However, the complexity of the wetland root environment is such that such models are inadequate and more elaborate treatments are necessary. Many of the mechanisms involved are still poorly defined and speculative, but their potential significance is clear.

7 Nutrients, Toxins and Pollutants

This chapter is concerned with the different types of wetland soil as sources, sinks and transformers of nutrients, particular nutrient deficiencies and mineral toxicities that commonly arise following submergence, and the fate of pollutants that are commonly added to submerged soils, both accidentally and intentionally.

7.1 NUTRIENT AND ACIDITY BALANCES As discussed in Chapter 1, the nutrient supplies of submerged wetland soils have a number of special features compared with upland soils. Nutrient removal in leaching and erosion tend to dominate the nutrient balance of upland soils. In wetlands, inputs from inflowing water tend to exceed leaching losses, and erosion does not occur. Rates of fixation of nitrogen from the atmosphere under wet conditions with a good supply of other nutrients are also often greater, though so too are losses through denitrification. Wetlands are therefore often net sinks for nutrients, and this is reflected in their generally high productivity. However there are large differences between the different wetland types and between locations.

7.1.1 NUTRIENT BALANCES IN RICEFIELDS The fact that rice production has sustained huge human populations on the river deltas of Asia for millennia is an indication of the favourable nutrient balance in wetland ricefields. Prior to 1960 and the green revolution, yields were sustained without artificial inputs of nutrients, other than by recycling through manures and night soil. The requirements of the crop were met by the inflow of nutrients and fertile sediments with floodwaters and by nitrogen fixation. The greatly increased yields since 1960 are sustained by inputs of mineral fertilizers. Figure 7.1 shows how increases in the yields of rice (and wheat) have been paralleled by increases in the use of nitrogen fertilizers since 1960 to keep pace with world population. Greenland (1997) has compiled realistic average annual nutrient balances for wetland ricefields pre- and post-1960 from probable inputs and outputs. Inputs come from rainfall, R, irrigation and floodwater, F , sediments, S, nitrogen fixation, N , and manures and fertilizers, M. Outputs are due to crop removals in The Biogeochemistry of Submerged Soils Guy Kirk  2004 John Wiley & Sons, Ltd ISBN: 0-470-86301-3

204

1.8

180

4.0

1.6

160

3.6

1.4

140

Population (billions)

1.2 4

arable area 1.0

3

rice

0.8 0.6

2 wheat 1

fertilizer N

2.8 120 2.4 100 2.0 80 1.6 60 1.2

0.4

40

0.2

20

0.0

0

population irrigated area

0

1860 1880 1900 1920 1940 1960 1980 2000 Year AD

3.2

Fertilizer N (Mt)

5

Arable or irrigated area (Gha)

6

0.8

World average rice and wheat yields (t ha−1)

Nutrients, Toxins and Pollutants

0.4 0.0

Figure 7.1 Increases in world population, arable area, average yields of rice and wheat, amount of fertilizer N used, and the irrigated area of the world (Evans, 1997). Reproduced by permission of the Royal Society

rice grain and straw and legumes, C, seepage and percolation, S, and gaseous emission, G. Therefore the balance, B, is B = (R + F + S + N + M) − (C + P + G)

(7.1)

Macronutrients The macronutrient balances for irrigated rice are shown in Figure 7.2. Pre-1960, there were no inputs from mineral fertilizers though manures were applied, but there were substantial inputs from sediments borne by the irrigation water, which was obtained by stream diversion. The sediment supplied the bulk of the annual P and K inputs, and the bulk of the N was derived from biological fixation in the soil and floodwater during the rice crop and in legume crops following the rice. The calculation is for a single rice crop of 2 t ha−1 of grain and 3 t ha−1 of straw and 0.5 t ha−1 of legume, all removed from the field. The figure shows that the balances of N and K are positive but that of P substantially negative. A positive balance for P is attained with a crop of 1 t ha−1 of rice grain if the straw is retained.

205

Nutrient and Acidity Balances Irrigated rice before 1960

R F

12

100

S

10

80 Cg

N

8

R F

Cs

6

40

Cs

4

20

Cl

2

0

P G

S

K (kg ha−1)

Cg P (kg ha−1)

N (kg ha−1)

120

60

180

14

140

160

R

140

F

120

Cg

100 80

S

Cs

60

Cl

40 M In

M 0

Out

In

Cl

20

P

0

Out

P

M In

Out

Irrigated rice after 1960

R F

40

N

Cg

200 Cs 100

Cl P

M

P (kg ha−1)

N (kg ha−1)

300

50

300 250

R F

Cg

30 Cg 20

M

In

Out

200 150

Cs

100 Cs 10 Cl P

G 0

K (kg ha−1)

400

0

In

Out

50 0

Cl

R F

P In

Out

Figure 7.2 Typical annual nutrient balances for irrigated rice soils pre- and post-1960 calculated from probable inputs (left side of each graph) and outputs (right side) (data from Greenland, 1997). Inputs come from R = rainfall, F = floodwater and irrigation, S = sediments, N = nitrogen fixation and M = manures and fertilizers. Outputs are due to removals in Cg = rice grain, Cs = rice straw, Cl = legume crop, S = seepage and percolation and G = gaseous emission

Post-1960 and the green revolution, much larger quantities of nutrients are removed in intensive double and sometimes triple rice cropping. The irrigation water is now often obtained by storage in reservoirs behind high dams and delivered through artificial channels so the sediment settles out of the water and no longer reaches the ricefields with its load of nutrients. However there are now much larger additions of nutrients in mineral fertilizers. A greater proportion of the mineral fertilizer N is lost through gaseous emissions, and, because under multiple cropping the soil is flooded for more of the year, percolation losses are greater, particularly of K.

206

Nutrients, Toxins and Pollutants

The minimum quantity of nitrogen that the crop must accumulate to produce 1 t of rough rice is of the order of 16–18 kg, though efficiencies are lower at low yield levels (Cassman et al., 1998; Dobermann et al., 2002). Thus 8 t of rice per ha requires 128–144 kg N ha−1 . Experiments without additions of N in a wide range of rice environments over many years have shown that from 50–80 kg N ha−1 can be accumulated from soil reserves that are replenished by biological N fixation and crop residues. For higher yields, additional N must be provided from sources outside the ricefield, either as organic manures or mineral fertilizers. The calculations in Figure 7.2 are for a rice–rice–legume cropping system removing 8 t ha−1 of rice grain (3 in the wet season, 5 in the dry), 8 t ha−1 of straw (i.e. a harvest index of 0.5 compared with 0.4 in the pre-1960 varieties) and 1 t ha−1 of legume. A positive balance is maintained for N and P, but because there are no additions of K fertilizer and no additions with sediment, there is a steady depletion of soil K reserves: 195 kg ha−1 year−1 if straw is removed or 35 kg ha−1 year−1 if retained. Such a picture is not unrealistic, and yield limitations due to K deficiency in irrigated rice systems are becoming increasingly common across Asia (Dobermann et al., 1996). The importance of mineral fertilizers in sustaining intensive rice production is evident. Figure 7.3 shows corresponding balances for rainfed rice systems. Here the yields are more modest: 2, 3 and 0.5 t ha−1 of rice grain, straw and grain legume, respectively, for rainfed lowland rice; 2 and 8 t ha−1 of grain and straw for floodprone rice; and 1, 2 and 0.5 t ha−1 of grain, straw and grain legume for upland rice. The nutrient budgets are correspondingly smaller. In rainfed lowland rice, as for the pre-1960 irrigated rice, positive balances are maintained for N and K but a negative balance for P; a positive P balance is maintained if only 1 t ha−1 of rice is harvested and the straw retained in the fields. The supplies of P and K in sediment are critical. In flood-prone rice the balances of all three nutrients are negative if straw is removed, but roughly balanced if it is retained. Nitrogen fixation in the deep, low P water is diminished, and the supplies of N, P and K in sediment are crucial. In upland rice, the N, P and K balances are again all negative, even for yields of only 1 t ha−1 . Few soils are sufficiently fertile to withstand such withdrawals for very long, hence the importance of the restorative fallow for several years in shifting cultivation systems based on upland rice. Secondary and Micronutrients In the colluvial and alluvial soils of the main rice producing areas, the amounts of calcium and magnesium deposited in irrigation and floodwaters, especially if they carry sediment, usually far exceed crop removals (Greenland, 1997; Dobermann and Fairhurst, 2000). Deficiencies do however occur in rainfed lowland rice, especially on highly weathered soils where they are compounded by deficiencies of other nutrients. The only secondary nutrient that is commonly removed in greater amounts than it is supplied in inflowing water is sulfur. Deficiencies of

207

Nutrient and Acidity Balances Rainfed lowland rice 120

60 Cg 40

N

R 6 4

Cs

S

20 0

2 Cl V In

100 80

Cg S

60 Cs

40

Cs

M

R F

120

Cg 8

K (kg ha−1)

80

140

10

R F S

P (kg ha−1)

N (kg ha−1)

100

160

12

Cl

M 0

Out

In

20 0

Out

Cl

M In

Out

Flood-prone rice 80

12

250

10

20

Cs

F

6

R F

150

F Cs

100 S

Cs 2

N In

R

4

S 0

8

K (kg ha−1)

R

Cg P (kg ha−1)

N (kg ha−1)

40

Cg

200

Cg

60

0

Out

50

S

In

0

Out

In

Out

Upland rice 100

80

10 Cg

Cg

8

60 Cg

40

Cl R

P (kg ha−1)

N (kg ha−1)

Cs 60

6 Cs

4

Cl

P 20

2 N

0

G In

Out

40

In

Out

Cs

20

P

R 0

K (kg ha−1)

80

Cl P

R 0

In

Out

Figure 7.3 Typical annual nutrient balances for rainfed rice soils from probable inputs (left side of each graph) and outputs (right side) (data from Greenland, 1997). Inputs come from R = rainfall, F = floodwater and irrigation, S = sediments, N = nitrogen fixation and M = manures and fertilizers. Outputs are due to removals in Cg = rice grain, Cs = rice straw, Cl = legume crop, S = seepage and percolation and G = gaseous emission

208

Nutrients, Toxins and Pollutants

sulfur have become more widespread as rice yields and the intensity of cropping have increased (Dobermann et al., 1998). However, while deficiencies of sulfur in crops in Europe have increased in recent decades as deposition from industrial pollution has decreased, deficiencies are being offset in rice in large parts of Asia by increasing emissions from industry and the large-scale burning of forest. Though it is not strictly an essential nutrient, rice plants accumulate very large amounts of silicon–shoot contents typically exceeding 5 %–and this has various beneficial effects on the plant (Savant et al., 1997). Silicon adds to the mechanical strength of cell walls, confers resistance to certain pests and diseases, and is thought to offset abnormalities in the supply of certain other nutrients. Deficiencies occur in highly weathered soils from which the soluble silicon has been leached, and in organic soils with low mineral reserves. More widespread incidences are expected as rice cropping continues to intensify (Dobermann and Fairhurst, 2000). Of the essential micronutrients (Fe, Mn, Zn, Cu, B and Cl), deficiency of zinc is the most commonly reported (Quijano-Guerta et al., 2002). Generally the amounts of zinc and other micronutrients brought in with irrigation water, rainfall and sediments are more than sufficient to offset crop removals. Deficiencies arise as a result of particular changes in the soil following submergence causing immobilization (Section 7.2). Such problems become more acute the greater the rate of removal in cropping, and increases in incidences of Zn deficiency are expected with the advent of Zn-dense rice for improved human nutrition (Welch and Graham, 1999). 7.1.2 ACIDITY BALANCES IN RICEFIELDS A further reason for the long-term sustainability of wetland rice farming is that the soils tend not to become acid after continuous, intensive cultivation. In cultivated upland soils, acidification occurs because of the leaching of the NO3 − ion. Nitrification of NH4 + added in mineral fertilizers produces 2 mol of H+ per mol of NH4 + nitrified (Table 7.1, Process 3). If some of the NO3 − is subsequently leached from the soil accompanied by an exchangeable cation, 2H+ are left behind per mol of NO3 − leached, acidifying the soil. Because in general little or no NO3 − is leached through submerged rice soils, any NO3 − entering the soil or formed in it being either absorbed by the crop or denitrified, this process does not occur. The removal of fertilizer N in the crop as NH4 + does not lead to acidification. Hydrolysis of urea fertilizer—by far the main form of N fertilizer used in wetland rice, together with ammonium bicarbonate in some countries—consumes 1 mol of H+ per mol of NH4 + formed (Table 7.1, Process 1). So although absorption of N as NH4 + leads to a net export of H+ from the roots to balance the resulting excess intake of cations over anions (Table 7.1, Process 5), this acidity is matched by the H+ consumed in urea hydrolysis. Likewise there is no net generation of acidity as a result of NH3 volatilization, although 1 mol of H+ is left behind per mol of NH4 + converted to NH3 (Table 7.1, Process 3).

209

Nutrient and Acidity Balances Table 7.1 Acid–base changes in nitrogen transformations in ricefields Process 1. Hydrolysis of urea fertilizer CO(NH2 )2 + 2H+ + H2 O → 2 NH4 + + CO2 2. NH3 volatilization NH4 + → NH3 + H+ 3. Nitrification NH4 + + 2CO2 + H2 O → NO3 − + 2CH2 O + 2H+ 4. Denitrification 4NO3 − + 5CH2 O + 4H+ → 2N2 + 5CO2 + 7H2 O 5. Removal of NH4 + in cropa 426CO2 + 12 NH4 + + H2 PO4 − + 408H2 O → C426 H855 O426 N12 P + 414O2 + 11H+


[H+ ]
[N] −1 +1 +2 −1 +0.92

a

Based on data of Dobermann and Fairhurst (2000) for mean mineral content of grain (for clarity, K+ , Ca2+ , Mg2+ , SO4 2− , Cl− , etc. omitted).

Nitrification of the NH4 + does not cause net acidification, whether the NO3 − is absorbed by the crop or denitrified. Two mol of H+ are formed per mol of NH4 + nitrified, resulting in a net addition of one H+ per urea-N hydrolysed. If the NO3 − is absorbed by the crop, 1 mol of OH− is exported from the roots per mol of NO3 − absorbed, or if it is denitrified, 1 mol H+ is formed per mol of N denitrified (Table 7.1, Process 4). Note that the anaerobic processes causing pH changes following submergence—reduction of ferric iron tending to increase the pH of acid soils and accumulation of CO2 tending to decrease the pH of alkaline soils—are reversed upon drainage and reoxidation of the soil. Thus, unless there has been substantial movement of acid or base out of the soil during submergence, as generally there will not have been, the pH changes are reversed. Permanent changes of pH only occur if the concentration of acid or base in the water entering the ricefield differs from that leaving it. Ferrolysis An exception to these general rules is the formation of so-called ferrolysed soils (Brinkman, 1970; van Breemen and Buurman, 1998). These occur under particular hydrological and geological conditions in which there is prolonged seasonal waterlogging of the soil and subsequent drainage as the regional water table falls. Dissolved Fe2+ formed in soil reduction displaces cations from the soil exchange complex, and these are subsequently removed in leaching or runoff. When the soil dries, adsorbed Fe2+ is oxidized producing acidity which reacts with the soil. The resulting H+ -saturated clay is unstable and partly decomposes to give Al-saturated clay and silica. Repeated cycles of this process can lead to

210

Nutrients, Toxins and Pollutants

near complete removal of weatherable minerals. The effects are most marked in soils derived from acidic rocks or strongly weathered sediments. Large wetland areas in south and south-east Asia have soils of this sort (Brammer and Brinkman, 1977; Brinkman, 1977a, b), but doubt has recently been cast on the importance of ferrolysis in European soils previously thought to have been formed by it (van Ranst and De Coninck, 2002). 7.1.3 PEAT BOGS At the opposite end of the fertility scale from ricefields are peat bogs in pluvial landscapes. Nutrient inputs come almost entirely from rainfall, and the nutrient reserves in the organic matter buffering the soil solution are small (Moore and Bellamy, 1974). The chemistry of peat bogs is therefore precarious and changes in the composition of the rainfall can have a large effect on the composition of the soil solution. Bogs are naturally acid. This is an inevitable consequence of their development. The principal source of acidity is the intake of mineral nutrients by the vegetation. Because the main forms of N absorbed under the anoxic conditions are NH4 + or N2 fixed from the air, the plants absorb more cations than anions and consequently export H+ from their roots to maintain electrical neutrality. At steady state the input of organic matter from primary production at the bog surface is balanced by loss of organic matter by decomposition throughout the profile (Clymo, 1984). But because by definition bogs largely comprise undecomposed plant material, at steady state there is a substantial and effectively permanent accumulation of alkalinity in the organic matter and of acidity in the soil. The process is self reinforcing: the greater the acidity that develops, the more the CEC of the organic and mineral matter in the peat is dominated by H+ and the weaker its ability to retain nutrient cations. Deposition of nitric or sulfuric acids in rainfall will add to the acidity. Subsequent denitrification and sulfate reduction generate an equivalent amount of base, so this acidity is neutralized. The acidity of wetland peats is discussed by Ross (1995). An example of the fragile nutrient balance in peat bogs is given in Table 7.2 for a blanket bog in northern England. The table shows the losses of N through erosion of the peat, and the losses of nutrient cations through leaching and removal in stream water. 7.1.4 RIPARIAN WETLANDS Riparian wetlands are those lands that are periodically inundated with water from adjacent rivers, streams, lakes or other freshwater bodies, and by runoff from upland areas. Large fluxes of energy and nutrients pass through riparian wetlands and they are important sinks and transformers of nutrients. In watersheds with extensive riparian wetlands, the composition of the river water may

211

Nutrient and Acidity Balances Table 7.2 Nutrient balance for blanket peat bog in the Pennines, northern England Amount (kg ha−1 year−1 )

Input Precipitation Output Sale of sheep Dissolved in stream Peat erosion in stream Net loss

Na

K

Ca

P

N

25.5

3.1

9.0

0.69

8.2

0.0 45.3 0.3 20.0

0.0 9.0 2.1 8.0

0.0 53.8 4.8 49.7

0.01 0.39 0.45 0.15

0.1 2.9 14.6 9.5

Source: data from Crisp (1966).

be dominated by transformations in the wetlands (Olson, 1992; Mitsch and Gosselink, 2000). There are large seasonal variations depending on the water flow and the state of the riparian vegetation. But in general inorganic forms of nutrients are transformed to organic forms and nitrate is denitrified. These transformations and losses have important consequences for the productivity of aquatic systems downstream. The terms in the nutrient balance of a riparian wetland are essentially the same as those in a traditional wetland ricefield in a river floodplain or delta, though of course the magnitudes differ. Inputs are delivered along the stream course as dissolved material and sediment, and in lateral runoff from neighbouring upland; dissolved and particulate material is filtered, absorbed, adsorbed and variously transformed in the wetland, and flows out in runoff and percolation. As for ricefields, additions from sediment vary very widely. The amount carried and its composition will depend on the landscape through which the river has flown and its soils and geology, and rainfall characteristics. The amount deposited will in turn depend on the local landscape and conditions, including the nature of the vegetation filtering and trapping the sediment. Table 7.3 compares additions of P in sediment in riparian wetlands in North America with those estimated for ricefields in Asia. The generally greater additions in North American sediments and the very large variations are apparent. Riparian wetlands are effective though not infinite sinks for nitrate and phosphate from agricultural runoff. Strips of wetland a few tens of metres wide have been shown to remove the bulk of nitrate and phosphate entering in runoff and groundwater, though the limits to this under different circumstances are not well quantified (Baker and Maltby, 1995; Mitsch and Gosselink, 2000). 7.1.5 TIDAL WETLANDS The balance in tidal wetlands is complicated by the tidal inflow and outflow of water across the submerged sediments and the greater influence of subsurface leaching under the large tidal head of water.

212

Nutrients, Toxins and Pollutants

Table 7.3 Additions of P in sediments in ricefields in Asia and riparian wetlands in North America Rate of deposition (g m−2 year−1 ) Ricefields in Asia Calculated from contents of tropical soils and assumed high sedimentation rate (1 kg m−2 year−1 ) Calculated from measured sediment contents and assumed high sedimentation rate Measured additions Guangdong, China Bangladesh deepwater sites Mekong delta Riparian wetlands in North America Southern Illinois Central Florida North Carolina North Carolina from input–output balance Northwestern Illinois

0.4–0.7 0.4–1.1 0.06 0.2 0.1 3.6 3.25 0.17 0.32–0.73 1.36

Sources: ricefields, Greenland (1997); others, Mitsch and Gosselink (2000).

Nutrient balances in tidal wetland systems have been studied at length and the picture is variable. In general the net exchanges are small in relation to the overall nutrient budgets, though nutrients may be transformed between dissolved and particulate inorganic and organic forms and oxidation states (Nixon, 1980; Childers et al., 2000; Mitsch and Gosselink, 2000). Nitrogen generally flows into the marsh largely as nitrate but is exported in dissolved and particulate reduced forms, and is denitrified. Table 7.4 shows a representative N budget, obtained in a large tidal salt marsh in Massachusetts. Though surface water inflows were not measured, there is a rough balance between inflows and outflows. The tidal exchange is far greater than any of the other components. Tidal marshes tend to be net sinks for total phosphorus, entering in estuarine water in dissolved organic and inorganic forms but there may be a remobilization of inorganic phosphate leached out of sediments by saline water.

7.2 TOXINS 7.2.1 ACIDITY In general high acidity and resulting high concentrations of toxic aluminium in solution do not occur in submerged soils because the electrochemical changes accompanying submergence tend to neutralize acidity present in the unflooded soil. Acid sulfate soils are a notable exception.

213

Toxins Table 7.4 Nitrogen budget of a tidal salt marsh in Massachusetts Flow (g N m−2 year−1 ) Inputs Surface water Rainfall Biological N fixation Groundwater Tidal inflow

? 0.8 6.5 27.0 116.0 150.3

Outputs Denitrification Tidal outflow

13.3 140.0 153.3

Source: data from Mitsch and Gosselink (2000).

Acid Sulfate Soils Acid sulfate soils are an especially difficult class of acid soil formed in former marine sediments that have been drained. The acidity is generated from the oxidation of pyrite in the soil resulting in acute aluminium toxicity, iron toxicity, and deficiencies of most nutrients, especially phosphate which becomes immobilized in ferric oxide. The development and management of acid sulfate soils are discussed in detail in Dost and van Breemen (1983) and Dent (1986). In brief, the steps in the formation of pyrite in marine sediments are: (1) reduction of Fe(III) in the sediment to soluble Fe2+ and reduction of SO4 2− from seawater to S2− ; (2) partial oxidation of S2− to elemental S or polysulfide, S2 2− ; (3) formation of pyrite, FeS2 , either directly from Fe2+ and S2 2− or via FeS formed from Fe2+ and S2− and subsequent reaction with S. The overall reaction is 2Fe2 O3 + 8SO4 2− + 16CH2 O + O2 → 4FeS2 + 16HCO3 − + 8H2 O

(7.2)

The necessary conditions are sources of iron oxide, dissolved SO4 2− and organic matter, and sufficiently reducing conditions for reduction of SO4 2− coupled to intermittent or localized oxidizing conditions to produce elemental S or polysulfide. Potential acidity develops by the removal of alkalinity (represented by HCO3 − in Equation 7.2) from the sediment by diffusion and tidal action. What

214

Nutrients, Toxins and Pollutants

little is known about rates of pyrite formation under natural conditions indicates rates of a few kg S m−3 of sediment in 100 years under mangrove vegetation in stationary or slowly aggrading coastal plains. Potential acid sulfate soils ripen into actual acid sulfate soils as a result of drainage and oxidation of the pyrite, forming sulfuric acid. The reaction between pyrite and oxygen is slow, but oxidation of FeS2 by Fe(III) in solution is fast producing Fe(II). This process is catalysed at low pH by the bacterium Thiobacillus ferrooxidans which mediates the oxidation of sulfur species and Fe(II), so regenerating Fe(III) and facilitating further FeS2 oxidation. The process requires acid conditions because Fe(III) is insufficiently soluble at pH greater than about 4 and because the growth of T. ferrooxidans is inhibited at higher pH. The overall reaction is 4FeS2 + 15O2 + 14H2 O → 4Fe(OH)3 + 8SO4 2− + 16H+

(7.3)

Most of the Fe(III) eventually crystallizes as reddish-brown ferric oxide in mottles, coatings and nodules. Under strongly oxidizing severely acid conditions, pale yellow coatings of the mineral jarosite, KFe3 (SO4 )2 (OH)6 , may form on ped faces. At higher pH, jarosite is hydrolysed to goethite. Hence ripe acid sulfate soils often have a layer of yellow jaorosite mottling adjacent overlying a still-reduced pyrite layer but overlain by layers from which acidity has been leached, and hence dominated by reddish-brown goethite. These features are used to assess the ripening of the soil. 7.2.2 IRON TOXICITY Iron toxicity is a syndrome of disorders associated with large concentrations of Fe2+ in the soil solution. It is only found in flooded soils. A wide range of concentrations produce the symptoms, from 1000 to only 10 mg L−1 in soils with poor nutrient status—especially of P or K—or with respiration inhibitors such as H2 S. There are large differences in tolerance between rice varieties. The effects include internal damage of tissues due to excessive uptake of Fe2+ ; impaired nutrient uptake, especially of P, K, Ca and Mg; and increased diseases associated with imbalanced nutrition, such as brown leaf spot (caused by Helminthosporium oryzae), sheath blight (caused by Rhizoctonia solani ) and blast (caused by Pyricularia oryzae). The circumstances of the toxicity are quite well established, though some of the details of the mechanisms involved are uncertain. Three main groups of Fe toxic soils are distinguished: • acid sulfate soils, in which extremely large concentrations of Fe2+ in the soil solution arise as a result of the soils’ peculiar mineralogy; • poorly drained sandy soils in valleys receiving interflow water from adjacent higher land with highly weathered sediments; and

215

Toxins

• more clayey, acid, iron-rich soils in sediments derived from highly weathered soils and which give iron toxicity without interflow. Where Fe toxicity is associated with interflow the concentrations of dissolved Fe in the upwelling water have been found to be too small to account for the large concentrations of Fe2+ in the root zone, and most of the Fe2+ is apparently formed in situ. Therefore the interflow aggravates toxicity by some mechanism other than bringing in Fe2+ , possibly involving depletion of other nutrients and upsetting the plant’s ability to exclude Fe (Section 6.5). It is often a symptom of imbalanced nutrition rather than high Fe2+ in the soil solution per se. Thus the soil solution Fe2+ concentrations at which it is reported vary from 10 to 1000 mg L−1 , and it is more often associated with low levels of P, K, Ca and Mg and impaired ability of roots to exclude Fe2+ . 7.2.3 ORGANIC ACIDS Decomposition of organic matter in submerged soils produces phytotoxic compounds such as aliphatic and phenolic acids (Takajima, 1964; Tsutsuki and Ponnamperuma, 1987). Many of the potentially phytotoxic compounds are produced only transiently, so it is difficult to assess the damage they cause. The most certain effects are seen in rice soils to which large quantities of organic manures are added, especially under temperate conditions. As a result, in ricefields in Japan and China, where organic manures are widely used, to avoid accumulation of phytotoxins in the root zone, greater percolation rates are maintained—5 to 10 mm day−1 compared with 1 to 5 mm day−1 elsewhere—and water is often completely drained from the fields midseason (Figure 7.4). This is less critical in tropical countries because higher temperatures allow the toxins to be decomposed more rapidly, and the use of organic manures is less.

Water depth

June

5 cm (Submergence) 4 3 2 1

Soil moisture

May

90% 80 70 60 50

(Intermittent drainage)

July

August

Sept.

(Intermittent irrigation)

Soil surface

(Midsummer drainage)

Figure 7.4 Water management in ricefields in Japan and parts of China (modified from Yukawa, 1989). Reproduced by permission of the Japanese Society of Irrigation, Drainage and Reclamation Engineering

216

Nutrients, Toxins and Pollutants

Research on the effects of phenolic acids on rice has measured effects on seed germination and rates of root elongation and seedling growth. This has shown that concentrations greater than a few mM of the more noxious acids are required to substantially impair root elongation (Olofsdotter et al., 2002). Under tropical conditions, without large additions of organic matter, total concentrations of alkali-soluble phenolic acids in the soil during rice cropping are generally less than this (Tsutsuki and Ponnamperuma, 1987), though concentrations may be greater locally, such as in the rhizosphere. Factors that exacerbate the toxic effects of phenolic acids include low plant N status (Vaughan and Ord, 1990); low soil pH, the undissociated acid having greater membrane permeability (Tanaka and Navaesero, 1967); and the nature of the acid, cinnamic acid derivatives being more inhibitory than benzoic acid derivatives, and lipid-soluble acids being more inhibitory than lipid-insoluble (Glass, 1973). Little research has been done on the effects of phenolic acids on ion uptake by rice roots, but ion uptake is presumably impaired at much smaller concentrations than root elongation. Recent experiments at the International Rice Research Institute (IRRI) on the maximum yields of high-yielding rice cultivars developed over the last 40 years have shown that the older cultivars no longer perform as well as they used to (Peng et al., 2000). The first modern high-yielding cultivar released by IRRI, IR8, which often produced 9–10 Mg of grain ha−1 at the IRRI farm in the 1960s under optimal management, now yields only 7–8 Mg ha−1 under similar conditions, whereas its most recent successors yield 9–10 Mg ha−1 . This does not appear to be due to deterioration in seed stocks over the years through repeated multiplication cycles (Peng, unpublished), or to new or increased pests or diseases. It appears that new abiotic stresses have arisen over the 40 years of continuous rice cropping on the IRRI farm, with two or three crops per year in flooded soil, and the more recent cultivars may be better adapted to these stresses. Changes in soil conditions have been observed, most notably changes in the nature of the soil organic matter associated with prolonged soil flooding and more strongly reducing conditions in the soil, particularly increased concentrations of phenolic compounds (Olk and Senesi, 2000). The decrease in grain yield of the older cultivars is associated with poor grain filling and harvest index, and impaired acquisition of soil nitrogen. A possible explanation is that the changes in soil conditions have led to impaired root function in the older cultivars through toxins associated with prolonged soil flooding, such as phenolic or other organic acids. 7.2.4 SALINITY Salinity occurs in coastal areas affected by seawater, in areas receiving salty water by lateral flow from salt-bearing rocks upstream, and also in otherwise non-saline environments as a result of soil waterlogging, mainly due to high ground water. In waterlogged land, whatever dissolved salt is brought in with the

Toxins

217

water necessarily accumulates. Even good quality water contains 200 mg L−1 of soluble salts, so, for example, a ricefield receiving 1000 mm of irrigation water will accumulate 2 t ha−1 of salt per year (Greenland, 1997). Also, salts in subsoils and groundwater in waterlogged land may be brought into the surface by mass flow and diffusion. In land that is flooded for part of the year but drains naturally after the floodwater recedes, accumulated salt is removed with the draining water and there is a natural renewal of the land. Percolation and lateral drainage at the start of the following rainy season but before the land is re-flooded also wash out accumulated salt. However this natural recovery is prevented if the water table remains above or close to the surface. This may happen in depressions, but also where large reservoirs have been established at a higher elevation than the flood-prone land, or where an unlined canal that carries a large volume of water has been built on permeable soil (Greenland, 1997). Such problems are more common in arid or semi-arid areas where there is both less leaching of the soil and groundand irrigation-waters are more likely to be saline. A further problem associated with waterlogging and salinity is sodicity. When the quantity of Na+ in the soil exceeds about 15 % of the CEC, the soil may become dispersed, i.e. aggregation is lost, and it will then dry to large tough clods. Salts in groundwater are often high in Na+ , so sodicity may be a problem even though salinity is not. Sodic soils are not necessarily problematic for wetland rice cultivation, though rates of percolation may be sub-optimal but they are difficult to cultivate for following dryland crops. About 5 Mha of tidal wetlands are cultivated with rice (IRRI, 2002). Although this is only a small part of the 147 Mha of land currently cropped with rice globally, there is some scope for expanding the area in response to increasing demand for rice and loss of more favourable land to non-rice uses (Greenland, 1997). There is also a need to improve the productivity of existing tidal rice areas to relieve pressure to clear marginal lands. The principal soil chemical stress in tidal wetlands is high salinity. Rice is only moderately tolerant of salt and is more sensitive to it than some cereals (Flowers and Yeo, 1981; Yoshida et al., 1983). The sensitivity varies over the growth cycle being most acute in the seedling stage and again during flowering. Although there are large differences in tolerance between cultivars, none are tolerant of salt throughout the growing season (Flowers et al., 2000; Gregorio et al., 2002). The suitability of rice for coastal saline areas therefore arises from its tolerance of soil submergence rather than exceptional salt tolerance: because it can tolerate soil submergence, and because flooding with less saline water dilutes the salt in the soil, rice will grow on land not able to support dryland crops. In addition, various other soil chemical stresses are prevalent. These include alkalinity, acidity, Fe toxicity, and deficiencies of P, Zn and other nutrients, typically in combination. Quijano-Guerta and Kirk (2002) discuss the tolerance of rice germplasm to the multiple soil chemical stresses in tidal wetlands.

218

Nutrients, Toxins and Pollutants

7.3 TRACE ELEMENTS 7.3.1 GLOBAL CYCLING OF TRACE ELEMENTS Wetlands are important in the cycling of trace metals and metalloids, firstly because they are often in high rainfall areas and receive correspondingly high additions by wet deposition; secondly because fluxial and phreatic wetlands receive large volumes of surface and ground water bearing dissolved and particulate trace elements; and thirdly because of their particular biogeochemistry which results in transformations and accumulation of trace elements. Concentrations of trace elements in surface and ground waters are controlled by deposition from the atmosphere and dissolution from soils and bedrock. Concentrations in the atmosphere arise from anthropogenic sources—fossil fuel combustion, cement production, extractive metallurgy—as well as through natural processes—windborne soil, volcanic ejecta, forest fires, biogenic processes. Depending on the metal, transport through the atmosphere and subsequent wet or dry deposition may exceed transport through surface and ground water. Elements for which atmospheric transport predominates are termed atmophile and those for which transport by water predominates are termed lithophile (Stumm and Morgan, 1996). Many atmophile metals are volatile or can become volatile through methylation, especially the B-type metals (Section 3.1) Hg, As and Pb. By contrast the A-type metals—Mn, Co, Cr, V and Ni—are lithophile. Hence Btype metals tend to be enriched in the environment through diffuse atmospheric pollution (Table 7.5). They also tend to be pernicious toxins because of their tendency to react with soft bases, such as –SH and –NH groups in enzymes.

7.3.2 TRANSPORT OF TRACE ELEMENTS THROUGH SOIL AND INTO PLANT ROOTS The factors controlling the transport through soil include: • • • •

the concentration of the free ion in solution; complexation with organic and inorganic ligands in solution; redox reactions; sorption on organic matter, clay minerals and oxides in the soil solid in outersphere and highly insoluble inner-sphere complexes; • precipitation and co-precipitation in insoluble compounds, particularly hydroxides, carbonates, sulfides or phosphates; • sorption, precipitation and co-precipitation in suspended colloids; • conversion to volatile forms. Because the importance of these factors differs between the different trace elements, predicting mobilities is complicated. The tendency to form organic

219

Trace Elements

Table 7.5 Global emissions of trace metals to the atmosphere and concentrations in freshwater Emissions (kt year−1 )a,b

Antimony Arsenic Cadmium Chromium Cobalt Copper Lead Manganese Mercury Molybdenum Nickel Selenium Vanadium Zinc

Natural

Anthropogenic

Total

Concentration in freshwater (µ g L−1 )c Mean (range)

2.6 12 1.4 43 6.1 28 12 317 2.5 3.0 29 10 28 45

3.5 19 7.6 31 35 332 38 3.6 52 6.3 5.1 5.1 86 132

6.1 31 9.0 74 41 360 50 320 54 9.3 34 15 114 177

0.2 (0.01–5) 0.5 (0.2–230) 0.1 (0.01–3) 1 (0.1–6) 0.2 (0.04–8) 3 (0.2–30) 3 (0.06–120) 8 (0.02–130) 0.1 (0.0001–2.8) 0.5 (0.03–10) 0.5 (0.02–27) 0.2 (0.02–1) 0.5 (0.01–20) 15 (0.2–100)

Sources: a Nriagu (1989). b Nriagu and Pacyna (1988). c Bowen (1979).

complexes increases in the order (Chapter 3): Cd < Zn < Co  Ni = Cu < Hg and the tendency to form strongly sorbed, inner-sphere complexes with oxides and clays increases in the order: Cd < Ni < Co < Zn  Cu < Hg The tendency to co-precipitate in secondary minerals also differs. Typical coprecipitates are (Sposito, 1983): Fe oxides Mn oxides Ca carbonates Clay minerals

V, Mn, Ni, Cu, Zn, Mo Fe, Co, Ni, Zn, Pb V, Mn, Fe, Co, Cd Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Pb

These differences are exemplified in Figure 7.5 which shows the results of an experiment in which Cd2+ , Zn2+ , Ni2+ and Cu2+ salts were applied on the surface of an acid soil, with and without lime, and the soil leached with 0.01 M CaCl2 for several hours (McBride, 1994). In the unlimed soil, Cd2+ , Zn2+ and Ni2+ moved readily to depth, but Cu2+ remained near the surface because it was strongly sorbed on soil solids. In the limed soil, with pH 6.5, increased sorption and

220

Nutrients, Toxins and Pollutants 0

Cu

Depth (cm)

10

Cu Zn

20

Ni

Cd

30

Zn/Ni Cd

unlimed

limed

40 Relative concentration of adsorbed metal

Figure 7.5 Profiles of surface-applied metals in acid soil, with and without lime and leached with 0.01 M CaCl2 (McBride, 1994). Reproduced by permission of Oxford University Press

precipitation of all four metals resulted in retarded leaching. The attenuation of Cd2+ , Zn2+ and Ni2+ leaching could be accounted for with a model allowing for simple, pH-dependent cation exchange. The results for Cu2+ required allowance for more-selective chemisorption and chelation reactions with highly nonlinear concentration dependence. The bioavailability of trace elements is further complicated by differences in the factors controlling transport to plant roots. These are: • desorption or dissolution from the soil solid, which may be slow compared with transport to roots, and complexation in solution; all of these may be affected by root-induced changes in the soil, which may both increase and decrease the solubilities of trace elements; • diffusion through the soil solution, especially as complexes with carrier ligands; • absorption across the root surface by passive and active transporters, including for ions complexed with carrier ligands; • translocation from root to shoot: cationic trace elements especially may accumulate on and in roots. 7.3.1 MOBILITIES OF INDIVIDUAL TRACE ELEMENTS In the following sections the biogeochemistries of important trace metals and metalloids in submerged soils are discussed. They are important either because of their redox chemistries or because they are particularly affected by soil redox

Trace Elements

221

conditions. The list is not exhaustive but it serves to illustrate the important processes. The properties of the elements are summarized in Table 7.6 and Table 7.7 gives the important redox equilibria.

Zinc Zinc occurs in soils exclusively in the +2 oxidation state and in solution as the B-type cation Zn2+ . It is weakly complexed by the main functional groups in organic matter, but under sulfate-reducing conditions forms insoluble sulfides (ZnS, pK = 24.7). In intermittently submerged soils, such as wetland rice soils, ZnS probably generally does not form because FeS and FeS2 are precipitated at a higher pe + pH and hence will form preferentially if the redox is poised by Fe(II) (Sajwan and Lindsay, 1986). Under such conditions Zn2+ forms solid solutions in oxides and clay minerals (see below). Hence it tends to be highly immobile under anaerobic conditions, but under acid oxidizing conditions it is released in soluble and mobile forms. Zinc solubility in soils tends to show a minimum at near neutral pH (Figure 3.14). At low pH the free ions are only weakly sorbed on charged soil surfaces, but at pH > 7, as concentrations of dissolved organic ligands increase, soluble Zn—organic complexes may form, raising the total concentrations of Zn in solution even though the activity of the free ion may be extremely small through sorption reactions. At high pH Zn2+ forms solid solutions in Ca and Mg carbonates, and mixed hydroxy-carbonates, so it is immobile and unavailable to plants in alkaline or calcareous soils. Zinc deficiency is widespread in wetland rice affecting up to 50 % of the area (Katyal and Vlek, 1985; Welch et al., 1991; Batten et al., 1992; Neue and Lantin, 1994). Zinc relations in rice have therefore been studied extensively. The deficiency is most often associated with poor drainage and perennial soil wetness. The soils typically have weak profile development, reflecting the poor drainage, and much of the Zn is in primary minerals or in other highly insoluble forms. It is also often associated with high soil organic matter content, high pH and high Mg:Ca ratios in the soil. All of these factors are present in the toposequence at Tiaong, Quezon Province, Philippines shown in Figure 7.6, which has been used for many years by the IRRI to screen rice for Zn deficiency tolerance (Quijano-Guerta et al., 2002). The toposequence is on the gently sloping foot-slope of a young inactive volcano, Mt Banahaw. The drainage is poor across the toposequence due to perennial upwelling of artesian water. The extent of Zn deficiency increases down the slope, as do soil wetness, organic C content, CaCO3 content and CEC. The pH, clay content and extractable Zn are uniform. The upwelling water contains high concentrations of Ca2+ , Mg2+ , HCO3 − and H4 SiO4 of volcanic origin. As it reaches the surface, CO2 degasses causing the pH to rise. This results in precipitation of CaCO3 and possibly de novo synthesis of Mg smectities, on and in which

Cr

[Ar]3d54s1 1.66 3,6

[Ar]3d54s2 1.55 2,3,4

Mn

VIIA

25

Fe

[Ar]3d64s2 1.83 2,3

26

VIIIA Co

[Ar]3d74s2 1.88 2(,3)

27

VIIIA Ni

[Ar]3d84s2 1.91 2(,3)

28

VIIIA [Ar]3d104s1 1.90 (1,)2

Cu

IB 29

[Xe]4f145d106s2 2.00 (1,)2

80Hg

[Kr]4d105s2 1.69 2

Cd

48

[Ar]3d104s2 1.65 2

Zn

IIB 30

82Pb

IVB

[Xe]4f145d106s2p1 [Xe]4f145d106s2p2 2.04 1,3 2.33 2(,4)

81TI

[He]2s2p1 2.04 3

B

5

IIIB

Groups classified by original IUPAC system. For each element: second row gives electron configuration, third gives electronegativity and important oxidation states.

[Ar]3d34s2 1.63 4,5

V

VIA

24

VA

23

Table 7.6 Properties of trace metals and metalloids important in submerged soils

As Sb [Kr]4d105s2p3 2.05 3,5

51

[Ar]3d104s2p3 2.18 3,5

33

VB

Se [Ar]3d104s2p4 2.55 −2,4,6

34

VIB

222

223

Trace Elements

Table 7.7 Equilibrium constants of reduction half-reactions of trace elements in submerged soils compared with those for Fe and Mn pe0

pe0∗ pH 5

pH 7

16.9

6.9

2.9

5.7

−4.3

V VO2 + + 2H+ + e− 2+

VO

+

+ 2H + e

= VO2+ + H2 O

−

=V

3+

+ H2 O

+

+

(note also VO2 + 2H2 O = VO(OH)3 + H , pK = 3.3; VO(OH)3 = VO2 (OH)2 +H+ , pK = 4.0; VO2 (OH)2 − = VO3 (OH)2− + H+ , pK = 8.55) Cr 1 HCrO4 − + 4H+ + e− 3 −

= 13 Cr(OH)3 + 13 H2 O +

(note also HCrO4 = H + CrO4

2−

18.9

10.6

−8.3 −

7.9

, pK = 6.5)

Mn 1 Mn3 O4 (s) 2

+ 4H+ + e−

MnOOH(s) + 3H+ + e− + 2H+ + e−

1 MnO2 (s) 2

= 32 Mn2+ + 2H2 O

30.8

16.3

8.3

= Mn2+ + 2H2 O

25.3

14.0

8.0

= 12 Mn2+ + 2H2 O

21.8

13.7

9.7

= Fe2+ + 3H2 O

16.5

4.5

−1.5

= Fe

11.3

−0.7

−6.7

= Co2+

30.6

30.6

30.6

= 12 Ni2+ + H2 O

29.8

22.3

18.3

2.6

2.6

2.6

= 12 Hg2 2+

15.4

15.4

15.4

=

1 Hg 2

14.4

14.4

14.4

= Tl2+

21.3

21.3

21.3

= 12 Pb2+ + H2 O

24.8

17.3

13.3

Fe Fe(OH)3 (s) + 3H+ + e− +

−

α-FeOOH(s) + 3H + e

2+

+ 2H2 O

Co Co3+ + e− Ni 1 NiO2 (s) 2

+ 2H+ + e−

Cu = Cu+

Cu2+ + e− Hg Hg2+ + e− 1 Hg2+ 2

−

+e

Tl Tl3+ + e− Pb 1 PbO2 (s) 2

+ 2H+ + e−

As (continued overleaf )

224

Nutrients, Toxins and Pollutants

Table 7.7

(continued ) pe0

pe0∗ pH 5

+ 2H+ + e−

1 HAsO4 2− 2

= 12 H3 AsO3 + 12 H2 O −

14.9

4.9

−

+

(note also H3 AsO4 = H2 AsO4 + H , pK = 2.24; H2 AsO4 = HAsO4 pK = 6.94; HAsO4

2−

= AsO4

3−

pH 7

2−

0.9 +

+H ,

−

+

+ H , pK = 11.5; H3 AsO3 = H2 AsO3 + H+ ,

pK = 9.29) Sb 1 SbO3 − 2

+ 32 H+ + e−

= 12 Sb(OH)3

11.3

3.8

0.8

(note also Sb(OH)3 + H+ = Sb(OH)2 + + H2 O, pK = −1.42; Sb(OH)3 + H2 O = Sb(OH)4 − + H+ , pK = 11.82) Se 1 SeO4 2− 2 1 SeO3 2− 4 1 SeO3 2− 6

+ H+ + e− 3 + H 2 +

+

= 12 SeO3 2− + 12 H2 O

14.9

9.9

7.9

+e

=

14.8

6.0

3.0

−

=

0.3

-1.7

−

+H +e

1 4 1 6

Se(s) + Se

−

2−

+

3 H O 4 2 1 H O 2 2

+

5.3 −

(note also H2 SeO3 = HSeO3 + H , pK = 2.4; HSeO3 = SeO3 SeO4

2−

+

2−

+

+ H , pK = 7.9;

−

+ H = HSeO4 , pK = −1.7)

I IO3 − + 6H+ + 6e− 1 I (aq) 2 2

−

+e

= I− + 3H2 O −

=I

18.3

13.3

11.3

10.5

10.5

10.5 ∗

Sources: pe0 values calculated with Equation (4.8) using
G0f values from Garrels and Christ (1965). pe0 values calculated with Equation (4.22) for conditions in submerged soil solutions: for trace element ions, (ion) = 10 µM, (Mn2+ ) = 0.2 mM, (Fe2+ ) = 1 mM. Constants for hydrolysis equilibria from Baes and Maesmer (1976).

Zn2+ becomes strongly immobilized as solid solutions (van Breemen et al., 1980; Scharpenseel et al., 1983). The formation of [Ca,Mg,Zn]CO3 solid solutions in submerged rice soils would explain the association between Zn deficiency and soils with high Mg:Ca ratios.

Cadmium Like Zn, Cd is a Group IIB element and occurs in soils exclusively in the +2 oxidation state as the Cd2+ cation. Cadmium and zinc are often co-precipitated with each other in sulfide minerals in rocks (pKCdS = 27.0). Hence Cd tends to be highly immobile under anaerobic sulfate-reducing conditions, but under acid, oxidizing conditions it is released in soluble and mobile forms. Hence soils

41

42

43

44

45

41

42

43

44

45

41

42

43

44

0

<0.5

2−3

CaCO3 content (%)

100

200

<1

4− 5

300

No rice grown (shrubs and grasses)

Extent of Zn deficiency

2.5−3.5 0.5−1.5 1.5−2.5 3.5−4

3−4

Organic C content (%)

Zn deficiency (weak, moderate, strong, very strong) Experimental fields

<1

Artesian well

1−2

400 m

Zn deficiency (strong, weak, none)

< 0.5

Depth of observation

3 −4

SW

Figure 7.6 Toposequence at Tiaong, Quezon Province, Philippines, showing extreme Zn deficiency in rice (van Breemen et al., 1980). Reproduced by permission of Kluwer Academic Publishers

NE m above sea level

45

225

226

Nutrients, Toxins and Pollutants

that contain toxic concentrations of Cd when aerobic may be entirely suitable for wetland rice cultivation (Takijima and Katsumi, 1973; Bingham et al., 1976). The Cd content of rice grain in Cd-contaminated soil has been found to be correlated with the number of days the soil is drained prior to harvest (Page et al., 1981). Cobalt, Nickel and Copper Cobalt and nickel are Group VIIIA and copper Group IB elements. They occur predominantly in the +2 oxidation state in soils as divalent cations, though Co2+ may be oxidized to Co3+ forming very insoluble compounds with Mn oxides, and Cu2+ may be reduced to Cu+ , especially if soft bases such as halides and S2− are present to stabilize the Cu+ ion. All are chalcophiles and tend to form insoluble sulfides in anaerobic conditions (pKs = 21.3–25.6, 19.4–26.6 and 36.1, respectively). They therefore tend to have low mobilities in submerged soils, especially Cu2+ , and accumulate. All are strongly sorbed on soil surfaces, increasingly as the pH increases, and are more strongly bound to functional groups in organic matter than Cd2+ or Zn2+ . They therefore tend to show the minimum in solubility at near neutral pH discussed for Zn. Ni2+ and Cu2+ form highly stable complexes with organic matter, especially with ligands containing N and S, and they therefore tend to accumulate in organic soils. Mercury Mercury occurs in soils predominantly in the +2 oxidation state. Elemental Hg in the atmosphere is oxidized to Hg2+ and deposited in rainfall. It is a strong chalcophile and under anaerobic conditions forms the extremely insoluble sulfide cinnabar (HgS, pK = 52.7). Nonetheless it is not entirely immobilized under anaerobic conditions because it is reduced to volatile Hg0 or methylated to volatile methyl mercury compounds by microbial action, and so returned to the atmosphere. The methylation is mediated by various bacteria, especially methanogens, through the reactions: methylation

Hg2+ −−−−−→ CH3 Hg+ methylation

CH3 Hg+ −−−−−→ (CH3 )2 Hg ↑ Other volatile methyl mercury compounds, such as (C6 H5 )2 Hg, are also formed. The CH3 Hg+ unit is very inert with respect to decomposition. Therefore, once formed, methyl mercury compounds are not readily demethylated. The biogeochemistry of Hg in the environment is reviewed by Ridley et al. (1977) and Mason et al. (1993).

Trace Elements

227

The chemistry of Hg in aerobic soils is also complicated and so it is difficult to make general predictions about its mobility. The Hg2+ cation is B-type and forms strong bonds with soft ligands such as the sulfhydryl group (–SH) and S2− anion, but not with the main functional groups in organic matter (Section 3.1). In aerobic soil it is therefore likely to be immobile at trace concentrations but moderately mobile at greater concentrations (McBride, 1994). However the mobility also depends on pH. At pH > 4, the predominant form in solution is Hg(OH)2 0 , which is little sorbed on soil surfaces, but at pH > 7 Hg2+ is precipitated as Hg(OH)2 and HgCO3 . Concentrations of Hg in the global atmosphere (Slemr et al., 1985; Slemr and Langer, 1992; Mason et al., 1994) and deposited in ice and lake sediments (Weiss et al., 1971; Swain et al., 1992) are increasing, probably due to industrial activity. Accumulations of Hg in soils and sediments tend to correlate with soil organic matter content, and the greatest natural accumulations are in peaty and submerged soils. Though submerged soils are sinks for Hg as HgS, they are also the main source of methyl mercury in the environment (St Louis et al., 1994).

Vanadium Vanadium occurs in soils predominantly as the +5 vanadate species (VO(OH)3 0 , VO2 (OH)2 − and VO3 (OH)2− ) and under reducing conditions as the +4 vanadyl cation (VO2+ ). Less commonly V3+ may also form and substitute for Fe3+ in minerals. Interchange between these oxidation states with redox conditions greatly alters the solubility of V in soils. The vanadate equilibria are given in Table 7.7. The VO2 (OH)2 − and VO3 (OH)2− anions are sorbed on positively charged sites on oxides and silicates at low pH, but sorption decreases with pH as the surface positive charge decreases. Consequently V is quite soluble at high pH and less soluble at low pH. Reduced V(IV) is much less soluble. The VO2+ cation behaves like Cu2+ and forms strong complexes with organic ligands and is chemisorbed on oxides and silicate clays. The V4+ ion is isomorphously substituted for Si4+ and Al3+ in kaolinite (Gehring et al., 1993). Hence the mobility of V under reducing or acid conditions is expected to be low. Reduction of VO2 + to VO2+ occurs at pe0∗ = 6.9 pH 5 and 2.9 at pH 7 (Table 7.7) and so requires only weakly reducing conditions. A wide range of heterotrophic bacteria and fungi is capable of reducing V(V) (Bautista and Alexander, 1972).

Chromium Chromium occurs in soils predominantly as the immobile +3 chromic cation (Cr3+ ), but may be oxidized to or added as +6 chromate species (CrO4 2− , HCrO4 − ). Chromate is weakly sorbed on soils and is highly toxic to

228

Nutrients, Toxins and Pollutants

plants and animals, whereas Cr(III) is more strongly sorbed, forms complexes with organic matter and precipitates as insoluble Cr(OH)3 at high pH, and is far less toxic. Oxidation of Cr(III) to Cr(VI) by O2 is slow, but oxidation by Mn oxides is thermodynamically favourable under acid conditions: in Table 7.8, pe0∗ values at pH 5 for reduction of Mn(III,IV) oxides are greater than for reduction of Cr(VI). This process is catalysed by sorption of Cr(III) onto Mn oxide surfaces (Eary and Rai, 1987). However it is slower than analogous reactions with other species that have been studied (As(III) → As(V) and Se(IV) → Se (VI)) because oxidation of Cr(III) is less thermodynamically favourable and because Cr3+ is less strongly sorbed on positively-charged Mn oxides at low pH (Scott and Morgan, 1996). Chromate is reduced to Cr(III) in dissimilatory microbial reactions, but this process is inhibited at moderate concentrations of C(VI) and so is probably of limited value in detoxifying soils contaminated with Cr(VI) (Lovley, 1993). However, Cr(VI) can also be reduced to Cr(III) abiotically by oxidation of Fe(II): Fe(III) in ferric oxide is reduced to Fe(II) biotically: 4Fe(OH)3 + CH2 O + 8H+ −−−→ 4Fe2+ + CO2 + 11H2 O subsequently Cr(VI) is reduced abiotically to Cr(III) as Fe(II) is re-oxidized to Fe(III): 3Fe2+ + HCrO4 − + 8H2 O −−−→ 3Fe(OH)3 + Cr(OH)3 + 5H+ Wielinga et al. (2001) demonstrated this process by incubating goethite anaerobically at pH 7 with lactate and an iron-reducing bacterium, and introducing Cr(VI) after commencement of Fe(III) reduction (Figure 7.7). In treatments without Cr(VI), accumulation of Fe(II) in solution continued, but in the treatments with Cr(VI) it was reversed; in abiotic controls there was no accumulation of Fe(II). Chromate can also be reduced abiotically by sulfide. Boron Boron occurs in soil predominantly as the uncharged B(OH)3 , though at high pH B(OH)3 is converted to B(OH)4 − (pK = 9.0), which forms insoluble Ca salts. It may therefore be deficient to plants in acid soils in humid regions, as a result of B(OH)3 leaching, or in calcareous soils as a result of precipitation in Ca salts. By contrast, in alkaline soils in arid regions, soluble Na borate salts may accumulate. Boron toxicity in rice is quite commonly reported where irrigation water is obtained from deep groundwater in dry seasons (Ponnamperuma and Yuan, 1966; Cayton, 1985; Ayers and Westcot, 1989). Thallium Thallium occurs in soils in both +3 and +1 oxidation states. Tl3+ behaves much like Al3+ , but hydrolyses even more readily and insoluble Tl(OH)3 is formed

229

Trace Elements

[Fe 2 + ] in solution (mg L−1)

70 60 50

Cr(VI) not added

40 30

Cr(VI) added

20 10

Abiotic control

0 0

20

40

60

80

Time (h) Start of Cr(VI) addition

Figure 7.7 Abiotic reduction of toxic Cr(VI) to Cr(III) by Fe(III) (Wielinga et al., 2001). Reproduced by permission of the American Chemical Society

at pH < 2 and remains stable to pH > 10. The mobility of Tl3+ in aerobic soil is therefore expected to be low. Under moderate reducing conditions Tl3+ is reduced to Tl+ (pe0 = 21.3, independent of pH). The reduced Tl+ behaves very differently, acting more like an exchangeable alkali metal cation. However incorporation into sulfide minerals may limit its solubility and mobility.

Lead Lead occurs mainly in the +2 oxidation state in soils, but it may be oxidized to Pb4+ . It is the least mobile heavy metal in soils. In aerobic soils it is chemisorbed on clays and oxides; forms complexes with organic matter, especially with Scontaining functional groups; and forms insoluble hydroxides, carbonates and phosphates. All of these increase with pH, so solubility is greatest under acid conditions. In anaerobic soils it is precipitated as the highly insoluble sulfide galena (PbS, pK = 27.5). It may also be methylated into volatile forms.

Arsenic and Antimony Arsenic and antimony are Group VB elements and both occur in soils predominantly in +3 and +5 oxidation states and they have similar redox and sorption behaviour. The oxidized forms are rather insoluble in soils and the reduced forms much more soluble.

230

Nutrients, Toxins and Pollutants

The oxidized form of As, arsenate, As(V), which is present as HAsO4 2− at neutral pH (pK values in Table 7.8), is sorbed on soil surfaces in a similar way to orthophosphate. The reduced form arsenite, As(III), which is present in solution largely as H3 AsO3 (pK1 = 9.29), is only weakly sorbed, hence mobility tends to increase under reducing conditions. Mobility will also increase without reduction of As(V) because, as for phosphate, reductive dissolution of iron oxides results in desorption of HAsO4 2− into the soil solution. Under prolonged submergence As(III) may be co-precipitated with sulfides. Additionally, like Hg, As is converted into volatile compounds in microbially catalysed reactions that are sensitive to pH and redox conditions (Fowler, 1983). Under strongly reducing conditions methyl- and alkyl-arsine compounds may form, resulting in loss of As to the atmosphere. The resulting cycle of reactions is complex but involves in anaerobic soil: reduction

H3 AsO3 −−−−→ AsH3 ↑ methylation

H3 AsO3 −−−−−→ (CH3 )3 As ↑ and on diffusion of (CH3 )3 As into oxic zones, methylation

(CH3 )3 As −−−−−→ (CH3 )3 HAsO ↑ Also in oxic zones, methylation

methylation

AsO4 3− −−−−−→ CH3 HAsO3 −−−−−→ (CH3 )3 HAsO ↑ Re-oxidation of As(III) to As(V) under oxidizing conditions is fast and is catalysed by sorption onto oxides with the oxide metal acting as oxidant (Scott and Morgan, 1995). Reductive dissolution of Fe oxyhydroxides holding sorbed As appears to explain the very large concentrations of As in water from wells drilled into alluvial sediments of the Brahmaputra and Ganges Rivers in Bangladesh and West Begal (Nickson et al., 1998, 2000). Dissolved As has accumulated from the reduction of As-rich Fe oxyhydroxides formed upstream of the contaminated areas by weathering of As-rich base metal sulfides. The reduction is driven by sedimentary organic matter in the deposits. Release of As from oxidation of pyrite in shallow wells contributes little to the water contamination because any As(IV) released would be re-sorbed on Fe oxides formed in pyrite oxidation. The HAsO4 2− ion is taken up by plant roots by the same transport systems as H2 PO4 − , leading to excessive uptake and toxicity in plants growing on soils with high arsenate levels (Meharg and Hartley-Whitaker, 2002). However the extent of uptake varies greatly between soil conditions and plant species (Marin et al., 1993; Onken and Hossner, 1995; Schm¨oger et al., 2000). Presumably under

Trace Elements

231

anaerobic conditions As(OH)3 is absorbed passively in the transpiration stream, and so because of the far greater solubility in soil of As(OH)3 than HAsO4 2− , As should accumulate in plants more rapidly under flooded conditions than under drained aerobic conditions. In rice, the disease ‘straighthead’ is repeatedly linked to moderate As concentrations in the plant (Horton et al., 1983) and this may limit the accumulation of As in rice grain. The redox and sorption behaviour of Sb is similar, but no volatile forms are produced. The oxidized form of Sb, antimonite, Sb(V), has the anionic form Sb(OH)6 − at pH > 4, and is sorbed on oxides and silicate clays. The reduced form, antimonite, Sb(III), is present as the uncharged Sb(OH)3 molecule except at very low or very high pH where the Sb(OH)2 + cation and Sb(OH)4 − anion form, respectively. The uncharged Sb(OH)3 is little sorbed on soil surfaces.

Selenium Selenium has a complex chemistry in the environment because of its multiple oxidation states and variable surface adsorption properties. Qualitatively it is analogous to sulfur occurring in the oxidation states +6 (selenate, SeO4 2− ), +4 (selenite, SeO3 2− ), 0 (elemental selenium) and −2 (Se2− , selenide) The Se2− anion closely resembles S2− (radii 0.20 and 0.185 nm, respectively) and is often associated with sulfide minerals. Also, like S, Se is subject to volatilization through biological methylation. Under oxidizing conditions SeO4 2− is the thermodynamically favoured form (for the reduction SeO4 2− → SeO3 2− , pe0∗ = 7.9 at pH 7—Table 7.8) and under mildly reducing conditions SeO3 2− is the favoured form (for SeO3 2− → Se, pe0∗ = 3.0 at pH 7). Since SeO3 2− is strongly sorbed on oxides and precipitates as Fe2 (SeO3 )3 , whereas SeO4 2− is only weakly sorbed, especially at high pH, this leads to large changes in solubility. Hence toxic concentrations of Se tend to occur in alkaline soils in arid and semi-arid regions, and irrigation of such soils may move SeO4 2− into groundwater. Microbially mediated reductions of SeO4 2− to SeO3 2− and of SeO3 2− to elemental Se have been documented in a wide variety of soils and aquatic sediments (Lovley, 1993). Reduction is inhibited by NO3 − and Mn(IV), which are preferred electron acceptors. In pure systems rates of transformation of SeO3 2− to SeO4 2− and vice versa are slow but, as for oxidation of Cr(III) and As(III), rapid oxidation of SeO3 2− sorbed on Mn oxides can occur, with Mn(IV) acting as oxidant (Scott and Morgan, 1996). In reducing environments Se is present as Se2− which forms insoluble compounds with metals, especially Fe(II), or, if metal concentrations are insufficient, the foul-smelling poisonous gas H2 Se may be formed. Reduction of SeO3 2− to Se2− (pe0∗ = 0.3 at pH 5 and −1.7 at pH 7) is microbially mediated at low pH (Lovley, 1993). Though large concentrations of Se can develop in poorly drained soils as a result of accumulation of insoluble Se2− compounds, Se is also lost under

232

Nutrients, Toxins and Pollutants

anaerobic conditions by methylation into volatile compounds. The reactions include (Reamer and Zoller, 1980): methylation

reduction

HSeO3 − −−−−−→ CH3 SeO3 H −−−−→ CH2 SeO2 − methylation

reduction

CH3 SeO2 − −−−−−→ (CH3 )2 SeO2 ↑ or CH3 SeOOCH3 ↑−−−−→ (CH3 )2 Se ↑ reduction

CH3 SeO2 − −−−−→ CH3 SeH or CH3 SeOH −−−→ CH3 SeSeCH3 ↑ The different steps are mediated by a consortium of microbes with tolerances to the various form of Se, resulting in removal of toxic Se from the soil though enhancing atmospheric Se transport.

Iodine Iodine is essential in the mammalian diet to produce the thyroid hormone thyroxine; deficiency in humans causes goitre. Collectively, deficiencies of iodine, iron, zinc and vitamin A in humans are thought to be at least as widespread and debilitating as calorie deficiencies (Welch and Graham, 1999). The main source of iodine in soils is oceanic salts rather than parent rock, and so deficiency is most widespread in areas remote from the sea (Fuge, 1996). In principle deficiency is easily corrected with dairy supplements. However in practice this is not always feasible. Addition of iodate to irrigation water has successfully corrected widespread iodine deficiency in parts of China where the usual methods of supplementation had failed (Cao et al., 1994; Jiang et al., 1997). However there is not much information on the behaviour of iodine in soil and water systems. Iodine is present in the environment predominantly in the oxidation states −1 (I− , iodide) and +5 (IO3 − , iodate). Reduction of IO3 − to I− occurs at pe0 = 13.3 at pH 5 and pe0 = 11.3 at pH 7. Hence I− is expected to predominate in the soil solution except in oxic alkaline soils (Whitehead, 1984). However Yuita (1992) found predominantly IO3 − in acid Japanese soils contaminated with iodine: the concentrations in solution were some 20 times those of I− and I2 . On flooding the soils, the total concentration of I in solution increased 10- to 50-fold, predominantly as I− . The concentrations of sorbed I were not measured, but both IO3 − and I− are expected to be bound to organic matter and oxides and hence their concentrations in solution are expected to increase with reductive dissolution reactions. Further, for a given concentration in solution, I− is more rapidly absorbed by plants than IO3 − (Mackowiak and Grossl, 1999). Hence flooding is expected to increase accumulation in plants both through increased solubility and increased absorption.

8 Trace Gases

This chapter considers the extent, mechanisms and possibilities for control of emissions of trace gases from submerged soils. The focus is on ricefields because this is where research has been most intense and because ricefields are the focus of the greatest scrutiny for possibilities to reduce emissions.

8.1 METHANE 8.1.1 GLOBAL BUDGET Table 8.1 shows recent estimates of the global methane budget made by the Intergovernmental Panel on Climate Change (IPCC) (Prather et al., 2001). There are substantial emissions from natural sources, particularly wetlands. But anthropogenic sources account for 60 % of the total emission and the abundance of CH4 in the atmosphere is now more than double its pre-industrial value–1745 ppb (molar mixing ratio in the troposphere) compared with 700 ppb in 1750. The rate of increase has been near exponential over the last 300 years. However the annual rate of increase has been highly variable and in the last 20 years it has declined for reasons that are not fully understood. The current percentage rate of increase is comparable to that of CO2 –about 0.4 % year−1 . The radiative forcing effect of CH4 is about 21 times that of CO2 per mole of gas. Currently, increases in CO2 account for about 50 % of global warming and increases in CH4 about 20 %. There is therefore political pressure to decrease man-made emissions of CH4 by whatever means possible. Since CH4 has a short lifetime in the atmosphere (8 years compared with 50–200 years for CO2 ), modest decreases in emissions can quickly have a large effect on atmospheric abundance. Adjusting the global CO2 balance requires larger percentage as well as absolute changes. Further, it is argued that the fossil fuels responsible for most of the atmospheric CO2 increase also produce aerosols that have negative radiative forcing effects in the troposphere (Hansen et al., 2000). These include aerosols of non-absorbing sulfates, which both directly reflect radiation and increase reflection by clouds. They therefore to some extent mitigate the effects of increased CO2 , and this complicates calculations of the relative importance of CO2 emissions versus other greenhouse gases. The Biogeochemistry of Submerged Soils Guy Kirk  2004 John Wiley & Sons, Ltd ISBN: 0-470-86301-3

234

Trace Gases

Table 8.1 Estimates of the global methane budget (Tg CH4 year−1 ) from different sources and sinks Reference

Base year Natural sources Wetlands Termites Oceans Hydrates Anthropogenic Energy Landfills Ruminants Waste treatment Rice agriculture Biomass burning Other Total source Sinks Tropospheric OH Stratosphere Soils Total sink

Fung Hein Olivier Lelieveld Mosier Cao Houweling Prather et al. et al. et al. et al. et al. et al. et al. et al. (1991) (1997) (1999) (1998) (1998b) (1998) (1999) (2001) 1980s — 1990 1992 1994 1998 — — 115 20 10 5

225b 20 15 10

237 — — —

75 40 80 — 100 55 — 500

97 35 90a

109 36 93a

a

a

88 40 — 587

10 450 — 460

— 489 46 535

60 23

110 40 115 25 b

40 — 600 30 510 40 580

92

89 14 25–54 34 15

53

145 20 15 — 89 73 93 — — 40 20 598

44

30

30 506 40 576

a

Waste treatment included under ruminants. Rice included under wetlands. Source: adapted from Prather et al. (2001).

b

Estimates of CH4 emissions from ricefields have improved greatly in the past decade and the contribution of ricefields to the global CH4 budget is far smaller than originally thought (Table 8.2). However, there is still considerable uncertainty. Recent estimates compiled by the IPCC range from 25 to 60 Tg CH4 year−1 out of a total global emission of about 600 Tg CH4 year−1 (Table 8.1), but credible estimates of less than 10 Tg CH4 year−1 are also made (Table 8.2). These compare with 100–111 Tg CH4 year−1 from fossil fuels, 80–115 Tg CH4 year−1 from ruminants, and 35–75 Tg CH4 year−1 from landfills. Rice therefore ranks about fourth among anthropogenic sources of methane. 8.1.2 PROCESSES GOVERNING METHANE EMISSIONS FROM RICE Reviewers of this topic include Sch¨utz et al. (1989a,b), Conrad (1993), Neue and Roger (1994) and Segers (1998). The rate of emission depends on the linked rates of CH4 production, transport and oxidation, which are sensitive to a host of soil, plant, climate and management variables. Production occurs through

235

Methane Table 8.2

1 2

3a

3b

4

5 6

Estimates of global CH4 emissions from ricefields in chronological order Method

Source strength (Tg year−1 )

Methane production in incubated samples of rice soils multiplied by estimated amounts of soil (Koyama, 1963) Uniform emission factor based on flux measurements multiplied by harvest area of rice (Cicerone and Shetter, 1981; Holzapfel-Pschorn and Seiler, 1986; Sch¨utz et al., 1989a, respectively) • Excluding upland rice area • Allowing for average temperature during growing season (IPCC, 1997) Methane emission proportional to net primary production, e.g. 3–7 % (Aselman and Crutzen, 1989), 5 % (Taylor et al., 1991) • Allowing for soil CH4 emission potential (Bachelet and Neue, 1993) Methane emission proportional to carbon returned to the soil: 30 % of the carbon retuned emitted as CH4 (Neue et al., 1990) • Allowing for soil CH4 emission potential (Bachelet and Neue, 1993) Specific emission factors for specific ecosystems, regions or management, or all (IPCC, 1997) • Rice ecosystem-specific emission factors (Neue and Sass, 1998) • Country-specific emission factors (Neue and Sass, 1998) • Regional rice statistics (Yao et al., 1996) Empirical models using data from national statistics linked to GIS (Kern et al., 1997) Mechanistic models using weather, soil, agronomic and other data linked to GIS Cao et al. (1996) Huang et al. (1998) Matthews et al. (2000a)

190 59, 70–170, 50–150

−12 % 60–105 60–140 47 63 52

30–50 32 15 (China only) 10 ± 3 (China only)

53 7.2–13.6 (China only) 6.5–17.4 (70 % of area)

Source: adapted from van der Gon et al. (2000). Reproduced with kind permission of Kluwer Academic Publishers.

the anaerobic decomposition of organic matter, mostly after inorganic terminal electron acceptors have been exhausted (Section 5.3). Transport occurs by ebullition (Section 2.3), by diffusion through the soil to root surfaces and then via the plant aerenchyma to the atmosphere (Section 6.2), and to a lesser extent by diffusion directly to the floodwater and atmosphere. Oxidation is also microbially mediated, mainly by obligate aerobes in the oxic floodwater–soil and root–soil interfaces. The sensitivity of these processes to many variables suggests the possibility of interventions to decrease emissions. It also complicates the prediction of emissions from readily measurable parameters.

236

Trace Gases

Differences between Rice Production Systems Early measurements were made mostly in temperate countries (Ciceron et al., 1983; Seiler etal., 1984; Holzapfel-Pschorn and Seiler, 1986; Sch¨utz et al., 1989a,b), but a large programme of measurements was conducted in Asia in the 1990s by the IRRI and partners using a common measurement system (summarized in the book by Wassmann et al., 2000b). This revealed large differences in emissions per season–more than an order of magnitude–between different climatic zones across Asia, between types of rice culture, and between management practices, particularly management of crop residues and use of organic manures. For example, mean emissions in China are large because of the widespread use of organic manures, in spite of the moderating effect of lower temperature compared with tropical Asia; whereas in India, crop residues are often largely removed from the fields and emissions are correspondingly smaller. Seasonal emissions from irrigated rice are generally two- to four-fold greater than from rainfed lowland rice under similar climates. Mean fluxes from deepwater rice are smaller than from irrigated rice, but because of the far longer growing season, the total seasonal emission may be similar. Extrapolating from measured seasonal emissions for the different rice ecosystems and the area of each planted annually, irrigated rice accounts for 70–80 % of global CH4 emissions from rice, rainfed lowland rice for 15 % and deepwater rice for 10 % (Wassmann et al., 2000d). Differences within Seasons Emissions from irrigated ricefields show distinct diurnal and seasonal variations which illustrate the interactions between the governing processes. The diurnal variation includes a maximum during the day and a minimum at night, and is mainly linked to changes in the temperature of the soil solution which drive changes in rates of CH4 production and solubility and therefore changes in emission, whether through the plant or by ebullition (Sch¨utz et al., 1990; Yagi et al., 1994; Wang et al., 1999). The seasonal variation often has two peak periods: one early in the season corresponding primarily to the decomposition of added organic matter and ending abruptly when the organic matter has been used up; and a second later in the season corresponding to emissions via the plant fuelled by root exudation and turnover (Holzapfel-Pschorn et al., 1986; Sch¨utz et al., 1989a,b; Yagi and Minami, 1990; Neue, 1997). Figure 8.1 shows the typical pattern for a field to which organic matter has been added. Various factors alter this basic pattern: (1) The amount of organic matter added. This is highly variable across rice production systems, depending on such factors as the time available between crops, mechanization allowing residue incorporation, alternative requirements for organic matter, and so forth. Often straw is entirely removed from the

237

Methane

Rate of emission (kg C ha−1 day −1)

25

20

15

10

5

0 −20

0

20

40

60

80

100

120

Time (days after planting)

Figure 8.1 Seasonal variation in CH4 emission. Rice straw (t ha−1 ) was incorporated in the soil 14 days before planting the crop (data from Wassmann et al., 2000a). Reproduced by permission of Kluwer Academic Publishers

field following a crop and there are no additions to the succeeding crop. The early-season peak may then be absent. (2) The availability of inorganic electron acceptors, both in the soil constituents and added in mineral fertilizers. This affects the time course of soil reduction and hence the rate at which sufficiently reducing conditions for methanogenesis develop. (3) Temperature and radiation. The temperature regime affects rates of CH4 production, transport and oxidation, and generally high temperature favours high rates of emission. The main effect of radiation is through its influence on crop growth. Hence dry season emissions at a particular site are often much smaller than wet season emissions, and a well-managed crop under optimal conditions of temperature and radiation emits less CH4 (see Section 8.1.5). (4) Water regime, particularly where there is mid-season drainage allowing escape of entrapped CH4 but also oxidation of the soil. The water regime is also affected by soil texture as this affects percolation rates; high percolation rates tend to decrease emissions because less reducing conditions are maintained in the soil. Texture may also affect gas entrapment and ebullition. So the picture is complicated. 8.1.3 MODELLING METHANE EMISSION Given the complexity, some form of mechanism-based modelling is required to understand or predict emissions in given circumstances. Approaches to modelling emissions from rice are reviewed by van der Gon et al. (2000). A complete

238

Trace Gases

treatment is given by Arah and Kirk (2000) in a general transport-reaction model, which they simplify to focus on emissions fuelled by root exudation and death and transmission through the plant. This model is now outlined. Following Equation (2.6), the concentration profile with depth z of any nonadsorbed substrate in an areally homogeneous system is given by: 
∂C ∂ ∂C (8.1) = D − vCL + O + P − Q − R − S ∂t ∂z ∂z where O is the root-mediated influx, P is production, Q is consumption, R is the root-mediated efflux and S is ebullition. The terms D, v, O, P , Q, R, S and C are effective areal averages at depth z and time t: they subsume within themselves any areal heterogeneity in the real system. Temperature is an implicit variable in Equation (8.1), influencing the instantaneous rates of all transport and reaction processes. Diffusion depends on the bulk concentration C; leaching and consumption on the solution-phase concentration CL ; and root-mediated efflux and ebullition on the gas-phase concentration CG . Root-mediated influx and production are independent of C, CL and CG , though they may depend on other properties of the system. The concentrations C, CL and CG are easily inter-converted assuming equilibrium between solution and gas phases: CL = H CG

(8.2)

where H is a dimensionless Henry’s law constant. The bulk concentration is given by C = θG CG + θL CL (8.3) where θG is the air-filled porosity and θL is the volumetric water constant. Hence CG =

1 C ∂θ CG = , i.e. θ G + H θL ∂C θ G + H θL

and CL = H

H C ∂θ CL = , i.e. θG + H θL ∂C θ G + H θL

(8.4)

(8.5)

The diffusion coefficient allows for both gas and liquid phase diffusion. It is given by (Stephen et al., 1998a,b): D=

DG θG + DL H θL (θG + H θL )f

(8.6)

where f is a tortuosity factor, approximately equal to unity in a well puddled soil. Root-mediated influx may be represented as an exchange process in which only the gas phase moves. Most simply this can be expressed (Stephen et al., 1998a,b): O = κDG CG0 (8.7)

239

Methane

where CG0 is the concentration at z = 0 and κ is a transmission constant which depends on such variables as the root length density, root porosity, the permeability of root tips and laterals, and root architecture. Similarly for root-mediated efflux at a particular depth: R = κDG CG (8.8) The rate of ebullition, S, of a particular substance depends on its gas-phase concentration. Most simply this is expressed: S = σ CG

(8.9)

where σ is a rate constant. The boundary conditions for solving Equation (8.1) are (a) for volatile solutes that the concentration at the surface is known and (b) for non-volatile solutes that the flux is zero.

Parameter Values With appropriate values for H, DG , DL , v, C0 and the depth-profiles of θG , θL , κ and σ , Equations (8.1) to (8.9) apply to any non-adsorbed substance. To simulate CH4 production, transport, oxidation and emission, we need to consider at least two mobile substances–O2 and CH4 –and at least three reactions: Oxic respiration

CH2 O + O2 −−−→ CO2 + H2 O

Methanogenesis

CH2 O + CH2 O −−−→ CO2 + CH4

CH4 oxidation

CH4 + 2O2 −−−→ CO2 + 2H2 O

Here CH2 O represents oxidizable organic matter. In reality the reactions with inorganic terminal electron acceptors, particularly Fe(III) and SO4 2− , should also be considered. But in the absence of a complete understanding of these processes (see Chapter 5), and for the sake of simplicity, we exclude them. Production, P.

Methanogenesis is inhibited by solution-phase O2 : PCH4 = I VM

(8.10)

where VM (z, t) is the CH4 production potential and I (z, t) is an inhibition function which we take to be: I=

1 1 + ηCLO2

0≤I ≤1

(8.11)

where η is an inhibition efficiency constant. No reaction produces O2 , i.e. PO2 = 0.

240

Trace Gases

Consumption, Q. Methane oxidation is described with dual-substrate Michaelis–Menten kinetics:

 CLO2 CLCH4 (8.12) QCHh = VO KO1 + CLO2 KO2 + CLCH4 where VO (z, t) is the oxidation potential and KO1 and KO2 are Michaelis constants. Oxygen is consumed in respiration and CH4 oxidation, the latter requiring two molecules of O2 per molecule of CH4 . Hence, assuming Michaelis–Menten kinetics and no carbon limitation:
 CLO2 + 2QCH4 (8.13) QO2 = VR KR + CLO2 where VR (z, t) is the respiration potential and KR a Michaelis constant. Reaction Potentials. The reaction potentials VM , VO and VR are the rates at which methanogenesis, CH4 oxidation and oxic respiration would proceed in situ were all enzymes saturated with the necessary substrates. They depend on in situ enzyme concentrations and hence on in situ microbial populations. They change over time. Equations (8.1)–(8.13) can be solved to provide transient- or steady-state profiles of O2 and CH4 concentration, reaction rates and surface fluxes for any combination of the controlling variables θG , θL , v, κ, σ, VM , VO and VR . Where, as is usual, one or more of the controlling variables may be further simplified, approximated or neglected, process-based simulation of CH4 emission becomes possible using a relatively limited set of input data.

Simplified Model Focusing on Effects of the Plant Arah and Kirk (2000) make the following assumptions to develop a simplified model: (1) the soil is saturated and air-filled porosity external to roots is negligible, i.e θG = 0; (2) water content, θL , is uniform with depth; (3) leaching is negligible, i.e. v = 0; (4) root transmissivity is proportional to root-length density, i.e. κ = kT LV ; (5) ebullition is negligible, i.e. σ = 0; (6) oxidation potential, VO , is constant; (7) CH4 production potential is proportional to respiration potential, VM = VR / 50; (8) respiration potential is proportional to root-length density, i.e. VR = kV LV ; (9) root-length density is normally distributed with depth, with maximum value LV max at depth zmax , and standard deviation equal to zmax / 2.

241

Methane

Assumptions 1–9 are ad hoc simplifications introduced in order to define a standard system with characteristics that can be explored. Some of the assumptions (1–3, 5) are relatively uncontroversial; others (7–9) depend on an underlying supposition that root-mediated processes dominate. Results. Figure 8.2 gives steady-state profiles of O2 and CH4 and the corresponding reaction rates calculated with the model for the fixed root system defined in Assumption 9. Net O2 consumption is 460 µmol m−2 h−1 , net CH4 emission is 480 µmol m−2 h−1 , the fractions of the O2 and CH4 fluxes through the plant are 0.84 and 0.97, respectively, and the fraction of CH4 oxidized prior to emission is 0.13. These are all credible numbers. Figure 8.3 shows the consequences of varying the root transmissivity factor kT and the substrate supply factor kV . It shows that, other things being equal, the CH4 flux increases with kV but decreases with kT . The latter, perhaps counterintuitive, result reflects the fact that transport through roots allows O2 into the system as well as CH4 out. Enhanced O2 concentrations in the rhizosphere inhibit methanogenesis and promote oxidation, and the combined effect of these two processes more than compensates for the greater ease with which CH4 can escape. The model also shows, unsurprisingly, that the fraction of the CH4 transmitted through the plants increases as root transmissivity increases and decreases as substrate supply increases. Figure 8.3(b) shows that the fraction of CH4 that is oxidized before reaching the atmosphere is a sensitive function of kV and kT . Increasing kV reduces the fraction oxidized, presumably because the oxidation potential VO is held constant in these simulations and increased production simply overwhelms the oxidation capacity; increasing kT increases the fraction oxidized where transmissivity is low and decreases it where transmissivity is high, presumably reflecting (a)

(b)

0

Depth (cm)

10 20 30 oxygen methane

40 50 0.0

0.1

0.2

Concentration (mM)

0.3

0

5

10

15

20

25

30

Reaction rate (mmol m−3 h−1)

Figure 8.2 Calculated profiles of O2 and CH4 concentrations (a) and reaction rates (b) (Arah and Kirk, 2000). Reproduced by permission of Kluwer Academic Publishers

Multiple of standard supply factor k V

242

Trace Gases 10

10

(a) CH4 flux (µmol m−2 h−1)

(b) Fraction of CH4 oxidized

1000

0.1

1000

1

1000

0.1

1000

100

100

0.1 0.1

0.2 0.3 0.4

10 1

10

1

1

0.1 0.1

10

100

0.2

1

100

0.1

0.5

0.2 0.3 0.4 0.5 0.6 0.7

10 0.1 1 Multiple of standard transport factor k T

0.2 0.3

0.3

0.4

0.4

0.5

0.5

0.6

0.6 0.7

10

Figure 8.3 Calculated effects of the CH4 supply factor kV (Assumptions 7 and 8 of the simplified model) and the root transmissivity factor kT (Assumption 4) on (a) the CH4 flux and (b) the fraction of CH4 oxidized. Lines are contours of CH4 flux or fraction oxidized (Arah and Kirk, 2000). Reproduced by permission of Kluwer Academic Publishers

the intricate balance between the twin effects of O2 , namely inhibiting CH4 production and promoting CH4 oxidation (and thereby anaerobiosis, and thereby CH4 production). Conclusions. The model shows that the bulk of mid to late season emission occurs via the plant; where organic matter has been added, large emissions early in the season must occur by ebullition. For any given root-length density profile: (1) rice cultivars with high specific substrate supply rates will lead to increased CH4 emissions; (2) cultivars with high specific transmissivities will decrease CH4 emissions; (3) drainage leading to an air-filled porosity of just 0.01 decreases CH4 emissions practically to zero. These findings broadly agree with experimental observations. Measured rates of CH4 oxidation in the rice rhizosphere range widely from 5 to 90 % of the CH4 transported (Holzapfel-Pschorn et al., 1985; Epp and Chanton, 1993; van der Gon and Neue, 1996). This agrees with the model. Rates of O2 flow through rice roots to the rhizosphere are of the order of a few mmol O2 m−2 (soil surface) h−1 (Section 6.4), which is sufficient to account for the rates of oxidation calculated with the model. Measured differences in emissions between rice cultivars are largely due to differences in root biomass (Lu et al., 1999); the effects of differences in root porosity are smaller (Aulakh et al., 2001a,b). What little is known about the microbiology of CH4 oxidation in the rice rhizosphere indicates complicated kinetics and competition effects.

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Methane

Studies of microbial growth rates indicate that VR >> VO but KO1 < KR in Equations (8.12) and (8.13) (van Bodegom et al., 2001). Hence heterotrophs will out compete methanotrophs for O2 except at very small O2 concentrations. This may constrain the spatial distribution of CH4 oxidation in the rhizosphere. Nutrient concentrations may also be limiting, in which case fertilizer may enhance oxidation and lessen emissions, depending on interactions with plant growth and other variables. Bodelier et al. (2000) found enhanced CH4 oxidation in the rice rhizosphere on adding N, contrary to expectations for aerobic soils where it is found that methanotrophs preferentially oxidize NH4 + over CH4 . In the rice rhizosphere in flooded soil, CH4 concentrations are much higher and, close to roots, NH4 + concentrations smaller. Likewise Lu et al. (1999) found diminished CH4 emissions from rice when P was added to a P-deficient flooded soil. Salinity also impairs CH4 oxidation and to a greater extent than it impairs methanogenesis (van der Gon and Neue, 1995).

Field-scale Model of Emissions Matthews et al. (2000a) have developed a field-scale model of emissions based on the above approach. In addition to the processes discussed above, the fieldscale model allows for added organic matter and soil organic matter separately, and for the effects of inorganic terminal electron acceptors. Figure 8.4 shows that the model was capable of predicting seasonal emissions at a particular site from model parameter values measured independent of the emission data.

Rate of emission (kg C ha−1 day −1)

25

20

15

10

5

0 −20

0

20 40 60 80 Time (days after planting)

100

120

Figure 8.4 Measured (points) and calculated (line) seasonal variation in CH4 emission. Measured data as in Figure 8.1; calculation described in text (Matthews et al., 2000a). Reproduced by permission of Kluwer Academic Publishers

244

Trace Gases

8.1.4 ESTIMATING EMISSIONS AT THE REGIONAL SCALE The uncertainty in estimates of the global CH4 emission from rice remains large: the mean estimate for the 1990s in Table 8.1 is 60 ± 30 Tg year−1 , equivalent to a range of 5 to 15 % of the total emission. This reflects the diversity of conditions in which rice is grown and the large effects of management. To date, most estimates have involved a down-scaling approach in which knowledge and understanding at the field or local scale are used to extrapolate to the regional scale and above; this approach is limited by the availability of reliable data at the required scale. An alternative approach is to work in the opposite direction, down-scaling by interpolation from measurements of overall terrestrial emissions made in global air sampling networks (Heimann and Kaminski, 1999). Further improvements in estimates are likely to come from a meeting in the middle of these approaches. I here outline their pros and cons.

Up-scaling using Mechanistic Models and GIS Knox et al. (2000) and Matthews et al. (2000b) have coupled a field-scale model of CH4 emissions from rice to GIS systems, and used available regional data on weather, soil, agronomic management and other variables to make regional-scale estimates of emissions. The model is based on the approach described earlier. The extrapolation is based on the following framework. Basic polygons for attributing vector datasets were derived from a digitized map of national and provincial or state boundaries for China (31 polygons), India (31), Indonesia (26), Philippines (80) and Thailand (73). At least one polygon was defined for each province or state. Data on crop production and cropped area under the four rice ecosystems were obtained for each polygon using the map of Huke and Huke (1997), mainly from 1990. Weather data in individual polygons were obtained from the nearest of 46 weather stations within the appropriate agroecological zone. Soil data were obtained from FAO-DSMW soil units (1:5 000 000) with supplementary data for individual soil units in top and subsoils: pH, organic C, Fe content, texture and available water capacity. Each soil property was given a weighted mean value for the polygon based on the distribution of FAO soil units. Locally recommended crop management was assumed. Due to lack of data, no allowance was made for differences in applications of organic manures, and this will probably have caused underestimates in emissions. The resulting global estimates are in the range 10–25 Tg CH4 year−1 . This approach is of course limited by the availability of reliable data and the resolution of the data. An inherent problem in the ‘up-scaling’ process is the interaction between variance in input parameters and non-linearity in models. This may produce chaotic behaviour. van Bodegom et al. (2002) discuss this in relation to CH4 emission from rice. The point at which input data are averaged before making model runs may also be limited by the available computing

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Methane

power. Nonetheless the great strength of a mechanism-based modelling approach is that the sensitivity to different variables can be tested and the effects of timedependent variables, feedback mechanisms and the consequences of changes in the system can be explored. Down-scaling using Inverse Modelling The spatial and temporal variation in sources and sinks of a trace gas are reflected in the spatial and temporal variation of its mixing ratio in the atmosphere. In inverse modelling, observed net emissions over a region are apportioned to known sources and sinks according to a priori assumptions about their relative importance. The resulting magnitudes of the sources and sinks and their distributions are then used to calculate the net flux a posteriori using models of atmospheric transport and chemistry. The agreement between the a priori and a posteriori values indicates the accuracy of the a priori assumptions. This approach has been applied to global emissions of CO2 , CH4 , N2 O, halocarbons and CO, which have sufficiently long lifetimes and well understood atmospheric chemistries (Heimann and Kaminski, 1999). Methane emissions have been studied by Hein et al. (1977) and Houweling et al. (1999). van der Gon et al. (2000) used inverse modelling to test the effects of different a priori assumptions about the magnitude of CH4 emissions from rice. In Scenario A a widely accepted standard range of 50–80 Tg CH4 year−1 (Lelieveld et al., 1998) is used, and in Scenario B their own best estimate of 15–30 Tg CH4 year−1 . The same total emission is assumed for the two scenarios, and the same combined flux from wetlands and ricelands. The global emission is apportioned to rice and other sources according to these assumptions, and calculations made for the whole globe, the northern and southern hemispheres, and an area roughly corresponding to the part of Asia where rice is most important. The results, summarized in Table 8.3, show that the assumed and calculated results for the rice area are much closer for the lower emission scenario, indicating that it is more realistic. Table 8.3 Global distributions of CH4 emissions (Tg CH4 year−1 ) calculated using inverse modelling. In Scenario A rice contributes 50–80 Tg year−1 and in B 15–30 Tg year−1 ; the net contribution of natural wetlands and ricelands is constant

Scenario A assumed calculated Scenario A assumed calculated

Globe

Northern hemisphere

Southern hemisphere

Asiaa

528 ± 90 505 ± 24

405 ± 81 340 ± 19

123 ± 40 165 ± 18

111 ± 56 77 ± 23

528 ± 24 508 ± 24

384 ± 66 342 ± 16

143 ± 38 166 ± 17

74 ± 31 66 ± 18

10◦ N, 75◦ W to 40◦ N, 135◦ W. Source: van der Gon et al. (2000). Reproduced with kind permission of Kluwer Academic Publishers.

a

246

Trace Gases

However, as yet monitoring networks on atmospheric mixing ratios are not sufficiently extensive or close to continental CH4 sources to make this approach entirely reliable for rice.

8.1.5 POSSIBILITIES FOR DECREASING EMISSIONS Methane emissions from rice are expected to increase over the next few decades as rice production increases to meet projected increases in population and demand. Intensified production to produce more rice on a smaller land area, with more crops per year, greater use of fertilizers, greater quantities of crop residues to be disposed of, legislation against burning residues, and mechanization allowing incorporation of residues are all likely to exacerbate emissions. However the better crop management necessary to increase yields will of itself tend to lessen emissions. Hence van der Gon et al. (2002) found that emissions over five years at an irrigated site in the Philippines were inversely related to grain yield (Figure 8.5). They found that large emissions were associated with small ratios of grain to biomass, particularly in the wet season, and hypothesized that this caused greater CH4 production from root carbon released into the soil. In a greenhouse experiment, removing spikelets to reduce the plants’ capacity to store photosynthate in grains increased CH4 emissions, possibly via more carbon entering the soil. Unfavourable conditions for spikelet formation in the wet season may similarly explain high CH4 emissions. For similar reasons, modern high yielding rice varieties generally emit less CH4 than traditional varieties (Neue et al., 1997; Aulakh et al., 2001a,b), and there are possibilities for breeding varieties with low emission potentials, exploiting differences in biomass partitioning and gas transport.

Seasonal CH4 emission (kg CH4-C ha−1)

500 dry season wet season

400 300

y = − 61x + 558 r 2 = 0.94

200 100 0

3

4

5

6

7

8

9

Grain yield (t ha−1)

Figure 8.5 Seasonal CH4 emission as a function of grain yield in wet and dry seasons at Maligaya, Luzon, Philippines (van der Gon et al., 2002). Reproduced by permission of National Academy of Sciences, USA

Nitrogen Oxides

247

Water management might also be manipulated to lessen emissions. Currently direct seeding and other water-conserving practices are being adopted in many parts of Asia in response to shortages of water and labour (Guerra et al., 1998). A single, well-timed period of drainage in the early season can decrease emissions by 50 % without compromising yield (Sass et al., 1992; Neue, 1997; Wassmann et al., 2000c). However the timing is critical so that entrapped CH4 that would otherwise be oxidized is not released, and N is not lost from the soil through nitrification–denitrification, especially if conditions are such that nitrous oxide forms.

8.2 NITROGEN OXIDES 8.2.1 GLOBAL BUDGET Nitrous oxide (N2 O) is an important greenhouse gas with a radiative forcing effect 310 times that of CO2 and a lifetime in the troposphere of approximately 120 years. Part of the N2 O is converted to NO in the stratosphere, and so contributes to depletion of ozone. Nitric oxide (NO) is very reactive in the atmosphere and has a lifetime of only 1–10 days. It contributes to acidification and to reactions leading to the formation of ozone in the troposphere, and so also to global warming. Table 8.4a shows estimates of the global nitrous oxide budget from different sources and sinks (Prather et al., 2001) and Table 8.4b estimates for NOx (NO + NO2 ). As for CH4 , there are substantial emissions from natural sources, particularly the ocean and humid tropical forests for N2 O and lightning and soil processes for NOx . However anthropogenic sources account for 40 % of the total emission in both cases. For NOx , this is largely from road transport and power plants, but for N2 O 60 % is from agricultural soils. The post-industrial increase in N2 O abundance in the atmosphere is smaller than that of CH4 –314 ppb (molar mixing ratio in the troposphere) compared with 270 ppb in 1750–and the current percentage increase (0.25 % year−1 ) is smaller than that of CH4 . However because of its large radiative forcing effect, the increase is highly significant. Irrigated ricefields are not expected to be major sources of N2 O if the fields are kept continuously submerged during the growing season (Buresh and Austin, 1988; De Datta, 1995; Hou et al., 2000). Rates of nitrification of NH4 + in ricefields and subsequent denitrification can be substantial (Chapter 5). In general, conditions are sufficiently reducing and the availability of organic substrate sufficiently large that denitrification proceeds as far as N2 with little intermediary N2 O produced en route. However, under fluctuating water regimes, as in rice systems in which the soil is deliberately drained in the middle of the season, conditions may be ideal for N2 O emission. This is often done to remove toxic products of anaerobic metabolism or simply to save water. A common practice

248

Trace Gases

Table 8.4a Estimates of the global nitrous oxide budget (Tg N year−1 ; mean and range) from different sources and sinks Reference

Olivier et al. (1998) 1990

Base year Natural sources Ocean Atmosphere (NH3 oxidation) Tropical soils Wet forest Dry savanna Temperate soils Forests Grasslands All soils Anthropogenic Agricultural soils Biomass burning Industrial sources Cattle and feedlots Total source Sinks Total sink (stratosphere) Implied total sourcea

3.6 0.6

(2.8–5.7) (0.3–1.2)

6.6

(3.3–9.9)

1.9 0.5 0.7 1.0 14.9

(0.7–4.3) (0.2–0.8) (0.2–1.1) (0.2–2.0) (7.7–24.5)

Mosier et al., (1998a); Kroeze et al., (1999) 1994 3.0 0.6

(1–5) (0.3–1.2)

3.0 1.0

(2.2–3.7) (0.5–2.0)

1.0 1.0

(0.1–2.0) (0.5–2.0)

4.2 0.5 1.3 2.1 17.7

(0.6–14.8) (0.2–1.0) (0.7–1.0) (0.6–3.1) (6.7–36.6)

12.3 16.2

(9–16)

Prather et al. (2001) 1990s

6.9

12.6 16.4

Total sink + atmospheric increase. Source: adapted from Prather et al. (2001).

a

Table 8.4b Estimates of the global NOx (NO + NO2 ) budget (Tg N year−1 ; mean and range) Base year 1990 Natural sources All soils Lightning NH3 oxidation in atmosphere N2 O destruction in stratosphere Anthropogenic Fossil fuel combustion Biomass burning Total source

5.5 12.2 0.9 0.7

(4–12) (2–20) (0–1.6) (0.4–1)

23.4 7.7 50.4

(13–31) (3–15) (22–81)

Source: Olivier et al. (1998).

in southern China is to apply large quantities of nitrogen fertilizer early in the growing season to stimulate crop growth and production of tillers, and to then abruptly drain the soil to arrest tillering by driving off nitrogen through nitrification–denitrification. Here and in other systems, large emissions of N2 O are to

Nitrogen Oxides

249

be expected. Current efforts to make water use in rice production more efficient will undoubtedly increase N2 O emissions unless steps are taken to avoid this. Rice can also be an indirect source of N2 O (and NO) emissions via deposition of volatilized ammonia on natural ecosystems, particularly wet tropical forests, which are one of the main ‘natural’ sources of N2 O (Table 8.4a). 8.2.2 PROCESSES GOVERNING NITROUS AND NITRIC OXIDE EMISSIONS FROM RICE Emissions of nitric and nitrous oxides are the result of microbial nitrification and denitrification in soils, controlled principally by soil water and mineral N contents, labile organic carbon, and temperature. Nitric oxide is a direct intermediate of both nitrification NH4 + −−−→ NH2 OH −−−→ NO −−−→ NO2 − −−−→ NO3 − and denitrification, NO3 − −−−→ NO2 − −−−→ NO −−−→ N2 O −−−→ N2 It is thought that little net NO is produced in denitrification, it being readily reduced to N2 O, and nitrification is therefore the main source of NO (Anderson and Levine, 1986; Skiba et al., 1993). Nitrous oxide is also produced in both nitrification and denitrification. At low O2 concentrations in otherwise aerobic soil, small amounts of N2 O are formed as a by-product of nitrification, N2 O not itself being reduced to NO2 − . In denitrification, the proportion of N2 O produced relative to N2 increases as the availability of O2 increases and that of carbon decreases (Tiedje, 1988). In general only a small fraction of the N nitrified or denitrified in these pathways is released as NO or N2 O. The emission is therefore sensitive to the amount of mineral N in the system, which is driven principally by additions of nitrogen fertilizers and deposition of nitrogen from the atmosphere. As discussed in Chapter 5, in submerged soils nitrification occurs in aerobic sites at the floodwater–soil and root–soil interfaces. Denitrification occurs upon diffusion of the NO3 − to the anaerobic bulk soil. Denitrification is favoured over dissimilatory reduction to NH4 + (NO3 − → NO2 − → NH4 + ) because of the large ratio of available carbon to electron acceptors in submerged soils. Denitrification is likely to proceed completely to N2 with little accumulation of N2 O because of the very large sink and therefore steep concentration gradient of O2 , and because carbon is less likely to be limiting (Section 5.1). However this will not be the case when a submerged soil is drained and air enters, leading to gradients of oxidation from the surfaces of soil cracks towards the anaerobic interiors of soil clods. Now conditions may be ripe for production of nitrous and nitric oxides. Hence there is a fine balance between conditions favouring methanogenesis and those favouring nitrous oxide production. This is nicely illustrated in Figure 8.6,

250

Trace Gases 40

30

CH4

30

20

N2O

20

10

10

0

0

−10

−10

−20

− 20

−30

− 30

−40

452

387

333

289

280 169 145 E H (mV)

−56 −189 −266 −279

N2O flux (µg m−2 h−1)

CH4 flux (mg m−2 h−1)

40

− 40

Figure 8.6 Fluxes of CH4 and N2 O from ricefields during cropping and fallows plotted against the corresponding soil EH (Hou et al., 2000). Reproduced by permission of Soil Sci. Soc. Am.

which shows emissions of CH4 and N2 O from a ricefield in northern China measured from March to December for 2 years, plotted against the corresponding soil redox potentials, EH (Hou et al., 2000). It shows that emissions of CH4 and N2 O were strongly correlated with EH . Significant CH4 emission only occurred at EH < −100 mV, whereas N2 O emission was only significant at EH > +200 mV. The results suggest the possibility of using management practices to maintain the redox potential in a range where both N2 O and CH4 emissions are low. 8.2.3 DIFFERENCES BETWEEN RICE PRODUCTION SYSTEMS Bronson et al. (1997a,b) made continuous measurements of CH4 and N2 O emissions from ricefields over a period that included two dry season and one wet season irrigated rice crops and the two intervening fallow periods. The soil was clayey and poorly drained. Figure 8.7 shows that during the growing seasons, N2 O fluxes were generally barely detectable although small emissions (≤ 3.5 mg N m2 day−1 ) occurred after N fertilizer applications. Methane fluxes, on the other hand, were substantial throughout the rice-growing seasons. The total emission of CH4 over the season decreased three- to four-fold when N was supplied as (NH4 )2 SO4 rather than urea at 200 kg N ha−1 , but emission of N2 O was 2.5-fold greater with (NH4 )2 SO4 . Mid-season drainage suppressed CH4 emission by ≤ 60 %, but markedly increased N2 O emissions. Figure 8.8 shows the results for the fallow periods. These lasted 5 to 11 weeks and were weedy. The soil was generally aerobic, and moderate amounts of NO3 − accumulated (7–20 kg N ha−1 ). Moderately high, continuous N2 O emissions occurred, apparently during nitrification of mineralized organic N in the topsoil and possibly also during denitrification in the wet subsoil. The flux of N2 O was greatest immediately after rainfall and after the field was flooded for rice at the end of the fallow, as a result of denitrification of accumulated NO3 − .

251

N2O flux (mg nm−2 day−1)

CH4 flux (mg cm−2 day−1)

Nitrogen Oxides

800

35 (a) straw

(b) urea 28

600

continuous flooding

drainage (arrows)

400

21 14

200

7 0

0 2.0

6 (c) straw

(d) urea

1.5 4 1.0 2 0.5 0.0 0

20

40

60

0 80 100 0 20 Days after transplanting

40

60

80

100

N2O flux (mg nm−2 day −1)

CH4 flux (mg cm−2 day−1)

Figure 8.7 Emissions of CH4 and N2 O during a rice crop with different water, straw and fertilizer managements. Single upward arrow = drainage; double downward arrow = flood irrigation (Bronson et al., 1997a). Reproduced by permission of Soil Sci. Soc. Am. 5

5 Geen manure Straw

4

4

3

3

2

2

1

1

0

0

80

80

60

60

40

40

20

20

0

0

6

12

18

24

0 30 36 0 6 Days after harvest

Urea Ammonium sulfate

12

18

24

30

36

Figure 8.8 Emissions of CH4 and N2 O during a fallow between rice crops. Single arrow = rainfall; double arrow = flood irrigation (Bronson et al., 1997b). Reproduced by permission of Soil Sci. Soc. Am.

252

Trace Gases

Little CH4 was emitted during the fallows. This study demonstrates that rice soils in the fallow periods can be significant sources of N2 O. A common cropping sequence in the rainfed lowlands is wet season rice followed by a dry season upland crop on residual soil moisture or supplemental irrigation, followed by a 60- to 70-day fallow during the dry-to-wet transition. Alternate soil wetting and drying in this system create particular difficulties for the conservation of nitrogen in the soil (Buresh et al., 1993a; George et al., 1993, 1994, 1995). Soil N mineralized and nitrified at the onset of rains in the fallow may be lost by leaching and by denitrification when the soil becomes submerged. Commonly high-value vegetable crops are grown in the dry season with heavy applications of fertilizers, leaving substantial amounts of residual nitrate in the soil. This situation leads to large losses of N before the wet season rice is established. Studies of N balances in an intensified rainfed lowland system of this sort in the Philippines have shown N losses of up to 550 kg ha−1 year−1 through nitrate leaching and denitrification (Tripathi et al., 1997).

8.3 AMMONIA 8.3.1 GLOBAL BUDGET Ammonia has a lifetime of only a few hours to a few days in the atmosphere. It and its reaction products are transported through the atmosphere and deposited on terrestrial surfaces elsewhere. It is the main gaseous alkaline species in the atmosphere and neutralizes a large part of the acid produced in oxidation of sulfur and nitrogen oxides, probably up to a half though its dry-deposition is much faster than that of NOx and SO2 (Dentener and Crutzen, 1994). Dry- and wet-deposition of ammonia contribute to soil acidification because 2 mol of H+ are produced in the nitrification of 1 mol of NH4 + . Also a large part of the ammonia deposited on moist forest soils may be re-emitted as N2 O (Section 8.2). Table 8.5 shows a global inventory of ammonia emissions compiled by Bouwman et al. (1997). The main sources are the excreta of domestic animals (40 %), use of nitrogen fertilizers (17 %), the oceans (15 %) and biomass burning (11 %). About half of the global emission comes from Asia, and 70 % is from food production. Europe, the Indian subcontinent and eastern China have the largest emission rates, reflecting the densities of domestic animals and the types and intensities of fertilizer use. Anthropogenic emissions have probably increased three-fold since 1950 in line with the increase in global population and food production. Ammonia volatilization from fertilizers is a function of the type of fertilizer, soil conditions, meteorological conditions–temperature, wind speed, precipitation–and fertilizer management. Table 8.6 shows the global use of nitrogenous fertilizers and the corresponding NH3 emissions based on empirical emission factors for different fertilizer types in temperate and tropical conditions (Bouwman

Ammonia

253

Table 8.5

Estimates of global ammonia emissions (Tg N year−1 ) from different sources

Reference Animals Cattle including buffaloes Pigs Horses, mules, asses Sheep, goats Poultry Wild animals Total animals Others Synthetic fertilizers Undisturbed ecosystems Crop plants Biomass burning Human excrement Sea surface Fossil fuel combustion Industry Total emission

Schlesinger and Hartley (1992)

Dentener and Crutzen (1994)

Bouwman et al. (1997)

19.9 2.0 1.8 4.1 2.4 32.3

14.2 2.8 1.2 2.5 1.3 2.5 24.5

14.0 3.4 0.5 1.5 1.9 0.1 21.7

8.5 10 — 5 4 13 2.2 — 75

6.4 5.1 — 2.0 — 7.0 — — 45.0

9.0 2.4 3.6 5.7 2.6 8.2 0.1 0.2 53.6

a

a Included in undisturbed ecosystems. Source: Bouwman et al. (1997). Reproduced by permission of American Geophysical Union.

Table 8.6 Global use of nitrogenous fertilizers and corresponding NH3 emissions based on empirical emission factors for different fertilizer types and uses Type of nitrogenous fertilizer Urea Ammonium bicarbonate Ammonium nitrate NPK Anhydrous ammonia Nitrogen solutions Calcium ammonium nitrate Ammonium phosphates Ammonium sulfate Others Total

Global use

Emission (Gg N year−1 )

(Tg N year−1 ) 29.2 9.5 8.2 6.6 5.2 4.2 4.1 3.7 2.6 3.7 77.0

Temperate

Tropical

Total

1632 802 25 40 18 11 9 35 34 20 2626

4137 1189 141 219 190 93 72 113 169 85 6409

5769 1991 166 259 209 104 82 147 203 105 9035

Source: Bouwman et al. (1997). Reproduced by permission of American Geophysical Union.

et al., 1997). Seventy per cent of the emission is from developing countries in the tropics; of this 65 % is from urea and 19 % from the volatile hydrolysis product of urea, ammonium bicarbonate, which is widely used in China. Based on data for rice area and yield by country (IRRI, 2002), the approximate relation

254

Trace Gases

between rice yield and N fertilizer use (Figure 7.1), and the emission factors used by Bouwman et al., I estimate a total emission of NH3 from wetland rice of very roughly 3.6 Tg N year−1 , of which 1.2 Tg N year−1 is from China and 0.6 from India. This compares with a total global emission from N fertilizer of 9.0 Tg N year−1 . Clearly wetland rice is an important source of NH3 .

8.3.2 PROCESSES GOVERNING AMMONIA EMISSIONS FROM RICE Urea is the main form of N fertilizer used in rice, together with, in China, ammonium bicarbonate. At least two applications are generally made by broadcasting the fertilizer onto the floodwater: the first 14–21 days after planting the crop and a second at the maximum tillering stage 45–55 days after planting. The first is subject to high rates of loss by volatilization (De Datta and Patrick, 1986; De Datta, 1995). Losses are smaller once the crop canopy and root system are established, because turbulence and hence gas exchange at the water surface are less and absorption by the crop is greater. Rates of volatilization during the early period measured by bulk aerodynamic and micrometeorological methods often account for 30–40 % and sometimes as much as 60 % of the fertilizer applied (Simpson et al., 1984; Cai et al., 1986; Fillery et al., 1986 Freney et al., 1990; De Datta et al., 1989). Losses during the later stages are typically less than half this, depending on how well matched the application is with crop demand. Urea broadcast into the ricefield floodwater is hydrolysed to ammonium, bicarbonate and hydroxyl ions; the reaction is catalysed by the enzyme urease: CO(NH2 )2 + 2H2 O + H+ −−−→ 2 NH4 + + HCO3 − One mol of H+ is consumed in this reaction for every 2 mol of NH4 + formed. In subsequent volatilization of NH3 , 1 mol of H+ is produced for every mol of NH4 + converted to NH3 : NH4 + −−−→ NH3 + H+ Because urease activities are much greater in the soil than in the floodwater, the NH4 + is largely formed in the soil as the urea moves downward by mass flow and diffusion. The NH4 + , H+ and other reactants will also move between the floodwater and soil–both upward and downward–with NH3 being lost from the floodwater by volatilization. The recovery of N in the crop therefore depends on the rate of movement of urea and its reaction products through the soil and on the rate at which the roots remove N from the downward moving pool. Rachhpal-Singh and Kirk (1993a,b) developed a model of these processes based on equations for the transport and reaction of urea, ammoniacal species (NH4 + , NH3 , NH4 OH), carbonate species (H2 CO3 , HCO3 − , CO3 2− ) and mobile acid–base pairs (H2 CO3 –HCO3 − , HCO3 − –CO3 2− , NH4 + –NH3 , NH4 + –NH4 OH, H2 O–OH− ). The equations are of the form of Equation (2.6)

5

4

3

2

1

0

2

60 50 40 30 20 10 0

0

3

2

6

soil)

5

10

dm−3

4

4 6 8 Time (days)

[Urea-N] (mmol

1

%N volatilized

7

0

2

[NH4-N] (mmol

1 dm−3

3 soil)

4

5

6.8

7.0

7.4 Soil pH

7.2

7.6

2 days 5 days 10 days

7.8

Figure 8.9 Profiles of urea-N, ammoniacal-N and pH with depth following broadcast application of urea on ricefield floodwater, and the corresponding rates of NH3 volatilization (calculated with the model of Rachhpal-Singh and Kirk, 1993a,b)

Depth in soil (cm)

0

255

256

Trace Gases

with terms for N, C and base added or removed in urea hydrolysis, organic C and N mineralization, and root uptake. The dynamics of CO2 in the floodwater and the coupled transfer of CO2 and NH3 across the air–water interface (Section 3.5) are allowed for. The model shows that cumulative volatilization of NH3 is sensitive to the initial distribution of urea in the soil, its rate of hydrolysis, and the rate of absorption of N by rice roots. It is largely insensitive to other parameters. For example, it might be thought that addition of organic matter to the soil to acidify the floodwater should lessen NH3 volatilization. However, the model shows that although increased CO2 production affects the diurnal change in floodwater pH, it little affects the daily average pH and hence NH3 volatilization. This is because the relative rates of movement of carbonate species and acidity between the soil and floodwater are such that the increased alkalinization of the floodwater resulting from increased CO2 loss is not matched by an equal inflow of acidity from the soil. The model shows that the spread of urea and NH4 + into the soil is typically only a centimetre or two in a week (Figure 8.9). The recovery of broadcast fertilizer N in the crop must therefore depend entirely on the superficial root system in the soil–floodwater interface. The good recovery of broadcast fertilizer N obtained if the fertilizer is added when the crop demand is maximal (Peng and Cassman, 1998) therefore indicate rapid uptake by roots in the soil–floodwater interface. 8.4 SULFUR COMPOUNDS 8.4.1 GLOBAL BUDGET Submerged soils are important sinks for atmospheric sulfur (Howarth et al., 1992). Sulfate washed into wetlands or deposited from the atmosphere is largely reduced to sulfide by sulfate-reducing bacteria. Subsequent precipitation with metals, especially as FeS, results in more or less permanent removal of the S from the global S cycle. Little sulfur is re-emitted from wetlands into the atmosphere. Table 8.7 gives estimates of global emissions of volatile sulfur compounds from different sources. Total emissions are in the range 98 to 120 Tg (S) year−1 ; 75 % is anthropogenic, mainly from fossil fuel combustion in the northern hemisphere. The main natural sources are the oceans and volcanoes. Wetlands and soils contribute less than 3 % of the total emission. 8.4.2 EMISSIONS FROM RICEFIELDS The main source of S emissions from ricefields is the burning of crop residues, during which most of the sulfur in the residues is converted to volatile oxides (Fox

H2 S

CH3 SCH3

Estimates of global sulfur emissions (Tg S year−1 ) CS2

OCS

SO2

SO4

Totala

b

Numbers in parentheses are fluxes from northern/southern hemispheres. Excluding contributions from sea salt. c Excluding contributions from soil dust. Source: Seinfeld and Pandis (1998). Reproduced by permission of Wiley, New York.

a

Fossil-fuel combustion + industry Total reduced S = 2.2 70 2.2 71–77 (68/6) (mid 1980s) Biomass burning <0.01? — <0.01? 0.075 2.8 0.1 2.2–3.0 (1.4/1.1) Oceans <0.3 15–25 0.08 0.08 — 40–320 15–25 (8.4/11.6)b Wetlands 0.006–1.1 0.003–0.68 0.0003–0.06 — — — 0.01–2 (0.8/0.2) Plants + soils 0.17–0.53 0.05–0.16 0.02–0.05 — — 2–4 0.25–0.78 (0.3/0.2)c Volcanoes 0.5–1.5 — — 0.01 7–8 2–4 9.3–11.8 (7.6/3.0) Total anthropogenic 73–80 Total natural (excluding sea salt and soil dust) 25–40 Total 98–120

Sources

Table 8.7

257

258

Trace Gases

and Hue, 1986; Lefroy et al., 1992). However these may be rapidly returned to the soil in rainfall, particularly during tropical wet seasons, though not necessarily at the same site. Sulfur may also be lost by volatilization as H2 S, but in most soils any S2− formed in reduction is promptly precipitated as FeS or other sulfides (Chapter 4), and so net losses are small. There are also modest emissions of organic-S compounds. Minami et al. (1993) measured S emissions from field lysimeters treated with S-containing compounds in amounts found in crop residues and organic manures. Emission of H2 S, OCS (carbonyl sulfide), CH3 SH (methyl mercaptan), CH3 SCH3 (dimethylsulfide, DMS), CS2 (carbon disulfide) and CH3 SSCH3 (dimethyl disulfide) were detected, with DMS by far the largest. Emissions of DMS ranged from 4.1 to 7.3 mg (S) m−2 year−1 , and varied diurnally and seasonally in ways indicating mediation by the rice plants. The type of soil had little effect. The measured emissions multiplied by the total global rice area indicate a potential global emission from ricefields of 0.004 to 0.01 Tg (S) year−1 . This compares with emissions from all wetlands of 0.003–0.68 Tg (S) year−1 , from other plants and soils of 0.05–0.16 Tg year−1 , and from oceans of 15–25 Tg year−1 . Likewise emissions of CS2 , OCS and other organic-S compounds from ricefields are small in comparison with other known sources.

8.5 CARBON SEQUESTRATION Table 1.3 gives estimates of the global distribution of carbon in soils. Wetlands are the single largest organic C pool, account for roughly 40 % of the total soil carbon. Destruction of wetlands therefore results in significant loss of the global terrestrial carbon store. There have been large losses of wetlands in developed countries in the past–almost half the original wetland area in the US in the last 200 years for example–but this is now largely under control. However preservation of wetlands is less of a priority in developing countries. About half the global area of natural wetlands is in the tropics. Despite the burning of crop residues in the productive, irrigated rice areas of tropical and subtropical Asia, and their removal for other purposes in the lowproducing rainfed rice areas, soil carbon levels are largely constant (Bronson et al., 1998). In any case, the amount of carbon in the shallow puddled layer of ricefields amounts to only a few per cent of the amount in natural wetlands.

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Index

absorption see nutrient absorption acetaldehyde 166 acetate 144, 146 acidification 200, 208 acidity see also pH peat bogs 210 ricefields 208–10 sulfate soils 213–14 toxins 212–14 trace metals 78 acids 46–7, 215–16 acid–base reactions 35–7, 46–7, 48, 64 acid sulfate soils 213–14 adsorption 76–9 aeration nutrient absorption model 172–7 roots 170–1 aerenchyma 167–9, 171 aerobic processes 147–50 air–water interface see also water CO2 transfer 61–4 gas transport 58–64 Alfisols 12–15 algae 154–5, 156 alkalinity changes after flooding 109–12 water 57 alluvial soils 13, 14, 15, 69 aluminium toxicity 213 amino acids 46, 180, 190 aluminosilicates 68 ammonia 7–8 emissions from rice 254–6 global budget 252–4 volatilization 64, 148, 252, 254–6 The Biogeochemistry of Submerged Soils Guy Kirk  2004 John Wiley & Sons, Ltd ISBN: 0-470-86301-3

ammonium 121–2 absorption 178–80, 185–6, 187–9 anoxia effects 186–7 formation 41–2 nitrates 187–9 reduction 141 anaerobic conditions 139, 140, 151, 165–7 anoxia decomposition 75–6, 144–7 ion transport 186–7 root processes 167–70 antimony 231 aqueous solutions carbonates 49 ferrous iron oxidation 128–9 Armstrong and Beckett’s model 170–1 arsenic 231 atmospheric methane 6 autotrophs 104–6 bacteria see also microbiological processes autotrophs 104 biological nitrogen fixation 157–8 cyanobacteria 154–5, 156, 157 heterotrophic 106, 143, 157 methane oxidation 149 nitrification 148 phototrophic 157 reduction 137, 142–3 bases 46–7 see also acids; acid–base reactions biological fixation 70 depletion 70 bicarbonate 28, 30, 111 air–water interface 61–3 rhizosphere 200, 202

284 bioavailability of trace elements 220 biodiversity 163–4 biological nitrogen fixation (BNF) 156–9 biological processes macrobiological 150–62 microbiological 135–50 biomass 154, 155 biotic catalysis 137 biotic factors 156 bioturbation 40–4, 161–2 bluegreen algae see cyanobacteria BNF see biological nitrogen fixation bogs 1, 2, 6, 8 boron 228 buffer power 36 see also derivatives bulk density depth gradient 25–6 impedance factor 27–8 burrowing invertebrates 40–4, 161–2 cadmium 224–6 calcification 70 calcite precipitation 85, 86 calculated changes in exchangeable cations 89–91 carbon balances 4–6, 7, 75 organic 4, 7, 9 oxidation state 146 sequestration 258 transformations 120 carbon dioxide accumulation in rice soils 137–40 air–water transfer 61–4 anaerobic incubation 139–40 diurnal changes 58 ebullition 38–9 floodwater dynamics 56–8 hydration 55–6 pressure increase 111 carriers, membranes 182–4 catalysis of redox reactions 102–6, 136–7 cation exchange capacity (CEC) 28, 30, 32, 116

Index cations calculated changes 89–91 concentration 66 immobilization 200–2 radii 84 CEC see cation exchange capacity channels, membranes 182, 183 charges, pH dependent 73–4 chemoautotrophs 104–6 chromium 227–8 clays 65–8, 69 structural charge 67 surface property changes 71–4 climate 155 co-precipitation, solid solutions 79, 82–4 coastal plains 14, 15 cobalt 226 complexes 48–50, 76–9 adsorption 78 inner- and outer-sphere 77 continuity equations 17–18 copper 226 cyanobacteria 154–5, 156, 157 Darcy’s law 20 dCL /dC derivative 33–5 decomposition 150–1 anoxic 75–6 methanogenesis 144–7 organic matter 120 deficiencies sulfur 206–8 zinc 208, 221, 225 denitrification anaerobic conditions 141–2, 148 nitrogen oxides 249 rhizosphere 196–7 depth changes 106–9 diffusion 22–38, 59, 81–2 pH changes 35–8 simultaneous oxidation 131–4 diffusion coefficients 22–35 bulk density 25–6 derivative dCL /dC 33–5 free solution 23–5 impedance factor 26–33 solutes 22–3

Index disaggregation 19 dissimilatory reduction 141, 143 dissolution of coatings 71–2 dissolved oxygen 153–4 diurnal variations in ricefields 58, 236 divalent cation radii 84 diversity, biological 163–4 ebullition 38–9 ecosystems 3 see also wetlands EH see redox potential electrode curves 118, 119 electron acceptors 135, 137–8, 141 electron activities 94–9 electron balances 146, 147 electron donors 141 emissions see also methane emissions ammonia 252–6 nitrogen oxides 247–52 sulfur compounds 256–8 trace elements 219 energetics, microbe-mediated reactions 102–6 Entisols 12–15 equilibrium calculations 50–2 gas–water 54–8 equilibrium constants acids–bases 47 carbonates 49 mineral phases in reduced soils 112 reduction half-reactions 95–6, 103 trace elements 223–4 exchangeable cations 89–91 extracellular transport 180 fauna 40–4, 159–62 fens 1, 2, 6, 8 fermentation 94, 165–7 ferric iron 28, 32 hydroxides 70–1, 113 oxides 70–1 reduced soil 132 reduction 70–1, 72–3 rhizosphere 192–4

285 structural Fe(III) reduction 70–1, 72–3 ferrihydrite 101 ferrolysis 209–10 ferrous iron 31, 32 calculated changes 113–16 changes after flooding 110, 112–13 depth distribution 107–9 hydroxides 113 oxidation kinetics 128–31 reduced soil 132 rhizosphere 192–4 toxicity 214–15 fertilizers 253–6 Fick’s laws 18, 23 flooding see also ricefields cation concentration 66 changes in pe, pH and Fe2+ 109–13 derivative dCL /dC 34–5 EH distribution 107–9 impedance factor 27–32, 33 soil mineralogy 69–71 surface properties 71–4 floodplains 2, 6, 8, 13–15 floodwater see also riparian wetlands; water CO2 dynamics 56–8 flora 154–9 macrobiological processes 150–62 microbiological processes 135–50 properties 152–4 salinity 216–17 soil zones 151–2 flora 154–9 fluxes, CO2 61–4 fluxial wetlands 4, 5 free energy changes 94–7, 105, 136, 139 functional analysis 163–4 Gaines and Thomas equation 88 Gapon equation 88 gas transfer see also aeration; diffusion; emissions air–water transport 58–64 ebullition 38–9 roots 167–70, 171, 174

286 gases see also individual gases equilibrium with water 54–8 global budgets 233–4, 247–9, 252–4 greenhouse gases 233 trace gases 233–58 genotypic analysis 163 GIS systems 244 global budgets ammonia 252–4 methane 233–4 nitrogen oxides 247–9 sulfur compounds 256 glucose oxidation 165–7 Henry’s law 60 heterotrophs 106, 143, 157, 243 Histosols 14 hydration of CO2 55–6 hydraulic conductivity 20 hydrogen 137, 144 hydroxides of iron 70–1, 113 hypoxia 186–7 immobilization 198, 200–2 impedance factor liquid phase 26–32 solid phase 32–3 Inceptisols 13–15 inland valleys 12–13, 14 inorganic nutrients 154 inputs to ricefields 203–8 see also fertilizers; nutrients interchanges, water 45–64 intracellular transport 180 inverse modelling 245–6 invertebrates 40–4, 159–60 iodine 232 ion transport (roots) 180–90 absorption 184–5, 187, 189–90 ammonium 187 anoxia effects 186–7 membrane transport 181–4 nitrate 1287 nutrient concentrations 185–6 ions 51 see also cations

Index iron see also ferric iron; ferrous iron pyrite oxidation 213–14 reduction 142–3 rice soils content 70–1 structural 70–1, 72–3 toxicity 214–15 irrigated rice soils 204, 205 kinetics absorption 184–5 ferrous iron oxidation 128–31 redox reactions 94–106 lakes 2, 6 landforms–soils relationship 12–15 lateral roots 173–4, 181 layer silicates 65–8 lead 229 ligands 47–50 lignin 76 lowland ricefields 1–3 macrobiological processes 150–62 fauna 159–62 floodwater flora 154–9 floodwater properties 152–4 floodwater–soil system 151–2 net primary production and decomposition 150–1 macrofauna 159–62 macronutrients 204–6 macrophytes 154–5, 156 manganese 107–9, 142–3 marshes 2, 6 mass flow 19–22 mechanistic models 244–5 meiofauna 159 membranes root transport processes 181–4 transporters 182–4 mercury 226–7 metal ions 51 metals 9 methane 233–47 see also methanogenesis atmospheric 6

Index ebullition 38–9 global budget 233–4, 245 oxidation 149–50, 240 methane emissions field-scale model 243 modelling 237–43 reduction 246–7 regional-scale estimation 244–6 from ricefields 234–7, 246–7, 251 simplified model 240–3 methanogenesis processes 144–7, 239–40 rice soils 137–9 ricefields 249–50 microbiological processes 135–50 see also bacteria aerobic processes 147–50 arsenic reduction 230 iron and manganese reduction 142–3 mercury reduction 226 nitrate reduction 141–2 redox reactions catalysis 102–6, 136–7 respiration 28 sequential reduction 136–40 sulfate reduction 143–4 micronutrients 206–8 mineral soils 10–12 mineralogy of rice soils 69–70 mixing by soil animals 39–44 modelling down-scaling 245–6 methane emissions 237–43 nutrient absorption 172–7 root aeration 170–1, 172–7 transport 17 up-scaling 244–5 net flux 21 net primary production (NPP) 4, 6, 150–1 nickel 226 nitrates absorption v. ammonium 187–9 concentration 148 reduction 141–2 nitrification 148, 196–7, 249

287 nitrogen acid–base changes 209 biological fixation 6–8, 156–9 ebullition 38–9 ricefields 206 root uptake 178–80 tidal soil marsh 213 transformations 120–2 nitrogen oxides emissions 249–52 global budget 247–9 NPP see net primary production nutrient absorption (roots) 180–90 ammonium 187–9 anoxia effects 186–7 efficiency improvement 189–90 external and internal concentrations 185–6 kinetics measurement 184–5 membrane transport processes 181–4 nitrates 187–9 root surfaces requirement 177–80 nutrient balances 203–12 peat bogs 210, 211 ricefields 203–8 riparian wetlands 210–11 tidal wetlands 211–12, 213 nutrients inorganic 154 transformations 119–26 Nye’s theory 35–8 oligochaetes 40, 161 organic acids 45, 111, 137–41, 215–16 organic carbon 4, 7, 9, 74–5 organic matter see soil organic matter organic soils 9–10 outputs from ricefields 203–8 oxidation see also redox reactions carbon 146 Fe2+ kinetics 128–31 glucose 165–7 methane 149–50, 240 organic matter 136–40 pyrite 213–14 reduced soil 127–34

288 oxidation (continued ) selenium 231 simultaneous diffusion 131–4 oxides 68–9, 71–2, 81 oxygen see also aeration; aerobic processes calculated changes 115–16 consumption 127–8, 169–70, 175 dissolved 153–4 root transport 169–70, 175 oxygenation of rhizosphere 191–4 pe calculated changes 113–16 pe–pH diagrams 99–102 redox couples concentration 97–9 redox reactions 94–7 time changes 109–11 peat bogs 210, 211 percolation rates 19–22 permeability 19 pH buffer capacity 53–4 calculated changes 113–16 charge changes 73–4 floodwater CO2 dynamics 56–8 pe–pH diagrams 99–102 propagation of changes 35–8 redox conditions 28, 30 reduced soil 132 rhizosphere 192–6, 202 time changes 109–12 phenolic acids 216 phenotypic analysis 163 Philippines, rice Zn deficiency tolerance 221–4, 225 phosphorus 9 diffusion 34 immobilization 125, 126, 198 solubilization 197–9 transformations 124–6 transport 42–4 wetlands 212 photoautotrophs 104 phototrophic bacteria 157 phreatic wetlands 4, 5 phytotoxic compounds 215 plasma membranes 181–4

Index pluvial wetlands 4, 5 pollutants 9 see also toxins precipitation 79–82 calcite 86 co-precipitation 79, 82–4 inhibition 85–7 rates 80–1 primary production 155–6 productivity of wetland rice systems 135, 154–5 puddling 12, 19–20 pumps, membranes 183, 184 pyrite oxidation 213–14 radiation 152–3 rainfed rice soils 206, 207 redox conditions derivative dCL /dC 34–5 impedance factor 27–32, 33 rice soils 70–1 redox potential (EH ) conditions 28, 30 distribution after flooding 107–9 electrodes 97 measurement 116–19 redox reactions 94–134 arsenic 230 catalysis 102–6, 136–7 free energy changes 105 microbe mediation 102–6 nutrient element transformations 119–26 pe and redox couples 97–9 pe–pH diagrams 99–102 reduced soil oxidation 127–34 soil conditions 106–19 redox species 136 redoxymorphic features 10–11 reduced soil, oxidation 127–34 reduction see also methanogenesis; redox reactions equations 114 equilibrium constants 96 half-reactions 95–6, 103, 223–4 iron and manganese 142–3 nitrates 141–2

Index sequential 136–40 structural Fe(III) 70–1 sulfates 143–4 rhizosphere 147–50, 152, 165–202 see also root architecture; root processes methane emissions 241, 242 methane oxidation 149–50 nitrification–denitrification 148, 196–7 oxygenation 191–4 pH 192–6, 202 rice plants root system 171, 173 yields 216 zinc deficiency tolerance 221–4, 225 rice soils see wetland rice soils ricefields 1–3, 6, 8 acidity balances 208–10 ammonia emissions 254–6 biological nitrogen fixation 158 carbon dioxide pressure 63 compacted soil pan 11 invertebrates 160 macronutrients 204–6 mass flow 21–2 methane emissions 234–7, 246–7, 251 micronutrients 206–8 nitrogen oxides emissions 249–52 nutrient balances 203–8 production systems 236, 250–2 productivity 135 radiation 152–3 salinity 217 seasonal differences 236–7 sulfur emissions 256–8 temperatures 152–3 water management 215, 247 zinc deficiency 208, 221, 225 riparian wetlands 210–11 river basins 13–15 root architecture 171–80 aeration/nutrient absorption model 172–7 aerenchyma 167–9, 171 individual roots and laterals 173–4, 181

289 length densities 171, 241, 242 oxygen budget 171–2, 175 structure of root system 172–3 surface required for nutrient absorption 177–80 root processes 165–202 see also wetland roots aeration 170–1 anoxia adaptations 167–70 fermentation 165–7 gas transfer 167–70, 171, 174 methane emissions 240–3 nutrient absorption properties 180–90 root-induced changes 190–202 transport 177–9, 180–4 root-induced changes 190–202 cation immobilization 200–2 nitrification–denitrification 196–7 phosphate solubilization 197–9 rhizosphere oxygenation 191–4 zinc solubilization 200 roots see also rhizosphere aerenchyma 167 cortical porosity 176 solute pathways 180–1 tissue morphology 168

salinity 216–17 saturation 10, 11 see also flooding seasonal variations in ricefields 236–7 secondary nutrients 206–8 selenium 231 self-diffusion coefficients 24 sequential reduction 136–40 shallow lakes 2, 6 silicates 65–8 silicon 208 sodicity 217 soil animals 39–44, 159–62 soil classification 12–5 soil organic matter (SOM) 11, 69, 74–6 decomposition 75–6, 120, 144–7 oxidation 136–40

290 soil profiles 10–11 see also depth changes soil redox conditions 106–19 depth changes 107–9 Fe2+ changes 112–13 nutrient elements transformations 119–26 pe and pH changes 109–11 redox potential 116–19 reduction, calculated changes 113–16 soils 65–91 acidity 155–6 carbon 4, 7 floodwater 151–2 landforms relationship 12–15 mixing by fauna 39–44 moisture content 25–6 solid surfaces 65–76 surface oxidation 129–31 surface property changes 71–4 types 9–12 solid phases 74 solid surfaces 65–76 solid–solution interactions 76–91 adsorption 76–9 co-precipitation 79, 82–4 equations 87–91 precipitation 79–82, 85–7 rates 81 solubilization phosphate 197–9 zinc 200, 201 solutes diffusion coefficients 22–3 soils 65–91 water 45–64 SOM see soil organic matter sorption equations 35 speciation 47–50 still water see ricefields structural iron reduction 70–1, 72–3 submergence see flooding sulfates acid soils 213–14 reduction 143–4 sulfur biogeochemical characteristics 8

Index distribution after flooding 107–9 emissions from ricefields 256 global budget 256 transformations 122–4 surface complexes 76–8 see also complexes surfaces 65–76 ferrous iron oxidation 129–31 property changes 71–4 wetland rice soils 69–71 swamps 1, 2, 6, 8 temperatures 152–3 thallium 228–9 thermodynamics, redox reactions 94–106 tidal wetlands 211–12, 213, 217 toxins 212–17 acidity 212–14 iron 214–15 organic acids 215–16 pollutants 9 salinity 216–17 trace elements 218–32 see also individual elements equilibrium constants 223–4 global cycling 218, 219 important properties 222 mobilities of elements 220–32 soil and plant transport 218–20 trace gases 233–58 see also individual gases trace metals 78 transformations of nutrient elements 119–26 transport processes 17–44 diffusion 22–38 ebullition 38–9 mass flow 19–22 mixing by soil animals 39–44 modelling 17 roots 177–9, 180–4 trace elements 218–20 tropical wetlands 1 tubificids 161, 162 Ultisols 12–15 uptake see nutrient absorption

291

Index urea 253 hydrolysis 86, 208, 254 vanadium 227 water 45–64 see also floodwater acids and bases 46–7 air interface, gas transport 58–64 composition 45–52 equilibrium calculations 50–2 equilibrium with gas phase 54–8 major inorganic species 52 pH buffer capacity 53–4 ricefields management 215, 247 saturation 10, 11 speciation 47–50 waterlogging see flooding; saturation wet tillage 19 wetland rice soils 11–12 see also ricefields iron contents 70–1 organic carbon 74–5

organic matter 76 phosphorus 126 solid surfaces 69–71 wetland roots architecture 171–80 ion transport 184–90 nutrient absorption 180–90 wetlands see also ricefields biogeochemical characteristics definitions 2 global extent 1–3 hydrology 5 invertebrates 159 soils and landforms 9–15 worm burrows 40–4, 160–2 yields of rice

3–9

203–4, 216

zinc deficiency 208, 221–4, 225 solubility 80 solubilization 200, 201

With kind thanks to Indexing Specialists, Hove, East Sussex, UK for compilation of this Index.