Soil Carbon in Sensitive European Ecosystems: From Science to Land Management

By Mats Olsson

Soil Carbon in Sensitive European Ecosystems - From Science to Land Management is a comprehensive overview of the latest research in this field drawn together by a network of scientists from across Europe. Soil carbon assessments are crucial at present to our understanding of the dynamics of terrestrial ecosystems and our ability to assess implications for the global carbon exchange and its consequences on the future climate. 

This book focuses primarily on ecosystems and their soil carbon stocks. The book identifies three key sensitive ecosystems within Europe: Mediterranean Forest and Agricultural Systems; Mountains; and Peatland.

Contributors include those currently working for the European research programme, COST Action 639 BurnOut (www.cost639.net; 2006-2010).

COST Action 639 emerged from a demand from policy makers in Europe for more detailed information on soil carbon dynamics. The cooperation between experts for reporting and experts for soil dynamics is the focus of the book. This book seeks to provide an up-to-date account on the state-of-the-art research within this topical field.

• Language: English
• Publisher: Wiley
• Release date: Oct 20, 2011
• ISBN: 9781119977674

Book preview

1

Introduction to carbon in sensitive European ecosystems: from science to land management

Robert Jandl¹ and Mats Olsson²

¹Bundesamt und Forschungszentrum für Wald (Forest Research Centre), Vienna, Austria

²Swedish University of Agricultural Sciences, Uppsala, Sweden

1.1 Rationale for this book

In recognition of the rich body of knowledge already available on carbon sequestration in soils and the effect of land management (Kutsch, Bahn and Heinemeyer, 2009; Roose et al., 2005; Lal and Follett, 2009), it was decided to focus on, especially, sensitive ecosystems and on ecosystems that are still not covered satisfactorily in the available literature.

The book is organized into three parts. Part 1 deals with ‘driving factors for greenhouse gas (GHG) emissions’. In Chapter 1, the questions of what are understood as particularly vulnerable sites and situations in which ecosystems are likely to lose greenhouse gases are approached. Also included in this chapter is the ‘toolbox of statistics’ for emphasizing the opportunities offered, and the limits exerted by, different statistical approaches of data evaluation. The second chapter deals with the effect of land use change on soil carbon pools. The comparison of the soil carbon stock in ‘managed’ versus ‘unmanaged’ land has clearly shown that the agricultural use of soils has led to a strong decline of soil carbon worldwide (Lal, 2004). Marginal agricultural land in Europe is frequently being afforested, with strong implications on carbon fluxes and pools. The state-of-knowledge for land use change is covered and evidence given on how well the understanding of carbon processes is supported by real data. A particular challenge is the temporal extent of the soil carbon change. Consequently, the chapter also explores how knowledge on land use change can be reconciled with the time frame of reporting.

Another chapter deals with disturbances. It is well understood that ecosystem disturbance changes the total carbon pool much quicker and sometimes with more severity than with the gradual evolution of an ecosystem (Körner, 2003). A series of natural and anthropogenic ecosystem disturbances are evaluated with hindsight to soil carbon pools, and it is demonstrated how management may affect the pools. The final chapter in the first part presents an overview on knowledge of soil carbon pools from a European perspective. This information is of crucial importance because it sets the limitations on an international soil carbon accounting scheme. It also addresses the highly important question of the baseline of soil carbon stocks that should be used when interpreting the current stock and stock changes of soil carbon.

Part 2 of the book picks out several types of ecosystems of particular relevance. It is intended to find a niche for this text by focusing on soils that deserve more attention than they have received in the past. In a chapter on mountain and high latitude ecosystems, the topic of above-average warming as predicted by the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) (Fischlin et al., 2007) is covered. Nevertheless, the biological activity of soil microorganisms is constrained by low temperatures and a short growing season. In a warmer climate substantial quantities of carbon dioxide may be lost from soils. A second strong driver is land use change due to the abandonment of alpine pastures and the subsequent reforestation.

A comprehensive treatment is given to ‘Peatlands’. From the knowledge of processes and responses of upland (mineral) soils to global warming, only limited predictions can be deduced for peatlands. Even their delineation on soil maps is uncertain. However, peatlands are a heterogeneous group of soils with different emissions. Drainage and subsequent land use change can have a strong effect on carbon fluxes and GHG emissions. The fate of peatlands as a consequence of climate change calls for a rigorous evaluation.

A separate chapter is devoted to Mediterranean ecosystems. Simulation models predict a low carbon sequestration potential for Mediterranean forest soils, mainly because the productivity of sites with a prolonged summer drought is low. More important than adapted forest management may be the effect of land use change (afforestation), because it may reverse the effects of earlier soil degradation. Afforestations in the Mediterranean regions have been shown to lead to considerable increases in soil carbon and nitrogen stocks. It needs to be shown how representative these results are for the entire region and how land use change effects can be communicated to landowners. An obstacle is that land use data and soil data are monitored by different authorities, which means that no harmonized and consistent data set on land use change is yet available.

In Part 3 of the book reporting issues are picked up. Firstly, based on the reports of greenhouse gases, how soils are treated is described, and of special relevance is the heterogeneity of data resources in Europe. The available databases on soil carbon stocks and land use are described. The role of simulation models is potentially very high in the reporting. Reporting soil carbon changes based on simulation results is assigned the highest Tier level in the Good Practice Guidance (IPCC, 2006). The modelling chapter gives an ample overview on different modelling approaches. The chapter is highly descriptive and leads the reader through a number of cases that are commonly encountered in reporting.

1.2 What do we need to know about soils for reporting purposes?

Accounting for changes in soil carbon stock requires an internationally agreed set of rules. The change in soil carbon needs to be reportable and verifiable based on data that are commonly available. Figure 1.1 shows the five compartments that need to be reported for forest ecosystems. For annual crops, the increase in biomass stocks in a single year is assumed equal to biomass losses from harvest and mortality in that same year, thus there is no net accumulation of biomass carbon stocks.

Figure 1.1 Five ecosystem compartments for which changes in soil carbon stocks are reported.

ch01fig001.eps

The reporting is done differently in the individual countries. The Good Practice Guidance (IPCC, 2006) identifies key categories that have a significant influence on a country's greenhouse gas inventory. When land use (agriculture, forestry, other land use [‘AFOLU’]) is a key category, countries use methods of higher complexity and with higher data demands (tier levels). Tier 1, the simplest version, applies to countries in which forests and the biomass carbon pool is not a key category and where no country-specific activity data are available. Tier 2 applies where forests and biomass carbon is a key category and where country-specific estimates of activity data (e.g. forest inventories) are available. Tier 3 applies where the forest land and biomass carbon is a key category. It requires detailed national forest inventory data supplemented by dynamic models or allometric equations calibrated to national circumstances that allow for direct calculation of biomass increment.

Assisting in the understanding and reporting in this area is the COST Domain Earth System Science and Environmental Management (ESSEM). COST is a programme fostering the European Cooperation in Science and Technology. Action 639 was a joint activity within ESSEM lasting from 2006 to 2010. The management committee for COST Action 639 is shown in Appendix 1.A.

1.3 Objectives and overview of COST Action 639

The main objectives of COST (European Cooperation in Science and Technology) Action 639 (Greenhouse gas budget of soils under changing climate and land use (BurnOut), 2006–2010) are: (i) the improved understanding of the management of greenhouse gas emissions from European soils under different forms of land use and, in particular, disturbance regimes; (ii) the identification of hot spots of greenhouse gas emissions from soils; (iii) the identification of soil and site conditions that are vulnerable to GHG emissions; and (iv) the development of an advanced reporting concept across different forms of land use and land use changes.

The entire COST Action 639 had a strong focus on processes involving soil carbon in recognition that soils represent the largest terrestrial organic carbon pool. The overall role of soils as a sink for carbon dioxide is controversial. This is due to the heterogeneity of ecosystems including various forms of organic pools and the wide range of possible effects of land management on soil carbon pools over time. The representative assessment of soil carbon stocks poses a challenge. Even more difficult is that the detection of soil carbon changes over time, because often a small change has to be evaluated against a large and spatially variable pool. The agreement between simulated and observed temporal changes of soil carbon is sometimes unconvincing. This imposes a further challenge on the current requirement of reporting soil carbon changes within short time-spans. The length of a commitment period is indeed so short that even large soil carbon changes, can only be detected with a considerable amount of samples or with high uncertainty.

1.4 Working Groups of COST Action 639

1.4.1 Working Group – Hot spots for effects of climate change on soil carbon and nitrogen

Research focuses on landforms and situations that are expected to respond strongly to climate change in a manner that is likely to turn these ecosystems into sources of GHGs. Landforms with a particular relevance for different regions in Europe have been selected. In addition, forms of ecosystem disturbances that are believed to be of widespread importance are chosen.

Peatlands are a frequent landform in Nordic countries and Western Europe. As a soil type, they have peculiar properties. From the knowledge of processes and responses of upland (mineral) soils to global warming, only limited predictions can be deduced for peatlands. Even their delineation on soil maps is uncertain. There is concern about peatland degradation in response to climate change or land management and the deleterious effects of such degradation on GHG release, hydrology, water quality and ecosystems. Virgin peatlands (mires) accumulate atmospheric carbon and nitrogen, but emit methane. Nitrogen oxide emissions from natural mires are insignificant. However, peatlands are a heterogeneous group of soils with different emissions. Drainage can have a dramatic effect on GHG emissions. In the Nordic countries, approximately 15 million hectares of peatland are used as managed forest land and have, to a certain extent, been drained. Following drainage, the methane emissions decrease and the net primary production and nitrous oxide (N2O) and carbon dioxide emissions increases. An integrated assessment of research needs to include an understanding of the links between hydrological processes, biogeochemistry, soil ecology, water flow paths, and the interactions between peatland and climate change. Moreover, peatland is understood as a renewable source of energy. Therefore, peatland is at some places exploited as a source for fuel. The impact of land use change of peatlands and the natural aggradation of peatlands as a consequence of global warming requires a rigorous evaluation. A GHG budget of the entire ecosystem is required in order to establish the net response (i.e. sink of carbon and nitrogen in higher biomass production vs source of GHGs from soils). The loss of peatland also affects the richness of the landscape and needs to be treated in the context of biodiversity issues. Understanding GHG emissions from peatland calls for a close cooperation between forest soil scientists and soil biologists.

In high elevation/latitude ecosystems the biological activity of soil microorganisms is constrained by low temperatures and a short growing season. In a warmer climate substantial quantities of carbon dioxide and nitrogen oxides may be lost from soils. The loss of GHGs from soils can be rapid, because large amounts of carbon and nitrogen occur in chemically labile forms that are rapidly mineralised. Thawing of permafrost may in some areas have a profound impact of emissions of carbon dioxide, nitrous oxide and methane. The extent to which increased plant productivity will compensate for soil GHG emissions is unknown. Budgeting the overall effect of soil warming requires understanding of the mechanisms of stabilization of soil organic matter and the stock of readily decomposable soil carbon. High elevation ecosystems are also undergoing a change because the land use is changing. Societal changes lead to the abandonment of pastures and the subsequent reforestation. The consequences for GHG emissions are not yet quantified.

Simulation models predict a low carbon sequestration potential for Mediterranean soils, mainly because the productivity of sites with a prolonged summer drought is low. More important than adapted forest management may be the effect of land use change (afforestation), because it may reverse the effects of earlier soil degradation. Afforestations in the Mediterranean region have been shown to lead to considerable increases in soil carbon and nitrogen stocks. It needs to be shown how representative these results are for the entire region and how land use changes can be communicated to landowners.

Natural and human-induced disturbances play an important role in ecosystem dynamics: forests are subject to wind throw and fire with a certain region-specific periodicity. Within a short time, large quantities of soil carbon and nitrogen are converted to GHGs (‘slow in / rapid out’). In Central Europe, secondary Norway spruce forests are common. This forest type is highly productive and is the backbone of forestry in several regions. The production risk of spruce monocultures is considerable and storm events regularly destroy vast areas of spruce forests. A second threat is the pressure from insect infestations, which often follow storm damage. As long as merely the economic value of timber production is compared, this forest type is superior to mixed-species forests. The main reason for GHG emissions from agricultural soils is tillage and nitrogen fertilization. Adapted forms of agriculture have a large potential for the reduction of emissions. However, agricultural soils are also responsive to climatic change. A major problem is erosion, especially when soils are bare during a part of the year.

Soils emit GHGs especially during drying/re-wetting cycles. These pulse emissions contribute a lot to the annual nitrogen oxide fluxes into the atmosphere. This knowledge has been soundly established on the basis of laboratory experiments and single case studies. The relevance for a national GHG budget is not clear. Preliminary results show that discontinuous monitoring of nitrogen oxide emissions can underestimate the annual emissions substantially when the short drying/re-wetting cycles are missed.

1.4.2 Working Group – Relation of land use, land use change and land use history on soil carbon and nitrogen

In the first commitment period (2008–2012) of the Kyoto Protocol, different types of land use are treated separately (IPCC Good Practice Guidance; IPCC, 2006). To avoid double accounting of GHG emissions and emission reductions across different forms of land use, a complex patchwork of reporting requirements has been established. It is anticipated that for future periods a transparent system, applicable to types of land use, will be necessary. Soil experts for different types of ecosystems (peatland, agriculture, forestry) need to be prepared for this situation. COST Action 639 served as a discussion platform, where expertise on key soil processes under specific forms of land use was exchanged in order to foster mutual understanding for seamless GHG accounting across different land use forms. Land use and land use history have a strong effect on the soil carbon and nitrogen stocks. For the relevance of land use changes for GHG reports, it needs to be shown how long the transition periods after a land use change are and how long an ecosystem can build up its carbon and nitrogen stocks in the soil until a new equilibrium is reached. Existing data sets were re-evaluated in the context of GHG reporting.

1.4.3 Working Group – Monitoring, statistics, simulation models

European forest soils are monitored in a harmonized way (for example, ICP Forest (http://www.icp-forests.org/) and Forest Focus (http://ec.europa.eu/environment/ forests/ffocus.htm)), but for other forms of land use the harmonization is less advanced. Peatlands are fundamentally different from mineral soils and require a specific monitoring method. The loss in carbon stocks is difficult to measure and sometimes less relevant in relation to emissions of methane and nitrous oxide. The detection of small changes in soil carbon and nitrogen stocks requires great sampling efforts. Specific sampling schemes will be recommended for the detection of subtle soil carbon and nitrogen stock changes with a large impact on greenhouse gas budgets.

Different simulation models were evaluated with respect to soil carbon and nitrogen dynamics. A particular challenge was the implementation of the dynamic properties of hot spots and of changes in land use. It is crucial for reporting purposes to understand where models are currently failing and to improve the interface with experts in field research and modelling. The assessment of stock changes requires a baseline for comparison. The present baseline is, arbitrarily, the pool size in the year 1990. In Chapter 4 an attempt is made to establish a more meaningful baseline based on land use, land use history and site properties.

Pool sizes for soil carbon and nitrogen are calculated from several input values. Each has an error that propagates. On top of the variability at the spot, the small and medium scale spatial variation has to be considered. How the variability of carbon and nitrogen pools can be comprehensively assessed under different situations of data availabilities is elucidated. The size of soil carbon and nitrogen stock changes that are theoretically required in order to be relevant for GHG reporting purposes is addressed. An error budget for undisturbed forests has been established in the project.

A further challenge for modellers is to account for ecosystem disturbances. Signatory countries of the Kyoto Protocol are including the sink strength of terrestrial ecosystems in their GHG budgets. Ecology tells that ecosystems have an inherent stability, a typical life span and have a certain probability of being subject to disturbances. A risk assessment needs to express the probability of ecosystem disturbances based on the knowledge of the past course of events and with hindsight to the effects of future changes (both with respect to land use and to climate). The data requirements for a risk assessment will be collected and compared with the availability of useful statistics in Europe (spatial/temporal resolution of records of wind damages, insect damages etc.).

1.4.4 Working Group – Implementation of results

‘End-users’ of the suggested methods (experts in greenhouse gas budgets) were involved in order to communicate upcoming reporting needs, recommendations for improvements, feedback on the relevance of the suggestions and testing of suggested methods. Our accounting concept will use existing information on European soils. The IPCC Good Practice Guidance presents a balanced view of available methods and approaches, but does not have the intention of developing new methods. The discussions on post-2012 reporting requirements modify existing Reporting Guidelines. COST Action 639 is aimed at the Tier 3 level methods, in order to use available information in many countries for the optimization of the level for reporting of soil changes. Suggestions for specific forms of land management with the objective of the retention of GHG in soils can be in conflict with aspects of nature conservancy (protection of rare ecosystems, biodiversity issues). These topics need to be resolved early on to avoid unrealistic suggestions for adapted land management.

Figure 1.2 Countries participating in COST Action 639. The light shades represents countries participating in meetings and correspondence; dark shades indicate countries that have made use of the scientific exchange programme offered by COST.

ch01fig002.eps

1.5 Regional coverage

COST Action 639 was met by considerable interest within Europe. The participation is shown in Figure 1.2. COST offers short term scientific missions to foster scientific exchange, preferably for the benefit of early stage researchers. This instrument of COST has been amply used within COST Action 639. Temporarily, scientists from the Russian Federation and from the United States of America made contributions.

Appendix 1.A Management Committee of COST Action 639

Austria

Michael ENGLISCH, Robert JANDL, Bundesamt und Forschungszentrum für Wald, Seckendorff-Gudent-Weg 8, 1130 Wien.

Belgium

Dominique PERRIN, Ecophysiologie des Arbres Forestiers, Faculte Univesitaire des Sciences Agronomiques, 2 Passage des Deportes, 5030 Gembloux.

Pascal BOECKX, Faculty of Bioscience Engineering, Gent University, Coupure 653, 9000 Gent.

Bulgaria

Dimitranka STOICHEVA, ‘N. Poushkarov’ Institute of Soil Science,7, ShoseeBankya Str.,1080 Sofia.

Mariya SOKOLOVSKA, Bulgarian Academy of Sciences, Laboratory of Soil Science, Forest Research Institute, 132, St. Kliment Ohridski Blvd, 1756 Sofia.

Czech Republic

Michal MAREK, Institute of Systems Biology and Ecology, Division of Ecosystems Processes, Laboratory of Plants Ecological Physiology, Na Sadkach 7, 370 050 Ceske Budejovice.

Denmark

Lars VESTERDAL, Karsten RAULUND RASMUSSEN, Forest & Landscape Denmark, University of Copenhagen, Horsholm Kongevej 11, 2970 Horsholm.

Estonia

Elve LODE, Institute of Ecology, Tallinn University, Uus-Sadama 5, 101 20 Tallinn.

Finland

Jari LISKI, Finnish Environment Institute, PL 140, 00251 Helsinki.

Jukka ALM, Joensuu Research Unit, Finnish Forest Research Institute, Yliopistokatu 6, 80101 Joensuu.

France

Bernhard ZELLER, INRA, Centre de Nancy, Route d’Amance, 54280 Champenoux.

Germany

Angelika THUILLE, Max Planck Institut für Biogeochemie, Hans Knoll Str. 10, 07745 Jena.

Rainer BARITZ, Federal Institute for Geosciences and Natural Resources, Stilleweg 2, 30655 Hannover.

Greece

Theodore KARYOTIS, National Agricultural Research Foundation, Institute for Soil Mapping and Classification, 1 Theophrastou Str., 41335 Larissa.

Kalliopi RADOGLOU, National Agricultural Research Foundation, Forest Research Institute, Vassilika, 57006 Thessaloniki.

Hungary

Balint HEIL, Gabor KOVACS, Faculty of Forestry, Institute of Soil Site Survey, University of West Hungary, Bajcsy-Zs. u.4, 9400 Sopron.

Ireland

Paul LEAHY, Centre for Hydrology, Micrometeorology and Climate Change, University College Cork, College Road, Cork.

Kenneth BYRNE, University Limerick, Limerick.

Israel

Guy LEVY, Agricultural Research Organization (ARO), Institute of Soil, Water and Environmental Sciences, PO Box 6, 50250 Bet Dagan.

Italy

Mirco RODEGHIERO, Fondazione Edmund Mach, Viote del Monte Bondone, 38100 Trento.

Lithuania

Saulius MARCINKONIS, Lithuanian Research Centre for Agriculture and Forestry, Zalioji a. 2, Traku Voke, 02232 Vilnius.

Edita BALTRENAITE, Faculty of Environmental Engineering, Vilnius Gediminas Technical University, Sauletekis av. 11, 10223 Vilnius.

Netherlands

Nynke SCHULP, Wageningen University, PO Box 47, 6700 AA Wageningen.

Rein DE WAAL, Peter KUIKMAN, Alterrra – Centrum Ecosystems, Droevendaalsesteeg 4, 6700 AA Wageningen.

Norway

Holger LANGE, Nicholas CLARKE, Norwegian Forest and Landscape Institute, PO Box 115, 1431 As.

Portugal

Manuel MADEIRA, Pedro AGUIAR PINTO, Jose LIMA SANTOS, Instituto Superior de Agronomia, Universidade Tecnica de Lisboa, Tapada da Ajuda, 1349-017 Lisboa.

Romania

Viorel BLUJDEA, Forest Research and Management Institute, Voluntari, Sos. Stefanesti 128, 77190 Voluntari.

Lucian DINCA, ICAS BRASOV, Forest Research and Management Institute, 11 Closca, Brasov.

Slovak Republic

Gabriela BARANCIKOVA, Soil Science and Conservation Research Institute, Raymanova 1, 08001 Presov.

Slovenia

Primoz SIMONCIC, Slovenian Forestry Institute, Ljubljana.

Spain

Joan ROMANYA, Facultat de Farmacia, Universitat de Barcelona, Avda. Joan XXIII s/n, 08028 Barcelona.

Agustín RUBIO SANCHEZ, Universidad Politecnica de Madrid, Ciudad Universitaria s/n, 28040 Madrid.

Sweden

Mats OLSSON, Dan BERGGREN, Swedish University of Agricultural Sciences, Box 7014, 750 07 Uppsala.

Switzerland

Christian KÖRNER, Institute of Botany, University of Basel, Schönbeinstrasse 6, 4056 Basel.

Frank Hagedorn, Soil Biogeochemistry, Swiss Federal Institute for Forest, Snow and Landscape Research, Zürcherstr. 11, 8903 Birmensdorf.

Turkey

Onay TURGUT, Orhan YENIGUN, Institute of Environmental Sciences, Bogazici University, Bebek, 34342 Istanbul.

United Kingdom

Marcel VAN OIJEN, Centre for Ecology and Hydrology, Biogeochemistry Programme, Bush Estate, Penicuik EH26 0QB.

Maurizio MENCUCCINI, School of GeoSciences, The University of Edinburgh, Crew Building, King's Buildings, West Mains Road, Edinburgh EH9 3JN.

Pete SMITH, Modelling Research Group, School of Biological Sciences, University of Aberdeen, Cruickshank Building, St Machar Drive, Aberdeen B24 3UU

References

Fischlin, A., Midgley, G.F., Price, J.T. et al. (2007) Ecosystems, their properties, goods, and services, in Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (eds M.L. Parry, O.F. Canziani, J.P. Palutikof et al.), Cambridge University Press, Cambridge, 211–272.

IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National Greenhouse Gas Inventories Programme (eds H.S. Eggleston, L. Buendia, K. Miwa et al.). Institute for Global Environmental Strategies (IGES), Japan.

Körner, C. (2003) Slow in, rapid out – Carbon flux studies and Kyoto targets. Science, 300, 1242–1243.

Kutsch, W.L., Bahn, M. and Heinemeyer, A. (eds) (2009) Soil carbon dynamics – an integrated methodology. Cambridge University Press.

Lal, R. (2004) Soil carbon sequestration impacts on climate change and food security. Science, 304, 1623–1627.

Lal, R., and Follett R.F. (2009) Soil Carbon Sequestration and the Greenhouse Effect, 2nd edn, SSSA Special Publication Vol. 57, Soil Science Society of America.

Roose, E.J., Lal, R., Feller, C. et al. (2005) Soil Erosion and Carbon Dynamics (Advances in Soil Science). CRC Press Inc.

2

Hot spots and hot moments for greenhouse gas emissions from soils

Frank Hagedorn¹ and Pat Bellamy²

¹Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland

²Natural Resources Department, Cranfield University, Cranfield, Bedfordshire, UK

2.1 Introduction

Hot spots are areas (or patches) that show disproportionately high reaction rates relative to the surrounding area (or matrix) (McClain et al., 2003). The concept can apply to either one or several biogeochemical reactions. However, hot spot reactions are often limited because one reactant is unstable in the dominant biogeochemical environment, or because the reaction only proceeds under particular/specific conditions (for example anoxia). From a mechanistic standpoint, hot spots are sites where individual ingredients (reactants) for specific biogeochemical reactions coincide (Figure 2.1). With respect to greenhouse gas emissions, hot spots are patches that (i) have a high and continuing supply of reactants and that (ii) have favourable conditions for the production of greenhouse gases. For instance, in the case of nitrous oxide (N2O) emissions, hot spots are sites under partially anoxic conditions having a high supply in microbially available carbon and NO3− (NO3−-rich groundwater entering a carbon-rich riparian zone).

Figure 2.1 Schematic illustrations for hot spot formation: (a) complementary reactants are mixing; (b) reactant B is transported into a patch containing reactant A (from McClain et al., 2003).

ch02fig001.eps

While hot spots are sites with extraordinary high reaction rates, hot moments are short periods that show disproportionately high reaction rates relative to longer intervening periods (McClain et al., 2003). Extraordinary high N2O losses at soil thawing or snowmelt are a typical hot moment where the major fluxes of the annual greenhouse gas emissions occur within a very short period (Papen and Butterbach-Bahl, 1999). Hot spots and moments may occur separately, but they may also overlap when high reaction rates occur for short periods at specific locations. For any particular area of soil, the measurements of, for example, denitrification rates are generally low with a few samples exhibiting extremely high rates, leading to a skewed probability distribution which can be described by a lognormal distribution (Parkin, 1987). This skewed distribution was also observed by Lark et al. (2004) in their data on N2O emission rates from a transect of 1000 m sampled at 4 m intervals. Lark et al. (2004) chose to analyse their data using wavelets, as this does not need normally distributed data. In ordinary correlation analysis strongly skewed data should be transformed, so as to reduce the leverage of observations in the upper tails of the marginal distributions. If such observations have different correlations from the rest, then the wavelet analysis should show this as different wavelet correlations at one or more spatial scales. This kind of skewed probability distribution with a small number of hotspots implies that (i) the processes and fluxes of a whole area are determined by a small fraction of it, (ii) that important sites and periods can easily be missed and (iii) that, as a consequence, the uncertainties associated with estimates for an area are high.

The hot spot or hot moment concept can also be applied to the effects of disturbances on greenhouse gas emissions. Perturbation can turn areas with formerly low emissions into hot spots by making reactants available or changing the environmental conditions. For instance, drainage can turn peatlands into large carbon dioxide sources through aeration, which improves the formerly hampered conditions for decomposition (Martikainen et al., 1993).

2.2 Hot spots: where are they?

Hot spots have been investigated at a number of different spatial scales from single aggregates (Parkin, 1987), soil profiles (Bundt et al., 2001) and fields (Röver et al., 1999) to landscapes (Sommer et al., 2004; Mitchell & Branfireun, 2005). These studies suggest that conditions for hot spots often occur at interfaces between different environments providing a continuous supply with different reactants to maintain high processing rates. Spatially, these are locations where aerobic conditions change into anaerobic conditions, which occur at different spatial scales from aggregates with anoxic microsites to landscapes with interfaces between upland and peatland areas. A review by McClain et al. (2003) suggests that hot spots are often associated with hydrological flow paths, where a constantly high supply of reactant is provided.

Denitrification is a good example how hot spots are linked to interfaces and water flow. The factors controlling denitrification rates are carbon and NO3− supply and anoxia. Appropriate conditions for the formation of denitrification hot spots are found at oxic–anoxic interfaces crossed by a continual water flow. Oxic conditions are needed for NO3− production by nitrification, denitrification requires anoxic conditions, and water serves as the transport medium. The underlying physiological basis for denitrification remains the same irrespective of the scale of analysis. At the soil profile scale, hot spots for N2O are patches of organic materials that are supplied with nitrate (Hojberg, Revsbech and Tiedje, 1994). At the landscape scale, riparian zones are hot spots for denitrification, because NO3− from upland areas flows and reacts in a carbon-rich partly anoxic environment (Martin et al., 2004).

2.2.1 Preferential flow paths – hot spots in soils

Surfaces of soil aggregates experiencing strong gradients in redox conditions and in substrate supply are known to be hot spots at the microscale (Parkin, 1987). At the soil profile scale, preferential flow paths – the dominant hydrological flow paths across a small part of the soil – have been identified as hot spots for carbon and nitrogen cycling (Hagedorn et al., 1999; Bundt et al., 2001). In a sprinkling experiment in a Swiss forest soil, a colour dye, brilliant blue, was first applied homogenously onto the soil surface. Then, soils were sampled from the blue-coloured flow paths and analysed for their biochemical properties (Figure 2.2).

Figure 2.2 Flow patterns in soils emerging after the addition of brilliant blue. Contents of microbial biomass and soil organic matter in the shaded (black patches) flow paths and in the non-coloured soil matrix (from Bundt et al., 2001; Hagedorn and Bundt, 2002).

ch02fig002.eps

Soils from the flow paths were clearly enriched in soil organic matter, microbial biomass and in DNA (Bundt et al., 2001; Hagedorn and Bundt, 2002), indicating that predominant water flow pathways were also sites with an increased microbial activity. This conclusion agrees with a field study, in which 50 micro suction cups, each with a surface area of 12 mm², were installed in a regular grid in the uppermost 5 cm of a subalpine Gleysol (Hagedorn et al., 1999). Based on the response of the micro suction cups to a brilliant blue dye tracer addition, the individual micro cups were assigned to dominant flow paths or to the soil matrix. The sites along flow paths had significantly higher NO3− concentrations. In contrast to the ‘slowly’ responding cups of the soil matrix, the temporal NO3− dynamics in flow paths closely matched denitrification, which suggests that sites along flow paths were also hot spots for nitrogen cycling and gaseous nitrogen losses (Figure 2.3). This clearly fits into the hot spot concept, where hot spots are located at the interface between oxic and anoxic conditions and at sites that have a continuous high supply of reactants.

2.2.2 Boundary and transient ecosystems as hot spots

The requirements for hot spots suggest that they are rather at the boundary of and at transitions between different soil forms and in temporarily changing ecosystems. On a spatial scale, riparian zones are typical hot spots that are wetlands at the transition between upland and aquatic environments which have a strong gradient in redox potentials (Mitchell and Branfireun, 2005). These landscape-level interfaces between oxic and anoxic conditions are often highly supplied with carbon and with NO3− from ground and surface waters, which makes them into hot spots for N2O, methane and DOC (Martin et al., 2004; Jones and Mulholland, 1998, Sommer et al., 2004; Fiedler, Höll and Jungkunst, 2005). Attempts to scale up by relating denitrification to the presence of riparian wetlands at the scale of 10–100 km² catchments have been largely unsuccessful (Osborne & Wiley, 1988; Tufford, McKellar and Hussey, 1998). At this scale, the arrangement of the wetlands relative to