ELSEVIER Geoderma 81 (1997) 1-3

G E O D E R ~

Preface

Soil organic matter (SOM) represents a major pool of carbon within the biosphere, estimated at about 1400 X 10 ~5 g globally, roughly twice that in atmospheric CO 2. SOM may act as both a source and sink of carbon during global environmental change. Changes in climate are likely to influence the rates of accumulation and decomposition of carbon in SOM, both directly through changes in temperature and moisture, and indirectly through changes in plant growth and rhizodeposition. Other factors, especially changes in land-use and management, may have even greater effects. Changes in land-use or manage- ment may occur as a direct result of climate change or other environmental factors, or may be influenced by agricultural, economic or social policies.

SOM models embody our best understanding of soil carbon dynamics and may be used to predict how global environmental change will influence soil carbon stocks, and to evaluate the likely effectiveness of different mitigation options. The primary purpose of the exercise reported in this special issue was to identify which SOM models are likely to be most appropriate for these purposes.

The first important step towards the systematic evaluation of SOM models is to test their simulations against real data. SOM turnover can be measured on both short (within year) and long (years, decades) time-scales, but it is the long-term trends that determine whether SOM will act as a net source or sink for carbon in ecosystems under global environmental change. It is essential, there- fore, that the models are evaluated against long-term data. Soil organic carbon (SOC) was chosen as the key measurement against which to test SOM models since it directly describes the carbon stock of the soil. Furthermore, it is the one variable that all models can simulate and for which measured data are available at all selected sites.

The work reported in this special issue was initiated at a NATO Advanced Research Workshop entitled 'Evaluation of Soil Organic Matter Models Using Existing Long-Term Datasets' held at IACR-Rothamsted, Harpenden, U.K. on 21-26 May 1995 which also marked the launch of the Global Change and Terrestrial Ecosystems (GCTE) Soil Organic Matter Network (SOMNET). This workshop brought together leading SOM model developers and leading long-term experimentalists from around the world to begin the process of testing SOM

0016-7061/97/$17.00 Published by Elsevier Science B.V.

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models. Long-term datasets from diverse ecosystems, land-uses and climatic zones within the temperate region were used. The key-note addresses, and model and experimental descriptions from this workshop can be found in: D.S. Powlson, P. Smith and J.U. Smith (Eds.) (1996) Evaluation of Soil Organic Matter Models Using Existing, Long-Term Datasets, NATO ASI I38, Springer- Verlag, Heidelberg, 429 pp. During this workshop modellers and dataholders exchanged data and ideas, and over the following year, nine models attempted to simulate twelve datasets from seven long-term experiments. It is this body of work that is reported in this special issue.

Since the range of land-uses, climatic conditions and land management practices represented among the datasets was so broad, many of the selected models had not been tested before under such conditions, and none of the models were parametrized to meet all situations. It was therefore decided at the workshop that modellers should be allowed to tune model outputs using site-specific data, by adjusting the initial distribution of carbon in the different model pools and exercising their judgement about organic carbon inputs other than those that had been specified (e.g. root turnover, rhizodeposition etc.). Modellers were also allowed discretion to choose appropriate starting values for SOC content, though many of the modellers used common starting values, usually the first measured data-point. It was decided that no modeller would be allowed to adjust run-time parameters such as SOM partitioning and turnover rate coefficients. In all cases but one, as much data as possible was made available to the modellers, including measured SOC values. As such, this exercise tests the ability of SOM models to simulate changes in SOC and does not test the predictive ability of the models. In one case, however, measured SOC data were withheld but all other data were provided, with SOC data for another selected rotation at the same site being provided to allow site-specific tuning. This was the only case in this exercise when models were forced to predict changes in SOC.

Although the work described in this special issue constitutes the most comprehensive evaluation and comparison of long-term SOM models to date, much work remains. Whilst the ability of models to simulate long-terms trends in SOC is of critical importance in determining which models are most suited for studying global environmental change in different ecosystems and climatic zones, short-term data such as surface CO 2 flux, soil water content, soil temperature, and detailed measurements of above- and below-ground carbon and nitrogen inputs etc., may be important for evaluating the description of short-term processes in models in order to explain why models perform better in some situations than others. A valuable future exercise would be to evaluate SOM models at the level of these shorter-term processes. Another key area that merits further attention is the ability of models to predict SOC dynamics without site-specific calibration. For use at large scales, and for predicting future changes, calibration data such as those used in this exercise will not exist. A

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major obstacle to the confident predictive use of models in global environmental change research is the need for such model calibration. Having determined in this exercise which models perform well in which situations, future SOM model evaluations should address these issues.

We thank Dr. Alex McBratney for the final evaluation of this special issue. We are grateful to NATO for sponsoring the workshop, and to the UK Natural Environment Research Council (NERC) for supporting PS to co-ordinate this exercise through a grant from its Terrestrial Initiative in Global Environmental Research (TIGER) programme.

Pete Smith David S. Powlson

Jo U. Smith E.T. (Ted) Elliott

(Guest Editors)