Articles | Volume 13, issue 19
Research article
13 Oct 2016
Research article |  | 13 Oct 2016

Soil carbon response to land-use change: evaluation of a global vegetation model using observational meta-analyses

Sylvia S. Nyawira, Julia E. M. S. Nabel, Axel Don, Victor Brovkin, and Julia Pongratz

Abstract. Global model estimates of soil carbon changes from past land-use changes remain uncertain. We develop an approach for evaluating dynamic global vegetation models (DGVMs) against existing observational meta-analyses of soil carbon changes following land-use change. Using the DGVM JSBACH, we perform idealized simulations where the entire globe is covered by one vegetation type, which then undergoes a land-use change to another vegetation type. We select the grid cells that represent the climatic conditions of the meta-analyses and compare the mean simulated soil carbon changes to the meta-analyses. Our simulated results show model agreement with the observational data on the direction of changes in soil carbon for some land-use changes, although the model simulated a generally smaller magnitude of changes. The conversion of crop to forest resulted in soil carbon gain of 10 % compared to a gain of 42 % in the data, whereas the forest-to-crop change resulted in a simulated loss of −15 % compared to −40 %. The model and the observational data disagreed for the conversion of crop to grasslands. The model estimated a small soil carbon loss (−4 %), while observational data indicate a 38 % gain in soil carbon for the same land-use change. These model deviations from the observations are substantially reduced by explicitly accounting for crop harvesting and ignoring burning in grasslands in the model. We conclude that our idealized simulation approach provides an appropriate framework for evaluating DGVMs against meta-analyses and that this evaluation helps to identify the causes of deviation of simulated soil carbon changes from the meta-analyses.

Short summary
We introduce an approach applicable to dynamic global vegetation models for evaluating simulated soil carbon changes from land-use changes against meta-analyses. The approach makes use of the large spatial coverage of the observations, and accounts for different ages of the sampled land-use transitions. The evaluation offers an opportunity for identifying causes of model–data discrepancies. Applied to the model JSBACH, we find that introducing crop harvest substantially improves the results.
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