Short- and Long-term Influence of Litter Quality and Quantity on Simulated Heterotrophic Soil Respiration in a Lowland Tropical Forest
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Heterotrophic soil respiration (SRH) alone can contribute up to 50% of total ecosystem respiration in tropical forests. Whereas the abiotic controls of SRH have been extensively studied, the influence of plant traits is less well characterised. We used field experiments and a modelling approach to test the relative influence of plant traits on SRH in lowland tropical forest in French Guiana. We measured leaf- and root litter traits for five common tree species and conducted a root decomposition experiment to evaluate the influence of root chemistry on decay rates. We measured SRH in trenched plots and used our field measurements to parameterize and test the Century model of soil C dynamics. Overall, the Century model performed well in simulating SRH, and species-specific root decomposition in Century corresponded well to decomposition rates measured in situ. Root litter characterized by low lignin-to-nitrogen ratios decomposed more rapidly than low-quality root litter during the first 6 months. Model runs over different time scales revealed that litter quality substantially influenced SRH on an annual time-scale by determining the rates of root- and leaf litter decomposition. However, litter mass had an overriding influence on SRH over the longer term in 20-year model runs. Synthesis Using simple plant trait data to parameterise the Century model, we were able to accurately simulate changes in SRH in a lowland tropical forest. Our results suggest that this approach could be used to predict changes in tropical soil C dynamics under global change scenarios by including data on changes in plant productivity and C inputs to the soil (for example litterfall and root turnover).
KeywordsCentury model decomposition leaf litter fine roots heterotrophic soil respiration sensitivity analysis soil carbon dynamics plant traits
We wish to thank Cyril Douthe and Louis Maire for their help during data acquisition in the field and laboratory. We are grateful to Nick Ostle and Ed Tanner for their helpful comments on improving the earlier drafts of the manuscript. We also acknowledge two anonymous reviewers who provided thoughtful comments that improved this manuscript. LB was funded by a PhD Grant from the French “Ministère de l’Education Nationale et de la Recherche”. The UMR EEF is supported by the French National Research Agency through the Laboratory of Excellence ARBRE (ANR-12- LABXARBRE-01). EJS was supported by funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013), ERC Grant Agreement No. 307888.
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