{"type": "FeatureCollection", "features": [{"id": "10.1016/j.ecolmodel.2023.110507", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:15:47Z", "type": "Journal Article", "created": "2023-10-10", "title": "Interactive effects of microbial functional diversity and carbon availability on decomposition \u2013 A theoretical exploration", "description": "<div><p>Microbial functional diversity in litter and soil has been hypothesized to affect the rate of decomposition of organic matter and other soil ecosystem functions. However, there are no clear theoretical expectations on how these effects might change with substrate availability, heterogeneity in the substrate chemistry, and different aspects of functional diversity itself (number of microbial groups vs. distribution of functional traits). To explore how these factors shape the decomposition-diversity relation, we carry out numerical experiments using a flexible reaction network comprising microbial processes and interactions with bioavailable carbon (extracellular degradation, uptake, respiration, growth, and mortality), and ecological processes (competition among the different groups). We also considered diverse carbon substrates, in terms of varying nominal oxidation state of carbon (NOSC). The reaction network was used to test the effects of (i) number of microbial groups, (ii) number of carbon pools, (iii) microbial functional diversity, and (iv) amount of bioavailable carbon. We found that the decomposition rate constant increases with increasing substrate concentration and heterogeneity, as well as with increasing microbial functional diversity or variance of microbial traits, albeit these biological factors are less important. 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Several theories have been proposed to construct process-based kinetics laws, but most of these theories do not consider that microbial decomposers can adapt to environmental conditions, thereby modulating decomposition. Starting from the assumption that a homogeneous microbial community maximizes its growth rate over the period of decomposition, we formalize decomposition as an optimal control problem where the decomposition rate is a control variable. When maintenance respiration is negligible, we find that the optimal decomposition kinetics scale as the square root of the substrate concentration, resulting in growth kinetics following a Hill function with exponent 1/2 (rather than the Monod growth function). When maintenance respiration is important, optimal decomposition is a more complex function of substrate concentration, which does not decrease to zero as the substrate is depleted. 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