Trait-based modeling of microbial decomposition

Background/Question/Methods

Diverse bacterial and fungal communities control the decomposition of complex organic material, thereby driving important ecosystem functions such as CO₂ production and nutrient regeneration. Predicting these functions is challenging because microbial communities and the chemical substrates they metabolize are complex. To address this challenge, I developed a theoretical model of microbial decomposition based on microbial traits involved in substrate degradation, uptake, and growth. The model represents a large number of microbial taxa, each of which possesses a set of trait values drawn at random from empirically-based distributions. The model also includes a large number of chemical substrates that can be degraded by microbial extracellular enzymes and taken up by membrane transporters. Microbes with different trait values for enzyme production and uptake capacity compete for chemical substrates and vary in abundance during model runs. I used the model to ask how spatial structure, enzyme specificity, and differences in microbial trait values affected community dynamics and the degradation of organic matter.

Results/Conclusions

Model results indicate that microbial communities are unstable in the absence of spatial structure, and collapse to a small number of taxa. Spatial structure leads to maintenance of diversity by introducing variation in substrate availability and resource supply. The model also suggests that microbes may trade off enzyme specificity and catalytic rate, such that highly specific enzymes can degrade or take up a narrow range of substrates at high rates. Such a tradeoff implies that specialist microbes may predominate in environments with pulse inputs of a small number of substrates, whereas generalists should predominate in environments with more constant inputs of a broad range of substrates. Together these results illustrate the range of strategies that microbes may employ in the process of organic matter degradation. Furthermore the optimal strategy differs according to the chemical composition of available substrates. Trait-based approaches to modeling complex microbial communities may provide a useful alternative to models that represent microbial taxa in discrete functional groups.