2020 ESA Annual Meeting (August 3 - 6)

OOS 7 Abstract - Modelling microbial trait evolution to predict soil carbon-climate feedbacks at local and global scales

Elsa Abs, Ecology and Evolutionary Biology, UC Irvine, Irvine, CA
Background/Question/Methods

There is increasing evidence that ecological and physiological processes in microbial communities play an important role in mediating microbial decomposition of soil organic matter. In particular, these processes will likely strongly influence the direction and amplitude of soil carbon-climate feedbacks. Neglected so far, however, is explicit evaluation of how evolutionary responses within microbial communities may affect the soil decomposition response to warming. To address this gap, we build an eco-evolutionary model of soil decomposition and test three scenarios of temperature sensitivity to investigate (i) the microscopic processes of microbial competition over diffusing resources (ii) the evolutionary dynamics of a key microbial trait, investment in enzyme production, (iii) how this evolutionary response feeds back on soil carbon stocks, and (iv) where, given variations in climate, organic matter substrate, and microbial traits, to expect the strongest evolutionary effects on soil carbon feedbacks to climate across terrestrial habitats around the globe.

Results/Conclusions

Spatially explicit simulations show a strong effect of the diffusibility of resources on microbial investment in production of extracellular enzymes. Microbes evolve high enzyme production in low diffusive soils, and either low or high enzyme production at high temperature depending on the temperature sensitivity scenario. In scenarios of higher enzyme production, microbial adaptive evolution accelerates decomposition and increases soil carbon loss predicted by models without evolution. This loss is however offset in scenarios of lower enzyme production. At the global scale microbial evolution could aggravate carbon loss by 33% overall. Our results highlight the pressing need to investigate experimentally microbial evolutionary response to climate change and to include soil eco-evolutionary feedbacks to carbon cycling in global climate models.