Evolutionary adaptation of soil microbial communities to climate change

Recent theory suggests that the evolutionary adaptation of soil microbial communities to climate change could significantly aggravate the currently predicted  global soil carbon loss in response to global warming through the selection of gene variants affecting carbon-cycling traits (e.g. respiration, decomposition or secondary metabolites production).

However, empirical evidence is still lacking to quantify the rate and magnitude of evolutionary changes in carbon-cycling traits across bacterial functional groups. This gap limits the integration of microbial evolutionary responses into carbon biogeochemical models.

We analysed long-term (10 years) high throughput metagenomic time series from two global change experiments: the SPRUCE peatland experiment (warming and elevated CO₂) and the Loma Ridge grassland drought experiment. We combined classical metagenomic analyses (read alignment, SNP detection) with collapsing gene-level variation into functional trait categories.

Focusing on the most abundant Metagenomes Assembled Genomes (MAGs), e.g. Acidocella sp., (> 10X and 50% of coverage), we identified genes showing signs of adaptive evolution associated with carbon-cycling traits, revealing which traits exhibit the strongest evolutionary responses under climate-change treatments such as traits involved in cellulose degradation.

These results provide a framework to link metagenomic time series with process-based carbon models by defining empirical-based evolutionary markers of climate-change response, enabling the explicit inclusion of microbial evolutionary dynamics in global carbon models such as ORCHIDEE.