Historical contingencies in microbial responses to climate change can constrain ecosystem responses
Although climate is a primary controller of microbial function, our understanding of how microbial communities will respond to climate change remains poorly understood. In part, this uncertainty arises from a lack of understanding of microbial response mechanisms and how those scale up to aggregate soil function. Environmental tracking would be facilitated if microbial communities respond to new climatic conditions via rapid physiological acclimatization, shifts in community composition, or adaptation. In contrast, historical contingencies could result from dispersal limitation or local adaptation to previous conditions. To address responses ranging from environmental tracking to historical contingency, we examined how soil microbial communities were affected by climate change at multiple scales and asked whether current or historical environment was a primary driver of the observed responses. We used a combination of lab incubations, reciprocal transplants, and climate manipulations to approach this problem.
Soil microbial community composition and function were strongly associated with historical conditions. Across a rainfall gradient, two-thirds of the variation in community composition was explained by mean annual precipitation. In experimental lab manipulations over one year, soil functional responses were constrained by historical rainfall, with a lower functional capacity in soils from drier sites regardless of current moisture. Historical effects held even after 18 months in reciprocal transplant common gardens in the field. Furthermore, when rainfall was manipulated at a single site over 4 years, new legacies did not develop. Overall, these findings are consistent with historical environmental conditions acting as a strong filter and constraining how microbial community composition and physiological respond to climate change. Placing the ecological and evolutionary dynamics of microbial communities in the context of historical and future environmental variation may thus provide us with a framework for improving prediction of ecosystem responses to climate change.