Mon, Aug 02, 2021:On Demand
Background/Question/Methods
Microbial communities regulate ecosystem responses to climate change. But predicting these responses is challenging due to complex interactions among processes at multiple ecological scales. Organismal traits determine individual performance and ecological interactions; therefore, they are essential for connecting environmental variation to ecological processes across scales, from individuals to ecosystems. The question is, can traits be used to predict these complex ecological responses to environmental change? We address this question using protists: single-celled eukaryotes that are central to food webs throughout the world and play a fundamental role in ecosystem functioning through top-down controls on bacterial and fungal decomposers. Using imaging microscopy, we measure three key functional traits associated with individual-level performance—cell size, shape, and contents. We compare variation in these traits with changes in population-level performance (intrinsic growth rate and negative density dependence) across temperatures using laboratory microcosm experiments. These population-level data are then incorporated into a community model to assess the impacts of temperature on equilibrium abundances, species composition, network structure, and total system respiration. Finally, we test these model predictions empirically by measuring these community- and ecosystem-level features in a second, community microcosm experiment.
Results/Conclusions We find that different microbial traits independently drive shifts in demographic rates across temperatures, having cascading effects on community structure, dynamics, and ecosystem functioning. Intra- and interspecific trait variation play distinct, trait-specific roles in these multi-scale temperature responses. Our community experiment shows that species-level responses scale up to cause predictable, nonlinear shifts in microbial community composition and respiration rates. Indeed, disentangling the unique roles of specific microbial traits on species’ demographic responses to temperature allows us to mechanistically track how temperature drives shifts in species richness, community network structure, and total community respiration. Because protists are ‘puppet masters’ of nutrient flux within microbial communities, these results have direct implications for the effects of warming on the global carbon cycle. By mechanistically linking environmental variation with microbial processes across scales through protist traits, our framework opens up possibilities to create a more holistic understanding of the climate-ecosystem feedbacks that control the pace of climate change itself. Such a multi-level, multi-trait approach is crucial for explaining spatiotemporal variation in the structure and function of ecosystems and forecasting the complex causes and consequences of climate change in the future.
Results/Conclusions We find that different microbial traits independently drive shifts in demographic rates across temperatures, having cascading effects on community structure, dynamics, and ecosystem functioning. Intra- and interspecific trait variation play distinct, trait-specific roles in these multi-scale temperature responses. Our community experiment shows that species-level responses scale up to cause predictable, nonlinear shifts in microbial community composition and respiration rates. Indeed, disentangling the unique roles of specific microbial traits on species’ demographic responses to temperature allows us to mechanistically track how temperature drives shifts in species richness, community network structure, and total community respiration. Because protists are ‘puppet masters’ of nutrient flux within microbial communities, these results have direct implications for the effects of warming on the global carbon cycle. By mechanistically linking environmental variation with microbial processes across scales through protist traits, our framework opens up possibilities to create a more holistic understanding of the climate-ecosystem feedbacks that control the pace of climate change itself. Such a multi-level, multi-trait approach is crucial for explaining spatiotemporal variation in the structure and function of ecosystems and forecasting the complex causes and consequences of climate change in the future.