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Mustri, M. P.

Publications and source records attributed to Mustri, M. P..

2 recordsLinked to original sources

A General Framework for Predicting the Temperature-Dependence of Microbial Interactions

Despite its global importance, our ability to predict the impacts of temperature change on the community dynamics of heterotrophic microbes remains limited. Here, we develop a metabolic trait-based mathematical framework to predict the temperature dependence of pairwise interactions among heterotrophic microbial consumers, accounting for their resource environment and community composition. Applying this framework leads to two general predictions. First, microbial species interactions are typically more thermally sensitive than the underlying metabolic traits. Second, temperature systematically reshapes intra- and interspecific interactions: their variance peaks at intermediate temperatures, while mean interaction strengths increase with warming more rapidly than interspecific interaction strengths. We show that these features of temperature-dependent interactions have far-reaching implications for the temperature responses of community coexistence, diversity, and stability. Our framework provides a mechanistic foundation for predicting how temperature affects the dynamics of heterotrophic microbial communities across diverse biological and environmental contexts. SignificanceCommunities of heterotrophic microbes, including bacteria, archaea, protists, and fungi, play a fundamental role in human health, bioprocessing, and global biogeochemical cycles. Predicting their responses to environmental change is a major challenge, with a key missing link being the effects of temperature on species interactions that ultimately shape community dynamics. By integrating metabolic constraints into consumer-resource theory, we derive general predictions about how interactions among heterotrophic microbial species respond to temperature changes. We show that interactions are more sensitive to warming than individual metabolic traits and undergo systematic temperature-dependent changes that alter community-level coexistence, diversity, and stability. These results hold across diverse environmental contexts and heterotrophic systems, providing a foundation for predicting how microbial community dynamics respond to environmental temperature, from biotechnological applications to natural ecosystems.

ecology↗

Accuracy of the Lotka-Volterra Model fails in strongly coupled microbial consumer-resource systems

The generalized Lotka-Volterra (GLV) model is a cornerstone in theoretical ecology for modeling the dynamics emerging from pairwise species interactions within complex ecological communities. The GLV is also increasingly being used to infer species interactions and predict dynamics from empirical data on microbial communities in particular. However, despite its widespread use, the accuracy of the GLVs pairwise interaction structure in capturing the unseen dynamics of microbial consumer-resource interactions--arising from resource competition and metabolite exchanges--remains unclear. Here, we rigorously quantify how well the GLV can represent the dynamics of a general mathematical model that encapsulates key consumer-resource processes in microbial communities. We find that the GLV significantly misrepresents the feasibility, stability, and reactivity of microbial communities above a threshold, biologically feasible level of consumer-resource coupling because it omits higher-order nonlinear interactions. We show that the probability of the GLV making inaccurate predictions can be quantified by a simple, empirically accessible measure of timescale separation between consumers and resources. These insights advance understanding of the temporal dynamics in resource-mediated microbial interactions and provide a method to gauge the GLVs reliability under various empirical and theoretical scenarios.

ecology↗