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            <funder>Funding was provided to E.A. by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 891576. S.M. has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 101001608). E.A., S.M., P.C., and S.D.A. acknowledge support from the CALIPSO project (Carbon Loss in Plant Soils and Oceans) project, funded through the generosity of Eric and Wendy Schmidt by recommendation of the Schmidt Futures program.</funder>
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              <p>Abstract Although substantial advances in predicting the ecological impacts of global change have been made, predictions of the evolutionary impacts have lagged behind. In soil ecosystems, microbes act as the primary energetic drivers of carbon cycling; however, microbes are also capable of evolving on timescales comparable to rates of global change. Given the importance of soil ecosystems in global carbon cycling, we assess the potential impact of microbial evolution on carbon‐climate feedbacks in this system. We begin by reviewing the current state of knowledge concerning microbial evolution in response to global change and its specific effect on soil carbon dynamics. Through this integration, we synthesize a roadmap detailing how to integrate microbial evolution into ecosystem biogeochemical models. Specifically, we highlight the importance of microscale mechanistic soil carbon models, including choosing an appropriate evolutionary model (e.g., adaptive dynamics, quantitative genetics), validating model predictions with ‘omics’ and experimental data, scaling microbial adaptations to ecosystem level processes, and validating with ecosystem‐scale measurements. The proposed steps will require significant investment of scientific resources and might require 10–20 years to be fully implemented. However, through the application of multi‐scale integrated approaches, we will advance the integration of microbial evolution into predictive understanding of ecosystems, providing clarity on its role and impact within the broader context of environmental change.</p>
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