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Abstract The oceans sequester a vast amount of carbon thus playing a central role in the global carbon cycle. Assessing how carbon cycling will be impacted by climate change requires an improved understanding of microbial dynamics, which are responsible for most carbon transformations in the oceans. Current numerical models used for predicting future states represent simplified microbial phenotypes and thus may not produce robust predictions of microbial communities. We propose reframing approaches for studying microbial trait change to allow for selection on multi-trait phenotypes. Integrating statistical approaches and trait-based models will allow for the incorporation of evolution into carbon cycle predictions. 

The oceans contain large reservoirs of inorganic and organic carbon and play a critical role in both global carbon cycling and climate. Most of the biogeochemical transformations in the oceans are driven by marine microbes. Thus, molecular processes occurring at the scale of single cells govern global geochemical dynamics, posing a challenge of scales. Understanding the processes controlling ocean carbon cycling from the cellular to the global scale requires the integration of multiple disciplines including microbiology, ecology, biogeochemistry, and computational fields such as numerical models and bioinformatics. A shared language and foundational knowledge will facilitate these interactions. This review provides the state of knowledge on the role marine microbes play in large-scale ocean carbon cycling through the lens of observational oceanography and biogeochemical models. We conclude by outlining ways in which the field can bridge the gap between -omics datasets and ocean models to understand ocean carbon cycling across scales. 

Phytoplankton are responsible for half of all oxygen production and drive the ocean carbon cycle. Metabolic theory predicts that increasing global temperatures will cause phytoplankton to become more heterotrophic and smaller. Here, we uncover the metabolic trade-offs between cellular space, energy, and stress management driving phytoplankton thermal acclimation and how these might be overcome through evolutionary adaptation. We show that the observed relationships between traits such as chlorophyll, lipid content, C:N, and size can be predicted on the basis of the metabolic demands of the cell, the thermal dependency of transporters, and changes in membrane lipids. We suggest that many of the observed relationships are not fixed physiological constraints but rather can be altered through adaptation. For example, the evolution of lipid metabolism can favor larger cells with higher lipid content to mitigate oxidative stress. These results have implications for rates of carbon sequestration and export in a warmer ocean.