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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. 

Abstract Atlantic bluefin tuna (ABT) (Thunnus thynnus) travel long distances to spawn in oligotrophic regions of the Gulf of Mexico (GoM) which suggests these regions offer some unique benefit to offspring survival. To better understand how larval survival varies within the GoM a spatially explicit, Lagrangian, individual-based model was developed that simulates dispersal and mortality of ABT early life stages within realistic predator and prey fields during the spawning periods from 1993 to 2012. The model estimates that starvation is the largest cumulative source of mortality associated with an early critical period. However, elevated predation on older larvae is identified as the main factor limiting survival to late postflexion. As a result, first-feeding larvae have higher survival on the shelf where food is abundant, whereas older larvae have higher survival in the open ocean with fewer predators, making the shelf break an optimal spawning area. The modeling framework developed in this study explicitly simulates both physical and biological factors that impact larval survival and hence could be used to support ecosystem based management efforts for ABT under current and future climate conditions.