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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. 

Microorganisms in marine oxygen minimum zones (OMZs) drive globally impactful biogeochemical processes. One such process is multistep denitrification (NO₃^–→NO₂^–→NO→N₂O→N₂), which dominates OMZ bioavailable nitrogen (N) loss and nitrous oxide (N₂O) production. Denitrification-derived N loss is typically measured and modeled as a single step, but observations reveal that most denitrifiers in OMZs contain subsets (“modules”) of the complete pathway. Here, we identify the ecological mechanisms sustaining diverse denitrifiers, explain the prevalence of certain modules, and examine the implications for N loss. We describe microbial functional types carrying out diverse denitrification modules by their underlying redox chemistry, constraining their traits with thermodynamics and pathway length penalties, in an idealized OMZ ecosystem model. Biomass yields of single-step modules increase along the denitrification pathway when organic matter (OM) limits growth, which explains the viability of populations respiring NO₂^–and N₂O in a NO₃^–-filled ocean. Results predict denitrifier community succession along environmental gradients: Pathway length increases as the limiting substrate shifts from OM to N, suggesting a niche for the short NO₃^–→NO₂^–module in free-living, OM-limited communities, and for the complete pathway in organic particle-associated communities, consistent with observations. The model captures and mechanistically explains the observed dominance and higher oxygen tolerance of the NO₃^–→NO₂^–module. Results also capture observations that NO₃^–is the dominant source of N₂O. Our framework advances the mechanistic understanding of the relationship between microbial ecology and N loss in the ocean and can be extended to other processes and environments. 

Heterotrophic bacteria and archaea (“heteroprokaryotes”) drive global carbon cycling, but how to quantitatively organize their functional complexity remains unclear. We generated a global-scale understanding of marine heteroprokaryotic functional biogeography by synthesizing genetic sequencing data with a mechanistic marine ecosystem model. We incorporated heteroprokaryotic diversity into the trait-based model along two axes: substrate lability and growth strategy. Using genetic sequences along three ocean transects, we compiled 21 heteroprokaryotic guilds and estimated their degree of optimization for rapid growth (copiotrophy). Data and model consistency indicated that gradients in grazing and substrate lability predominantly set biogeographical patterns, and we identified deep-ocean “slow copiotrophs” whose ecological interactions control the surface accumulation of dissolved organic carbon. 

Marine microbes form the base of ocean food webs and drive ocean biogeochemical cycling. Yet little is known about the ability of microbial populations to adapt as they are advected through changing conditions. Here, we investigated the interplay between physical and biological timescales using a model of adaptation and an eddy-resolving ocean circulation climate model. Two criteria were identified that relate the timing and nature of adaptation to the ratio of physical to biological timescales. Genetic adaptation was impeded in highly variable regimes by nongenetic modifications but was promoted in more stable environments. An evolutionary trade-off emerged where greater short-term nongenetic transgenerational effects (low-γ strategy) enabled rapid responses to environmental fluctuations but delayed genetic adaptation, while fewer short-term transgenerational effects (high-γ strategy) allowed faster genetic adaptation but inhibited short-term responses. Our results demonstrate that the selective pressures for organisms within a single water mass vary based on differences in generation timescales resulting in different evolutionary strategies being favored. Organisms that experience more variable environments should favor a low-γ strategy. Furthermore, faster cell division rates should be a key factor in genetic adaptation in a changing ocean. Understanding and quantifying the relationship between evolutionary and physical timescales is critical for robust predictions of future microbial dynamics.