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Bubble-mediated exchange during wave breaking is an essential pathway for oxygen transfer at the ocean–atmosphere interface. Conventional wind-dependent gas transfer velocity formulations generally ignore wave-bubble effects and use local wind speed alone to determine the air–sea gas exchange rate. Here, we quantify the influence of waves and bubbles using a generalised wind-wave-bubble gas transfer formulation that accounts for symmetric (diffusive flux through the unbroken ocean and large bubble surface) and asymmetric (pressurised large and small bubbles that dissolve completely) contributions. We contrast it with a widely used wind-dependent formulation using simulations from a global ocean circulation model over the historical period (1959–2020). Including waves and bubbles reduces the model–observation mismatch with quality-controlled biogeochemical Argo float oxygen concentrations in key mode and deep water mass formation regions by ∼70% to 90% and captures observed episodes of bubble-induced supersaturation. This addresses the systematic oxygen undersaturation bias simulated by the wind-dependent simulation. These surface changes propagate into the interior, raising oxygen concentrations by +2 to +10 µmol kg⁻¹across most water mass layers. The wind-wave-bubble formulation also enhances flux variability across timescales, and amplifies the climatological seasonal amplitude of the global air–sea oxygen flux by ∼30% relative to the wind-dependent formulation. These results establish bubbles as a first-order, global-scale control on ocean oxygen, resulting in a closer match to observed oxygen saturation and enhancing interior oxygen ventilation. 

Diel vertical migrations in the ocean play a key role in predator-prey dynamics and the functioning of the biological carbon pump. However, changes in ocean conditions including warming and deoxygenation threaten to significantly perturb vertical migration patterns over the twenty-first century. Specifically, vertical migrations over regions of critically low oxygen, known as oxygen minimum zones (OMZs), are likely to be most sensitive to changes in temperature and oxygen. In this study, we apply a simplified prognostic ecosystem model (APECOSM-1D) to changing conditions in the Pacific Ocean OMZ as simulated by 13 Earth System Models from the Coupled Model Intercomparison Project Phase 6 (CMIP6). We find that modeled fish migration depths at a given location in the region may deepen or shoal by over 100 m by the end of the century; however, there are large uncertainties across the CMIP6 ensemble for the geographic pattern of migration depth changes. To reconcile this, we adopt a water mass based approach which aggregates changes into regions defined by their vertical oxygen minimum value. In this framework, we find that fish migration depths over the lowest oxygen core of the OMZ remain stable due to compensating changes in temperature and oxygen. Meanwhile, away from the OMZ core, ocean warming and deoxygenation together drive shallower migration depths in projected conditions. 

Abstract Climate change reduces ocean oxygen levels, posing a serious threat to marine ecosystems and their benefits to society. State‐of‐the‐art Earth System Models (ESMs) project an intensification of global oxygen loss in the future, but poorly constrain its patterns and magnitude, with contradictory oxygen gain or loss projected in tropical oceans. We introduce an oxygen water mass framework—grouping waters with similar oxygen concentrations from lowest to highest levels—and separate oxygen changes into two components: thetransformationof oxygen in water masses by biological, chemical, or physical processes along their pathways in “ventilation‐space,” and theredistributionof these water masses in “geographic‐space.” The redistribution of water masses explains the large projection uncertainties in the tropics. ESMs with more realistic representations of water masses provide tighter constraints on future redistribution than less skilled ESMs, leading to over a third more of tropical area exhibiting consistent oxygen projections (58% vs. 22%), and a 30% reduction in model spread for tropical oxygen projections. These higher‐skilled ESMs also project weaker global deoxygenation than less skilled models (median of −2.9 vs. −4.2 Pmol per °C of surface warming) controlled by an increase in global water residence times, and they project a stronger increase in oxygen minimum zone ventilation by ocean mixing. These tighter constraints on future oxygen changes are critical to anticipate and mitigate impacts for ecosystems and inform management and conservation strategies of marine resources. 

Abstract. Phytoplankton blooms, especially diatom blooms, account for a large fraction of marine carbon fixation. Species succession and biogeochemical parameters change rapidly over a bloom, and determine the resulting biological productivity. This study implemented daily sampling of a 24 L microcosm bloom simulation experiment to assess changes in assemblage and biogeochemical processes while excluding changes due to advection. 15NO3- and H13CO3- tracer incubations were performed alongside pigment and DNA sampling to compare temporal trends in community composition and primary productivity (nitrogen (N) and carbon (C) transport rates). Rapid drawdown of nutrients and maximum C and N transport rates corresponded with peak chlorophyll a and fucoxanthin pigment concentrations. Fucoxanthin, typically associated with diatoms, was the dominant diagnostic pigment, with very low peridinin (dinoflagellate) and zeaxanthin (cyanobacteria) concentrations, indicating a diatom bloom. 18S rRNA gene analysis showed clear community succession throughout the duration of the bloom and multiple species of diatoms co-occurred, including during the bloom peak. The presence of metazoan 18S, high carbon-to-chlorophyll ratios, and a model analysis provide evidence of grazing in the latter half of the bloom. A traditional bloom framework suggests that species succession occurs as the bloom progresses and that phytoplankton diversity reaches a minimum of just one or two dominant species when phytoplankton productivity is at its maximum. However, this study produced a negatively monotonic productivity–diversity relationship (PDR) with relatively high minimum diversity values. This 18S-based analysis therefore presents a more complex relationship between bloom progression and phytoplankton diversity. 

Abstract The northern Indian Ocean is a hotspot of nitrous oxide (O) emission to the atmosphere. Yet, the direct link between production and emission of O in this region is still poorly constrained, in particular the relative contributions of denitrification, nitrification and ocean transport to the O efflux. Here, we implemented a mechanistically based O cycling module into a regional ocean model of the Indian Ocean to examine how the biological production and transport of O control the spatial variation of O emissions in the basin. The model captures the upper ocean physical and biogeochemical dynamics of the northern Indian Ocean, including vertical and horizontal O distribution observed in situ and regionally integrated O emissions of 286 152 Gg N (annual mean seasonal range) in the lower range of the observation‐based reconstruction (391 237 Gg N ). O emissions are primarily fueled by nitrification in or right below the surface mixed layer (57%, including 26% in the mixed layer and 31% right below), followed by denitrification in the oxygen minimum zones (30%) and O produced elsewhere and transported into the region (13%). Overall, 74% of the emitted O is produced in subsurface and transported to the surface in regions of coastal upwelling, winter convection or turbulent mixing. This spatial decoupling between O production and emissions underscores the need to consider not only changes in environmental factors critical to O production (oxygen, primary productivity etc.) but also shifts in ocean circulation that control emissions when evaluating future changes in global oceanic O emissions. 

Bubble-mediated gas exchange associated with wave breaking is a critical pathway for ocean–atmosphere exchange of low solubility gases such as oxygen. Yet, ocean and climate models, as well as observation-based products, usually rely on wind-only air–sea flux formulations derived from carbon constraints that ignore the asymmetric nature of the bubble flux, contributing to discrepancies between estimates of oxygen inventories and their response to climate change. Without bubbles, gas exchange is controlled by a symmetric wind-driven exchange, with the ocean–atmosphere gas partial pressure difference controlling whether outgassing or uptake occurs. Bubbles entrained by wave breaking can enhance this symmetric turbulent exchange, and contribute an additional asymmetric flux, always leading to an uptake, as they get squeezed by hydrostatic pressure (large bubbles) or collapse and fully dissolve (small bubbles). We present an observation-constrained theoretical framework of the air–sea flux accounting for air entrainment due to wave breaking and symmetric and asymmetric bubble exchange. The combined evidence from theory, laboratory, and field measurements of carbon dioxide fluxes, oxygen concentration, and noble gas supersaturation yields a universal formulation of gas exchange which we implement into a global ocean biogeochemical model. We discuss the resulting oxygen fluxes and demonstrate that our wind–wave–bubble formulation better reproduces observed in situ oxygen concentrations in water mass formation regions, where air–sea exchange is high, than a commonly used wind-only formulation. We show that the asymmetric bubble flux is essential for evaluating air–sea oxygen fluxes and estimating the magnitude of the ocean oxygen loss associated with global warming. 

Since 1980, atmospheric pollutants in South Asia and India have dramatically increased in response to industrialization and agricultural development, enhancing the atmospheric deposition of anthropogenic nitrogen in the northern Indian Ocean and potentially promoting primary productivity. Concurrently, ocean warming has increased stratification and limited the supply of nutrients supporting primary productivity. Here, we examine the biogeochemical consequences of increasing anthropogenic atmospheric nitrogen deposition and contrast them with the counteracting effect of warming, using a regional ocean biogeochemical model of the northern Indian Ocean forced with atmospheric nitrogen deposition derived from an Earth System Model. Our results suggest that the 60% recent increase in anthropogenic nitrogen deposition over the northern Indian Ocean provided external reactive nitrogen that only weakly enhanced primary production (+10 mg C.m^–2.d^–1.yr^–1in regions of intense deposition) and secondary production (+4 mg C.m^–2.d^–1.yr^–1). However, we find that locally this enhancement can significantly offset the declining trend in primary production over the last four decades in the central Arabian Sea and western Bay of Bengal, whose magnitude are up to -20 and -10 mg C.m^–2.d^–1.yr^–1respectively. 

Abstract. Zooplankton diel vertical migration (DVM) is critical to ocean ecosystem dynamics and biogeochemical cycles, by supplying food and injecting carbon to the mesopelagic ocean (200–800 m). The deeper the zooplankton migrate, the longer the carbon is sequestered away from the atmosphere and the deeper the ecosystems they feed. Sparse observations show variations in migration depths over a wide range of temporal and spatial scales. A major challenge, however, is to understand the biological and physical mechanisms controlling this variability, which is critical to assess impacts on ecosystem and carbon dynamics. Here, we introduce a migrating zooplankton model for medium and large zooplankton that explicitly resolves diel migration trajectories and biogeochemical fluxes. This model is integrated into the MOM6-COBALTv2 ocean physical-biogeochemical model, and applied in an idealized high-resolution (9.4 km) configuration of the North Atlantic. The model skillfully reproduces observed North Atlantic migrating zooplankton biomass and DVM patterns. Evaluation of the mechanisms controlling zooplankton migration depth reveals that chlorophyll shading reduces by 60 meters zooplankton migration depth in the subpolar gyre compared with the subtropical gyre, with pronounced seasonal variations linked to the spring bloom. Fine-scale spatial effects (<100 km) linked to eddy and frontal dynamics can either offset or reinforce the large-scale effect by up to 100 meters. This could imply that for phytoplankton-rich regions and filaments, which represent a major source of exportable carbon for migrating zooplankton, their high-chlorophyll content contributes to reducing zooplankton migration depth and carbon sequestration time. 

Abstract. We introduce and evaluate the regional ocean model MOM6-COBALT-IND12 version 1 coupling the MOM6 ocean dynamics model to the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALT) biogeochemical model at a horizontal resolution of 1/12°. The model covers the northern Indian Ocean (from 8.6° S to the northern continental boundaries), central to the livelihoods and economies of countries that comprise about one-third of the world’s population. We demonstrate that the model effectively captures the key physical and biogeochemical basin-scale features related to seasonal monsoon reversal, interannual Indian Ocean Dipole and multi-decadal variability, as well as intraseasonal and fine-scale variability (e.g., eddies and planetary waves), which are all essential for accurately simulating patterns of coastal upwelling, primary productivity, temperature, salinity, and oxygen levels. Well represented features include the timing and amplitude of the monsoonal blooms triggered by summer coastal upwelling and winter mixing, the strong contrast between the high evaporation/high salinity Arabian Sea and high precipitation/high runoff/low salinity Bay of Bengal, the seasonality of the Great Whirl gyre and coastal Kelvin upwelling/downwelling waves, as well as the physical and biogeochemical patterns associated with intraseasonal and interannual variability. Quantitatively, the model exhibits relatively small biases, as reflected by root mean square error (RMSE) values in key variables: sea surface temperature (0.25–0.3 °C), mixed layer depth (7–8.09 m), sea level anomaly (0.02 m), sea surface salinity (0.53–0.71 psu), vertical chlorophyll (0.03–0.3 mg m−3), subsurface temperature (0.33 °C), and subsurface salinity (0.07 psu). A major model bias (16 µmol kg−1 of oxygen) is the larger oxygen minimum zone simulated in the Bay of Bengal, a common challenge of ocean and Earth system models in this region. This bias was partly mitigated by improving the representation of the export and burial of organic detritus to the deep ocean (e.g., sinking speed, riverine lithogenic material inputs that protect organic material and burial fraction), and water-column denitrification (e.g., nitrate-based respiration at higher oxygen levels) using observational constraints. These results indicate that the regional MOM6-COBALT-IND12 v1.0 model is well suited for physical and biogeochemical studies on timescales ranging from weeks to decades, in addition to supporting marine resource applications and management in the northern Indian Ocean.