Understanding and predicting the ocean environment and marine ecosystem status depends on accurate representations of regional ocean dynamics. Recently, the Modular Ocean Model version 6 (MOM6) has been configured to span the Northeast Pacific Ocean from Baja California to the Chukchi Sea (MOM6-NEP). In this study we present a physical hindcast (1993-2018) simulation of MOM6-NEP where it is coupled to a thermodynamic-dynamic sea-ice module and includes tides. We evaluate the performance of this model in the Bering Sea. Various model metrics are benchmarked against in-situ mooring data and satellite observations. The simulation captures the general characteristics of Bering Sea dynamics, particularly with respect to seasonal and interannual variability of the middle shelf water mass properties. Modeling of shear induced mixing was found to be critical to the model's ability to reproduce the observed sharp summer thermocline and its depth. The hindcast simulation reproduces the long-term mean timing of sea-ice arrival and retreat in both the northern and southern Bering Sea, with the remaining mild biases primarily occurring in May over the northern shelf - the model captures the mean timing of sea-ice retreat, though it tends to retreat earlier in colder years and later in warmer years compared to observations. This pattern in biases suggests that the melting rate in the model likely underestimates the well-known melt-rate dependency on ice property whereby thicker (thinner) ice melts more slowly (quickly). As a result of high skills in reproducing sea-ice areal coverage, the interannual variability of the cold pool (the cold-water mass present on the bottom of the Bering Sea shelf in summer) extent is accurately reproduced by the model. Skillful representation of sea ice and the cold pool is essential for understanding ecosystem dynamics and successful fisheries management in the Bering Sea. The findings of this study contribute to the development of reliable oceanographic modeling and forecasting of marine ecosystem conditions to support fisheries management decision making.

Regional ocean models enable the generation of computationally affordable and regionally tailored ensembles of near-term forecasts and long-term projections of sufficient resolution to serve marine resource management. Climate change, however, has created marine resource challenges, such as shifting stock distributions, that cut across domestic and international management boundaries and have pushed regional modeling efforts toward "coastwide" approaches. Here, we present and evaluate a multidecadal hindcast with a Northeast Pacific regional implementation of the Modular Ocean Model, version 6, with sea ice and biogeochemistry that extends from the Chukchi Sea to the Baja California Peninsula at 10 km horizontal resolution (MOM6-COBALT-NEP10k, or NEP10k). This domain includes an Arctic-adjacent system with a broad, shallow shelf seasonally covered by sea ice (the eastern Bering Sea), a sub-Arctic system with upwelling in the Alaska Gyre and predominant downwelling winds and large freshwater forcing along the coast (the Gulf of Alaska), and a temperate, eastern boundary upwelling ecosystem (the California Current Ecosystem). The coastwide model was able to recreate seasonal and cross-ecosystem contrasts in numerous ecosystem-critical properties including temperature, salinity, inorganic nutrients, oxygen, carbonate saturation states, and chlorophyll. Spatial consistency between modeled quantities and observations generally extended to plankton ecosystems, though small to moderate biases were also apparent. Fidelity with observed zooplankton biomass, for example, was limited to first-order seasonal and cross-system contrasts. Temporally, simulated monthly surface and bottom temperature anomalies in coastal regions (<500 m deep) closely matched estimates from data-assimilative ocean reanalyses. Performance, however, was reduced in some nearshore regions coarsely resolved by the model's 10 km resolution grid and for point measurements. The time series of satellite-based chlorophyll anomaly estimates proved more difficult to match than temperature. System-specific ecosystem indicators were also assessed. In the eastern Bering Sea, NEP10k robustly matched observed variations, including recent large declines, in the area of the summer bottom water "cold pool" (<2 degrees C), which exerts a profound influence on eastern Bering Sea fisheries. In the Gulf of Alaska, the simulation captured patterns of sea surface height variability and variations in thermal, oxygen, and acidification risk associated with local modes of interannual to decadal climate variability. In the California Current Ecosystem, the simulation robustly captured variations in upwelling indices and coastal water masses, though discrepancies in the latter were evident in the Southern California Bight. Enhanced model resolution may reduce such discrepancies, but any benefits must be carefully weighed against computational costs given the intended use of this system for ensemble predictions and projections. Meanwhile, the demonstrated NEP10k skill level herein, particularly in recreating cross-ecosystem contrasts and the time variation of ecosystem indicators over multiple decades, suggests considerable immediate utility for coastwide retrospective and predictive applications.

We analyze the frequency and amplitude of projected warming and ocean acidification extremes under high CO2 and strongly mitigating scenarios. We find interpretational differences in projections arising from methodological choices associated with specification of stressor thresholds. Use of absolute versus distribution-based thresholds, and, in the distribution-based case, the inclusion or exclusion of seasonal variability, can lead to very different regional patterns in projected stress. The choice of fixed versus adaptive baseline, for example, determines whether future stress frequency in the low-CO2 scenario most closely resembles that in the high-emissions scenario or historical period. We find that mitigation through emissions reductions, in combination with representation of rates of adaptation that are realistic for some marine organisms, has the potential to dampen end of century threshold exceedance to frequencies of occurrence closer to the recent historical period than to the high-emissions scenario.

Trajectories of >1,600 virtual Argo profiling floats and their sampled variability in key ocean physical and biogeochemical variables are simulated using a 0.125° global ocean physical-biogeochemical model (NOAA GFDL’s MOM6-SIS2-COBALTv2) and an offline Lagrangian particle tracking algorithm. Virtual floats are deployed at 92 locations within 26-50°N, 114-132°W in the California Current System (CCS) during the summers and winters of 2008-2012 with varying sampling strategies adopted (e.g., floats are set to park and drift at different depths, and to profile at different intervals). The overall direction and spatial spreads of simulated float trajectories depend on the latitudes of deployment locations with the largest area and variability sampled by floats deployed in the central CCS. Floats drifting at shallower depths (200 m and 500 m) tend to sample larger variability associated with larger sampled area, while those drifting at 1000 m show the strongest association with eddy-like ocean features. Sensitivity experiments with varying sampling intervals suggest that spatiotemporal variability in float observables are adequately sampled with a typical 5-day or 10-day interval. Furthermore, simulated float trajectories and sampled variability are compared against 3 real float trajectories and along-track observations. Results suggest that the fidelity of both our model simulations and the prevalent Argo float sampling design are generally satisfactory in characterizing interior ocean biogeochemical variability. This study provides new insights to inform optimal float deployment planning, sampling strategies, and data interpretation.

Patterns of population connectivity shape ecological and evolutionary phenomena from population persistence to local adaptation and can inform conservation strategy. Connectivity patterns emerge from the interaction of individual behavior with a complex and heterogeneous environment. Despite ample observation that dispersal patterns vary through time, the extent to which variation in the physical environment can explain emergent connectivity variation is not clear. Empirical studies of its contribution promise to illuminate a potential source of variability that shapes the dynamics of natural populations. We leveraged simultaneous direct dispersal observations and oceanographic transport simulations of the clownfish Amphiprion clarkii in the Camotes Sea, Philippines, to assess the contribution of oceanographic variability to emergent variation in connectivity. We found that time-varying oceanographic simulations on both annual and monsoonal timescales partly explained the observed dispersal patterns, suggesting that temporal variation in oceanographic transport shapes connectivity variation on these timescales. However, interannual variation in observed mean dispersal distance was nearly 10 times the expected variation from biophysical simulations, revealing that additional biotic and abiotic factors contribute to interannual connectivity variation. Simulated dispersal kernels also predicted a smaller scale of dispersal than the observations, supporting the hypothesis that undocumented abiotic factors and behaviors such as swimming and navigation enhance the probability of successful dispersal away from, as opposed to retention near, natal sites. Our findings highlight the potential for coincident observations and biophysical simulations to test dispersal hypotheses and the influence of temporal variability on metapopulation persistence, local adaptation, and other population processes.

The california current system (CCS) supports a wide array of ecosystem services with hypoxia historically occurring in near-bottom waters. Limited open ocean data coverage hinders the mechanistic understanding of CCS oxygen variability. By comparing three different models with varying horizontal resolutions, we found that dissolved oxygen (DO) anomalies in the CCS are propagated from shallower coastal areas to the deeper open ocean, where they are advected at a density and velocity consistent with basin-scale circulation. Since DO decreases have been linked to water mass redistribution in the CCS, we conduct a water mass analysis on two of the models and on biogeochemical Argo floats that sampled multiple seasonal cycles. We found that high variability in biogeochemical variables (DO and nutrients) seen in regions of low variability of temperature and salinity could be linked to water mass mixing, as some of the water masses considered had higher gradients in biogeochemical variables compared to physical variables. Additional DO observations are needed, therefore, to further understand circulation changes in the CCS. We suggest that increased DO sampling north of 35N and near the shelf break would benefit model initialization and skill assessment, as well as allow for better assessment of the role of equatorial waters in driving DO in the northern CCS.

Climate change is an environmental emergency threatening species and ecosystems globally. Oceans have absorbed about 90% of anthropogenic heat and 20%–30% of the carbon emissions, resulting in ocean warming, acidification, deoxygenation, changes in ocean stratification and nutrient availability, and more severe extreme events. Given predictions of further changes, there is a critical need to understand how marine species will be affected. Here, we used an integrated risk assessment framework to evaluate the vulnerability of 132 chondrichthyans in the Eastern Tropical Pacific (ETP) to the impacts of climate change. Taking a precautionary view, we found that almost a quarter (23%) of the ETP chondrichthyan species evaluated were highly vulnerable to climate change, and much of the rest (76%) were moderately vulnerable. Most of the highly vulnerable species are batoids (77%), and a large proportion (90%) are coastal or pelagic species that use coastal habitats as nurseries. Six species of batoids were highly vulnerable in all three components of the assessment (exposure, sensitivity and adaptive capacity). This assessment indicates that coastal species, particularly those relying on inshore nursery areas are the most vulnerable to climate change. Ocean warming, in combination with acidification and potential deoxygenation, will likely have widespread effects on ETP chondrichthyan species, but coastal species may also contend with changes in freshwater inputs, salinity, and sea level rise. This climate‐related vulnerability is compounded by other anthropogenic factors, such as overfishing and habitat degradation already occurring in the region. Mitigating the impacts of climate change on ETP chondrichthyans involves a range of approaches that include addressing habitat degradation, sustainability of exploitation, and species‐specific actions may be required for species at higher risk. The assessment also highlighted the need to further understand climate change's impacts on key ETP habitats and processes and identified knowledge gaps on ETP chondrichthyan species.

AbstractGlobal Earth system models are often enlisted to assess the impacts of climate variability and change on marine ecosystems. In this study, we compare high frequency (daily) outputs of potential ecosystem stressors, such as sea surface temperature and surface pH, and associated variables from an Earth system model (GFDL ESM4.1) with high frequency time series from a global network of moorings to directly assess the capacity of the model to resolve local biogeochemical variability on time scales from daily to interannual. Our analysis indicates variability in surface temperature is most consistent between ESM4.1 and observations, with a Pearson correlation coefficient of 0.93 and bias of 0.40°C, followed by variability in surface salinity. Physical variability is reproduced with greater accuracy than biogeochemical variability, and variability on seasonal and longer time scales is more consistent between the model and observations than higher frequency variability. At the same time, the well‐resolved seasonal and longer timescale variability is a reasonably good predictor, in many cases, of the likelihood of extreme events. Despite limited model representation of high frequency variability, model and observation‐based assessments of the fraction of days experiencing surface T‐pH and T‐Ωarag multistressor conditions show reasonable agreement, depending on the stressor combination and threshold definition. We also identify circumstances in which some errors could be reduced by accounting for model biases.

Across the United States, there is increasing concern about the poor performance of American students in science and our country’s position as a world leader in innovation (National Science Board, 2022). Furthermore, young people are inequitably prepared to fulfill our nation's workforce needs as educational resources and achievement disparities are magnified in youth from diverse racial and ethnic backgrounds who live in poverty (National Science Board, 2022). Science test scores for students of color who reside in low socioeconomic status communities lag far behind those of Caucasian students and students from more affluent areas (Irwin et al., 2022). These students are also less likely to pursue the higher education necessary for science- and technology-based careers (Fry et al., 2021). As a result, the United States’ scientific workforce does not reflect the population of the nation as a whole; for example, Hispanic individuals represent 18.9% of the US population, but only 8% of jobs in science, technology, engineering, and math (STEM) fields (Fry et al., 2021). The Ocean Discovery Institute, a 501(c)(3) organization, was founded in 1999 to address this problem. Here, we describe Ocean Discovery’s unique model for empowering underrepresented students. It includes (1) embedding students within the community served, (2) reaching all students in a single cluster of schools (a “school-shed”), and (3) a program structure that emphasizes science identity (“belief”) and reinforces it through intentional mentorship.

We present the development and evaluation of MOM6-COBALT-NWA12 version 1.0, a 1/12∘ model of ocean dynamics and biogeochemistry in the northwest Atlantic Ocean. This model is built using the new regional capabilities in the MOM6 ocean model and is coupled with the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALT) biogeochemical model and Sea Ice Simulator version-2 (SIS2) sea ice model. Our goal was to develop a model to provide information to support living-marine-resource applications across management time horizons from seasons to decades. To do this, we struck a balance between a broad, coastwide domain to simulate basin-scale variability and capture cross-boundary issues expected under climate change; a high enough spatial resolution to accurately simulate features like the Gulf Stream separation and advection of water masses through finer-scale coastal features; and the computational economy required to run the long simulations of multiple ensemble members that are needed to quantify prediction uncertainties and produce actionable information. We assess whether MOM6-COBALT-NWA12 is capable of supporting the intended applications by evaluating the model with three categories of metrics: basin-wide indicators of the model's performance, indicators of coastal ecosystem variability and the regional ocean features that drive it, and model run times and computational efficiency. Overall, both the basin-wide and the regional ecosystem-relevant indicators are simulated well by the model. Where notable model biases and errors are present in both types of indicator, they are mainly consistent with the challenges of accurately simulating the Gulf Stream separation, path, and variability: for example, the coastal ocean and shelf north of Cape Hatteras are too warm and salty and have minor biogeochemical biases. During model development, we identified a few model parameters that exerted a notable influence on the model solution, including the horizontal viscosity, mixed-layer restratification, and tidal self-attraction and loading, which we discuss briefly. The computational performance of the model is adequate to support running numerous long simulations, even with the inclusion of coupled biogeochemistry with 40 additional tracers. Overall, these results show that this first version of a regional MOM6 model for the northwest Atlantic Ocean is capable of efficiently and accurately simulating historical basin-wide and regional mean conditions and variability, laying the groundwork for future studies to analyze this variability in detail, develop and improve parameterizations and model components to better capture local ocean features, and develop predictions and projections of future conditions to support living-marine-resource applications across timescales.

Abstract Deposition of mineral dust plays an important role in upper‐ocean biogeochemical processes, particularly by delivering iron to iron‐limited regions. Here we examine the impact of dynamically changing iron deposition on tropical Pacific Ocean biogeochemistry in fully coupled earth system model projections under several emissions scenarios. Projected end‐of‐21st‐century increases in central tropical Pacific dust and iron deposition strengthen with increasing emissions/radiative forcing, and are aligned with projected soil moisture decreases in adjacent land areas and precipitation increases over the equatorial Pacific. Increased delivery of soluble iron results in a reduction in, and eastward contraction of, equatorial Pacific phytoplankton iron limitation and shifts primary production and particulate organic carbon flux projections relative to a high emissions projection (SSP5‐8.5) wherein soluble iron deposition is prescribed as a static climatology. These results highlight modeling advances in representing coupled land‐air‐sea interactions to project basin‐scale patterns of ocean biogeochemical change.

Climate change may impact ocean ecosystems through a number of mechanisms, including shifts in primary productivity or plankton community structure, ocean acidification, and deoxygenation. These processes can be simulated with global Earth system models (ESMs), which are increasingly being used in the context of fisheries management and other living marine resource (LMR) applications. However, projections of LMR-relevant metrics such as net primary production can vary widely between ESMs, even under identical climate scenarios. Therefore, the use of ESM should be accompanied by an understanding of the structural differences in the biogeochemical sub-models within ESMs that may give rise to these differences. This review article provides a brief overview of some of the most prominent differences among the most recent generation of ESM and how they are relevant to LMR application.

Efforts to manage living marine resources (LMRs) under climate change need projections of future ocean conditions, yet most global climate models (GCMs) poorly represent critical coastal habitats. GCM utility for LMR applications will increase with higher spatial resolution but obstacles including computational and data storage costs, obstinate regional biases, and formulations prioritizing global robustness over regional skill will persist. Downscaling can help address GCM limitations, but significant improvements are needed to robustly support LMR science and management. We synthesize past ocean downscaling efforts to suggest a protocol to achieve this goal. The protocol emphasizes LMR-driven design to ensure delivery of decision- relevant information. It prioritizes ensembles of downscaled projections spanning the range of ocean futures with durations long enough to capture climate change signals. This demands judicious resolution refinement, with pragmatic consideration for LMR-essential ocean features superseding theoretical investigation. Statistical downscaling can complement dynamical approaches in building these ensembles. Inconsistent use of bias correction indicates a need for objective best practices. Application of the suggested protocol should yield regional ocean projections that, with effective dissemination and translation to decision-relevant analytics, can robustly support LMR science and management under climate change.

Figure 2 in the original article has been updated with this figure 2 due to discrepancies related to incorrect mapping with one of the islands.

Multidisciplinary, integrated ocean observing programs provide critical data for monitoring the effects of climate change on marine ecosystems. California Cooperative Oceanic Fisheries Investigations (CalCOFI) samples along the US West Coast and is one of the world’s longest-running and most comprehensive time series, with hydrographic and biological data collected since 1949. The pairing of ecological and physical measurements across this long time series informs our understanding of how the California Current marine ecosystem responds to climate variability. By providing a baseline to monitor change, the CalCOFI time series serves as a Keeling Curve for the California Current. However, challenges remain in connecting the data collected from long-term monitoring programs with the needs of stakeholders concerned with climate change adaptation (i.e., resource managers, policy makers, and the public), including for the fisheries and aquaculture sectors. We use the CalCOFI program as a case study to ask: how can long-term ocean observing programs inform ecosystem based management efforts and create data flows that meet the needs of stakeholders working on climate change adaptation? Addressing this question and identifying solutions requires working across sectors and recognizing stakeholder needs. Lessons learned from CalCOFI can inform other regional monitoring programs around the world, including those done at a smaller scale in developing countries.

We used univariate and multivariate spatiotemporal delta models to quantify changes in the distribution of ichthyoplankton in the southern California Current System from 1951 to 2016. We focus on mesopelagic species, because they are most abundant, and on northern anchovy (Engraulis mordax), Pacific sardine (Sardinops sagax), and Pacific hake (Merluccius productus), because they are important commercial and forage fish species. Univariate models indicated that changes in the relative abundance, area occupied, center of gravity, and spatiotemporal variability of numerically dominant warm-water and cool-water-associated mesopelagic ichthyoplankton show strong species-specific differences. Multivariate models revealed that the warm-water-associated mesopelagic assemblage exhibits an increasing, nonmonotonic, secular trend of increasing relative abundance underlying interannual variability, suggesting a tropicalization of the southern California Current System. In contrast, the cool-water-associated mesopelagic assemblage shows mainly interannual variability, with little secular trend over the 65-year period. Correlation matrices of the modeled ichthyoplankton densities showed that the spatial distributions of northern anchovy and Pacific hake are highly correlated with cool-water mesopelagic ichthyoplankton, but Pacific sardine is spatially correlated with both warm- and cool-water-associated mesopelagic species. Declines of adult sardine, anchovy, and hake are occurring concurrently with tropicalization of the southern California Current System. The most parsimonious explanation for tropicalization of the ichthyoplankton is increased presence of Pacific Equatorial-influenced Water in the inshore southern California region. We modeled the distribution of ichthyoplankton in the southern California Current System from 1951 to 2016. We focus on abundant mesopelagic species and on northern anchovy (Engraulis mordax), Pacific sardine (Sardinops sagax), and Pacific hake (Merluccius productus), because they are important commercial and forage fish species. Single species models indicated that changes in abundance, area, distribution center, and variability of the most abundant mesopelagic ichthyoplankton associated with warm and cool water show strong differences between the species. Models of species groups revealed that the warm-water mesopelagic larval fishes exhibit a long-term trend of increasing relative abundance underlying year-to-year variability, suggesting tropicalization of the southern California Current System. In contrast, the cool-water mesopelagic larvae show mainly year-to-year variability, with little long-term trend. Correlations between the modeled species showed that the spatial distributions of northern anchovy and Pacific hake are highly correlated with cool-water mesopelagic larvae, but Pacific sardine is correlated with both warm- and cool-water-associated mesopelagic species. The spatial variability of hake over time is highly positively correlated with cool-water mesopelagics and with northern anchovy, but sardine fluctuate independently of the mesopelagics and both anchovy and hake. Declines of adult sardine, anchovy, and hake are occurring concurrently with tropicalization of the southern California Current System. The simplest explanation for more tropical ichthyoplankton is increased presence of Pacific Equatorial-influenced Water in the inshore southern California region.

Ocean acidification (OA) threatens coral reef ecosystems by slowing calcification and enhancing dissolution of calcifying organisms and sediments. Nevertheless, multiple factors have been shown to modulate OA's impact on calcification, including the nutritional status of the coral host. In three separate experiments, we exposed juveniles of the Atlantic golf ball coral, Favia fragum, to elevated CO2 and varied nutritional (light or feeding) conditions. Juveniles reared from planulae larvae were significantly larger and produced more CaCO3 when fed, regardless of CO2 level. However, corals subjected to elevated CO2 produced less CaCO3 per mm(2) regardless of feeding condition. Additionally, unfed corals reared under elevated light levels exhibited lower chlorophyll a and higher total lipid content, but light had no significant effect on coral calcification. Conversely, elevated CO2 had a significant, negative affect on calcification, regardless of light condition but no detectable effect on physiological tissue parameters. Our results indicate that the sensitivity of juvenile F. fragum calcification to OA was neither modulated by light nor by feeding, despite physiological indications of enhanced nutritional status. This suggests that corals do not necessarily divert energy to maintain calcification under high CO2, even when they have the energetic resources to do so.

The oceans are warming and coral reefs are bleaching with increased frequency and severity, fueling concerns for their survival through this century. Yet in the central equatorial Pacific, some of the world’s most productive reefs regularly experience extreme heat associated with El Niño. Here we use skeletal signatures preserved in long-lived corals on Jarvis Island to evaluate the coral community response to multiple successive heatwaves since 1960. By tracking skeletal stress band formation through the 2015-16 El Nino, which killed 95% of Jarvis corals, we validate their utility as proxies of bleaching severity and show that 2015-16 was not the first catastrophic bleaching event on Jarvis. Since 1960, eight severe (>30% bleaching) and two moderate (<30% bleaching) events occurred, each coinciding with El Niño. While the frequency and severity of bleaching on Jarvis did not increase over this time period, 2015–16 was unprecedented in magnitude. The trajectory of recovery of this historically resilient ecosystem will provide critical insights into the potential for coral reef resilience in a warming world.