The Bering Sea shelf supports a highly productive marine ecosystem that is vulnerable to ocean acidification (OA) due to the cold, carbon-rich waters. Previous observational evidence suggests that bottom waters on the shelf are already seasonally undersaturated with respect to aragonite (i.e. Omega(arag )<1) and that OA will continue to increase the spatial extent, duration, and intensity of these conditions. Here, we use a regional ocean biogeochemical model to simulate changes in ocean carbon chemistry for the Bering Sea shelf from 1970-2022. Over this timeframe, model results suggest that surface Omega(arag) decreases by -0.043 per decade and surface pH by -0.014 per decade, comparable to observed global rates of OA. However, bottom water pH decreases at twice the rate of surface pH, while bottom [H+] decreases at nearly 3 times the rate of surface [H+]. This amplified bottom water acidification has emerged over the past 25 years and is likely driven by a combination of anthropogenic carbon accumulation and increasing primary productivity and subsurface respiration and remineralization. Due to this enhanced bottom water acidification, the spatial extent of bottom waters with Omega(arag )<1 has greatly expanded over the past 2 decades, along with pH conditions harmful to red king crab. Interannual variability in surface and bottom Omega arag, pH, and [H+] has also increased over the past 2 decades, resulting in part from the increased physical climate variability. We also find that the Bering Sea shelf is a net annual carbon sink of 1.1-7.9 Tg C yr(-1), with the range resulting from the difference in the two different atmospheric forcing reanalysis products used. Seasonally, the shelf is a significant carbon sink from April-October but a somewhat weaker carbon source from November-March.

Uncertainty related to biogeochemical model structure-the equations, parameters, and variables used to simulate lower trophic level dynamics-can contribute significantly to overall uncertainty of regional model predictions of living marine resources metrics such as primary production. This may be particularly true in shallow coastal regions, where there is growing interest in using these types of regional models to inform ecosystem management. Here, we use a biogeochemical model intercomparison to analyze the divergence of ecosystem metrics across models for the eastern Bering Sea shelf region, and identify the biogeochemical processes that may lead to this spread. We run three biogeochemical models with varying complexity coupled to the same regional ocean model and run 30-year hindcast simulations spanning 1990-2020. We find that the models differ widely in their spatial and temporal patterns of simulated primary production, and that these differences propagate to most of the higher trophic level metrics examined. We highlight structural elements that lead to these differences, including (a) representation of benthic processes and their role in retaining nitrogen on the shelf, (b) the role of grazing control on spring bloom timing, and (c) the role of zooplankton groups in supporting regenerated production through the summer months. Overall, we conclude that the potential uncertainty associated with even well-established biogeochemical models may be high, particularly when these models are pushed beyond the original contexts under which they were developed. End users should strive to acknowledge and communicate this, particularly when using biogeochemical model output in management contexts.

Understanding the abiotic and biotic drivers of species distribution is critical for climate-informed ecosystem management. We aimed to understand habitat selection of northern fur seals in the eastern Bering Sea, a declining population that is also a key predator of walleye pollock, the target species for the largest U.S. commercial fishery. We developed species distribution models using random forest models by combining satellite telemetry data from lactating female fur seals tagged at different rookery complexes on the Pribilof Islands in the eastern Bering Sea with regional ocean model simulations. We explored how data aggregation at two spatial scales (Pribilof-wide and complex-specific) impacted model performance and predicted distributions. Spatial predictions under hindcasted (1992–2018) and projected (2050–2059) physical and biological conditions were used to identify areas of core habitat, overlap with commercial fishery catches, and potential changes in future habitat suitability. The most important environmental predictor variables across all models were bathymetry, bottom temperature, and surface temperature. The Pribilof-wide model both under- and overrepresented the importance of specific areas, while complex-specific models exhibited considerable variability in transferability performance. The majority of core habitat occurred on the continental shelf in areas that overlapped with commercial catches of walleye pollock during the “B” season (June – October), with an average of 76

To better understand ecosystem dynamics in the Gulf of Alaska, Bering Sea, and Chukchi Sea, researchers at the U.S. National Oceanic and Atmospheric Administration’s (NOAA’s) Pacific Marine Environmental Laboratory and Alaska Fisheries Science Center have been conducting hydrographic and biological surveys in Alaska waters for decades. This article describes a new data compendium (“ACOD”) that assembles data sets from select NOAA programs into a single-point-of-access quality-controlled product. Included are 29717 vertical profiles of temperature and salinity (1974–2021), and 7016 profiles of dissolved inorganic macronutrients (nitrate, nitrite, ammonium, orthosilicic acid, and phosphate) at discrete depths (2001–2021). This value-added product includes systematic quality control of metadata, salinity, and nutrient data – in addition to creating a single point of access for data from 495 cruises across a nearly 50-year time period. ACOD files are archived at the Dryad Research Data Repository and will include annual or biennial updates. File types include netCDF (profiles and nutrients) and csv (nutrients), and a table with metadata from each cruise.

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.

Ecosystem-based fisheries management strives to account for species interactions and ecosystem processes in natural resource management and conservation. In this context, ecosystem-wide caps on total fishery catches have been proposed as one tool to manage multispecies fisheries with an ecosystem approach. However, determining effective ecosystem caps is complicated because fish stock production is influenced by environmental conditions, species interactions, and fishing. Consequently, the implementation of ecosystem caps in fisheries management frameworks remains uncommon. We investigated whether ecosystem caps should account for climate variability and for predator-prey dynamics to achieve management objectives in complex marine ecosystems. We considered the example of the Gulf of Alaska (United States), a North Pacific large marine ecosystem where annual groundfish catches are managed using an "optimum yield" ecosystem cap of 800,000 t. We simulated multispecies yield of the 12 most abundant and commercially valuable groundfish stocks under selected climate and fishing scenarios using an end-to-end marine ecosystem model (Atlantis), which accounts for predator-prey and ecosystem dynamics. We found that total groundfish yield was never projected to exceed the 800,000 mt optimum yield cap across scenarios and fishing mortalities. Projected climate change led to decreased groundfish yield, and predation from the underexploited groundfish predator arrowtooth flounder (Atheresthes stomias) led to foregone catches. Groundfish removals had negative indirect effects on groundfish predators, despite total yield never exceeding the optimum yield cap, highlighting that an ineffective cap may not protect non-target species. These results suggest that the optimum yield cap currently used in the Gulf of Alaska may be too high to constrain groundfish catches under future climate change and low exploitation rates of predators. We propose that ecosystem caps should be reviewed when environmental conditions, stock productivity, or species interactions change.

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.

The Bering10K Regional Ocean Modeling System (ROMS) model is a high-resolution (10-km) regional ocean model that has been used over the past decade to investigate relationships between the physical environment and the eastern Bering Sea shelf ecosystem in both research and management contexts. Extensive validation for this model has been conducted previously, particularly focused on bottom temperature, a key physical driver shaping ecosystem dynamics in this region. However, previous observations of bottom temperature were primarily limited to the summer months. Recent deployments of pop-up floats capable of overwinter measurements now allow us to extend the previous validation to other seasons. Here, we characterize bottom temperature on the southeastern Bering Sea shelf across time scales by combining data from our new pop-up floats with several existing temperature datasets. We then use this combination of data to systematically assess the skill of the Bering10K ROMS model in capturing these features, focusing on spatial variability in skill metrics and the potential processes leading to these patterns. We confirm that the model captures shelf-wide patterns in bottom temperature well, including mean patterns as well as both seasonal and interannual variability. However, a few areas of potential improvement were also identified: underestimated surface mixing in the model leads to delayed destratification across the middle and outer shelves, the position of the inner front may be offset slightly in the model, and bathymetric smoothing leads to poor representation near the shelf break and potentially underestimated flow onto the shelf through shelf break canyons. Overall, this paper presents the most detailed spatiotemporal analysis of this model’s skill in simulating bottom temperature across the eastern Bering Sea shelf to date and supplies a benchmark analysis framework that can be used for planned regional model transitions and improvements over the coming years.

Modelling has predicted that reductions in ocean pH and increases in temperature will reduce vital rates (survival and growth) of North Pacific crab stocks and hence the target levels of fishing mortality consistent with sustainable harvesting. However, these predictions have been based on the best estimates of the effects of changes in ocean pH and temperature on vital rates from laboratory experiments. We quantified the effects of several climate and market sources of variability in Alaskan red king and southern Tanner crab fisheries on predicted optimal fishing mortality rates, including changes in ocean chemistry and temperature on vital rates, non-linear relationships between prices, costs and catch, and the uncertainty in population dynamics models. The declines in survival consistently lead to predictions of a reduction in productivity and hence the optimal level of fishing intensity over time, but the extent of change is uncertain. Uncertainty related to the effects of ocean pH and temperature on vital rates and variability among Earth System Models and future emission scenarios are the dominant sources of uncertainty, although potential fluctuations in prices and costs are also consequential. Further, simulations are used to explore the relationship between changes in ocean pH or temperature and vital rates (additional experimental replicates and a wider range of levels of ocean pH in experiments) and hence identify approaches to reduce the uncertainty in estimates of future projections of target fishing mortality rates. Importantly, we demonstrate that optimal approaches to reducing uncertainty depend on life stage (juvenile growth for red king crab and larval survival for southern Tanner crab), and the optimal experiment depends on species (increasing the range of pH levels for red king crab vs increasing sample sizes for southern Tanner crab). The results of this study can inform priorities for future ocean acidification-related laboratory experiments and provide a basis for evaluating "investment in research" more broadly.

In the California Current Ecosystem, the California Undercurrent (CU) is the predominate subsurface current that transports nutrient-rich water from southern California poleward. In this study, we used a large dataset of spatially explicit in situ observations of Pacific hake ( Merluccius productus) and the CU (36.5–48.3°N) to estimate relationships between northward undercurrent velocity and hake distribution and determine whether these relationships vary across space or life-history stage. We found that both hake occurrence and density had strong spatially complex relationships with the CU. In areas north of 44°N (central Oregon), the CU effect was spatially consistent and opposite for occurrence (negative) and density (positive), indicating that hake may aggregate in areas of high northward velocity in this region. In areas south of 44°N, the CU effect showed a cross-shelf gradient for both occurrence and density, indicating a more nearshore hake distribution when northward velocity is higher in this region. Together, our results suggest that future changes in the CU due to climate change are likely to impact hake differently in northern and southern areas.

As climate stressors are impacting marine ecosystems and fisheries across the world, ecosystem models that incorporate environmental variables are increasingly used to inform ecosystem-based fisheries management. The assumptions around the mechanistic links between climate stressors and the biological processes in these models are important, but the implications for model outcomes of which stressors are captured and how they affect modeled biological processes are seldom explored. Using a whole-ecosystem model (Atlantis) for the Gulf of Alaska, we explore the effects of capturing physical (increased temperature) and biogeochemical (decreased low trophic level productivity) climate stressors, and disentangle the effects of each stressor on the productivity of forage fish, groundfish, and fish-eating seabirds. We then test the effects of alternative model specifications of temperature-driven habitat determination and bioenergetics. Increased temperature resulted in increased weight-at-age and higher natural mortality, while decreased productivity resulted in decreased weight-at-age and higher natural mortality. Model specification of temperature dependence of movement and spawning influenced model outcomes, and decoupling these processes from temperature led to overly optimistic biomass predictions. As the use of ecosystem models to inform fisheries management becomes more operational, we illustrate that the assumptions around the links between climate stressors and ecological processes influence model outcomes.

In recognition of the impact of climate change on marine ecosystems worldwide, integrated research teams have coupled climate change projections with social-ecological models to inform management and evaluate adaptation strategies for the fishing industry and fishing communities. A key step in this process is the selection of scenarios that enable improved adaptation strategies and decision-making through engagements with constituents with diverse interests in the future use of marine resources. This paper presents an approach to selecting and refining climate-informed social-ecological scenarios for groundfish and crab fisheries in the eastern Bering Sea. The approach involved: (a) initial model development to provide worked examples; (b) engagement with stakeholders to seek input on climate-related concerns, priorities, and adaptation options; and (c) establishment of pathways for uptake of climate-informed decision support information into existing management systems. This approach narrowed the range of candidate scenarios, identified pressing climate concerns of constituents, and clarified timelines for scheduling modeling projects to address these concerns. Separating evaluation of management strategies (research modeling) from proposed changes to Fishery Management Plans preserved opportunities for public debate of proposed changes through a well-established regulatory review process. Collectively, these outcomes help to advance the development of a regionally relevant climate-ready harvest policy.

Decision makers are increasingly requesting that environmental and climate drivers be included in stock assessments and subsequent projections that provide managers with advice on the consequences of applying harvest control rules. Another key direction in stock assessment science is to capture the full range of uncertainty (model, process, and estimation). However, multiple sources of uncertainty are rarely accounted for when conducting projections based on environmental and climate drivers. We describe a framework for conducting projections that allows for structural model uncertainty (in the structure of the population dynamics model on which the assessment is based, and the Earth System Models and emission scenarios used to drive future recruitment and growth), for process error in future recruitment, and for uncertainty in the parameter estimates of the population dynamics model. We then apply the framework to data for Pacific cod, Gadus macrocephalus, in the eastern Bering Sea, with projections based on a harvest control rule that attempts to maximize the difference between revenue and variable costs based on the current growth and recruitment dynamics of the stock. Increases in temperature are found to increase weight-at-age but reduce recruitment. However, the negative effects on recruitment outweigh the positive effects on weight-at-age. In many cases, the harvest control rules considered in this paper, particularly those based on the assumption of no future environmental effects on population parameters, fail to conserve the stock if the inferred catch limits are taken, which suggests that declines in biomass and catch will take place if the current harvest control rules continue to be used. The strategies that lead to reductions in catch and biomass also lead to much lower profits for the fishery, particularly over the long-term. However, basing future catches on the environmental scenario that leads to the poorest outcomes (GFDL ssp585) generally keeps the stock above the threshold of 20 % of unfished spawning biomass under most climate scenarios and also achieves long-term profits at or greater than those expected in the next ten years.

The commercial Dungeness crab (Metacarcinus magister) fishery in Oregon and Washington (USA) is one of the most valuable fisheries in the region, but it experiences high interannual variability. These fluctuations have been attributed to environmental drivers on seasonal and annual timescales. In this study, researchers and state and tribal fisheries managers develop a statistical model for Dungeness crab catch per unit effort (CPUE) to help inform dynamic management decisions in Oregon and Washington. Fishing observations were matched to seasonally forecast and lagged ocean conditions from J-SCOPE, a regional forecast system (http://www.nanoos.org/products/j-scope/). Inclusion of dynamic and lagged ocean conditions improved model skill compared to simpler models, and the best model captured intraseasonal trends and interannual variability in catch rates, and spatial catch patterns. We also found that model skill relied on fishing behaviour, which varies interannually, highlighting the need for advanced fishing behaviour modelling to reduce uncertainty. The relationships between catch rates and ocean conditions may help elucidate environmental influences of catch variability. Forecast products were co-designed with managers to meet their needs for key decision points. Our results illustrate a seasonal forecasting approach for management of other highly productive, but also dynamic, invertebrates that increasingly contribute to global fisheries yield.

Warming temperatures elicit shifts in habitat use and geographic distributions of fishes, with uneven effects across life stages. Spawners and embryos often have narrower thermal tolerances than other life stages, and are thus particularly sensitive to warming. Here, we examine the spatiotemporal variability of thermal spawning habitat for Pacific cod in the eastern Bering Sea. Specifically, we use bottom temperatures from downscaled global climate models coupled with an experimentally-derived hatch success and temperature relationship to predict how the spatial extent, mean latitude, and consistency of thermal spawning habitat has varied over time. Predictions are validated with observations of spawning adults and early larvae. We find that habitat availability has not increased in the past but is predicted to increase and shift northward in the future, particularly if no climate change mitigation occurs. Habitat hotspots are consistent across shorter time periods but do shift across the shelf by the end of the century such that highly suitable areas in the past and present are not predicted to be suitable in the future. This work highlights the importance of coupling experimental data with climate models to identify the complex and mechanistic dynamics among temperature, life histories, and ecology, particularly under climate change.

Historical (hindcast) and September initialized forecast fields from the J-SCOPE system (more information here: https://www.nanoos.org/products/j-scope/). The historical fields are annual averages while the forecasts are averaged monthly. The fields here were used to generate the CPUE models described in Norton et al. (2023). Abstract from the paper: The commercial Dungeness crab (Metacarcinus magister) fishery in Oregon and Washington (USA) is one of the most valuable fisheries in the region, but it experiences high interannual variability. These fluctuations have been attributed to environmental drivers on seasonal and annual timescales. In this study, researchers and state and tribal fisheries managers develop a statistical model for Dungeness crab catch per unit effort (CPUE) to help inform dynamic management decisions in Oregon and Washington. Fishing observations were matched to seasonally forecast and lagged ocean conditions from J-SCOPE, a regional forecast system (http://www.nanoos.org/products/j-scope/). Inclusion of dynamic and lagged ocean conditions improved model skill compared to simpler models, and the best model captured intraseasonal trends and interannual variability in catch rates, and spatial catch patterns. We also found that model skill relied on fishing behaviour, which varies interannually, highlighting the need for advanced fishing behaviour modelling to reduce uncertainty. The relationships between catch rates and ocean conditions may help elucidate environmental influences of catch variability. Forecast products were co-designed with managers to meet their needs for key decision points. Our results illustrate a seasonal forecasting approach for management of other highly productive, but also dynamic, invertebrates that increasingly contribute to global fisheries yield.

The high-latitude Pacific is home to highly productive ecosystems, including vast populations of commercially and subsistence harvested fish. These regions can be challenging to sample directly. Over several decades at the NOAA Pacific Marine Environmental Laboratory, we have applied numerical models to infer past, present, and future states of these regional oceans and their biota. These estimates are provided to fisheries scientists to help identify the local biophysical dynamics that underlie marine resource fluctuations and to managers to help develop effective management strategies in the face of short- and long-term environmental changes.

The high-latitude Pacific is home to highly productive ecosystems, including vast populations of commercially and subsistence harvested fish. These regions can be challenging to sample directly. Over several decades at the NOAA Pacific Marine Environmental Laboratory, we have applied numerical models to infer past, present, and future states of these regional oceans and their biota. These estimates are provided to fisheries scientists to help identify the local biophysical dynamics that underlie marine resource fluctuations and to managers to help develop effective management strategies in the face of short- and long-term environmental changes.