Search

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 are particularly sensitive to environmental conditions, with direct impacts of temperature on spawning habitat, as well as indirect connections between their population dynamics and fisheries effort, productivity, and management. Here, we ask how changing environmental conditions and thermal sensitivities of developing embryos confer spatiotemporal variability of thermally-suitable spawning habitat for Pacific cod in the eastern Bering Sea. Specifically, we use bottom temperature values from regionally downscaled global climate models coupled with an experimentally-derived relationship between hatch success and temperature to predict how the extent, mean latitude, and consistency of suitable spawning habitat has changed in the past and may change into the future. We then validate our predictions of suitable spawning habitat with distributions of adults and larvae and examine whether thermal habitat availability relates to recruitment success into the adult cod into the population. We find that the extent and mean latitude of suitable spawning habitat increase over time, particularly if no climate change mitigation occurs in the future. Hotspots of suitable spawning habitat are consistent across shorter time periods but do shift across the Bering Sea shelf by the end of the century. Finally, we find no correlation between the availability of suitable spawning habitat and annual estimates of recruitment. Collectively, our results suggest that as temperatures warm, the availability of suitable spawning habitat will increase and expand spatially and, thus, is not likely to limit recruitment. 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, and offers a pathway for examining life stage-specific changes in habitat use and distribution with continued climate change.

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.

Spatial management has been adopted worldwide to mitigate habitat impacts while achieving fisheries management objectives. However, there is little theory or practice for predicting the impact of spatial regulations on future fishery production; this would provide scientific basis for greater flexibility in fisheries management when balancing fishery and conservation goals. We propose that predicting changes in fishery production resulting from human activities within specific habitats is a “Grand Challenge” for habitat science in the coming decade(s). We then outline three difficulties in resolving this Grand Habitat Challenge, including: (i) stage-structured responses to habitat impacts, (ii) nonlocal responses, and (iii) mechanistic associations among habitat variables. We next discuss analytical approaches to address each difficulty, respectively: (i) ongoing developments for spatial demographic models; (ii) individual movement models and rank-reduction approaches to identify regional variability; (iii) causal analysis involving structural equation models. We demonstrate nonlocal effects in detail using a diffusion-taxis movement model applied to sablefish (Anoplopoma fimbria) in the Gulf of Alaska and discuss all three approaches for deep-sea corals. Despite isolated progress to resolve individual difficulties, we argue that resolving this Grand Habitat Challenge will require a coordinated commitment from science agencies worldwide.

Climate-related distribution shifts for marine species are, in general, amplified in northern latitudes. The objective of this study was to predict future distributions of commercially important species in the eastern Bering Sea under six climate scenarios, by incorporating predictions of future oceanographic conditions. We used species distribution modelling to determine potential distribution changes in four time periods (2013–2017, 2030–2039, 2060–2069, and 2090-2099) relative to 1982–2012 for 16 marine fish and invertebrates. Most species were predicted to have significant shifts in the centre of gravity of the predicted abundance, the area occupied, and the proportion of the predicted abundance found in the standard bottom trawl survey area. On average the shifts were modest, averaging 35.2 km (ranging from 1 to 202 km). There were significant differences in the predicted trend for distribution metrics among climate scenarios, with the most extensive changes in distribution resulting from Representative Concentration Pathway 8.5 climate scenarios. The variability in distributional shifts among years and climate scenarios was high, although the magnitudes were low. This study provides a basis for understanding where fish populations might expand or contract in future years. This will provide managers’ information that can help guide appropriate actions under warming conditions.

The Bering Sea is a highly productive ecosystem, supporting a variety of fish, seabird, and marine mammal populations, as well as large commercial fisheries. Due to its unique shelf geometry and the presence of seasonal sea ice, the processes controlling productivity in the Bering Sea ecosystem span the pelagic water column, the benthic sea floor, and the sympagic sea ice environments. The Bering Ecosystem Study Nutrient-Phytoplankton-Zooplankton (BESTNPZ) model has been developed to simulate the lower-trophic-level processes throughout this region. Here, we present a version of this lower-trophic-level model coupled to a three-dimensional regional ocean model for the Bering Sea. We quantify the model's ability to reproduce key physical features of biological importance as well as its skill in capturing the seasonal and interannual variations in primary and secondary productivity over the past several decades. We find that the ocean model demonstrates considerable skill in replicating observed horizontal and vertical patterns of water movement, mixing, and stratification, as well as the temperature and salinity signatures of various water masses throughout the Bering Sea. Along the data-rich central portions of the southeastern Bering Sea shelf, it is also able to capture the mean seasonal cycle of primary production. However, its ability to replicate domain-wide patterns in nutrient cycling, primary production, and zooplankton community composition, particularly with respect to the interannual variations that are important when linking variation in productivity to changes in longer-lived upper-trophic-level species, remains limited. We therefore suggest that near-term application of this model should focus on the physical model outputs, while model development continues to elucidate potential mechanisms controlling nutrient cycling, bloom processes, and trophic dynamics.

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, use of Earth system models 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 provides a brief overview of some of the most prominent differences among the most recent generation of Earth system models and how they are relevant to LMR application.

The continental shelf around Kodiak Island is incised with numerous submarine canyons, which play an important role in the cross-shelf transport of heat, salt, and nutrients, and the transport of ichthyoplankton of deep-spawning fish from the slope region into the shallow nursery grounds surrounding Kodiak Island. To explore the pathways and variability of flow, and the extent of tidal mixing within the canyons, moorings were placed in the Chiniak, Barnabas, and Amatuli troughs, and off the shelf from Resurrection Bay (Seward Line) and the Kenai Peninsula (Gore Point). In the troughs, intensified flow was evident near the trough walls, and flow was directed by bathymetry with inflow along the upstream (northern) side and outflow along the downstream (southern) side. The presence of mesoscale eddies in the gulf had no unique influence on currents or salinity in the troughs. Tidal mixing was strongest in Chiniak Trough, and this introduced cold, nutrient-rich bottom waters into the upper water column. Intensified bottom flow associated with the Alaskan Coastal Current was evident along the Seward Line and Gore Point, and directed toward the Kennedy-Stevenson Entrances, which are also regions of strong tidal mixing. Observations of tidal mixing were consistent with model results and satellite images showing cooler, phytoplankton-rich water in summer in the nursery grounds that surround Kodiak Island. Patterns of flow within the troughs and in Shelikof Strait were consistent with the springtime advance of ichthyoplankton across the shelf.

We present the results of a study of the connectivity between Pacific cod spawning and nursery areas, and settlement of Pacific cod in the Gulf of Alaska. This work was conducted to address the hypothesis that spatial and temporal patterns of recruitment are related to variability in connectivity between spawning and nursery areas. To examine this hypothesis, we developed a Lagrangian, biophysical, individual-based model of Pacific cod early life history and dispersal using the Dispersal Model for Early Life Stages (DisMELS) framework. This model is driven by currents and scalars such as temperature from a version of the Regional Oceanographic Model System (ROMS) developed for the Gulf of Alaska. Results of our study show connectivity patterns predicted by the model that agree with our understanding (based on genetic analyses) that there is a high degree of localized retention in Pacific cod. The results indicate that the Shumagin Islands and Prince William Sound regions may serve as important collectors of Pacific cod recruits from upstream spawning areas. We also find correlations between individual-based model outputs and several large-scale climate indicators that appear to show settlement in several important nursery areas, and recruitment overall, are positively affected by slower gyre circulation in the Gulf of Alaska. We hypothesize that this is due to enhancement of retention, settlement in the Shumagin Island region, and reduction of transport of young cod out of the Gulf of Alaska to the southwest.

Little is known about the mechanism of transport that enables age-0 sablefish (Anoplopoma fimbria) to reach suitable nursery sites from spawning locations far offshore, or the strength of the connection between individual spawning sites and nursery areas, or how variability in the strength of these connections may impact recruitment success. Using a model for the early life stages of sablefish, we explored the variability in connectivity between spawning and recruitment sites that can arise solely from interannual variability in environmental forcing and its impact on transport. Our major findings are that 1) the model indicates young sablefish settling in nursery areas in the Gulf of Alaska were most likely spawned in the eastern Gulf; 2) sablefish spawned in the western Gulf of Alaska are unlikely to settle anywhere in the Gulf, and are more likely to be advected farther west, perhaps to settle in the Aleutian islands or Bering Sea (to contribute to the Alaska population, they would have to undergo an active return migration as they mature); 3) total connectivity between all spawning sites and nursery areas showed stronger correlation with recruitment estimates than the strength of connections to or from specific regions; and 4) transport to St. John Baptist Bay, a known sablefish nursery area, was not the most probable end point for sablefish spawned throughout our Gulf of Alaska model domain. This suggests that young individuals arrive at this persistent nursery area due to directional swimming behavior, highly localized spawning, or small-scale currents not captured in the hydrographic model. The fact that no single correlate in our analysis had a very strong relationship to sablefish recruitment indicates that recruitment variability arises from complex interactions between the environment and the individual, and a possible disconnect in spatial scales between the Gulf of Alaska sablefish IBM and the broader sablefish stock assessment, which includes both the GOA and the Eastern Bering Sea, as well as possible contributions from Canadian stocks to the south. Our analyses determined that although the timing and extent of this transport shows significant interannual variability, both the location of likely sablefish spawning (source) areas and the comparative strength of connectivity between spawning and nursery sites appear to be relatively consistent year-to-year.

Little is known regarding the importance of early-life transport and dispersion mechanisms in determining recruitment variability for Pacific ocean perch (POP) in the Gulf of Alaska (GOA). These mechanisms influence the degree of, and variability in, connectivity between offshore natal areas (parturition sites) and inshore demersal nursery habitats for young-of-the year juveniles, and may thus play an important role in the “gauntlet” that individuals must survive from parturition to recruitment. As a first attempt to assess interannual variability in connectivity between natal and nursery areas for POP in the GOA in a synthetic manner, we developed a coupled biophysical individual-based model (IBM) for POP early life history and dispersal with simple representations of active vertical movement, passive horizontal movement, growth, and settlement in appropriate nursery habitat to integrate known early-life traits with variability in environmental forcing. We used an oceanographic model for the GOA based on the Regional Ocean Modeling system (ROMS) to provide the underlying daily physical environment to force the IBM for 1996–2011 and simulated hundreds of thousands of individual POP from parturition along the shelf break to settlement in inshore demersal nursery habitats as young-of-the-year. We used the IBM results to assess spatial patterns of annual “maximum potential” connectivity between presumed natal and nursery areas at alongshore scales of ~ 150 km, as well as the interannual variability in these patterns. Results showed that, even in the absence of mortality, most (> 70%) individuals were unsuccessful in dispersing from presumed natal areas along the continental shelf break to inshore nursery areas. For those that were successful, connectivity was directed in a counterclockwise fashion (southeast to northwest) around the GOA following prevailing current patterns. Typical dispersion distances were on the order of 100's of km alongshore, much larger than those inferred from genetic sampling. Natal areas from which the highest fractions of successful individuals originated were in the southeast GOA, while the nursery areas most frequently reached by those successful individuals were in the central GOA. POP from natal areas in the western GOA were consistently exported from the system and likely contribute little to the GOA population, although they may contribute to populations in the Aleutian Islands and eastern Bering Sea. We also found that annual indices derived from the connectivity matrices were not very strongly related to any of a suite of basin- and regional-scale environmental indices, reflecting the overall complexity and scale of the pathways POP in the GOA may undertake during their early life stages and suggesting that multiple drivers operating at different spatial and temporal scales influence connectivity patterns. Finally, while our results indicate that interannual variability in physical transport may have a substantial impact on connectivity, we found little support for the hypothesis that this alone drives variability in POP recruitment.

Synthesis of four decades of Gulf of Alaska ichthyoplankton data indicates that species diversity and total abundance peaks during spring, a common pattern in temperate and sub-arctic ocean regions due to synchrony with the spring peak in plankton production. Nevertheless, fish larvae occur in the plankton at all times of year and peak abundance periods vary significantly by species and habitat. Larval size at hatching and at transformation to the juvenile stage is also highly variable and associated with a variety of larval durations and temporal supply of larval cohorts to pelagic habitats. This phenological diversity represents variability in exposure and adaptation to seasonal cycles in the ocean. Water temperature, winds and currents, and availability of suitable zooplankton prey vary significantly on a seasonal scale affecting degrees of synchrony among larval species with optimal environmental conditions for growth, transport and survival. This synchrony is also affected by interannual shifts in the oceanographic environment, and different early life phenologies among species generate different sensitivities to such interannual variability. Early life history strategies and synchronies are evaluated here and environmental sensitivities are proposed for the numerically dominant species of fish larvae occurring in Gulf of Alaska plankton, including commercially and ecologically important species. For winter to early spring spawners, cold temperatures are an advantage in terms of slowing development so that larvae do not use up all their lipid reserves prior to optimal availability of suitable larval zooplankton prey. Interannual variability in winter temperature may therefore be a good indicator of survival outcomes, especially as influenced by the timing of the switch to exogenous feeding. Variability in temperature-influenced larval growth during late spring and summer months may be less consequential in maintaining synchrony with larval food availability for spring-summer spawners. Rapid growth in association with warm summer conditions facilitates access to a wide size range of prey organisms and minimizes critical periods of vulnerability to trophic mismatch. The Gulf of Alaska is a highly advective environment; storms and alongshore winds promote onshore advection of surface waters. This onshore Ekman transport is strongest during winter and spring when deep water spawned larvae are most abundant over the slope and require access to the shelf. Enhanced shoreward transport of larvae in the canyons intersecting the slope is also an important mechanism. Interannual variability in such transport mechanisms may be critical in determining early ontogeny survival for these species. During all seasons, but especially spring and summer, there are species of larvae for which retention nearshore is vital for survival and mesoscale oceanographic features as well as larval behavioral abilities may be crucial. Annual patterns in phytoplankton and zooplankton production and abundance indicate high-amplitude variation in the composition of prey fields available to larvae, including variability in abundance and the size spectrum of organisms that larvae might encounter and consume. Food limitation seems less likely for larval species that are most abundant in spring-summer than for species with peak abundance in winter-spring. It is probable that the more selective a species is in terms of zooplankton prey, the more susceptible that species is to a trophic mismatch. Species-specific intrinsic rates and morphological development during early ontogeny also influence the interaction of larvae with their environment, and larval growth trajectories can be quite different even among species with identical early life phenology. This insight clearly indicates that although phenology is critical, timing is not everything and all fish larvae are not equal. For the 23 species and two genera of fish in this study, a synoptic overview is provided of their early ontogeny environmental synchronies and proposed sensitivities. This ecological synthesis of phenologies helps us characterize vulnerability and resilience factors for intervals of the planktonic phase in the pelagic environment. It also identifies environmental signals that could be tested as species-specific ecosystem indicators of population trends for fish stocks in the Gulf of Alaska. Further, understanding seasonal dynamics in the ichthyoplankton is considered important for gauging food availability and energy flow more broadly in this and other pelagic ecosystems, as well as to understanding environmental forcing on the fish populations themselves.

The northern Gulf of Alaska (GOA) shelf is dynamic spatially and temporally. With two major current systems and numerous eddies and meanders, interpretation of field data from ship-based observations at specific times and locations is complicated. We used the Regional Ocean Modeling System (ROMS) with an embedded nutrient-phytoplankton-zooplankton (GOANPZ) model to aid in understanding spatial-temporal patterns of productivity, chlorophyll concentration and biomass over the GOA shelf between 132oW and 160oW from 2000 to 2013. Carbon chlorophyll ratios in the model were varied in response to light to alter production-irradiance curves by season to conform to field measurements. Simulations reveal regions of high productivity in March–May on the southeast Alaskan Shelf, and the western inner shelf between Prince William Sound (PWS) and the Shumagin Islands, but with lower productivity on the outer shelf between PWS and western Kodiak. The model produced regions of elevated productivity on the outer shelf of the western GOA during summer and fall. This pattern is driven by circulation affecting the distribution of iron on the western shelf. Simulated productivity on the shelf between 2000 and 2006 was elevated relative to 2007–2013, apparently due to changes in the simulated iron concentration. Correlations indicate that simulated production on the western GOA shelf during March–May can explain up to 65% of the variance in the mean biomass of large copepods from net tows during spring. Simulations suggest that detailed temporal-spatial data on iron concentration and the processes affecting iron are crucial to understanding interannual spatial-temporal differences in magnitudes of production and biomass at lower trophic levels on the GOA shelf.

Recent observations of record low winter sea-ice coverage and warming water temperatures in the eastern Bering Sea have signaled the potential impacts of climate change on this ecosystem, which have implications for commercial fisheries production. We investigate the impacts of forecasted climate change on the eastern Bering Sea food web through the end of the century under medium- and high-emissions climate scenarios in combination with a selection of fisheries management strategies by conducting simulations using a dynamic food web model. The outputs from three global earth system models run under two greenhouse gas emission scenarios were dynamically downscaled using a regional ocean and biogeochemical model to project ecosystem dynamics at the base of the food web. Four fishing scenarios were explored: status quo, no fishing, and two scenarios that alternatively assume increased fishing emphasis on either gadids or flatfishes. Annual fishery quotas were dynamically simulated by combining harvest control rules based on model-simulated stock biomass, while incorporating social and economic tradeoffs induced by the Bering Sea’s combined groundfish harvest cap. There was little predicted difference between the status quo and no fishing scenario for most managed groundfish species biomasses at the end of the century, regardless of emission scenario. Under the status quo fishing scenario, biomass projections for most species and functional groups across trophic levels showed a slow but steady decline toward the end of the century, and most groups were near or below recent historical (1991–2017) biomass levels by 2080. The bottom–up effects of declines in biomass at lower trophic levels as forecasted by the climate-enhanced lower trophic level modeling, drove the biomass trends at higher trophic levels. By 2080, the biomass projections for species and trophic guilds showed very little difference between emission scenarios. Our method for climate-enhanced food web projections can support fisheries managers by informing strategic guidance on the long-term impacts of ecosystem productivity shifts driven by climate change on commercial species and the food web, and how those impacts may interact with different fisheries management scenarios.

Stepwise methodology for determining climate-informed multispecies biological references points for sustainable fishery harvest. This approach follows the status quo North Pacific Marine Fishery Council reviewed multispecies assessment methodology and represents a precautionary approach that minimizes inflation of Acceptable Biological Catch (ABC) due to predator release and also minimizes potential non-intuitive compound effects of climate change and fishing under declining conditions (i.e., whereby a climate informed B0 declines with climate-change and produces a lower target biomass such as B40%).

Climate change is impacting fisheries worldwide with uncertain outcomes for food and nutritional security. Using management strategy evaluations for key US fisheries in the eastern Bering Sea we find that Ecosystem Based Fisheries Management (EBFM) measures forestall future declines under climate change over non-EBFM approaches. Yet, benefits are species-specific and decrease markedly after 2050. Under high-baseline carbon emission scenarios (RCP 8.5), end-of-century (2075–2100) pollock and Pacific cod fisheries collapse in >70% and >35% of all simulations, respectively. Our analysis suggests that 2.1–2.3 °C (modeled summer bottom temperature) is a tipping point of rapid decline in gadid biomass and catch. Multiyear stanzas above 2.1 °C become commonplace in projections from ~2030 onward, with higher agreement under RCP 8.5 than simulations with moderate carbon mitigation (i.e., RCP 4.5). We find that EBFM ameliorates climate change impacts on fisheries in the near-term, but long-term EBFM benefits are limited by the magnitude of anticipated change., Ecosystem Based Management measures developed to prevent overfishing could be particularly important under climate change. Here the authors combine climate and fish stock modelling to show that EBM cap implementation reduces climate-driven fishery declines under RCP 4.5 and 8.5 before midcentury. However, there are thermal tipping points beyond which potential collapses are predicted.

Characterization of uncertainty (variance) in ecosystem projections under climate change is still rare despite its importance for informing decision-making and prioritizing research. We developed an ensemble modeling framework to evaluate the relative importance of different uncertainty sources for food web projections of the eastern Bering Sea (EBS). Specifically, dynamically downscaled projections from Earth System Models (ESM) under different greenhouse gas emission scenarios (GHG) were used to force a multispecies size spectrum model (MSSM) of the EBS food web. In addition to ESM and GHG uncertainty, we incorporated uncertainty from different plausible fisheries management scenarios reflecting shifts in the total allowable catch of flatfish and gadids and different assumptions regarding temperature-dependencies on biological rates in the MSSM. Relative to historical averages (1994–2014), end-of-century (2080–2100 average) ensemble projections of community spawner stock biomass, catches, and mean body size (±standard deviation) decreased by 36% (±21%), 61% (±27%), and 38% (±25%), respectively. Long-term trends were, on average, also negative for the majority of species, but the level of trend consistency between ensemble projections was low for most species. Projection uncertainty for model outputs from ∼2020 to 2040 was driven by inter-annual climate variability for 85% of species and the community as a whole. Thereafter, structural uncertainty (different ESMs, temperature-dependency assumptions) dominated projection uncertainty. Fishery management and GHG emissions scenarios contributed little (

The Alaska Climate Integrated Modeling (ACLIM) project represents a comprehensive, multi-year, interdisciplinary effort to characterize and project climate-driven changes to the eastern Bering Sea (EBS) ecosystem, from physics to fishing communities. Results from the ACLIM project are being used to understand how different regional fisheries management approaches can help promote adaptation to climate-driven changes to sustain fish and shellfish populations and to inform managers and fishery dependent communities of the risks associated with different future climate scenarios. The project relies on iterative communications and outreaches with managers and fishery-dependent communities that have informed the selection of fishing scenarios. This iterative approach ensures that the research team focuses on policy relevant scenarios that explore realistic adaptation options for managers and communities. Within each iterative cycle, the interdisciplinary research team continues to improve: methods for downscaling climate models, climate-enhanced biological models, socio-economic modeling, and management strategy evaluation (MSE) within a common analytical framework. The evolving nature of the ACLIM framework ensures improved understanding of system responses and feedbacks are considered within the projections and that the fishing scenarios continue to reflect the management objectives of the regional fisheries management bodies. The multi-model approach used for projection of biological responses, facilitates the quantification of the relative contributions of climate forcing scenario, fishing scenario, parameter, and structural uncertainty with and between models. Ensemble means and variance within and between models inform risk assessments under different future scenarios. The first phase of projections of climate conditions to the end of the 21st century is complete, including projections of catch for core species under baseline (status quo) fishing conditions and two alternative fishing scenarios are discussed. The ACLIM modeling framework serves as a guide for multidisciplinary integrated climate impact and adaptation decision making in other large marine ecosystems.

Ecologists and oceanographers inform population and ecosystem management by identifying the physical drivers of ecological dynamics. However, different research communities use different analytical tools where, for example, physical oceanographers often apply rank-reduction techniques (a.k.a. empirical orthogonal functions [EOF]) to identify indicators that represent dominant modes of physical variability, whereas population ecologists use dynamical models that incorporate physical indicators as covariates. Simultaneously modeling physical and biological processes would have several benefits, including improved communication across sub-fields; more efficient use of limited data; and the ability to compare importance of physical and biological drivers for population dynamics. Here, we develop a new statistical technique, EOF regression, which jointly models population-scale dynamics and spatially distributed physical dynamics. EOF regression is fitted using maximum-likelihood techniques and applies a generalized EOF analysis to environmental measurements, estimates one or more time series representing modes of environmental variability, and simultaneously estimates the association of this time series with biological measurements. By doing so, it identifies a spatial map of environmental conditions that are best correlated with annual variability in the biological process. We demonstrate this method using a linear (Ricker) model for early-life survival ("recruitment") of three groundfish species in the eastern Bering Sea from 1982 to 2016, combined with measurements and end-of-century projections for bottom and sea surface temperature. Results suggest that (a) we can forecast biological dynamics while applying delta-correction and statistical downscaling to calibrate measurements and projected physical variables, (b) physical drivers are statistically significant for Pacific cod and walleye pollock recruitment, (c) separately analyzing physical and biological variables fails to identify the significant association for walleye pollock, and (d) cod and pollock will likely have reduced recruitment given forecasted temperatures over future decades.

Three different global earth system models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) were used to explore anticipated changes in the Bering Sea under high (SSP126) and low (SSP585) carbon mitigation scenarios (i.e. low and high emission scenarios), via dynamical downscaling. A multivariate pattern analysis, based on Empirical Orthogonal Functions applied to monthly time series, reveals strong coupling of changes across several biophysical variables and the global forcing itself, on both yearly and multidecadal time scales. Rising air and ocean temperatures from the global models are strongly coupled with rising regional temperatures and reduced ice cover/thickness, as well as strong changes to the phenology of the plankton food chain, including reduced biomass of large zooplankton in the fall. This method ultimately provides a compact way to estimate the changes to many regional attributes under a variety of global change scenarios. Application of this method to a broad ensemble of the CMIP6 global model air temperatures suggests that compared to present conditions, the Bering Sea shelf bottom temperatures in July will warm by an average of ∼4 degrees C by the end of the 21st century under SSP585, as compared with ∼1 degrees C under SSP126, with greatest warming focused on the outer northern shelf.

In this study we present projected changes in the Eastern Bering Sea shelf (EBS) biophysical processes in response to climate forcing scenarios from the Coupled Model Intercomparison Phase 6 (CMIP6). These changes are obtained by dynamical downscaling using a Bering Sea regional model. Surface atmospheric and ocean boundary forcing from three Earth System Models (ESMs) in CMIP6, and a low and a high emission scenario of Shared Socioeconomic Pathway (SSP126 and SSP585) of each of the ESMs are considered. Ensemble mean results suggest that, contrary to an anticipated increase in ocean stratification under warming, diminishing ice cover in response to climate forcing and resultant reduced surface freshening weakens EBS stratification in the melt season. Modeled ensemble mean phytoplankton and zooplankton biomass on the EBS exhibits subsurface maxima during the growing season; the amplitude of these maxima decreases with warming, along with a reduction in primary productivity and oxygen concentration over much of the EBS water column. Phenology of both phytoplankton and zooplankton biomass on the EBS shifts earlier, leading to an increase (decrease) in biomass averaged between April–July (August–November), while annually averaged biomass decreases under warming. Projected changes of primary and secondary plankton biomass at the end of the 21st century are not well separated between the SSP126 and SSP585 scenario in light of the large across model spread under each scenario. The projected ensemble mean warming amplitude of the EBS summer bottom temperature is largely unchanged between results forced by the Coupled Model Intercomparison Phase 5 Representative Concentration Pathway 8.5 (CMIP5 RCP8.5) and CMIP6 SSP585 scenarios. Likewise, the reduction rate of annual mean phytoplankton and large zooplankton biomass are comparable between RCP8.5 and SSP585 projections, even though the absolute amplitudes of biomass are sensitive to modeling parameters such as the solar irradiance attenuation curve. Hence, within the Bering Sea dynamical downscaling framework, projected long-term warming trends in EBS bottom temperature and plankton biomass reduction rates are robust responses to climate forcing.

Climate-enhanced stock assessment models represent potentially vital tools for managing living marine resources under climate change. We present a climate-enhanced stock assessment where environmental variables are integrated within a population dynamics model assessment of biomass, fishing mortality and recruitment that also accounts for process error in demographic parameters. Probability distributions for the impact of the associated environmental factors on recruitment and growth can either be obtained from Bayesian analyses that involve fitting the population dynamics model to the available data or from auxiliary analyses. The results of the assessment form the basis for the calculation of biological and economic target and limit reference points, and projections under alternative harvest strategies. The approach is applied to northern rock sole (Lepidopsetta polyxystra), an important component of the flatfish fisheries in the Eastern Bering Sea. The assessment involves fitting to data on catches, a survey index of abundance, fishery and survey age-compositions and survey weight-at-age, with the relationship between recruitment and cold pool extent and that between growth increment in weight and temperature integrated into the assessment. The projections also allow for an impact of ocean pH on expected recruitment based on auxiliary analyses. Several alternative models are explored to assess the consequences of different ways to model environmental impacts on population demography. The estimates of historical biomass, recruitment and fishing mortality for northern rock sole are not markedly impacted by including climate and environmental factors, but estimates of target and limit reference points are sensitive to whether and how environmental variables are included in stock assessments and projections.

High latitude and subpolar regions like the Gulf of Alaska (GOA) are more vulnerable than equatorial regions to rising carbon dioxide (CO2) levels, in part due to local processes that amplify the global signal. Recent field observations have shown that the shelf of the GOA is currently experiencing seasonal corrosive events (carbonate mineral saturation states Ω, Ω

The pteropod Limacina helicina frequently experiences seasonal exposure to corrosive conditions (Ωar ar conditions in the natural environment. Combining field observations, high-CO2 perturbation experiment results, and retrospective ocean transport simulations, we investigated biological responses based on histories of magnitude and duration of exposure to Ωar 2 experimental conditions do not show acclimatization capacity or physiological tolerance related to history of exposure to corrosive conditions. Pteropods from the coastal CCE appear to be at or near the limit of their physiological capacity, and consequently, are already at extinction risk under projected acceleration of OA over the next 30 years. Our results demonstrate that Ωar exposure history largely determines pteropod response to experimental conditions and is essential to the interpretation of biological observations and experimental results.

Observations indicate that spring and fall phytoplankton blooms on the Eastern Bering Sea (EBS) continental shelf tend to co-vary on inter-annual scales – that is, a year with a strong spring bloom also tends to have a strong fall bloom. Similar co-variability of primary production is also seen in the multi-year (1987–2007) integration of a coupled physical–biological model. Moreover, the modeled seasonal amplitudes of 10-meter chlorophyll-a concentrations at the EBS middle shelf mooring locations, computed using the canonical Redfield ratio and a mean carbon-to-chlorophyll-a ratio, are generally consistent with the in situ mooring measurements. The coupled physical–biological model simulation is used to examine the relative contributions of wind mixing, local nutrient recycling/regeneration, horizontal nutrient advection, and water-column stability to this co-variability. There is no significant correlation between the spring and fall surface wind mixing. Although wind mixing is an important mechanism for bringing nutrients in the lower water column to the surface layers, it is not the mechanism tying the two seasons׳ productivity together. Local regeneration/recycling of the nutrients initially fueling spring production is an important mechanism for spring-to-fall nutrient accumulation in the bottom layers at the middle shelf. Horizontal advection does not appear to be the dominant factor for supplying nutrients to the middle shelf during the spring-to-fall period. Fall primary production in the model is strongly influenced by the lower water-column stability/stratification. Taken together, these results highlight the importance of local recycling/regeneration of nutrients assimilated by spring phytoplankton bloom in linking together the spring and fall primary productions on EBS middle shelf.

We combined field data and the output from a climate-to-fish coupled biophysical model to calculate weekly climatologies and 1971–2009 time series of physical and biological drivers for 16 distinct regions of the eastern Bering Sea shelf and slope. We focus on spatial trends and physical-biological interactions as a framework to compare model output to localized or season-specific observations. Data on pollock (≥8 cm) diet were used to evaluate energy flows and zooplankton dynamics predicted by the model. Model validation shows good agreement to sea-ice cover albeit with a one month delay in ice retreat. Likewise, the timing of spring phytoplankton blooms in the model were delayed approximately one month in the south and extend further into summer, but the relative timing between the spring and fall bloom peaks was consistent with observations. Ice-related primary producers may shift the timing of the spring bloom maximum biomass earlier in years when sea ice was still present after mid-March in the southern regions. Including the effects of explicit, dynamic fish predation on zooplankton in the model shifts the seasonal spring peak and distribution of zooplankton later in the year relative to simulations with implicit predation dependent only on zooplankton biomass and temperature; the former capturing the dynamic demand on zooplankton prey by fish. Pollock diets based on stomach samples collected in late fall and winter from 1982–2013 show overwintering euphausiids and small pollock as key prey items in the outer and southern Bering Sea shelf; a characteristic not currently present in the model. The model captured two large-scale gradients, supported by field data, characterizing the overall dynamics: 1) inshore to off-shelf physical and biological differences with a gradient in inter-annual variability from higher frequency inshore to lower frequency offshore; and 2) latitudinal gradients in the timing of events. The combined effects of length of day, bathymetry, and tides, which are consistent from year to year, and the two large-scale gradients, characterize the environment on which regional differences were based and restrict their inter-annual and seasonal variability. Thus, the relative timing and sequence of events remained consistent within regions. The combination of model outputs and observational data revealed specific ecosystem processes: (1) The spatial progression in the timing, peaks and sequence of events over the shelf is driven by wind, sea ice, and stratification and creates a seasonal expansion and contraction of the warmer pelagic and bottom habitat suitable to pollock. (2) The seasonal warming of air temperature and the spring-summer expansion of the warm pelagic and bottom habitats influence the ice retreat and the associated ice edge and open water spring blooms, as well as subsequent production/abundance of copepods and euphausiids. (3) These warmer conditions favor pelagic energy flows to pollock (≥10 cm) and allow their distribution to expand shoreward and northward along the shelf break. (4) The fall-winter expansion of the seasonal ice cover drives the contraction of warmer waters towards the outer and southwest shelf and favors benthic energy flows over most of the shelf. There, fall blooms allow for additional lipid storage by large copepods and euphausiids that sink close to the bottom where they either go into diapause or have a restricted diel migration over winter. (5) During these cold months, the preferred pollock habitat shifts and contracts towards the outer and southwest shelf where their increased density and reduced prey availability leads to winter pollock cannibalism and consumption of overwintering euphausiids. Our project highlights the benefits of linking continuous and long-term field work with the development and implementation of highly complex models. In the face of uncertainty, simulations such as these, tightly coupled to field programs, will be instrumental as testbeds for process exploration and management evaluation, increasing their relevance for future fisheries and ecosystem management and strategic planning.

Three global climate simulations from the Intergovernmental Panel on Climate Change Fourth Assessment (AR4) were used as physical forcing to drive a regional model that includes both physical and biological elements of the Bering Sea. Although each downscaled projection indicates a warming of 1–2 °C between 2010 and 2040 on the Bering Sea shelf, the interannual and interdecadal details of this trend vary considerably among the three realizations. In each case, the magnitude of presently observed interannual variability of bottom temperatures and ice cover is found in the models to be maintained out to at least 2040, but with a steadily increasing probability of warm years with less ice on the southern shelf. The overall trends indicate warmer temperatures and the retreat of ice in the southeastern Bering Sea, but continued ice cover in the northeastern Bering Sea. Sensitivity analyses suggest both increasing air temperature and northward wind stress as primary drivers of higher water-column temperatures. Based on currently available models, changes in shortwave radiation are not likely to have a significant role in this warming. Warming trends on the outer shelf may lead to decreased production of large crustacean zooplankton at that location, but could increase such production on the inner shelf.

Chinook salmon (Oncorhynchus tshawytscha, Salmonidae) returns to western Alaska were historically high and variable but recently reached record lows. Understanding the differential influence of climatic and oceanic conditions on the growth of juvenile Chinook salmon in the north and south eastern Bering Sea is key to understanding mechanisms and factors affecting the production dynamics of Chinook salmon from western Alaska and the Arctic. Summer growth was lower and more variable among years for Chinook salmon in the south than the north eastern Bering Sea. Summer growth decreased with a rise in sea temperatures in the north and south and increased with more sea ice coverage and a later time of ice retreat in the south but not in the north. Capelin (Mallotus villosus), an important prey for juvenile Chinook salmon in the north and during cold years may link increased growth to cooler sea temperatures. Reduced and more variable summer growth of juvenile Chinook salmon from the eastern Bering Sea with warming may have implications on overwintering survival.

Trait-based climate vulnerability assessments based on expert evaluation have emerged as a rapid tool to assess biological vulnerability when detailed correlative or mechanistic studies are not feasible. Trait-based assessments typically view vulnerability as a combination of sensitivity and exposure to climate change. However, in some locations, a substantial amount of information may exist on system productivity and environmental conditions (both current and projected), with potential disparities in the information available for data-rich and data-poor stocks. Incorporating this level of detailed information poses challenges when conducting, and communicating uncertainty from, rapid vulnerability assessments. We applied a trait-based vulnerability assessment to 36 fish and invertebrate stocks in the eastern Bering Sea (EBS), a data-rich ecosystem. In recent years, the living marine resources of the EBS and Aleutian Islands have supported fisheries worth more than US $1 billion of annual ex-vessel value. Our vulnerability assessment uses projections (to 2039) from three downscaled climate models, and graphically characterizes the variation in climate projections between climate models and between seasons. Bootstrapping was used to characterize uncertainty in specific biological traits and environmental variables, and in the scores for sensitivity, exposure, and vulnerability. The sensitivity of EBS stocks to climate change ranged from "low" to "high," but vulnerability ranged between "low" and "moderate" due to limited exposure to climate change. Comparison with more detailed studies reveals that water temperature is an important variable for projecting climate impacts on stocks such as walleye pollock (Gadus chalcogrammus), and sensitivity analyses revealed that modifying the rule for determining vulnerability increased the vulnerability scores. This study demonstrates the importance of considering several uncertainties (e.g., climate projections, biological, and model structure) when conducting climate vulnerability assessments, and can be extended in future research to consider the vulnerability of user groups dependent on these stocks.

The Bering Sea is highly vulnerable to ocean acidification (OA) due to naturally cold, poorly buffered waters and ocean mixing processes. Harsh weather conditions within this rapidly changing, geographically remote environment have limited the quantity of carbon chemistry data, thereby hampering efforts to understand underlying spatial-temporal variability and detect long-term trends. We add carbonate chemistry to a regional biogeochemical model of the Bering Sea to explore the underlying mechanisms driving carbon dynamics over a decadal hindcast (2003–2012). The results illustrate that coastal processes generate considerable spatial variability in the biogeochemistry and vulnerability of Bering Sea shelf water to OA. Substantial seasonal biological productivity maintains high supersaturation of aragonite on the outer shelf, whereas riverine freshwater runoff loaded with allochthonous carbon decreases aragonite saturation states (ΩArag) to values below 1 on the inner shelf. Over the entire 2003–2012 model hindcast, annual surface ΩArag decreases by 0.025 – 0.04 units/year due to positive trends in the partial pressure of carbon dioxide (pCO2) in surface waters and dissolved inorganic carbon (DIC). Variability in this trend is driven by an increase in fall phytoplankton productivity and shelf carbon uptake, occurring during a transition from a relatively warm (2003–2005) to cold (2010–2012) temperature regime. Our results illustrate how local biogeochemical processes and climate variability can modify projected rates of OA within a coastal shelf system.