Rapid warming in the Gulf of Alaska provides an opportunity for assessing emerging impacts of climate change on walleye pollock (Gadus chalcogrammus), which support a valuable fishery in that ecosystem. We evaluated the effects of ocean warming on weight at age, recruitment, and age diversity on the Gulf of Alaska walleye pollock stock. Specifically, we tested the predictions of the temperature-size rule that warming should increase (decrease) weight at age for juvenile (adult) fish. We also assessed whether warming effects on recruitment had subsequent lagged effects on age diversity, which is an important component of resilience to warming and other perturbations. Our analysis used data from a 2019-2022 beach seine survey of age-0 fish, a 1986-2021 acoustic trawl survey of spawning aggregations, and 1987-2021 data on commercial catches collected by on-board observers. We found limited support for the temperature-size rule: warming was associated with increased weight at age for age-0 fish, and decreased weight for mature (age 3-10) fish, but also decreased weight for immature (age 1-2) fish. Declines in weight at age were large enough (approximate to - 1 SD in log space) to suggest that temperaturecorrected estimates of weight are likely important for accurate translation of population estimates into biomass for setting management reference points. We also found negative effects of warming on recruitment. Strong reductions in recruitment, combined with the dominance of the spawning population by the exceptionally large 2012 year class, contributed to a lagged temperature effect of reduced age diversity in the spawning population during 2014-2018. A diverse age structure is an important predictor of resilience in fish stocks, and the warming effects on recruitment and age diversity suggest poor resilience of this stock to continued warming.

Tanner crab (Chionoecetes bairdi) and snow crab (C. opilio) populations in the eastern Bering Sea have reached historic lows in recent years, and declines have been linked to recruitment failures and mortality events. Bitter crab disease, caused by a parasitic dinoflagellate (Hematodinium sp.), contributes to high mortality rates in Tanner and snow crab, and outbreaks have the potential to reduce recruitment and population productivity. Here, we employed a polymerase chain reaction assay to detect Hematodinium sp. in Tanner and snow crab hemolymph samples to: 1) evaluate testing accuracy of visual disease detection methods; 2) estimate bitter crab disease prevalence from 2015 to 2017 in eastern Bering Sea monitoring sites; and 3) identify factors influencing the likelihood of Hematodinium sp. infection. Our results indicated that visual diagnostic methods failed to detect 93 % of infections, and underestimated disease prevalence by up to 90 %. Infection risk was highly dependent on host size, sex and sampling date. Small Tanner crab (<30 mm carapace width) were nearly twice as susceptible to infection, and female snow crab were 9 % more likely to be infected than males. Most notably, bitter crab disease prevalence exceeded 50 % at two monitoring sites during the study period, and annual disease prevalence increased by approximately 10 % per year in both populations. We emphasize the severe population-level consequences for these high prevalence levels in eastern Bering Sea Tanner and snow crab stocks. Our approach highlights the critical importance of continued monitoring and mechanistic modeling of bitter crab disease in severely depressed crab populations.

Marine heatwaves can result in mass mortality events, but the mechanisms underlying population collapse and recovery dynamics are often poorly understood. Here, we employed a comparative analysis between collapsing and noncollapsing portions of the Bering Sea snow crab population to evaluate linkages between energetic condition and population abundance during and after a recent collapse. We show that abundance declines during the collapse were associated with dramatic declines in energetic condition, and the negative impact of high population density on energetic reserves was intensified by warming during a marine heatwave. Elevated energetic condition coincided with strong recruitment post-collapse, suggesting rapid initial population recovery in the eastern Bering Sea. However, we show that cold-water habitat (≤0 °C) is critical for supporting high snow crab density in rebuilding towards a pre-collapse state. These results suggest that warming and loss of sea ice will exacerbate the risk of collapse in snow crab through energetic constraints on survival. Furthermore, we highlight the validation of an indirect energetic condition metric that will facilitate continued energetics monitoring and rapid integration into management.

Non‐stationarity (time‐varying mean or variance) in climate conditions can alter relationships between basin‐scale climate indices and the ecological conditions that map onto them. We consider evidence of time‐varying climate conditions in the California Current System (CCS) based on sea level pressure dynamics that characterize the North Pacific High (NPH), and evaluate the temporal stability of regional relationships between climate indices and physical and biological conditions across the CCS. We find relationships between climate indices and ecological conditions are relatively stable through time, but do not capture short‐term ecological trends. These results show that popular basin‐scale climate indices are insufficient in characterizing the North Pacific climate system, especially from ecosystem perspectives. Applications of associations between climate and ecological variables should consider proximate physical forcing mechanisms and the stability of relationships through time.

Persistent declines in the abundance of red king crab in Bristol Bay, Alaska, have triggered recent fishery closures, heightening interest in conservation measures for this stock. However, fisheries-independent data are only collected in the summer, while proposed conservation actions target red king crab bycatch in the fall and winter, and the lack of seasonal crab distribution data outside the summer hampers evaluation of proposed management actions. To address this problem, we used fishery-dependent data to build a species distribution model (SDM) for legal male red king crab during the fall directed fishery season. Our model showed that spatial distribution was driven by variability in bottom temperature, summer distribution patterns (measured by a fisheries-independent survey), depth, and maximum tidal current. While predicted hotspots of red king crab abundance generally fell within existing management areas in Bristol Bay, these hotspots shifted with temperature, suggesting that the utility of static management areas may change over time with climate conditions. This model is the first dynamic predictive tool to evaluate red king crab distribution during the directed fishery season and provides an example of using fisheries-dependent data to inform management decisions during seasons when fisheries-independent data are unavailable.

We used semi-parametric Bayesian regression to determine whether ocean acidification or climate warming could explain declining productivity for southeast Bering Sea red king crab (Paralithodes camtchaticus). Negative effects of acidification explained ~21% of recruitment variability over 1980-2023, and ~45% since 2000. Ocean warming had a negligible effect in our analysis. Model-estimated annual mean bottom pH in the region has fallen from ~8.03 in 1980 to ~7.89 in 2023, approaching levels that reduce juvenile survival in laboratory studies. Improved model validation and better understanding of potential threshold effects on red king crab are needed to better understand the possible population-level acidification effect that we demonstrate.

Ecosystem-based fisheries management requires the successful integration of ecosystem information into the fisheries management process. In the Northeast Pacific Ocean, ecosystem data collection and accessibility have achieved successful milestones, yet application to the harvest specification process remains challenging. The synthesis, interpretation, and application of ecosystem information to groundfish fisheries management in the Gulf of Alaska (GOA) can be supported by the identification of common ecosystem trends and ecosystem states across a diverse set of indicators. In this study, we used Dynamic Factor Analysis (DFA) and hidden Markov models (HMM) to analyze 92 indicators in climate, lower-trophic, mid-trophic, and seabird models for the western and eastern GOA marine ecosystems. Time series ranged from 25 to 52 years in length, analyzed through 2022. The DFA identified common trends across indicators and groups of covarying indicators (e.g., biomass of zooplankton species), highlighting opportunities to streamline communication of these data to management. Non-stationarity analyses revealed past changes in relationships, and can provide early warnings in future annual updates if previously identified correlations change. The HMM identified two to three ecosystem states in each sub-model that largely aligned with previously observed long- and short-term shifts in ecosystem dynamics in the region (i.e., shifts starting in 1975, 1988, and 2014). Annually updating these analyses, within an existing framework of reporting ecosystem information to management bodies, can streamline communication and improve early warning of changes in ecosystem dynamics. These tools can provide ecosystem support to management decisions relative to groundfish productivity and resulting harvest specifications.

Warming temperatures in the Gulf of Alaska have been linked to recruitment failure in Pacific cod (Gadus macrocephalus), but the mechanisms and timing of mortality events for juveniles are unclear. To date, limited research has focused on overwintering success, and the knowledge of juvenile ecology and physiology is based entirely on summer observations. Here, we investigate the changes in body condition, diet composition, and tissue-specific fatty acid (FA) storage for age-0 Pacific cod in Kodiak, Alaska, from February to December during 2018 and 2020. We observed protracted nearshore residency from June to December. Cod body condition (Kdry) and predicted weight at length were lowest in October, November, and December. Although not different interannually, diet composition varied seasonally, which corresponded to an increase in cod length. A range of condition metrics (HSIwet, FA concentration in liver tissue, and the % of whole body FAs stored in the liver) began to increase in September. Cod prioritized growth during the summer, while in the autumn and pre-winter they allocated more energy into lipid storage. We conclude that seasonal changes in tissue-specific FA storage and pre-winter fish conditions are important factors to consider for understanding overwintering potential of juvenile Pacific cod.

The abrupt collapse of the Bering Sea snow crab stock can be explained by rapid borealization that is >98% likely to have been human induced. Strongly boreal conditions are similar to 200 times more likely now (at 1.0-1.5 degrees C of warming) than in the pre-industrial climate, while strongly Arctic conditions are now expected in only 8% of years. Stakeholders should accelerate adaptation planning for the complete loss of Arctic characteristics in traditional fishing grounds.

Declining Bristol Bay red king crab (BBRKC) abundance has triggered recent closures of this iconic Bering Sea fishery and raised interest in bycatch in non-directed fisheries as a possible conservation concern. One particular concern is the effectiveness of static closed areas for bycatch fisheries in an era of climate warming and widespread distribution shifts. However, spatial data for supporting management decisions concerning bycatch is lacking, as fisheries-independent data are collected only in the summer, and the relationship to BBRKC distribution in the fall/winter/spring, when most bycatch occurs, is unknown. We filled this information gap by using fishery-dependent data to build predictive models of BBRKC bycatch distribution in non-pelagic trawl groundfish fisheries in the data-poor seasons. We trained Boosted Regression Tree models for bycatch occurrence and abundance of four BBRKC sex-size/maturity categories, and evaluation metrics indicated good to excellent predictive ability across all models. We found that flatfish directed-fishery CPUE, summer survey CPUE for BBRKC and flatfish, and depth were important predictors for bycatch occurrence and abundance. Physical variables (ice cover and temperature) were generally less important. We also found strong correlations between the mean latitude of observed bycatch and the summer survey for BBRKC, highlighting the ability of summer survey data to predict non-summer bycatch distributions. BBRKC bycatch prediction is a tractable problem, and our results are the first step towards operating models that may be used to evaluate proposed management actions. We also conclude that northward shifts in fishery-independent and -dependent data suggest the possible value of reassessing decades-old static closure areas for managing BBRKC bycatch.

We apply climate attribution techniques to sea surface temperature time series from five regional North Pacific ecosystems to track the growth in human influence on ocean temperatures over the past seven decades (1950–2022). Using Bayesian estimates of the Fraction of Attributable Risk (FAR) and Risk Ratio (RR) derived from 23 global climate models, we show that human influence on regional ocean temperatures could first be detected in the 1970s and grew until 2014–2020 temperatures showed overwhelming evidence of human contribution. For the entire North Pacific, FAR and RR values show that temperatures have reached levels that were likely impossible in the preindustrial climate, indicating that the question of attribution is already obsolete at the basin scale. Regional results indicate the strongest evidence for human influence in the northernmost ecosystems (Eastern Bering Sea and Gulf of Alaska), though all regions showed FAR values > 0.98 for at least one year. Extreme regional SST values that were expected every 1000–10 000 years in the preindustrial climate are expected every 5–40 years in the current climate. We use the Gulf of Alaska sockeye salmon fishery to show how attribution time series may be used to contextualize the impacts of human-induced ocean warming on ecosystem services. We link negative warming effects on sockeye fishery catches to increasing human influence on regional temperatures (increasing FAR values), and we find that sockeye salmon migrating to sea in years with the strongest evidence for human effects on temperature (FAR ⩾ 0.98) produce catches 1.4 standard deviations below the long-term log mean. Attribution time series may be helpful indicators for better defining the human role in observed climate change impacts, and may thus help researchers, managers, and stakeholders to better understand and plan for the effects of climate change.

The rapid decline in Pacific cod (Gadus macrocephalus, Gadidae) biomass following multiple Gulf of Alaska marine heatwaves (2014-2016 and 2019) may be one of the most dramatic documented changes in a sustainably managed marine fishery. As such, fisheries managers are exploring new recruitment paradigms for Pacific cod under novel environmental conditions. In this review, we address the challenges of managing and forecasting Pacific cod populations in the Eastern Pacific where thermal habitats for early life stages are undergoing varying rates of change across space and time. We use observational data to examine changes in distribution, abundance and demographics of the population from 1993 to 2020, and model contemporary and future changes of thermal habitat for both spawning success and age-0 juvenile growth potential. Results indicate that reduced spawning habitat and early life stage abundance may be a precursor to regional population decline, but the recent apparent increases in size-at-age of pre-recruits will have unknown impacts on future recruitment in these regions. We contend that continued monitoring of early life stages will be necessary to track changes in phenology and growth that likely determine size-at-age and the survival trajectories of year classes into the adult population. These include complex size- and temperature-dependent energetics spanning seasonal habitats through the first winter. Climate-ready management of Pacific cod will, therefore, require new process investigations beyond single-season surveys focused on one-life stage.

The snow crab is an iconic species in the Bering Sea that supports an economically important fishery and undergoes extensive monitoring and management. Since 2018, more than 10 billion snow crab have disappeared from the eastern Bering Sea, and the population collapsed to historical lows in 2021. We link this collapse to a marine heatwave in the eastern Bering Sea during 2018 and 2019. Calculated caloric requirements, reduced spatial distribution, and observed body conditions suggest that starvation played a role in the collapse. The mortality event appears to be one of the largest reported losses of motile marine macrofauna to marine heatwaves globally.

Fisheries-independent surveys provide critical data products used to estimate stock status and inform management decisions. While it can be possible to redistribute sampling effort to improve survey efficiency and address changing monitoring needs in the face of unforeseen challenges, it is important to assess the consequences of such changes. Here, we present an approach that relies on existing survey data and simulations to evaluate the impacts of strategic reductions in survey sampling effort. We apply this approach to assess the potential effects of reducing high density sampling near St. Matthew Island and the Pribilof Islands in the NOAA eastern Bering Sea (EBS) bottom trawl survey. These areas contain high density “corner stations” that were implemented for finer-scale monitoring of associated blue king crab stocks (Paralithodes platypus) which historically supported commercial fisheries but have since declined and are seldom eligible for harvest. We investigate the effects of removing these corner stations on survey data quality for focal P. platypus stocks and other crab and groundfish species monitored by the EBS survey. We find that removing the St. Matthew and Pribilof Islands corner stations has negligible effects on data quality for most stocks, except for those whose distributions are concentrated in these areas. However, the data quality for such stocks was relatively low even with higher density sampling, and corner station removal had only minor effects on stock assessment outcomes. The analysis we present here provides a generic approach for evaluating strategic reductions in sampling effort for systematic survey designs and can be applied by scientists and managers facing similar decisions elsewhere.

Climate change makes fish stocks more vulnerable to recruitment failure, and early detection of these events is important for an effective management response. Here, we evaluate the value of larval and juvenile surveys, and a thermal spawning habitat index, for predicting recruitment in two economically important gadids, walleye pollock (Gadus chalcogrammus) and Pacific cod (G. macrocephalus), in the Gulf of Alaska. These stocks have been exposed to rapid human-induced ocean warming since 2014, which has apparently contributed to anomalies in age structure, size at age, and other population variables (for pollock) and stock collapse (for cod). We found that warming results in recruitment that falls short of predictions from historical spawner-recruit relationships for both stocks, highlighting that climate change makes recruitment expectations based on historical experience less reliable. However, we also found that recruitment could be successfully predicted with surveys of early-life stages. Using Bayesian regression, we found that juvenile trawl survey data for pollock predicts recruitment to age-1 (as estimated by a stock assessment model), while prediction from larval surveys was less successful. Beach seine estimates of juvenile abundance also predicted pollock recruitment, a surprising result for a species that is typically sampled in offshore habitats. The spawning habitat index and beach seine survey both predicted cod recruitment to age-3 as estimated by the stock assessment model. We did not find a predictive relationship between cod larval abundance and recruitment. However, residuals from the larval model showed low-frequency variability, suggesting nonstationarity (time-dependence) in the predictive relationship. Dynamic Factor Analysis (DFA) models summarizing information across multiple data sets showed reasonable predictive value for both species (Bayesian R2 ≈ 0.4 for log recruitment), and they also allowed recruitment prediction for years with missing observations in some data sets. We conclude that surveying multiple early life stages may be the most useful approach for predicting gadid recruitment.

Ocean ecosystems are vulnerable to climate-driven perturbations, which are increasing in frequency and can have profound effects on marine social-ecological systems. Thus, there is an urgency to develop tools that can detect the response of ecosystem components to these perturbations as early as possible. We used Bayesian Dynamic Factor Analysis (DFA) to develop a community state indicator for the California Current Ecosystem (CCE) to track the system’s response to climate perturbations, and to forecast future changes in community state. Our key objectives were to (1) summarize environmental and biological variability in the southern and central regions of the CCE during a recent and unprecedented marine heatwave in the northeast Pacific Ocean (2014–2016) and compare these patterns to past variability, (2) examine whether there is evidence of a shift in the community to a new state in response to the heatwave, (3) identify relationships between community variability and climate variables; and (4) test our ability to create one-year ahead forecasts of individual species responses and the broader community response based on ocean conditions. Our analysis detected a clear community response to the marine heatwave, although it did not exceed normal variability over the past six decades (1951–2017), and we did not find evidence of a shift to a new community state. We found that nitrate flux through the base of the mixed layer exhibited the strongest relationship with species and community-level responses. Furthermore, we demonstrated skill in creating forecasts of species responses and community state based on estimates of nitrate flux. Our indicator and forecasts of community state show promise as tools for informing ecosystem-based and climate-ready fisheries management in the CCE. Our modeling framework is also widely applicable to other ecosystems where scientists and managers are faced with the challenge of managing and protecting living marine resources in a rapidly changing climate.

Ecological processes are rarely directly observable, and inference often relies on estimating hidden or latent processes. State‐space models have become widely used for this task because of their ability to simultaneously estimate the multiple sources of variation (natural variability and variance attributed to observation errors). For multivariate time series, a second aim is often dimension reduction, or estimating a number of latent processes that are smaller than the number of observed time series. Dynamic factor analysis (DFA) has been used for performing time‐series dimension reduction, where latent processes are modelled as random walks. Whereas this may be suitable for some situations, random walks may be too flexible for other cases. Here, we introduce a new class of models, where latent processes are modelled as smooth functions (basis splines, penalized splines or Gaussian process models). We implement these models in our bayesdfa r package, which uses the rstan package for fitting. After evaluating model performance with simulated data, we apply conventional models and our smooth trend models to two long‐term datasets from the west coast of the United States: (a) a 35‐year dataset of pelagic juvenile rockfishes and (b) a 39‐year dataset of fisheries catches. Our simulations demonstrate that models matching the underlying trend smoothness make better out‐of‐sample predictions, but this advantage diminishes with increasing levels of observation error. For both case studies, the best smooth trend models had higher predictive accuracy, and yielded more precise predictions, compared to the conventional approach. The smooth trend factor models introduced here offer a new approach for state‐space dimension reduction of multivariate time series. These flexible Bayesian models may be particularly useful for data that are clumped in time, for data with high signal to noise ratios and generally for data where the underlying trend is assumed to be relatively smooth.

The Pacific cod (Gadus macrocephalus) fishery recently collapsed in the Gulf of Alaska after a series of marine heatwaves that began in 2014. To gauge the likelihood of population recovery following these extreme warming events, we investigate potential thermal stress on age-0 cohorts through a comprehensive analysis of juvenile cod abundance, condition, growth, and survival data collected from 15 years of beach seine surveys. Abundance was strongly negatively related to ocean temperature during the egg and larval phase (winter-spring), but age-0 cod were larger in the early summer following warm winter-spring temperatures. Body condition indices suggest that warm summers may improve energetic reserves prior to the first winter; however, there was no summer temperature effect on post-settlement growth or survival. Spatial differences in abundance, condition, or growth were not detected, and density-dependent effects were either weak or positive. While the positive effects of increased summer temperatures on juvenile condition may benefit overwintering survival, they cannot compensate for high pre-settlement mortality from warming winter-spring temperatures. We conclude the critical thermal bottleneck for juvenile abundance occurs pre-settlement.

The temperature–size rule predicts that climate warming will lead to faster growth rates for juvenile fishes but lower adult body size. Testing this prediction is central to understanding the effects of climate change on population dynamics. We use fisheries-independent data (1999–2019) to test predictions of age-specific climate effects on body size in eastern Bering Sea walleye pollock ( Gadus chalcogrammus). This stock supports one of the largest food fisheries in the world but is experiencing exceptionally rapid warming. Our results support the predictions that weight-at-age increases with temperature for young age classes (ages 1, 3, and 4) but decreases with temperature for old age classes (ages 7–15). Simultaneous demonstrations of larger juveniles and smaller adults with warming have thus far been rare, but pollock provide a striking example in a fish of exceptional ecological and commercial importance. The age-specific response to temperature was large enough (0.5–1 SD change in log weight-at-age) to have important implications for pollock management, which must estimate current and future weight-at-age to calculate allowable catch, and for the Bering Sea pollock fishery.