CAFA Publications

Author(s): Whitehouse, G. A., K. Y. Aydin, A. B. Hollowed, K. K. Holsman, W. Cheng, A. Faig, A. C. Haynie, A. J. Hermann, K. A. Kearney, and A. E. Punt

Project PI: Hollowed
DOI: http://doi.org/10.3389/fmars.2021.624301

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.

Author(s): Hollowed, A. B., K. K. Holsman, A. Haynie, A. Hermann, A. Punt, K. Aydin, J. Ianelli, S. Kasperski, W. Cheng, A. Faig, K. Kearney, J. Reum, P. Spencer, I. Spies, W. Stockhausen, C. Szuwalski, G. A. Whitehouse, T. Wilderbuer.

Project PI: Hollowed
DOI: http://doi.org/10.3389/fmars.2019.00775

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.

Author(s): Holsman, K. K., A. Haynie, A. B. Hollowed, A. J. Hermann, W. Cheng, A. Faig, J. Ianelli, K. Kearney, A. Punt, J. Reum

Project PI: Hollowed
DOI: http://doi.org/10.1038/s41467-020-18300-3

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.

Author(s): Kearney, K., A. Hermann, W. Cheng, I. Ortiz, and K. Aydin.

Project PI: Hollowed
DOI: http://https://doi.org/10.5194/gmd-13-597-2020

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.

Author(s): McHuron, E. A., K. Luxa, N. A. Pelland, K. Holsman, R. Ream, T. Zeppelin, and J. T. Sterling.

Project PI: Hollowed
DOI: http://doi.org/10.3389/fmars.2020.597973

Food availability is a key concern for the conservation of marine top predators, particularly during a time when they face a rapidly changing environment and continued pressure from commercial fishing activities. Northern fur seals (Callorhinus ursinus) breeding on the Pribilof Islands in the eastern Bering Sea have experienced an unexplained population decline since the late-1990s. Dietary overlap with a large U.S. fishery for walleye pollock (Gadus chalcogrammus) in combination with changes in maternal foraging behavior and pup growth has led to the hypothesis that food limitation may be contributing to the population decline. We developed age- and sex-specific bioenergetic models to estimate fur seal energy intake from May–December in six target years, which were combined with diet data to quantify prey consumption. There was considerable sex- and age-specific variation in energy intake because of differences in body size, energetic costs, and behavior; net energy intake was lowest for juveniles (18.9 MJ sea-day^–1, 1,409.4 MJ season^–1) and highest for adult males (66.0 MJ sea-day^–1, 7,651.7 MJ season^–1). Population-level prey consumption ranged from 255,232 t (222,159 – 350,755 t, 95% CI) in 2006 to 500,039 t (453,720 – 555,205 t) in 1996, with pollock comprising between 41.4 and 76.5% of this biomass. Interannual variation in size-specific pollock consumption appeared largely driven by the availability of juvenile fish, with up to 81.6% of pollock biomass coming from mature pollock in years of poor age-1 recruitment. Relationships among metabolic rates, trip durations, pup growth rates, and energy intake of lactating females suggest the most feasible mechanism to increase pup growth rates is by increasing foraging efficiency through reductions in maternal foraging effort, which is unlikely to occur without increases in localized prey density. By quantifying year-specific fur seal consumption of pollock, our study provides a pathway to incorporate fur seals into multispecies pollock stock assessment models, which is critical for fur seal and fishery management given they were a significant source of mortality for both juvenile and mature pollock.

Author(s): Reum, J., J. L. Blanchard, K. K. Holsman, K. Aydin, A. B. Hollowed, A. Hermann, W. Cheng, A. Faig, A. Haynie, A. E. Punt.

Project PI: Hollowed
DOI: http://doi.org/10.3389/fmars.2020.00124

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 (<10%) to projection uncertainty, with the exception of catches for a subset of flatfishes which were dominated by fishery management scenarios. Long-term outcomes were improved in most cases under a moderate “mitigation” relative to a high “business-as-usual” GHG emissions scenario and we show how inclusion of temperature-dependencies on processes related to body growth and intrinsic (non-predation) natural mortality can strongly influence projections in potentially non-additive ways. Narrowing the spread of long-term projections in future ensemble simulations will depend primarily on whether the set of ESMs and food web models considered behave more or less similarly to one another relative to the present models sets. Further model skill assessment and data integration are needed to aid in the reduction and quantification of uncertainties if we are to advance predictive ecology.

Author(s): Thorson, J. T., W. Cheng, A. J. Hermann, J. N. Ianelli, M. A. Litzow, C. A. O’Leary, G. G. Thompson.

Project PI: Hollowed
DOI: http://doi.org/10.1111/gcb.15149

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.

Author(s): Whitehouse, G. A., K. Y. Aydin.

Project PI: Hollowed
DOI: http://doi.org/10.1016/j.ecolmodel.2020.109074

Ecosystem modelling is a useful tool for exploring the potential outcomes of policy options and conducting experiments that would otherwise be impractical in the real world. However, ecosystem models have been limited in their ability to engage in the management of living marine resources due in part to high levels of uncertainty in model parameters and model outputs. Additionally, for multispecies or food web models, there is uncertainty about the predator-prey functional response, which can have implications for population dynamics. In this study, we evaluate the sensitivity of large marine food webs in Alaska to parameter uncertainty, including parameters that govern the predator-prey functional response. We use Rpath, an R implementation of the food web modeling program Ecopath with Ecosim (EwE), to conduct a series of mortality-based perturbations to examine the sensitivity and recovery time of higher trophic level groups in the eastern Chukchi Sea, eastern Bering Sea, and Gulf of Alaska. We use a Monte Carlo approach to generate thousands of plausible ecosystems by drawing parameter sets from the range of uncertainty around the base model parameters. We subjected the ecosystem ensembles to a series of mortality-based perturbations to identify which functional groups the higher trophic level groups are most sensitive to when their mortality was increased, whether the food webs returned to their unperturbed configurations following a perturbation, and how long it took to return to that state. In all three ecosystems, we found that the number of disrupted ensemble food webs was positively related to the biomass and the number of trophic links of the perturbed functional group, and negatively related to trophic level. The eastern Chukchi Sea was most sensitive to perturbations to benthic invertebrate groups, the eastern Bering Sea was most sensitive to shrimp and walleye pollock, and the Gulf of Alaska was most sensitive to shrimps, pelagic forage fish, and zooplankton. Recovery time to perturbations were generally less than 5 years in all three ecosystems. The recovery times when fish groups were perturbed were generally longer than when benthic invertebrates were perturbed, and recovery times were shortest when it was pelagic invertebrates. The single model ensemble approach produced simulation results that described a range of possible outcomes to the prescribed perturbations and provided a sense for how robust the results are to parameter uncertainty.

Author(s): Gilligan‐Lunda, Erin K., Daniel S. Stich, Katherine E. Mills, Michael M. Bailey, and Joseph D. Zydlewski

Project PI: Stich
DOI: https://doi.org/10.1002/tafs.10299

American Shad Alosa sapidissima is an anadromous species with populations ranging along the U.S. Atlantic coast. Past American Shad stock assessments have been data limited and estimating system-specific growth parameters or instantaneous natural mortality (M) was not possible. This precluded system-specific stock assessment and management due to reliance on these parameters for estimating other population dynamics (such as yield per recruit). Furthermore, climate-informed biological reference points remain a largely unaddressed need in American Shad stock assessment. Population abundance estimates of American Shad and other species often rely heavily on M derived from von Bertalanffy growth function (VBGF) parameters. Therefore, we developed Bayesian hierarchical models to estimate coastwide, regional, and system-specific VBGF parameters and M using data collected from 1982 to 2017. We tested predictive performance of models that included effects of various climate variables on VBGF parameters within these models. System-specific models were better supported than regional or coast-wide models. Mean asymptotic length (L∞) decreased with increasing mean annual sea surface temperature (SST) and degree days (DD) experienced by fish during their lifetime. Although uncertain, K (Brody growth coefficient) decreased over the same range of lifetime SST and DD. Assuming no adaptation, we projected changes in VBGF parameters and M through 2099 using modeled SST from two climate projection scenarios (Representative Concentration Pathways 4.5 and 8.5). We predicted reduced growth under both scenarios, and M was projected to increase by about 0.10. It is unclear how reduced growth and increased mortality may influence population productivity or life history adaptation in the future, but our results may inform stock assessment models to assess those trade-offs.