CAFA Publications

Author(s): Smith JA, et al

Project PI: Jacox
DOI: https://doi.org/10.3389/fmars.2021.630607

Time-area closures are a valuable tool for mitigating fisheries bycatch. There is increasing recognition that dynamic closures, which have boundaries that vary across space and time, can be more effective than static closures at protecting mobile species in dynamic environments. We created a management strategy evaluation to compare static and dynamic closures in a simulated fishery based on the California drift gillnet swordfish fishery, with closures aimed at reducing bycatch of leatherback turtles. We tested eight operating models that varied swordfish and leatherback distributions, and within each evaluated the performance of three static and five dynamic closure strategies. We repeated this under 20 and 50% simulated observer coverage to alter the data available for closure creation. We found that static closures can be effective for reducing bycatch of species with more geographically associated distributions, but to avoid redistributing bycatch the static areas closed should be based on potential (not just observed) bycatch. Only dynamic closures were effective at reducing bycatch for more dynamic leatherback distributions, and they generally reduced bycatch risk more than they reduced target catch. Dynamic closures were less likely to redistribute fishing into rarely fished areas, by leaving open pockets of lower risk habitat, but these closures were often fragmented which would create practical challenges for fishers and managers and require a mobile fleet. Given our simulation’s catch rates, 20% observer coverage was sufficient to create useful closures and increasing coverage to 50% added only minor improvement in closure performance. Even strict static or dynamic closures reduced leatherback bycatch by only 30–50% per season, because the simulated leatherback distributions were broad and open areas contained considerable bycatch risk. Perfect knowledge of the leatherback distribution provided an additional 5–15% bycatch reduction over a dynamic closure with realistic predictive accuracy. This moderate level of bycatch reduction highlights the limitations of redistributing fishing effort to reduce bycatch of broadly distributed and rarely encountered species, and indicates that, for these species, spatial management may work best when used with other bycatch mitigation approaches. We recommend future research explores methods for considering model uncertainty in the spatial and temporal resolution of dynamic closures.

Author(s): Tommasi, Desiree, et al

Project PI: Jacox
DOI: https://doi.org/10.3389/fmars.2021.624161

One of the significant challenges to using information and ideas generated through ecosystem models and analyses for ecosystem-based fisheries management is the disconnect between modeling and management needs. Here we present a case study from the U.S. West Coast, the stakeholder review of NOAA’s annual ecosystem status report for the California Current Ecosystem established by the Pacific Fisheries Management Council’s Fisheries Ecosystem Plan, showcasing a process to identify management priorities that require information from ecosystem models and analyses. We then assess potential ecosystem models and analyses that could help address the identified policy concerns. We screened stakeholder comments and found 17 comments highlighting the need for ecosystem-level synthesis. Policy needs for ecosystem science included: (1) assessment of how the environment affects productivity of target species to improve forecasts of biomass and reference points required for setting harvest limits, (2) assessment of shifts in the spatial distribution of target stocks and protected species to anticipate changes in availability and the potential for interactions between target and protected species, (3) identification of trophic interactions to better assess tradeoffs in the management of forage species between the diet needs of dependent predators, the resilience of fishing communities, and maintenance of the forage species themselves, and (4) synthesis of how the environment affects efficiency and profitability in fishing communities, either directly via extreme events (e.g., storms) or indirectly via climate-driven changes in target species availability. We conclude by exemplifying an existing management process established on the U.S. West Coast that could be used to enable the structured, iterative, and interactive communication between managers, stakeholders, and modelers that is key to refining existing ecosystem models and analyses for management use.

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.

Author(s): Chen, C., Zhao, L., Gallager, S., Ji, R., He, P., Davis, C. S., Beardsley, R.C., Hart, D., Gentleman, W.C., Wang, L., Li, S., Lin, H., Stokesbury, K., Bethoney, D.

Project PI: Ji/David/Rubao
DOI: https://doi.org/10.1016/j.pocean.2021.102604

Sea scallops (Placopecten magellanicus) are a highly fecund species that supports one of the most commercially valuable fisheries in the northeast U.S. continental shelf region. Scallop landings exhibit significant interannual variability, with abundances widely varied due to a combination of anthropogenic and natural factors. By coupling a pelagic-stage Individual-Based scallop population dynamics Model (hereafter referred to as Scallop-IBM) with the Northeast Coastal Ocean Forecast System (NECOFS) and considering the persistent aggregations over Georges Bank (GB)/Great South Channel (GSC) as source beds, we have examined the dispersion and settlement of scallop larvae over 1978–2016. The results demonstrated that the significant interannual variability of larval dispersal was driven by biophysical interactions associated with scallop larval swimming behaviors in their early stages. The duration, frequency, and stimulus of larval vertical migration in the ocean mixed layer (OML) affected the residence time of larvae in the water column over GB. It thus sustained the persistent aggregations of scallops in the GB/GSC and Southern New England region. In addition to larval behavior in the OML, the larval transport to the Middle Atlantic Bight (MAB) was also closely related to the intensity and duration of northeasterly wind in autumn. There was no conspicuous connectivity of scallop larvae between GB/GSC and MAB in the past 39 years except in the autumn of 2009. In 2009, the significant larval transport to the MAB was produced by unusually strong northeasterly winds. Ignoring larval behavior in the OML could overestimate the scallop population’s connectivity between GB and the MAB and thus provide an unrealistic prediction of scallop larval recruitment in the region. Both satellite-derived SST and NECOFS show that the northeast U.S. shelf experienced climate change-induced warming. The extreme warming at the shelfbreak off GB tends to intensify the cross-isobath water temperature gradient and enhance the clockwise subtidal gyre over GB. This change can increase the larval retention rate over GB/GSC, facilitating enhanced productivity on GB.

Author(s): Fiechter, J., Buil, M.P., Jacox, M.G., Alexander, M.A. and Rose, K.A.

Project PI: Curchister
DOI: http://doi.org/10.3389/fmars.2021.685241

Predicting changes in the abundance and distribution of small pelagic fish species in response to anthropogenic climate forcing is of paramount importance due to the ecological and socioeconomic importance of these species, especially in eastern boundary current upwelling regions. Coastal upwelling systems are notorious for the wide range of spatial (from local to basin) and temporal (from days to decades) scales influencing their physical and biogeochemical environments and, thus, forage fish habitat. Bridging those scales can be achieved by using high-resolution regional models that integrate global climate forcing downscaled from coarser resolution earth system models. Here, “end-to-end” projections for 21st century sardine population dynamics and catch in the California Current system (CCS) are generated by coupling three dynamically downscaled earth system model solutions to an individual-based fish model and an agent-based fishing fleet model. Simulated sardine population biomass during 2000–2100 exhibits primarily low-frequency (decadal) variability, and a progressive poleward shift driven by thermal habitat preference. The magnitude of poleward displacement varies noticeably under lower and higher warming conditions (500 and 800 km, respectively). Following the redistribution of the sardine population, catch is projected to increase by 50–70% in the northern CCS and decrease by 30–70% in the southern and central CCS. However, the late-century increase in sardine abundance (and hence, catch) in the northern CCS exhibits a large ensemble spread and is not statistically identical across the three downscaled projections. Overall, the results illustrate the benefit of using dynamical downscaling from multiple earth system models as input to high-resolution regional end-to-end (“physics to fish”) models for projecting population responses of higher trophic organisms to global climate change.

Author(s): Frawley, T.H., Muhling, B.A., Brodie, S., Fisher, M.C., Tommasi, D., Le Fol, G., Hazen, E.L., Stohs, S.S., Finkbeiner, E.M. and Jacox, M.G.

Project PI: Curchister
DOI: http://doi.org/10.1111/faf.12519

Marine fisheries around the globe are increasingly exposed to external drivers of social and ecological change. Though diversification and flexibility have historically helped marine resource users negotiate risk and adversity, much of modern fisheries management treats fishermen as specialists using specific gear types to target specific species. Here, we describe the evolution of harvest portfolios amongst Pacific Northwest fishermen over 35+ years with explicit attention to changes in the structure and function of the albacore (Thunnus alalunga, Scombridae) troll and pole-and-line fishery. Our analysis indicates that recent social–ecological changes have had heterogenous impacts upon the livelihood strategies favoured by different segments of regional fishing fleets. As ecological change and regulatory reform have restricted access to a number of fisheries, many of the regional small (<45 ft) and medium (45–60 ft) boat fishermen who continue to pursue diverse livelihood strategies have increasingly relied upon the ability to opportunistically target albacore in coastal waters while retaining more of the value generated by such catch. In contrast, large vessels (>60 ft) targeting albacore are more specialized now than previously observed, even as participation in multiple fisheries has become increasingly common for this size class. In describing divergent trajectories associated with the albacore fishery, one of the US West Coast's last open-access fisheries, we highlight the diverse strategies and mechanisms utilized to sustain fisheries livelihoods in the modern era while arguing that alternative approaches to management and licensing may be required to maintain the viability of small-scale fishing operations worldwide moving forward.

Author(s): Kaplan, I.C., Gaichas, S.K., Stawitz, C.C., Lynch, P.D., Marshall, K.N., Deroba, J.J., Masi, M., Brodziak, J.K., Aydin, K.Y., Holsman, K. and Townsend, H

Project PI: Curchister
DOI: http:// https://doi.org/10.3389/fmars.2021.624355

Management strategy evaluation (MSE) is a simulation approach that serves as a “light on the hill” (Smith, 1994) to test options for marine management, monitoring, and assessment against simulated ecosystem and fishery dynamics, including uncertainty in ecological and fishery processes and observations. MSE has become a key method to evaluate trade-offs between management objectives and to communicate with decision makers. Here we describe how and why MSE is continuing to grow from a single species approach to one relevant to multi-species and ecosystem-based management. In particular, different ecosystem modeling approaches can fit within the MSE process to meet particular natural resource management needs. We present four case studies that illustrate how MSE is expanding to include ecosystem considerations and ecosystem models as ‘operating models’ (i.e., virtual test worlds), to simulate monitoring, assessment, and harvest control rules, and to evaluate tradeoffs via performance metrics. We highlight United States case studies related to fisheries regulations and climate, which support NOAA’s policy goals related to the Ecosystem Based Fishery Roadmap and Climate Science Strategy but vary in the complexity of population, ecosystem, and assessment representation. We emphasize methods, tool development, and lessons learned that are relevant beyond the United States, and the additional benefits relative to single-species MSE approaches.

Author(s): Cheng, Wei, A. Hermann, A. Hollowed, K. Holsman, K. Kearney, D. Pilcher, C. Stock, K. Aydin

Project PI: Hollowed
DOI: http://doi.org/10.1016/j.dsr2.2021.104975

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.

Author(s): Drenkard, E., C. Stock, A. Adcroft, M. Alexander, V. Balaji, S. J. Bograd, M. Butenschön, W. Cheng, E. Curchitser, E. Di Lorenzo, K. W. Dixon, R. Dussin, A. Haynie, M. Harrison, A. Hermann, A. Hollowed, K. Holsman, J. Holt, M. G. Jacox, C. Joo Jang, K. A. Kearney, B. A. Muhling, M. Pozo Buil, A. C. Ross, V. Saba, A. Britt Sandø, D. Tommasi, M. Wang.

Project PI: Hollowed
DOI: http://doi.org/10.1093/icesjms/fsab100

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.

Author(s): Essington, T. E., M. E. Matta, B. A. Black, T. E. Helser, P. D. Spencer.

Project PI: Hollowed
DOI: http://doi.org/10.1139/cjfas-2021-0046

Identifying changes in fish growth is important for accurate scientific advice used for fisheries management, because environmental change is affecting fish growth and size-at-age is a critical component of contemporary stock assessment methods. Growth-increment biochronologies are time series of growth-increments derived from hard parts of marine organisms that may reveal dynamics of somatic fish growth. Here we use time series of otolith increments of two fish stocks to fit and compare a biologically derived growth model and a generalized statistical model. Both models produced similar trajectories of annual growth trends, but the biologically based one was more precise and predicted smaller interannual fluctuations than the statistical model. The biologically based model strongly indicated covariance between anabolic and catabolic rates among individuals. Otolith size-at-age did not closely match fish length-at-age, and consequently the growth model could not accurately hindcast observed fish length-at-age. For these reasons, fitted growth dynamics from otolith biochronologies may best suited to identify growth rate fluctuations, understand past drivers of growth dynamics, and improve ecological forecast in the face of rapid environmental change.