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Owen Liu and colleagues projected future abundance and distribution of groundfish based on historic empirical data of fish densities, bottom temperature and dissolved oxygen Analysis focuses on a complex of 4 lower shelf/upper slope groundfish (sablefish, Dover sole, shortspine thornyhead, longspine thornyhead) Projections indicate species-specific changes in abundance and distributional responses; contrast shown here between sablefish (decrease and move into deeper water) and Dover sole (models disagree on abundance, relatively little change in depth)

These trends are tending to push some stocks to the margins of present-day fishing footprints for West Coast ports, which could lead to changes catch composition

Related work suggests that the effects of these types of changes will be felt most in groundfish fisheries in northern ports, and that distributional shifts will lead to future overlap between high densities of fish and areas slated for offshore wind energy development

Atlantis end to end model of the California Current, similar to models developed for most other regions of the US, and globally by Beth Fulton and team. Previous versions of this Atlantis model have been in use for over a decade. This newest version features several critical innovations that are now generating preliminary outputs. The key innovations (arrows) are: 1) forcing Atlantis with downscaled GLORYS + ESM ocean projections under climate change (thru a collaboration known as Future Seas, led by UCSC and SWFSC); 2) forcing groundfish distributions through climate-driven SDMs of groundfish + pelagics (e.g., from Liu et al in press, 1 slide ago); and 3) parameterizing fishing effort spatially to match empirical Fishing Footprints of key port groups

Preliminary results here just illustrate that we are projecting changes in biomass and distribution, which leads to port-level changes in catch of target species. For instance, in this example, four of our major target groundfish species generally shift north, and some ports experience a slight increase in catch under climate change relative to a no-climate change base case. However, some stocks also move deeper and offshore, beyond the ‘footprints’ of certain ports, leading to decreases in catch, which is what we observe for the northernmost ports at the top of the plot.

CEATTLE, developed by Kirstin Holsman at the Alaska Center, is a multispecies statistical catch-at-age assessment model that includes ecosystem considerations like bioenergetics and multispecies interactions (Holsman et al. applications in AK) or, in this case, multiple life-stage interactions.

Sophia Wassermann and colleagues have applied the model to study how temperature variability and cannibalism in Pacific hake interact to influence stock productivity. Adding cannibalism to the model leads to higher estimated recruitment and biomass, due to the inclusion of predation mortality, largely on age-1 hake.

This work is expected to be relevant to other highly cannibalistic hake stocks; additionally the NWFSC team welcomes input and advice from other examples where cannibalism has been included in assessments, such as for Northeast Arctic Cod.

We conducted a management strategy evaluation to assess the robustness of current and alternative Pacific sardine harvest control rules under a variety of recruitment scenarios representing potential projections of future climate conditions in the California Current. The current environmentally informed control rule modifies the harvest rate for the northern sardine subpopulation based on average sea surface temperatures measured during California Cooperative Oceanic Fisheries 24 Investigations (CalCOFI) field cruises. This rule prioritizes catch at intermediate biomass levels but may increase variability in catch and closure frequency compared to alternative control rules, especially if recruitment is unrelated to ocean temperatures. Fishing at maximum sustainable yield and using dynamically estimated reference points reduced the frequency of biomass falling below 150,000 mt by up to 17%, while using survey index-based biomass estimates resulted in a 29 14% higher risk of delayed fishery closure during stock declines than when using assessment based estimates.

Changing distribution and abundance of small pelagics may drive changes in predator distributions, affecting predator availability to fisheries and surveys. However, small pelagic fish are difficult to survey directly, so we developed a novel method of assessing small pelagic fish aggregate abundance via predator diet data. We used piscivore diet data collected from multiple bottom trawl surveys within a Vector Autoregressive Spatio-Temporal (VAST) model to assess trends of small pelagics on the Northeast US shelf. The goal was to develop a spatial “forage index” to inform survey and/or fishery availability in the bluefish (Pomatomus saltatrix) stock assessment. Using spring and fall surveys from 1973-2020, 20 small pelagic groups were identified as major bluefish prey using the diet data. Then, predators were grouped by diet similarity to identify 19 piscivore species with the most similar diet to bluefish in the region. Diets from all 20 piscivores were combined for the 20 prey groups at each surveyed location, and the total weight of small pelagic prey per predator stomach at each location was input into a Poisson-link delta model to estimate expected prey mass per predator stomach. Best fit models included spatial and spatio-temporal random effects, with predator mean length, number of predator species, and sea surface temperature as catchability covariates. Spring and fall prey indices were split into inshore and offshore areas to reflect changing prey availability over time in areas available to the recreational fishery and the bottom trawl survey, and also to contribute to regional ecosystem reporting

Using NEFSC bottom trawl survey diet data from 1973-2021, 20 small pelagic groups were identified as major bluefish prey with 10 or more observations (in descending order of observations): Longfin squids (Doryteuthis formerly Loligo sp.), Anchovy family (Engraulidae), bay anchovy (Anchoa mitchilli), Atlantic butterfish, (Peprilus triachanthus), Cephalopoda, (Anchoa hepsetus), red eye round herring (Etrumeus teres), Sandlance (Ammodytes sp.), scup (Stenotomus chrysops), silver hake (Merluccius bilinearis), shortfin squids (Illex sp.), Atlantic herring (Clupea harengus), Herring family (Clupeidae), Bluefish (Pomatomus saltatrix), silver anchovy (Engraulis eurystole), longfin inshore squid (Doryteuthis pealeii), Atlantic mackerel (Scomber scombrus), flatfish (Pleuronectiformes), weakfish (Cynoscion regalis), and Atlantic menhaden (Brevoortia tyrannus).

Prey categories such as fish unidentified, Osteichthyes, and unidentified animal remains were not included in the prey list. Although unidentified fish and Osteichthyes can comprise a significant portion of bluefish stomach contents, we cannot assume that unidentified fish in other predator stomachs represent unidentified fish in bluefish stomachs.

Image credits: Striped and bay anchovy photo--Robert Aguilar, Smithsonian Environmental Research Center; redeye round herring photo--https://diveary.com ; sandlance photo--Virginia Institute of Marine Science; all others NOAA Fisheries.

WHAM is a state space stock assessment model framework: https://timjmiller.github.io/wham/

The Bigelow index fit with the fall forage fish index did not improve the model fit (AIC), was slightly worse fit and gave identical results The Albatross index fit with the fall forage fish index did not converge or hessian was not positive definite for any of the models (even when how = 0 for some of them). The MRIP index fit with the annual forage fish index did not converge or hessian was not positive definite for any of the models