Maia Kapur, UW School of Aquatic and Fisheries Sciences Alum

ABSTRACT TBD

James Faulkner, NOAA Northwest Fisheries Science Center

ABSTRACT TBD

Michael Kinneen, University of Washington

ABSTRACT TBD

Andre Punt, University of Washington

Natural mortality (M) is a key parameter in age- and size-structured methods of fish stock assessment because estimates of biomass in absolute terms and relative to reference points are sensitive to its value. M can be pre-specified based on “indirect” methods, estimated with a prior, and estimated without a prior. However, there is an absence of best practice guidelines for how to treat M within stock assessments. Five alternative broad categories of methods for treating M in stock assessments (unconstrained estimation, estimation with a prior, the “lowest plausible” and “highest plausible” values based on indirect methods, and the results of the Hamel-Amax indirect method) are compared for ten stocks in Australia’s Southern and Eastern Scalefish and Shark Fishery using likelihood profiles, retrospective analyses and hindcast skill. There is no method that performs best in all cases. The results support a best practice where estimation with a prior should be the default unless diagnostics suggest that the population dynamics or the observation model is clearly mis-specified (e.g., an estimate of M that differs markedly from the mean of a prior based on longevity information). It is also best practice to conduct sensitivity analyses and use decision tables to highlight the effects of incorrectly assumed values of M when mis-specification is suspected and M is pre-specified using a longevity-based method.

Caitlin Stern, Alaska Department of Fish and Game

Indices of abundance are key inputs to stock assessment models, influencing model outputs that shape fisheries management decisions. Design-based methods for producing these indices from fishery-independent surveys come with potential drawbacks, including highly variable estimates when spatial dependence in survey catch is present yet excluded from calculations, and biased results when survey sampling deviates from survey design. Implications for stock assessment models include the potential for better predictive ability when using model-based rather than design-based indices. The stock assessment for red king crab (Paralithodes camtschaticus) in Norton Sound, Alaska, uses design-based indices of abundance based on three fishery-independent surveys. These surveys cover different years and areas, and within a survey the locations sampled sometimes varies among years, suggesting a need for spatiotemporal standardization to improve abundance estimation. Here, I evaluate the effects on key outputs of the stock assessment model of using design-based survey indices versus a spatiotemporally standardized model-based index of abundance. Fits to size composition data were similar for models using design-based versus model-based indices, while fits to standardized fishery catch per unit effort indices were poorer for models using model-based indices. Retrospective patterns were less extreme for models using the spatiotemporal model-based index, indicating an improved ability to predict stock biomass in the terminal year. The estimated scale of the population was lower across the time series when using the model-based index. While estimated stock status was comparable or higher when using the spatiotemporal model-based index, model-estimated abundance was reduced, as was recommended harvest.