Sensitivity of multispecies statistical catch-at-age models to inclusion of annual recruitment deviations as random effects and diet estimation

Grant Adams1
1SAFS
January 29th, 2019 9:00 (PST): FSH 203

Sensitivity of multispecies statistical catch-at-age models to inclusion of annual recruitment deviations as random effects and diet estimation

The development of analytical tools that address ecosystem based fisheries management (EBFM) needs is essential for rationally managing fisheries resources in the face of changing climate and ecological processes. Multispecies statistical catch-at-age (MSCAA) models are one tool of particular value for providing both tactical and strategic EBFM advice by accounting for trade-offs among fisheries for multiple species. MSCAA links multiple single-species age-structured models via predator-prey interactions conditioned on bioenergetics and diet information. Within MSCAA models, annual recruitment are commonly estimated as deviations away from a mean process and predator-prey interactions conditioned on predator-prey suitability. For most MSCAA models, penalized likelihood approaches have been used to constrain recruitment deviations away from zero and suitability assumed to be known. Such an approach requires the a priori selection of recruitment variance and limit uncertainty in predation mortality. However, this can limit our understanding of the variation in recruitment and extent of predation and may also have an impact on estimates of biological reference points. Alternatively, recruitment deviations can be treated as random effects and suitability estimated., allowing for the estimation of variance terms and annual predation mortality. Using a MSCAA developed for groundfish in the Bering Sea (CEATTLE for climate-enhanced, age-based model with temperature-specific trophic linkages and energetics), I evaluate the sensitivity of MSCAA models to the incorporation of annual recruitment deviations as random effects and suitability estimation. This research addresses the need for a greater understanding of parameter uncertainty in MSCAA models prior to further implementation in fisheries management.

Posted in Fisheries Think Tank.

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