A Management Strategy Evaluation for Transboundary Sablefish in the Northeast Pacific Ocean

Abstract

Fisheries assessment science has long concerned itself about the incorporation of spatial stock structure into the development, testing and deployment of management strategies. The population dynamics of a stock may not match static political boundaries due to migration, ontogenetic changes in demography, and spatially varying exploitation. Correctly specifying spatial structure can reduce bias in management quantities to a greater degree than correcting other parameters or population processes. While the value of developing spatially-structured assessment models is well recognized, there are many barriers to implementation, including the cost of collecting and evaluating datasets at the appropriate spatial resolution to determine how such assessments should be structured. The management strategy evaluation (MSE) approach enables scientists to test how various spatial assessment configurations might impact management performance, before moving to tactical implementation. Sablefish (Anoplopoma fimbria) of the northeast Pacific support a highly mobile, valuable fishery resource worth over $112 million USD. At the federal level, sablefish in this region are currently managed as three separate populations (Alaska, British Columbia and the US West Coast) by the National Oceanic and Atmospheric Administration (NOAA-US) and the Department of Fisheries and Oceans (DFO – Canada). Recent work has shown sablefish to be genetically mixed across the range, tagging studies confirm high movement rates and there is range wide synchrony in biomass trends, including declines during the last decade. These observations have led scientists and managers to consider whether evaluating the stock as a spatially structured population might reveal transboundary dynamics, and/or preclude poor management outcomes at the regional scale. An investigation of growth rates throughout the northeast Pacific revealed roughly four regions of distinct sablefish growth. These regions correspond with large oceanographic features that characterize large marine ecosystems (LME). A spatially structured statistical catch-at-age model, conditioned to historical catch, discard, survey and age-composition data from the three management regions suggested that the data can be plausibly fit as a spatially structured population, and corroborated other investigations indicating that LMEs delineate sablefish spawning populations within each management area. An MSE including estimation methods across a gradient of spatial complexity revealed that spatial models of intermediate structural complexity, including those that match the current paradigm in terms of having three modeled areas, can satisfy stakeholder objectives and avoid negative outcomes for the sablefish fishery. The MSE tool built for this dissertation can be used to evaluate management performance in the context of climate-induced changes to reproduction, alternative structural hypotheses, or changes to fleet dynamics.