‘Drivin' with your eyes closed’: Results from an international, blinded simulation experiment to evaluate spatial stock assessments

作者：Daniel R. Goethel, Aaron M. Berger, Simon Hoyle, Patrick D. Lynch, Caren Barceló, Jonathan J. Deroba, Nicholas D. Ducharme‐Barth, Alistair Dunn, Dan Fu, Francisco Izquierdo, Craig Marsh, Haikun Xu, Giancarlo M. Correa, Brian J. Langseth, Mark N. Maunder, Jeremy R. McKenzie, Richard D. Methot, Matthew T. Vincent, Teresa A’mar, Massimiliano Cardinale, Marta Cousido‐Rocha, Nick Davies, John Hampton, Carolina V. Minte‐Vera, Agurtzane Urtizberea · 发表于：Fish and Fisheries · 年份：2024 · DOI：10.1111/faf.12819 · 被引用次数：14 · 研究领域：Marine and fisheries research、Marine Bivalve and Aquaculture Studies、Coral and Marine Ecosystems Studies

Abstract Spatial models enable understanding potential redistribution of marine resources associated with ecosystem drivers and climate change. Stock assessment platforms can incorporate spatial processes, but have not been widely implemented or simulation tested. To address this research gap, an international simulation experiment was organized. The study design was blinded to replicate uncertainty similar to a real‐world stock assessment process, and a data‐conditioned, high‐resolution operating model (OM) was used to emulate the spatial dynamics and data for Indian Ocean yellowfin tuna ( Thunnus albacares ). Six analyst groups developed both single‐region and spatial stock assessment models using an assessment platform of their choice, and then applied each model to the simulated data. Results indicated that across all spatial structures and platforms, assessments were able to adequately recreate the population trends from the OM. Additionally, spatial models were able to estimate regional population trends that generally reflected the true dynamics from the OM, particularly for the regions with higher biomass and fishing pressure. However, a consistent population biomass scaling pattern emerged, where spatial models estimated higher population scale than single‐region models within a given assessment platform. Balancing parsimony and complexity trade‐offs were difficult, but adequate complexity in spatial parametrizations (e.g., allowing time‐ and age‐variation in movemen...