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Management performance of five alternative stock assessment methods wasevaluated by using them to set harvest levels targeting multi-species maximumyield in a multi-species flatfish fishery, including single-species andhierarchical multi-species models, and methods that pooled data across speciesand spatial strata, with catch outcomes of each method under three datascenarios compared to catch under an omniscient manager simulation. Operatingmodels included technical interactions between species intended to producechoke effects often observed in output controlled multi-species fisheries.Hierarchical multi-species models outperformed all other methods underdata-poor and data-moderate scenarios, and outperformed single-species modelsunder the data-rich scenario. Hierarchical models were least sensitive to priorprecision, sometimes improving in performance when prior precision was reduced.Choke effects were found to both positive and negative effects, sometimesleading to underfishing of non-choke species, but at other times preventingoverfishing of non-choke species. We highlight the importance of includingtechnical interactions in multi-species assessment models and managementobjectives, how choke species can indicate mismatches between managementobjectives and system dynamics, and recommend hierarchical multi-species modelsfor multi-species fishery management systems.

Hierarchical stock assessment methods improve management performance in multi-species, data-limited fisheries