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