Spatial awareness: Good practices and pragmatic recommendations for developing spatially structured stock assessments

Spatial population structure is a fundamental aspect of marine populations, yet it rarely incorporated in stock assessment models. The unit assumption, common feature many assessments, an axiom the single-species modeling convention, which developed mid-20th century when spatial resolution fishery data was coarse and uncertain, computing power limited, impact biocomplexity on sustainable harvest levels not well understood. Despite rapid advances along all these research fronts 21st century, assessments remain utilized as basis management decision-making. A potential hindrance to broader utilization lack guidance how choose appropriate framework for given application. Thus, we review types models available, summarize options parameterize structure, offer promote development candidate application procedures, provide pragmatic guide choosing model observed limitations, concerns. should match unit(s) interdisciplinary identification adequately represent within unit, simultaneously multiple interacting units, appropriate, outputs managers that can be used prevent local depletion spawning populations. As permits, higher intra-population addressed increase homogeneity modeled while connectivity among units may also explicitly incorporated. Small sample sizes limit applications, but incorporating novel sources parameterizing efficiently (e.g., sharing parameters implementing habitat preference functions improve movement dynamics, including autocorrelation) resolve some practical constraints. Management strategy evaluation more widely identify minimally complex procedures robust advice, imprecision weighed against inherent bias spatially aggregated assessments.