Identifying Conservation Leverage Points in a Fishery System Facing Practical Constraints on the Scale of Management

Spatial complexity is a common feature of marine fish populations that is often ignored in fisheries stock assessment and management. The rationale for assuming homogeneity of spatially structured populations is anchored in uncertainty about mechanisms governing population structure (e.g., dispersal rates, local population density, and life history variation), and extends to questions of data sufficiency for conducting spatially structured stock assessments. In this study, we develop a closed-loop simulation approach to evaluate how mis-matches between the spatial scales of fisheries management and fish population dynamics lead to management failures. Existing studies indicate that such a mis-match may lead to over-harvesting of the least productive sub-populations, and erode the spatial complexity that is believed to contribute to population resilience and persistence. However, these evaluations make simplifying assumptions about the spatial dynamics of fish populations, fisheries, or both, which makes it difficult to draw broad conclusions about the need for fine-scale fisheries management.

 Our modelling approach involves two main components. First, we develop an operating model that simulates the spatial and temporal responses of multiple fish populations and fisheries to management regulations. The second component is a management procedure that determines annual total allowable catch limits based on survey data, stock assessment analyses, and a harvest control rule. A key assumption of the management procedure is that the fish population is a single, homogeneous stock. We test the management procedure against three operating model scenarios for fish population structure: (1) multiple, discrete subpopulations that are each closed to immigration and emigration; and (2) multiple migratory populations that are fully mixed by a high rate of adult dispersal. The spatial dynamics of the fishery are determined by an ideal-free distribution, where the fishery responds rapidly to changes in sub-population biomass so that profitability is equalized among harvesting sites. A key feature of this model is that it allows profitability thresholds to drive the spatial dynamics of the fishery. We show that the least productive population components are protected from harvesting under moderate- to high-profit fishery scenarios. We demonstrate that high connectivity increases the productivity and profitability of fishing local populations, and yields relatively higher harvest rates on the population as a whole. Therefore, reconciling the spatial scales of assessment and population dynamics does not guarantee management success. Efforts to conserve spatially structured populations should focus on refining the scale of management control.