In addition to fostering biodiversity goals, marine protected area (MPA) implementation has economic consequences for both commercial and recreational fisheries. During the implementation of the State of California (USA) Marine Life Protection Act (MLPA), which mandates the creation of an MPA network in California's state waters, the stakeholders and policymakers utilized a pair of economic analyses that addressed these considerations. One was a comparative, static assessment of short-term, " worst case" potential socioeconomic impacts to important fisheries based on surveys of local fishermen. This analysis made no assumptions about fishery management outside of MPAs, assumed no spillover of fish from MPAs into fished areas or reallocation of fishing effort, and estimated the maximum potential dollar-value economic impacts over a short time scale. The other was a dynamic, bioeconomic assessment of the changes in spatial distribution of biomass and catch, based on published biological parameter values, oceanographic models of larval connectivity, and a range of possible levels of fishing. This analysis explicitly accounted for fish population dynamics, spillover, fisher movement, and fishery management outside of the MPAs, but was limited to long-term, equilibrium-based results because of a lack of baseline abundance data. Both evaluation methods were novel in their spatial resolution and their use directly in an MPA design process, rather than after implementation. The two methods produced broadly similar (at a regional spatial scale) evaluations of the likely effects of proposed MPAs on fisheries, at least when the bioeconomic model assumed fishery management was conservative. Our experience with these analyses in the MLPA Initiative process led to several suggestions for future MPA design efforts: (i) since the change in fish biomass inside MPAs partly depends on fisheries management outside of them, it is useful to integrate or coordinate conventional fishery management and MPA planning efforts; (ii) integrate modeling assessments early into MPA design, as part of a post-implementation adaptive management approach; and (iii) integrate empirical fishery data into bioeconomic models in order to improve representations of human behavior and short-term forecasts of changes in fished populations. © 2012 Elsevier Ltd.
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