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Trade-offs between spatial temporal closures and effort reduction measures to ensure fisheries sustainability
Overexploitation has led to large scale declines in many fish stocks around the world with the 2030 United Nations agenda calling for more spatial management tools to achieve sustainability targets. However, without spatially explicit consideration of fisheries dynamics, assessment of management measures combining spatial temporal closures and effort reduction measures remain limited. This is particularly true when balancing population biomass recovery goals and their socioeconomic consequences. Using ISIS-Fish, the first spatially explicit bioeconomic model describing hake (Merluccius merluccius) fisheries in the Gulf of Lion, Mediterranean Sea, we investigated the consequences of individual spatial temporal closures and spatial closure network effects with all-at-one and gradual effort reduction measures. Their effectiveness in restoring the collapsed population and economic objectives were quantified to identify measures best suited for rebuilding population biomass, increasing catch weight, and maintaining revenue levels. While severe effort reduction was more effective in achieving population recovery goals than spatial temporal closures, these scenarios did not lead to an increase in catches until after five years. In contrast, spatial temporal closures failed to reach population recovery goals at any point during the simulation period, but impacted revenues the least. Simulated effort redistribution also led to greater depletion of juvenile hake, a pattern common elsewhere in the world. The present study illustrates how robust spatially explicit models may be used to evaluate the impacts of complex alternative management scenarios and to identify tradeoffs between biomass recovery, fishery viability, and the management equitability (and acceptability) between fishing fleets.
Keyword(s)
Marine resource management evaluation tools, Demersal mixed fisheries, Marine spatial closures, Spatial fleet dynamics, Fisheries bioeconomic modeling