Evaluating fisheries conservation strategies in the socio-ecological system: A grid-based dynamic model to link spatial conservation prioritization tools with tactical fisheries management.

ABSTRACT: Spatial conservation prioritization concerns trade-offs between marine conservation and resource exploitation. This approach has been increasingly used to devise spatial management strategies for fisheries because of its simplicity in the optimization model and less data requirement compared to complex dynamic models. However, most of the prioritization is based on static models or algorithms; whose solutions need to be evaluated in a dynamic approach, considering the high uncertainty and opportunity costs associated with their implementation. We developed a framework that integrates species distribution models, spatial conservation prioritization tools and a general grid-based dynamic model (Grid-DM) to support evaluation of ecological and economic trade-offs of candidate conservation plans. The Grid-DM is spatially explicit and has a tactical management focus on single species. We applied the Grid-DM to small yellow croaker (Larimichthys polyactis) in Haizhou Bay, China and validated its spatial and temporal performances against historical observations. It was linked to a spatial conservation prioritization tool Marxan to illustrate how the model can be used for conservation strategy evaluation. The simulation model demonstrated effectiveness in capturing the spatio-temporal dynamics of the target fishery as well as the socio-ecological effects of conservation measures. We conclude that the model has the capability and flexibility to address various forms of uncertainties, simulate the dynamics of a targeted fishery, and to evaluate biological and socioeconomic impacts of management plans. The modelling platform can further inform scientists and policy makers of management alternatives screening and adaptive conservation planning.

SUBMITTER: Li Y 

PROVIDER: S-EPMC7122822 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature