Optimizing future networks of marine protected areas in response to global change by combining genetic connectivity and biophysical models

点击翻译按钮获取中文摘要

The conservation of marine biodiversity and the sustainability of fisheries are major global environmental and economic challenges. One management tool that addresses these concerns is the development of Marine Protected Areas (MPAs). Although MPAs can contribute to the management of fisheries, uncertainties remain about the optimal spatial design of MPAs that will maintain regional populations, especially since changes in fishing pressure and environmental conditions may both alter connectivity patterns. Given that the number of MPAs is likely to increase substantially, if parties committed to the Convention on Biological Diversity are to meet the target of protecting 10% of the world's oceans by 2020, it is becoming urgent to effectively measure and incorporate connectivity between populations in the selection of new MPAs within MPA networks. A reliable measure of connectivity should include both data about species dispersal capacity and genetic differen-tiation. However, at present, we still lack the large-scale genetic data and dispersal models necessary to define optimal spatial design of MPAs, and evaluate the effects of climate change. In this project, we combine biophysical oceanographic models, network connectivity models, genetic-demographic models and genomic tools to: (i) estimate genetic connectivity for four exploited species (three fishes, one invertebrate) in two regions where MPAs networks are established; and (ii) compare alternative scenarios of potential impacts of future climate change and fishing pressure on genetic connectivity.