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Biological Conservation
Volume 266, 2022, 109469

Using movement models and systematic conservation planning to inform marine protected area design for a multi-species predator community

Maurits P.M. van Zinnicq Bergmanna,b, Tristan L. Guttridgeb,c, Matthew J. Smukallb,d, Vanessa M. Adamse

Institute of Environment, Department of Biological Sciences, Florida International University, North Miami, FL, United States.

Abstract

 Marine protected areas (MPAs) are increasingly applied to regulate fishing and conserve marine biodiversity. Yet, MPAs are often designed without sufficient ecological knowledge of the species they are intended to protect. This is particularly relevant to large and wide-ranging marine predators including many elasmobranchs (sharks and rays), for which region-specific space-use information is limited. Further, uncertainty remains in how to integrate movement datasets with systematic conservation planning frameworks to meet explicit conservation objectives. We addressed these knowledge gaps by combining movement models, constructed from passive acoustic telemetry data for eight elasmobranch species, and systematic conservation planning to investigate the design and adequacy of MPAs in Bimini, The Bahamas. Currently, there is a proposal for a no-take MPA in North Bimini (NBMPA), although it is unclear how this MPA would benefit elasmobranch communities if or when implemented. Our results show that although the NBMPA would contribute to elasmobranch conservation, the supplementation with an additional MPA southwest of Bimini would be necessary to protect important habitats for multiple elasmobranch species. This southwestern area was highlighted as a conservation priority area of both permanent MPA designs as well as seasonal time-area closures, regardless of NBMPA implementation status and conservation targets considered in this study. Our integrative approach also demonstrates its ability to optimize MPA designs for marine predator communities, combining multi-species movement models, constructed from acoustic telemetry datasets that include space-use estimates over multiple years, with MPA optimization tools.

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