Biologically representative and well-connected marine reserves enhance biodiversity persistence in conservation planning
Other text in scientific journal, 2018

Current methods in conservation planning for promoting the persistence of biodiversity typically focus on either representing species geographic distributions or maintaining connectivity between reserves, but rarely both, and take a focal species, rather than a multispecies, approach. Here, we link prioritization methods with population models to explore the impact of integrating both representation and connectivity into conservation planning for species persistence. Using data on 288 Mediterranean fish species with varying conservation requirements, we show that: (1) considering both representation and connectivity objectives provides the best strategy for enhanced biodiversity persistence and (2) connectivity objectives were fundamental to enhancing persistence of small-ranged species, which are most in need of conservation, while the representation objective benefited only wide-ranging species. Our approach provides a more comprehensive appraisal of planning applications than approaches focusing on either representation or connectivity, and will hopefully contribute to build more effective reserve networks for the persistence of biodiversity.

spatial planning

marine reserve design

spatial prioritization

marine protected areas

larval dispersal

biodiversity conservation


Rafael A. Magris

University of Victoria

Ministry of Environment of Brazil

James Cook University

Marco Andrello

University of Montpellier

Robert L. Pressey

James Cook University

David Mouillot

University of Montpellier

James Cook University

Alicia Dalongeville

University of Montpellier

Martin Nilsson Jacobi

Chalmers, Space, Earth and Environment, Physical Resource Theory

Stephanie Manel

University of Montpellier

Conservation Letters

1755-263X (ISSN)

Vol. 11 4 UNSP e12439

Subject Categories

Other Computer and Information Science

Landscape Architecture

Bioinformatics (Computational Biology)



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