%0 Journal Article %T Marine Protected Area Networks: Assessing Whether the Whole Is Greater than the Sum of Its Parts %+ Department of Integrative Biology %+ Laboratoire d'Excellence CORAIL (LabEX CORAIL) %+ Humboldt State University Marine Laboratory (HSU Marine Lab) %+ Marine Science Institute %+ Department of Ecology and Evolutionary Biology (University of California Santa Cruz) %+ Great Barrier Reef Marine Park Authority (GBRMPA) %+ Department of Biology %+ Centre de recherches insulaires et observatoire de l'environnement (CRIOBE) %+ Institute of Marine Sciences %+ Division of Aquatic Resources %A Grorud-Colvert, Kirsten %A Claudet, Joachim %A Tissot, Brian N. %A Caselle, Jennifer E. %A Carr, Mark H. %A Day, Jon C. %A Friedlander, Alan M. %A Lester, Sarah E. %A Loma, Thierry Lison De %A Malone, Daniel %A Walsh, William J. %< avec comité de lecture %@ 1932-6203 %J PLoS ONE %I Public Library of Science %8 2014-08-01 %D 2014 %R 10.1371/journal.pone.0102298 %K Conservation science %K Marine conservation %K Marine fish %K Marine ecology %K Marine ecosystems %K Marine monitoring %K Ecological economics %K Marine biology %Z Life Sciences [q-bio]/Ecology, environment %Z Environmental Sciences/Environmental EngineeringJournal articles %X Anthropogenic impacts are increasingly affecting the world's oceans. Networks of marine protected areas (MPAs) provide an option for increasing the ecological and economic benefits often provided by single MPAs. It is vital to empirically assess the effects of MPA networks and to prioritize the monitoring data necessary to explain those effects. We summarize the types of MPA networks based on their intended management outcomes and illustrate a framework for evaluating whether a connectivity network is providing an outcome greater than the sum of individual MPA effects. We use an analysis of an MPA network in Hawai'i to compare networked MPAs to non-networked MPAs to demonstrate results consistent with a network effect. We assert that planning processes for MPA networks should identify their intended outcomes while also employing coupled field monitoring-simulation modeling approaches, a powerful way to prioritize the most relevant monitoring data for empirically assessing MPA network performance. %G English %2 https://univ-perp.hal.science/hal-01341695/document %2 https://univ-perp.hal.science/hal-01341695/file/journal.pone.0102298.PDF %L hal-01341695 %U https://univ-perp.hal.science/hal-01341695 %~ IRD %~ SDE %~ EPHE %~ UNIV-AG %~ AFRIQ %~ CNRS %~ UNIV-PERP %~ UNIV-NC %~ EHESS %~ IFREMER %~ GIP-BE %~ AGROPOLIS %~ CRIOBE %~ PSL %~ UNIV-POLYNESIE %~ UPF %~ TEST-DEV %~ UNC %~ EPHE-PSL %~ EHESS-PSL %~ LABEX-CORAIL %~ PUNC-UNC %~ LARJE-PUNC-UNC %~ LA-NI-PUNC-UNC %~ CRESICA-PUNC-UNC %~ LIRE-PUNC-UNC %~ RESONANCES-PUNC-UNC