Models and indicators for assessing conservation and fisheries-related effects of marine protected areas
|Author(s)||Pelletier Dominique1, Claudet Joachim2, 3, Ferraris J4, Benedetti Cecchi L5, Garcia Charton J6|
|Affiliation(s)||1 : IFREMER, Dept Ecol & Modeles Halieut, Inst Francais Rech Exploitat Mer, F-44311 Nantes 03, France.
2 : Univ Perpignan, EPHE, CNRS, UMR 5244, F-66860 Perpignan, France.
3 : Univ Salento, Dept Biol & Environm Sci & Technol, I-73100 Lecce, Italy.
4 : Univ Perpignan, IRD UR CoReUs, F-66860 Perpignan, France.
5 : Univ Pisa, Dipartimento Fis Uomo & Ambiente, I-56126 Pisa, Italy.
6 : Univ Murcia, Dept Ecol & Hidrol, E-30100 Murcia, Spain.
|Source||Canadian journal of fisheries and aquatic sciences (0706-652X) (NRC), 2008-04 , Vol. 65 , N. 4 , P. 765-779|
|WOS© Times Cited||46|
|Keyword(s)||ecosystem conservation, fisheries management, modelling, indicators, Marine Protected Areas|
|Abstract||Two kinds of approaches have been used for assessing conservation and fisheries-related effects of marine protected areas (MPAs): (i) statistical modelling based on field data and (ii) mathematical modelling quantifying the consequences of MPAs on the dynamics of populations, communities, and fisheries. Statistical models provide a diagnostic on the impact of MPAs on the ecosystem and resources; they are also needed for devising and assessing sampling designs for monitoring programs. Dynamic models enable exploration of the consequences of MPA designs and other management policies. We briefly review how each of these approaches has been implemented up to now in the literature and identify potential indicators of MPA effects that can be obtained from each approach to provide scientific advice for managers. Methodological gaps that impede the assessment of MPA effects and the construction of appropriate indicators are then discussed, and recent developments in this respect are presented. We finally propose ways to reconcile the two approaches based on their complementarity to derive suitable indicators to support decision making. In this respect, we suggest in addition that MPA managers should be associated from the beginning to the design and construction of indicators.|