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Accounting for uncertainty in marine reserve design.
Halpern, Benjamin S; Regan, Helen M; Possingham, Hugh P; McCarthy, Michael A.
Afiliação
  • Halpern BS; National Center for Ecological Analysis and Synthesis, 735 State St., Santa Barbara, CA 93101, USA. halpern@nceas.ucsb.edu
Ecol Lett ; 9(1): 2-11; discussion 11-4, 2006 Jan.
Article em En | MEDLINE | ID: mdl-16958861
ABSTRACT
Ecosystems and the species and communities within them are highly complex systems that defy predictions with any degree of certainty. Managing and conserving these systems in the face of uncertainty remains a daunting challenge, particularly with respect to developing networks of marine reserves. Here we review several modelling frameworks that explicitly acknowledge and incorporate uncertainty, and then use these methods to evaluate reserve spacing rules given increasing levels of uncertainty about larval dispersal distances. Our approach finds similar spacing rules as have been proposed elsewhere - roughly 20-200 km - but highlights several advantages provided by uncertainty modelling over more traditional approaches to developing these estimates. In particular, we argue that uncertainty modelling can allow for (1) an evaluation of the risk associated with any decision based on the assumed uncertainty; (2) a method for quantifying the costs and benefits of reducing uncertainty; and (3) a useful tool for communicating to stakeholders the challenges in managing highly uncertain systems. We also argue that incorporating rather than avoiding uncertainty will increase the chances of successfully achieving conservation and management goals.
Assuntos
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Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Conservação dos Recursos Naturais / Incerteza / Modelos Biológicos Tipo de estudo: Prognostic_studies Idioma: En Revista: Ecol Lett Ano de publicação: 2006 Tipo de documento: Article País de afiliação: Estados Unidos
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Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Conservação dos Recursos Naturais / Incerteza / Modelos Biológicos Tipo de estudo: Prognostic_studies Idioma: En Revista: Ecol Lett Ano de publicação: 2006 Tipo de documento: Article País de afiliação: Estados Unidos