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Type: Artigo
Title: Predicting species distribution from fishers’ local ecological knowledge: a new alternative for data-poor management
Author: Lopes, Priscila F. M.
Verba, Júlia T.
Begossi, Alpina
Pennino, Maria Grazia
Abstract: Many developing countries lack information to manage their endangered species, urging the need for affordable and reliable information. We used Bayesian hierarchical spatial models, with oceanographic variables, to predict the distribution range of Epinephelus marginatus, the dusky grouper, for the entire Southwest Atlantic. We ran a model using scientific information gathered from the literature and another using information gathered from fishers on species presence or absence. In both models, temperature was an important determinant of species occurrence. The predicted occurrence of the dusky grouper overlapped widely (Schoener’s D = 0.71; Warren’s I = 0.91) between the models, despite small differences on the southern and northern extremes of the distribution. These results suggest that basic information provided by fishers on species occurrence in their area can be reliable enough to predict species occurrence over large scales and can be potentially useful for marine spatial planning. Fishers’ knowledge may be an even more viable alternative to data collection than what was previously thought, for countries that both struggle with financial limitations and have urgent conservation needs
Subject: Conhecimento ecológico local
Country: Canadá
Editor: Canadian Science
Rights: Fechado
Identifier DOI: 10.1139/cjfas-2018-0148
Date Issue: 2019
Appears in Collections:NEPA - Artigos e Outros Documentos

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