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Trait-based indicators of bird species sensitivity to habitat loss are effective within but not across data sets.
Hatfield, Jack H; Orme, C David L; Tobias, Joseph A; Banks-Leite, Cristina.
Afiliação
  • Hatfield JH; Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, SL5 7PY, United Kingdom.
  • Orme CDL; Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, SL5 7PY, United Kingdom.
  • Tobias JA; Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, SL5 7PY, United Kingdom.
  • Banks-Leite C; Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, SL5 7PY, United Kingdom.
Ecol Appl ; 28(1): 28-34, 2018 01.
Article em En | MEDLINE | ID: mdl-29083522
Species' traits have been widely championed as the key to predicting which species are most threatened by habitat loss, yet previous work has failed to detect trends that are consistent enough to guide large-scale conservation and management. Here we explore whether traits and environmental variables predict species sensitivity to habitat loss across two data sets generated by independent avifaunal studies in the Atlantic Forest of Brazil, both of which detected a similar assemblage of species, and similar species-specific responses to habitat change, across an overlapping sample of sites. Specifically, we tested whether 25 distributional, climatic, ecological, behavioral, and morphological variables predict sensitivity to habitat loss among 196 bird species, both within and across studies, and when data were analysed as occurrence or abundance. We found that four to nine variables showed high explanatory power within a single study or data set, but none performed as strong predictors across all data sets. Our results demonstrate that the use of species traits to predict sensitivity to anthropogenic habitat loss can produce predictions that are species- and site-specific and not scalable to whole regions or biomes, and thus should be used with caution.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aves / Ecossistema Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Animals País/Região como assunto: America do sul / Brasil Idioma: En Revista: Ecol Appl Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Reino Unido País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aves / Ecossistema Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Animals País/Região como assunto: America do sul / Brasil Idioma: En Revista: Ecol Appl Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Reino Unido País de publicação: Estados Unidos