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• W2079761956 endingPage "20140016" @default.
• W2079761956 startingPage "20140016" @default.
• W2079761956 abstract "In taxon-wide assessments of threat status many species remain not included owing to lack of data. Here, we present a novel spatial-phylogenetic statistical framework that uses a small set of readily available or derivable characteristics, including phylogenetically imputed body mass and remotely sensed human encroachment, to provide initial baseline predictions of threat status for data-deficient species. Applied to assessed mammal species worldwide, the approach effectively identifies threatened species and predicts the geographical variation in threat. For the 483 data-deficient species, the models predict highly elevated threat, with 69% ‘at-risk’ species in this set, compared with 22% among assessed species. This results in 331 additional potentially threatened mammals, with elevated conservation importance in rodents, bats and shrews, and countries like Colombia, Sulawesi and the Philippines. These findings demonstrate the future potential for combining phylogenies and remotely sensed data with species distributions to identify species and regions of conservation concern." @default.
• W2079761956 created "2016-06-24" @default.
• W2079761956 creator A5005036733 @default.
• W2079761956 creator A5039391064 @default.
• W2079761956 date "2015-02-19" @default.
• W2079761956 modified "2023-10-01" @default.
• W2079761956 title "Towards a general framework for predicting threat status of data-deficient species from phylogenetic, spatial and environmental information" @default.
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• W2079761956 doi "https://doi.org/10.1098/rstb.2014.0016" @default.
• W2079761956 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4290430" @default.
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