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Predicting potential distributions of two rare allopatric sister species,the globally threatened Doliornis cotingas in the Andes
Authors:Frédéric Jiguet  Morgane Barbet‐Massin  Pierre‐Yves Henry
Institution:1. UMR 7204 MNHN‐CNRS‐UPMC, Muséum National d’Histoire Naturelle, 55 rue Buffon, CP 51, 75005 Paris, France;2. UMR 7179 MNHN‐CNRS, Muséum National d’Histoire Naturelle, 1 avenue du Petit Chateau, 91800 Brunoy, France
Abstract:ABSTRACT Conservation of rare, elusive species is difficult because of limited knowledge of their biology and distribution. The two species of Doliornis cotingas are known from 7 (Chestnut‐bellied Cotinga, D. remseni) and 13 (Bay‐vented Cotinga, Doliornis sclateri) locations, respectively. Their limited ranges in combination with habitat loss make them vulnerable to extinction. We modeled the potential distribution of these two rare, allopatric sister species separated by an orographic barrier using species distribution modeling with an ensemble forecast approach using eight modeling techniques. Predicted distributions (with conservative thresholds of probability of presence, i.e., lowest presence thresholds) for these sister species showed virtually no overlap, although their respective niches were statistically not dissimilar. Hence, the existence of the recently discovered Chestnut‐bellied Cotinga could not have been predicted from the range of its sister species, unless using very crude distribution models (with extensive extrapolation). New areas of likely occurrences were identified for both species, and the genus, and will be useful for directing future field searches. The estimates of potentially suitable range for both species still qualify both species as “vulnerable to extinction.” Our study illustrates how opportunistic records collected by field ornithologists can be objectively transformed, with the help of existing software, into information potentially useful in the conservation of rare species.
Keywords:allopatric sister taxa  alloprediction  BIOMOD  distribution range  species distribution modeling  tropical montane forest
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