Modelling the Species Distribution of Flat-Headed Cats (Prionailurus planiceps), an Endangered South-East Asian Small Felid
Land Cover
Data deficient
Species distribution
DOI:
10.1371/journal.pone.0009612
Publication Date:
2010-03-16T22:16:00Z
AUTHORS (17)
ABSTRACT
Background The flat-headed cat (Prionailurus planiceps) is one of the world's least known, highly threatened felids with a distribution restricted to tropical lowland rainforests in Peninsular Thailand/Malaysia, Borneo and Sumatra. Throughout its geographic range large-scale anthropogenic transformation processes, including pollution fresh-water river systems landscape fragmentation, raise concerns regarding conservation status. Despite an increasing number camera-trapping field surveys for carnivores South-East Asia during past two decades, few these studies recorded cat. Methodology/Principal Findings In this study, we designed predictive species model using Maximum Entropy (MaxEnt) algorithm reassess potential current status Eighty-eight independent occurrence records were gathered from surveys, literature records, museum collections. These historical analysed relation bioclimatic variables (WorldClim), altitude (SRTM) minimum distance larger water resources (Digital Chart World). Distance was identified as key predictor cats (>50% explanation). addition, used different land cover maps (GLC2000, GlobCover SarVision LLC Borneo), information on protected areas regional human population density data extract suitable habitats predicted by MaxEnt model. Between 54% 68% habitat has already been converted unsuitable types (e.g. croplands, plantations), only between 10% 20% categorised fully according IUCN criteria. remaining are fragmented forest patches remain. Conclusion/Significance Based our findings, recommend that future efforts should focus localities be implemented through continuous dialogue local stakeholders, conservationists scientists ensure long-term survival. can serve flagship protection several other endangered associated forests surface sources region.
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