Predicted distribution of the Malay civet Viverra tangalunga (Mammalia: Carnivora: Viverridae) on Borneo

Joanna Ross, Andrew J. Hearn, David W. Macdonald, Raymond Alfred, Susan M. Cheyne, Azlan Mohamed, Ramesh Boonratana, Henry Bernard, Jason Hon, Rustam, Jedediah F. Brodie, Anthony Giordano, Matt Heydon, Gono Semiadi, John Mathai, Gabriella Fredriksson, Andrew J. Marshall, John D. Pilgrim, Tim van Berkel, Jerrold L. BelantStephanie Kramer-Schadt, Andreas Wilting

Research output: Contribution to journalArticlepeer-review

Abstract

The Malay civet Viverra tangalunga is a small carnivore occurring on several Indonesian islands, Malaysia, the Philippines and Singapore. The Malay civet occurs in diverse habitats, including primary and logged forest, and disturbed habitats near villages. It is listed by The IUCN Red List of Threatened Species as globally Least Concern; however, the extent to which it can tolerate habitat alteration is unclear. We analysed 69 (Balanced Model) and 115 (Spatial Filtering Model) location records to predict habitat suitability on Borneo. The resulting models predicted a high proportion of Borneo as suitable habitat for the Malay civet, although most coastal areas, swamp forests and high-elevation areas were predicted to be unsuitable. Highly suitable areas for the Malay civet include the central forest block in Sabah, much of the production forest in Sarawak and East and North Kalimantan, Bukit Baka Bukit Raya National Park, and production forest in Central Kalimantan. The Malay civet is currently widespread and appears somewhat tolerant of habitat alteration, and therefore there are currently no species-specific conservation requirements, beyond the maintenance of the current remaining habitat in protected areas.

Original languageEnglish
Pages (from-to)78-83
Number of pages6
JournalRaffles Bulletin of Zoology
Volume2016
StatePublished - 2016

Keywords

  • Borneo Carnivore Symposium
  • Brunei
  • Conservation priorities
  • Habitat suitability index
  • Indonesia
  • Malaysia
  • Species distribution modelling
  • Survey gaps

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