JOURNAL ARTICLE

An updated mammal inventory of Langkawi Island, Malaysia using camera traps and transect surveys.

  • Published In: Malayan Nature Journal, 2025, v. 77, n. 3. P. 181 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: DONNELLY, HARRY; MIARD, PRISCILLIA; ROSELY, NIK FADZLY; SAH, SHAHRULANUAR MOHD; RUPPERT, NADINE 3 of 3

Abstract

Mammal communities on tropical islands remain understudied, often lacking basic information on species composition and distribution, which are crucial for conservation planning. Camera traps and transect surveys are usually compared in terms of efficiency, but combining both enhances research output as their efficiency in detecting different species may vary. The Langkawi archipelago in Malaysia exemplifies this, as it lacks a recent assessment of its medium to large-sized mammal community. A camera trap survey was conducted in the forests of Langkawi Island in 2021, complemented by nocturnal mammal transect walks, to establish an updated mammal inventory of the island. Species diversity and occupancy were assessed for a subset of abundant species. Thirteen mammal species were recorded, including the Asiatic brush-tailed porcupine (Atherurus macrourus), which was documented in Langkawi for the first time. Three detected species are classified as "Endangered" and one as "Critically Endangered" by the IUCN, underscoring the urgent need for targeted conservation measures. These findings provide essential baseline data to guide local conservation strategies, habitat management, and future monitoring efforts for threatened mammals in Langkawi. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Malayan Nature Journal. 2025/09, Vol. 77, Issue 3, p181
  • Document Type:Article
  • Subject Area:Zoology
  • Publication Date:2025
  • ISSN:0025-1291
  • DOI:10.62613/mnj.25773.03
  • Accession Number:189049180
  • Copyright Statement:Copyright of Malayan Nature Journal is the property of Malaysian Nature Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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