Modeling the distribution of rare or cryptic bird species of Taiwan

Tsai Yu Wu, Pei Fen Lee, Ruey Shing Lin, Jian Long Wu, Bruno A. Walther

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


For the study of the macroecology and conservation of Taiwan's birds, there was an urgent need to develop distribution models of bird species whose distribution had never before been modeled. Therefore, we here model the distributions of 27 mostly rare and cryptic breeding bird species using a statistical approach which has been shown to be especially reliable for modeling species with a low sample size of presence localities, namely the maximum entropy (Maxent) modeling technique. For this purpose, we began with a dedicated attempt to collate as much high-quality distributional data as possible, assembling databases from several scientific reports, contacting individual data recorders and searching publicly accessible database, the internet and the available literature. This effort resulted in 2022 grid cells of 1 × 1 km size being associated with a presence record for one of the 27 species. These records and 10 pre-selected environmental variables were then used to model each species' probability distribution which we show here with all grid cells below the lowest presence threshold being converted to zeros. We then in detail discuss the interpretation and applicability of these distributions, whereby we pay close attention to habitat requirements, the intactness and fragmentation of their habitat, the general detectability of the species and data reliability. This study is another one in an ongoing series of studies which highlight the usefulness of using large electronic databases and modern analytical methods to help with the monitoring and assessment of Taiwan's bird species.

Original languageEnglish
Pages (from-to)342-358
Number of pages17
Issue number4
Publication statusPublished - 2012


  • Biogeography
  • Conservation status
  • GIS
  • Rarity
  • Taiwan avifauna

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology


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