Application of Ecological-Niche Factor Analysis in Habitat Assessment of Giant Pandas
January 17, 2008 - Wang, Xuezhi; Xu, Weihua; Ouyang, Zhiyun; Liu, Jianguo "Jack"; Xiao, Yi; Youping, Chen; Lianjun, Zhao; Junzhong, Huang
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EmailJournal or Book Title: Acta Ecologica Sinica
Keywords: giant panda; Ailuropoda melanoleuca; ecological-niche factor analysis; habitat suitability; habitat assessment
Volume/Issue: 28/2
Page Number(s): 821-828
Year Published: 2008
Ecological-niche factor analysis (ENFA) is a multivariate approach to study geographic distribution of species on a large scale with only presence data. It has been widely applied in many fields including wildlife management, habitat assessment and habitat prediction. In this paper, this approach was applied in habitat suitability assessment for giant pandas in Pingwu County, Sichuan Province, China. With presence data of giant pandas and remote sensing data, habitat suitability of pandas in this county was evaluated based on ENFA model, and spatial distribution pattern of nature reserves and conservation gaps were then evaluated. The results show that giant pandas in this county prefer high-elevation zones (> 2128 m) dominated by coniferous forest, and mixed coniferous and deciduous broadleaf forest, and avoid deciduous broadleaf forest and shrubs. Pandas avoid staying at habitats with human disturbances. Farmland is a major factor threatening panda habitat. Panda habitat is mainly distributed in north and west of Pingwu with a total area of 234033 hm2, 106345hm2 for suitable habitat and 127688 hm2 for marginally suitable habitat). 3 nature reserves were located in Pingwu, covering over 49.2% of total suitable habitat and 45.6% of total marginally suitable habitat. Although 47.2% of panda habitat was in reserves under protection, connectivity between reserves was weak and a conservation gap existed in the north part of Pingwu. Thus, a new nature reserve in Baima and Mupi should be established to link the isolated habitats.
URL: Application of Ecological-Niche Factor Analysis
DOI: 10.1016/S1872-2032(08)60030-X
Type of Publication: Journal Article
