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Modeling Species Distribution

Modeling Species Distribution

Yongyut Trisurat, Albertus G. Toxopeus
Copyright: © 2011 |Pages: 27
ISBN13: 9781609606190|ISBN10: 1609606191|EISBN13: 9781609606206
DOI: 10.4018/978-1-60960-619-0.ch009
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MLA

Trisurat, Yongyut, and Albertus G. Toxopeus. "Modeling Species Distribution." Land Use, Climate Change and Biodiversity Modeling: Perspectives and Applications, edited by Yongyut Trisurat, et al., IGI Global, 2011, pp. 171-197. https://doi.org/10.4018/978-1-60960-619-0.ch009

APA

Trisurat, Y. & Toxopeus, A. G. (2011). Modeling Species Distribution. In Y. Trisurat, R. Shrestha, & R. Alkemade (Eds.), Land Use, Climate Change and Biodiversity Modeling: Perspectives and Applications (pp. 171-197). IGI Global. https://doi.org/10.4018/978-1-60960-619-0.ch009

Chicago

Trisurat, Yongyut, and Albertus G. Toxopeus. "Modeling Species Distribution." In Land Use, Climate Change and Biodiversity Modeling: Perspectives and Applications, edited by Yongyut Trisurat, Rajendra P. Shrestha, and Rob Alkemade, 171-197. Hershey, PA: IGI Global, 2011. https://doi.org/10.4018/978-1-60960-619-0.ch009

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Abstract

The results show that among the three approaches, the potentially suitable habitats derived from cartographic overlay cover the largest area and are likely to overestimate existing occurrence areas. The logistic regression model predicts approximately 56% as suitable area, while maximum entropy results covers approximately 9% of the sanctuary. Although the results show large differences in the suitable areas, it should not be concluded that any one method always proves better than the others. Utilization of any method is dependent on the situation and available information. If species observations are limited, the cartographic overlay or habitat suitability is recommended. The logistic regression method is recommended when adequate presence and absence data are available. If presence-only data is available, a niche-based model or the maximum entropy method (MAXENT) is highly recommended.

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