Nest-Site Selection And Distribution Model Of The White-Bellied Sea-Eagle Haliaeetus Leucogaster Using Geographic Information System

The White-bellied Sea-Eagle (Haliaeetus leucogaster) is the largest raptor species in Penang as well as in Malaysia and is commonly sighted in coastal and near coastal of Penanng National Park. The species distribution is island-wide but with a high concentration in Penang National Park, in terms...

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Bibliographic Details
Main Author: Zainudin, Mohd Syafiq Masduqi Mohd
Format: Thesis
Language:English
Published: 2012
Subjects:
Online Access:http://eprints.usm.my/46041/1/MOHD%20SYAFIQ%20MASDUQI%20BIN%20MOHD%20ZAINUDIN_HJ.pdf
http://eprints.usm.my/46041/
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Summary:The White-bellied Sea-Eagle (Haliaeetus leucogaster) is the largest raptor species in Penang as well as in Malaysia and is commonly sighted in coastal and near coastal of Penanng National Park. The species distribution is island-wide but with a high concentration in Penang National Park, in terms of nesting sites and population density. The main aim of this study is to develop the predictive distribution model and map the potential and suitable nesting habitat for the species in the study area based on nest-site selection analysis. A total of 34 nesting sites have been located during the survey on December 2007 to April 2009 in coastal forest of Penang National Park and therefore used in nest-site selection analysis by comparing the selected and available habitat using t-test analysis. Seven habitat features or variables were chosen for analysis; elevation, slope, aspect, ruggedness index, distance to road, distance to building and distance to water. Variables of elevation, slope, distance to road and distance to water showed significance result (P < 0.05). The information from the nest-site selection analysis was used to build the predictive distribution model for the species. Thirteen independent nests located at evaluation area were used for model validation and give 30.2% accuracy and showed satisfactory result when tested against random points. The information and results from this study is highly valuable and crucial for future management and conservation of the species.