Species distribution model to predict the occurrence of Malayan partridge
Climate change has caused several problems in Malaysia such as increase of temperature and change in precipitation patterns. Malayan Partridge (Arborophila campbelli) is a bird species found in Peninsular Malaysia that is facing the threat of habitat loss due to climate changes. Currently, this spec...
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| Format: | Final Year Project / Dissertation / Thesis |
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2025
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| Online Access: | http://eprints.utar.edu.my/7095/1/fyp_CS_2025_LDCH.pdf http://eprints.utar.edu.my/7095/ |
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| _version_ | 1854094471921139712 |
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| author | Leong, Darren Chien Hsiung |
| author_facet | Leong, Darren Chien Hsiung |
| author_sort | Leong, Darren Chien Hsiung |
| building | UTAR Library |
| collection | Institutional Repository |
| content_provider | Universiti Tunku Abdul Rahman |
| content_source | UTAR Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Climate change has caused several problems in Malaysia such as increase of temperature and change in precipitation patterns. Malayan Partridge (Arborophila campbelli) is a bird species found in Peninsular Malaysia that is facing the threat of habitat loss due to climate changes. Currently, this species is understudied and that leads to less information about the future occurrence of this species. Therefore, this study aims to produce a prediction of current and future occurrence of Malayan Partridge in Peninsular Malaysia with different models Species Distribution Model (SDM) that are Maximum Entropy Model (MaxEnt), Random Forest (RF), Support Vector Machine (SVM), Generalized Linear Model (GLM) and Bioclim. Different pseudoabsence data settings will be implemented to identify the best setting to predict the occurrence of the species. Species occurrence data were collected from public biodiversity databases 19 bioclimatic variables were sourced from WorldClim to predict the current occurrence of the species. A variable selection process will be used to identify the important bioclimatic variables. These variables will be used for the models of SDM. To predict the potential future occurrence of the species, Shared Socioeconomic Pathway (SSP) will be implemented. The performance of the model will be evaluated through Area Under Curve (AUC) and cross-validation techniques. Habitat suitability maps will be produced because of the model to provide visualization. |
| format | Final Year Project / Dissertation / Thesis |
| id | my-utar-eprints.7095 |
| institution | Universiti Tunku Abdul Rahman |
| publishDate | 2025 |
| record_format | eprints |
| spelling | my-utar-eprints.70952025-12-28T15:32:50Z Species distribution model to predict the occurrence of Malayan partridge Leong, Darren Chien Hsiung T Technology (General) Climate change has caused several problems in Malaysia such as increase of temperature and change in precipitation patterns. Malayan Partridge (Arborophila campbelli) is a bird species found in Peninsular Malaysia that is facing the threat of habitat loss due to climate changes. Currently, this species is understudied and that leads to less information about the future occurrence of this species. Therefore, this study aims to produce a prediction of current and future occurrence of Malayan Partridge in Peninsular Malaysia with different models Species Distribution Model (SDM) that are Maximum Entropy Model (MaxEnt), Random Forest (RF), Support Vector Machine (SVM), Generalized Linear Model (GLM) and Bioclim. Different pseudoabsence data settings will be implemented to identify the best setting to predict the occurrence of the species. Species occurrence data were collected from public biodiversity databases 19 bioclimatic variables were sourced from WorldClim to predict the current occurrence of the species. A variable selection process will be used to identify the important bioclimatic variables. These variables will be used for the models of SDM. To predict the potential future occurrence of the species, Shared Socioeconomic Pathway (SSP) will be implemented. The performance of the model will be evaluated through Area Under Curve (AUC) and cross-validation techniques. Habitat suitability maps will be produced because of the model to provide visualization. 2025-06 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/7095/1/fyp_CS_2025_LDCH.pdf Leong, Darren Chien Hsiung (2025) Species distribution model to predict the occurrence of Malayan partridge. Final Year Project, UTAR. http://eprints.utar.edu.my/7095/ |
| spellingShingle | T Technology (General) Leong, Darren Chien Hsiung Species distribution model to predict the occurrence of Malayan partridge |
| title | Species distribution model to predict the occurrence of Malayan partridge |
| title_full | Species distribution model to predict the occurrence of Malayan partridge |
| title_fullStr | Species distribution model to predict the occurrence of Malayan partridge |
| title_full_unstemmed | Species distribution model to predict the occurrence of Malayan partridge |
| title_short | Species distribution model to predict the occurrence of Malayan partridge |
| title_sort | species distribution model to predict the occurrence of malayan partridge |
| topic | T Technology (General) |
| url | http://eprints.utar.edu.my/7095/1/fyp_CS_2025_LDCH.pdf http://eprints.utar.edu.my/7095/ |
| url_provider | http://eprints.utar.edu.my |