지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2022.3
- 수록면
- 81 - 95 (15page)
- DOI
- 10.33162/JAR.2022.3.22.1.081
이용수
초록· 키워드
오류제보하기
Purpose: Predicting the occurrence of wild species at the landscape level is a crucial task for environmental managers and conservation biologists. Modeling and evaluating wildlife habitat quality based on the Geographic Information Systems (GIS) technique provides new opportunities for enhancing model predictability.
Methods: We developed a GIS-based habitat suitability index (HSI) model for Korean water deer (Hydropotes inermis argyropus) in Chungnam province, Korea, where they are a significant cause of damage to vegetables and crops. The model was based primarily on logistic regression analysis and was used to assess the impact of multiple variables, such as landscape patterns and structures, topographic characteristics, and human disturbance, on habitat suitability for the species. After developing the model, we employed it to produce a habitat-suitability map.
Results: The HSI model yielded a p-value of 0.339 (χ² = 9.033) and a 74.0% correct prediction rate for the overall predicted data. The model also demonstrated that 42.4% of the province is covered in poor-quality habitat, while Korean water deer prefer fair-quality habitats (mean HSI = 0.50). In addition, the observation probability increased when HSI values rose, meaning that the model has good predictive power.
Conclusion: Associations between landscape patterns and habitat requirements could be utilized to build accurate, easy-to-apply, predictive models for the habitats of wild species. The HSI model and habitat-suitability map provide solid foundations on which to build effective wildlife management and Agri-Environment policies with local governments to conserve endangered species.
Methods: We developed a GIS-based habitat suitability index (HSI) model for Korean water deer (Hydropotes inermis argyropus) in Chungnam province, Korea, where they are a significant cause of damage to vegetables and crops. The model was based primarily on logistic regression analysis and was used to assess the impact of multiple variables, such as landscape patterns and structures, topographic characteristics, and human disturbance, on habitat suitability for the species. After developing the model, we employed it to produce a habitat-suitability map.
Results: The HSI model yielded a p-value of 0.339 (χ² = 9.033) and a 74.0% correct prediction rate for the overall predicted data. The model also demonstrated that 42.4% of the province is covered in poor-quality habitat, while Korean water deer prefer fair-quality habitats (mean HSI = 0.50). In addition, the observation probability increased when HSI values rose, meaning that the model has good predictive power.
Conclusion: Associations between landscape patterns and habitat requirements could be utilized to build accurate, easy-to-apply, predictive models for the habitats of wild species. The HSI model and habitat-suitability map provide solid foundations on which to build effective wildlife management and Agri-Environment policies with local governments to conserve endangered species.
목차
1. Introduction
2. Materials and Methods
3. Results
4. Discussions
5. Conclusions
References
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