Journal of the Korean Society of Environmental Restoration Technology (한국환경복원기술학회지)

The Korea Society of Environmental Restoration Technology (한국환경복원기술학회)
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A Study on the Application of Modeling to predict the Distribution of Legally Protected Species Under Climate Change - A Case Study of Rodgersia podophylla -

기후변화에 따른 법정보호종 분포 예측을 위한 종분포모델 적용 방법 검토 - Rodgersia podophylla를 중심으로 -

  • Yoo, Youngjae (Ojeong Resilience Institute, Korea University) ;
  • Hwang, Jinhoo (Ojeong Resilience Institute, Korea University) ;
  • Jeon, Seong-woo (Division of Environmental Science & Ecological Engineering, Korea University)
  • 유영재 (고려대학교 오정리질리언스연구원) ;
  • 황진후 (고려대학교 오정리질리언스연구원) ;
  • 전성우 (고려대학교 환경생태공학부)
  • Received : 2024.03.27
  • Accepted : 2024.06.03
  • Published : 2024.06.30
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Abstract

Legally protected species are one of the crucial considerations in the field of natural ecology when conducting environmental impact assessments (EIAs). The occurrence of legally protected species, especially 'Endangered Wildlife' designated by Ministry of Environment, significantly influences the progression of projects subject to EIA, necessitating clear investigations and presentations of their habitats. In perspective of statistics, a minimum of 30 occurrence coordinates is required for population prediction, but most of endangered wildlife has insufficient coordinates and it posing challenges for distribution prediction through modeling. Consequently, this study aims to propose modeling methodologies applicable when coordinate data are limited, focusing on Rodgersia podophylla, representing characteristics of endangered wildlife and northern plant species. For this methodology, 30 random sampling coordinates were used as input data, assuming little survey data, and modeling was performed using individual models included in BIOMOD2. After that, the modeling results were evaluated by using discrimination capacity and the reality reflection ability. An optimal modeling technique was proposed by ensemble the remaining models except for the MaxEnt model, which was found to be less reliable in the modeling results. Alongside discussions on discrimination capacity metrics(e.g. TSS and AUC) presented in modeling results, this study provides insights and suggestions for improvement, but it has limitations that it is difficult to use universally because it is not a study conducted on various species. By supporting survey site selection in EIA processes, this research is anticipated to contribute to minimizing situations where protected species are overlooked in survey results.

Keywords

Acknowledgement

본 연구는 환경부의 재원으로 한국환경산업기술원의 ICT기반 환경영향평가 의사결정 지원 기술개발사업의 지원을 받아 연구되었습니다.(2020002990009)

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