• 제목/요약/키워드: road-kill hotspot

검색결과 3건 처리시간 0.016초

야생동물 서식지 패치와 로드킬 핫스팟의 상관관계 연구 (A Study on the Correlation between Road-kill Hotspot and Habitat Patches)

  • 석상묵;이지영
    • 환경영향평가
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    • 제24권3호
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    • pp.233-243
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    • 2015
  • 도로의 개발 등과 같은 선형적인 개발로 인해 생태계 파편화 현상이 발생함에 따라 야생동물 로드킬이 지속적으로 발생하고 있다. 이에 정부는 로드킬 저감대책의 일환으로 생태통로 및 유도펜스, 경고표지판 등 다양한 구조물의 설치를 통해 로드킬 저감방안을 마련하고 있다. 그러나 그간 국내에 설치되어 온 많은 구조물들은 입지선정 및 목표종 선정, 관리 등의 미흡으로 인해 그 실효성에 대하여 많은 문제점이 제기되어 왔다. 이러한 정책의 효과를 높이기 위해서는 로드킬 저감을 위한 구조물 설치구역 선정 시 실제 이용 대상이 되는 목표종의 선정 및 분석이 매우 중요하다. 이에 본 연구에서는 로드킬 지점과 야생동물 서식지 패치 간의 관계성을 파악하여 야생동물 서식지 패치의 공간적 위치가 로드킬 저감을 위한 정책 마련 시 중요한 요소 중 하나로 활용될 수 있음을 제시하고자 하였다. 본 연구의 목표종은 선행연구를 통해 오대산 국립공원의 다람쥐로 선정하였으며, 다람쥐의 서식지 선호도 분석을 통해 서식변수를 선정 중첩하여 다람쥐 서식지 패치를 도출하였다. 이후 로드킬 발생지점 정보와 Getis-Ord $G_i^*$ 분석을 활용하여 로드킬 핫스팟을 도출하고, 서식지 패치-도로 간의 거리와 $G_i$ Z-score 간의 상관분석을 통해 두 변수간의 상관관계를 파악하였다. 그 결과 두 변수 사이의 부적 상관관계가 나타남에 따라 서식지 패치와 도로가 인접할수록 $G_i^*$ Z-score가 높아지는 경향을 보이는 것으로 나타났다.

Korea Road-Kill Observation System: The First Case to Integrate Road-Kill Data in National Scale by Government

  • Kim, Kyungmin;Woo, Dong-Gul;Seo, Hyunjin;Park, Taejin;Song, Eui-Geun;Choi, Tae-Young
    • Journal of Forest and Environmental Science
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    • 제35권4호
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    • pp.281-284
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    • 2019
  • Efficient management of road-kill data is difficult at national scale when there are many organizations that are in charge of different road types. Here, we described the first case to integrate road-kill data through Korea Road-kill Observation System (KROS) by the Korean government. The system was launched in June 2018 to approximately 3,000 road menders. During 15 months, 5,812 road-kill observations were registered on KROS including mammals, birds, reptiles and amphibians. Of them, about 86 % was occupied by five species (Hydropotes inermis, Felis catus, Capreolus pygargus, Nyctereutes procyonoides, and Canis lupus familiaris) listed in number of occurrences. The observed road-kill frequency rapidly increased until April 2019 and peaked on May 2019. However, as the system is just starting, the results from KROS cannot be treated as the exact representation of road-kill trend in the country. Although the efficient method to manage national road-kill statistic is arranged, still there are some limitations to overcome to make the system stable.

제주도 노루 로드킬 방지를 위한 저감시설 대상지 선정방안 연구 (Selection Method for Installation of Reduction Facilities to Prevention of Roe Deer(Capreouls pygargus) Road-kill in Jeju Island)

  • 김민지;장래익;유영재;이준원;송의근;오홍식;성현찬;김도경;전성우
    • 한국환경복원기술학회지
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    • 제26권5호
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    • pp.19-32
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    • 2023
  • The fragmentation of habitats resulting from human activities leads to the isolation of wildlife and it also causes wildlife-vehicle collisions (i.e. Road-kill). In that sense, it is important to predict potential habitats of specific wildlife that causes wildlife-vehicle collisions by considering geographic, environmental and transportation variables. Road-kill, especially by large mammals, threatens human safety as well as financial losses. Therefore, we conducted this study on roe deer (Capreolus pygargus tianschanicus), a large mammal that causes frequently Road-kill in Jeju Island. So, to predict potential wildlife habitats by considering geographic, environmental, and transportation variables for a specific species this study was conducted to identify high-priority restoration sites with both characteristics of potential habitats and road-kill hotspot. we identified high-priority restoration sites that is likely to be potential habitats, and also identified the known location of a Road-kill records. For this purpose, first, we defined the environmental variables and collect the occurrence records of roe deer. After that, the potential habitat map was generated by using Random Forest model. Second, to analyze roadkill hotspots, a kernel density estimation was used to generate a hotspot map. Third, to define high-priority restoration sites, each map was normalized and overlaid. As a result, three northern regions roads and two southern regions roads of Jeju Island were defined as high-priority restoration sites. Regarding Random Forest modeling, in the case of environmental variables, The importace was found to be a lot in the order of distance from the Oreum, elevation, distance from forest edge(outside) and distance from waterbody. The AUC(Area under the curve) value, which means discrimination capacity, was found to be 0.973 and support the statistical accuracy of prediction result. As a result of predicting the habitat of C. pygargus, it was found to be mainly distributed in forests, agricultural lands, and grasslands, indicating that it supported the results of previous studies.