Journal of Environmental Impact Assessment (환경영향평가)

Korean Society of Environmental Impact Assessment (한국환경영향평가학회)
권호 표지
DOI QR코드

DOI QR Code

Analyzing Priority Management Areas for Domestic Cats (Felis catus) Using Predictions of Distribution Density and Potential Habitat

고양이(Feliscatus)의 분포밀도와 잠재서식지 예측을 이용한 우선 관리 대상 지역 분석

  • Ahmee Jeong (Department of Environmental Science and Engineering, Ewha Womans University) ;
  • Sangdon Lee (Department of Environmental Science and Engineering, Ewha Womans University)
  • 정아미 (이화여자대학교 환경공학과) ;
  • 이상돈 (이화여자대학교 환경공학과)
  • Received : 2023.11.06
  • Accepted : 2023.11.27
  • Published : 2023.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

This study aimed to predict the distribution density and potential habitat of domestic cats (Felis catus) in order to identify core distribution areas. It also aimed to overlay protected areas to identify priority areas for cat management. Kernel density estimation was used to determine the distribution density, and areas with high density were classified in Greater Seoul, Chungnam, Daejeon, and Daegu. Elevation, distance from the used area and roughness were identified as important variables in predicting potential habitat using the MaxEnt model. In addition, the classification of suitable and unsuitable areas based on thresholds showed that the predicted presence of habitat was more extensive in Seoul, Sejong, Daejeon, Chungnam, and Daegu. Core distribution areas were selected by overlapping high-density areas with suitable areas. Priority management areas were identified by overlaying core distribution areas with designated wildlife sanctuaries. As a result, Gyeonggi, and Chungnam have the largest areas. In addition, buffer zones will be implemented to effectively manage the core distribution area and minimize the potential for additional introductions in areas of high management priority, such as protected areas. These results can be used as a basis for investigating the status of the cat's habitat and developing more effective management strategies.

본 연구는 국내 고양이(Felis catus)의 분포밀도와 잠재 서식지를 예측하여 핵심분포지역을 선정하고, 보호지역을 중첩하여 우선으로 고양이 관리가 시행되어야 할 지역을 선정하고자 하였다. 분포밀도 파악을 위해 커널밀도추정을 사용하였고, 고밀도 지역을 분류한 결과 수도권 지역과 충남, 대전, 대구에서 밀도가 높았다. MaxEnt 모형을 활용한 잠재 서식지 예측에서는 고도, 시가지로부터의 거리, 지표 거칠기 등이 중요한 변수로 확인되었고, 임계값을 기준으로 출현/비출현 지역을 분류한 결과 수도권과 세종, 대전, 충남, 대구에서 출현 예측 지역의 면적이 높았다. 고밀도 지역과 출현 예측 지역을 중첩하여 핵심분포지역을 선정하였고, 핵심분포지역과 야생동물 보호지역을 중첩하여 우선으로 관리해야 할 지역을 파악하였다. 그 결과 경기도와 충남지역이 제일 면적이 넓은 지역으로 선정되었다. 또한 보호지역과 같은 우선 관리 대상 지역을 중심으로 핵심분포지역이 둘러싸고 있어, 추가적인 유입을 막고 관리하기 위한 완충구역을 설정하는 것이 필요하다. 이러한 결과는 고양이의 서식현황을 조사하고, 우리나라 실정에 맞는 관리방안 설정을 위한 기초자료로 활용될 수 있다.

Keywords

Acknowledgement

본 연구는 한국연구재단(KRF-2021R1A2C1011213), 환경부 환경산업기술원(2020002990006), 서울녹색환경지원센터(SESTC-2023)의 지원을 받아 연구되었습니다.

References

  1. Cove MV, Gardner B, Simons TR, Kays R, O'Connell AF. 2018. Free-ranging domestic cats (Felis catus) on public lands: estimating density, activity, and diet in the Florida Keys. Biological Invasions, 160(20): 333-344. https://doi.org/10.1007/s10530-017-1534-x
  2. Dauphine N, Cooper RJ. 2009. Impacts of free-ranging domestic cats (Felis catus) on birds in the United States: a review of recent research with conservation and management recommendations. In: Proceedings of the fourth international partners in flight conference: tundra to tropics, 205-219.
  3. Edwards GP, De Preu N, Shakeshaft BJ, Crealy IV, Paltridge RM. 2008. Home range and movements of male feral cats (Felis catus) in a semiarid woodland environment in central Australia. Austral Ecology, 26(1): 93-101. https://doi.org/10.1046/j.1442-9993.2001.01091.x
  4. Ferreira JP, Leitao I, Santos-Reis M, Revilla E. 2011. Human-related factors regulate the spatial ecology of domestic cats in sensitive areas for conservation. PLoS One, 6(10): e25970.
  5. Hwang MK. 2013. Comparison of the Diet and Density of Free-roaming Cats between Urban and Rural Environments, Korea. MS dissertation. Seoul National University, Seoul. [Korean Literature]
  6. Jakub ZK. 2021. The impact of feral domestic cats on native bird populations. Predictive modelling approach on a country scale. Ecological Complexity, 48: 100964.
  7. Kang YJ, Noh YJ. 2019. Comparison Study of Kernel Density Estimation according to Various Bandwidth Selectors. Computational Structural Engineering Institute of Korea, 32(3): 173-182. [Korean Literature] https://doi.org/10.7734/COSEIK.2019.32.3.173
  8. Kauhala K, Auttila M. 2010. Estimating habitat selection of badgers a test between different methods. Folia Zoological, 59: 16-25. https://doi.org/10.25225/fozo.v59.i1.a4.2010
  9. Kim AR, Kim YC, Lee DH. 2018. A Management Plan According to the Estimation of Nutria (Myocastor coypus) Distribution Density and Potential Suitable Habitat. Journal of Environmental Impact Assessment, 27(2): 203-214. [Korean Literature]
  10. Kim JS. 2015. Evaluation of Feral Cat (Felis catus) Management at Mt. Dobong Based on Home Range, Demographic Status, and Population Viability Analyse. MS dissertation. Seoul National University, Seoul. [Korean Literature]
  11. Kim YJ, Lee WS, Choi CY. 2020. Population Size and Home Range Estimates of Domestic Cats (Felis catus) on Mara Islet, Jeju, in the Republic of Korea. Korean Journal of Environment and Ecology, 34(1): 9-17. [Korean Literature] https://doi.org/10.13047/KJEE.2020.34.1.9
  12. Korea Database on Protected Areas. 2022. [cited 2023 Sep 1]. Available from: http://www.kdpa.kr/ [Korean Literature]
  13. Kwon KJ. 2001. Feeding habits of cat (Felis catus) in Korea. MS dissertation. Kyungnam University, Gyeongnam. [Korean Literature]
  14. Lee CI, Chung CU, Kim CY. 2009. Analyse the Winter Season Home Range of Felis catus resided in Gyeongju National Park of Korea. Korean Journal of Environment and Ecology, 23(5): 485-491. [Korean Literature]
  15. Liu C, Berry PM, Dawson TP, Pearson RG. 2005. Selecting Thresholds of Occurrence in the Prediction of Species Distributions. Ecography, 28(3): 385-393. https://doi.org/10.1111/j.0906-7590.2005.03957.x
  16. Lopez-Jara MJ, Sacristan I, Farias AA, Maron-Perez F, Acuna F, Aguilar E, Garcia S, Contreras P, Silva-Rodriguez EA, Napolitano C. 2021. Free-roaming domestic cats near conservation areas in Chile: Spatial movements, human care and risks for wildlife. Perspectives in Ecology and Conservation, 19(3): 387-398. https://doi.org/10.1016/j.pecon.2021.02.001
  17. Loss SR, Will T, Marra PP. 2013. The impact of free-ranging domestic cats on wildlife of the United States. Nature communications, 4(1): 1-8. https://doi.org/10.1038/ncomms2380
  18. Lowe S, Browne M, Boudjelas S, De Poorter M. 2000. 100 of the world's worst invasive alien species: a selection from the global invasive species database. Invasive Species Specialist Group Species Survival Commission, World Conservation Union (IUCN).
  19. Mariano RR, Philip JS, Antoni BM. 2015. Niche and movement models identify corridors of introduced feral cats infringing ecologically sensitive areas in New Zealand. Biological Conservation, 192: 48-56.
  20. Ministry of Agriculture and Forestry. 2001. An analysis of the damage state made by wildlife in Jeju island and a study on effective ways to cope with it. Ministry of Agriculture and Forestry. [Korean Literature]
  21. Ministry of Environment. 2001. Study on habitat status and management of feral cats in Korea. Ministry of Environment. [Korean Literature]
  22. Ministry of Environment. 2020. The Fourth Master Plan for Wildlife Conservation ('21~'25). Ministry of Environment. [Korean Literature]
  23. National Institute of Environmental Research. 2010. Detailed Studies on Invasive Alien Species and Their Management[V]. National Institute of Environmental Research. [Korean Literature]
  24. Normand C, Urbanek RE, Gillikin MN. 2019. Population density and annual and seasonal space use by feral cats in an exurban area. Urban Ecosystems, 22: 303-313. https://doi.org/10.1007/s11252-018-0812-4
  25. Phillips SJ, Anderson RP, Schapire RE. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190(3-4): 231-259. https://doi.org/10.1016/j.ecolmodel.2005.03.026
  26. Ryu JE, Choi YY, Jeon SW, Sung HC. 2018. Evaluation of Habitat Function of National Park Based on Biodiversity and Habitat Value. The Korea Society of Environmental Restoration Technology, 21(5): 39-60. [Korean Literature]
  27. Silverman BW. 1986. Density Estimation for Statistics and Data Analysis. London- New York, Chapman and Hall.
  28. Williamson SD, van Dongen R, Trotter L, Palmer R, Robinson TP. 2021. Fishing for Feral Cats in a Naturally Fragmented Rocky Landscape Using Movement Data. Remote Sensing, 13(23): 4925.
  29. Worton BJ. 1995. Using Monte Carlo Simulation to EvaluateKernel-BasedHomeRangeEstimators. The Journal of Wildlife Management, 59(4): 794-800. https://doi.org/10.2307/3801959
  30. Yoo SY, Hong MJ, Moon YM, Choi JH, Lee JY, Yoo JC, Kwon IK. 2022. Study on the distribution of waterbirds and their core habitats in coastal wetlands in Incheon and Gyeonggi Bay. Korean Journal of Ornithology, 29(2): 119-130. [Korean Literature] https://doi.org/10.30980/KJO.2022.12.29.2.119