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

The Korea Society of Environmental Restoration Technology (한국환경복원기술학회)
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Monitoring Urban Ecological corridors in Gwanggyo New Town Using Camera Trapping

카메라트래핑을 활용한 광교신도시 내 도시형 생태통로 모니터링

  • Park, Il-Su (Dept. of Environmental Horticulture and Landscape Architecture, Dankook University) ;
  • Kim, Whee-Moon (Dept. of Environmental Horticulture and Landscape Architecture, Dankook University) ;
  • Kim, Seoung-Yeal (Dept. of Environmental Horticulture and Landscape Architecture, Dankook University) ;
  • Park, Chan (Dept. of Landscape Architecture, University of Seoul) ;
  • Song, Won-Kyong (School of Environmental Horticulture and Landscape Architecture, Dankook University)
  • 박일수 (단국대학교 환경원예.조경학과 대학원) ;
  • 김휘문 (단국대학교 환경원예.조경학과 대학원) ;
  • 김성열 (단국대학교 환경원예.조경학과 대학원) ;
  • 박찬 (서울시립대학교 조경학과) ;
  • 송원경 (단국대학교 환경원예.조경학부)
  • Received : 2021.01.18
  • Accepted : 2021.02.08
  • Published : 2021.02.26
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Abstract

The new town in Korea, developed as a large-scale housing plan, has created urban ecological corridors to provide habitat and movement routes to wildlife and to promote natural ecological flow. This study aimed to investigate the use of wildlife in 10 ecological corridors in Gwanggyo New Town through camera trap technology and confirm effectiveness by identifying environmental factors affecting the use of wildlife's urban ecological corridors. Our researchers installed 20 unmanned sensor cameras at each the entrance and exit of the ecological corridors, and monitored urban wildlife for 10 weeks. According to the monioring results, the main species in Gwanggyo New Town were identified not only raccons, cats, water deer, korean hare and avain but also magpies, dove, eurasian tree sparrow, ring-necked pheasant, and eurasian jay. The number of uses ecological corridors of urban residents was 801(13.49%), as high as that of urban wildlife (1,140, 19.20%), which was judged to have disturbed the use of ecological corridors by wildlife. However, most dominant species of urban wildlife are nocturnal so that, it was judged that they share home range with urban residents at a time interval. In addition, according to the correlation analysis results between the mammal using rate of the urban ecological corridors and environmental factors(ecological corridor-specific length, ecological corridor-specific width, cover degree, shielding degree, connected green area, separation of movement routes, and presence of streetlights), environmental factors were not statistically significant. However, the more the area of green space connected to ecological corridors, the more increasing the mammal using rate of ecological corridor(r=0.71, p<0.05). Therefore, the area of green space connected to the ecological corridors that is associated with rate of wildlife using corridors should be considered as a priority when developing an urban ecological corridors. In the future, this study will extend the observation period of the ecological corridors and continuously accumulate data by adding the number of observation cameras. Furthermore, it is expected that the results of this study can be used as basic data for the standards for urban ecological corridors installation.

Keywords

References

  1. Adam TF․PC Anthony․B Andrew. 2009. Comparison of Methods of Monitoring Wildlife Crossing-Structures on Highways. The Journal of Wildlife Management. 73(7) : 1213-1222. https://doi.org/10.2193/2008-387
  2. Apps, PJ and JW McNutt. 2018. How camera traps work and how to work them. African Journal of Ecology. 56(4) : 702-709. https://doi.org/10.1111/aje.12563
  3. Cervinka, J․J Riegert․S Grill and M Salek. 2015. Large-scale evaluation of carnivore road mortality: the effect of landscape and local scale characteristics. Mammal Research. 60(3). https://doi.org/10.1007/s13364-015-0227-z
  4. Cho, HJ. 2016. Analysis of Animal Usage of Eco-bridge and Ecoduct Using an Infrared CCTV at the Baekdudaegan Mountain Range, Korea. Ecology and Resilient Infrastructure. 3(3) : 177-181. https://doi.org/10.17820/eri.2016.3.3.177
  5. Choi, TY and HM Choi. 2007. Trace picture book of wild animals. Dolbegae,
  6. Choi, TY․BG Yang․DG Woo. 2012. The Suitable Types and Measures of Wildlife Crossing Structures for Mammals of Korea. Journal of Environmental Impact Assessment. 21(1) : 209-218. https://doi.org/10.14249/EIA.2012.21.1.209
  7. Chung, CU.․JY Cha․YC Kim․SC Kim․GH Kwon․HJ Lee. 2014. Monitoring Efficiency Evaluation of Camera Trapping in Terrestrial Mammals. The Korea Society For Environmental Restoration and Revegetation Technology. 17(3) : 65-74.
  8. Corlatti, L․K Hacklander and F. Frey-roos. 2009. Ability of Wildlife Overpasses to Provide Connectivity and Prevent Genetic Isolation. Conservation Biology. 23(3) : 548-556. https://doi.org/10.1111/j.1523-1739.2008.01162.x
  9. Erritzoe, J․TD Mazgajski and L Rejt. 2003. Bird Casualties on European Roads - A Review. Acta Ornithologica 38(2) : 77-93. https://doi.org/10.3161/068.038.0204
  10. Huh YS. 2014. Evaluation and Activation Plan of Urban Eco-corridors for Linkage of Seoul's North and South Green Network. Seoul National University Master Thesis.
  11. Jongman, RHG․M Kulvik and Ib Kristiansen. 2004. European ecological networks and greenways. 68 : 305-319. https://doi.org/10.1016/S0169-2046(03)00163-4
  12. Kim, CH․CS Lee and YS Woo. 2007. Study on Compact City Model for Sustainable New Town Development in Korea. Korea Planning Association. 42(2) : 49-68. (in Korean with English summary)
  13. KNPS(Korea National Park Service). 2016. National park wildlife roadkill and ecological pathway monitoring.
  14. KNPS(Korea National Park Service). 2013. National Park Wildlife Roadkill Reduction Report.
  15. Korea Land Corporation. 1997. Bundang New Town Development History.
  16. Mazerolle, MJ and MA Villard. 1999. Patch characteristics and landscape context as predictors of species presence and abundance: A review. Ecoscience. 6 : 117-124. https://doi.org/10.1080/11956860.1999.11952204
  17. ME(Ministry of Environment). 2010. Guidelines for Design and Management of Wildlife Crossing Structures in Korea.
  18. NIE(National Institute of Ecology). 2020. Ecological Corridors map services. https://wildlifecrossing.nie.re.kr/mapservice/MapserviceList.do
  19. Noss, RF and LD Harris. 1986. Nodes, networks, and MUMs: Preserving diversity at all scales. Environmental Management. 10 : 299-309. https://doi.org/10.1007/BF01867252
  20. Peng, J․H Zhao and Y Liu. 2017. Urban ecological corridors construction: A review. Acta Ecologica Sinica. 37(1) : 23-30. https://doi.org/10.1016/j.chnaes.2016.12.002
  21. Prugh, LR․KE Hodges․ARE Sinclair and JS Brashares. 2008. Effect of habitat area and isolation on fragmented animal populations. PNAS. 105(52) : 20770-20775. https://doi.org/10.1073/pnas.0806080105
  22. Rovero F.M Tobler. J Sanderson. 2010. Camera trapping for inventorying terrestrial vertebrates. Manual on field recording techniques and protocols for All Taxa Biodiversity Inventories and Monitoring. The Belgian National Focal Point to the Global Taxonomy Initiative. 100-128.
  23. Smith, DJ.․R. Ree.․C. Rosell. 2015. Wildlife crossing structures. Handbook of Road Ecology. 172-183.
  24. Schneider, S․S Greenberg․GW Taylor and SC Kremer. 2020. Three critical factors affecting automated image species recognition performance for camera traps. Ecology and Evolution. 10(7) : 3503-3517. https://doi.org/10.1002/ece3.6147
  25. Song, IJ. 2006. Analysis on the Effect of Ecological Corridor in Seoul and Construction of Management Maunal. Seoul Development Institute.
  26. Swanson, A․M Kosmala․C Lintott․R Simpson ․A Smith and C Packer. 2016. Snapshot Serengeti, high-frequency annotated camera trap images of 40 mammalian species in an African savanna. Scientific Data 2. 150026. https://doi.org/10.1038/sdata.2015.26
  27. Tabak, MA․MS Norouzzadeh․DW Wolfson․SJ Sweeney․KC Vercauteren․NP Snow․JM Halseth․PA Di Salvo․JS Lewis․MD White․B Teton․JC Beasley․PE Schlichting․RK Boughtion․B Wight․ES Newkirk․JS Ivan․EA Odell․RK Brook․PM Lukacs․AK Moeller․EG Mandevillev․J Clune and RS Miller. 2018. Machine learning to classify animal species in camera trap images Applications in ecology. Methods in Ecology and Evolution. 10(4) : 585-590.
  28. Thronton, DH․LC Branch and ME Sunquist. 2011. The influence of landscape, patch, and within-patch factors on species presence and abundance: a review of focal patch studies. Landscape Ecology in Review. 26 : 7-18. https://doi.org/10.1007/s10980-010-9549-z
  29. Treves, A․P Mwima․AJ Plumptre․S Isoke. 2010. Camera-trapping forest-woodland wildlife of western Uganda reveals how gregariousness biases estimates of relative abundance and distribution. Biological Conservation, 143(2) : 521-528. https://doi.org/10.1016/j.biocon.2009.11.025
  30. Underhill, JE.PG Angold. 1999. Effects of roads on wildlife in an intensively modified landscape. Environmental Reviews. 8(1) : 21-39. https://doi.org/10.1139/a00-003
  31. Watling, JI and MA Donnelly. 2006. Fragments as Islands: a Synthesis of Faunal Responses to Habitat Patchiness. Conservation Biology. 20(4) : 1016-1025. https://doi.org/10.1111/j.1523-1739.2006.00482.x
  32. Woo, DG․TY Choi․HS Seo․DH Lee․YS Park․HB Park․HG Moon․JG Cha․SM Lee․HY Park․BS Seo․JG Jung․JJ Park․SG Lee․YJ Park․GY Cheon․KA Kim․JM Kim and JC Choi. 2015. A study on analysis of habitat fragmentation and improvement of wildlife passage effectiveness. National Institute of Ecology. (in Korean with English summary)