Habitat Potential Evaluation Using Maxent Model - Focused on Riparian Distance, Stream Order and Land Use -

Maxent 모형을 이용한 서식지 잠재력 평가 - 하천으로부터의 거리, 하천의 차수, 토지이용을 중심으로-

  • Lee, Dong-Kun (Department of Landscape Architecture and Rural System Engineering, Seoul National University) ;
  • Kim, Ho-Gul (Graduate School, Seoul National University)
  • 이동근 (서울대학교 조경.지역시스템공학부) ;
  • 김호걸 (서울대학교 대학원)
  • Received : 2010.11.22
  • Accepted : 2010.12.16
  • Published : 2010.12.31

Abstract

As the interest on biodiversity has increased around the world, researches about evaluating potential for habitat are also increasing to find and comprehend the valuable habitats. This study focus on comprehending the significance of stream in evaluating habitat's potential. The purpose of this study is to evaluate habitat potential with applying stream as a main variable, and to comprehend the relationship between the variables and habitat potential. Basin is a unit that has hydrological properties and dynamic interaction with ecosystem. Especially, biodiversity and suitability of habitat in basin area has direct correlation with stream. Existing studies also are proposing for habitat potential evaluation in basin unit, they applied forest, slope and road as main variables. Despite stream is considered the most important factor in basin area, researchers haven't applied stream as a main variable. Therefore, in this study, three variables that can demonstrate hydrological properties are selected, which are, riparian distance, stream order and land use disturbance, and evaluate habitat potential. Habitat potential is analyzed by using Maxent (Maximum entropy model), and vertebrate's presence data is used as dependent variables and stream order map and land cover map is used as base data of independent variables. As a result of analysis, habitat potential is higher at riparian and upstream area, and lower at frequently disturbed area. Result indicates that adjacent to stream, upstream, and less disturbed area is the habitat that vertebrate prefer. In particular, mammals prefer adjacent area of stream and forest and reptiles prefer upriver area. Birds prefer adjacent area of stream and midstream and amphibians prefer adjacent area of stream and upriver. The result of this research could help to establish habitat conservation strategy around basin unit in the future.

Keywords

References

  1. 서창완.최태영.최윤수.김동영, 2008. 설악산 산양을 대상으로 한 서식지 적합성 모형에 관한 연구. 한국환경복원녹화기술학회지 11(3):28-38.
  2. 수자원공사. 2006. 하천차수도.
  3. 이동근.송원경. 2008. 삵의 서식지 적합성 평가를 위한 분석단위 설정 및 보전지역 선정- 충청도 지역을 중심으로-. 한국조경학회 36(5):64-72.
  4. 윤무부. 2005. 재미나는 새와 환경, 군산시 전문가 특강 보고서.
  5. 최희선. 2007. 물순환형 생태도시를 위한 유역차원의 습지조성 입지선정에 관한 연구-환경생태계획 적용방안을 중심으로-. 서울대학교 박사학위논문.
  6. 환경부. 2001. 토지피복도
  7. 환경부. 2005. 2차 자연환경기초조사(1997-2005).
  8. Ekness, P., and T. Randhir. 2007. Effects of riparian areas, stream order, and land use disturbance on watershed-scale habitat potential:an ecohydrologic approach to policy, American water resources association, 43(6):1468-1482. https://doi.org/10.1111/j.1752-1688.2007.00102.x
  9. Elith J., Ferrier S., Huettmann F., and Leathwick J. 2006. The evaluation strip:A new and robust method for plotting predicted responses from species distribution models, Ecol Model, 186(3):280-289.
  10. Murakami, M., and S. Nakano, 2001, Species-Specific Foraging Behavior of Birds in a Riparian Forest, Ecological Research, 16:913-923.
  11. Novak, J. M., P. G. Hunt, K. C. Stone, D. W. Watts and M. H. Johnson. 2002. Riparian Zone Impact on Phosphorus Movement to a Coastal Plain Black Water Stream, Journal of Soil and Water Conservation, 57(7):127-133.
  12. Phillips, S., M. Dudik and R. Schapire. 2004. A Maximum Entropy Approach to Species Distribution Modeling. Proceedings of the 21st International Conference on Machine Learning, Banff, Canada.
  13. Phillips, S., R. Anderson, and R. Schapire. 2006. Maximum entropy modeling of species geographic distributions, Ecological Modelling, 190:231-259. https://doi.org/10.1016/j.ecolmodel.2005.03.026
  14. Steinmetz, J., S. L. Kohler and D. A. Soulk. 2002. Birds Are Overlooked Top Predators in Aquatic Food Webs, Ecology, 84(5):1324-1328.
  15. Store R., and J. Kangas. 2001. Integrating Spatial Multi-criteria Evaluation and Expert Knowledge for GIS-based Habitat Suitability Modelling, Landscape urban palning, 55:79-93. https://doi.org/10.1016/S0169-2046(01)00120-7
  16. Smith, V. H., G. D. Tilman and J. C. Nekola. 1999. Eutrophication:Impacts of Excess Nutrient Inputs on Freshwater, Marine, and Terrestrial Ecosystems, Environmental Pollution, 100(1-3):179-196. https://doi.org/10.1016/S0269-7491(99)00091-3
  17. Tuanmu M. N., Vina A., and Bearer S. et al., 2010. Mapping understory vegetation using phenological characteristics derived from remotely sensed data, Remote Sens Environ (in press).