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Prediction of Potential Habitat and Damage Amount of Rare·Endemic Plants (Sophora Koreensis Nakai) Using NBR and MaxEnt Model Analysis - For the Forest Fire Area of Bibongsan (Mt.) in Yanggu -

NBR과 MaxEnt 모델 분석을 활용한 희귀특산식물(개느삼) 분포 및 피해량 예측 - 양구 비봉산 산불피해지를 대상으로-

  • Received : 2022.01.11
  • Accepted : 2022.02.04
  • Published : 2022.04.01

Abstract

This study was conducted to predict the distribution of rare·endemic plants (Sophora koreensis Nakai) in the border forests where wildfire damage occurred and to quantify the damage. For this purpose, we tried to derive more accurate results through forest area damage (NBR) according to the Burn severity of wildfires, damage by tree species type (Vegetation map), and MaxEnt model. For Burn severity analysis, satellite imagery (Landsat-8) was used to analyze Burn severity (ΔNBR2016-2015) and to derive the extent of damage. To prepare the Vegetation map, the land cover map prepared by the Ministry of Environment, the Vegetation map prepared by the Korea Forest Service, and the vegetation survey conducted by itself were conducted to prepare the clinical map before and after the forest fire. Lastly, for MaxEnt model analysis, the AUC value was derived by using the habitat coordinates of Sophora koreensis Nakai based on the related literature and self-report data. As a result of combining the Maxent model analysis data with the Burn severity data, it was confirmed that 45.9% of the 44,760 m2 of habitat (predicted) area of Sophora koreensis Nakai in the wildfire damaged area or 20,552 m2, was damaged.

본 연구는 산불피해가 발생한 접경지역 산림 내 희귀특산식물(개느삼) 분포를 예측하고 피해를 정량화하고자 수행되었다. 이를 위해 산불피해강도에 따른 산림면적 피해(NBR), 임상도를 통한 수종별 피해(Vegetation map), MaxEnt 모델 분석을 수행, 보다 정밀한 결과를 도출하고자 하였다. 우선, 산불피해강도 분석은 위성영상(Landsat-8)을 활용하여, 산불피해강도(ΔNBR2016-2015)를 분석하고 피해범위를 도출하였다. 임상도 작성은 환경부의 토지피복도, 산림청의 임상도, 자체적으로 식생조사를 진행하여, 산불 전·후의 임상도를 작성하고, 수종 피해 및 변화를 확인하였다. 마지막으로 MaxEnt 모델 분석은 관련문헌과 자체조사 자료를 기준으로 작성된 개느삼 실제서식지 좌표를 활용하여, AUC(Area Under Curve) 값을 도출하였다. 분석된 결과의 정밀도를 높이고자, 임상도와 결합하여, 개느삼이 주로 분포하는 소나무 군락 및 소나무-참나무림 군락을 대상으로 재분석한 결과, 대상지 내 개느삼 실제출현 좌표 325개소 중 299개 지점에서 개느삼 출현가능성이 92.0%로 예측되어 유의미한 결과를 얻을 수 있었다. 해당 자료를 산불피해강도(ΔNBR2016-2015) 자료와 중첩한 결과, 산불피해지 내 개느삼 서식가능지(예측) 면적 44,760 m2의 45.9%인 20,552 m2가 훼손된 것을 확인할 수 있었다. 따라서 본 연구는 산불로 인해 훼손된 희귀식물 서식지 면적을 정량화하고 희귀식물 보전·관리를 위한 사례가 될 것으로 기대된다.

Keywords

References

  1. An, J.B. 2019. Conservation strategies and vegetation characteristics of Echinosophora koreensis of Korean endemic plants. Department of Forest Resources, Ph. D. Thesis, Gangwon Nat'l Univ., Korea. pp. 1-149 (in Korean).
  2. Cocke, A.E., P.Z. Fule and J.E. Crouse. 2005. Comparison of burn severity assessments using differenced normalized burn ratio and ground data. Int. J. Wildland Fire 14(2):189-198. https://doi.org/10.1071/WF04010
  3. Elith, J., S.J. Phillips, T. Hastie, M. Dudik, Y.E. Chee and C.J. Yates. 2011. A statistical explanation of MaxEnt for ecologist. Diversity and Distributions 17(1):43-57. https://doi.org/10.1111/j.1472-4642.2010.00725.x
  4. Granstrom, A. 2001. Fire management for biodiversity in the European boreal forest. Scand J For Res. 16(1):62-69. https://doi.org/10.1080/028275801300090627
  5. Key, C.H. and N.C. Benson. 2002. Measuring and remote sensing of burn severity. US Geological Survey Wildland Fire Workshop, Los Almos, NM (USA), p. 2.
  6. Key, C.H. and N.C. Benson. 2005. Landscape assessment: Ground measure of severity the composite burn index, Firemon: Fire effects monitoring and inventory system. General Technical Report. Oregan (USA). p. 51.
  7. Korea Forest Research Institute. 2000. East coast forest fire area detailed survey report for restoration of healthy natural ecosystem and establishment of permanent forest restoration plan. Korea Forest Research Institute, Seoul, Korea. pp. 1-311 (in Korean).
  8. Korea Forest Service. 2021a. 2020 Forest basic statistics. Korea Forest Service, Sejong, Korea. pp. 1-371 (in Korean)
  9. Korea Forest Service. 2021b. Forest common sense. (accessed on 10 June 2021). https://www.forest.go.kr/kfsweb/kfi/kfs/cms/cmsView.do?mn=NKFS_03_06_01_01&cmsId=FC_001569.
  10. Korea Forest Service. 2021c. Forest forestry statistics platform: Status of wildfire damage. (accessed on 15 april 2021). https://kfss.forest.go.kr/stat/ptl/stat/statDtl.do?curMenu=3194&statSeq=5215.
  11. Korea Forest Service. 2021d. Forest geo-spatial information service. (accessed on 2 april 2021). https://map.forest.go.kr/forest/.
  12. Kreisel, K.J. and S.J. Stein. 1999. Bird use of burned and unburned coniferous forest during winter. Wilson Bulletin. 111:243-250.
  13. Lee, G.S. and S.D. Park. 2004. Development of vegetation structure after forest fire in the east coastal region Korea. J. Eco. Env. 27(2):99-106 (in Korean).
  14. Lopez-Garcia, M. and V. Caselles. 1991. Mapping burns and natural reforestation using thematic mapper data. Geocarto Int. 6:31-37.
  15. Ma, H.S. and W.O. Jeong. 2008. Long-term change of the amount of soil erosion in forest fire damaged area. J. Korean Soc. For. Sci. 97(4):363-367 (in Korean).
  16. Marques, M.A. and E. Mora. 1998. Effects on erosion of two postfire management practices: clear-cutting versus non-intervention. Soil Tillage Res. 45(3):433-439. https://doi.org/10.1016/S0933-3630(97)00039-1
  17. Ministry of Environment. 2021. Environmental geospatial information service. (accessed on 4 april 2021). https://egis.me.go.kr/main.do.
  18. National Institute for Disaster Prevention. 2003. Observation and counseling measures for rainwater and soil runoff in mountainous areas. National Institute for Disaster Prevention, Seoul, Korea. pp. 1-173 (in Korean).
  19. National Institute of Environmental Research. 2017. 2016 DMZ ecosystem survey: eastern mountain region north of civil control Line. National Institute of Environmental Research. Incheon, Korea. pp. 1-545 (in Korean).
  20. Phillips, S.J., R.P. Anderson and R.E. Schapire. 2006. Maximum entropy modeling of species geographic distributions. Ecol. Modell. 190(3):231-259. https://doi.org/10.1016/j.ecolmodel.2005.03.026
  21. Phillips, S.J., R.P. Anderson, M. Dudik, R.E. Schapire and M.E. Blair. 2017. Opening the black box: An open-source release of maxent. Ecography 40:887-893. https://doi.org/10.1111/ecog.03049
  22. Roy, D.P., L. Boschetti and S.N. Trigg. 2006. Remote sensing of fire severity: assessing the performance of the normalized burn ratio. IEEE Geosci Remote Sens Lett. 3(1):112-116. https://doi.org/10.1109/LGRS.2005.858485
  23. Seo, C.W., Y.R. Park and Y.S. Choi. 2008. Comparison of species distribution models according to location data. J. Korean Soc. GIS. 16(4):59-64 (in Korean).
  24. Sung, C.Y., H.T. Shin, S.H. Choi and H.S. Song. 2018. Predicting potential habitat for Hanabusaya asiatica in the north and south Korean border region using maxent. Korean J. Environ. Ecol. 32(5):469-477 (in Korean). https://doi.org/10.13047/KJEE.2018.32.5.469
  25. United States Department of Agriculture. 2021. Remote sensing applications center. (accessed on 1 March 2021). http://fsweb.rsac.fs.fed.us.
  26. United States Geological Survey. 2021. USGS earth explorer. (accessed on 10 April 2021). https://earthexplorer.usgs.gov/
  27. van Wagtendonk, J.W., R.R. Root and C.H. Key. 2004. Comparison of AVIRIS and landsat ETM+ detection capabilities for burn severity. Remote Sens. Environ. 92(3):397-408. https://doi.org/10.1016/j.rse.2003.12.015
  28. Won, M.S., K.S. Koo and M.B. Lee. 2007. An quantitative analysis of severity classification and burn severity for the large forest fire areas using normalized burn ratio of landsat imagery. Journal of the KAGIS 10(3):80-92 (in Korean).
  29. Won, M.S., K.S. Koo, M.B. Lee and Y.M. Son. 2008. Estimation of non-CO2 greenhouse gases emissions from biomass burning in the Samcheok large-fire area using landsat TM imagery. Korean J. AFM. 10(1):1-24 (in Korean).
  30. You, J.H and S.Y. Kwon. 2019. Analysis on vegetation change of forest fire damaged area in Sogeumgang district, Gyeongju national park. J. Korean Env. Res. Tech 22(4):47-64 (in Korean).
  31. Yun, H.G., A.Y. Lee, J.B. An, T.Y. Hwang and J.W. Lee. 2021. A study on the vascular flora and its management plan at the forest genetic resource reserve of Mt. Munsu (Gimpo). Korean J. Plant Res. 34(4):311-338 (in Korean). https://doi.org/10.7732/KJPR.2021.34.4.311