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앙상블 기후 시나리오 자료를 활용한 우리나라 잣나무림 분포 적지 전망

Predicting the Potential Distribution of Korean Pine (Pinus koraiensis) Using an Ensemble of Climate Scenarios

  • 김재욱 (한국환경정책.평가연구원) ;
  • 정휘철 (한국환경정책.평가연구원) ;
  • 전성우 (고려대학교 환경생태공학부) ;
  • 이동근 (서울대학교 조경.지역시스템공학부)
  • Kim, Jaeuk (Korea Environment Institute) ;
  • Jung, Huicheul (Korea Environment Institute) ;
  • Jeon, Seong Woo (Division of Environmental Science and Ecological Engineering, Korea University) ;
  • Lee, Dong-Kun (Dept. of Landscape Architecture and Rural System Engineering, Seoul National University)
  • 투고 : 2015.03.12
  • 심사 : 2015.04.27
  • 발행 : 2015.04.30

초록

Preparations need to be made for Korean pine(Pinus koraiensis) in anticipation of climate change because Korean pine is an endemic species of South Korea and the source of timber and pine nut. Therefore, climate change adaptation policy has been established to conduct an impact assessment on the distribution of Korean pine. Our objective was to predict the distribution of Korean pine while taking into account uncertainty and afforestation conditions. We used the 5th forest types map, a forest site map and BIOCLIM variables. The climate scenarios are RCP 4.5 and RCP 8.5 for uncertainty and the climate models are 5 regional climate models (HadGEM3RA, RegCM4, SNURCM, GRIMs, WRF). The base period for this study is 1971 to 2000. The target periods are the mid-21st century (2021-2050) and the end of the 21st century (2071-2100). This study used the MaxEnt model, and 50% of the presences were randomly set as training data. The remaining 50% were used as test data, and 10 cross-validated replicates were run. The selected variables were the annual mean temperature (Bio1), the precipitation of the wettest month (Bio13) and the precipitation of the driest month (Bio14). The test data's ROC curve of Korean pine was 0.689. The distribution of Korean pine in the mid-21st century decreased from 11.9% to 37.8% on RCP 4.5 and RCP 8.5. The area of Korean pine at an artificial plantation occupied from 32.1% to 45.4% on both RCPs. The areas at the end of the 21st century declined by 53.9% on RCP 4.5 and by 86.0% on RCP 8.5. The area of Korean pine at an artificial plantation occupied 23.8% on RCP 4.5 and 7.2% on RCP 8.5. Private forests showed more of a decrease than national forests for all subsequent periods. Our results may contribute to the establishment of climate change adaptation policies for considering various adaptation options.

참고문헌

  1. Ahmed, M..N. Khan.M. Wahab.U. Zafar and J. Palmer. 2012. Climate/Growth correlations of tree species in the Indus basin of the Karakorum range, North Pakistan. IAWA Journal 33 (1): 51-61. https://doi.org/10.1163/22941932-90000079
  2. Ayebare, S..R. Ponce-Reyes.D. B. Segan.J. E. M. Watson.H. P. Possingham.A. Seimon and A. J. Plumptre. 2013. Identifying climate-resilient corridors for conservation in the Albertine Rift. Unpublished Report by the Wildlife Conservation Society to MacArthur Foundation.
  3. Chun JH. 2013. Assessing the Effects of Climate Change on the Geographic Distribution of Major Tree Species in Korea using Ecological Niche Model. PhD Thesis. Kookmin University, Seoul, Korea. (in Korean with English summary)
  4. Heibl, C. and S. S. Renner. 2012. Distribution Models and a Dated Phylogeny for Chilean Oxalis Species Reveal Occupation of New Habitats by Different Lineages, not Rapid Adaptive Radiation. Systematic Biology 61(5): 823-834. https://doi.org/10.1093/sysbio/sys034
  5. Hu, J. and Z. Jiang. 2011. Climate Change Hastens the Conservation Urgency of an Endangered Ungulate. PLOS ONE 6(8): e22873. doi:10.1371/journal.pone.0022873. https://doi.org/10.1371/journal.pone.0022873
  6. Jeon SW.Kim JU.Jung HC.Lee WK and Kim JS. 2014. Species Distribution Modeling of Endangered Mammals for Ecosystem Services Valuation - Focused on National Ecosystem Survey Data. Journal of the Korea Society of Environmental Restoration Technology 17(1): 111-122. (in Korean with English summary) https://doi.org/10.13087/kosert.2014.17.1.111
  7. Kim JY.Seo CW.Kwon HS.Ryu JE and Kim MJ. 2012. A Study on the Species Distribution Modeling using National Ecosystem Survey Data. Journal of Environmental Impact Assessment 21(4): 593-607. (in Korean with English summary) https://doi.org/10.14249/EIA.2012.21.4.593
  8. Kim TW. 2013. Estimation of Productive Areas for Common Tree Species in South Korea Based on Ecoprovinces and Environmental Factors. MS Thesis. Kookmin University, Seoul, Korea. (in Korean with English summary)
  9. Kim YK. 2012. Changes in potential distribution of major coniferous plantations to climate changes in Korea. MS Thesis. Korea University, Seoul, Korea. (in Korean with English summary)
  10. Korea Forest Research Institute. 2014. Prediction the Changes of Productive Areas for major Tree Species under Climate Change in Korea. Report 14-21.
  11. Korea Forest Service. 2014a. Production of Forest Products 2014.
  12. Korea Forest Service. 2014b. Statistical Yearbook of Forestry No. 44.
  13. Korea Forestry Promotion Institute. 2014. The Domestic Timber Market Price Trends.
  14. Lee YS.Sung JH.Chun JH and Shin MY. 2012. Development of Site Index Equations and Assessment of Productive Areas Based on Environmental Factors for Major Coniferous Tree Species. Journal of Korean Forest Society 101(3): 395-404. (in Korean with English summary)
  15. Phillips, S. J..R. P. Anderson and R. E. Schapire. 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
  16. Rehfeldt, G. E..N. L. Crookston.M. V. Warwell and J. S. Evans. 2006. Empirical Analyses of Plant-Climate Relationships for the Western United States. International Journal of Plant Sciences 167(6): 1123-1150 https://doi.org/10.1086/507711
  17. Seo CW.Park YR and Choi YS. 2008. Comparison of Species Distribution Models According to Location Data. Journal of the Korean society for geo-spatial information system 16(4): 59-64. (in Korean with English summary)
  18. Shin MY.Jung IB.Koo KS and Won HG. 2006. Development of a Site Index Equation for Pinus koraiensis Based on Environmental Factors and Estimation of Productive Areas for Reforestation. Korean Journal of Agricultural and Forest Meteorology 8(2): 97-106. (in Korean with English summary)
  19. Song WK and Kim EY. 2012. A Comparison of Machine Learning Species Distribution Methods for Habitat Analysis of the Korea Water Deer(Hydropotes inermis argyropus). Korean Journal of Remote Sensing 28(1): 171-180. (in Korean with English summary) https://doi.org/10.7780/kjrs.2012.28.1.171
  20. Tronstad, L. and M. Andersen. 2011. Monitoring Rare Land Snails in the Black Hills National Forest. Report prepared by the Wyoming Natural Diversity Database, Laramie, Wyoming for the Black Hills National Forest Service, Custer, South Dakota.