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Habitat prediction and impact assessment of Neolitsea sericea (Blume) Koidz. under Climate Change in Korea

기후변화에 따른 한반도 참식나무 생육지 예측과 영향 평가

  • Yun, Jong-Hak (Ecosystem assessment team, National Institute of Ecology) ;
  • Nakao, Katsuhiro (Dep. of Plant Ecology, Forestry and Forest Products Research Institute) ;
  • Kim, Jung-Hyun (Plant Research Division, National Institute of Biological Resource) ;
  • Kim, Sun-Yu (Plant Research Division, National Institute of Biological Resource) ;
  • Park, Chan-Ho (Plant Research Division, National Institute of Biological Resource) ;
  • Lee, Byoung-Yoon (Plant Research Division, National Institute of Biological Resource)
  • Received : 2013.11.28
  • Accepted : 2014.02.18
  • Published : 2014.04.30

Abstract

The research was carried out in order to find climate factors which determine the distribution of Neolitsea sericea, and the potential habitats (PHs) under the current climate and three climate change scenario by using species distribution models (SDMs). Four climate factors; the minimum temperature of the coldest month (TMC), the warmth index (WI), summer precipitation (PRS), and winter precipition (PRW) : were used as independent variables for the model. Three general circulation models under A1B emission scenarios were used as future climate scenarios for the 2050s (2040~2069) and 2080s (2070~2099). Highly accurate SDMs were obtained for N. sericea. The model of distribution for N. sericea constructed by SDMs showed that minimum temperature of the coldest month (TMC) is a major climate factor in determining the distribution of N. sericea. The area above the $-4.4^{\circ}C$ of TMC revealed high occurrence probability of the N. sericea. Future PHs for N. sericea were projected to increase respectively by 4 times, 6.4 times of current PHs under 2050s and 2080s. It is expected that the potential of N. sericea habitats is expanded gradually. N. sericea is applicable as indicator species for monitoring in the Korean Peninsula. N. sericea is necessary to be monitored of potential habitats.

Keywords

References

  1. 김중현, 윤종학, 남기흠, 이정현, 최병희, 이병윤, 2011, 덕적군도 내 무인도서의 관속식물상 연구, 한국환경과학회지, 20, 1-23. https://doi.org/10.5322/JES.2011.20.1.1
  2. 이창복, 1980, 대한식물도감, 향문사, 서울.
  3. 이우철, 임양재, 2002, 식물지리, 강원대학교, 춘천.
  4. 윤종학, 中尾勝洋, 박찬호, 이병윤, 2011a, 기후변화에 따른 한반도 후박나무의 잠재 생육지및 분포예측, 한국환경생태학회지, 25, 903-910.
  5. 윤종학, 김중현, 오경희, 이병윤, 2011b, 한반도 난온대 상록활엽수의 분포변화와 기후조건, 한국환경생태학회지, 25, 47-56.
  6. 中尾勝洋, 松井哲哉, 田中信行, 福島 司, 2009, 日本における常綠カシ類2種の個および優占林の分布を規定する候 件, 日本立地学会誌 森林立地, 51, 27-37.
  7. 津山幾太郞, 松井哲哉, 小川みふゆ, 小南裕志, 田中信行, 2008, 本州東部におけるチチマザサの潜在分布域の予測と気候変化の影響評価, GIS-理論と応用, 16, 11-25.
  8. Armonies, W. and K. Reise, 2003, Empty habitat in coastal sediments for populations of macrozoobenthos, Helgoland Mar Research, 56, 279-287.
  9. Clark, L. A. and D. Pregibon, 1992, Tree-based models, In: J. M. Chambers and T. J. Hastie, eds., Statistical Models in S, California, Wadsworth & Brooks/Cole Advanced Books & Software, Pacific Grove, pp.377-419.
  10. De'Ath, G., and K. E. Fabricius, 2000, Classification and regression trees: A powerful yet simple technique for ecological data analysis, Ecology, 81, 3178-3192. https://doi.org/10.1890/0012-9658(2000)081[3178:CARTAP]2.0.CO;2
  11. Bakkenes, M., J. R. M. Alkemade, F. Ihle, R. Leemans and J. B. Latour, 2002, Assessing effects of forecasted climate change on the diversity and distribution of European higher plants for 2050, Global Change Biology, 8, 390-407. https://doi.org/10.1046/j.1354-1013.2001.00467.x
  12. Berry, P. M., T. P. Dawson, P. A. Harrison, R. Pearson and N. Butt, 2003, The sensitivity and vulnerability of terrestrial habitats and species in Britain and Ireland to climate change, Journal of Nature Conservation, 11, 15-23. https://doi.org/10.1078/1617-1381-00030
  13. Breiman, L., J. H. Friedman, R. A. Olshen and C. J. Stone, 1984, Classification and regression trees, Chapman & Hall/CRC, Boca Raton, FL, US, 358pp.
  14. Hanley, J. and B. McNeil, 1982, The meaning and use of the area under areceiver operating characteristic (ROC) curve, Radiology, 143, 29-36. https://doi.org/10.1148/radiology.143.1.7063747
  15. Harrison, P. A., P. M. Berry and T. P. Dawson, eds., 2001, Climate Change and Nature Conservation in Britain and Ireland: Modelling Natural Resource Responses to Climate Change (the MONARCH project), UKCIP Technical Report, Oxford.
  16. Horikawa, M., I. Tsuyama, T. Matsui, Y. Kominami and N. Tanaka, 2009, Assessing the potential impacts of climate change on the alpine habitat suitability of Japanese stone pine (Pinus pumila), Landscape Ecology, 24, 115-128. https://doi.org/10.1007/s10980-008-9289-5
  17. IPCC, 2007, Climate Change 2007: the Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press.
  18. Iverson, L. R. and A. M. Prasad, 1998, Predicting abundance of 80 tree species following climate change in the eastern United States, Ecological Monographs, 68, 465-485. https://doi.org/10.1890/0012-9615(1998)068[0465:PAOTSF]2.0.CO;2
  19. Kira, T.(1977) A Climatological interpretation of Japanese vegetation zones. In Miyawaki, A. and Tuxen, R. (eds.) Vegetation science and environmental protection. Maruzen, Tokyo, pp.21-30.
  20. Lee, B. Y., G. H. Nam, J. H. Yun, G. Y. Cho, J. S. Lee, J. H. Kim, T. S. Park, K. K. Kim and K. H. Oh, 2010, Biological indicators to monitor responses against climate change in Korea, Korean Journal of Plant Taxonomy, 40, 202-207.
  21. MaCarthy, J. J., O. F. Canziani, N. A. Leary, D. J. Dokken and K. S. White, eds., 2001, Cimate Change 2001: Impacts, Adaptation, and Vulnerability, Cambridge: Cambridge University Press.
  22. Matsui, T., N. Tanaka, T. Yagihashi, Y. Kominami, I. Tsuyama and K. Takahashi, 2009, Prediction and impact assessment of the changes in suitable habitats for beech (Fagus crenata) forests under climate change scenarios, Journal of Global Enviroment, 14, 165-174.
  23. Matsui, T., T. Yagihashi, T. Nakaya, H. Taoda and N. Tanaka, 2004a, Climatic controls on distribution of Fagus crenata forests in Japan, Journal of Vegetation Science, 15, 57-66.
  24. Matsui, T., T. Yagihashi, T. Nakaya, H. Taoda S. Yoshinaga, H. Daimaru and N. Tanaka, 2004b, Probability distributions, vulnerability and sensitivity in Fagus crenata forests following predicted climate changes in Japan, Journal of Vegetation Science, 15, 605-614.
  25. Metz, C. E., 1978, Basic principles of ROC Analysis, Seminars in Nuclear Medicine, 8, 283-298.
  26. Ohsawa, M., 1990, An interpretation in latitudinal patterns of limits in south and east Asian mountains, Journal of Ecology, 78, 326-339. https://doi.org/10.2307/2261115
  27. R Development Core Team, 2011, R: A language and environment for statistical computing, R. Foundation for Statistical Computing, Vienna, Austria, ISBN 3-900051-07-0, URL://www.R-project.org.
  28. Swets, K. A., 1988, Measuring the accuracy of diagnostic systems, Science 240, 1285-1293. https://doi.org/10.1126/science.3287615
  29. Tanaka, N., 2007, PRDB (Phytosociological Releve Data Base), Environment change impact team, Forestry and Forest Products Research Institute.
  30. Tanaka, N., E. Nakazono, I. Tsuyama and T. Matsui, 2009, Assessing impact of climate warming on potential habitats of ten conifer species in Japan, Global Environmental Research, 14, 153-164.
  31. Thuiller, W., 2003, BIOMOD-optimizing predictions of species distributions and projecting potential shifts under global change, Global Change Biology, 9, 1353-1362. https://doi.org/10.1046/j.1365-2486.2003.00666.x
  32. Thuiller, W., S. Lavorel, M. B. Araujo, M. T. Sykes and I. C. Prentice, 2005, Climate Change threats to plant diversity in Europe, Proceeding of the National Academy of Sciences of the United States of America, 102, 8245-8250.
  33. Tsuyama,I., K. Nakao, T. Matsui, M. Higa, M. Horikawa, Y. Kominami and N. Tanaka, 2011, Climatic controls of a keystone understory species, Sasamorpha borealis, and an impact assessment of climate change in Japan, Annals of Forest Science, 68, 689-699. https://doi.org/10.1007/s13595-011-0086-y
  34. Yim, Y. J., 1977, Distribution of forest vegetation and climate in the Korea Peninsula, IV. Zonal distribution of forest vegetation in relation to thermal climate, Japanese Journal of Ecology, 21, 269-278.
  35. Zweig, M. H. and G. Campbell, 1993, Receiveroperating characteristic (ROC) Plots: a fundamental evaluation tool in clinical medicine, Climical Chemistry, 39, 561-577.

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