Korean Journal of Environment and Ecology (한국환경생태학회지)

Korean Society of Environment and Ecology (한국환경생태학회)
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Potential Habitats and Change Prediction of Machilus thunbergii Siebold & Zucc. in Korea by Climate Change

기후변화에 따른 한반도 후박나무의 잠재 생육지 및 변화예측

  • Yun, Jong-Hak (Plant Resources Division, National Institute of Biological Resource) ;
  • Nakao, Katsuhiro (Department of Plant Ecology, Forestry and Forest Products Research Institute) ;
  • Park, Chan-Ho (Plant Resources Division, National Institute of Biological Resource) ;
  • Lee, Byoung-Yoon (Plant Resources Division, National Institute of Biological Resource)
  • Received : 2011.10.17
  • Accepted : 2011.12.01
  • Published : 2011.12.31
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Abstract

The research was carried out in order to find climate factors which determine the distribution of Machilus thunbergii, and the potential habitats under the current climate and three climate change scenario by using classification tree (CT) model. 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. The model of distribution for Machilus thunbergii (Mth-model) constructed by CT analysis showed that minimum temperature of the coldest month (TMC) is a major climate factor in determining the distribution of M. thunbergii. The area above the $-3.3^{\circ}C$ of TMC revealed high occurrence probability of the M. thunbergii. Potential habitats was predicted $9,326km^2$ under the current climate and $61,074{\sim}67,402km^2$(South Korea: $58,419{\sim}61,137km^2$, North Korea: $2,655{\sim}6,542km^2$) under the three climate change scenarios (CCCMA-A2, CSIRO-A2, HADCM3-A2). The Potential habitats was to predicted increase by 51~56%(South Korea: 49~51%, North Korea: 2~5%) under the three climate change scenarios. The potential expand of M. thunbergii habitats has been expected that it is competitive with warm-temperate deciduous broadleaf forest. M. thunbergii is evaluated as the indicator of climate change in Korea and it is necessary for M. thunbergii to monitor of potential habitats.

본 연구는 기후변화에 따른 한반도 후박나무의 분포를 규정하는 기후요인과 현재기후와 미래기후에서의 잠재 생육지를 CT모델을 이용하여 예측하였다. 모델 구축을 위한 4개 독립변수로는 최한월최저기온(TMC), 온량지수(WI), 하계강수량(PRS), 동계강수량(PRW)을 사용하였다. CT분석을 통해 구축된 후박나무 분포 모델(Mth-model)에서 TMC(최한월최저기온)가 분포를 규정하는 주요요인으로 작용하였으며, TMC(최한월최저기온) $-3.3^{\circ}C$이상인 지역에서 후박나무의 높은 출현확률을 나타냈다. 현재기후에서 한반도 후박나무의 잠재 생육지(PH)는 $9,326km^2$로 예측되었으며, 3종류 미래기후 시나리오(CCCMA-A2, CSIRO-A2, HADCM3-A2)에서 $61,074{\sim}67,402km^2$(남한: $58,419{\sim}61,137km^2$, 북한:$2,655{\sim}6,542km^2$)로 예측되었다. 미래기후에서 잠재 생육지는 49~51%(남한: 49~51%, 북한: 2~5%) 증가된 면적이 예측되었다. 기후변화에 따라 한반도 후박나무의 잠재 생육지의 확대는 난온대 낙엽활엽수림과 경쟁이 예상된다. 후박나무는 한반도 기후변화 지표종으로 유효하다고 판단되며 잠재 생육지에 대한 지속적인 모니터링이 중요하다.

Keywords

References

  1. 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
  2. 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 and Brooks/Cole Advanced Books and Software, Pacific Grove, pp. 377-419.
  3. De'Ath, G. and K.E. Fabricius(2000) Classification and regression trees: A powerful yet simple technique for ecological data analysis. Ecology 81(11): 3,178-3,192. https://doi.org/10.1890/0012-9658(2000)081[3178:CARTAP]2.0.CO;2
  4. Hanley, J. and B. McNeil(1982) The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143: 29-36. https://doi.org/10.1148/radiology.143.1.7063747
  5. 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.
  6. 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
  7. Huntley, B.(1991) How plants respond to climate change: Migration rates, individualism and the consequences for plant communities. Annals of Botany 67: 15-22. https://doi.org/10.1093/oxfordjournals.aob.a088205
  8. Huntley, B., P.M. Berry, W. Cramer and A.P. McDonald(1995) Modelling present and potential future ranges of some European higher plants using climate response surfaces. Journal of Biogeography 22: 967-1001. https://doi.org/10.2307/2845830
  9. 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.
  10. 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
  11. Iverson, L.R., A.M. Prasad, B.J. Hale and E.K. Sutherland(1999) An Atlas of Current and Potential Future Distributions of Common Trees of the Eastern United States, Gen. Tech. Rep. NE-265, US. Department of Agriculture, Forest Service, Northeastern Research Station.
  12. 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.
  13. 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 J. Pl. Taxon. 40: 202-207. https://doi.org/10.11110/kjpt.2010.40.4.202
  14. Lee, J.H. and B.H. Choi(2010) Distribution and northernmost limit on the Korean Peninsula of three evergreen trees. Korean J. Pl. Taxon. 40: 267-273. (in Korean with English abstract) https://doi.org/10.11110/kjpt.2010.40.4.267
  15. 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
  16. 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.
  17. 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.
  18. Metz, C.E.(1978) Basic principles of ROC Analysis. Seminars in Nuclear Medicine 8: 283-298. https://doi.org/10.1016/S0001-2998(78)80014-2
  19. Nakao, K., T. Matusi, N. Tanaka and T. Hukusima(2009) Climatic controls of the distribution and abundance of two evergreen Quercus species in Japan. Jpn. J. For. Environment 51(1): 27-37. (in Japanese with English abstract)
  20. Nogami, M.(1994) Thermal condition of the forest vegetation zones and their potential distribution under different climates in Japan. J. of geography 103: 886-897. (in Japanese with English abstract) https://doi.org/10.5026/jgeography.103.7_886
  21. Normand, S., J.C. Svenning and F. Skov(2007) National and European perspectives on climate change sensitivity of the habitats directive characteristic plant species. 15: 41-53. https://doi.org/10.1016/j.jnc.2006.09.001
  22. Ohsawa, M.(1990) An interpretation in latitudinal patterns of limits in south and east Asian mountains. J. Eco. 78: 326-339.
  23. Ohsawa, M.(1991) Structural comparison of tropical mountain rain-forests along latitudinal and altitudinal gradients in south and east-Asia. Vegetatio 97:1-10.
  24. Ohsawa, M.(1993) Latitudinal pattern of mountain vegetation zonation in southern and eastern Asia. Journal of Vegetation Science 4: 13-18. https://doi.org/10.2307/3235728
  25. 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.
  26. Swets, K.A.(1988) Measuring the accuracy of diagnostic systems. Science 240: 1285-1293. https://doi.org/10.1126/science.3287615
  27. Takahashi, K., Y. Matsuoka, T. Okamura and H. Harasawa(2001) Development of climate change secnarios for impact assessment using results of General Circulation Model simulations. Journal of Global Environmental Engineering 7: 31-45.
  28. Tanaka, N.(2007) PRDB (Phytosociological Relevé Data Base). Environment change impact team, Forestry and Forest Products Research Institute. Available at URL://www.ffpri.affrc.go.jp/ labs/prdb/index-e.html.
  29. 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.
  30. Thuiller, W.(2003) BIOMOD-optimizing predictions of species distributions and projecting potential shifts under global change. Global Change Biology 9: 1,353-1,362.
  31. Thuiller, W., S. Lavorel, M.B. Araújo, 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: 8,245-8,250. https://doi.org/10.1073/pnas.0409902102
  32. Tsunekawa, A., H, Ikeguchi and K. Omasa(1993) Effects of climatic change on the vegetation distribution in response to climatic change. In: Omsa, K., K. Kai, H. Taoda, Z. Uchijima and M. Yoshino eds., Climate change and Plant in East Asia, Springer 57-65.
  33. Tsuyama, I., T. Matsui, M. Horikawa, Y. Kominami and N. Tanaka(2008b) Habitat prediction and impact assessment of climate change on dwarf bamboo of the Section Sasa in Japan. Theory and Applications of GIS. 16(2): 11-25. (in Japanese with English abstract)
  34. Tsuyama, I., T. Matsui, M. Ogawa, Y. Kominami and N. Tanaka(2008a) Habitat prediction and impact assessment of climate change on Sasa Kurilensis in eastern Honshu, Japan. Theory and Applications of GIS. 16(1): 11-25. (in Japanese with English abstract)
  35. 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. Jap. J. Ecol. 21: 269-278.
  36. Yun, J.H., J.H. Kim, K.H. Oh and B.Y. Lee(2011a) Distributional change and climate conditions of warm-temperate evergreen broad-leaved trees in Korea. Kor. J. Env. Eco. 25: 47-56. (in Korean with English abstract)
  37. Yun, J.H., K. Nakao, C.H. Park, B.Y. Lee and K.H. Oh(2011b) Change prediction for Potential Habitats of Warm-temperate Evergreen Broad-leaved Trees in Korea by Climate Change. Kor. J. Env. Eco. 25: 590-600. (in Korean with English abstract)
  38. Zweig, M.H. and G. Campbell(1993) Receiver-operating characteristic (ROC) Plots: a fundamental evaluation tool in clinical medicine. Climical Chemistry. 39: 561-577.