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Changes in Potential Distribution of Pinus rigida Caused by Climate Changes in Korea  

Kim, Yong-Kyung (Department of Climate Environment, Graduate School of Life & Environmental Sciences, Korea University)
Lee, Woo-Kyun (Department of Climate Environment, Graduate School of Life & Environmental Sciences, Korea University)
Kim, Young-Hwan (Center for Forest & Climate Change, Korea Forest Research Institute)
Oh, Suhyun (Department of Climate Environment, Graduate School of Life & Environmental Sciences, Korea University)
Heo, Jun-Hyeok (Department of Climate Environment, Graduate School of Life & Environmental Sciences, Korea University)
Publication Information
Journal of Korean Society of Forest Science / v.101, no.3, 2012 , pp. 509-516 More about this Journal
Abstract
In this research, it was intended to examine the vulnerability of Pinus rigida to climate changes, a major planting species in Korea. For this purpose, the distribution of Pinus rigida and its changes caused by climate changes were estimated based on the 'A1B' climate change scenario suggested by IPCC. Current distribution of Pinus rigida was analyzed by using the $4^{th}$Forest Type Map and its potential distribution in the recent year (2000), the near future (2050) and the further future (2100) were estimated by analyzing the optimized ranges of three climate indices - warmth index(WI), minimum temperature index of the coldest month (MTCI) and precipitation effectiveness index(PEI). The results showed that the estimated potential distribution of Pinus rigida declines to 56% in the near future(2050) and 15% in the further future (2100). This significant decline was found in most provinces in Korea. However, in Kangwon province where the average elevation is higher than other provinces, the area of potential distribution of Pinus rigida increases in the near future and the further future. Also the result indicated that the potential distribution of Pinus rigida migrates to higher elevation. The potential distributions estimated in this research have relatively high accuracy with consideration of classification accuracy (44.75%) and prediction probability (62.56%).
Keywords
climate change; Pinus rigida; potential distribution;
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  • Reference
1 산림청. 2011. 임업통계연보. pp. 484.
2 이상철, 최성호, 이우균, 박태진, 오수현, 김순아. 2011. 기후변화 시나리오에 따른 산림분포 취약성 평가. 한국임학회지 100(2): 256-265.
3 이종수, 이우균, 손요환, 조용성, 송철철. 2006. 산림부문에서의 기후변화 취약성 평가모델 비교. 한국산림측정학회지 9: 87-100.
4 이현우. 2012. 4차 임상도와 HyTAG 모형에 의한 소나무림과 참나무림의 공간분포 및 탄소저장량 예측. 고려대학교 대학원 석사학위논문. pp. 46.
5 임종환 외 13인. 2008. 지구환경변화에 대응한 장기생태 연구. 국립산림과학원 연구사업보고서. pp. 1096.
6 최종근. 2007. 지구통계학, 시그마프레스,서울, pp. 188-231.
7 Allen, C.D., Macalady, A.K., Chenchouni, H., Bachelet, D., McDowell, N., Vennetier, M., Kitzberger, T., Rigling, A., Breshears, D.D., Hogg, E.H., Gonzalez, P., Fensham, R., Zhang, Z., Castro, J., Demidova, N., Lim, J.H., Allad, G., Running, S.W., Semerci, A. and Cobb, N. 2010. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. Forest Ecology and Management 259: 660-684.   DOI   ScienceOn
8 기상청. 2009. Climate Change Handbook. pp. 91.
9 기후변화정보센터. 2011. 미래 기상 예측자료. 인터넷 : http://www.climate.go.kr/index.html
10 Bachelet, D., Lenihan, J.M., Daly, C., Neilson, R.P., Ojima, D.S. and Parton, W.J. 2001. MC1: a dynamic vegetation model for estimating the distribution of vegetation and associated carbon, nutrients, and water-technical documentation. Version 1.0. USDA Forest Service, Pacific Northwest Research Station.
11 Ceballos, A., Martinez, J. and Luengo, M.A. 2004. Analysis of rainfall trends and dry periods on a pluviometric gradient representative of Mediterranean climate in the Duero Basin, Spain. Journal of Arid Environments 58(2): 215-233.   DOI   ScienceOn
12 Choi, S., Lee, W.K., Kwak, D.A., Lee, S., Son, Y., Lim, J.H. and Saborowski, J. 2011. Predicting forest cover changes in future climate using hydrological and thermal indices in Korea. Climate Research 49: 220-245.
13 Currie, D.J. and Paquin, V. 1987. Large-scale biogeographical patterns of species richness of trees. Nature 329(6137): 326-327.   DOI
14 Inverson, L.R. and Prasad, A.M. 1998. Predicting abundance of 80 tree species following climate change in the eastern United States. Ecological Monograph 68: 465-485.   DOI   ScienceOn
15 Kira T. 1945. A new classification of climate in eastern Asia as the basis for agricultural geography. Horticultural Institute. Kyoto Univ, Kyoto (in Japanese).
16 Neilson, R.P. 1995. A model for predicting continentalscale vegetation distribution and water balance. Ecological Applications 5(2): 362-385.   DOI   ScienceOn
17 The Government of Japan. 2002. Japan's Third National Communication Under the United Nations Framework Convention on Climate Change. 1.
18 Thornthwaite, C.W. 1948. An Approach toward a Rational Classification of Climate. Geographical Review 38(1): 55-94.   DOI   ScienceOn
19 Yim, Y.J. 1977. Distribution of forest vegetation and climate in the Korean peninsula III. Distribution of tree species along the thermal gradient. Japanese Journal of Ecology 27: 177-189.