한국농림기상학회지, 제 15권 제4호(2013) (pISSN 1229-5671, eISSN 2288-1859)
Korean Journal of Agricultural and Forest Meteorology, Vol. 15, No. 4, (2013), pp. 219~233
DOI: 10.5532/KJAFM.2013.15.4.219
ⓒ Author(s) 2014. CC Attribution 3.0 License.

소나무의 지리적 분포 및 생태적 지위 모형을 이용한
기후변화 영향 예측

천정화(1), 이창배(2)
(1)국립산림과학원 산림생태연구과, (2)산림청 녹색사업단

(2013년 10월 23일 접수; 2013년 10월 06일 수정; 2013년 11월 25일 수락)

Assessing the Effects of Climate Change on the
Geographic Distribution of Pinus densiflora
in Korea using Ecological Niche Model

Jung Hwa Chun(1), Chang-Bae Lee(2)
(1)Division of Forest Ecology, Korea Forest Research Institute, Seoul 130-712, Korea
(2)Korea Green Promotion Agency, Daejeon 302-831, Korea

(Received October 23, 2013; Revised October 06, 2013; Accepted November 25, 2013)

We employed the ecological niche modeling framework using GARP (Genetic Algorithm for Ruleset Production) to model the current and future geographic distribution of Pinus densiflora based on environmental predictor variable datasets such as climate data including the RCP 8.5 emission climate change scenario, geographic and topographic characteristics, soil and geological properties, and MODIS enhanced vegetation index (EVI) at 4 km2 resolution. National Forest Inventory (NFI) derived occurrence and abundance records from about 4,000 survey sites across the whole country were used for response variables. The current and future potential geographic distribution of Pinus densiflora, one of the tree species dominating the present Korean forest was modeled and mapped. Future models under RCP 8.5 scenarios for Pinus densiflora suggest large areas predicted under current climate conditions may be contracted by 2090 showing range shifts northward and to higher altitudes. Area Under Curve (AUC) values of the modeled result was 0.67. Overall, the results of this study were successful in showing the current distribution of major tree species and projecting their future changes. However, there are still many possible limitations and uncertainties arising from the select of the presence-absence data and the environmental predictor variables for model input. Nevertheless, ecological niche modeling can be a useful tool for exploring and mapping the potential response of the tree species to climate change. The final models in this study may be used to identify potential distribution of the tree species based on the future climate scenarios, which can help forest managers to decide where to allocate effort in the management of forest ecosystem under climate change in Korea.

Keyword: Ecological niche modeling, GARP, NFI, Geographic distribution, Pinus densiflora, Climate change, RCP 8.5 scenarios



본 연구는 산림에서 나타나는 수종의 분포 패턴을 해석하고 예측하기 위한 목적으로 수행되었다. 국내에서 처음으로 시도된 전국 규모의 체계적 산림조사라 할 수 있는 NFI (National Forest Inventory)의 수종별 출현 정보와 출현지점별 풍부도를 기반으로 소나무의 현존분포도를 작성하였다. 생태적 지위 모형의 하나인 GARP (Genetic Algorithm for Ruleset Production)를 이용하여 소나무 현존분포와 연관성이 높은 환경요인변수들을 선정하였고, 선정된 변수들을 설명변수로 하는 소나무 잠재분포 모형을 작성한 후 기후변화 시나리오를 적용하여 미래의 잠재분포를 예측하였다. 기후, 지리·지형, 토양·지질, 토지이용 및 식생현황 등 27개 환경요인변수를 각각 설명변수로 하여 모형을 구동함으로써 소나무 현존분포와의 연관성을 평가한 결과 1월 평균기온이 최상위를 차지하였고 연평균기온, 8월평균기온, 연교차 등도 영향을 미치는 것으로 분석되었다. NFI 정보로부터 추출하여 소스개체군으로 선정된 조사지점들을 소나무의 최종출현정보로, 환경요인변수 간의 연관성 분석을 통해 최종적으로 선정된 변수 세트를 설명변수로 하여 모형을 구동함으로써 최적의 모형을 선정한 후 잠재분포도를 작성하였다. 현재 시점의 환경요인변수들에 의해 트레이닝 된 잠재분포 모형에서 기후관련변수들을 RCP 8.5 기후변화시나리오에서 산출한 변수들로 대체하여 2020년대, 2050년대, 2090년대의 소나무의 예측 잠재분포도를 작성하였다. 최종적으로 작성된 소나무 잠재분포모형의 평가통계량인 AUC (Area Under Curve)는 0.67로 다소 미흡하였으나 향후 기후변화 환경 하에서 소나무림의 보전 및 관리를 위한 최소한의 실마리를 제공할 수 있을 것으로 판단되었다.


Allen, T. F. H., and T. B. Starr, 1982: Hierarchy: perspectives for ecological complexity. Chicago: The University of Chicago Press. pp. 310.

Anderson, R. P., M. Gomez-Laverde, and A. T. Peterson, 2002: Geographical distributions of spiny pocket mice in South America: Insights from predictive models. Global Ecology and Biogeography 11, 131-141.crossref(new window)

Clark, J. S., M. Lewis, and L. Horvath, 2001: Invasion by extremes: population spread with variation in dispersal and reproduction. American Naturalist 157, 537-554.crossref(new window)

Clements, F. E., 1936: Nature and Structure of the Climax. Journal of Ecology 24, 252-284.crossref(new window)

Curtis, J. T., 1959: The vegetation of Wisconsin. University of Wisconsin Press, Madison WI. pp. 657.

Davis, M. B., and R. G. Shaw, 2001: Range shifts and adaptive responses to Quaternary climate change. Science 292, 673-679.crossref(new window)

Dawson, T. P., S. T. Jackson, J. I. House, I. C. Prentice, and G. M. Mace, 2011: Beyond predictions: biodiversity conservation in a changing climate. Science 332, 53-58.crossref(new window)

Elith, J., M. A. Burgman, and H. M. Regan, 2002: Mapping epistemic uncertainty and vague concepts in predictions of species’ distribution. Ecological Modelling 157, 313-329.crossref(new window)

Elton, C., 1927: Animal Ecology. Sidgwick and Jackson, London. pp. 209.

Ferrier, S., G. Watson, J. Pearce, and M. Drielsma, 2002: Extended statistical approaches to modelling spatial pattern in biodiversity in northeast new south wales. Species-level modelling. Biodiversity and Conservation 11, 2275-2307.crossref(new window)

Grinnell, J., 1917: The niche-relationships of the California thrasher. The Auk 34, 427-433.crossref(new window)

Huntley, B., and T. Webb, 1988: Vegetation History, Vol. 7 in Handbook of Vegetation Science. Kluwer Academic Publ., Dordrecht, The Netherlands. pp. 803.

Hutchinson, G. E., 1957: Concluding remarks. Cold Spring Harbour Symposium on Quantitative Biology 22, 415-427.

Hutchinson, M. F., and R. J. Bishof, 1983: A new method for estimating the spatial distribution of mean seasonal and annual rainfall applied to the Hunter Valley, New South Wales. Australian Meteorological Magazine 31, 179-184.

Jackson, S. T., J. L. Betancourt, R. K. Booth, and S. T. Gray, 2009: Ecology and the ratchet of events: climate variability, niche dimensions, and species distributions. Proceedings of the National Academy of Sciences of the United States of America 106, 19685-19692.crossref(new window)

Korea Environment Institute., 2001: Climate change impacts assessment and adaptation measures on ecosystem. II -Forest eco-climate model development. pp. 107.

Korea Forest Research Institute., 2007: 2007 Annual Report. pp. 1103.

Korea Forest Research Institute., 2012a: Economic Tree Species 1 Pine tree. pp. 250.

Korea Forest Research Institute., 2012b: Forestry technology manual. pp. 1664.

Korea National Arboretum., 2012: Korea biodiversity information system (

Loarie, S. R., P. B. Duffy, H. Hamilton, G. P. Asner, C. B. Field, and D. D. Ackerly, 2009: The velocity of climate change. Nature 462, 1052-1055.crossref(new window)

Mooney, H. A., and M. Godron, 1983: Disturbance and ecosystems: components of response. Berlin: Springer-Verlag. pp. 292.

Paine, R. T., and S. A. Levin, 1981: Intertidal landscapes: disturbance and dynamics of pattern. Ecological Monography 51, 145-178.crossref(new window)

Pearson, R. G., and T. P. Dawson, 2003: Predicting the impacts of climate change on the distribution of species: Are bioclimate envelope models useful. Global Ecology and Biogeography 12, 361-371.crossref(new window)

Peterson, A. T., 2001: Predicting species’ geographic distributions based on ecological niche modeling. Condor 103, 599-605.crossref(new window)

Peterson, A. T., 2003: Predicting the geography of species’ invasions via ecological niche modeling. The Quarterly Review of Biology 78, 419-433.crossref(new window)

Peterson, A. T., and D. A. Vieglais, 2001: Predicting species invasions using ecological niche modeling: new approaches from bioinformatics attack a pressing problem. BioScience 51, 363-371.crossref(new window)

Peterson, A. T., D. R. B. Stockwell, and D. A. Kluza, 2002: Distributional prediction based on ecological niche modeling of primary occurrence data. In: Scott, J. M., P. J. Heglund, M. L. Morrison (Eds.), Predicting Species Occurrences: Issues of Scale and Accuracy. Island Press, Washington, D.C, pp. 617-623.

Pickett, S. T. A., and P. S. White, 1985: The ecology of natural disturbance and patch dynamics. San Diego, CA: Academic Press. pp. 472.

Pulliam, H. R., 1988: Sources, sinks, and population regulation. The American Naturalist. 132, 652-661.crossref(new window)

Ryan, M. G., S. R. Archer, A. Birdsey, C. N. Dahm, L. S. Heath, J. A. Hicke, D. Y. Hollinger, T. E. Huxman, G. S. Okin, R. Oren, J. T. Randerson, and W. H. Schlesinger, 2008: Land Resources: Forests and Arid Lands in The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity in the United States. U.S. Climate Change Science Program and the Subcommittee on Global Change Research. pp. 75-120.

Shin, J. H., 2002: Ecosystem Geography of Korea. in Ecology of Korea. pp. 406.

Shugart, H., R. Sedjo, and B. Sohngen, 2003: Forests & Global Climate Change: Potential Impacts on U.S. Forest Resources. In. Pew Center on Global Climate Change, Arlington. pp. 52.

Stehman, S. V., 1997: Selecting and interpreting measures of thematic classification accuracy. Remote Sensing of Environment 62(1), 77-89.crossref(new window)

Stockwell, D., and D. Peters, 1999: The GARP modeling system: Problems and solutions to automated spatial prediction. International Journal of Geographical Information Science 13(2), 143-158.crossref(new window)

Stockwell, D. R. B., and A. T. Peterson, 2002: Effects of sample size on accuracy of species distribution models. Ecological Modelling 148, 1-13.crossref(new window)

Swets, J. A., 1988: Measuring the accuracy of diagnostic systems. Science 240, 1285-1293.crossref(new window)

Warren, F. J., E. Barrow, R. Schwartz, J. Andrey, B. Mills, and D. Riedel, 2004: Climate Change Impacts and Adaptation: A Canadian Persapective. Natural Resources Canada, Ottawa, Ontario. pp. 174.

West, C. C., and M. J. Gawith, 2005: Measuring progress: Preparing for climate change through the UK Climate Impacts Programme. UKCIP, Oxford. pp. 71.

White, P. S., 1979: Pattern, process, and natural disturbance invegetation. Botanical Review 45, 229-299.crossref(new window)

Whittaker, R. H., 1956: Vegetation of the Great Smoky Mountains. Ecological Monography 26, 1-80.crossref(new window)

Whittaker, R. H., 1975: Communities and ecosystems. Edn. 2. Macmillan, New York.

Wickens C. D., and J. G. Hollands, 1999: Engineering Psychology and Human Performance Translated by Kwak, Ho Wan. 2003: Sigmapress. pp. 678.

Woodall., 2010: US FOREST SERVICE NORTHERN RESEARCH STATION. Research Review. 11. Autumn 2010.

Woodward, F. I., 1987: Climate and Plant Distribution. Cambridge: Cambridge University Press Distribution, Cambridge: Cambridge University Press.

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.

Zhu, K., C. W. Woodall, and J. S. Clark, 2011: Failure to migrate: lack of tree range expansion in response to climate change. Global Change Biology 18(3), 1042-1052.