Advanced SearchSearch Tips
Shifts of Geographic Distribution of Pinus koraiensis Based on Climate Change Scenarios and GARP Model
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Shifts of Geographic Distribution of Pinus koraiensis Based on Climate Change Scenarios and GARP Model
Chun, Jung Hwa; Lee, Chang Bae; Yoo, So Min;
  PDF(new window)
The main purpose of this study is to understand the potential geographic distribution of P. koraiensis, which is known to be one of major economic tree species, based on the RCP (Representative Concentration Pathway) 8.5 scenarios and current geographic distribution from National Forest Inventory(NFI) data using ecological niche modeling. P. koraiensis abundance data extracted from NFI were utilized to estimate current geographic distribution. Also, GARP (Genetic Algorithm for Rule-set Production) model, one of the ecological niche models, was applied to estimate potential geographic distribution and to project future changes. Environmental explanatory variables showing Area Under Curve (AUC) value bigger than 0.6 were selected and constructed into the final model by running the model for each of the 27 variables. The results of the model validation which was performed based on confusion matrix statistics, showed quite high suitability. Currently P. koraiensis is distributed widely from 300m to 1,200m in altitude and from south to north as a result of national greening project in 1970s although major populations are found in elevated and northern area. The results of this study were successful in showing the current distribution of P. koraiensis and projecting their future changes. Future model for P. koraiensis suggest large areas predicted under current climate conditions may be contracted by 2090s showing dramatic habitat loss. Considering the increasing status of atmospheric and air temperature in Korea, P. koraiensis seems to experience the significant decrease of potential distribution range in the future. The final model in this study may be used to identify climate change impacts on distribution of P. koraiensis in Korea, and a deeper understanding of its correlation may be helpful when planning afforestation strategies.
Ecological niche modeling;GARP;NFI;Pinus koraiensis;Climate change;RCP 8.5 secnarios;Geographic distribution;
 Cited by
Brief history of Korean national forest inventory and academic usage, Korean Journal of Agricultural Science, 2016, 43, 3, 299  crossref(new windwow)
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)

Bae, S. W., J. H. Hwang, S. T. Lee, H. S. Kim and J. M. Jeong, 2010: Change in soil temperature, moisture content, light availability and diameter growth after thinning in Korean Poin (Pinus koraiensis) plantation. Journal of Korea Forest Society 99(3), 397-403.

Chon, S. K., M. Y. Shin and D. J. Chung, 1999: Characteristics of the Early Growth for Korean White Pine (Pinus koraiensis Sieb. et Zucc.) and Effects of Local Climatic Conditions on the Growth-Relation between Periodic Annual Increment and Local Climate Conditions. Journal of Korea Forest Society 88(1), 73-85.

Christopher, D. W., 2003: Engineering psychology. Sigma press, 678pp.

Chun, J. H., and C. B. Lee, 2013: Assessing the Effects of Climate Change on the Geographic Distribution of Pinus densiflora in Korea using Ecological Niche Model. Korean Journal of Agricultural and Forest Meteorology 15(4), 219-233. (in Korean with English abstract) crossref(new window)

Choi, S. H., W. K. Lee, S. J. Yoo, S. M. Park, J. G. Byun and G. S. Cui, 2009: Simulation on vegetation cover and terrestrial carbon distribution by climate change in Korea. Proceedings of GIS Autumn Conference, 138-139. (in Korean with English abstract)

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

FAO, 2011: State of the World's Forest. 164pp.

Han, S. S. and W. G. Park, 1988: Diameter Growth and Key-year in Pinus koraiensis and Pinus densiflora Trees. Journal of Korea Forest Society 77(2), 216-221. (in Korean with English abstract)

Kang, W. M., D. Kang, and C. R. Park, 2012: Decreased Habitat Area and Connectivity of Kalopanax pictus under Climate Change in South Korea. Proceeding of The 55th symposium of International Assocation for Vegetation Science, Organizing Committee of IAV2012, Mokpo Korea, 102pp.

Korea Environment Institute, 2000: Evaluation of the Ecological Effect and Corresponding Strategy Due to Climate Change 1. Forest Ecology, 86pp.

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

Korea Forest Research Institute, 2009: 2009 Annual Report, Korea Forest Service, 771pp.

Korea Forest Research Institute, 2011: 2011 Annual Report -Forest Conservation, Korea Forest Service, 694pp.

Korea Forest Research Institute, 2012: Economic Tree Species Pinus koraiensis, Korea Forest Service, 168pp.

Millennium Ecosystem Assessment, 2005: Ecosystems and Human Well-Being: Current State and Trends. Volume 1. R. Hassan, R. Scholes, and N. Ash (Eds.). Island Press, 137pp.

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, 617-623pp.

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)

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

Scholes, R. J. and M. R. van der Merwe, 1996: Sequestration of Carbon in Savannas and Woodlands. The Environmental Professional 18, 96-103.

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

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

The National Weather Service, 2013: Summary for decision maker of police in accordance with a scientific basis, 28pp.

The National Weather Service, 2015: 2014 Climate Change Report, 155pp.

Weiss, A. D., 2001: Topographic Position and Landforms Analysis. Poster presentation. Proceedings of ESRI User Conference, San Diego, CA

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.