DOI QR코드

DOI QR Code

Estimating Stand Volume Pinus densiflora Forest Based on Climate Change Scenario in Korea

미래 기후변화 시나리오에 따른 우리나라 소나무 임분의 재적 추정

  • Kim, Moonil (Division of Environment Science and Ecological Engineering, Korea University) ;
  • Lee, Woo-Kyun (Division of Environment Science and Ecological Engineering, Korea University) ;
  • Guishan, Cui (Division of Environment Science and Ecological Engineering, Korea University) ;
  • Nam, Kijun (Division of Environment Science and Ecological Engineering, Korea University) ;
  • Yu, Hangnan (Division of Environment Science and Ecological Engineering, Korea University) ;
  • Choi, Sol-E (Division of Environment Science and Ecological Engineering, Korea University) ;
  • Kim, Chang-Gil (Korea Rural Economic Institute) ;
  • Gwon, Tae-Seong (Division of Forest Ecology, Korea Forest Research Institute)
  • 김문일 (고려대학교 환경생태공학부) ;
  • 이우균 (고려대학교 환경생태공학부) ;
  • ;
  • ;
  • ;
  • 최솔이 (고려대학교 환경생태공학부) ;
  • 김창길 (한국농촌경제연구원) ;
  • 권태성 (국립산림과학원 산림생태연구과)
  • Received : 2013.08.14
  • Accepted : 2014.01.29
  • Published : 2014.03.31

Abstract

The main purpose of this study is to measure spatio-temporal variation of forest tree volume based on the RCP(Representative Concentration Pathway) 8.5 scenario, targeting on Pinus densiflora forests which is the main tree species in South Korea. To estimate nationwide scale, $5^{th}$ forest type map and National Forest Inventory data were used. Also, to reflect the impact of change in place and climate on growth of forest trees, growth model reflecting the climate and topography features were applied. The result of the model validation, which compared the result of the model with the forest statistics of different cities and provinces, showed a high suitability. Considering the continuous climate change, volume of Pinus densiflora forest is predicted to increase from $131m^3/ha$ at present to $212.42m^3/ha$ in the year of 2050. If the climate maintains as the present, volume is predicted to increase to $221.92m^3/ha$. With the climate change, it is predicted that most of the region, except for some of the alpine region, will have a decrease in growth rate of Pinus densiflora forest. The growth rate of Pinus densiflora forest will have a greater decline, especially in the coastal area and the southern area. With the result of this study, it will be possible to quantify the effect of climate change on the growth of Pinus densiflora forest according to spatio-temporal is possible. The result of the study can be useful in establishing the forest management practices, considering the adaptation of climate change.

본 연구는 우리나라 주요 수종인 소나무림을 대상으로 RCP(Representative Concentration Pathway)8.5 시나리오에 따른 임목 재적의 시 공간적 변이를 예측하기 위해 수행되었다. 전국 규모의 예측을 위해 5차임상도와 국가산림자원조사 자료를 이용하였으며, 기후와 공간의 변이가 임목 생장에 미치는 영향을 반영하기 위해 기상 및 지형인자를 반영한 생장모형을 적용하였다. 모형의 검증을 위해 시, 도별 산림통계와 모형 결과를 비교한 결과, 비교적 높은 적합도를 보이는 것으로 나타났다. 기후변화를 고려하였을 때, 소나무림의 임분 재적은 현재 $131m^3/ha$에서 2050년에는 $212.42m^3/ha$까지 증가 할 것으로 예측되었으며, 현재의 기후가 유지될 경우에는 $221.92m^3/ha$까지 증가할 것으로 예측되었다. 기후변화의 영향으로 인해 일부 고산지대를 제외한 대부분의 지역에서 소나무림의 생장률이 감소할 것으로 예측되었으며, 특히 해안지역과 남부지역에서 생장률의 감소가 클 것으로 나타났다. 본 연구결과를 통해 기후변화가 소나무림 생장에 미치는 영향을 시 공간에 따라 정량화 할 수 있었으며, 이는 기후변화 적응을 고려한 산림관리 및 시업계획을 수립하는데 유용하게 활용될 수 있을 것이다.

Keywords

References

  1. Byun, J., Lee, W.K., Kim, M., Kwak, D.A., Kwak, H., Park, T., Byun, W.H., Son, Y., Choi, J.K., Lee, Y.J., Saborowski, J., Chung, D.J., and Jung, J.H. 2013. Radial growth response of Pinus densiflora and Quercus spp. to topographic and climatic factors in South Korea. Journal of Plant Ecology 6(5): 380-392. https://doi.org/10.1093/jpe/rtt001
  2. Byun, J.G., Lee, W.K., Nor, D.K., Kim, S.H., Choi, J.K., and Lee, Y.J. 2010. The relationship between tree radial growth and topographic and climate factors in red pine and oak in central regions of Korea. Journal of Korean Forestry Society 99(6): 908-913.
  3. Choi, S., Lee, W.K., Kwak, D.A., Lee, S.C., Lim, J.H., and Saborowski, J. 2012. Predicting forest cover changes in future climate using hydrological and thermal indices in South Korea. Climate Research 49: 229-245.
  4. Chun, J.H., Lim, J., and Lee, D.K. 2007. Biomass Estimation of Gwangneung Catchment Area with Landsat ETM+ Image. Journal of Korea Forest Society 96(5): 591-601.
  5. Dale, V.H., Joyce, L.A., Mcnulty, S., Neilsom, R.P., Ayres, M.P., Flannigan, M.D., Hanson, P.H., Irland, L.C., Lugo, A.E., Peterson, C.J., Simberloff, D., Swanson, F.J., Stocks, B.J., and Wotton, B.M. 2001. Climate Change and Forest Disturbances. Journal of BioScience 51(9): 723-734. https://doi.org/10.1641/0006-3568(2001)051[0723:CCAFD]2.0.CO;2
  6. Fang, J., Lechowicz, M.J. 2006. Climatic limits for the present distribution of beech (Fagus L.) species in the world. Journal of Biogeography 33: 1804-1819. https://doi.org/10.1111/j.1365-2699.2006.01533.x
  7. IPCC 2007: Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Core Writing Team, Pachauri, R. K. and Reisinger, A.(Eds.). IPCC, Geneva, Switzerland. pp. 104.
  8. Jung, J.H., Heo, J., Yoo, S.H., Kim, K.M., and Lee, J.B. 2010. Estimation of Aboveground Biomass Carbon Stock in Danyang Area using kNN Algorithm and Landsat TM Seasonal Satellite Images. Journal of The Korean Society for Geo-Spatial Information System 18(4): 119-129.
  9. Kim, C.S., Park, J.H., and Jang, D.H. Changes of the Forest Types by Climate Changes using Satellite imagery and Forest Statistical Data: A case in the Chungnam Coastal Ares, Korea. Journal of Environmental Impact Assessment 20(4): 523-538.
  10. Kim, E.S., Kim, K.M., Lee, J.B., Lee, S.H., and Kim, C.C. 2011. Spatial upscaling of aboveground biomass estimation using national forest inventory data and forest type map. Journal of Korea Forest Society 100(3): 455-465.
  11. Kim, J.W. and Lee, D.K. A study on the vulnerability assessment of forest vegetation using regional climate model. Journal of the Korea Society of Environmental Restoration Technology 9(5): 32-40.
  12. Kim, M.I., Lee, W.K., Park, T.J., Kawk, H.B., Byun, J.Y., Nam, K.J., Lee, K.H., Son, Y.M., Won, H.K., and Lee, S.M. 2012. Developing dynamic DBH growth prediction model by thinning intensity and cycle: based on yield table data. Journal of Korean Forest Society 101(2): 266-278.
  13. Korea Forest Research Institute. 2010. Carbon emission factor of major species for forest greenhouse gas inventory.
  14. Korea Forest Service. Statistical Yearbook of Forestry 2011. Korea Forest Service, Seoul, 2011. p. 32.
  15. Korea Forest Service. Statistical Yearbook of Forestry 2012. Korea Forest Service, Seoul, 2012. pp. 33-211.
  16. Kwak, D.A., Lee, W.K., Son, Y., Choi, S., Yoo, S., Chung, D.J., Lee, S.H., Kim, S.H., Choi, J.K., Lee, Y.J., and Byun, W.H. 2012. Predicting distributional change of forest cover and volume in future climate of South Korea. Forest Science and Technology 8(2): 105-115. https://doi.org/10.1080/21580103.2012.673751
  17. Lee, M.A., Lee, W.K., Son, Y., Cho, Y.S., Song, C.C., Kim, T.M., Yu, L., and Tao, B. 2007. Sensitivity and Adaptability of Vegetation and Soil Carbon Storage to Climate Change with CEVSA Model in Korea. Proceedings of 2007 A3 Foresight Program, A3 Foresight Program. p. 24.
  18. Oberhuber, W., Stumbock, M., and Kofler, W. 1998. Climatetree-growth relationships of Scots pine stands (Pinus sylvestris L.) exposed to soil dryness. Trees 13: 19-27.
  19. Park, H.J., Shin, H.S., Roh, Y.H., Kim, K.M., and Park, K.H. 2012. Estimating Forest Carbon Stocks in Danyang Using Kriging Methods for Aboveground Biomass. Journal of the Korean Association of Geographic Information Studies 15(1): 16-33. https://doi.org/10.11108/kagis.2012.15.1.016
  20. Song, K.M., Kim, C.S., Moon, M.O., and Kim, M.H. 2012. A change and distribution in Pinus densiflora forest of Mt. Hallasan. Journal of the Environmental Science 21(1): 41-47. https://doi.org/10.5322/JES.2012.21.1.41
  21. Yu, H., Lee, W.K., Son, Y., Kwak, D.A., Nam, K., Kim, M, Byun, J., Lee, S., and Kwon, T. 2013. Estimating carbon stocks in Korean forests between 2010 and 2110: a prediction based on forest volume-age relationships. Forest Science and Technology 9(2): 105-110. https://doi.org/10.1080/21580103.2013.801174

Cited by

  1. Becoming a city Buddhist among the young generation in Seoul vol.31, pp.4, 2016, https://doi.org/10.1177/0268580916643089
  2. The Relationship between Stand Mean DBH and Temperature at a Watershed Scale: The Case of Andong-dam Basin vol.18, pp.4, 2016, https://doi.org/10.5532/KJAFM.2016.18.4.287
  3. Brief history of Korean national forest inventory and academic usage vol.43, pp.3, 2016, https://doi.org/10.7744/kjoas.20160032
  4. Buddhism during the Chosŏn Dynasty (1392-1910): A Collective Trauma? vol.22, pp.1, 2014, https://doi.org/10.1215/21581665-4153349
  5. The Role of Forests in Climate Change Regarding Carbon, Nitrogen, and Water: A Case Study of Pinus densiflora vol.13, pp.21, 2021, https://doi.org/10.3390/w13213050