기후변화 시나리오에 의한 중부지방소나무의 연도별 적지분포 변화 예측 = Predicting the Changes of Yearly Productive Area Distribution for Pinus densiflora in Korea Based on Climate Change Scenarios

국문 초록 (Abstract)

본 연구는 환경인자를 이용하여 우리나라에 생태권 역별로 분포하는 중부지방소나무의 지위지수 추정식을 개발하고 기후변화 시나리오를 적용하여 적지면적 및 적지분포를 추정하기 위해 수행하였다. 이를 위해 산림입지도와 전자기후도 및 기후변화 시나리오 RCP 4.5와 RCP 8.5를 사용하여 산림생산력에 영향을 미칠것으로 판단되는 19개의 기후변수를 포함한 총 48개 환경인자를 도출한 후, 최적 조합에 의해 지위지수 추정식을 개발하였다. 최종 생태권역별 중부지방소나무의 지위지수 추정식에는 각각 5~7개의 환경인자가 독립변수로 사용되었고, 지위지수 추정식의 설명력을 나타내는 결정계수는 0.32~0.46의 범위에 있는 것으로 분석되었다. 이 추정식은 모형의 평균편의, 정도, 표준 오차의 3가지 평가통계량에 근거하여 검증을 실시한 결과 비교적 지위 추정능력이 높은 것으로 판명되었다. 또한 본 연구에서는 생태권역별 중부지방소나무의 지위지수 추정식과 기후변화 시나리오 RCP 4.5와 RCP 8.5를 연계하여 시간 경과에 따른 중부지방소나무의 연도별 적지면적 및 적지분포의 변화를 추정하였다.

다국어 초록 (Multilingual Abstract)

This study was conducted to predict the changes of yearly productive area distribution for pinus densiflora under climate change scenario. For this, site index equations by ecoprovinces were first developed using environmental factors. Using the large data set from both a digital forest site map and a climatic map, a total of 48 environmental factors including 19 climatic variables were regressed on site index to develop site index equations. Two climate change scenarios, RCP 4.5 and RCP 8.5, were then applied to the developed site index equations and the distribution of productive areas for pinus densiflora were predicted from 2020 to 2100 years in 10-year intervals. The results from this study show that the distribution of productive areas for pinus densiflora generally decreases as time passes. It was also found that the productive area distribution of Pinus densiflora is different over time under two climate change scenarios. The RCP 8.5 which is more extreme climate change scenario showed much more decreased distribution of productive areas than the RCP 4.5. It is expected that the study results on the amount and distribution of productive areas over time for pinus densiflora under climate change scenarios could provide valuable information necessary for the policies of suitable species on a site.

참고문헌 (Reference)

1 김동현, "기후변화를 고려한 낙엽송 지위지수 추정" 한국임학회 101 (101): 53-61, 2012

2 Snee, R. D., "Validation of regression models : Methods and example" 19 : 415-428, 1977

3 Shin, M. Y., "The use of ridge regression for yield prediction models with multicolinearity" 79 (79): 260-268, 1990

4 Shin, J. W., "The ecosystem classification in Korea(I): Ecoprovince classification" 54 : 188-189, 1996

5 Nakawatase, J. M., "Spatial variability in forest growth-climate relationships in the Olympic Mountains, Washington" 36 (36): 77-91, 2006

6 Corona, P., "Relationship between environmental factors and site index in Douglas-Fir plantation in central Italy" 110 : 195-207, 1998

7 Belsley, D. A., "Regression diagnostics" John Wiley & Sons 292-, 1980

8 Choi, S. H., "Prediction of the change of tree distribution and above-ground carbon distribution by climate change" 138-139, 2009

9 Curt, T., "Predicting site index of Douglas-Fir plantations from ecological variables in the Massif Central area of France" 149 : 61-74, 2001

10 Bae, B. H., "Phytosociological studies for vegetation conservation of pine forest" 22 (22): 21-29, 1999

11 Tyler, A. L., "Models to predict the General Yield Class of Douglas-Fir, Japanese larch and Scots pine on better quality land in Scotland" 1 : 13-24, 1996

12 Kang, Y. H., "Mapping of the reighteous tree selection for a given site by using of digital terrain analysis on a northern temperate forest" 54 : 94-103, 1996

13 Kang, Y. H., "Mapping of the reighteous tree selection for a given site by using of digital terrain analysis on a central temperate forest" 86 (86): 241-250, 1997

14 Shin, M. Y., "Local correction of tree volume equation for Larix Ieptolepis by ratio-ofmeans estimator" 85 (85): 56-65, 1996

15 Judge, G. G., "Introduction to the theory and practice of econometrics" John Wiley & sons 1024-, 1988

16 Kabrick, J. M., "Factors associated with oak mortality in Missouri Ozak forest" USDA 27-35, 2004

17 Son, Y. M., "Evaluation and Prediction system of tree resources" 49-52, 2003

18 Korea Forest Research Institute, "Development of site index equations for main tree species by ecoprovince classification based on environmental and climatic factors" 101-, 2012

19 Korea Forest Research Institute, "Development of site index equations and estimation of productive areas for main species based on environmental and climatic factors" 71-, 2011

20 Albert, M., "Climate-sensitive modelling of site-productivity relationships for Norway spruce (Picea abies (L.) Karst.) and common beech (Fagus sylvatica L.)" 259 : 739-749, 2010

21 Myers, R. H., "Classical and modern regression with applications" Duxbury Press 395-, 1986

22 Arbatzis, A. A., "An evaluation of sampling methods and model forms for estimating height-diameter relationships in loblolly pine plantation" 38 (38): 192-198, 1992