S-Space College of Agriculture and Life Sciences (농업생명과학대학) Dept. of Landscape Architecture and Rural System Engineering (생태조경·지역시스템공학부) Theses (Master's Degree_생태조경·지역시스템공학부)
Estimating Korean Pine(Pinus koraiensis) Habitat Distribution Considering Climate Change Uncertainty - Using Species Distribution Models and RCP Scenarios-
불확실성을 고려한 잣나무의 서식 적지 분포 예측 - 종 분포 모형과 RCP시나리오를 중심으로 -
- 농업생명과학대학 생태조경·지역시스템공학부
- Issue Date
- 서울대학교 대학원
- Ensemble models; BIOMOD2; Machine learning models; Statistical models; Species distribution; Forest ecosystem
- 학위논문 (석사)-- 서울대학교 대학원 : 생태조경·지역시스템공학부, 2015. 8. 이동근.
- Climate change can significantly affect tree species distribution in forests. Therefore, adaptation planning is needed to obtain maximum returns on tree growth. Pinus koraiensis, the common name is Korean pine, is a major afforestation species in Korea and is normally distributed in frigid zones. For this reason, global warming could affect the distribution of the Korean pine. Therefore, this study aimed to predict the distribution of the Korean pine and its suitable habitat area considering uncertainty by applying climate change scenarios in an ensemble model.
Species distribution points and environmental variables data were used for the input data in the model. First, a site index was considered when selecting present and absent points by using the stratified method. Secondly, environmental and climate variables were chosen by literature review and then correlation analysis was performed to select variables that were not correlated. Subsequently, the selected variables were confirmed with experts. Those variables were then used as input data of BIOMOD2 (BIOdiversity MODelling 2). Next, the present distribution model was made and the result was validated with data splitting and Receiver Operating Characteristic (ROC). Next, Representative Concentration Pathways (RCPs) scenarios were applied to the models to create the future distribution model. Finally, the ensemble models were built and consensus maps were created using model committee averaging (MCA). In addition, overlay maps and uncertainty maps were used to quantify the uncertainties of the results.
The estimated results of the individual models showed significant variation. Among the eight models, Random Forest (RF) had the highest accuracy. The Artificial Neural Network (ANN) model tended to overestimate results, and the Maximum Entropy Algorithm (Maxent) results were distinct from those of the other models. These differences can be explained by the algorithms of each model, the interaction of input data, and the verification methodology. The uncertain area from individual models was excluded from the ensemble model results.
In the midterm future (2040s), the models themselves created the major differences observed in Korean pine distribution. In contrast, both the models and RCPs scenarios caused variation in the long-term future (2090s). Results of ensemble models were calculated using uncertainty and overlay maps, with the uncertainty of one overlay map close to 17%. The uncertainty of the five times overlaid area was around 8% in both the midterm and long-term futures.
Suitable habitat for the Korean pine in the midterm future is mainly distributed in the central part of Korea, Gangwon province, and the southern part of Korea. In the long-term future, this preferred area will disappear from the southern part of Korea as well as some areas of Gangwon province. Generally, most model and ensemble results predicted that the suitable habitat area would decrease in the mid- and long-term future.
As the Korean pine is an afforestation species, it cannot be planted in protected areas. Therefore, protected areas were eliminated from the results of the ensemble model.
The ratios of protected area were 25%, 25%, 19%, and 22% in RCPs 2.6, 4.5, 6.0, and 8.5, respectively, in the midterm future. There was no significant difference among the results. The protected area ratios were 24%, 40%, 31%, and 24% in the long?term future, indicating that available areas to plant Korean pine will be reduced in the future.
In conclusion, climate change scenarios and species distribution models (SDMs) create uncertainties in the evaluation of the future distribution of the Korean pine. Therefore, when estimating species distribution under climate change, uncertainties should be considered. In addition, the models show that the suitable habitat area for the Korean pine will decrease in the future, making it important for the climate change adaptation plan to reduce this impact.
This study is significant in that it considered uncertainties in the SDMs and RCPs scenarios. The results of this study could be important considerations in the process of plantation planning.