Predicting forest cover changes in future climate using hydrological and thermal indices in South Korea

Abstract

We studied the potential responses of forest vegetation to climate change in South Korea using a Korea-specific forest cover distribution model based on hydrological and thermal indices. The past and future climatic parameters were converted to hydrological and thermal indices that have been reported as climatic controllers of forest vegetation distribution: (1) the Precipitation Effectiveness Index (PEI), (2) Warmth Index (WI), and (3) Minimum Temperature of the Coldest Month Index (MTCI). The vegetation map from the Ministry of Environment was applied to determine the optimal habitat PEI, WI, and MTCI ranges for major tree species in Korea. Then, 8 plant functional types (PFTs) were defined according to the analogies in the optimal habitat PEI, WI, and MTCI ranges, and the result was named the Hydrological and Thermal Analogy Groups (HyTAGs). The HyTAG model was used to simulate the potential forest cover distribution of Korea in the past (1971 to 2000), near future (2045 to 2065), and far future (2080 to 2099) with 3 IPCC climate change scenarios (B1, A1B, and A2). The potential forest cover distribution changes of the HyTAGs resulted in the shrinking of the cool temperate forests and the expansion of the warm temperate and subtropical forests, with different rates in each climate change scenario. The classification accuracy (CA) and prediction probability (PrP) values of 32.4 and 35.0%, respectively, validated the accuracy of HyTAGs as being relatively predictive of overall distributions of cool-temperate (HyTAG-A), temperate (HyTAG-B), and warm-temperate (HyTAG-C) mixed forests.