ALBERT

Description: This study estimates the impact of potential climate change, and human interference (anthropogenic deforestation), on temperate forest carbon pool change in the capital area of South Korea, using a dynamic global vegetation model (DGVM). Additionally, the characteristics of forest carbon pool change were simulated based on a biogeochemical module. The change of atmospheric carbon dioxide (CO2) concentration is deeply related to the change of the forest carbon pool, which is estimated with the measures of Net Primary Productivity (NPP), and Soil Carbon Storage (SCS). NPP and SCS were estimated at 2.02–7.43 tC ha−1 year−1 and 34.55–84.81 tC ha−1, respectively, during the period 1971–2000. SCS showed a significant decreasing tendency under the conditions of increasing air temperature, and precipitation, in the near future (2021–2050), and far future (2071–2100), which were simulated with future-climate scenario data without any human interference. Besides, it is estimated that the temporal change in NPP indicates only a small decrease, which is little influenced by potential climate change. In the case of potential climate change plus human interference, the decrease rate of NPP and SCS were simulated at 17–33% and 21–46%, respectively, during 2000–2100. Furthermore, the effect of potential human interference contributes to 83–93% and 61–54% of the decrease rate of NPP and SCS, respectively. The decline in the forest carbon pool simulated in this study can play a positive role in increasing atmospheric carbon dioxide. Consequently, the effect of potential human interference can further accelerate the decline of the temperate forest carbon pool. For the effective reduction of carbon dioxide emissions in urbanizing areas, it would be more effective to control human interference. Consequently, this study suggests that a rate of reforestation corresponding to the deforestation rate should be at least maintained, with long term monitoring and modeling-related studies, against climate change problems.

Description: The study was the first attempt to identify the habitat use pattern of red-crowned cranes (Grus japonensis) around the demilitarized zone (DMZ) by overlapping coordinates with the land cover classification (LCC). Daily habitat use pattern was highly different (P = 0.000) between daytime (06:00–18:00) and nighttime (18:00–06:00). Cranes in Cheolwon used agricultural paddies more frequently in the daytime (P = 0.002), and forest areas at night and this indicated that cranes presumably use rice paddies for feeding and forests for resting, respectively. Cranes night time in Paju used wetlands more often than random expectation based on the available wetland surface area (P = 0.017). This indicated a different habitat use pattern between coastal (Paju) and inland (Cheolwon) areas. Securing agricultural paddies is important for providing crucial areas for feeding, and forests should be important for rest during the night time in Cheolwon, which support crane populations during their wintering migration in Korea.

Description: Information on the phenological shift of plants can be used to detect climate change and predict changes in the ecosystem. In this study, the changes in first flowering dates (FFDs) of the plum tree (Prunus mume), Korean forsythia (Forsythia koreana), Korean rosebay (Rhododendron mucronulatum), cherry tree (Prunus yedoensis), and peach tree (Prunus persica) in Korea during 1920–2019 were investigated. In addition, the changes in the climatic factors (temperature and precipitation) and their relationship with the FFDs were analyzed. The changes in the temperature and precipitation during the January–February–March period and the phenological shifts of all research species during 1920–2019 indicate that warm and dry spring weather advances the FFDs. Moreover, the temperature has a greater impact on this phenological shift than precipitation. Earlier flowering species are more likely to advance their FFDs than later flowering species. Hence, the temporal asynchrony among plant species will become worse with climate change. In addition, the FFDs in 2100 were predicted based on representative concentration pathway (RCP) scenarios. The difference between the predicted FFDs of the RCP 4.5 and RCP 6.0 for 2100 was significant; the effectiveness of greenhouse gas policies will presumably determine the degree of the plant phenological shift in the future. Furthermore, we presented the predicted FFDs for 2100.