Forest management can mitigate negative impacts of climate and land-use change on plant biodiversity: Insights from the Republic of Korea.

Over the past century, the decline in biodiversity due to climate change and habitat loss has become unprecedentedly serious. Multiple drivers, including climate change, land-use/cover change, and qualitative change in habitat need to be considered in an integrated approach, which has rarely been taken, to create an effective conservation strategy. The purpose of this study is to quantitatively evaluate and map the combined impacts of those multiple drivers on biodiversity in the Republic of Korea (ROK). To this end, biodiversity persistence (BP) was simulated by employing generalized dissimilarity modeling with estimates of habitat conditions. Habitat Condition Index was newly developed based on national survey datasets to represent the changes in habitat quality according to the land cover changes and forest management, especially after the ROK's National Reforestation Programme. The changes in habitat conditions were simulated for a period ranging from the 1960s to the 2010s; additionally, future (2050s) spatial scenarios were constructed. By focusing on the changes in forest habitat quality along with climate and land use, this study quantitatively and spatially analyzed the changes in BP over time and presented the effects of reforestation and forest management. The results revealed that continuous forest management had a positive impact on BP by offsetting the negative effects of past urbanization. Improvements in forest habitat quality also can effectively reduce the negative impacts of climate change. This quantitative analysis of successful forest restoration in Korea proved that economic development and urbanization could be in parallel with biodiversity enhancement. Nevertheless, current forest management practices were found to be insufficient in fully offsetting the decline in future BP caused by climate change. This indicates that there is a need for additional measures along with mitigation of climate change to maintain the current biodiversity level.

Spatialization and Prediction of Seasonal NO2 Pollution Due to Climate Change in the Korean Capital Area through Land Use Regression Modeling.

Urbanization is causing an increase in air pollution leading to serious health issues. However, even though the necessity of its regulation is acknowledged, there are relatively few monitoring sites in the capital metropolitan city of the Republic of Korea. Furthermore, a significant relationship between air pollution and climate variables is expected, thus the prediction of air pollution under climate change should be carefully attended. This study aims to predict and spatialize present and future NO2 distribution by using existing monitoring sites to overcome deficiency in monitoring. Prediction was conducted through seasonal Land use regression modeling using variables correlated with NO2 concentration. Variables were selected through two correlation analyses and future pollution was predicted under HadGEM-AO RCP scenarios 4.5 and 8.5. Our results showed a relatively high NO2 concentration in winter in both present and future predictions, resulting from elevated use of fossil fuels in boilers, and also showed increments of NO2 pollution due to climate change. The results of this study could strengthen existing air pollution management strategies and mitigation measures for planning concerning future climate change, supporting proper management and control of air pollution.