Application of integrated Korean forest growth dynamics model to meet NDC target by considering forest management scenarios and budget.

BACKGROUND: Forests are atmospheric carbon sinks, whose natural growth can contribute to climate change mitigation. However, they are also affected by climate change and various other phenomena, for example, the low growth of coniferous forests currently reported globally, including in the Republic of Korea. In response to the implementation of the Paris Agreement, the Korean government has proposed 2030 greenhouse gas roadmap to achieve a Nationally Determined Contribution (NDC), and the forest sector set a sequestration target of 26 million tons by 2030. In this study, the Korean forest growth model (KO-G-Dynamic model) was used to analyze various climate change and forest management scenarios and their capacity to address the NDC targets. A 2050 climate change adaptation strategy is suggested based on forest growth and CO2 sequestration. RESULTS: Forest growth was predicted to gradually decline, and CO2 sequestration was predicted to reach 23 million tons per year in 2050 if current climate and conditions are maintained. According to the model, sequestrations of 33 million tCO2 year-1 in 2030 and 27 million tCO2 year-1 in 2050 can be achieved if ideal forest management is implemented. It was also estimated that the current forest management budget of 317 billion KRW (264 million USD) should be twice as large at 722 billion KRW (602 million USD) in the 2030s and 618 billion KRW (516 million USD) in the 2050s to achieve NDC targets. CONCLUSIONS: The growth trend in Korea's forests transitions from young-matured stands to over-mature forests. The presented model-based forest management plans are an appropriate response and can increase the capacity of Korea to achieve its NDC targets. Such a modeling can help the forestry sector develop plans and policies for climate change adaptation.

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.

Understanding global PM2.5 concentrations and their drivers in recent decades (1998-2016).

The threat of fine particulate matter (PM2.5) is increasing globally. Tackling this issue requires an accurate understanding of its trends and drivers. In this study, global risk regions of PM2.5 concentrations during 1998-2016 were spatiotemporally derived. Time series analysis was conducted in the spatial relationship between PM2.5 and three socio-environmental drivers: population, urban ratio, and vegetation greenness that can cause changes in the concentration of PM2.5. "High Risk" areas were widely distributed in India and China. In India and sub-Saharan Africa, the increased overall population was strongly correlated with PM2.5 concentrations. Urban ratio increased in both developed and developing countries. A "decoupling" phenomenon occurred in developed countries, where urban expansion continued while PM2.5 concentrations decreased. Vegetation greenness and PM2.5 were strongly correlated in High Risk zones. Although urban expansion and population growth generally reduce vegetation greenness, developed countries reduced PM2.5 while maintaining greenness, whereas developing countries increased PM2.5 with decreasing greenness significantly in High Risk regions. Ultimately, economic and national growth should occur without increasing PM2.5 concentrations. Recent cases from Europe and the eastern United States demonstrate that this is possible, depending on the development pathway.

Corrigendum to "Mann-Kendall Monotonic Trend Test and Correlation Analysis using Spatio-temporal Dataset: the case of Asia using vegetation greenness and climate factors" [MethodsX 5 (2018) 803-807].

[This corrects the article DOI: 10.1016/j.mex.2018.07.006.][This corrects the article DOI: 10.1016/j.scitotenv.2017.09.145.].

Decoupling of forest water supply and agricultural water demand attributable to deforestation in North Korea.

This study focused on changes in water balance attributable to severe deforestation in North Korea. The forest water supply and agricultural water demand of North Korea were quantified to identify their decoupling over the past three decades. Forest water supply and agricultural water demand before and after deforestation were estimated using the InVEST-WY (Integrated Valuation of Ecosystem Services and Trade-offs - Water Yield) and EPIC (Environmental Policy Integrated Climate) models, respectively. Analysis of land cover change before and after deforestation showed that area under forests decreased by 25%, whereas that under cropland increased by 63%, and that the conversion from forest to cropland was the largest for the study period. As a result, agricultural water demand increased and forest water supply decreased, significantly. Analysis of the net impact of deforestation on water budgets using recent climate and two land covers showed that forest water supply decreased by 43% and agricultural water demand increased by 62%. An assessment of the water balance at the watershed level showed that the Taedong, Ryesong, and Tumen Rivers suffered the largest negative change in terms of the large gross impact of deforestation on water resources. The water balance of the entire North Korea has declined by 51% and this is attributable to deforestation. In contrast, South Korea has experienced success in national-scale afforestation in recent decades, and North Korea can emulate this. The restoration of forests in North Korea promises more than environmental benefits; it will provide a new growth engine for the prosperity of the Korean Peninsula as a whole.

Long-term trend of and correlation between vegetation greenness and climate variables in Asia based on satellite data.

Satellite data has been used to ascertain trends and correlations between climate change and vegetation greenness in Asia. Our study utilized 33-year (1982-2014) AVHRR-GIMMS (Advanced Very High Resolution Radiometer-Global Inventory Modelling and Mapping Studies) NDVI3g and CRU TS (Climatic Research Unit Time Series) climate variable (temperature, rainfall, and potential evapotranspiration) time series. First, we estimated the overall trends for vegetation greenness and climate variables and analyzed trends during summer (April-October), winter (November-March), and the entire year. Second, we carried out correlation and regression analyses to detect correlations between vegetation greenness and climate variables. Our study revealed an increasing trend (0.05-0.28) in temperature in northeastern India (bordering Bhutan), Southeast Bhutan, Yunnan Province of China, Northern Myanmar, Central Cambodia, northern Laos, southern Vietnam, eastern Iran, southern Afghanistan, and southern Pakistan. However, a decreasing trend in temperature (0.00 to -0.04) was noted for specific areas in southern Asia including Central Myanmar and northwestern Thailand and the Guangxi, Southern Gansu, and Shandong provinces of China. The results also indicated an increasing trend for evapotranspiration and air temperature accompanied by a decreasing trend for vegetation greenness and rainfall. Increases in both the mean annual signal and annual cycle occurred in the forest, herbaceous, and cropland areas of India, Northwest China, and eastern Kazakhstan. The temperature was found to be the main driver of the changing vegetation greenness in Kazakhstan, northern Mongolia, Northeast and Central China, North Korea, South Korea, and northern Japan, showing an indirect relationship (R = 0.84-0.96). •Temperature is the main climatic variable affecting vegetation greenness.•A downward trend in vegetation greenness was observed during summer (April-October).•Temperature showed an upward trend across many areas of Asia during the study period.•In winter, rainfall showed downward and upward trends in different parts of Asia.

Long-term trend and correlation between vegetation greenness and climate variables in Asia based on satellite data.

Satellite data has been used to ascertain trends and correlations between climate change and vegetation greenness in Asia. Our study utilized 33-year (1982-2014) AVHRR-GIMMS (Advanced Very High Resolution Radiometer - Global Inventory Modelling and Mapping Studies) NDVI3g and CRU TS (Climatic Research Unit Time Series) climate variable (temperature, rainfall, and potential evapotranspiration) time series. First, we estimated the overall trends for vegetation greenness, climate variables and analyzed trends during summer (April to October), winter (November to March), and the entire year. Second, we carried out correlation and regression analyses to detect correlations between vegetation greenness and climate variables. Our study revealed an increasing trend (0.05 to 0.28) in temperature in northeastern India (bordering Bhutan), Southeast Bhutan, Yunnan Province of China, Northern Myanmar, Central Cambodia, northern Laos, southern Vietnam, eastern Iran, southern Afghanistan, and southern Pakistan. However, a decreasing trend in temperature (0.00 to -0.04) was noted for specific areas in southern Asia including Central Myanmar and northwestern Thailand and the Guangxi, Southern Gansu, and Shandong provinces of China. The results also indicated an increasing trend for evapotranspiration and air temperature accompanied by a decreasing trend for vegetation greenness and rainfall. The temperature was found to be the main driver of the changing vegetation greenness in Kazakhstan, northern Mongolia, Northeast and Central China, North Korea, South Korea, and northern Japan, showing an indirect relationship (R=0.84-0.96).