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As climate change continues to impact the planet, the importance of forests is becoming increasingly emphasized. The International Co-operative Program on the Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests) has been monitoring and assessing forests in 40 countries since 1985. In Republic of Korea, the first Forest Health Management (FHM) survey was a nationwide sample point assessment conducted between 2011 and 2015. However, there are limitations in representing the health of forests that occupy 63.7% of Korea’s land area due to the nature of sample point surveys, which survey a relatively small area. Accordingly, a species richness map was created to promote species diversity in forest health evaluations in Republic of Korea. The map was created using data from the first FHM survey, which examined 28 factors with 12 survey indicators in four categories: tree health, vegetation health, soil health, and atmospheric health. We conducted an ensemble modeling of species distribution for woody plant species that are major habitats in Republic of Korea. To select the species, we used the first FHM survey data and chose those with more than 100 sample points, resulting in a total of 11 species. We then created the species richness map of Republic of Korea by overlaying their distributions. To verify the accuracy of the derived map, an independent verification was conducted using statistical verification and external data from the National Natural Environment Survey. To support forest management that accounts for climate change adaptation, the derived species richness map was validated based on the vegetation climate distribution map of the Korean Peninsula, which was published by the Korea National Arboretum. The map confirmed that species richness is highest around the boundary of the deciduous forest in the central temperate zone and lowest around the evergreen and deciduous mixed forest in the southern temperate zone. By establishing this map, it was possible to confirm the spatial distribution of species by addressing the limitations of direct surveys, which are unable to represent all forests. However, it is important to note that not all factors of the first FHM survey were considered during the spatialization process, and the target area only includes Republic of Korea. Thus, further research is necessary to expand the target area and include additional items.

The IPCC Sixth Assessment Report (AR6) reported that global surface temperature continues to increase. Also, recent climate change is widespread and accelerating (IPCC, 2021). Thus, the impact of climate changes we are experiencing will increase in the future. In particular, since agriculture is closely related to the climate and is directly or indirectly affected, climate change is expected to have diverse and severe effects on crops. Therefore, it is necessary to simulate the potential productivity of barley according to climate change, identify the climate change impact, and establish appropriate management and cultivation methods accordingly. In this study, we aim to simulate barley production based on the SSP5-8.5 climate change scenario, which represents the high end of the range of future pathways. As the study area, we selected Jeollabuk-do, an administrative district with the highest barley cultivation in Korea.We used the DSSAT-CERES-Barley (Decision Support System for Agrotechnology Transfer-Crop Environment Resource Synthesis) model for simulating barley production. It requires the Minimum Data Set as input data (i.e., weather, soil, crop management, and experimental data). Thus, we used the data as follows; (1) the High-Resolution SSP Climate Change Scenario, acquired by the Korea Meteorological Administration (KMA), was used for weather data. It has a 1km spatial resolution, (2) Soil data were generated using the information on physical and chemical properties of each soil texture, acquired by the National Institute of Agricultural Sciences, and (3) crop management data was applied according to the standard cultivation methods for barley, and field experimental data from the Rural Development Administration (RDA) were used. In addition, since the genotype-specific parameters have a significant impact on the result, the parameter for the Korean barley cultivar was used suggested by Kim et al. (2013).Furthermore, the mask maps for barley were generated by extracting only cultivated grids in the current and future land use map, and the steps for pre-processing and generating spatial data were done using R programming language and ArcGIS v10.8.The findings of this study are expected to be useful in implementing adaptation plans in the agricultural sector and/or establishing measures to ensure stable barley production under climate change.※ This work was supported by Korea Environment Industry &Technology Institute (KEITI) through "Climate Change R&D Project for New Climate Regime.", funded by Korea Ministry of Environment (MOE) (No. 202201344001)

According to the guidelines of the Nagoya Protocol, species are now recognized as ‘resources’ and owned by each country, thereby emphasizing the significance of biological resources and the importance of the continuous efforts made to systematically manage them. Despite these efforts, climate change, which influences climatic factors such as temperature and precipitation, is expected to negatively impact the struggle for conservation of biological resources by affecting species’ habitats. We aimed to devise methodologies that could be utilized for the management of biological resources, especially valuable tree species, that are experiencing difficulties due to climate change. First, changes in habitat of the northern-region plant Needle fir (Abies holophylla) due to of climate change were estimated using the BIOMOD2 package in R under the RCP8.5 scenario. Second, the time period of management was estimated based on the change in habitat area over time. It is expected that 30% of the current habitat of A. holophylla will be lost by 2030 and 50% will be lost by 2042. Third, four management zones (maintenance, reduction, dispersal, and non-habitat areas) were derived by comparing habitats according to the period of management required. In this case, we compared the present and the time point at which 30% habitat loss (2030) is expected to occur. After that, the management steps that can be taken for each management zone were suggested. Our results show the impact of climate change, especially change in Bio1 (annual mean temperature) and Bio13 (precipitation of wettest month), on species distribution patterns and have potential applicability in biological resource management. We have specified the suitable point of time, area, and direction of management in this study, which will contribute to climate change management planning and policy-making. By doing so, we hope that when a management policy on biological resources is applied, by dividing the four management zones, policymakers will be able to apply a cost-efficient policy.

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.

Jeju island’s unique and diverse species of flora and fauna and well-preserved natural environment earned Jeju the designation as a UNESCO Biosphere Reserve in December 2002(World Heritage Office & Jeju Special Self-Governing Province, 2016). To achieve no net loss and preferably a net gain of this outstanding biodiversity, ‘biodiversity offsets’ can be implemented(BBOP, 2009). Until now, there have been attempts in Korea to introduce the concept of offset, such as the establishment of the ‘Total Natural Resource Conservation’(Lee et al., 2020), but studies on the specific criteria or method of biodiversity offset area are insufficient. It is desirable not to prepare offset area whenever damage occurs, but to select them in consideration of ecological connectivity, environmental functional aspects, and socio-cultural continuity in the planning process(Lee et al., 2020). Therefore, we intend to select the offset area of Jeju Island using the methodology of Pilgrim et al (2012), which derives the relative offsetability in consideration of the biodiversity conservation concern, residual impact magnitude, theoretical offset opportunity, practical offset feasibility. Potential offset area derived from previous studies has already reflected the concept of biodiversity conservation concern, including vulnerability and irreplaceability. Through the Environmental Impact Assessment(EIA) of Jeju Island, the type of development that had a significant impact on biodiversity is selected as an example, and the impact magnitude of the development type is identified. In addition, offset opportunity is derived by considering functional area and natural distribution, and offset feasibility is derived by factors such as developer capacity and financing. Finally, the relative offsetability is evaluated and the offsetability map is established. The characteristics of offset areas are analyzed using the established offsetability map. For instance, the size and patterns of sites with high offsetability can be studied. As a result, the offsetability map is established by evaluating the relative offsetability of potential offset areas. Therefore, it is possible to specifically find where the biodiversity offset is available in Jeju Island, and to identify the offset priority through comparison of the relative offsetability between the selected offset sites. By analyzing the characteristics of the offset area, it is possible to identify what characteristics increase the offsetability, how large it should be to have high offsetability, and what patterns exist between the selected offset areas. This study shows the specific offset area selection process, and through this, it will help to create a roadmap for selecting a site for a biodiversity offset where the biodiversity offset concept was not introduced into the policy. This work was supported by the Korea Environment Industry and Technology Institute (KEITI) through the Decision Support System Development Project for Environmental Impact Assessment, funded by the Korea Ministry of Environment (MOE) (No. 2020002990009). This work was Supported by a Korea University Grant.

Jeju Island, the research area, has been registered as a UNESCO World Natural Heritage Site and has high biodiversity and ecological value, such as designation as a global geopark and biosphere reserve. It also has a beautiful landscape, so it is not only necessary for conservation but also highly demanded as a landscape resource (Kim et al., 2015; Ko, 2011). Accordingly, it is necessary to prioritize the conservation area that can reconcile the conflict between indiscriminate development and nature protection, as well as to establish potential offset sites for ‘No Net Loss’ in order to respond to development impacts. Selecting conservation areas based on biodiversity value can be an effective offset decision-making tool on where and how to prioritize conservation policies (Li et al., 2021; SANBI & UNEP-WCMC, 2016). There have been many studies on biodiversity conservation between excellent ecological value and development pressure in Jeju Island, but there are almost no studies on the implementation conditions of the offset or offset sites. We here aim to map a conservation area map in consideration of the environmental characteristics of Jeju Island and to select a potential offset area that can practically work offset. We will use ‘Zonation’ program, which is a systematic conservation planning-based model. Zonation is a useful land planning tool that can minimize development impact and realize biodiversity offset (Wintle, 2008; Lethomaki & Moilanen, 2013). The biodiversity attributes inputs required for running Zonation are potential habitat data using MaxEnt and environmental variable data. As a result, we will identify the spatial range and location of the potential biodiversity offset area through Zonation Priority Rank Map output. In addition, we can also analyze their spatial and environmental characteristics, and group out the shape of potential offset site composition (size or pattern). This study can be utilized as a basis for feasible offset policy by proposing potential offset areas through selecting conservation areas in Jeju Island. This work was conducted with the support of the Korea Environment Industry & Technology Institute (KEITI) through its Urban Ecological Health Promotion Technology Development Project, and funded by the Korea Ministry of Environment (MOE) (2020002770003).

The IPCC emphasizes the role of forests in the sequestration of greenhouse gases, a significant cause of climate change. Accordingly, it shows the importance of predicting changes in forests due to climate change, evaluating them to reduce vulnerability under adaptive capacity, and finding ways to find climate resilient development pathways. In this study, the KO-G-Dynamic model, a Korean growth model, was linked with the frameworks of AR5 and 6 to assess risk dynamics in the forest growth sector. At this time, the sensitivity is a variability due to the reduction in forest growth, the exposure is the forest as an object, the hazard is climate change, the adaptive capacity is forest management, and the vulnerability is a mechanism that sensitivity could not be adjusted according to adaptive capacity. The risk was assessed by ranking overall risks derived from the process of vulnerability generated by the interaction of the above factors. As a result, the current forests in Korea are age class imbalanced, and the effects of distribution are centered on fast-growing tree species. If climate change and overprotection continue, the vulnerable area expands as sensitivity increases, since the total growth reduces due to increasing over-matured forests. From the regional-based analysis, Gangwon-do and Gyeongsangnam-do mostly consist of the higher V age class, the ratio of ‘very high’ risk grade was high and the area of ‘high’ risk grade changed rapidly. However, after applying forest management scenarios of adaptive capacity such as harvesting, reforestation, and thinning based on Republic of Korea’s forest management policy, the ratio of ‘Low’ risk grades increased according to the reduction of vulnerability areas. Therefore, forest management can act as an important factor to reduce the risk of forest growth in response to climate change.

Purpose: The present study sought to identify prognostic factors for breast cancer survival and recurrence using a machine learning approach and electronic medical record data.Methods: We used a machine learning technique called feature selection to identify factors influencing breast cancer prognosis, and factors affecting survival and recurrence in a Cox regression model. Results: History of relapse, type of surgery, diagnostic route, SEER stage, and hormone therapy all affected breast cancer survival. Recurrence of breast cancer was affected by age, history of diabetes, breast reconstruction, pain, breast lumps, nipple discharge, and the presence of other symptoms. According to the survival analysis based on feature selection, patients with diabetes had a significantly higher risk of early recurrence of breast cancer (hazard ratio, 4.8; 95% confidence interval, 2.04–11.2, p < 0.05). Conclusions: The present study identified several factors associated with breast cancer prognosis. While survival was affected by the diagnostic route, recurrence was primarily influenced by breast cancer symptoms and other underlying health conditions. A more accurate and standardized model considering time-to-event data could be developed in the future to evaluate prognostic factors and predict prognoses, and for clinical validation

This paper quantified carbon budget in the past 30 years (1981–2010) and identified the impact of land cover change on carbon dynamics using vegetation integrated simulator for trace gases (VISIT) model. North Korea was converted from carbon sink to source with 10.72 ± 5.18 Tg C yr−1 of net ecosystem production (NEP) in the 1980s, 3.00 ± 7.96 Tg C yr−1 in the 1990s, and −0.46 ± 5.13 Tg C yr−1 in the 2000s. NEP in South Korea was 10.55 ± 1.09 Tg C yr−1 in the 1980s, 10.47 ± 7.28 Tg C yr−1 in the 1990s, and 6.32 ± 5.02 Tg C yr−1 in the 2000s, showing a gradual decline. In North Korea, NEP was decreased by 0.52 Tg yr−1 in the 1990s due to reduction of forest, and increased by 0.36 Tg yr−1 in the 2000s due to expansion of cropland. In South Korea, it was decreased by 0.24 Tg yr−1 in the 1990s as urban and built-up area expanded, and increased by 0.04 Tg yr−1 in the 2000s with the expansion of forest. These results suggest the importance of forest and land cover management against deforestation for ensuring national carbon balance.