The study aims to establish a direction for forest ecological restoration by classifying forest types and understanding the ecological characteristics of the Uljin forest area damaged by a large fire in 2022. Hierarchical cluster analysis and indicator species analysis were conducted on 78 survey plots located in the forest fire-affected area, and four forest cover types were derived: P. densiflora pure forests, P. densiflora dominant forests, mixed broad-leaved forests, and Q. variabilis dominant forests. As a result of visually comparing changes in forest types before and after forest fire damage, by classifying data according to whether or not upper dead trees are included, it was confirmed that pine forests, which have a high proportion of pine trees, spread widely due to forest fire damage. However, broad-leaved mixed forests and oyster oak dominant forests showed characteristics of maintaining concentration, indicating that pine forests were severely damaged. As a result of the important value analysis, during the process of natural recovery after a forest fire, the species that appear early in the lower layer are the sprouts of existing species such as Quercus mongolica Fisch. ex Ledeb., Quercus variabilis Blume, Fraxinus sieboldiana Blume, Rhododendron mucronulatum Turcz. The distribution of diameter at breast height by forest cover type showed that among areas with extreme forest fire damage, the proportion of dead trees was relatively high and structural changes were large in P. densiflora pure forests and P. densiflora dominant forests where pine trees had a high distribution ratio. However, if continuous monitoring is carried out in the future with reference to the results of this study and plant data is collected and analyzed from a mid- to long-term perspective, it is believed that it will be used as useful data to promote forest ecological restoration projects in forest fire-affected areas.

The purpose of this study is to investigate the habitat of Luciola unmunsana to understand the status of land snails, which are the larvae prey, and to evaluate the effects of larval feeding preferences and prey size for the restoration of the L. unmunsana habitat as a basis for future restoration projects. The research methods included field surveys of the habitat and laboratory experiments on feeding preferences using three types of land snails (Allopeas clavulinum kyotoense, Euphaedusa fusaniana, Pupinella rufa) observed in the habitat. Field surveys of 13 L. unmunsana habitat sites revealed a total of 24 land snail species. The experimental results regarding the larvae prey were analyzed for statistical significance of feeding preferences using Chi-square tests and independent sample t-tests. Consequently, larvae showed the highest preference for A. c. kyotoense, with statistically significant differences in feeding preferences (p<0.05). Also, statistically significant differences were observed in the size between the land snails that were eaten as prey and those that were not eaten. This research can deepen the understanding of the feeding preferences of L. unmunsana larvae and provide practical guidelines for the effective conservation and restoration strategies of the firefly habitat.

Legally protected species are one of the crucial considerations in the field of natural ecology when conducting environmental impact assessments (EIAs). The occurrence of legally protected species, especially 'Endangered Wildlife' designated by Ministry of Environment, significantly influences the progression of projects subject to EIA, necessitating clear investigations and presentations of their habitats. In perspective of statistics, a minimum of 30 occurrence coordinates is required for population prediction, but most of endangered wildlife has insufficient coordinates and it posing challenges for distribution prediction through modeling. Consequently, this study aims to propose modeling methodologies applicable when coordinate data are limited, focusing on Rodgersia podophylla, representing characteristics of endangered wildlife and northern plant species. For this methodology, 30 random sampling coordinates were used as input data, assuming little survey data, and modeling was performed using individual models included in BIOMOD2. After that, the modeling results were evaluated by using discrimination capacity and the reality reflection ability. An optimal modeling technique was proposed by ensemble the remaining models except for the MaxEnt model, which was found to be less reliable in the modeling results. Alongside discussions on discrimination capacity metrics(e.g. TSS and AUC) presented in modeling results, this study provides insights and suggestions for improvement, but it has limitations that it is difficult to use universally because it is not a study conducted on various species. By supporting survey site selection in EIA processes, this research is anticipated to contribute to minimizing situations where protected species are overlooked in survey results.

Heavy metals emitted from urban development do not decompose in the soil and remain for long periods, continually impacting the environment. Since the mid-1990s, there has been increasing societal concern in South Korea regarding soil contamination, prompting various legislative revisions to reduce pollution. This study utilizes the Environmental Impact Assessment Support System (EIASS) to investigate projects in the metropolitan area that have exceeded the Ministry of Environment's soil contamination concern levels from 1989 to 2022 and to examine improvements in the environmental impact assessment (EIA) process. The results reveal that the average concentrations of nine contaminants-cadmium (Cd), copper (Cu), arsenic (As), mercury (Hg), lead (Pb), hexavalent chromium (Cr6+), zinc (Zn), nickel (Ni), and fluoride (F)-have all increased over the years. Among these, Zn had the highest relative proportion, with 37.5% of the 40 sites exceeding environmental concern levels. Investigation of 19 specific projects at these exceedance sites showed that only 7 had documented analyses of contamination causes and remediation plans, and just one had contracted additional remediation services, though results from these efforts were found to be lacking. Furthermore, since 2019, a significant proportion of these sites were involved in residential developments, likely due to government initiatives in new city development and extensive housing supply plans. This research emphasizes the importance of public disclosure of the processes and outcomes of remediation efforts on historically contaminated soils prior to project development. It discusses improvements to the EIA by reviewing current legislation and international examples. The findings of this study are expected to heighten public awareness about heavy metal contamination and enhance transparency in soil remediation efforts, contributing to sustainable environmental management and development.

Coastline changes evolution of different intensities at all times under the influence of natural and anthropogenic effects. In this paper, we extracted the coastline of the Tumen River estuary from 1985 to 2020 using the digitizing method, verified the accuracy using the visual interpretation results, and analyzed the changes of the coastline of the Tumen River estuary through the area method and the baseline method. The results showed that the coastline showed an erosion trend during 35 years, with an average erosion rate of 0.05 m/year, an average erosion distance of 3.06 m, and an erosion area of 19.25 ha. Among the human activities that retarded the erosion of the coastline, these activities had a long-term impact on the natural morphology of the coastline.

In the context of rapid temperature rise in mid-to-high latitude regions, cold region wetlands have become a hotspot for current wetland carbon cycle research due to their high sensitivity to climate change. Strengthening the monitoring of CO₂ fluxes in wetland ecosystems is of great practical significance for clarifying the carbon balance of wetlands and maintaining the ecological balance of wetland ecosystems in China's high latitude regions. In this study, the carbon flux (NEE, Net ecosystem exchange; GPP, Gross Primary Production; RECO, Ecosystem response) of Jingxin Wetland was monitored by eddy correlation method from August 2021 to March 2024.2022-2023 shows CO₂ sinks, absorbing 349.4 g C·m^-2·yr^-1 annually. The correlation analysis showed that Ta, VPD and PPFD were the main environmental factors affecting CO₂ flux in Jingxin wetland.