• Korean Journal of Environment and Ecology
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• v.34 no.6
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• pp.589-600
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• 2020

Effective conservation and management of protected areas require monitoring the settlement of invasive alien species and reducing their dispersion capacity. We simulated the potential distribution of invasive alien plant species (IAPS) using three representative species distribution models (Bioclim, GLM, and MaxEnt) based on the IAPS distribution in the forest genetic resource reserve (2,274ha) in Uljin-gun, Korea. We then selected the realistic and suitable species distribution model that reflects the local region and ecological management characteristics based on the simulation results. The simulation predicted the tendency of the IAPS distributed along the linear landscape elements, such as roads, and including some forest harvested area. The statistical comparison of the prediction and accuracy of each model tested in this study showed that the GLM and MaxEnt models generally had high performance and accuracy compared to the Bioclim model. The Bioclim model calculated the largest potential distribution area, followed by GLM and MaxEnt in that order. The Phenomenological review of the simulation results showed that the sample size more significantly affected the GLM and Bioclim models, while the MaxEnt model was the most consistent regardless of the sample size. The optimal model overall for predicting the distribution of IAPS among the three models was the MaxEnt model. The model selection approach based on detailed flora distribution data presented in this study is expected to be useful for efficiently managing the conservation areas and identifying the realistic and precise species distribution model reflecting local characteristics.

• Korean Journal of Environment and Ecology
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• v.32 no.5
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• pp.469-477
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• 2018

Hanabusaya asiatica is an endemic species whose distribution is limited in the mid-eastern part of the Korean peninsula. Due to its narrow range and small population, it is necessary to protect its habitats by identifying it as Key Biodiversity Areas (KBAs) adopted by the International Union for Conservation of Nature (IUCN). In this paper, we estimated potential natural habitats for H. asiatica using maximum entropy model (MaxEnt) and identified candidate sites for KBA based on the model results. MaxEnt is a machine learning algorithm that can predict habitats for species of interest unbiasedly with presence-only data. This property is particularly useful for the study area where data collection via a field survey is unavailable. We trained MaxEnt using 38 locations of H. asiatica and 11 environmental variables that measured climate, topography, and vegetation status of the study area which encompassed all locations of the border region between South and North Korea. Results showed that the potential habitats where the occurrence probabilities of H. asiatica exceeded 0.5 were $778km^2$, and the KBA candidate area identified by taking into account existing protected areas was $1,321km^2$. Of 11 environmental variables, elevation, annual average precipitation, average precipitation in growing seasons, and the average temperature in the coldest month had impacts on habitat selection, indicating that H. asiatica prefers cool regions at a relatively high elevation. These results can be used not only for identifying KBAs but also for the reference to a protection plan for H. asiatica in preparation of Korean reunification and climate change.

• Korean Journal of Environmental Biology
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• v.36 no.4
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• pp.672-679
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• 2018

This study was conducted to predict the potential distribution and risk of invasive alien plant, Amaranthus patulus, in an agricultural area of South Korea. We collected 254 presence localities of A. patulus using field survey and literature search and stimulated the potential distribution area of A. patulus using maximum entropy modeling (MaxEnt) with six climatic variables. Two different kinds of agricultural risk index, raster risk index and regional risk index, were estimated. The 'raster risk index' was calculated by multiplying the potential distribution by the field area in $1{\times}1km$ and 'regional risk index' was calculated by multiplying the potential distribution by field area proportion in the total field of South Korea. The predicted potential distribution of A. patulus was almost matched with actual presence data. The annual mean temperature had the highest contribution for distribution modeling of A. patulus. Area under curve (AUC) value of the model was 0.711. The highest regions were Gwangju for potential distribution, Jeju for 'raster risk index' and Gyeongbuk for 'regional risk index'. This different ranks among the index showed the importance about the development of various risk index for evaluating invasive plant risk.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.274-274
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• 2019

• Korean Journal of Environmental Biology
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• v.40 no.2
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• pp.214-223
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• 2022

Among migratory insect pests, Mythimna seperata and Cnaphalocrocis medinalis are invasive pests introduced into South Korea through westerlies from southern China. M. seperata and C. medinalis are insect pests that use rice as a host. They injure rice leaves and inhibit rice growth. To understand the distribution of M. seperata and C. medinalis, it is important to understand environmental factors such as temperature and humidity of their habitat. This study predicted current and future habitat suitability models for understanding the distribution of M. seperata and C. medinalis. Occurrence data, SSPs (Shared Socio-economic Pathways) scenario, and RCP (Representative Concentration Pathway) were applied to MaxEnt (Maximum Entropy), a machine learning model among SDM (Species Distribution Model). As a result, M. seperata and C. medinalis are aggregated on the west and south coasts where they have a host after migration from China. As a result of MaxEnt analysis, the contribution was high in the order of Land-cover data and DEM (Digital Elevation Model). In bioclimatic variables, BIO_4 (Temperature seasonality) was high in M. seperata and BIO_2 (Mean Diurnal Range) was found in C. medinalis. The habitat suitability model predicted that M. seperata and C. medinalis could inhabit most rice paddies.

• Ecology and Resilient Infrastructure
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• v.2 no.3
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• pp.198-205
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• 2015

Impacts of climate change on aquatic ecosystems range from changes in physiological processes of aquatic organisms to species distribution. In this study, MaxEnt that has high prediction power without nonoccurrence data was used to simulate fish distribution changes in the Geum river watershed according to climate change. The fish distribution in 2050 and 2100 was predicted with RCP 8.5 climate change scenario using fish occurrence data (a total of 47 species, including 17 endemic species) from 2007 to 2009 at 134 survey points and 9 environmental variables (monthly lowest, highest and average air temperature, monthly precipitation, monthly lowest, highest and average water temperature, altitude and slope). The fitness of MaxEnt modeling was successful with the area under the relative operating characteristic curve (AUC) of 0.798, and environmental variables that showed a high level of prediction were as follows: altitude, monthly average precipitation and monthly lowest water temperature. As climate change proceeds until 2100, the probability of occurrence for Odontobutis interrupta and Acheilognathus yamatsuatea (endemic species) decreases whereas the probability of occurrence for Microphysogobio yaluensis and Lepomis macrochirus (exotic species) increases. In particular, five fish species (Gnathopogon strigatus, Misgurnus mizolepis, Erythroculter erythropterus, A. yamatsuatea and A. koreensis) were expected to become extinct in the Geum river watershed in 2100. In addition, the species rich area was expected to move to the northern part of the Geum river watershed. These findings suggest that water temperature increase caused by climate change may disturb the aquatic ecosystem of Geum river watershed significantly.

• Journal of Korean Society of Forest Science
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• v.111 no.1
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• pp.50-60
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• 2022

In this study, habitat suitability was analyzed for three major honey tree species, namely Kalopanax septemlobus, Tilia amurensis, and Styrax obassis, in the Baekdudaegan Mountains using MaxEnt models. The AUC values indicating the prediction accuracies of the models were 0.747, 0.790, and 0.755 for K. septemlobus, T. amurensis, and S. obassis, respectively. The most important variables for K. septemlobus and T. amurensis were elevation, mean annual temperature, and slope, whereas mean annual temperature, elevation, and mean annual precipitation were the most important predictors for S. obassis. For all three studied species, elevation and mean annual temperature were the most important topographic and climatic factors, respectively, indicating that such variables are crucial for explaining species distribution. Honey tree species are essential resources in forest beekeeping, a high value-added process for improving forest income, and this study identified sites with the potential for management of such species in the Baekdudaegan Mountains, where it may be possible to establish a honey forest. However, the accuracy of the models should be improved through comprehensive analysis with abiotic variables, such as soil properties and aridity, which affect the distribution of honey tree species, as well as biotic variables, such as interspecific competition.

• Ecology and Resilient Infrastructure
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• v.9 no.4
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• pp.282-289
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• 2022

Analyzing the impact of climate change on the Korean Peninsula on the forest ecosystem is important for the management of subtropical forest bioresources. In this study, we collected location data and bioclimatic variables of the warm-temperate woody plant species, Myrica rubra and Cyzygium buxifolium, and applied the MaxEnt model based on the collected data to estimate the potential distribution area. Precipitation and temperature seasonality in the warmest quarter were the main environmental factors that determined the distribution of M. rubra, and the main environmental factors for S. buxifolium were precipitation in the warmest quarter and precipitation in the wettest quarter. The results of the MaxEnt model by administrative district, the M. rubra showed an area increase rate of 4.6 - 17.7% in the SSP2-4.5 climate change scenario and 13.8 - 30.5% in the SSP5-8.5 climate change scenario. S. buxifolium showed area increase rates of 4.8 - 32.2% in the SSP2-4.5 climate change scenario and 12.9 - 48.6% in the SSP5-8.5 climate change scenario. This study is meaningful in establishing a database and identifying future potential distribution areas of warm and subtropical plants by applying climate change scenarios.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.35 no.2
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• pp.87-97
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• 2017

Paulownia species has long been recognized in Korean traditional culture and the values of the species have been researched in various focuses. However, studies on distribution and ecological characteristics of the species are still needed. This study aimed to identify distribution trends and ecological characteristics of two Paulownia species in Busan metropolitan city using the MaxEnt model. The MaxEnt model was established based on the environmental factors such as positioning information of the Paulownia species, topography, climate and degree of anthropogenic disturbance potentiality (ADP), which was collected in the on-site research. The study verified that the accuracy of the model was appropriate as the AUC value of Paulownia coreana and P. tomentosa was 0.809, respectively. In terms of the distribution trends of the two Paulownia species in the research area depending on the distribution model, they were both mainly distributed in downtown where built-up area and bare ground were densely concentrated. The potential distribution area of the two species was identified as $137.4km^2$ for P. coreana and $135.0km^2$ for P. tomentosa. The distribution probability was high in Jung-gu, Dongrae-gu, Busanjin-gu and Yeonje-gu. As a result of the analysis on contribution of the environmental factors, it was turned out that the degree of anthropogenic disturbance potentiality (ADP) contributed to distribution of P. coreana and P. tomentosa by about 50%, and the contribution of the environmental factors had a positive correlation with the degree of ADP. The elevation had a negative correlation with both the two species, which was considered because the species must compete more with native species in natural habitats as the altitude above sea level rises. The research findings demonstrated numerically that the distribution of P.coreana and P. tomentosa depended on artificial activities, and indicated the relevance with the Korean traditional landscape. These findings are expected to provide meaningful information in using, preserving and restoring Paulownia species.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.2
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• pp.47-56
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• 2020

Decline of pine forests happens in Korea due to various disturbances such as insect pests, forest fires and extreme climate, which may further continue with ongoing climate change. For conserving and reestablishing pine forests, understanding climate-induced future shifts of pine tree distribution is a critical concern. This study predicts future geographical distribution of Pinus densiflora, using Maximum Entropy Model (MaxEnt). Input data of the model are locations of pine tree stands and their environmental variables such as climate were prepared for the model inputs. Alternative future projections for P. densiflora distribution were conducted with RCP 4.5 and RCP 8.5 climate change scenarios. As results, the future distribution of P. densiflora steadily decreased under both scenarios. In the case of RCP 8.5, the areal reductions amounted to 11.1% and 18.7% in 2050s and 2070s, respectively. In 2070s, P. densiflora mainly remained in Kangwon and Gyeongsang Provinces. Changes in temperature seasonality and warming winter temperature contributed primarily for the decline of P. densiflora., in which altitude also exerted a critical role in determining its future distribution geographic vulnerability. The results of this study highlighted the temporal and spatial contexts of P. densiflora decline in Korea that provides useful ecological information for developing sound management practices of pine forests.