• Korean Journal of Plant Taxonomy
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• v.50 no.2
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• pp.154-165
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• 2020

Coastal regions are experiencing habitat changes due to coastal development and global warming. To estimate the future distribution of coastal plants on the Korean Peninsula due to climate change, the potential distribution of ten species of coastal plants was analyzed using the MaxEnt program. The study covered the eastern, western, and southern coastal areas of the Korean Peninsula. We used the distributional data of coastal plants of the East Asian region and the 19 climate variables of WorldClim 2.0. The future potential distribution was estimated using future climate variables projected from three general circulation models (CCSM4, MIROC-ESM, and MPI-ESM-LR), four representative concentration pathways (2.5, 4.5, 6.0, and 8.5), and two time periods (2050 and 2070). The annual mean temperature influenced the estimation of the potential distribution the most. Under predicted future distribution scenarios, Lathyrus japonicus, Glehnia littoralis, Calystegia soldanella, Vitex rotundifolia, Scutellaria strigillosa, Linaria japonica, and Ixeris repens are expected to show contracted distributions, whereas the distribution of Cnidium japonicum is expected to expand. Two species, Salsola komarovii and Carex kobomugi, are predicted to show similar distributions in the future compared to those in the present. The average potential distribution in the future suggests that the effects of climate change will be greater in the west and the south coastal regions than in the east coastal region. These results will be useful baseline data to establish a conservation strategy for coastal plants.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.139-151
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• 2017

The habitat preference of roe deers(Capreolus pygargus) in Jeju island, South Korea was analyzed by using their occurrence probability in MaxEnt model in this study. Totally 490 surveying data were gathered and 15 environmental variables were chosen for the model in which 6 variables out of 15 ones were filtered and finally removed because of there being higher correlation(over 0.7 in correlation coefficient). According to the modeling, roe deers were known to prefer the area ranging from 200 to 700 meter and over 1,500 meter in sea level, where there were not many dominant tree and/or dominant vegetation with low density so that understory vegetation can grow well with plentiful sunlight and can be used as a food of herbivore like roe deers. Otherwise, the region ranging from 700 to 1,500 meter was mostly covered with high density vegetation which cut off sunlight trying to penetrate through the dominant vegetation. It can cause a lower density of vegetation on surface, which can not attract to roe deers.

• Ecology and Resilient Infrastructure
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• v.8 no.3
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• pp.154-163
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• 2021

This study was carried out to identify the factors affecting the distribution of suitable habitats for Geranium carolinianum, which was naturalized in South Korea, and to predict the changes of distribution in the future. We collected occurrence data of G. carolinianum at 68 sites in South Korea, and applied the MaxEnt model under climate change scenarios (SSP2-4.5, and SSP5-8.5). Precipitation seasonality (bio15), mean temperature of warmest quarter (bio10), and mean temperature of driest quarter (bio09) had high contribution for potential distribution of G. carolinianum. According to climate change scenarios, high suitable habitats of G. carolinianum occupied 6.43% of the land of South Korea in historical period (1981~2010), and 92.60% under SSP2-4.5, and 98.36% undr SSP5-8.5 in far future (2071~2100).

• Korean Journal of Ecology and Environment
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• v.48 no.4
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• pp.229-237
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• 2015

This study aims to offer basic data to effectively preserve and manage pine forests using more precise pine forests' distribution status. In this regard, this study predicts the geographical distribution change of pine forests growing in South Korea, due to climate change, and evaluates the spatial distribution characteristics of pine forests by age. To this end, this study predicts the potential distribution change of pine forests by applying the MaxEnt model useful for species distribution change to the present and future climate change scenarios, and analyzes the effects of bioclimatic variables on the distribution area and change by age. Concerning the potential distribution regions of pine forests, the pine forests, aged 10 to 30 years in South Korea, relatively decreased more. As the area of the region suitable for pine forest by age was bigger, the decreased regions tend to become bigger, and the expanded regions tend to become smaller. Such phenomena is conjectured to be derived from changing of the interaction of pine forests by age from mutual promotional relations to competitive relations in the similar climate environment, while the regions suitable for pine forests' growth are mostly overlap regions. This study has found that precipitation affects more on the distribution of pine forests, compared to temperature change, and that pine trees' geographical distribution change is more affected by climate's extremities including precipitation of driest season and temperature of the coldest season than average climate characteristics. Especially, the effects of precipitation during the driest season on the distribution change of pine forests are irrelevant of pine forest's age class. Such results are expected to result in a reduction of the pine forest as the regions with the increase of moisture deficiency, where climate environment influencing growth and physiological responses related with drought is shaped, gradually increase according to future temperature rise. The findings in this study can be applied as a useful method for the prediction of geographical change according to climate change by using various biological resources information already accumulated. In addition, those findings are expected to be utilized as basic data for the establishment of climate change adaptation policies related to forest vegetation preservation in the natural ecosystem field.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.802-811
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• 2023

Marine spatial planning (MSP) is a crucial element for rational allocation and sustainable use of marine areas. Particularly, Fishing Activity Protected Areas constitute essential zones accounting for 45.6% designated for sustainable fishing activities. However, the current assessment of these zones does not adequately consider future demands and potential values, necessitating appropriate evaluation methods and predictive tools for long-term planning. In this study, we selected key fish species (Scomber japonicus, Trichiurus lepturus, Engraulis japonicus, and Larimichthys polyactis) within the Fishing Activity Protected Area to predict their distribution and compare it with the current designated zones for evaluating the ability of the prediction tool. Employing the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report scenarios (SSP1-2.6 and SSP5-8.5), we used species distribution models (such as MaxEnt) to assess the movement and distribution changes of these species owing to future variations. The results indicated a 30-50% increase in the distribution area of S. japonicus, T. lepturus, and L. polyactis, whereas the distribution area of E. japonicus decreased by approximately 6-11%. Based on these results, a species richness map for the four key species was created. Within the marine spatial planning boundaries, the overlap between areas rated "high" in species richness and the Fishing Activity Protected Area was approximately 15%, increasing to 21% under the RCP 2.6 scenario and 34% under the RCP 8.5 scenario. These findings can serve as scientific evidence for future evaluations of use zones or changes in reserve areas. The current and predicted distributions of species owing to climate change can address the limitations of current use zone evaluations and contribute to the development of plans for sustainable and beneficial use of marine resources.

• Korean Chemical Engineering Research
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• v.58 no.2
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• pp.197-208
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• 2020

This study was carried out to analyze spatial and temporal incidence characteristics of scrub typhus and predict the future incidence of scrub typhus since the incidences of scrub typhus have been rapidly increased among vector-borne diseases. A maximum entropy (MaxEnt) ecological model was implemented to predict spatial distribution and incidence rate of scrub typhus using spatial data sets on environmental and social variables. Additionally, relationships between the incidence of scrub typhus and critical spatial data were analyzed. Elevation and temperature were analyzed as dominant spatial factors which influenced the growth environment of Leptotrombidium scutellare (L. scutellare) which is the primary vector of scrub typhus. A temporal number of diseases by scrub typhus was predicted by a deep neural network (DNN). The model considered the time-lagged effect of scrub typhus. The DNN-based prediction model showed that temperature, precipitation, and humidity in summer had significant influence factors on the activity of L. scutellare and the number of diseases at fall. Moreover, the DNN-based prediction model had superior performance compared to a conventional statistical prediction model. Finally, the spatial and temporal models were used under climate change scenario. The future characteristics of scrub typhus showed that the maximum incidence rate would increase by 8%, areas of the high potential of incidence rate would increase by 9%, and disease occurrence duration would expand by 2 months. The results would contribute to the disease management and prediction for the health of residents in terms of public health.

• Journal of Environmental Impact Assessment
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• v.27 no.2
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• pp.203-214
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• 2018

The purpose of this study is to estimate the concentrated distribution area of nutria (Myocastor coypus) and potential suitable habitat and to provide useful data for the effective management direction setting. Based on the nationwide distribution data of nutria, the cross-validation value was applied to analyze the distribution density. As a result, the concentrated distribution areas thatrequired preferential elimination is found in 14 administrative areas including Busan Metropolitan City, Daegu Metropolitan City, 11 cities and counties in Gyeongsangnam-do and 1 county in Gyeongsangbuk-do. In the potential suitable habitat estimation using a MaxEnt (Maximum Entropy) model, the possibility of emergency was found in the Nakdong River middle and lower stream area and the Seomjin riverlower stream area and Gahwacheon River area. As for the contribution by variables of a model, it showed DEM, precipitation of driest month, min temperature of coldest month and distance from river had contribution from the highest order. In terms of the relation with the probability of appearance, the probability of emergence was higher than the threshold value in areas with less than 34m of altitude, with $-5.7^{\circ}C{\sim}-0.6^{\circ}C$ of min temperature of the coldest month, with 15-30mm of precipitation of the driest month and with less than 1,373m away from the river. Variables that Altitude, existence of water and wintertemperature affected settlement and expansion of nutria, considering the research results and the physiological and ecological characteristics of nutria. Therefore, it is necessary to reflect them as important variables in the future habitable area detection and expansion estimation modeling. It must be essential to distinguish the concentrated distribution area and the management area of invasive alien species such as nutria and to establish and apply a suitable management strategy to the management site for the permanent control. The results in this study can be used as useful data for a strategic management such as rapid management on the preferential management area and preemptive and preventive management on the possible spreading area.

• Korean journal of applied entomology
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• v.57 no.3
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• pp.127-135
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• 2018

Climate change can affect variables related to the life cycle of insects, including growth, development, survival, reproduction and distribution. As it encourages alien insects to rapidly spread and settle, climate change is regarded as one of the direct causes of decreased biodiversity because it disturbed ecosystems and reduces the population of native species. Hypera postica caused a great deal of damage in the southern provinces of Korea after it was first identified on Jeju lsland in the 1990s. In recent years, the number of individuals moving to estivation sites has concerned scientists due to the crop damage and national proliferation. In this study, we examine how climate change could affect inhabitation of H. postica. The MaxEnt model was applied to estimate potential distributions of H. postica using future climate change scenarios, namely, representative concentration pathway (RCP) 4.5 and RCP 8.5. As variables of the model, this study used six bio-climates (bio3, bio6, bio10, bio12, bio14, and bio16) in consideration of the ecological characteristics of 66 areas where inhabitation of H. postica was confirmed from 2015 to 2017, and in consideration of the interrelation between prediction variables. The fitness of the model was measured at a considered potentially useful level of 0.765 on average, and the warmest quarter has a high contribution rate of 60-70%. Prediction models (RCP 4.5 and RCP 8.5) results for the year 2050 and 2070 indicated that H. postica habitats are projected to expand across the Korean peninsula due to increasing temperatures.

• Korean Journal of Ecology and Environment
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• v.47 no.3
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• pp.160-166
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• 2014

This study was aimed at looking into the distribution status and age structure of Abies holophylla population in Sudo-Am temple forest. It was found that a total of 302 individuals of Abies holophylla existed which were more than 2m in height within the study area. Furthermore the population size is one of the largest in the southern region of Korea. The CBH of Abies holophylla ranged from 1.5 cm to 500.8 cm. Age structure of Abies holophylla looks like a gourd-shaped bottle. This means that they have an unstable structure status and do not survive very long. This status results from a variety of factors including, vegetation succession, anthropogenic activities, and global warming. The environmental characteristics of Abies holophylla population was $931{\pm}64.5m$ in mean altitude, $19.2{\pm}8.7^{\circ}$ in mean slope in the northeastern and southeastern area of the slope direction, and $1,324,323{\pm}174,459wh\;m^{-2}$ in average of direct normal irradiation. Among the site environmental factors, the significant ones which influence the potential habitat for Abies holophylla distribution were chosen using the MaxEnt model. According to the results of this study, altitude and slope were found as the important factors. The average value of environmental conditions by ROC analysis were altitude 903.2 m, slope $20.04^{\circ}$, irradiation $1,352.248wh\;m^{-2}$, and the southeastern aspect.

• Korean Journal of Environment and Ecology
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• v.29 no.3
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• pp.333-343
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• 2015

This research aims at identifying the goshawk's possible and replaceable breeding ground by using the MaxEnt prediction model which has so far been insufficiently used in Korea, and providing evidence to expand possible protection areas for the goshawk's breeding for the future. The field research identified 10 goshawk's nests, and 23 appearance points confirmed during the 3rd round of environmental research were used for analysis. 4 geomorphic, 3 environmental, 7 distance, and 9 weather factors were used as model variables. The final environmental variables were selected through non-parametric verification between appearance and non-appearance coordinates identified by random sampling. The final predictive model (MaxEnt) was structured using 10 factors related to breeding ground and 7 factors related to appearance area selected by statistics verification. According to the results of the study, the factor that affected breeding point structure model the most was temperature seasonality, followed by distance from mixforest, density-class on the forest map and relief energy. The factor that affected appearance point structure model the most was temperature seasonality, followed by distance from rivers and ponds, distance from agricultural land and gradient. The nature of the goshawk's breeding environment and habit to breed inside forests were reflected in this modeling that targets breeding points. The northern central area which is about $189.5 km^2$(2.55 %) is expected to be suitable breeding ground. Large cities such as Cheongju and Chungju are located in the southern part of Chungcheongbuk-do whereas the northern part of Chungcheongbuk-do has evenly distributed forests and farmlands, which helps goshawks have a scope of influence and food source to breed. Appearance point modeling predicted an area of $3,071 km^2$(41.38 %) showing a wider ranging habitat than that of the breeding point modeling due to some limitations such as limited moving observation and non-consideration of seasonal changes. When targeting the breeding points, a specific predictive area can be deduced but it is difficult to check the points of nests and it is impossible to reflect the goshawk's behavioral area. On the other hand, when targeting appearance points, a wider ranging area can be covered but it is less accurate compared to predictive breeding point since simple movements and constant use status are not reflected. However, with these results, the goshawk's habitat can be predicted with reasonable accuracy. In particular, it is necessary to apply precise predictive breeding area data based on habitat modeling results when enforcing an environmental evaluation or establishing a development plan.