• Ecology and Resilient Infrastructure
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• v.2 no.3
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• pp.206-215
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• 2015

Predicting the changes in the potential distribution of invasive alien plants under climate change is an important and challenging task for the conservation of biodiversity and management of the ecosystems in streams and reservoirs. This study explored the effects of climate change on the potential future distribution of Paspalum distichum var. indutum in the Korean Peninsula. P. distichum var. indutum is an invasive grass species that has a profound economic and environmental impact in the waterfronts of freshwater ecosystems. The Maxent model was used to estimate the potential distribution of P. distichum var. indutum under current and future climates. A total of nineteen climatic variables of Worldclim 1.4 were used as current climatic data and future climatic data predicted by HadGEM2-AO with both RCP 2.6 and RCP 8.5 scenarios for 2050. The predicted current distribution of P. distichum var. indutum was almost matched with actual positioning data. Major environmental variables contributing to the potential distribution were precipitation of the warmest quarter, annual mean temperature and mean temperature of the coldest quarter. Our prediction results for 2050 showed an overall reduction in climatic suitability for P. distichum var. indutum in the current distribution area and its expansion to further inland and in a northerly direction. The predictive model used in this study appeared to be powerful for understanding the potential distribution, exploring the effects of climate change on the habitat changes and providing the effective management of the risk of biological invasion by alien plants.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.171-180
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• 2012

The field of wildlife habitat conservation research has attracted attention as integrated biodiversity management strategies. Considering the status of the species surveying data and the environmental variables in Korea, the GARP and Maxent models optimized for presence-only data could be one of the most suitable models in habitat modeling. For make sure applicability in the domestic environment we applied the machine learning species distribution model for analyzing habitats of the Korea water deer($Hydropotes$ $inermis$ $argyropus$) in the $Sapgyocheon$ watershed, $Chungcheong$ province. We used the $3^{rd}$ National Natural Environment Survey data and 10 environment variables by literature review for the modelling. Analysis results showed that habitats for the Korea water deer were predicted 16.3%(Maxent) and 27.1%(GARP), respectively. In terms of accuracy(training/test) the Maxent(0.85/0.69) was higher than the GARP(0.65/0.61), and the Spearman's rank correlation coefficient result of the Maxent(${\rho}$=0.71, p<0.01) was higher than the result of GARP(${\rho}$=0.55, p<0.05). However results could be depended on sites and target species, therefore selection of the appropriate model considering on the situation will be important to analyzing habitats.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.5
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• pp.1-14
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• 2021

Excessive development and urbanization have destroyed animal, plant, habitats and reduced biodiversity. In order to preserve species diversity, habitat prediction studies are have been conducted at home and overseas using various modeling techniques. This study was conducted to suggest optimal habitat modeling research by comparing HSI and MaxEnt, which are widely used among habitat modeling techniques. The study was targeted on the endangered species of Prionailurus bengalensis in nearby areas (5460.35km2) including Cheonan City, and the same data were used for analysis to compare those models. According to the HSI analysis, Prionailurus bengalensis's habitat probability was 74.65% for less than 0.5 and 25.34% for more than 0.5 and the top 30% were forest (99.07%). MaxEnt's analysis showed that 56.22% of those below 0.5 and 43.79% of those above 0.5 were found to have a high explanatory power of 78.3% of AUC. The Paired Wilcoxn test, which evaluated the significance of thoes models, confirmed that the mean difference between the two models was statistically significant (p<0.05). Analysis of the differences in the results of those models using the matrix table shows that score 24.43% HSI and MaxEnt was accordance,12.44% of the 0.0 to 0.2 section, 7.22% of the 0.2 to 0.4 section, 2.73% of the 0.4 to 0.6 section, 1.96% of the 0.6 to 0.8, and 0.08% of the 0.9 to 1.0. To verify where the score difference appears, the result values of those models were reset to values from 1 to 5 and overlaid. Overlapping analysis resulted in 30.26% of the Strongly agree values, 56.77% of the agree values, and 11.92% of the Disagree values. The places where the difference in scores occurs were analyzed in the order of forest (45.23%), agricultural land (34.57%), and urbanization area (7.65%). This confirmed that the analysis of the same target species within the same target site also has differences in forecasts depending on the modelling method. Therefore, a novel analysis method combining the advantages of each modeling in habitat prediction studies should be developed, and future study may be used to select Prionailurus bengalensis and species-protected areas and species protection areas in the future. Further research is judged to require higher accuracy studies through the use of various modeling techniques and on-site verification.

• Journal of Forest and Environmental Science
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• v.28 no.3
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• pp.158-169
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• 2012

Sabah has experienced a rapid decline in the extent of forest cover. The precise impact of habitat loss on the conservation status of the plants of Sabah is uncertain. In this study we use the niche modelling algorithm MAXENT to construct preliminary, revised and final ecological niche models for Dipterocarpus lamellatus and Dipterocarpus ochraceus and combined these models with data on current land-use to derive conservation assessments for each species. Preliminary models were based on herbarium data alone. Ground surveys were conducted to evaluate the performance of these preliminary models, and a revised niche model was generated from the combined herbarium and ground survey data. The final model was obtained by constraining the predictions of the revised models by filters. The range overlap between the preliminary and revised models was 0.47 for D. lamellatus and 0.39 for D. ochraceus, suggesting poor agreement between them. There was substantial variation in estimates of habitat loss for D. ochraceus, among the preliminary, revised and constrained models, and this has the potential to lead to incorrect threat assessments. From these estimates of habitat loss, the historic distribution and estimates of population size we determine that both species should be classified as Critically Endangered under IUCN Red List guidelines. Our results suggest that ground-truthing of ecological niche models is essential, especially if the models are being used for conservation decision making.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.1
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• pp.31-52
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• 2024

Considering the significant relationship between a tree's branch structure and physiology, understanding the detailed branch structure is crucial for fields such as species classification, and 3D tree modelling. Recently, terrestrial laser scanning (TLS) and quantitative structure model (QSM) have enhanced the understanding of branch structures by capturing the radius, length, and branching angle of branches. Previous studies examining branch structure with TL S and QSM often relied on mean or median of branch structure parameters, such as the radius ratio and length ratio in parent-child relationships, as representative values. Additionally, these studies have typically focused on the relationship between trunk and the first order branches. This study aims to explore the distribution of branch structure parameters up to the third order in Aesculus hippocastanum, Ginkgo biloba, and Prunus yedoensis. The gamma distribution best represented the distributions of branch structure parameters, as evidenced by the average of Kolmogorov-Smirnov statistics (radius = 0.048; length = 0.061; angle = 0.050). Comparisons of the mode, mean, and median were conducted to determine the most representative measure indicating the central tendency of branch structure parameters. The estimated distributions showed differences between the mode and mean (average of normalized differences for radius ratio = 11.2%; length ratio = 17.0%; branching angle = 8.2%), and between the mode and median (radius ratio = 7.5%; length ratio = 11.5%; branching angle = 5.5%). Comparisons of the estimated distributions across branch orders and species were conducted, showing variations across branch orders and species. This study suggests that examining the estimated distribution of the branch structure parameter offers a more detailed description of branch structure, capturing the central tendencies of branch structure parameters. We also emphasize the importance of examining higher branch orders to gain a comprehensive understanding of branch structure, highlighting the differences across branch orders.