• Journal of Ecology and Environment
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• v.34 no.2
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• pp.203-214
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• 2011

The objectives of this research were to predict land-use/land-cover change at the Sakaerat Environmental Research Station (SERS) and to analyze its consequences on the distribution for Black-crested Bulbul (Pycnonotus melanicterus), which is a popular species for bird-watching activity. The Dyna-CLUE model was used to determine land-use allocation between 2008 and 2020 under two scenarios. Trend scenario was a continuation of recent land-use change (2002-2008), while the integrated land-use management scenario aimed to protect 45% of study area under intact forest, rehabilitated forest and reforestation for renewable energy. The maximum entropy model (Maxent), Geographic Information System (GIS) and FRAGSTATS package were used to predict bird occurrence and assess landscape fragmentation indices, respectively. The results revealed that parts of secondary growth, agriculture areas and dry dipterocarp forest close to road networks would be converted to other land use classes, especially eucalyptus plantation. Distance to dry evergreen forest, distance to secondary growth and distance to road were important factors for Black-crested Bulbul distribution because this species prefers to inhabit ecotones between dense forest and open woodland. The predicted for occurrence of Black-crested Bulbul in 2008 covers an area of 3,802 ha and relatively reduces to 3,342 ha in 2020 for trend scenario and to 3,627 ha for integrated-land use management scenario. However, intact habitats would be severely fragmented, which can be noticed by total habitat area, largest patch index and total core area indices, especially under the trend scenario. These consequences are likely to diminish the recreation and education values of the SERS to the public.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.5
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• pp.45-58
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• 2020

This study was conducted to comprehend the spatial distribution characteristics, habitats and appearances of Hydropotes inermis by using the biotope mapping in Daebudo Island, Ansan-si. The result is base data to understand status and manage potential inhabitation of Hydropotes inermis in Daebudo Island through the Maximum Entropy model. The study used 105 traces from the primary investigation and 452 traces in the secondary investigation. The biotope types were distinquished Hydropotes inermis habitats largest from the order of natural forest (15.1%), natural coast (13.7%), marshy cultivated land (12.6%), and dry cultivated land (11.7%), and from the inhabitation trace results. Hydropotes inermis appearanced biotope types were the greatest in the order of cultivated land (49.73%) > forest (18.85%) > coast (7.00%) > grassland (6.28%). Since forests in Daebudo Island have low slope and altitude, it was concluded that Hydropotes inermis would live in most of the forests. A high number of Hydropotes inermis was found to appear in areas where the grassland is formed including cultivated lands (include unused paddies and fields) and marshy grasslands, which would result in direct damage of crops. According to the Maxent modeling analysis that used location information of Hydropotes inermis, the AUC value was 0.635 based on the ROC curve. In Daebudo Island, areas with over 0.635 potential inhabitation value are distributed all over the place, and it was concluded that each population would have a different scope of influence and home range. Hydropotes inermis living in Daebudo Island have high habitat suitability mainly around the cultivated lands near the roads, but due to the bare lands and roads, it is expected that their habitats would be fragmented and damaged, which would have a direct and indirect effect in maintaining the Hydropotes inermis population. Also, considering habitat disturbance, diverse methods for reducing damage including capturing some individuals within the limit that does not disperse Hydropotes inermis population in Daebudo Island must be carried out.

• Journal of Environmental Impact Assessment
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• v.23 no.6
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• pp.453-465
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• 2014

Hotspots are top sites in terms of species diversity as the most threatened and most diverse sites which have been used to select priority areas for reserves. The purpose of this paper is to identify biodiversity hotspots through analyzing nationwide spatial patterns of species richness and rarity of Korean mammals. Four endangered mammals and eleven common mammals were selected as target species. Environmental variables as model input data were consisted of topography, distance, and vegetation structure etc. and Maxent was used to develop species distribution models for target species. Species richness and rarity were used as index of biodiversity. The results of this study were as follows. Firstly, hotspots of species richness for endangered mammals were in high elevation and steep mountain areas. However, species richness for whole mammals were high in low elevation of mountains. Secondly, distribution pattern of species rarity for endangered mammals were similar as richness. However, hotspots of species rarity for whole mammals were a little different from species richness. Species rarity was high in both low and high elevation of mountain areas. This study will provide the useful information for a biodiversity assessment, a habitat conservation, a national ecological network plan, and the management of protected areas.

• 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.