The influx of marine exotic and alien species is disrupting marine ecosystems and aquaculture. Herdmania momus, reported as an invasive species, is distributed all along the coast of Jeju Island and has been confirmed to be distributed and spread to Busan. The potential habitats and distribution of H. momus were estimated using the maximum entropy (MaxEnt) model, quantum geographic information system (QGIS), and Bio-ocean rasters for analysis of climate and environment(Bio-ORACLE), which can predict the distribution and spread based only on species occurrence data using species distribution model (SDM). Temperature and salinity were selected as environmental variables based on previous literature. Additionally, two different representative concentration pathway (RCP) scenarios (RCP 4.5 and RCP 8.5) were set up to estimate future and potential habitats owing to climate change. The prediction of potential habitats and distribution for H. momus using MaxEnt confirmed maximum temperature as the highest contributor(77.1%), and mean salinity, the lowest (0%). And the potential habitats and distribution of H. momus were the highest on Jeju Island, and no potential habitat or distribution was seen in the Yellow Sea. Different RCP scenarios showed that at RCP 4.5, H. momus would be distributed along the coast of Jeju Island in the year 2050 and that the distribution would expand to parts of the Korea Strait by the year 2100. RCP 8.5, the distribution in 2050 is predicted to be similar to that at RCP 4.5; however, by 2100, the distribution is predicted to expand to parts of the Korea Strait and the East Sea. This study can be utilized as basic data to effectively control the ecological injuries by H. momus by predicting its spread and distribution both at present and in the future.
Kim, Hogul;Lee, Dong-Kun;Mo, Yongwon;Kil, Sungho;Park, Chan;Lee, Soojae
Journal of Environmental Impact Assessment
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v.22
no.1
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pp.39-50
/
2013
Occurrence of landslides has been increasing due to extreme weather events(e.g. heavy rainfall, torrential rains) by climate change. Pyeongchang, Korea had seriously been damaged by landslides caused by a typhoon, Ewiniar in 2006. Moreover, the frequency and intensity of landslides are increasing in summer due to torrential rain. Therefore, risk assessment and adaptation measure is urgently needed to build resilience. To support landslide adaptation measures, this study predicted landslides occurrence using MaxEnt model and suggested susceptibility map of landslides. Precipitation data of RCP 8.5 Climate change scenarios were used to analyze an impact of increase in rainfall in the future. In 2050 and 2090, the probability of landslides occurrence was predicted to increase. These were due to an increase in heavy rainfall and cumulative rainfall. As a result of analysis, factors that has major impact on landslide appeared to be climate factors, prediction accuracy of the model was very high(92%). In the future Pyeongchang will have serious rainfall compare to 2006 and more intense landslides area expected to increase. This study will help to establish adaptation measure against landslides due to heavy rainfall.
Background: Climate change is believed to be continuously affecting ticks by influencing their habitat suitability. However, we attempted to model the climate change-induced impacts on future genus Rhipicephalus distribution considering the major environmental factors that would influence the tick. Therefore, 50 tick occuance points were taken to model the potential distribution using maximum entropy (MaxEnt) software and 19 climatic variables, taking into account the ability for future climatic change under representative concentration pathways (RCPs) 4.5 and 8.5, were used. Results: MaxEnt model performance was tested and found with the AUC value of 0.99 which indicates excellent goodness-of-fit and predictive accuracy. Current models predict increased temperatures, both in the mid and end terms together with possible changes of other climatic factors like precipitation which may lead to higher tick-borne disease risks associated with expansion of the range of the targeted tick distribution. Distribution maps were constructed for the current, 2050, and 2070 for the two greenhouse gas scenarios and the most dramatic scenario; RCP 8.5 produced the highest increase probable distribution range. Conclusions: The future potential distribution of the genus Rhipicephalus show potential expansion to the new areas due to the future climatic suitability increase. These results indicate that the genus population of the targeted tick could emerge in areas in which they are currently lacking; increased incidence of tick-borne diseases poses further risk which can affect cattle production and productivity, thereby affecting the livelihood of smallholding farmers. Therefore, it is recommended to implement climate change adaptation practices to minimize the impacts.
Climate change and invasive alien plant species (IAPs) are having a significant impact on mountain ecosystems. The combination of climate change and socio-economic development is exacerbating the invasion of IAPs, which are a major threat to biodiversity loss and ecosystem functioning. Species distribution modelling has become an important tool in predicting the invasion or suitability probability under climate change based on occurrence data and environmental variables. MaxEnt modelling was applied to predict the current suitable distribution of most noxious weed A. adenophora (Spreng) R. King and H. Robinson and analysed the changes in distribution with the use of current (year 2000) environmental variables and future (year 2050) climatic scenarios consisting of 3 representative concentration pathways (RCP 2.6, RCP 4.5 and RCP 8.5) in Bhutan. Species occurrence data was collected from the region of interest along the road side using GPS handset. The model performance of both current and future climatic scenario was moderate in performance with mean temperature of wettest quarter being the most important variable that contributed in model fit. The study shows that current climatic condition favours the A. adenophora for its invasion and RCP 2.6 climatic scenario would promote aggression of invasion as compared to RCP 4.5 and RCP 8.5 climatic scenarios. This can lead to characterization of the species as preferring moderate change in climatic conditions to be invasive, while extreme conditions can inhibit its invasiveness. This study can serve as reference point for the conservation and management strategies in control of this species and further research.
Quantitative habitat model is established with species occurrence and spatial abundance data, which were usually acquired by professional field ecologists and citizen scientists. The importance of citizen science data is increasing, but the quality of these data needs to be evaluated. This study aims to identify and compare both expert-based data and citizen science data based on the performance power of quantitative models derived from both data sets. A Maximum Entropy (MaxENT) model was developed using eight environmental variables, including climate, topography, landcover and distance to forest edge. The AUC values derived from the MaxENT model were 0.842 and 0.809, respectively, indicating a high level of explanatory power. All environmental variables has similar values for both data sets, except for the distance to forest edge and rice paddy, which was relatively higher for expert-based survey data than that of the citizen science data as the distances increased. This result suggests that habitat model derived from expert-based survey data shows more ecological niche including wider ranges from forest edges and isolated habitat patches of rice paddy. This is presumably because citizen scientists focuses on direct observation methods, whereas professional field surveys investigate a wider variety of methods.
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.
Changes in biota, species distribution range shift and catastrophic climate influence due to recent global warming have been observed during the last century. Since global warming affects various sectors, such as agriculture and vegetation, it is important to predict more accurate impact of future climate change. The purpose of this study is to examine the observed distribution of Abeliophyllum distichum in the Korean peninsula. For this purpose, two period (present and future) climate data were used. Mean data between 1950 and 2000, were used as the present value and the year 2050 and 2080 data from A1B senario in IPCC SRES were used for the future value. Potential habitation is analyzed by MaxEnt(Maximum Entropy model), and Abeliophyllum distichum's coordinates data were used as a dependent variable and independent variables are composed of environmental data such as BioClim, altitude, aspect and slope. The result of six types GCM mean calculation, the potential habitability decreased by 40-60% of the average existing distribution. The methodogies and results of this research can be applicable to the climate changing adaptation stratiegies for the biodiversity conservation.
Proceedings of the National Institute of Ecology of the Republic of Korea
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v.4
no.3
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pp.115-126
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2023
Understanding the carrying capacity of a habitat is crucial for effectively managing populations of wild boars (Sus scrofa), which are designated as harmful wild animal species in national parks. Carrying capacity refers to the maximum population size supported by a park's environmental conditions. This study aimed to estimate the appropriate wild boar population size by integrating population characteristics and habitat suitability for wild boars in the Bukhansan National Park using the HexSim program. Population characteristics included age, survival, reproduction, and movement. Habitat suitability, which reflects prospecting and resource acquisition, was determined using the Maximum Entropy model. This study found that the optimal population size for wild boar ranged from 217 to 254 individuals. The population size varied depending on the amount of resources available within the home range, indicating fewer individuals in a larger home range. The estimated wild boar population size was 217 individuals for the minimum amount of resources (50% minimum convex polygon [MCP] home range), 225 individuals for the average amount of resources (95% MCP home range), and 254 individuals for the maximum amount of resources (100% MCP home range). The results of one-way analysis of variance revealed a significant difference in wild boar population size based on the amount of resources within the home range. These findings provide a basis for the development and implementation of effective management strategies for wild boar populations.
Korean Journal of Agricultural and Forest Meteorology
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v.23
no.1
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pp.55-67
/
2021
Hornbeams (Carpinus spp.), which are widely distributed in South Korea, are recognized as one of the most abundant species at climax stage in the temperate forests. Although the distribution and vegetation structure of the C. laxiflora community have been reported, little ecological information of C. tschonoskii is available. Little effort was made to examine the distribution shift of these species under the future climate conditions. This study was conducted to predict potential shifts in the distribution of C. laxiflora and C. tschonoskii in 2050s and 2090s under the two sets of climate change scenarios, RCP4.5 and RCP8.5. The MaxEnt model was used to predict the spatial distribution of two species using the occurrence data derived from the 6th National Forest Inventory data as well as climate and topography data. It was found that the main factors for the distribution of C. laxiflora were elevation, temperature seasonality, and mean annual precipitation. The distribution of C. tschonoskii, was influenced by temperature seasonality, mean annual precipitation, and mean diurnal rang. It was projected that the total habitat area of the C. laxiflora could increase by 1.05% and 1.11% under RCP 4.5 and RCP 8.5 scenarios, respectively. It was also predicted that the distributional area of C. tschonoskii could expand under the future climate conditions. These results highlighted that the climate change would have considerable impact on the spatial distribution of C. laxiflora and C. tschonoskii. These also suggested that ecological information derived from climate change impact assessment study can be used to develop proper forest management practices in response to climate change.
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