• Title/Summary/Keyword: MaxEnt model

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Evaluation of Habitat Suitability of Honey Tree Species, Kalopanax septemlobus Koidz., Tilia amurensis Rupr. and Styrax obassis Siebold & Z ucc. in the Baekdudaegan Mountains using MaxEnt Model (MaxEnt 모형을 활용한 백두대간에 자생하는 주요 밀원수종인 음나무, 피나무, 쪽동백나무의 서식지 적합성 평가)

  • Sim, Hyung Seok;Lee, Min-Ki;Lee, Chang-Bae
    • 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.

Predicting the Potential Habitat and Future Distribution of Brachydiplax chalybea flavovittata Ris, 1911 (Odonata: Libellulidae) (기후변화에 따른 남색이마잠자리 잠재적 서식지 및 미래 분포예측)

  • Soon Jik Kwon;Yung Chul Jun;Hyeok Yeong Kwon;In Chul Hwang;Chang Su Lee;Tae Geun Kim
    • Journal of Wetlands Research
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    • v.25 no.4
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    • pp.335-344
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    • 2023
  • Brachydiplax chalybea flavovittata, a climate-sensitive biological indicator species, was first observed and recorded at Jeju Island in Korea in 2010. Overwintering was recently confirmed in the Yeongsan River area. This study was aimed to predict the potential distribution patterns for the larvae of B. chalybea flavovittata and to understand its ecological characteristics as well as changes of population under global climate change circumstances. Data was collected both from the Global Biodiversity Information Facility (GBIF) and by field surveys from May 2019 to May 2023. We used for the distribution model among downloaded 19 variables from the WorldClim database. MaxEnt model was adopted for the prediction of potential and future distribution for B. chalybea flavovittata. Larval distribution ranged within a region delimited by northern latitude from Jeju-si, Jeju Special Self-Governing Province (33.318096°) to Yeoju-si, Gyeonggi-do (37.366734°) and eastern longitude from Jindo-gun, Jeollanam-do (126.054925°) to Yangsan-si, Gyeongsangnam-do (129.016472°). M type (permanent rivers, streams and creeks) wetlands were the most common habitat based on the Ramsar's wetland classification system, followed by Tp type (permanent freshwater marshes and pools) (45.8%) and F type (estuarine waters) (4.2%). MaxEnt model presented that potential distribution with high inhabiting probability included Ulsan and Daegu Metropolitan City in addition to the currently discovered habitats. Applying to the future scenarios by Intergovernmental Panel on Climate Change (IPCC), it was predicted that the possible distribution area would expand in the 2050s and 2090s, covering the southern and western coastal regions, the southern Daegu metropolitan area and the eastern coastal regions in the near future. This study suggests that B. chalybea flavovittata can be used as an effective indicator species for climate changes with a monitoring of their distribution ranges. Our findings will also help to provide basic information on the conservation and management of co-existing native species.

Prediction of Landslides Occurrence Probability under Climate Change using MaxEnt Model (MaxEnt 모형을 이용한 기후변화에 따른 산사태 발생가능성 예측)

  • 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
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    • 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.

Predicting the Potential Distribution of Pinus densiflora and Analyzing the Relationship with Environmental Variable Using MaxEnt Model (MaxEnt 모형을 이용한 소나무 잠재분포 예측 및 환경변수와 관계 분석)

  • Cho, NangHyun;Kim, Eun-Sook;Lee, Bora;Lim, Jong-Hwan;Kang, Sinkyu
    • 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.

Prediction of changes in distribution area of Scopura laminate in response to climate changes of the Odaesan National Park of South Korea

  • Kwon, Soon Jik;Kim, Tae Geun;Park, Youngjun;Kwon, Ohseok;Cho, Youngho
    • Journal of Ecology and Environment
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    • v.38 no.4
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    • pp.529-536
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    • 2015
  • This study was performed to provide important basic data for the preservation and management of Scopura laminata, a species endemic to Korea, by elucidating the spatial characteristics of its present, potential, and future distribution areas. Currently, this species is found in the Odaesan National Park area of South Korea and has been known to be restricted in its habitat due to its poor mobility, as even fully grown insects do not have wings. Utilizing the MaxEnt model, 20 collection points around Odaesan National Park were assessed to analyze and predict spatial distribution characteristics. The precision of the MaxEnt model was excellent, with an AUC value of 0.833. Variables affecting the potential distribution area of S. laminata by more than 10% included the range of annual temperature, seasonality of precipitation, and precipitation of the driest quarter, in order of greatest to least impact. Compared to the current potential distribution area, no significant difference in the overall habitable area was predicted for the 2050s or 2070s. It was, however, demonstrated that the potential habitable area would be reduced in the 2050s by up to 270.3 km from the current area of 403.9 km; further, no potential habitable area was anticipated by the 2070s according to our predictive model. Taken together, it is anticipated that this endemic species could be significantly affected by climate changes, and hence effective countermeasures are strongly warranted for the preservation of habitats and species management.

Modeling the potential climate change-induced impacts on future genus Rhipicephalus (Acari: Ixodidae) tick distribution in semi-arid areas of Raya Azebo district, Northern Ethiopia

  • Hadgu, Meseret;Menghistu, Habtamu Taddele;Girma, Atkilt;Abrha, Haftu;Hagos, Haftom
    • Journal of Ecology and Environment
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    • v.43 no.4
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    • pp.427-437
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    • 2019
  • 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.

Distribution Patterns and Ecological Characters of Paulownia coreana and P. tomentosa in Busan Metropolitan City Using MaxEnt Model (MaxEnt 모형을 활용한 부산광역시 내 오동나무 및 참오동나무의 분포 경향과 생태적 특성)

  • Lee, Chang-Woo;Lee, Cheol-Ho;Choi, Byoung-Ki
    • 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.

A Comparative Study on HSI and MaxEnt Habitat Prediction Models: About Prionailurus bengalensis (HSI와 MaxEnt를 통한 삵의 서식지 예측 모델 비교 연구)

  • Yoo, Da-Young;Lim, Tai-Yang;Kim, Whee-Moon;Song, Won-Kyong
    • 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.

Prediction of potential habitats and distribution of the marine invasive sea squirt, Herdmania momus

  • Park, Ju-Un;Lee, Taekjun;Kim, Dong Gun;Shin, Sook
    • Korean Journal of Environmental Biology
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    • v.38 no.1
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    • pp.179-188
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    • 2020
  • 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.

Spatio-Temporal Projection of Invasion Using Machine Learning Algorithm-MaxEnt

  • Singye Lhamo;Ugyen Thinley;Ugyen Dorji
    • Journal of Forest and Environmental Science
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    • v.39 no.2
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    • pp.105-117
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    • 2023
  • 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.