Review of CLIMEX and MaxEnt for studying species distribution in South Korea

Byeon, Dae‐hyeon; Jung, Sunghoon; Lee, Wang‐Hee

doi:10.1016/j.japb.2018.06.002

Cited by 94 publications

(66 citation statements)

References 50 publications

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“…Studies have reported that MaxEnt is an internationally accepted and widely used model for mapping and analysis of both animals and plant species under different climate scenarios (Qin et al, 2017;Esfanjani et al, 2018;Lamsal et al, 2018;Sharma et al, 2018). There are also reports of species distribution modelling (SDM) being developed for rice and its ecosystem (Heumann et al, 2011;Ojara et al, 2017;Byeon et al, 2018). Modelling studied of Kim et al (2013), Chun et al (2016) and Zhang and Tao (2013) reported marked changes in the rice response to the changes in the projections of future climate.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Bhutan's ecological distribution of rice (Oryza sativaL.) under the impact of climate change through maximum entropy modelling

et al. 2020

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The current research investigated the present and future projected distribution of rice (Oryza sativa L.) based on climatic suitability under three representative concentration pathways (RCPs) of the Intergovernmental Panel on Climate Change using maximum entropy (MaxEnt) modelling. The MaxEnt models predict that rice distribution in Bhutan will undergo major changes in terms of spatial range shift of varying magnitudes by 2060. Under the anthropogenic radiative forcing of RCP2.6, RCP4.5 and RCP8.5, ecological space of rice is predicted to change between 1 and 43%. Major changes are likely to take place in major rice-growing ecological zones of the country. This is likely to have a negative impact on the livelihood and food security of the people as crop production might start declining due to unfavourable climatic factors. Therefore, the findings of this study could prove beneficial for forecasting focus sites requiring interventions, including future climate research, planning, policy formulation and conservation of natural resources.

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Section: Introductionmentioning

confidence: 99%

Prediction of Bhutan's ecological distribution of rice (Oryza sativaL.) under the impact of climate change through maximum entropy modelling

et al. 2020

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“…CLIMEX requires climate-and target species-specific parameters, which ultimately determine species distribution [20,26]. It uses, for instance, parameters such as temperature index (TI), moisture index (MI), light index (LI), and degree-days per generation (PDD), which affect growth and limit populations.…”

Section: Parameter Estimation For Simulating Potato Tuber Moth and Pomentioning

confidence: 99%

“…The SDM method allows for the evaluation of potential risk for a specific area by simulating pest occurrence as a function of environmental factors [17,18]. In addition, it allows for the projection of changes in species distribution and dispersion patterns in climate change scenarios [19,20]. Rafoss and Saethre [21], for example, assessed the potential geographical distribution of the codling moth and Colorado potato beetle in Norway using CLIMEX software under three different climate scenarios.…”

Section: Introductionmentioning

confidence: 99%

The Potential Distribution of the Potato Tuber Moth (Phthorimaea Operculella) Based on Climate and Host Availability of Potato

Jung

Lee²,

Kim³

et al. 2019

Agronomy

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This study evaluated the potential distribution of the potato tuber moth. This species severely impacts global potato production, especially in China and India, which have the world’s largest potato production. We developed two indices considering host plant availability and production in addition to climatic suitability, which was simulated using the CLIMEX model. Thus, three different indices were used to project potential distribution of the potato tuber moth under a climate change scenario: (1) climatic suitability (ecoclimatic index (EI)) (EIM), (2) climatic suitability combined with host plant availability (EIN1), and (3) climatic suitability combined with host plant production (EIN2). Under the current climate, EIM was high in southern India and central to southern China, while EIN1 and EIN2 were approximately 38% and 20% lower than EIM, respectively. Under the Special Report on Emissions Scenario A1B, the potato tuber moth would probably not occur in India, but its distribution could be extended to the north, reaching N47°. The areas with the highest climatic suitability by potato tuber moth based on three indices were Sichuan and Karnataka in response to climate change. These areas require adequate pest control, such as prevention of spread through transport of potato seed or by using cold storage facilities.

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“…Despite the importance of hazard ratings for controlling the CFP, there are limited studies on hazard ratings using the CLIMEX model [37] which is used for the prediction of species distribution [38][39][40][41] and for risk assessment of invasive species [42,43]. CLIMEX is a climate-specific model to predict potential distribution and relative abundance of species by considering climatic conditions [44].…”

Section: Introductionmentioning

confidence: 99%

“…MaxEnt cannot be applied to abundance data, only to presence data. Recently, studies to predict the distribution of (potential) invasive species, including CFP, using CLIMEX and MaxEnt were reviewed by evaluating their effectiveness [39].…”

Section: Introductionmentioning

confidence: 99%

Occurrence Prediction of the Citrus Flatid Planthopper (Metcalfa pruinosa (Say, 1830)) in South Korea Using a Random Forest Model

Lee

Bae

Byun

et al. 2019

Forests

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Invasive species cause a severe impact on existing ecosystems. The citrus flatid planthopper (CFP; Metcalfa pruinosa (Say, 1830)) is an invasive species in many countries. Predicting potential occurrence areas of the species related to environmental conditions is important for effective forest ecosystem management. In this study, we evaluated the occurrence patterns of the CFP and predicted its potential occurrence areas in South Korea using a random forest model for a hazard rating of forests considering meteorological and landscape variables. We obtained the occurrence data of the CFP in South Korea from literature and government documents and extracted seven environmental variables (altitude, slope, distance to road (geographical), annual mean temperature, minimum temperature in January, maximum temperature in July, and annual precipitation (meteorological)) and the proportion of land cover types across seven categories (urban, agriculture, forest, grassland, wetland, barren, and water) at each occurrence site from digital maps using a Geographic Information System. The CFP occurrence areas were mostly located at low altitudes, near roads and urbanized areas. Our prediction model also supported these results. The CFP has a high potential to be distributed over the whole of South Korea, excluding high mountainous areas. Finally, factors related to human activities, such as roads and urbanization, strongly influence the occurrence and dispersal of the CFP. Therefore, we propose that these factors should be considered carefully in monitoring and surveillance programs for the CFP and other invasive species.

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Review of CLIMEX and MaxEnt for studying species distribution in South Korea

Cited by 94 publications

References 50 publications

Prediction of Bhutan's ecological distribution of rice (Oryza sativaL.) under the impact of climate change through maximum entropy modelling

Prediction of Bhutan's ecological distribution of rice (Oryza sativaL.) under the impact of climate change through maximum entropy modelling

The Potential Distribution of the Potato Tuber Moth (Phthorimaea Operculella) Based on Climate and Host Availability of Potato

Occurrence Prediction of the Citrus Flatid Planthopper (Metcalfa pruinosa (Say, 1830)) in South Korea Using a Random Forest Model

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