Prediction of potential suitable habitats of Malania oleifera under future climate scenarios based on the MaxEnt model. [PDF]
Zhang Y +5 more
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Modeling the Habitat Suitability and Range Shift of <i>Daphniphyllum macropodum</i> in China Under Climate Change Using an Optimized MaxEnt Model. [PDF]
Xiang Y +10 more
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Ecological Risk Assessment and Management of Forest Fires in Tamil Nadu, India: A MaxEnt Model-Based Approach for Strategic Resource Allocation and Fire Mitigation. [PDF]
Meraj G +3 more
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Potential geographical distribution of Garcinia paucinervis Chun et How in China under future climate change scenarios based on the MaxEnt Model. [PDF]
Li H, Cheng L, Song J, Sun X.
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Analysis of Spatial Suitable Habitats of Four Subspecies of <i>Hippophae rhamnoides</i> in China Based on the MaxEnt Model. [PDF]
He M +6 more
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Potential Distribution of Tribe Erythroneurini in China Based on the R-Optimized MaxEnt Model, with Implications for Management. [PDF]
Yuan X +5 more
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Modeling the Susceptibility of Ips sexdentatus with Maximum Entropy (MaxEnt)
Forests are most affected by climate change and related factors. Climate change causes changes in the distribution of host trees and their associated pests. Predictive models that determine the spatial distributions of species are important for applications that will guide planners in the field of ecology and conservation. It is predicted that the ever-
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Predicting the impact of climate change on the distribution of rhododendron on the qinghai-xizang plateau using maxent model. [PDF]
Chai SX +8 more
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Predicting potentially suitable Bletilla striata habitats in China under future climate change scenarios using the optimized MaxEnt model. [PDF]
Luo M +6 more
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Quantifying Potentially Suitable Geographical Habitat Changes in Chinese Caterpillar Fungus with Enhanced MaxEnt Model. [PDF]
Peng Y, Xu D, Ali H, Liu Z, Zhuo Z.
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