This study predicted the potential hibernation habitats of two endangered bat species, Myotis rufoniger and Plecotus ognevi, using a Random Forest-based species distribution model (SDM) that integrated occurrence records and environmental variables. The model incorporated climatic (BIO1, BIO12), topographic (DEM), and land cover variables. Both models exhibited statistically significant predictive performance, with P. ognevi (AUC=0.8054, TSS=0.634) showing higher reliability than M. rufoniger (AUC=0.7351, TSS=0.3824). Variable importance analysis indicated that DEM, BIO1, and BIO12 were key predictors for M. rufoniger, while BIO1, DEM, and BIO12 were most influential for P. ognevi, suggesting that climatic and topographic factors predominantly shaped habitat suitability. Predicted suitability maps revealed that M. rufoniger favored lowland agricultural areas, whereas P. ognevi was primarily associated with high-elevation mountainous regions. These findings provide quantitative insights into the environmental requirements of hibernating bats and offer a robust scientific basis for developing conservation and management strategies for endangered species in Korea.
Modeling the Potential Hibernation Habitat Distribution of the Endangered Bats Myotis rufoniger and Plecotus ognevi
Taek-Woo Lee,Chulhuyn Choi,Ha-Cheol Sung
Published 2025 in GEO DATA
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2025
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GEO DATA
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2025-12-31
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