Environmental Drivers of Geographic Isolation in Three Pika Species in Northeast Asia.

Geographic segregation among closely related species may arise from divergent environmental preferences or constraints of interspecific interactions. For these three congeneric pika species in northeastern Asia, the relative contributions of these mechanisms remain poorly understood. This study investigates three congeneric species: Ochotona coreana, Ochotona mantchurica, and Ochotona hyperborea, to identify how environmental gradients and interspecific niche relationships jointly shape their spatial segregation. We combined public records with field survey to build species distribution models and reduced sampling bias through regional mammal density to optimize environmental variables and background points. We quantified each species' potential distribution, identified key environmental drivers, and evaluated ecological niche overlap to assess whether isolation reflects potential competition or habitat divergence. The three species showed distinct distribution patterns and environmental associations. O. coreana had the smallest potential range, restricted to high-elevation forests and tundra of the Changbai Mountains in China and DPR Korea. O. hyperborea ranged from northeastern China to the Russian Far East, with suitability driven by precipitation seasonality, isothermality, and forest composition. O. mantchurica distribution across Hulunbuir and eastern Mongolian grasslands mainly associated with precipitation seasonality and slope. Niche overlap was high between O. mantchurica and O. hyperborea, but low for O. coreana and the other species. Limited sympatry between the two wide-ranging species suggests potential niche segregation. The three species are isolated by distinct environmental drivers and potential competitive interactions. Our findings clarify the environmental and ecological drivers shaping species boundaries in these closely related pika species and provide a framework for evaluating distributional dynamics in data-limited small mammals.