Synergistic pollution-climate-host interactions drive nonlinear flea dynamics on Mongolian gerbils

As climate change and human activities intensify, the ecological responses of rodent ectoparasitic flea (Siphonaptera) communities and their population dynamics exhibit nonlinear characteristics. However, the synergistic effects of air pollution and climatic drivers, and the critical role of host traits in modulating these interactions, remain poorly understood. We conducted a nine-month field survey of Mongolian gerbils and their fleas on the Ordos Plateau, China, integrating our collections with high-resolution meteorological and Air Quality Index (AQI) data. We developed a “climate-pollution-host” framework, employing Redundancy Analysis (RDA) and Generalized Linear Mixed Models (GLMMs) to systematically analyze the interactive effects of these multiple stressors on flea communities and populations. Air Quality Index (AQI), a previously overlooked factor, emerged as a key driver of flea dynamics. Complex, nonlinear interactions between AQI and climatic variables defined two critical high-risk transmission zones: (1) areas with moderate temperatures (15–20 °C) and high pollution (AQI > 60), particularly under southwesterly winds, and (2) areas with low temperatures (10–15 °C) and high pollution (AQI > 42) under low-wind conditions. The impact of these environmental stressors was significantly modulated by host biology; the positive effect of pollution on flea loads was most pronounced on subadult and reproductive individuals when AQI exceeded 50, a pattern consistent with the framework of an immunocompetence-energy trade-off. Ultimately, these complex drivers resulted in distinct ecological niche differentiation between the two dominant flea species: Xenopsylla conformis conformis preferred temperate, high-AQI conditions, whereas Nosopsyllus laeviceps kuzenkovi was more tolerant of low-temperature and high-wind stress. Our study identifies the Air Quality Index (AQI) as a critical driver of flea community dynamics. We demonstrate that complex, multi-way interactions between AQI, climatic variables, and host traits nonlinearly regulate flea abundance and define high-risk transmission zones. This climate–pollution–host interaction framework provides a novel and powerful approach for understanding and predicting vector ecology under multifaceted environmental change.