Watershed boundaries and human-amplified environmental gradients shape ostracod metacommunities in Yunnan, China, a biodiversity hotspot

Disentangling the multi-scale processes that generate and maintain biodiversity is a central challenge in ecology, particularly within global biodiversity hotspots where conservation stakes are highest. Metacommunity theory provides a framework for this endeavor, but empirical tests in topographically complex landscapes remain scarce for microorganisms. Here, we investigate the hierarchical drivers of ostracod (Crustacea) metacommunity assembly in the mountains of southwestern China, a global biodiversity hotspot. We employed a multi-faceted analytical approach, combining community-level multivariate statistics (PERMANOVA, RDA/CCA) with species-level machine learning (ML). At the regional scale, PERMANOVA revealed highly significant differentiation in community composition among the Nu, Lancang, and Yuan river basins, confirming that watershed boundaries act as primary biogeographical filters. Within these basins, both constrained ordination and the ML ensemble consistently identified a powerful hydro-ionic gradient, defined by electrical conductivity, temperature, and altitude, as the dominant local environmental filter. Crucially, our analyses reveal that this natural gradient is significantly amplified by anthropogenic pressures; agricultural and urban land use systematically favors tolerant, generalist species by increasing turbidity and altering water chemistry, leading to the decline of sensitive specialists. Synthesizing these findings, we propose a hierarchical framework integrating regional hydrological connectivity with local environmental filtering. This research provides a clear empirical validation of metacommunity theory within complex river networks and offers a scientific foundation for a more robust, spatially explicit bioassessment strategy for freshwater ecosystem conservation.