Vegetation structure mediates topographic effects on bat assemblages in Amazonian white-sand ecosystems

Understanding how topography structures tropical faunal communities require disentangling direct effects from indirect effects mediated by vegetation and hydrology. We investigated these pathways in bat assemblages within Central Amazonian white-sand ecosystems, which are nutrient-poor, structurally heterogeneous habitats that remain largely understudied for bats. Using mist nets, we captured 602 individuals from 31 Phyllostomidae species across 19 plots spanning campina (open, shrubby) and campinarana (forested) formations within the Rio Negro Sustainable Development Reserve. We applied structural equation models (SEMs) to disentangle direct and indirect causal pathways linking terrain elevation, streams proximity, and vegetation structure to bat richness, abundance, and composition. Understory openness (positive effect) and stream proximity (negative effect) were the main direct predictors of bat diversity, particularly for frugivorous bats. Critically, terrain elevation exerted minimal direct influence but strong indirect effects: lower elevations and areas near streams supported more open vegetation, which in turn increased bat richness and abundance. This indirect and positive pathway was the dominant mechanism structuring bat assemblages, with frugivorous species showing the strongest responses. Campinas and riparian campinaranas functioned as biodiversity hotspots, likely due to their open understory structure and higher food availability. Our results demonstrate that fine-scale topographic variation (~ 30 m elevation range) can significantly structure tropical bat communities through indirect ecological pathways, a pattern consistent with other tropical open ecosystems. Because elevation and stream networks can be obtained from remote sensing, they represent valuable proxies for predicting biodiversity in data-limited landscapes. Thus, elevation can be used as a proxy for vegetation structure variables, which are more difficult, time-consuming, and costly to measure in the field.