Diversity and Horizontal Turnover Depend on the Vertical Position in Neotropical Butterfly Communities

Aim It is well‐documented that the tropical forest biota is vertically stratified, and ecological theories from studies of the latitudinal gradient have been applied to predict and understand how communities vary across vertical strata. In butterflies, differences in abiotic conditions between the canopy and the understorey promote the evolution of distinct flight morphologies and physiologies. However, how these distinct morphologies relate to differences in dispersal ability is poorly explored and we lack a general understanding of how and why vertical stratification influences community turnover in tropical forests. Here, we explored how vertical stratification influences diversity, horizontal spatial similarity of assemblages and distance‐decay patterns in understory and canopy butterflies across multiple ecosystems. Location Seven forest ecosystems in Ecuador, South America. Taxon Butterflies (Lepidoptera: Papilionoidea). Methods We assessed patterns of diversity by employing data from standardized butterfly monitoring programmes during the years 2011–2019 across seven sites in Ecuador (37,370 records from 1099 species), and a framework based on metacommunity theory and Jost's diversity estimates. Results Our results suggest three vertical patterns for neotropical butterfly communities: (a) a strong partitioning of canopy and understorey subcommunities, with distinct resulting diversity profiles; (b) greater spatial similarity for the canopy assemblages compared to the understorey (both locally and regionally); and (c) steeper distance‐decay patterns for understorey assemblages compared to the canopy. Main Conclusions Our study shows the generality of vertical stratification diversity patterns across multiple Neotropical ecosystems, including previously unstudied montane cloud forests. It also shows that horizontal variation in community composition depends on the vertical position of taxa within Neotropical forests and is in general consistent with predictions based on species ecology and morphology.