Beta diversity patterns of bats in the Atlantic Forest: How does the scale of analysis affect the importance of spatial and environmental factors?

Abstract

AbstractAimEnvironmental and spatial factors are broadly recognized as important predictors of beta diversity patterns. However, the scale at which beta diversity patterns are evaluated will affect the outcoming results. For example, studies at larger scales will usually find spatial processes as the main predictor of beta diversity patterns. In this study, we evaluate how beta diversity patterns change when analyses are conducted at different scales by reducing the scale of analysis in a hierarchical manner.LocationAtlantic Forest biome.TaxonChiroptera.MethodsInformation on the occurrence of 59 bat species were obtained from the Atlantic Bats and Species Link database. We partitioned beta diversity into its two components (nestedness and turnover), and calculated these indexes hierarchically: the biome in its entirety (all ecoregions); between larger regions (north, central and south); and between ecoregions within each region. We performed a Generalized Dissimilarity Model (GDM) to identify and predict the turnover of bat species in the Atlantic Forest based on geo‐climatic predictors. We obtained 19 geo‐climatic data from AMBDATA, an environmental dataset based on different data sources commonly used in species distribution modelling.ResultsWe found that turnover was the main component influencing a latitudinal gradient when the biome was analysed in its entirety. However, when the scale of the analysis was reduced, we found that species loss (nestedness component) had a large effect in determining beta diversity dissimilarity. We also found that nestedness was the main pattern explaining beta diversity dissimilarity along a longitudinal gradient.Main conclusionsBeta diversity patterns changed with the scale of analysis, which indicates that bat species composition does not follow the same pattern throughout the Atlantic Forest. This corroborates the importance of analysing beta diversity patterns at different scales to understand how environmental dissimilarity across geographical space can influence species distribution patterns.