Identifying the Drivers of Spatial Taxonomic and Functional Beta-Diversity of British Breeding Birds

Abstract

Spatial variation in community composition may be driven by a variety of processes, including environmental filtering and dispersal limitation. While work has been conducted on the relative importance of these processes on various taxa and at varying resolutions, tests using high-resolution empirical data across large spatial extents are sparse. Here, we use a dataset on the presence/absence of breeding bird species collected at the 10 km × 10 km scale across the whole of Britain. Pairwise spatial taxonomic and functional beta diversity, and the constituent components of each (turnover and nestedness/richness loss or gain), were calculated alongside two other measures of functional change (mean nearest taxon distance and mean pairwise distance). Predictor variables included climate and land use measures, as well as a measure of elevation, human influence, and habitat diversity. Generalized dissimilarity modeling was used to analyze the contribution of each predictor variable to variation in the different beta diversity metrics. Overall, we found that there was a moderate and unique proportion of the variance explained by geographical distance per se, which could highlight the role of dispersal limitation in community dissimilarity. Climate, land use, and human influence all also contributed to the observed patterns, but a large proportion of the explained variance in beta diversity was shared between these variables and geographical distance. However, both taxonomic nestedness and functional nestedness were uniquely predicted by a combination of land use, human influence, elevation, and climate variables, indicating a key role for environmental filtering. These findings may have important conservation implications in the face of a warming climate and future land use change.

Drivers of Taxonomic, Phylogenetic, and Functional Beta Diversity of Himalayan Riverine Birds

“…Geographical distance is an important driver of beta diversity patterns in birds (Wayman et al, 2021). However, we did not find a significant influence of geographical distance on beta diversity patterns in the E or the W Himalaya.…”

“…We found that the different beta diversity measures were related to similar predictors within a region (i.e., E or W Himalaya). However, the relative contribution of the different predictors in explaining the variation in beta diversity differed across the different measures (Figure 5), which has been reported elsewhere (Wayman et al, 2021). Interestingly, precipitation explained a large proportion of variation in taxonomic component of beta diversity in the W Himalaya (Figure 5), but a lower proportion of variation in phylogenetic and functional component.…”

“…Climatic factors such as precipitation and temperature are related to the variation in beta diversity patterns (Naka et al, 2020;Wayman et al, 2021). We found that precipitation was an important factor in explaining the variation in beta diversity patterns in the W Himalaya.…”

Replacement drives native β‐diversity of British avifauna, while richness differences shape alien β‐diversity

“…Lennon et al, 2000;Wayman et al, 2021). Our results for native β-diversity are in full agreement with the aforementioned studies.…”

“…However, native and alien species might respond to ecological gradients in similar or opposite ways. For instance, climate, especially temperature and precipitation, and land uses are considered important—albeit of different strength—drivers of species composition of alien and native bird communities (Li et al, 2018; Sinha et al, 2022; Wayman et al, 2021; Zellweger et al, 2017), but human‐related or other factors (e.g. introduction event characteristics) and native diversity might play a role in shaping alien β‐diversity (Ascensão et al, 2020; Dyer et al, 2016; Latombe et al, 2018).…”