Deconstructing richness patterns by commonness and rarity reveals bioclimatic and spatial effects in black fly metacommunities

Abstract

1. Deconstructing biological communities by grouping species according to their commonness or rarity might improve our understanding about the processes driving variation in biological communities. Such an approach considers differences among organisms and emergent ecological patterns. 2. In this study, we addressed the relative role of spatial and large-scale bioclimatic variables along a commonness and rarity gradient using Simuliidae (Diptera) species richness. A database of species occurrences at 459 locations in Brazil was used to estimate the distribution of 58 simuliid species. Total species richness at each location was estimated first using all occurrences and then by removing one species at a time, following a commonest to rarest gradient (CtR) and vice-versa (RtC). Partial regression analysis was used to test the influence of sets of bioclimatic (E) and spatial (S) variables for Simuliidae species richness across both CtR and RtC gradients. 3. In the CtR gradient, the pure spatial component alone explained between 40% and 60% of the variation in simuliid richness when the total number of species was greater than~35. After removal of the 35th most common species, the model fit decreased sharply reaching nearly zero when only rare species were present. Variation explained by the shared component E + S decreased continuously along the CtR gradient. The relative role of predictor variables on the RtC gradient was similar to CtR gradient. However, removing the rare species first did not change which components best explained species richness. 4. Our gradual deconstructive approach revealed that common species contribute more to species richness variation than rare species, and that the role of predictors in explaining this pattern cannot be untangled by analysing richness of rare and common species in a categorical way.

Effects of land use and limnological variables on the dissimilarity of common and rare aquatic insects in Atlantic Forest streams

“…In undisturbed communities of organisms, species have a distinct distribution (Heino & Mendoza, 2016), where some species are very abundant, others only moderately common, while the rest of the species are rare. Species may be biologically distinct in various ways, such as in relation to their dispersal ability and life strategies (Roque et al, 2016). Therefore, species may respond differently to environmental conditions (Hepp, Landeiro, & Melo, 2012;Heino & Mendoza, 2016) and spatial processes (Kunin & Shimida, 1997;Cornwell & Ackerly, 2010;Hepp & Melo, 2013).…”

“…In the conservation context, the importance of rare organisms within aquatic communities has been much discussed (Heino & Mendoza, 2016;Roque et al, 2016) and various approaches are used to incorporate the rarity of species into analyses (Siqueira et al, 2011). On the other hand, these organisms can be considered as the best indicators of environmental stress (Poos & Jackson, 2012).…”

Determinants of stream bryophyte community structure: bringing ecology into conservation

“…This pattern has also been documented in previous bryological studies (Vanderpoorten & Engels, ; Vanderpoorten et al ., ). Additionally, our findings indicate that widely distributed species were largely responsible for the observed patterns of species richness, as in other reports (Pearman & Weber, ; Roque et al ., ). Such knowledge is of great importance for the development of sampling and monitoring strategies, identification of bryophyte diversity hotspots and potential areas of high conservation value, protected area prioritisation and network design (Hallingbäck & Tan, ; Sérgio et al ., ).…”

Communities in high definition: Spatial and environmental factors shape the micro‐distribution of aquatic invertebrates

“…Alternatively, the observed co‐occurrence patterns could reflect a shared response to environmental variables not measured in this study (Ovaskainen et al., 2017). Co‐occurrences could also partly be explained by our exclusion of rare taxa, whose distributions could be more stochastic (Roque et al, 2016), whereas common taxa may occur at most sampling points but at different abundances, which are modulated by habitat preferences (Burgazzi et al., 2018).…”