Freshwater bacterioplankton richness in oligotrophic lakes depends on nutrient availability rather than on species–area relationships

A central goal in ecology is to grasp the mechanisms that underlie and maintain biodiversity and patterns in its spatial distribution can provide clues about those mechanisms. Here, we investigated what might determine the bacterioplankton richness (BR) in lakes by means of 454 pyrosequencing of the 16S rRNA gene. We further provide a BR estimate based upon a sampling depth and accuracy, which, to our knowledge, are unsurpassed for freshwater bacterioplankton communities. Our examination of 22 669 sequences per lake showed that freshwater BR in fourteen nutrient-poor lakes was positively influenced by nutrient availability. Our study is, thus, consistent with the finding that the supply of available nutrients is a major driver of species richness; a pattern that may well be universally valid to the world of both micro- and macro-organisms. We, furthermore, observed that BR increased with elevated landscape position, most likely as a consequence of differences in nutrient availability. Finally, BR decreased with increasing lake and catchment area that is negative species–area relationships (SARs) were recorded; a finding that re-opens the debate about whether positive SARs can indeed be found in the microbial world and whether positive SARs can in fact be pronounced as one of the few ‘laws'' in ecology.     

‘Bigger data’ on scale-dependent effects of invasive species on biodiversity cannot overcome confounded analyses: a comment on Stohlgren & Rejmánek (2014)

A recent study by Stohlgren & Rejmánek (SR: Stohlgren TJ, Rejmánek M. 2014 Biol. Lett. 10. (doi:10.1098/rsbl.2013.0939)) purported to test the generality of a recent finding of scale-dependent effects of invasive plants on native diversity; dominant invasive plants decreased the intercept and increased the slope of the species–area relationship. SR (2014) find little correlation between invasive species cover and the slopes and intercepts of SARs across a diversity of sites. We show that the analyses of SR (2014) are inappropriate because of confounding causality.     

Moving beyond abundance distributions: neutral theory and spatial patterns in a tropical forest

Assessing the relative importance of different processes that determine the spatial distribution of species and the dynamics in highly diverse plant communities remains a challenging question in ecology. Previous modelling approaches often focused on single aggregated forest diversity patterns that convey limited information on the underlying dynamic processes. Here, we use recent advances in inference for stochastic simulation models to evaluate the ability of a spatially explicit and spatially continuous neutral model to quantitatively predict six spatial and non-spatial patterns observed at the 50 ha tropical forest plot on Barro Colorado Island, Panama. The patterns capture different aspects of forest dynamics and biodiversity structure, such as annual mortality rate, species richness, species abundance distribution, beta-diversity and the species–area relationship (SAR). The model correctly predicted each pattern independently and up to five patterns simultaneously. However, the model was unable to match the SAR and beta-diversity simultaneously. Our study moves previous theory towards a dynamic spatial theory of biodiversity and demonstrates the value of spatial data to identify ecological processes. This opens up new avenues to evaluate the consequences of additional process for community assembly and dynamics.     

River density and landscape roughness are universal determinants of linguistic diversity

Global linguistic diversity (LD) displays highly heterogeneous distribution patterns. Though the origin of the latter is not yet fully understood, remarkable parallelisms with biodiversity distribution suggest that environmental variables should play an essential role in their emergence. In an effort to construct a broad framework to explain world LD and to systematize the available data, we have investigated the significance of 14 variables: landscape roughness, altitude, river density, distance to lakes, seasonal maximum, average and minimum temperature, precipitation and vegetation, and population density. Landscape roughness and river density are the only two variables that universally affect LD. Overall, the considered set accounts for up to 80% of African LD, a figure that decreases for the joint Asia, Australia and the Pacific (69%), Europe (56%) and the Americas (53%). Differences among those regions can be traced down to a few variables that permit an interpretation of their current states of LD. Our processed datasets can be applied to the analysis of correlations in other similar heterogeneous patterns with a broad spatial distribution, the clearest example being biological diversity. The statistical method we have used can be understood as a tool for cross-comparison among geographical regions, including the prediction of spatial diversity in alternative scenarios or in changing environments.     

Fine-scale spatial patterns in bacterial community composition and function within freshwater ponds

The extent to which non-host-associated bacterial communities exhibit small-scale biogeographic patterns in their distribution remains unclear. Our investigation of biogeography in bacterial community composition and function compared samples collected across a smaller spatial scale than most previous studies conducted in freshwater. Using a grid-based sampling design, we abstracted 100+ samples located between 3.5 and 60 m apart within each of three alpine ponds. For every sample, variability in bacterial community composition was monitored using a DNA-fingerprinting methodology (automated ribosomal intergenic spacer analysis) whereas differences in bacterial community function (that is, carbon substrate utilisation patterns) were recorded from Biolog Ecoplates. The exact spatial position and dominant physicochemical conditions (for example, pH and temperature) were simultaneously recorded for each sample location. We assessed spatial differences in bacterial community composition and function within each pond and found that, on average, community composition or function differed significantly when comparing samples located >20 m apart within any pond. Variance partitioning revealed that purely spatial variation accounted for more of the observed variability in both bacterial community composition and function (range: 24–38% and 17–39%) than the combination of purely environmental variation and spatially structured environmental variation (range: 17–32% and 15–20%). Clear spatial patterns in bacterial community composition, but not function were observed within ponds. We therefore suggest that some of the observed variation in bacterial community composition is functionally ‘redundant''. We confirm that distinct bacterial communities are present across unexpectedly small spatial scales suggesting that populations separated by distances of >20 m may be dispersal limited, even within the highly continuous environment of lentic water.