The problem and promise of scale dependency in community phylogenetics

The problem of scale dependency is widespread in investigations of ecological communities. Null model investigations of community assembly exemplify the challenges involved because they typically include subjectively defined "regional species pools." The burgeoning field of community phylogenetics appears poised to face similar challenges. Our objective is to quantify the scope of the problem of scale dependency by comparing the phylogenetic structure of assemblages across contrasting geographic and taxonomic scales. We conduct phylogenetic analyses on communities within three tropical forests, and perform a sensitivity analysis with respect to two scaleable inputs: taxonomy and species pool size. We show that (1) estimates of phylogenetic overdispersion within local assemblages depend strongly on the taxonomic makeup of the local assemblage and (2) comparing the phylogenetic structure of a local assemblage to a species pool drawn from increasingly larger geographic scales results in an increased signal of phylogenetic clustering. We argue that, rather than posing a problem, "scale sensitivities" are likely to reveal general patterns of diversity that could help identify critical scales at which local or regional influences gain primacy for the structuring of communities. In this way, community phylogenetics promises to fill an important gap in community ecology and biogeography research.     

Air quality modeling of hazardous pollutants: current status and future directions

The current requirements and status of air quality modeling of hazardous pollutants are reviewed. Many applications require the ability to predict the local impacts from industrial sources or large roadways as needed for community health characterization and evaluating environmental justice concerns. Such local-scale modeling assessments can be performed by using Gaussian dispersion models. However, these models have a limited ability to handle chemical transformations. A new generation of Eulerian grid-based models is now capable of comprehensively treating transport and chemical transformations of air toxics. However, they typically have coarse spatial resolution, and their computational requirements increase dramatically with finer spatial resolution. The authors present and discuss possible advanced approaches that can combine the grid-based models with local-scale information.     

Meter-scale variation within a single transect demands attention to taxon accumulation curves in riverine microbiome studies

● Riverine microbiomes exhibited hyperlocal variation within a single transect. ● Certain family-level taxa directionally associated with river center and bank. ● Taxon accumulation curves within a transect urges more nuanced sampling design. Microbial communities inhabiting river ecosystems play crucial roles in global biogeochemical cycling and pollution attenuation. Spatial variations in local microbial assemblages are important for detailed understanding of community assembly and developing robust biodiversity sampling strategies. Here, we intensely analyzed twenty water samples collected from a one-meter spaced transect from the near-shore to the near-center in the Meramec River in eastern Missouri, USA and examined the microbial community composition with 16S rRNA gene amplicon sequencing. Riverine microbiomes across the transect exhibited extremely high similarity, with Pearson’s correlation coefficients above 0.9 for all pairwise community composition comparisons. However, despite the high similarity, PERMANOVA revealed significant spatial differences between near-shore and near-center communities (p = 0.001). Sloan’s neutral model simulations revealed that within-transect community composition variation was largely explained by demographic stochasticity (R² = 0.89). Despite being primarily explained by neutral processes, LefSe analyses also revealed taxa from ten families of which relative abundances differed directionally from the bank to the river center, indicating an additional role of environmental filtering. Notably, the local variations within a river transect can have profound impacts on the documentation of alpha diversity. Taxon-accumulation curves indicated that even twenty samples did not fully saturate the sampling effort at the genus level, yet four, six and seven samples were able to capture 80% of the phylum-level, family-level, and genus-level diversity, respectively. This study for the first time reveals hyperlocal variations in riverine microbiomes and their assembly mechanisms, demanding attention to more robust sampling strategies for documenting microbial diversity in riverine systems.     

Conserving alpha and beta diversity in wood-production landscapes

International demand for wood and other forest products continues to grow rapidly, and uncertainties remain about how animal communities will respond to intensifying resource extraction associated with woody bioenergy production. We examined changes in alpha and beta diversity of bats, bees, birds, and reptiles across wood production landscapes in the southeastern United States, a biodiversity hotspot that is one of the principal sources of woody biomass globally. We sampled across a spatial gradient of paired forest land-uses (representing pre and postharvest) that allowed us to evaluate biological community changes resulting from several types of biomass harvest. Short-rotation practices and residue removal following clearcuts were associated with reduced alpha diversity (−14.1 and −13.9 species, respectively) and lower beta diversity (i.e., Jaccard dissimilarity) between land-use pairs (0.46 and 0.50, respectively), whereas midrotation thinning increased alpha (+3.5 species) and beta diversity (0.59). Over the course of a stand rotation in a single location, biomass harvesting generally led to less biodiversity. Cross-taxa responses to resource extraction were poorly predicted by alpha diversity: correlations in responses between taxonomic groups were highly variable (−0.2 to 0.4) with large uncertainties. In contrast, beta diversity patterns were highly consistent and predictable across taxa, where correlations in responses between taxonomic groups were all positive (0.05–0.4) with more narrow uncertainties. Beta diversity may, therefore, be a more reliable and information-rich indicator than alpha diversity in understanding animal community response to landscape change. Patterns in beta diversity were primarily driven by turnover instead of species loss or gain, indicating that wood extraction generates habitats that support different biological communities.