Macroecological patterns in coarse-grained microbial systems

The structure of microbial communities is intrinsically hierarchical due to the shared evolutionary history of community members. This history is primarily captured through taxonomic assignment and phylogenetic reconstruction, sources of information that are frequently used to group microbes into higher levels of organization in experimental and natural communities. However, the macroecological consequences of this shared history are rarely examined. This omission is not simply a methodological detail, as the shared history of community members provides an opportunity to investigate the dependence of microbial patterns of diversity and abundance across scales of organization. Here, we evaluate the extent that macroecological laws endure across taxonomic and phylogenetic scales among disparate environments using data from the Earth Microbiome Project. We find that measures of biodiversity at a given scale can be consistently predicted using a minimal model containing zero free parameters, the Stochastic Logistic Model of growth (SLM). Extending these within-scale results, we examine the relationship between measures of biodiversity calculated at different scales (e.g., genus vs. family), an empirical prediction known as the Diversity Begets Diversity (DBD) hypothesis. We find that the relationship between richness estimates at different scales can be quantitatively predicted using the SLM, a stark contrast to the results we obtaned using the Unified Neutral Theory of Biodiversity. Contrastingly, only by including correlations between species (i.e., interactions) can we predict the relationship between estimates of diversity at different scales. The results of this study characterize novel microbial patterns across scales of evolutionary organization and establish a sharp demarcation between macroecological patterns that can and cannot be captured by a minimal model of biodiversity.