Environment and host identity structure communities of green algal symbionts in lichens

For trees, mammals, birds, reptiles, insects, and amphibians, the species richness on mountaintops is generally less than that of lowland areas. Coincident with this decline in species richness with increasing elevation is an increase in the altitudinal range of species. This pattern is analogous to the relationship between the latitudinal range of species and latitude (Rapoport's latitudinal rule). Both of these Rapoport phenomena, the latitudinal and the new elevational rule discussed here, can be explained as being results of differences in the breadth of climatic conditions organisms experience along the geographical gradients. The influence of latitudinal or altitudinal range size on local species richness is poorly understood, but the tendency for range margins to fall in species-rich, rather than species-poor, areas may mean that species-rich communities contain many species that are maintained only through immigration. The presence of these persistent but locally non-self-maintaining populations may explain the increased number of species found in rich communities as compared to species-poor communities without the need to invoke other differences in local species interactions.

Previously we presented Swarm v1, a novel and open source amplicon clustering program that produced fine-scale molecular operational taxonomic units (OTUs), free of arbitrary global clustering thresholds and input-order dependency. Swarm v1 worked with an initial phase that used iterative single-linkage with a local clustering threshold (d), followed by a phase that used the internal abundance structures of clusters to break chained OTUs. Here we present Swarm v2, which has two important novel features: (1) a new algorithm for d = 1 that allows the computation time of the program to scale linearly with increasing amounts of data; and (2) the new fastidious option that reduces under-grouping by grafting low abundant OTUs (e.g., singletons and doubletons) onto larger ones. Swarm v2 also directly integrates the clustering and breaking phases, dereplicates sequencing reads with d = 0, outputs OTU representatives in fasta format, and plots individual OTUs as two-dimensional networks.

High-throughput sequencing of PCR-amplified taxonomic markers (like the 16S rRNA gene) has enabled a new level of analysis of complex bacterial communities known as microbiomes. Many tools exist to quantify and compare abundance levels or OTU composition of communities in different conditions. The sequencing reads have to be denoised and assigned to the closest taxa from a reference database. Common approaches use a notion of 97% similarity and normalize the data by subsampling to equalize library sizes. In this paper, we show that statistical models allow more accurate abundance estimates. By providing a complete workflow in R, we enable the user to do sophisticated downstream statistical analyses, whether parametric or nonparametric. We provide examples of using the R packages dada2, phyloseq, DESeq2, ggplot2 and vegan to filter, visualize and test microbiome data. We also provide examples of supervised analyses using random forests and nonparametric testing using community networks and the ggnetwork package.