The ecology of the phyllosphere: geographic and phylogenetic variability in the distribution of bacteria on tree leaves

Abstract

Large populations of bacteria live on leaf surfaces and these phyllosphere bacteria can have important effects on plant health. However, we currently have a limited understanding of bacterial diversity on tree leaves and the inter- and intra-specific variability in phyllosphere community structure. We used a barcoded pyrosequencing technique to characterize the bacterial communities from leaves of 56 tree species in Boulder, Colorado, USA, quantifying the intra- and inter-individual variability in the bacterial communities from 10 of these species. We also examined the geographic variability in phyllosphere communities on Pinus ponderosa from several locations across the globe. Individual tree species harboured high levels of bacterial diversity and there was considerable variability in community composition between trees. The bacterial communities were organized in patterns predictable from the relatedness of the trees as there was significant correspondence between tree phylogeny and bacterial community phylogeny. Inter-specific variability in bacterial community composition exceeded intra-specific variability, a pattern that held even across continents where we observed minimal geographic differentiation in the bacterial communities on P. ponderosa needles.

Fig. 1

Relative abundances of bacterial phyla and sub-phyla in each of the phyllosphere communities from the ‘inter-species’ study: (A) bacterial phyla (B) only proteobacterial sub-phyla. Note that B only shows the percentages of the various proteobacterial sub-phyla relative to the total abundance of Proteobacteria on each tree. We also note that in this figure we are only focusing on the interspecies variation as each symbol represents data from a single individual tree (see Fig. 3 and the associated section of the Results for a description of how intraspecies variation in bacterial community composition compares to interspecies variation across this study site).

Fig. 2

NMDS plot illustrating differences between bacterial communities on 56 tree species. Pairwise community distances determined using the weighted Unifrac algorithm (A) and the Kulczynski distance metric (B). Figure S3 shows this same plot with labels indicating the specific tree species represented by each point.

Fig. 3

Phylogenetic and OTU-based distances (Unifrac and Kulczynski distances respectively) between bacterial communities on an individual tree, on different individual trees of the same species, and on different tree species. Distances calculated from the 10 tree species that were examined to determine with intra-and inter-individual replicate samples. Note that this figure represents results from trees sampled at the same location (the University of Colorado campus) on the same day. Bars represent 95% confidence intervals around the mean.

Fig. 4

NMDS plots based on weighted UniFrac distances (A and C) and Kulczynski distances (panels B and D). Panels A and B show the Pinus ponderosa samples collected from sites in Australia and the USA along with samples representing other tree species (the P. ponderosa samples are within the dashed boxes). These two panels show that bacterial communities on P. ponderosa are relatively similar to one another regardless of geographic location (i.e. more similar to one another than to the bacteria on other tree species). Panels C and D focus just on the P. ponderosa samples in order to better show that sampling location has little to no effect on the observed differences between P. ponderosa- associated bacterial communities.