Seasonal Assembly of Nectar Microbial Communities Across Angiosperm Plant Species: Assessing Contributions of Climate and Plant Traits

Abstract

Plant-microbe associations are ubiquitous, but parsing contributions of dispersal, host filtering, competition and temperature on microbial community composition is challenging. Floral nectar-inhabiting microbes, which can influence flowering plant health and pollination, offer a tractable system to disentangle community assembly processes. We inoculated a synthetic community of yeasts and bacteria into nectars of 31 plant species while excluding pollinators. We monitored weather and, after 24 h, collected and cultured communities. We found a strong signature of plant species on resulting microbial abundance and community composition, in part explained by plant phylogeny and nectar peroxide content, but not floral morphology. Increasing temperature reduced microbial diversity, while higher minimum temperatures increased growth, suggesting complex ecological effects of temperature. Consistent nectar microbial communities within plant species could enable plant or pollinator adaptation. Our work supports the roles of host identity, traits and temperature in microbial community assembly, and indicates diversity-productivity relationships within host-associated microbiomes.

Keywords: bacteria; coexistence; community assembly; microbiome; nectar; plant–microbe; pollination syndrome; species interactions; synthetic community; yeasts.

FIGURE 1

Schematic overview of the experiment. (A) We prepared a standardised, synthetic community of five microbe species—two yeasts and three bacteria—which are common representatives of floral nectar communities. (B) We inoculated 1 μL of this community (containing roughly 10⁴ cells of each species) suspended in a sucrose‐glycerol solution into the standing nectar of flowers of various species of plants which were bagged prior to opening to prevent microbial deposition by pollinators. Small blue arrows indicate direction of pipetting. (C) We left inoculated flowers bagged on plants for 24 h, recording afternoon high and overnight low temperatures. (D) After 24 h, we extracted nectar and plated aliquots on agar media and incubated them for a week. Afterwards, all CFUs were identified, tallied and used to calculate microbial abundance and density in the original nectar sample. Figure was prepared using BioRender (biorender.com).

FIGURE 2

Phylogenetic relationships among plant species (left) inoculated in this study, with plant species aligned to their respective nectar volumes, microbe CFU densities, CFU Shannon diversities (middle), and mean proportional composition of microbe species (right). For simplicity, the cladogram represents only branching order, not divergence times, among plant species. Coloured, transparent boxes indicate three major clades of angiosperms: Monocots in blue, and the eudicot superasterids in yellow and superrosids in pink. Subclades are indicated with circles positioned at their ancestral node: The asterid subclades the lamiids (L) and campanulids (C), along with the rosid subclades the malvids (M) and fabids (F).

FIGURE 3

Shannon diversity of inoculated microbe CFUs in relation to (A) total CFU density and (B) nectar volume across all plant species. In (A), the curved black solid line indicates a significant quadratic relationship, while in (B), the dashed grey line represents a nonsignificant linear trend line. Each point represents one inoculated flower, and all plant species are included.

FIGURE 4

(A) Nonmetric multidimensional scaling (NMDS) ordination of microbe community composition by plant species based on mean CFU densities. Each circular point represents the centroid of all observations for a given plant species, with whiskers representing the standard error of the mean for replicates in vertical and horizontal dimensions. Plants further apart in two‐dimensional space exhibited more dissimilar microbe communities. Plants are additionally coloured orange, green or purple based on the three clusters generated via hierarchical clustering analysis of microbe community composition (Figure S5). Statistically significant (p < 0.05) vectors for microbe species are shown as labelled black arrows (Met. = Metschnikowia, Aur. = Aureobasidium, etc.). The size and direction of vectors indicate the strength of the correlation and direction of increase for the variable in NMDS space respectively. (B) Boxplot showing median and interquartile range (with outliers as points) of multivariate homogeneity of group dispersions (equivalent to beta diversity) for the 31 plant species and two experimental control solutions. The y‐axis represents the distance of replicates to their respective group centroids, or equivalently the variability in community composition within plant species. Boxes are arranged in order of descending mean distance, with the three colours indicating the respective hierarchical cluster.

FIGURE 5

Relationship between microbial total CFU density in nectar of inoculated flowers and mean nectar peroxide concentration by plant species. Each point represents one inoculated flower and the respective species mean peroxide value. Points are jittered slightly horizontally to better visualise density.

FIGURE 6

Relationships between temperature extrema and microbe community metrics: (A, B) total CFU density and (C, D) CFU Shannon diversity. Statistically significant (p < 0.05) relationships with temperature variables (afternoon high of day of inoculation, and overnight low of night following inoculation) according to linear mixed models are indicated with solid black lines in panels (B, C), while nonsignificant trend lines are indicated with grey‐dashed lines in panels (A, D). Points are jittered slightly horizontally to better visualise density.