Molecular EcologyEcologyPeer-reviewed journal article
Seasonal assembly of the phyllosphere fungal microbiome of a perennial grass is robust to nutrient addition
Elizabeth T. GreeniD, Ignazio CarboneiD, Charles E. MitchelliD
Abstract
The leaf microbiome plays an important role in plant health and defense. Despite its importance, how the assembly of the leaf microbial community is modified by environmental conditions such as nutrient availability remains relatively uninvestigated. Soil nutrient availability may shift the outcome of microbial interactions within a host individual or influence the pool of microbes across the plant community. We hypothesized that leaf microbial diversity would increase across the season as leaves collect additional taxa, and that this seasonal assembly would be sensitive to nutrient addition. To assess this, we tracked the assembly of the fungal phyllosphere microbiome of the grass tall fescue (Lolium arundinaceum) in old-field vegetation over the growing season and experimentally tested whether the seasonality of the microbiome was modified by experimental addition of soil nutrients. Fungal diversity (Shannon diversity index, richness, and evenness) increased early in the season, with most metrics saturating before the end of the season. Community composition as measured by Bray-Curtis dissimilarity also shifted over the early and mid-growing season. Phylogeny-based machine-learning identified fungal lineages that were abundant in different seasons, linking seasonal community shifts to their evolutionary context. Nutrient addition was less important than time of season, but still significantly altered community composition and interacted with time to influence richness, with lowest richness in the low nutrient addition plots early in the season. The clear seasonality of the microbiome provides support for a dynamic phyllosphere microbiome, suggesting further studies manipulating fungal recruitment over the season. Furthermore, it highlights the robustness of seasonal assembly to variation in nutrient availability.
- organism: plant (other)
- assay: metagenomics
- research focus: ecology & biodiversity
- approach: machine learning (classical)
- Citations
- 2
- FWCI
- 7.36
- Field percentile
- top 6%
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