Evidence map›Paper›PMID 40527519›Full record

SynthesisEnvironmental microbiology2025

How Useful Are Plant Traits in Explaining Variation in Phyllosphere Microbial Abundance and Composition Across Hosts?

Geneviève Lajoie, Laurine Dariel

Abstract readSystematic Review
In one paragraph

Synthesis in Environmental microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Geneviève LajoieInstitut de Recherche en Biologie Végétale, Université de Montréal, Montréal, Canada.ORCID https://orcid.org/0000-0002-7133-6164
Laurine DarielInstitut de Recherche en Biologie Végétale, Université de Montréal, Montréal, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plant taxonomy has emerged as a key driver of plant-microbe associations, but the mechanisms underlying these associations remain poorly understood. By defining selective environmental gradients for microbial taxa, plant traits can provide more proximate explanations of microbial taxonomic turnover across plants than plant taxonomy alone. Whether key plant traits may generally predict plant-microbe associations, however, remains unknown. Here, we conducted a systematic review of the phyllosphere literature to evaluate whether specific plant traits consistently explained variation in the abundance and composition of leaf microbes within and among plant species. Drawing on results from over 100 studies, we showed that plant traits linked to development, primary metabolism and defence consistently shaped the composition of leaf bacterial and fungal communities, highlighting the relevance of these traits in predicting plant-microbe associations in the phyllosphere. Since most plant traits tested did not influence leaf microbial composition more frequently than expected by chance, our study underscores the importance of: (1) rethinking the scale and selection of plant traits used to investigate microbiome assembly; (2) refining the taxonomic resolution at which microbial communities are analysed and (3) considering alternative explanations such as stochastic processes or historical factors for improving our understanding of plant-microbe associations.

Indexed as

BacteriaFungiMicrobiotaPlant LeavesPlantscommunity assemblydata synthesisfunctional traitsphyllosphereplant microbiome

Identifiers

PMID40527519
PMCPMC12173714

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.