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Abstract Background and aimsPlant interactions with soil microbial communities are critical for understanding plant health, improving horticultural and agricultural outcomes, and maintaining diverse natural communities. In some cases, disease suppressive soils enhance plant survival in the presence of pathogens. However, species-specific differences and seasonal variation complicate our understanding of the drivers of soil fungal communities and their consequences for plants. Here, we aim to describe soil fungal communities acrossRhododendronspecies and seasons as well as the test for fungal indicators ofRhododendronspecies in the soil. Further, we test possible mechanisms governing disease suppressive soils to the oomycete pathogenPhytophthora cinnamomi. Variation in disease susceptibility to this pathogen across species and clades allows us to test for possible fungal drivers of disease suppressive soils. MethodsWe conducted high throughput sequencing of the fungal communities found in soil collected under 14Rhododendronspecies and across 2 seasons (April, October) at two sites in Ohio, USA. Phylogenetic analyses were used to ask whether fungal community composition correlated with increased plant survival with the addition of whole soil communities from a prior greenhouse experiment. ResultsEffects ofRhododendronspecies (R2 = 0.13), season (R2 = 0.01) and their interaction on fungal communities (R2 = 0.11) were statistically significant. Fungal community composition negatively correlated with survival following exposure to whole soil microbial communities, though this result depended on the presence ofR. minus. Forty-fiveTrichodermataxa were identified across our soil samples, and someTrichodermawere significantly associated with particularRhododendronspecies (e.g.Trichoderma atroviridewas associated withR. molle) in indicator species analyses. ConclusionThe correlation between plant responses to soil biotic communities and fungal community composition, as well as the presence of potential beneficial taxa such asTrichodermaand mycorrhizal fungi, are consistent with fungal-mediated survival benefits from the pathogenPhytophthora cinnamomi.
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This content will become publicly available on April 1, 2027
Multiple Mechanisms Required to Predict Grass Community Composition
ABSTRACT Accurate prediction of community assembly is a central goal in ecology but is challenging because assembly is governed by numerous mechanisms. Few theoretical models explicitly incorporate or test multiple mechanisms at once. We empirically tested the predictive performance of a plant community assembly model built using all possible combinations of four ‘mechanisms’ (soil resource competition, dispersal and colonisation, spatiotemporal niche differentiation, population growth rates) and 11 underlying ‘attributes’ based on measured traits (e.g., fecundity, phenology). The full model accurately predicted out‐of‐sample biomass observations of five grasses sown in mixture along a soil nitrogen gradient (overallR2 = 0.65). Alternative model variants, parameterised using subsets of the mechanisms and their nested attributes, still retained high explanatory power if the model included at least three of the four mechanisms. Our results suggest that plant community composition is determined by simultaneous effects of multiple mechanisms, and simpler theories have much lower predictive abilities.
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- Award ID(s):
- 2425352
- PAR ID:
- 10686797
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Ecology Letters
- Volume:
- 29
- Issue:
- 4
- ISSN:
- 1461-023X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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