Different spatial structure of plant‐associated fungal communities above‐ and belowground
Bibliographic record
Abstract
Abstract The distribution and community assembly of above‐ and belowground microbial communities associated with individual plants remain poorly understood, despite its consequences for plant–microbe interactions and plant health. Depending on how microbial communities are structured, we can expect different effects of the microbial community on the health of individual plants and on ecosystem processes. Importantly, the relative role of different factors will likely differ with the scale examined. Here, we address the driving factors at a landscape level, where each individual unit (oak trees) is accessible to a joint species pool. This allowed to quantify the relative effect of environmental factors and dispersal on the distribution of two types of fungal communities: those associated with the leaves and those associated with the soil of Quercus robur trees in a landscape in southwestern Finland. Within each community type, we compared the role of microclimatic, phenological, and spatial variables, and across community types, we examined the degree of association between the respective communities. Most of the variation in the foliar fungal community was found within trees, whereas soil fungal community composition showed positive spatial autocorrelation up to 50 m. Microclimate, tree phenology, and tree spatial connectivity explained little variation in the foliar and soil fungal communities. Foliar and soil fungal communities differed strongly in community structure, with no significant concordance detected between them. We provide evidence that foliar and soil fungal communities assemble independent of each other and are structured by different ecological processes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".