Tree Diversity Reduces Fungal Endophyte Richness and Diversity in a Large-Scale Temperate Forest Experiment
Why this work is in the frame
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Bibliographic record
Abstract
Although decades of research have typically demonstrated a positive correlation between biodiversity of primary producers and associated trophic levels, the ecological drivers of this association are poorly understood. Recent evidence suggests that the plant microbiome, or the fungi and bacteria found on and inside plant hosts, may be cryptic yet important drivers of important processes, including primary production and trophic interactions. Here, using high-throughput sequencing, we characterized foliar fungal community diversity, composition, and function from 15 broadleaved tree species (N = 545) in a recently established, large-scale temperate tree diversity experiment using over 17,000 seedlings. Specifically, we tested whether increases in tree richness and phylogenetic diversity would increase fungal endophyte diversity (the “Diversity Begets Diversity” hypothesis), as well as alter community composition (the “Tree Diversity–Endophyte Community” hypothesis) and function (the “Tree Diversity–Endophyte Function” hypothesis) at different spatial scales. We demonstrated that increasing tree richness and phylogenetic diversity decreased fungal species and functional guild richness and diversity, including pathogens, saprotrophs, and parasites, within the first three years of a forest diversity experiment. These patterns were consistent at the neighborhood and tree plot scale. Our results suggest that fungal endophytes, unlike other trophic levels (e.g., herbivores as well as epiphytic bacteria), respond negatively to increasing plant diversity.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it