Core arbuscular mycorrhizal fungi are predicted by their high abundance–occupancy relationship while host‐specific taxa are rare and geographically structured
Bibliographic record
Abstract
Habitat restoration may depend on the recovery of plant microbial symbionts such as arbuscular mycorrhizal (AM) fungi, but this requires a better understanding of the rules that govern their community assembly. We examined the interactions of soil and host-associated AM fungal communities between remnant and restored patches of subtropical montane forests. While AM fungal richness did not differ between habitat types, community membership did and was influenced by geography, habitat and host. These differences were largely driven by rare host-specific AM fungi that displayed near-complete turnover between forest types, while core AM fungal taxa were highly abundant and ubiquitous. The bipartite networks in the remnant forest were more specialized and hosts more specific than in the restored forest. Host-associated AM fungal communities nested within soil communities in both habitats, but only significantly so in the restored forest. Our results provide evidence that restored and remnant forests harbour the same core fungal symbionts, while rare host-specific taxa differ, and that geography, host identity and taxonomic resolution strongly affect the observed distribution patterns of these fungi. We suggest that host-specific interactions with AM fungi, as well as spatial processes, should be explicitly considered to effectively re-establish target host and symbiont communities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".