Root-colonizing and soil-borne communities of arbuscular mycorrhizal fungi in a temperate forest understorey
Bibliographic record
Abstract
We analyzed arbuscular mycorrhizal fungal (AMF) communities in plant root samples from a natural forest ecosystem — a primeval forest in Järvselja, Estonia. AMF small-subunit (SSU) ribosomal RNA genes were subjected to 454-pyrosequencing and BLAST-based taxonomic identification. Seventy-six AMF sequence groups (virtual taxa, VT) were identified from plant roots. Taken together with seven additional VT recorded in an earlier investigation of soil AMF communities at the site, this represents the highest number of AMF reported from a single ecosystem to date. The six study plant species hosted similar AMF communities. However, AMF community composition in plant roots was significantly different from that in soil and considerably more VT were retrieved from roots than from soil. AMF VT identified from plant roots as a whole and from individual plant species were frequently phylogenetically clustered compared with local and global taxon pools, suggesting that nonrandom assembly processes, notably habitat filtering, may have shaped fungal assemblages. In contrast, the phylogenetic dispersion of AMF communities in soil did not differ from random subsets of the local or global taxon pools.
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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 | 0.001 | 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) | 0.000 | 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 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".