Plant community influences on soil microfungal assemblages in boreal mixed-wood forests
Bibliographic record
Abstract
We studied the relationships between assemblages of soil microfungi and plant communities in the southern boreal mixed-wood forests of Quebec. Sampling took place in 18,100 m2 plots from an existing research site. Plots were separated into three categories based on dominant overstory tree species: (i) trembling aspen, (ii) white birch and (iii) a mixture of white spruce and balsam fir. Within each plot a 1 m2 subplot was established in which the understory herbaceous layer was surveyed and soil cores were collected. Microfungi were isolated from soil cores with the soil-washing technique and isolates were identified morphologically. To support our morphological identifications DNA sequences were obtained for the most abundant microfungi. The most frequently occurring microfungal species were Penicillium thomii, P. spinulosum, P. janthinellum, Penicillium sp., P. melinii, Trichoderma polysporum, T. viride, T. hamatum, Mortierella ramanniana, Geomyces pannorum, Cylindrocarpon didymum, Mortierella sp. and Mucor hiemalis. Multivariate analyses (redundancy analysis followed by variance partitioning) revealed that most of the variation in microfungal communities was explained by understory plant species composition as opposed to soil chemistry or overstory tree species. In this floristically diverse system saprophytic microfungal assemblages were not correlated with the overstory tree species but were significantly correlated with the main understory herbs, thereby reflecting differences at a smaller spatial scale.
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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 | 0.001 | 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) | 0.001 | 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".