Edaphic Selection Pressures as Drivers of Contrasting White Spruce Ectomycorrhizal Fungal Community Structure and Diversity in the Canadian Boreal Forest of Abitibi-Témiscamingue Region
Bibliographic record
Abstract
Little is known about edaphic selection pressures as drivers of contrasting white spruce ectomycorrhizal fungal community structure and diversity in the Canadian boreal forest. We hypothesized that community composition differs among the four sites sampled-nursery, mining site, forest edge, and natural forest. Ectomycorrhizal (ECM) fungal community structure and diversity was studied at the four locations with soil fertility gradient through morpho-molecular and phylogenetic analyses in relationships with rhizospheric soil chemical properties. 41 different species were identified. Mining site had a significantly different species composition than the surrounding environments. Soil pH and percentage of roots colonized by ECM fungi increased while soil P, N, Fe, C, K, Mg, Al, Ca, and Na contents declined across the soil fertility gradient: nursery → natural forest → forest edge → mining site. Contrary to the preference of acid soils by ECM fungi, a few ecologically adapted to high pH, poor soil chemical fertility, and low organic matter content colonize white spruce roots on the non-acidogenic mining site, allowing natural regeneration of white spruce seedlings. Other ECM fungi are adapted to high fertigation level of commercial nursery. This study clearly shows the contrasting difference in white spruce ectomycorrhizal fungal community structure and diversity driven by edaphic selection pressures.
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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 | 0.001 |
| 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".