Isolation, identification, and community study of root fungal isolates from disturbed and undisturbed Arctic and alpine tundra habitats in Northern Quebec, Canada
Bibliographic record
Abstract
In northern ecosystems such as the subarctic tundra, mining activities increase stress to a point where actions are needed to promote site reclamation. Ecological restoration of these mining-impacted sites with beneficial microorganisms, such as mycorrhizal fungi, is considered necessary and useful for the growth and survival of their host plants, but also for their tolerance to poor and contaminated environments, such as mine tailings. Here, we are interested in root symbionts associated with plants from the Schefferville mining site in northern Quebec. Very few studies of root fungal communities have been conducted in such a northern environment. The spatial and host plant variation of root fungal isolates was investigated. A total of 456 culturable fungi were isolated, of which 376 were successfully identified and assigned to 106 taxa based on rDNA internal transcribed spacer analysis using ITSF-1 and ITS-4 primers. The most commonly isolated fungi belonged to three genetically related groups: the Rhizoscyphus ericae aggregate, the dark septate endophytes, and Umbelopsis rammaniana and Mortierella sp., which are known to be genetically very close and often misclassified as one another. These groups were present on both disturbed and natural sites, but it appears that plants from disturbed sites had a greater affinity for dark septate endophytes. This study is the first step in the development of a restoration plan for the Schefferville mining site, and the baseline data obtained open new avenues for future studies, including the use of indigenous mycorrhizal-based biofertilizers to implement ecological revegetation strategies.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".