Offsite effects of mining on the frequency and abundance of five understorey plant species in western Québec (Canada)
Bibliographic record
Abstract
Although the mining industry provides minerals and metals to the global market and represents important economic opportunities, it also constitutes a major anthropogenic disturbance in the ecosystems where it takes place. However, little is known about its offsite impacts on plant communities. We assessed the frequency and the abundance of five common boreal understorey plant species (Coptis trifolia (L.) Salisb., Cornus canadensis L., Linnaea borealis L., Lysimachia borealis (Raf.) U.Manns & Anderb., and Maianthemum canadense Desf.) at different distances around six mines in Abitibi-Témiscamingue and Nord-du-Québec (Québec). Frequency and (or) abundance of Coptis trifolia and M. canadense decreased near mines, suggesting that they might be sensitive to the loss of forest cover, particle deposition, and soil contamination induced by mining. Conversely, the frequency and abundance of Cornus canadensis increased near active mines, which indicates its resilience to the stress caused by mines and its ability to exploit the niche space left by more sensitive species. No effects on Linnaea borealis and Lysimachia borealis were observed. Our study suggests the possible presence of offsite impacts of mines on plant communities. Further studies considering enigmatic impacts should be conducted in order to develop our understanding of the broader environmental footprint of mining activity.
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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 | 0.001 | 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".