Synergistic effects in mine offsite landscapes: Predicted ecosystem shifts could exacerbate mining effects on bryophyte community structure
Bibliographic record
Abstract
Global change is shifting ecosystem type relative abundance in boreal forests, while the green energy transition results in increased mining activities around the globe. The interaction and consequent effects of these two trends on biodiversity have not been examined in depth. Bryophytes species can be used as indicators to measure these effects because they play key ecological roles in boreal forests. We identified and evaluated the interaction between ecosystem type (i.e., coniferous, deciduous, mixed forest and open canopy) and mining on microhabitat scale bryophyte diversity and composition in 1-km landscapes surrounding six mine sites at different stages of the mining lifecycle in the Canadian boreal forest. Irrespective of microhabitat type, the combined effects of ecosystem type and mining stage were interactive on bryophytes. Bryophyte richness and community composition were negatively affected by offsite effects of mines in only deciduous and mixed forests. The interacted effects on bryophyte richness mainly occurred on the ground r microhabitats. We also found that deciduous, mixed forests (coniferous forest as a reference) and mines had a negative impact on the abundance of feather mosses and sphagna. Furthermore, indicator species were identified for areas affected by mines (Pohlia nutans and Dicranum polysetum) and for control areas (Sphagnum angustifolium and Plagiomnium cuspidatum). Our results suggest the predicted ecosystem shifts with global changes, from coniferous to deciduous forests, could potentially increase the effects of mining on forest ecosystem resistance through the changes in bryophyte community structure. Adding microhabitats (i.e., adding coarse woody debris) near mine sites is a potential strategy to maintain species richness. Collectively, these findings advance our understanding of how mining affects biodiversity and highlight the importance of considering mine offsite landscapes in future environmental evaluations of development projects in the context of global changes.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".