Out of site, out of mind: Changes in feather moss phyllosphere microbiota in mine offsite boreal landscapes
Bibliographic record
Abstract
Plant-microbe interactions play a crucial role in maintaining biodiversity and ecological services in boreal forest biomes. Mining for minerals, and especially the emission of heavy metal-enriched dust from mine sites, is a potential threat to biodiversity in offsite landscapes. Understanding the impacts of mining on surrounding phyllosphere microbiota is especially lacking. To investigate this, we characterized bacterial and fungal communities in the phyllosphere of feather moss Pleurozium schreberi (Brid). Mitt in boreal landscapes near six gold mine sites at different stages of the mine lifecycle. We found that (1) both mining stage and ecosystem type are drivers of the phyllosphere microbial community structure in mine offsite landscapes; (2) Bacterial alpha diversity is more sensitive than fungal alpha diversity to mining stage, while beta diversity of both groups is impacted; (3) mixed and deciduous forests have a higher alpha diversity and a distinct microbial community structure when compared to coniferous and open canopy ecosystems; (4) the strongest effects are detectable within 0.2 km from operating mines. These results confirmed the presence of offsite effects of mine sites on the phyllosphere microbiota in boreal forests, as well as identified mining stage and ecosystem type as drivers of these effects. Furthermore, the footprint was quantified at 0.2 km, providing a reference distance within which mining companies and policy makers should pay more attention during ecological assessment and for the development of mitigation strategies. Further studies are needed to assess how these offsite effects of mines affect the functioning of boreal ecosystems.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".