A restoration strategy to promote tree establishment in mining‐polluted rocky outcrops using bryophytes
Bibliographic record
Abstract
Abstract Introduction Mining activities can lead to the formation of degraded, barren, or metal‐contaminated ecosystems. Resource‐poor ecosystems such as rocky outcrops are more sensitive to mining degradation, and their natural regeneration can be challenging due to soil erosion, lack of resources or seeds, and soil acidification. Objectives Our aim was to test the effectiveness of using locally collected bryophyte ( Ceratodon purpureus [Hedw.] Brid.) mats as a restoration treatment to protect and promote the establishment of tree seedlings in mining‐polluted rocky outcrops in Rouyn‐Noranda (Canada). Methods The bryophyte restoration treatment inspired by natural succession processes was compared to a control, where only local soil was used as substrate, and to a liming treatment that increases soil pH. The three treatments were applied to sixty 1 × 1 m units located on five outcrops at various distances (1.9–26.9 km) from the pollution source. Four tested tree species were each seeded at a density of 100 seeds/m 2 on all units. Results The bryophyte treatment had a positive effect on the establishment success of Jack pine seedlings ( Pinus banksiana Lamb.) with an establishment rate of 12% compared to 5 and 4% for liming and control treatments, respectively. Wind exposure had a significant negative effect on seedling establishment, potentially masking any negative effects of soil heavy metal concentration, which were not statistically significant. Conclusions Our strategy using bryophytes and mimicking natural succession has the potential to effectively regenerate trees in degraded rocky outcrops.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".