Assessing the Long-Term Ecosystem Productivity Benefits and Potential Impacts of Forests Re-Established on a Mine Tailings Site
Bibliographic record
Abstract
Restoring sites disturbed by industrial activity to a forested condition can ensure the continued provision of economic and ecosystem services from these areas. Impounded mine tailings are particularly challenging sites, and positive benefits of establishing trees must be balanced against risks associated with metal contamination, ongoing tailings stability, and the possibility of acid mine drainage. We used a hybrid biometric modelling approach based on dendrochronological reconstruction to retrospectively (1980–2015) quantify productivity and carbon dynamics of pine plantations growing on impounded mine tailings at the Vale waste management facility near Sudbury, Canada. Historical reclamation practices had remediated conditions sufficiently to allow conifer plantation establishment in the late 1970s. The revegetated sites were highly productive, when compared to reference conditions based on site index, wood volume growth, and ecosystem production, congruent with other studies showing that forests on revegetated post mining sites can be highly productive. However, metal concentrations in the forest floor were high, and further research is warranted to evaluate ecosystem impacts. Due to the requirement for energy-intensive inputs, we estimated that it took 12 years or more to recover the emissions associated with the revegetation process through C accumulated in biomass and soil at the revegetated sites.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".