Using diatom assemblages and sulfur in sediments to uncover the effects of historical mining on Lake Arnoux (Quebec, Canada): a retrospective of economic benefits vs. environmental debt
Bibliographic record
Abstract
Monitoring changes in environmental conditions is increasingly important as the Canadian economic infrastructure ramps up exploration and mining development in the more inaccessible northern regions of Canada. Governments are concurrently assessing effects from past mining activities and absorbing the economic cost to society with on-going remediation and monitoring initiatives. The abandoned Aldermac mine in northwestern Quebec, mined from 1932–1943, is an excellent case study for assessing the state of environmental and economic effects of past mining operations. A paleolimnological approach, using diatoms as environmental proxies, was used to evaluate the spatial and temporal impacts on aquatic receiving environments. Based on the inferences drawn from diatom assemblages in Lake Arnoux, prior to mining activity, lake water pH was similar to that of surrounding lakes (circumneutral to weakly acidic). After mining operations terminated, changes in pH and alkalinity in Lake Arnoux coincided with distinct increases in sediment sulphur content. Across a 30- to 40-year span (circa 1940 to 1970s) a significant decline in phytoplankton flora coincided with lake acidification and increased clarity of the water column. This resulted in an increase in the benthic diatom population (>90%), replacing the planktonic diatoms. Observed shifts in environmental proxies are concurrent with one, and possibly two, reported tailings pond breaches at the abandoned mine site. Adverse effects of the abandoned Aldermac mine on nearby ecosystems, combined with pressure from local citizens and environmental groups, forced responsible accountability for site restoration led by the Quebec government. Based on the historical period of economic growth, the financial benefits of the Aldermac mine were significant and justify the current pay-it-backward costs for environmental remediation. However, it has now been documented that the pay-it-backward model is not sustainable in the modern economy.
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".