Algal responses to metal(loid) pollution, urbanization, and climatic changes in subarctic lakes around Yellowknife, Canada
Bibliographic record
Abstract
The lakes around Yellowknife (Northwest Territories, Canada) have been impacted by multiple environmental stressors throughout the 20th and early 21st centuries. Here, we have synthesized diatom assemblage data from ten lake sediment cores from the Yellowknife area and used a landscape-scale paleolimnological approach to investigate the cumulative impacts of past gold mining activities, urbanization, and climate warming on aquatic biota. Our investigations indicated that diatom species turnover (measured using detrended canonical correspondence analysis) was highest at lakes closer to the city and mines, as these sites were more severely impacted by land-use changes (e.g., sewage disposal, run-off from waste disposal sites) and roaster stack emission from the gold mines. Diatom assemblage shifts indicative of climate-induced changes to lake thermal properties were also observed across the gradient of human activities. The inclusion of remote sites was useful to disentangle the effects of climate-mediated changes from impacts related to mining and urbanization. This investigation suggests that the diatom assemblages of the lakes around Yellowknife have changed markedly over the last ∼80 years and there are no signs of biological recovery since the cessation of mining activities around the turn of the 21st century. The biota of the subarctic lakes around Yellowknife are now strongly influenced by climate-mediated changes to lake thermal properties and the urban lakes are also influenced by the legacies of past land-use changes.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".