A Paleoenvironmental Study Tracking Eutrophication, Mining Pollution, and Climate Change in Niven Lake, the First Sewage Lagoon of Yellowknife (Northwest Territories) + Supplementary Appendix 1 (See Article Tools)
Bibliographic record
Abstract
Niven Lake was the first wastewater disposal site for the City of Yellowknife (Northwest Territories, Canada), receiving domestic sewage for more than 30 years. Here, we used a high-resolution sediment core to track past sewage inputs to Niven Lake by comparing changes in sedimentary sterols and three diagnostic ratios for human fecal contamination, as well as biological assemblages and overall lake production, with the known history of sewage inputs to the lake from 1948 to 1981. Coprostanol, often considered the best indicator of human fecal contamination, increased by ~8% between depths of 7.5 cm and 5 cm (~1950 to 1981) and was more reliable in tracking sewage contamination than diagnostic sterol ratios. Muted responses in subfossil diatom and chironomid assemblages were noted during the time of sewage inputs, and similar responses have been reported in other eutrophic Arctic sites, as well as in many macrophyte-dominated shallow lakes in general. More marked shifts in diatoms and chironomids occurred a decade after the end of sewage inputs, in the 1990s, a time that closely aligned with the warmest years on record for Yellowknife. This post–sewage era response was indicative of anoxia and possibly of positive feedback from internal phosphorus loading. The response may have been facilitated by recent climate warming, resulting in a lagging recovery from eutrophication. Changes in the diatoms and chironomids of Niven Lake were also indicative of metal pollution, suggesting that the lake has experienced the compounding effects of arsenic contamination from nearby gold mining.
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 | 0.001 | 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) | 0.002 | 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".