Evaluating recovery in aquatic production in the Bay of Quinte: A perspective based on changes in sedimentary diatom assemblages
Bibliographic record
Abstract
The International Joint Commission (IJC) designated 43 sites along the Great Lakes as Areas of Concern (AOCs) in North America in 1987. These areas were extremely damaged due to anthropogenic activities and chosen for immediate recovery plans. One of the AOCs is the Bay of Quinte, an inlet of Lake Ontario. Although remediation efforts started in the Bay of Quinte in the early 1980s, the structure and function of this ecosystem remains impaired from excess nutrients, toxic contaminants, invasive species like dreissenid mussels, and in recent years the added stressor of climate change. The Bay of Quinte is one of the most well studied regions in Canada with over 50 years of monitoring data. Using a paleolimnological approach, I tracked changes in the diatom assemblage composition and abundance over time, to assess the cumulative impact of environmental stressors on diatom production and assess ecosystem recovery. Diatom assemblages were identified in two sediment cores taken from the middle and lower bays to assess changes over the last century, but with a focus on ecosystem recovery since the 1970s. Diatom assemblages were assessed at a decadal-scale resolution using changes in relative abundance and concentration and compared to government monitoring data. Overall findings are consistent with the monitoring data with changes in diatom abundance and composition reflecting more eutrophic assemblages in the 1960s and 70s, and a change to less productive conditions following nutrient abatement laws in 1978 and recorded changes in aquatic production. An enhanced production in benthic taxa was also seen in the sediment record, inferring an increase in littoral production coincident with enhanced water clarity from both nutrient abatement and zebra mussel establishment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".