Aquatic vegetation trends from 1992 to 2012 in Hamilton Harbour and Cootes Paradise, Lake Ontario
Bibliographic record
Abstract
Over the past two hundred years, anthropogenic activities have resulted in the substantial decline of the once extensive wetlands in both Hamilton Harbour and Cootes Paradise. Some of the key stressors for aquatic vegetation have been infilling, sustained high water levels and level regulation in Lake Ontario, and reduced water clarity because of eutrophication and suspended sediments. Designated an Area of Concern in 1985, remediation efforts have included upgrades to the sewage treatment plants discharging into the harbour to reduce eutrophication and the 1996 construction of a fish barrier to exclude large Carp from entering Cootes Paradise to reduce turbidity. Over the past ten years, Cootes Paradise has seen a 120% increase in the areal extent of emergent vegetation, but this still represents less than 20% of the circa 1900's marsh area. Despite substantial reductions in Carp density in Cootes Paradise, submerged aquatic vegetation has been sparse and typically found at depths of less than 0.5 m, likely because of impaired light penetration. Following a significant improvement in water clarity in Hamilton Harbour between 1987 and 1997, submerged aquatic vegetation in the harbour proper expanded, achieving a mean maximum depth of 2.9 m in 2012. Species richness was considerably lower in Hamilton Harbour when compared to Cootes Paradise; however, the species composition in both these areas indicated degraded conditions throughout the time period of our assessment. Using our recent dataset, we tested relationships that had been previously established in the literature between emergent extent and water levels for Cootes Paradise and also the connection between maximum depth of submergent colonization and Secchi depths but simple univariate tests were not significant. A combination of small sample size, simple tests, and a small range for the independent variable may be issues in establishing simplified response relationships and are likely oversimplifications of vegetation response in the area that require more complex modelling.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".