Evaluation of Toronto Region area of concern degradation of phytoplankton and zooplankton populations and analysis to support loss of fish and wildlife habitat beneficial use impairments
Bibliographic record
Abstract
This study identifies plankton communities impairments within the Toronto and Region Area of Concern (AOC) to determine food resources for forage fishes in different habitats to support an assessment of Beneficial Use Impairment (BUI) 13 (Degradation of Phytoplankton and Zooplankton Populations) and provide georeferenced habitat data for BUI 14 (Loss of Fish and Wildlife Habitat). Water quality, zooplankton abundance and biomass differed across habitat ecotypes, with Inner Harbour exhibiting very low biomass similar to the open waters of Lake Ontario and a higher proportion of small taxa like rotifers, in spite of elevated nutrients. Zooplankton prey reductions are likely due to multiple urban environmental impacts including runoff and contaminants. Ecotype impacted zooplankton productivity but not primary productivity, indicating that protected systems (Island channels, Habitat Cells and Embayments) can offer diverse physical habitats and forage for fishes. Though primary productivity rates were reduced in most habitats, productivity was shunted into bacterial growth which were highly elevated throughout the entire AOC. Seasonality in habitat characteristics differed between ecotype, notably the Cells and Islands. Seasonal plankton community assessments among a range of habitats are needed to determine how plankton are incorporated into the food web, and continued monitoring is critical to assess the effectiveness of major remediation initiatives, such as wetland creation, the ongoing Don Mouth Naturalization, and Flood Protection Projects.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".