An integrated approach to identifying ecosystem recovery targets: Application to the Bay of Quinte
Bibliographic record
Abstract
In 1985, the International Joint Commission identified the Bay of Quinte as an Area of Concern due to its degraded ecosystem. A Remediation Action Plan was established with delisting targets including the goals of decreasing phosphorous loading and restoring the upper (fish and wildlife) and lower (phytoplankton, zooplankton, and benthic invertebrates) trophic levels. We examined the consistency among seven Remedial Action Plan targets using Ecopath, a mass-balance model, for the upper Bay of Quinte for the post Zebra Mussel (Dreissena polymorpha) invasion period (1995–2002). We quantified the trophic consequences of bottom-up-control by gradually reducing the phytoplankton biomass until the Ecopath model became unbalanced (27% reduction). Replicate (n = 25) mass-balance solutions consistently showed that reductions in Zebra Mussel biomass were necessary to achieve mass-balance. This bottom-up control met the nutrient (total phosphorus), fish, benthic invertebrates, and phytoplankton population RAP targets. Based on these consistent results, it is recommended that future modelling efforts examine the effects of further phytoplankton biomass reductions.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".