Evaluating the efficacy of ecological restoration of fish habitat in coastal waters of Lake Ontario
Bibliographic record
Abstract
Ecological restoration is a common strategy applied to degraded wetlands and tributaries in large lakes. As resources are typically limited for restoration, it is essential to ensure that such efforts achieve associated goals. Using both discrete and continuous methods, we evaluated the efficacy of ecological restoration efforts on fish habitat within Canada's largest city, Toronto (Cell 2 and Embayment D of Tommy Thompson Park) relative to a control site (Toronto Islands). First, we used a long-term electrofishing dataset (i.e., discrete) to examine catch and community composition relative to restoration status. Catch for northern pike (Esox lucius) remained constant at both restoration sites, and catch of invasive common carp (Cyprinus carpio) decreased at Embayment D, indicating that exclusion barriers may be effective. Restoration was less effective for largemouth bass (Micropterus nigricans) as catches remained similar after restoration at Cell 2, but decreased within Embayment D. We also found that relative abundance for coldwater species at both restoration sites decreased post-restoration, with increases in warmwater species at Cell 2 and coolwater species at Embayment D. Next, we used a long-term acoustic telemetry dataset (i.e., continuous sampling) with three focal species: largemouth bass, northern pike, and invasive common carp. Based on telemetry, we found that restoration efficacy was species-specific, with largemouth bass present before and after ecological restoration (particularly in spring, which may be associated with spawning), but clear reductions in use of the restored areas for common carp and northern pike. Exclusion barriers, while effective at blocking common carp, appeared to also negatively influence access for northern pike. Using both discrete and continuous methods longitudinally and across both treatment and control sites provided complementary information on the efficacy of restoration works within Toronto Harbour, with electrofishing data highlighting changes in fish community composition while acoustic telemetry provided continuous information on timing and duration of habitat use.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".