Biotelemetry-based Monitoring of Fish-habitat Interactions as an Informative Window into Habitat Management in a Multi-species Fish Community in Toronto Harbour
Bibliographic record
Abstract
Understanding how animals interact with habitat is a fundamental ecological question with applied implications for conservation and management of biodiversity.In the Laurentian Great Lakes, coastal wetlands provide critical habitat for over 80% of fish species in the community; however, over 70% of all wetlands have been lost and many of the remaining wetlands have seen declines in habitat quality.I used acoustic telemetry to track the space use behaviour of Largemouth Bass (Micropterus nigricans), Northern Pike (Esox lucius), Common Carp (Cyprinus carpio), and Yellow Perch (Perca flavescens) in coastal habitat of Toronto Harbour, Lake Ontario.In Chapter 2, I found that Northern Pike, and Yellow Perch had higher daily site fidelity in restored areas, while Common Carp had lower daily site fidelity in restored areas.Each species exhibited highest daily site fidelity during the summer and lowest during the fall.Overall, daily site fidelity estimates were highest in warm, shallow, vegetated, and sheltered regions of the harbour.In Chapter 3, I found that the size and degree of overlap in activity spaces was influenced by season and body size.Generally, activity spaces were largest in the summer and smallest in the winter.The degree of overlap between individual activity spaces was greatest during both of these seasons, but overall, overlap was quite low.In general, the estimated activity spaces were moderately sized compared with those reported in the literature.In Chapter 4, I found that variation in activity was influenced by species, habitat, season, diel period, and body size.Generally, Largemouth Bass exhibited greater activity levels compared to Northern Pike; however, there was considerable variability within both species.The greatest differences in the activity levels between species were observed in colder, exposed habitats, whereas, in coastal vegetated opportunities to attend management meetings and scientific conferences and perform fieldwork.Thank you for sharing in my successes and supporting me in my 'nonsuccesses'.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".