The thermal biology of fish in the Laurentian Great Lakes: insight from biologging and biotelemetry tools.
Bibliographic record
Abstract
Although the thermal biology of many freshwater species of fish is well known, the majority of this information has been determined in a laboratory setting, while information on thermal biology of free-swimming fish is rare.The purpose of this thesis was to characterize the thermal biology of three important fish species in the Laurentian Great Lakes using biologging and biotelemetry tools.Thermal patterns for adult walleye from Lake Erie and Huron were determined using biologging to assess the effects of sex, fish size, diel periods, and location (i.e., lake) using a generalized linear mixed model.Sex, size, and diel periods had no effect on thermal occupancy of adult walleye in either lake.Thermal occupancy differed between lakes and seasons.The depths and temperatures used by different sizes of northern pike and largemouth bass in the Toronto Harbour of Lake Ontario were studied using biotelemetry.Analyses of the data revealed northern pike occupied deeper depths, while experiencing similar thermal regimes throughout the majority of the year compared to largemouth bass, with the exception of summer, where pike were observed in cooler waters than bass.As water temperatures exceeded 10 o C, both northern pike and largemouth bass were observed to behaviourally thermoregulate and selected temperatures warmer than those in the vicinity of the telemetry stations at which they were detected.When water temperatures exceeded 20 o C, northern pike were observed to select cooler waters.As a whole, this thesis enhances the understanding of the thermal biology of free-swimming fish in the Laurentian Great Lakes informing the management of three economically, ecologically, and socially important fish species.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".