Thermal Habitat Use by Lake Trout in Two Contrasting Yukon Territory Lakes
Bibliographic record
Abstract
Abstract Thermal habitat use by lake trout Salvelinus namaycush in two northern lakes in the southern portion of the Yukon Territory that differ in morphometry and thermal regime was monitored using temperature‐sensitive acoustics and radiotelemetry. We then contrasted in situ temperature selection by lake trout in these lakes with previously published estimates of the species' optimal thermal range of 8–12°C. We found that thermal habitat use by lake trout in the two northern lakes is not consistent with these literature‐derived expectations. In Dezadeash Lake, which is isothermal in summer, temperatures typically exceeded the literature‐derived upper limit of 12°C. Throughout the summer lake trout sought the coldest water in the lake, which was in the form of shallow coldwater plumes derived from alpine ice‐pack meltwater streams. Once lake temperatures declined in the fall, lake trout were distributed throughout the lake. In Kathleen Lake, where water temperatures ranged from approximately 2°C to 12°C in the summer, the majority of lake trout selected habitats throughout the summer and fall that were colder than the 8°C lower limit of their literature‐derived optimal thermal range. Our results highlight the importance of summer thermal refugia for lake trout inhabiting marginal systems and the variation in thermal habitat use among populations inhabiting different thermal environments. Given the established importance of thermal habitat availability to lake trout production, our results suggest the need to better understand optimal thermal habitat characteristics in nature, particularly in light of factors such as climate warming.
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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 | 0.001 |
| 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".