The effect of changing winter temperature conditions on the overwintering behaviour of a northern smallmouth bass population
Bibliographic record
Abstract
Under a changing global climate, north temperate lakes are experiencing warmer winter temperatures with receding ice duration. Yet, how warm-water fish inhabiting these ecosystems behaviourally respond to changing year-over-year winter conditions is unknown. Here, I employed acoustic telemetry to track the overwintering behaviours (daily temperature occupancy, depth, and activity, and winter home ranges) of 13 adult smallmouth bass (Micropterus dolomieu), a warm-water centrarchid, in a boreal lake (Smoke Lake, Algonquin Park, Ontario) across three consecutive winters (2021-22, 2022-23, 2023-24). Winter temperatures and smallmouth bass overwintering behaviours varied across the three years. Within-year variation across individuals was high, but the population migrated to deeper depths to maintain consistent experienced temperatures during years 1 and 2 (9.0 +/- 6.6 m and 14.9 +/- 6.9m, respectively, and 2.34 +/- 0.20˚C and 2.26 +/- 0.36˚C, respectively). However, the bass remained at shallower, colder depths in year 3 (7.8 +/- 5.0 m and 1.84 +/- 0.24˚C), the year with shortened ice duration, despite warmer temperatures being available deeper. Overwinter space use size was greatest in year 2, with significant variation observed among individuals. Finally, in the year spring warming began two weeks earlier, an increase in smallmouth bass activity coincided. My research provides evidence of a Centrarchidae species responding to changing thermal conditions in winter via behavioural traits, including what appears to be the first confirmation of flexible depth use beneath an ice-covered lake, which may play an important role in their responsiveness to 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".