Differences in movements of northern pike inhabiting rivers with contrasting flow regimes
Bibliographic record
Abstract
Abstract Little is known about the effect of short‐term flow changes on the movement of northern pike (Esox lucius L.). We conducted a comparative study in two rivers with different flow regimes (i.e. one regulated and one unregulated) to evaluate the extent to which adult northern pike movement is influenced by short‐term river flow conditions. Data on northern pike hourly movement were collected in northeastern Ontario on 40 individuals in the Mississagi River, a river subjected to extreme daily flow variations associated with hydro‐electric operations (i.e. hydropeaking), and the Aubinadong River, an unregulated river. Using manual tracking by radio‐telemetry, we found that northern pike moved at a higher rate in the river subjected to short‐term changes in river flow than in the unregulated river. Results also show that the relationship between movement of northern pike and flow can vary among rivers. In the Mississagi River, flow had a significant positive effect on northern pike activity, while the effect of flow in the Aubinadong River depended on water temperature. Moreover, fish in the Mississagi River utilized a restricted river section and travelled more laterally in comparison to fish inhabiting the Aubinadong River, where longer upstream‐downstream movements were more common. The present study contributes to our understanding of the effects of short‐term changes in flow on fish movement. This constitutes the first step towards assessing the effect of flow on fish habitat use, and eventually developing flow management strategies to mitigate impacts on fish. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".