Seasonal movement patterns of Credit River brown trout (<i>Salmo trutta</i>)
Bibliographic record
Abstract
Zimmer M, Schreer JF, Power M. Seasonal movement patterns of Credit River brown trout ( Salmo trutta ). Ecology of Freshwater Fish 2010: 19: 290–299. © 2010 John Wiley & Sons A/S Abstract – Movement habits in riverine populations of brown trout vary among watersheds. Thus it is important to identify factors influencing differences in individual behaviour so as to improve the information resource base available for the design of river‐specific management strategies. Such information is particularly needed in the rapidly urbanising watersheds of eastern North America where relatively little is known about anthropogenic influences on brown trout populations. In this study, we examined the influence of water temperature on brown trout behaviour in the Credit River in south‐central Ontario, Canada with respect to seasonal movement patterns. Observed patterns of movement were also correlated with variations in river discharge and habitat quality. Forty‐three radio‐tagged, adult brown trout were tracked in a confined 39.8 km portion of the Credit River from 15 May 2002 to 28 July 2003. Fish were captured in three sections of the river that differed in distance downstream and habitat quality. Fish size had little impact on movement patterns. However, there was considerable variation in seasonal movement with upstream movements to summer positions, maintenance of summer positions, downstream and often extensive movements in fall. Also observed was maintenance of winter positions and repeated upstream movements in late spring‐early summer to previously used summer positions. The elaborate movement behaviour in the Credit River population was attributed to seasonal changes in thermal habitat quality. Fish tagged in less suitable thermal habitats moved significantly more than fish from more suitable thermal habitats.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.022 | 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 teacher head, 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".