Seasonal and spatial patterns of growth of rainbow trout in the Colorado River in Grand Canyon, Arizona
Bibliographic record
Abstract
Rainbow trout (Oncorhynchus mykiss) have been purposely introduced in many regulated rivers, with inadvertent consequences on native fishes. We describe how trout growth rates and condition could be influencing trout population dynamics in a 130 km section of the Colorado River below Glen Canyon Dam based on a large-scale mark–recapture program where ∼8000 rainbow trout were recaptured over a 3-year period (2012–2014). There were strong temporal and spatial variations in growth in both length and weight as predicted from von Bertalanffy and bioenergetic models, respectively. There was more evidence for seasonal variation in the growth coefficient and annual variation in the asymptotic length. Bioenergetic models showed more variability for growth in weight across seasons and years than across reaches. These patterns were consistent with strong seasonal variation in invertebrate drift and effects of turbidity on foraging efficiency. Highest growth rates and relative condition occurred in downstream reaches with lower trout densities. Results indicate that reduction in rainbow trout abundance in Glen Canyon will likely increase trout size in the tailwater fishery and may reduce downstream dispersal into Grand Canyon.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".