Factors controlling the abundance of rainbow trout in the Colorado River in Grand Canyon in a reach utilized by endangered humpback chub
Bibliographic record
Abstract
We estimated the abundance, survival, movement, and recruitment of non-native rainbow trout (Oncorhynchus mykiss) in the Colorado River in Grand Canyon to determine what controls their abundance near the Little Colorado River (LCR) confluence where endangered humpback chub (Gila cypha) rear. Over a 3-year period, we tagged more than 70 000 trout and recovered over 8200 tagged fish. Trout density was highest (10 000–25 000 fish·km–1) in the reach closest to Glen Canyon Dam, where the majority of trout recruitment occurs, and was 30- to 50-fold lower (200–800 fish·km–1) in reaches near the LCR confluence ∼100 km downstream. The extent of rainbow trout movement was limited with less than 1% of recaptures making movements greater than 20 km. However, because of high trout densities in upstream source areas, this small dispersal rate was sufficient to explain the threefold increase in the relatively small population near the LCR. Reducing dispersal rates of trout from upstream sources is the most feasible solution to maintain low densities near the LCR to minimize negative effects of competition and predation on humpback chub.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".