Drought-related changes in water quality surpass effects of experimental flows on trout growth downstream of Lake Powell reservoir
Bibliographic record
Abstract
Flows released from reservoirs are often modified to mitigate the negative ecosystem effects of dams. We estimated the effects of two experimental flows, fall-timed floods and elimination of sub-daily variation in flows on weekends, on growth rates of rainbow trout ( Oncorhynchus mykiss) in the Colorado River downstream from Glen Canyon Dam. Experimental flow effects were compared to effects of water temperature, phosphorous concentration, solar insolation, and competition, by fitting mixed effect von Bertalanffy models to ∼ 10 000 observations of growth from mark-recapture between 2012 and 2021. There was strong support for models predicting faster growth during intervals with higher solar insolation, and lower water temperature and competition for prey. Effects of phosphorus and experimental flows were small and uncertain. Drought-related increases in dam release temperatures during summer and fall were predicted to result in severe weight loss for larger trout and could eventually threaten the viability of the population and the fishery it supports. The effects of water temperature and competition on fish growth substantially exceeded the effects of controlled floods and steadier flows.
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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 | 0.000 | 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".