Declining reservoir elevations following a two-decade drought increase water temperatures and non-native fish passage facilitating a downstream invasion
Bibliographic record
Abstract
River ecosystems are threatened by interactions among river regulation, non-native species, and climate change. Water use has exceeded supply in USA’s Colorado River basin draining its two largest storage reservoirs (Lake Powell and Lake Mead). In 2022, Lake Powell began releasing water from its lower epilimnion into the Grand Canyon segment of the Colorado River, which (1) increased rates of fish passage from the reservoir through the dam and (2) created river temperatures suitable for establishment of non-native fishes. Subsequently, smallmouth bass ( Micropterus dolomieu) reproduced there for the first time. To assist managers concerned about this invasion, we developed models that (1) predicted propagule pressure at different reservoir elevations and (2) linked reservoir storage/operations, water temperatures, and population dynamics to forecast smallmouth bass population growth potential. Maintaining Lake Powell elevations above 1094 m (3590 ft) would likely minimize propagule pressure from the reservoir and create downstream conditions that minimize smallmouth bass population growth. Dam and reservoir management will likely be less effective for managing smallmouth bass if smallmouth bass become abundant in far downstream reaches.
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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".