A comparison of turbine entrainment rates and seasonal entrainment vulnerability of two sympatric char species, bull trout and lake trout, in a hydropower reservoir
Bibliographic record
Abstract
Abstract Potadromous salmonids that reside in hydropower reservoirs often have a high recreational and conservation value. However, the potential seasonal turbine entrainment vulnerability patterns of potadromous salmonids are not well understood. Here, we use acoustic telemetry to test the hypothesis that adults of two species of the Salvelinus genus (bull trout and lake trout) differ in their seasonal patterns of entrainment and entrainment vulnerability over a 2‐year period. Our results show that while both species were entrained at similarly low annual rates (~1%), these two salmonids differed in their patterns of forebay residency and proximity, with implications for entrainment risk. Bull trout occupied the forebay at low rates across all seasons, with no clear seasonal pattern of forebay proximity. In contrast, lake trout displayed a strongly seasonal pattern of entrainment vulnerability with a distinct movement away from the forebay during the summer, and a large increase in forebay proximity and use in the winter and spring. These findings provide a novel species‐specific demonstration of the potential entrainment vulnerability of lake trout. The seasonal patterns of entrainment vulnerability seen in previous bull trout studies, where bull trout occupied top pelagic predator niches, were not replicated in our study where bull trout occur in sympatry with another top pelagic predator. These findings, which indicate that species composition plays an important role determining entrainment vulnerability, have important implications for the conservation of indigenous lake trout and bull trout populations, and together highlight the need for a site‐specific approach to entrainment quantification.
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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 | 0.000 |
| 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".