Downstream effects of hydroelectric dam operation on thermal habitat use by Brook Trout (<i>Salvelinus fontinalis</i>) and Slimy Sculpin (<i>Cottus cognatus</i>)
Bibliographic record
Abstract
Abstract Hydroelectric dams can alter downstream water temperatures, impacting thermal habitat available for fishes. Decreases in river water temperatures resulting from hydroelectric dam operations may be beneficial to coldwater species and could potentially offset warming resulting from climatic trends. We used two coldwater fish species, Slimy Sculpin ( Cottus cognatus ) and Brook Trout ( Salvelinus fontinalis ) to assess the impact of a cool water draw below a 15 MW hydroelectric dam on fish thermal habitat use relative to a nearby naturally flowing river. Cooler water temperatures below the dam corresponded with significantly cooler mean growth season temperature use for Slimy Sculpin, but not Brook Trout, relative to the natural river. As well, mean growing season temperature use by Slimy Sculpin was significantly cooler relative to Brook Trout in both rivers, and significantly different amongst studied sites in the regulated river. Fish condition was significantly correlated with temperature use for Slimy Sculpin in the naturally flowing river only. Our results indicate that manipulating river water temperatures through hydroelectric dam operations to benefit multiple fish species will be difficult given the complexity of riverine thermal habitat and species‐specific differences in thermal preferences and behaviour.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".