Growth, Condition and Survival of Three Forage Fish Species Exposed to Two Different Experimental Hydropeaking Regimes in a Regulated River
Bibliographic record
Abstract
Abstract Hydroelectric dam operation can alter discharge and temperature patterns, impacting fish populations downstream. Previous investigations into the effects of river regulation on fish have focused on a single species within a river, yet different results among studies suggest the potential for species‐specific impacts. Here, we compare the impacts of two different hydropeaking regimes relative to a naturally flowing river on three ecologically important members of the forage fish community: longnose dace ( Rhinichthys cataractae ), slimy sculpin ( Cottus cognatus ) and trout‐perch ( Percopsis omiscomaycus ). Annual growth, estimated from otolith back‐calculations, was higher for each of the species in the regulated river relative to the naturally flowing river but did not differ between hydropeaking regimes. Condition was assessed using weight–length relationships and differed between rivers for each species, and between hydropeaking regimes for longnose dace and slimy sculpin. Survival of longnose dace and slimy sculpin was lower in the regulated river relative to the naturally flowing river, but comparable between rivers for trout‐perch. Annual growth was significantly related to mean summer discharge in the regulated river and to mean summer water temperature in the naturally flowing river for each species, and significantly different slopes among species indicate species‐specific responses to discharge and temperature alterations. This study demonstrates different biological responses among fish species within rivers to regulation in general, as well as to specific hydropeaking regimes. Future studies should focus on multiple species and multiple indicators of fish health to more fully characterize the impacts of river regulation on downstream fish communities. Copyright © 2016 John Wiley & Sons, Ltd.
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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".