Water level regulation affects niche use of a lake top predator, Arctic charr (<i>Salvelinus alpinus</i>)
Bibliographic record
Abstract
Abstract Water level fluctuations are expected to deteriorate the littoral zone in heavily regulated hydropower reservoirs, but there is limited empirical evidence of how food webs and fish populations are affected. We contrasted the size, growth, condition, niche use (i.e., habitat and diet), and parasite infection of allopatric Arctic charr ( Salvelinus alpinus ) populations in two neighboring and comparable Norwegian mountain lakes. We hypothesized that the presumed abiotic and biotic deterioration of the littoral zone would lead to reduced abundance and growth as well as to increased pelagic niche use and reduced niche width of the charr in the heavily regulated Govdajavri (maximum regulation amplitude 24 m) as compared with the unregulated Cazajavri. Our stable isotope and parasite data showed that charr had a slightly narrower and more pelagic feeding niche in the regulated than in the unregulated lake. The relative abundance of charr was lower in the regulated lake, but no between‐lake differences were observed in charr condition, and the charr grew slightly faster in the regulated than in the unregulated lake. Our study suggests that impaired littoral production can alter food webs in alpine hydropower reservoirs and induce a pelagic niche shift by top predators. These results argue for further investigations of hydropower impacts on lake food webs along with other factors that influence the abundance and niche use of fish, such as intraspecific interactions and compensatory growth, which may partly mask the potential impacts.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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; both teacher heads agree on what is shown here.
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".