Physiological assessment of the effects of changing water levels associated with reservoir management on fattening rates of neotropical migrants at a stopover site
Bibliographic record
Abstract
Riparian habitat makes up a small fraction of the landscape but provides important stopover habitat for migratory birds. Hydroelectric dam operations cause fluctuations in water levels that can change the amount or quality of riparian habitat, which in turn might affect potential fattening rates of migrant birds. Here we used plasma metabolite analysis to estimate variation in fattening rate in relationship to variable water levels associated with reservoir management in four species of neotropical migratory songbirds using riparian habitat at a dam-impacted stopover site in Revelstoke, British Columbia, Canada. Residual plasma triglyceride, our measure of estimated fattening rate, varied systematically with time of day and Julian date and varied consistently among species, but did not vary with age or sex. Controlling for potentially confounding variables, we found no inter-annual variation in estimated fattening rate, even though there were marked differences in water levels among years. Likewise, there was no relationship between daily variation in water levels and estimated fattening rate. Data on feather isotopes (δD), indicative of migratory origin, did not add explanatory power to our models. There was inter-annual variation in plasma glycerol and β-hydroxybutyrate levels and significant, though weak, relationships between these metabolites and water level (higher metabolite levels when drier) that might indicate effects on 'body condition' independent of fattening rate. Our study suggests that, at present, although hydroelectric dam operations influence water levels in the Arrows Lake Reservoir and adjacent riparian habitats, this does not significantly impact fattening rates of migratory passerines using these habitats.
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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".