Elevational differences in estimated fattening rates suggest that high-elevation sites are high-quality habitats for fall migrants
Bibliographic record
Abstract
ABSTRACT. Many migrant songbird species use high-elevation habitats for stopovers in fall throughout North America, but whether these are good migration habitats as indicated by high fueling rates or other measures has not been previously quantified. At high-quality stopover sites, birds can refuel while maintaining their optimal or preferred migration schedules. We used plasma metabolite analysis to estimate fueling rates of four songbird species during the fall migration period over 3 years at two high-elevation (1,200 m above sea level) and two low-elevation (<25 m above sea level) sites in southwestern British Columbia. For three species with more frugivorous diets during fall—the Fox Sparrow (Passerella iliaca), Golden-crowned Sparrow (Zonotrichia atricapilla), and Hermit Thrush (Catharus guttatus)—estimated fattening rates (defined as residual plasma triglyceride levels) were 37–65% higher at high-elevation sites than at low-elevation sites. By contrast, the largely insectivorous and smaller-bodied Orange-crowned Warbler (Oreothlypis celata) had higher estimated fattening rates at low-elevation sites. We found no elevational differences in plasma beta-hydroxybutyrate or glycerol levels except in Hermit Thrushes, which had lower glycerol levels at high elevation. Estimated fattening rates did not differ among the two sparrows and the Hermit Thrush at high-elevation sites, and all three had higher fattening rates than Orange-crowned Warblers. Our data showing strong elevational differences in residual plasma triglyceride levels support the hypothesis that high elevations can be high-quality stopover habitats and, thus, should be considered for protection in songbird management and conservation plans.
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 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 | 0.000 | 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) | 0.002 | 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".