Establishing elemental turnover in exercising birds using a wind tunnel: implications for stable isotope tracking of migrants
Bibliographic record
Abstract
Stable isotope measurements are being used increasingly to track migratory wildlife, especially birds. This approach relies on the assumption that tissue isotopic values represent a known period of dietary integration and that such a period is long enough to provide information on previous geographic origin. To date, such measurements have been obtained by switching isotopic composition of diets of sedentary captive individuals. The assumption has been that such measurements of elemental turnover likely represent minimal estimates, since wild migratory birds undergo increased metabolism and exercise during migratory flights. We tested this assumption using isotopic manipulation of diet on captive Rosy Starling ( Sturnus roseus (L., 1758)) conditioned for flight in a wind tunnel. We used four control (no exercise) and four experimental (exercised) birds. For both groups, diet was switched from primarily a C-3 content to a C-4 content and blood samples were taken throughout our experiment until day 53. Contrary to expectation, δ13C values in blood did not follow an exponential model of growth to a plateau under the new diet. Instead, the best fit was a linear increase in δ13C value of the blood cellular fraction following the switch (day 15) until day 50, after which no further isotopic change was noted. We found no difference between experimental and control groups in the rate of carbon turnover. Our results support the contention that metabolic costs of migratory flight in conditioned birds may not result in increases in carbon elemental turnover in tissues and that previous estimates of tissue isotopic turnover based on captive, nonexercised birds may be applied to wild birds.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".