Using stable-hydrogen isotopes to reveal immigration in an Arctic-breeding songbird population
Bibliographic record
Abstract
Abstract Background Knowledge of immigration and emigration rates is crucial for understanding of population dynamics, yet little is known about these vital rates, especially for arctic songbirds. We estimated immigration in an Arctic population of northern wheatears on Baffin Island, Canada, by the use of stable hydrogen isotopes in tail feathers (δ2HK). We assumed that δ2HK values of juvenile (hatch-year) feathers grown at the breeding grounds were representative of the local population, while those of breeding adults were indicative of where they grew their feathers during their post-breeding molt the previous year. The extent to which adult isotope values differ from those of juveniles provides an estimate of the minimum level of immigration into the breeding population. Results Mean δ2HK values did not differ in juvenile birds between years. Breeding adult birds did not differ significantly in mean δ2HK values compared to juveniles but did differ in their respective standard deviations, reflecting a significantly wider range of isotopic signatures in adults than in juveniles. Thirty-eight percent of the δ2HK values in adults were greater ± 2 SD of the mean δ2HK values of juveniles, suggesting that at least 38 % of the breeding adults were of non-local origin, thus immigrants from elsewhere. Conclusions Although the use of stable isotopes has limitations, the use of stable-hydrogen isotopic markers has the potential to contribute valuable information towards understanding immigration rates in bird populations. In our study, hydrogen isotope measurements of the feathers of northern wheatears indicated a high rate of immigration into the breeding population, which is consistent with low return rates of banded breeding adults as well as implying high emigration rates of local breeders.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".