Assigning birds to geographic origin using feather hydrogen isotope ratios (δ<sup>2</sup>H): importance of year, age, and habitat
Bibliographic record
Abstract
In North America, gradients in the ratio of stable hydrogen isotopes in amount-weighted, growing-season mean precipitation (2H:1H; depicted as δ2Hp) form a largely latitude-sensitive isoscape that can be used to estimate the geographical origin of animals. Feathers are metabolically inert following growth and δ2Hfvalues retain information on geographical origins. However, there are important assumptions underlying this approach that can only be tested using birds of known origin. Here, we investigated sources of variation in δ2Hfmeasurements from Ovenbirds ( Seiurus aurocapilla (L., 1766)) associated with year, age class, feather type, season, and habitat type in New Brunswick, Canada. The observed δ2Hfgenerally followed that predicted from the Global Network of Isotopes in Precipitation database. However, we found a strong year × age interaction on δ2Hf. Season, habitat type, and feather type explained only a small portion of the overall variation in δ2Hf. These results show the advantages of using annual δ2Hpisoscapes and age-specific corrections when converting δ2Hpto δ2Hf. We submit that the interaction effect can be modeled by accounting for interannual variation in the amount of precipitation during the breeding season. These procedures will allow for more precise estimates of the geographical origin of individual birds, especially for studies conducted near oceanic coasts, which are subject to significant annual variations in growing season δ2Hp.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".