Identifying the African Wintering Grounds of Hybrid Flycatchers Using a Multi–Isotope (δ2H, δ13C, δ15N) Assignment Approach
Bibliographic record
Abstract
Migratory routes and wintering grounds can have important fitness consequences, which can lead to divergent selection on populations or taxa differing in their migratory itinerary. Collared (Ficedula albicollis) and pied (F. hypoleuca) flycatchers breeding in Europe and wintering in different sub-Saharan regions have distinct migratory routes on the eastern and western sides of the Sahara desert, respectively. In an earlier paper, we showed that hybrids of the two species did not incur reduced winter survival, which would be expected if their migration strategy had been a mix of the parent species' strategies potentially resulting in an intermediate route crossing the Sahara desert to different wintering grounds. Previously, we compared isotope ratios and found no significant difference in stable-nitrogen isotope ratios (δ15N) in winter-grown feathers between the parental species and hybrids, but stable-carbon isotope ratios (δ13C) in hybrids significantly clustered only with those of pied flycatchers. We followed up on these findings and additionally analyzed the same feathers for stable-hydrogen isotope ratios (δ2H) and conducted spatially explicit multi-isotope assignment analyses. The assignment results overlapped with presumed wintering ranges of the two species, highlighting the efficacy of the method. In contrast to earlier findings, hybrids clustered with both parental species, though most strongly with pied flycatcher.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".