Tracking Natal Dispersal in a Coastal Population of a Migratory Songbird Using Feather Stable Isotope (δ2H, δ34S) Tracers
Bibliographic record
Abstract
Adult birds tend to show high fidelity to their breeding territory or disperse over relatively short distances. Gene flow among avian populations is thus expected to occur primarily through natal dispersal. Although natal dispersal is a critical demographic process reflecting the area over which population dynamics take place, low recapture rates of birds breeding for the first time have limited our ability to reliably estimate dispersal rates and distances. Stable isotope approaches can elucidate origins of unmarked birds and so we generated year- and age-specific δ2H and δ34S feather isoscapes (ca. 180 000 km2) of coastal-breeding Ovenbirds (Seiurus aurocapilla) and used bivariate probability density functions to assign the likely natal areas of 35 males recruited as first-year breeders into a population located in northwestern New Brunswick, Canada. Most individuals (80-94% depending on the magnitude of an age correction factor used; i.e. 28-33 out of 35) were classified as residents (i.e. fledged within our study area) and estimated minimum dispersal distances of immigrants were between 40 and 240 km. Even when considering maximum dispersal distances, the likely origin of most first-year breeders was<200 km from our study area. Our method identified recruitment into our population from large geographic areas with relatively few samples whereas previous mark-recapture based methods have required orders of magnitude more individuals to describe dispersal at such geographic scales. Natal dispersal movements revealed here suggest the spatial scale over which many population processes are taking place and we suggest that conservation plans aiming to maintain populations of Ovenbirds and ecologically-similar species should consider management units within 100 or at most 200 km of target breeding populations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".