Population structure, patterns of natal dispersal and demographic history in a declining aerial insectivore, the purple martin <i>Progne subis</i>
Bibliographic record
Abstract
Genetic variation is a fundamental component of biodiversity, and studying population structure, gene flow and demographic history can help guide conservation strategies for many species. Like other aerial insectivores, the purple martin Progne subis is in decline, and yet their genetic background remains largely unknown. To address this knowledge gap, we assessed population structure in the nominate eastern subspecies ( P. s. subis ) with relation to natal dispersal and examined historical genetic patterns in all three subspecies ( P. s. subis , P. s. arboricola , P. s. hesperia ) across their North American breeding range by estimating effective population sizes over time. We used next‐generation sequencing strategies for genomic analyses, integrating whole‐genome resequencing data with continent‐wide band encounter records to examine natal dispersal. We documented population structure across P. s. subis , with the highest differentiation between the northern (Alberta) and more southern colonies and following patterns of isolation‐by‐distance. Consistent with spatial patterns of genetic differentiation, we also found greater longitudinal than latitudinal natal dispersal distances, signifying potential latitudinal constraints on gene flow. Earlier contractions in effective population sizes in the western P. s. arboricola and P. s. hesperia compared to the eastern P. s. subis subspecies suggest these subspecies originated from two different glacial refugia. Together, these findings support latitudinal distinction in P. s. subis , and elucidate the origin of subspecies differentiation, highlighting the importance of conserving populations across the range to maximize genetic diversity and adaptive potential in the purple martin.
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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 | 0.000 | 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".