High site fidelity does not equate to population structure for common goldeneye and Barrow’s goldeneye in North America.
Bibliographic record
Abstract
Delineation of population structure provides valuable information for conservation and management of species, as levels of demographic and genetic connectivity not only affect population dynamics but also have important implications for adaptability and resiliency of populations and species. Here, we measure population genetic structure and connectivity across the respective ranges of two sister species of Goldeneye, Barrow’s Goldeneye (Bucephala islandica) and Common Goldeneye (B. clangula). We use two different marker types: 7 nuclear microsatellite loci assayed across 229 samples and 3,678 double digest Restriction-site Associated DNA Sequencing (ddRAD-seq) loci assayed across 61 samples. First, both datasets failed to uncover genetic structure within Common or Barrow’s Goldeneye, including between North American and European samples of Common Goldeneye. These results are in contrast with previous mitochondrial DNA, band recovery, and telemetry data which suggests that goldeneyes are structured across their range. We posit that the discordance between autosomal genetic markers and other data types suggests that males, possibly subadult males, may be maintaining genetic connectivity across each species’ respective ranges. Next, although inter-specific brood parasitism was expected to cause some level of gene flow, we only identified a single F1 hybrid with no further evidence of contemporary or historical gene flow. Despite ddRAD-seq demographic analyses which recovered an optimum evolutionary model of split with migration (i.e., secondary contact), estimates of gene flow were <<1 migrant per generation in both directions. Together, we conclude that either strong ecological barriers or assortative mating are likely playing a role in preventing further backcrossing. Finally, demographic analyses estimated a relatively deep divergence time between Barrow’s Goldeneye and Common Goldeneye of ~1.6 million years before present and that the genomes of both species have been under similar evolutionary constraints.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".