Genetic consequences of breaking migratory traditions in barnacle geese <i>Branta leucopsis</i>
Bibliographic record
Abstract
Cultural transmission of migratory traditions enables species to deal with their environment based on experiences from earlier generations. Also, it allows a more adequate and rapid response to rapidly changing environments. When individuals break with their migratory traditions, new population structures can emerge that may affect gene flow. Recently, the migratory traditions of the Barnacle Goose Branta leucopsis changed, and new populations differing in migratory distance emerged. Here, we investigate the population genetic structure of the Barnacle Goose to evaluate the consequences of altered migratory traditions. We used a set of 358 single nucleotide polymorphism (SNP) markers to genotype 418 individuals from breeding populations in Greenland, Spitsbergen, Russia, Sweden and the Netherlands, the latter two being newly emerged populations. We used discriminant analysis of principal components, FST , linkage disequilibrium and a comparison of geneflow models using migrate-n to show that there is significant population structure, but that relatively many pairs of SNPs are in linkage disequilibrium, suggesting recent admixture between these populations. Despite the assumed traditions of migration within populations, we also show that genetic exchange occurs between all populations. The newly established nonmigratory population in the Netherlands is characterized by high emigration into other populations, which suggests more exploratory behaviour, possibly as a result of shortened parental care. These results suggest that migratory traditions in populations are subject to change in geese and that such changes have population genetic consequences. We argue that the emergence of nonmigration probably resulted from developmental plasticity.
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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 | 0.000 | 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".