Genetic structure and phylogeography of a European flagship species, the white‐tailed sea eagle <i>Haliaeetus albicilla</i>
Bibliographic record
Abstract
We analysed 120 white‐tailed sea eagles Haliaeetus albicilla from eastern (Poland and Estonia) and southeastern (Serbian Danube population) Europe for genetic variability and structuring at the mitochondrial control region and seven nuclear microsatellite loci. We combined this new dataset with sequence and genotype data from previous analyses covering Greenland and Eurasia (total sample sizes of 420 and 186 individuals for mtDNA and microsatellites, respectively) to address the following questions: 1) does the large eastern population in Europe add significantly to the species‘ overall genetic diversity? 2) Do the new sequence data match the clinal distribution pattern (west to east) of the two major mtDNA lineages? 3) Does the preliminary hypothesis of two nuclear genetic clusters recently found in this species hold for the whole of Europe, and do these clusters show a geographic pattern? Our results confirmed Europe as a stronghold of genetic diversity in white‐tailed sea eagles, and the east of the continent contributed disproportionately to this, the reason being the admixture of eagles with different genetic background. As hypothesised, both mitochondrial lineages were recovered also in eastern Europe, but the globally more eastern lineage was dominant. The presence of two microsatellite clusters was also confirmed, and these groups, too, show a non‐random geographic distribution, with, except for Poland, a high proportion of ‘eastern‐type’ eagles in the populations of east–central and eastern Europe.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".