Genetic structure in the nonbreeding range of<i>rufa</i>Red Knots suggests distinct Arctic breeding populations
Bibliographic record
Abstract
Abstract An understanding of the migratory connectivity between breeding and nonbreeding areas is fundamental to the management of long-distance migrants under pressure from habitat change along their flyways. Here we describe evidence for genetic structure within the nonbreeding range of the endangered Arctic-Canadian rufa subspecies of Red Knots (Calidris canutus). Using blood and tissue samples from the major nonbreeding regions in Argentina (Tierra del Fuego and Río Negro), northern Brazil (Maranhão), and southeastern USA (Florida), we estimated genetic structure in 514 amplified fragment length polymorphism (AFLP) loci, applying cluster assignment analyses in DAPC, assignPOP, and STRUCTURE. Using a priori location information, individuals could be correctly re-assigned to their nonbreeding regions, which validated that the assignment accuracy of the data was sufficient. Without using a priori location information, we detected 3–5 genotype clusters, and posterior assignment probabilities of samples to these genotype clusters varied among the three regions. Lastly a chi-square test confirmed that allele frequencies varied significantly among nonbreeding regions, rejecting the hypothesis that samples were drawn from a single gene pool. Our findings hint at undescribed structure within the Red Knot rufa breeding range in the Canadian Arctic and indicate that each rufa nonbreeding area in this study hosts a different subsample of these breeding populations. The observation that nonbreeding sites of rufa Red Knots contain different genetic pools argues for separate conservation management of these sites.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".