The American Kestrel (<i>Falco sparverius</i>) Genoscape: Implications for Monitoring, Management, and Subspecies Boundaries
Bibliographic record
Abstract
Identifying population genetic structure is useful for inferring evolutionary process and comparing the resulting structure with subspecies boundaries can aid in species management. The American Kestrel (Falco sparverius) is a widespread and highly diverse species with 17 total subspecies, only 2 of which are found north of U.S./Mexico border (F. s. paulus is restricted to southeastern United States, while F. s. sparverius breeds across the remainder of the U.S. and Canadian distribution). In many parts of their U.S. and Canadian range, American Kestrels have been declining, but it has been difficult to interpret demographic trends without a clearer understanding of gene flow among populations. Here we sequence the first American Kestrel genome and scan the genome of 197 individuals from 12 sampling locations across the United States and Canada in order to identify population structure. To validate signatures of population structure and fill in sampling gaps across the U.S. and Canadian range, we screened 192 outlier loci in an additional 376 samples from 34 sampling locations. Overall, our analyses support the existence of 5 genetically distinct populations of American Kestrels—eastern, western, Texas, Florida, and Alaska. Interestingly, we found that while our genome-wide genetic data support the existence of previously described subspecies boundaries in the United States and Canada, genetic differences across the sampled range correlate more with putative migratory phenotypes (resident, long-distance, and short-distance migrants) rather than a priori described subspecies boundaries per se. Based on our results, we suggest the resulting 5 genetically distinct populations serve as the foundation for American Kestrel conservation and management in the face of future threats.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".