DNA Barcode Detects High Genetic Structure within Neotropical Bird Species
Bibliographic record
Abstract
BACKGROUND: Towards lower latitudes the number of recognized species is not only higher, but also phylogeographic subdivision within species is more pronounced. Moreover, new genetically isolated populations are often described in recent phylogenies of Neotropical birds suggesting that the number of species in the region is underestimated. Previous COI barcoding of Argentinean bird species showed more complex patterns of regional divergence in the Neotropical than in the North American avifauna. METHODS AND FINDINGS: Here we analyzed 1,431 samples from 561 different species to extend the Neotropical bird barcode survey to lower latitudes, and detected even higher geographic structure within species than reported previously. About 93% (520) of the species were identified correctly from their DNA barcodes. The remaining 41 species were not monophyletic in their COI sequences because they shared barcode sequences with closely related species (N = 21) or contained very divergent clusters suggestive of putative new species embedded within the gene tree (N = 20). Deep intraspecific divergences overlapping with among-species differences were detected in 48 species, often with samples from large geographic areas and several including multiple subspecies. This strong population genetic structure often coincided with breaks between different ecoregions or areas of endemism. CONCLUSIONS: The taxonomic uncertainty associated with the high incidence of non-monophyletic species and discovery of putative species obscures studies of historical patterns of species diversification in the Neotropical region. We showed that COI barcodes are a valuable tool to indicate which taxa would benefit from more extensive taxonomic revisions with multilocus approaches. Moreover, our results support hypotheses that the megadiversity of birds in the region is associated with multiple geographic processes starting well before the Quaternary and extending to more recent geological periods.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".