Hybridization between closely related songbirds is related to human habitat disturbance
Bibliographic record
Abstract
Human habitat disturbances can promote hybridization between closely related, but typically reproductively isolated, species. We explored whether human habitat disturbances are related to hybridization between two closely related songbirds, black-capped and mountain chickadees, using both genomic and citizen science data sets. First, we genotyped 409 individuals from across both species' ranges using reduced-representation genome sequencing and compared measures of genetic admixture to a composite measure of human landscape disturbance. Then, using eBird observations, we compared human landscape disturbance values for sites where phenotypically diagnosed hybrids were observed to locations where either parental species was observed to determine whether hybrid chickadees are reported in more disturbed areas. We found that hybridization between black-capped and mountain chickadees positively correlates with human habitat disturbances. From genomic data, we found that (1) hybrid index (HI) significantly increased with habitat disturbance, (2) more hybrids were sampled in disturbed habitats, (3) mean HIs were higher in disturbed habitats versus wild habitats, and (4) hybrids were detected in habitats with significantly higher disturbance values than parentals. Using eBird data, we found that both hybrid and black-capped chickadees were significantly more disturbance-associated than mountain chickadees. Surprisingly, we found that nearly every black-capped chickadee we sampled contained some proportion of hybrid ancestry, while we detected very few mountain chickadee backcrosses. Our results highlight that hybridization between black-capped and mountain chickadees is widespread, but initial hybridization is rare (few F1s were detected). We conclude that human habitat disturbances can erode pre-zygotic reproductive barriers between chickadees and that post-zygotic isolation is incomplete. Understanding what becomes of recently hybridizing species following large-scale habitat disturbances is a new, but pressing, consideration for successfully preserving genetic biodiversity in a rapidly changing world.
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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".