Human disturbance causes the formation of a hybrid swarm between two naturally sympatric fish species
Bibliographic record
Abstract
Most evidence for hybrid swarm formation stemming from anthropogenic habitat disturbance comes from the breakdown of reproductive isolation between incipient species, or introgression between allopatric species following secondary contact. Human impacts on hybridization between divergent species that naturally occur in sympatry have received considerably less attention. Theory predicts that reinforcement should act to preserve reproductive isolation under such circumstances, potentially making reproductive barriers resistant to human habitat alteration. Using 15 microsatellites, we examined hybridization between sympatric populations of alewife (Alosa pseudoharengus) and blueback herring (A. aestivalis) to test whether the frequency of hybridization and pattern of introgression have been impacted by the construction of a dam that isolated formerly anadromous populations of both species in a landlocked freshwater reservoir. The frequency of hybridization and pattern of introgression differed markedly between anadromous and landlocked populations. The rangewide frequency of hybridization among anadromous populations was generally 0-8%, whereas all landlocked individuals were hybrids. Although neutral introgression was observed among anadromous hybrids, directional introgression leading to increased prevalence of alewife genotypes was detected among landlocked hybrids. We demonstrate that habitat alteration can lead to hybrid swarm formation between divergent species that naturally occur sympatrically, and provide empirical evidence that reinforcement does not always sustain reproductive isolation under such circumstances.
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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 | 0.000 |
| 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) | 0.001 | 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".