Natural hybrids in Atlantic eels (<i>Anguilla anguilla</i>,<i>A. rostrata</i>): evidence for successful reproduction and fluctuating abundance in space and time
Bibliographic record
Abstract
The outcome of natural hybridization is highly variable and depends on the nonexclusive effects of both pre- and post-mating reproductive barriers. The objective of this study was to address three specific questions regarding the dynamics of hybridization between the American and European eels (Anguilla rostrata and Anguilla anguilla). Using 373 AFLP loci, 1127 eels were genotyped, representing different life stages from both continents, as well as multiple Icelandic locations. We first evaluated the extent of hybridization and tested for the occurrence of hybrids beyond the first generation. Second, we tested whether hybrids were randomly distributed across continents and among Icelandic sampling sites. Third, we tested for a difference in the proportion of hybrids between glass eel and yellow eel stages in Iceland. Our results provided evidence for (i) an overall hybrid proportion of 15.5% in Iceland, with values ranging from 6.7% to 100% depending on life stages and locations; (ii) the existence of hybrids beyond the first generation; (iii) a nonrandom geographic distribution of hybrids in the North Atlantic; and (iv) a higher proportion of first and later generation hybrids in yellow eels compared to glass eels, as well as a significant latitudinal gradient in the proportion of hybrids in Icelandic freshwater. We propose that the combined effect of both differential survival of hybrids and variation in hybridization rate through time best explain these patterns. We discuss the possibility that climate change, which is impacting many environmental features in the North Atlantic, may have a determinant effect on the outcome of natural hybridization in Atlantic eels.
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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 | 0.001 | 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".