Lack of genetic divergence in capelin (<i>Mallotus</i><i>villosus</i>) spawning at beach versus subtidal habitats in coastal embayments of Newfoundland
Bibliographic record
Abstract
Capelin (Mallotus villosus (Müller, 1776)), a focal forage fish in the north Atlantic, spawn on both beach and demersal (deep-water) sites throughout their circumpolar distribution. Although these habitats rarely occur in close proximity, demersal spawning sites within 4 km of beach spawning sites (subtidal) have recently been discovered in two coastal embayments in Newfoundland, Canada. The physical environment differs considerably between beach and subtidal spawning sites, creating the potential for local adaptation and genetic divergence of capelin from the two habitats, but this has never been investigated on a fine spatial scale. We use eight microsatellite loci to test for genetic divergence between capelin spawning at beach and subtidal sites within these two coastal regions in Newfoundland. We found no genetic differentiation between fish spawning at beach and subtidal sites or between the two regions. The results from this fine-scale study are in agreement with the lack of habitat-based structure reported in other studies examining beach and demersal sites separated by a larger geographic area. We suggest that instead of showing site fidelity and local adaptation, the facultative use of alternate spawning habitats may be a more successful strategy in an unpredictable environment.
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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 | 0.001 | 0.001 |
| 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".