Temporal genetic heterogeneity within a developing mussel (<i>Mytilus trossulus</i> and <i>M. edulis</i>) assemblage
Bibliographic record
Abstract
The genetic structure of mussel recruits on a rocky shore in Nova Scotia was measured after a rare ice-scouring event which completely removed the intertidal community. Genotype frequencies were measured at three enzyme loci, phosphoglucose mutase (PGM), aminopeptidase-I (product of the leucine aminopeptidase (LAP) locus), and mannose phosphate isomerase (MPI), using cellulose acetate gel electrophoresis. The developing mussel assemblage was a mixture of Mytilus trossulus, M. edulis and their hybrids, with a greater proportion of the former species. Mussel settlers were collected for two years to examine whether genetic heterogeneity existed within and between cohorts of settlers. Settlement of mussels of both species began in April or May and continued into January. Temporal genetic heterogeneity was observed among groups of settlers, resulting from both variations in the relative proportions of the two species and from genetic heterogeneity within M. trossulus. Allele frequencies of mussel cohorts were followed from settlement to ten months post-settlement to investigate the possibility of species-specific selection and of genotype-specific selection within M. trossulus. Temporal genetic heterogeneity primarily was attributed to changes in the proportions of each species, indicating that post-settlement processes were species-specific. Early post-settlement changes were inconsistent, but later changes were clearly directional, resulting in decreased proportions of M. edulis in larger mussels in both years. There was some evidence of genotype-specific post-settlement mortality within M. trossulus, particularly during the early post-settlement period. Our results indicate that temporally variable settlement patterns and post-settlement selection interacted to produce temporal genetic heterogeneity in this mussel assemblage.
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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) | 0.000 | 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".