Phenotypic and genotypic population differentiation in the bivalve mollusc Arctica islandica: results from RAPD analysis
Bibliographic record
Abstract
The bivalve mollusc Arctica islandica is an important commercial species with a presumed panmictic dispersal strategy, and is widely distributed throughout much of the soft sediment benthos of the North Atlantic continental shelf.Previous studies have shown that there can be gross morphological differences between populations, which has led to the suggestion that this may be reflected in genotype.So far, only one study has examined the population genetics of this species, revealing, depending upon location, that populations are only genetically distinct at a macroscale (>1000 km), thereby supporting the assumption of panmixia.Examination of the quantitative morphological traits between 5 different populations (4 North Sea and 1 Canadian) determined that all populations could be readily identified from their unique morphologies (shapes/growth patterns) derived from 2 factors resulting from a principal components analysis.Investigation, using random amplified polymorphic DNA (RAPD) analysis, into the genetics of the populations, to indirectly assess whether the observed phenotypic differences could be related to potential differences in genotype, revealed that all populations were genetically distinct (between populations overall phi ST = 0.662) from each other even at a microscale (< 25 km) (phi ST = 0.719).However, no correlation between genetic distance, morphological distance and/or geographical distance, whatever metric was applied, could be obtained.It is concluded that although phenotypic differences can be used to distinguish between populations of A. islandica, it should not and cannot be used to infer genetic differences in the absence of further studies.What is interesting is that the results from the genetic analysis dispute the presumption that the dispersal patterns of A. islandica is in any shape or form panmictic.This has very important consequences for the management of the species.The results are discussed with reference to the possible mechanisms responsible for maintaining a high degree of genetic diversity between the populations that were studied.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".