Genetic population structure and contemporary dispersal patterns of a recent European invader, the Chinese mitten crab, <i>Eriocheir sinensis</i>
Bibliographic record
Abstract
Genetic studies of recently established populations are challenging because the assumption of equilibrium underlying many analyses is likely to be violated. Using microsatellites, we investigated determinants of genetic structure and migration among invasive European-Chinese mitten crab populations, applying a combination of traditional population genetic analyses and nonequilibrium Bayesian methods. Consistent with their recent history, invasive populations showed much lower levels of genetic diversity than a native Chinese population, indicative of recent bottlenecks. Population differentiation was generally low but significant and especially pronounced among recently established populations. Significant differentiation among cohorts from the same geographical location (River Thames) suggests the low effective population size and associated strong genetic drift that would be anticipated from a very recent colonization. An isolation-by-distance pattern appears to be driven by an underlying correlation between geographical distance and population age, suggesting that cumulative homogenizing gene flow reduces founder bottleneck-associated genetic differentiation between longer-established populations. This hypothesis was supported by a coalescent analysis, which supported a drift + gene flow model as more likely than a model excluding gene flow. Furthermore, admixture analysis identified several recent migrants between the UK and Continental European population clusters. Admixture proportions were significantly predicted by the volume of shipping between sites, indicating that human-mediated transport remains a significant factor for dispersal of mitten crabs after the initial establishment of populations. Our study highlights the value of nonequilibrium methods for the study of invasive species, and also the importance of evaluating nonequilibrium explanations for isolation by distance patterns.
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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 | 0.001 | 0.001 |
| 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".