Complex genetic patterns in closely related colonizing invasive species
Bibliographic record
Abstract
Anthropogenic activities frequently result in both rapidly changing environments and translocation of species from their native ranges (i.e., biological invasions). Empirical studies suggest that many factors associated with these changes can lead to complex genetic patterns, particularly among invasive populations. However, genetic complexities and factors responsible for them remain uncharacterized in many cases. Here, we explore these issues in the vase tunicate Ciona intestinalis (Ascidiacea: Enterogona: Cionidae), a model species complex, of which spA and spB are rapidly spreading worldwide. We intensively sampled 26 sites (N = 873) from both coasts of North America, and performed phylogenetic and population genetics analyses based on one mitochondrial fragment (cytochrome c oxidase subunit 3-NADH dehydrogenase subunit I, COX3-ND1) and eight nuclear microsatellites. Our analyses revealed extremely complex genetic patterns in both species on both coasts. We detected a contrasting pattern based on the mitochondrial marker: two major genetic groups in C. intestinalis spA on the west coast versus no significant geographic structure in C. intestinalis spB on the east coast. For both species, geo-graphically distant populations often showed high microsatellite-based genetic affinities whereas neighboring ones often did not. In addition, mitochondrial and nuclear markers provided largely inconsistent genetic patterns. Multiple factors, including random genetic drift associated with demographic changes, rapid selection due to strong local adaptation, and varying propensity for human-mediated propagule dispersal could be responsible for the observed genetic complexities.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".