Data from: Genomic evidence of hybridization between two independent invasions of European green crab (Carcinus maenas) in the Northwest Atlantic
Bibliographic record
Abstract
Invasive species have been associated with significant negative impacts in their introduced range often outcompeting native species, yet the long-term evolutionary dynamics of biological invasions are not well understood. Hybridization, either among waves of invasion or between native and introduced populations, could alter the ecological and evolutionary impacts of invasions yet has rarely been studied in marine invasive species. The European green crab (Carcinus maenas) invaded eastern North America twice from northern and southern locations in its native range. Here we examine the frequency of hybridization among these two distinct invasions at locations from New Jersey, USA to Newfoundland, Canada using restriction-site associated DNA sequencing (RAD-seq), microsatellite loci, and COI mtDNA sequences. We used Bayesian clustering and hybrid assignment analyses to investigate hybridization between the northern and southern populations. Of the samples analyzed, six locations contained at least one hybrid individual, while two locations were characterized by extensive hybridization, with 95% of individuals collected from Placentia Bay, Newfoundland being hybrids (mostly F2), and 90% of individuals from Kejimkujik, Nova Scotia being classified as hybrids, mostly backcrosses to the northern ecotype. The presence of both F2 hybrids and backcrossed individuals suggests that these hybrids are viable and introgression is occurring between invasions. Our results provide insight into the demographic and evolutionary consequences of hybridization between independent invasions, and will inform the management of green crabs in eastern North America.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".