Genomewide evidence of environmentally mediated secondary contact of European green crab (<i>Carcinus maenas</i>) lineages in eastern North America
Bibliographic record
Abstract
Abstract Genetic‐environment associations are increasingly revealed through population genomic data and can occur through a number of processes, including secondary contact, divergent natural selection, or isolation by distance. Here, we investigate the influence of the environment, including seasonal temperature and salinity, on the population structure of the invasive European green crab ( Carcinus maenas ) in eastern North America. Green crab populations in eastern North America are associated with two independent invasions, previously shown to consist of distinct northern and southern ecotypes, with a contact zone in southern Nova Scotia, Canada. Using a RAD ‐seq panel of 9,137 genomewide SNP s, we detected 41 SNP s (0.49%) whose allele frequencies were highly correlated with environmental data. A principal components analysis of 25 environmental variables differentiated populations into northern, southern, and admixed sites in concordance with the observed genomic spatial structure. Furthermore, a spatial principal components analysis conducted on genomic and geographic data revealed a high degree of global structure ( p < .0001) partitioning a northern and southern ecotype. Redundancy and partial redundancy analyses revealed that among the environmental variables tested, winter sea surface temperature had the strongest association with spatial structuring, suggesting that it is an important factor defining range and expansion limits of each ecotype. Understanding environmental thresholds associated with intraspecific diversity will facilitate the ability to manage current and predict future distributions of this aquatic invasive species.
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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) | 0.001 | 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".