Data from: Human-mediated and natural dispersal of an invasive fish in the eastern Great Lakes
Bibliographic record
Abstract
The globally invasive Round Goby (Neogobius melanostomus) was introduced to the Great Lakes around 1990, spreading widely and becoming the dominant benthic fish in many areas. The speed and scope of this invasion is remarkable and calls into question conventional secondary spread models and scenarios. We utilized 9 microsatellites to identify large-scale genetic structure in Round Goby populations in the eastern Great Lakes, and assessed the role of colonization versus secondary transport and dispersal in developing this structure. We identified three clusters, corresponding with Lake Huron, eastern Lake Erie, and western Lake Erie plus eastern Lake Ontario, along with three highly-divergent populations. Bottleneck analysis identified founder effects in two divergent populations. Regression analyses of isolation-by-distance and allelic richness vs. distance from the initial invasion site were consistent with limited migration. However, some populations in eastern Lake Erie and Lake Ontario showed anomalously low genetic distance from the original site of colonization, consistent with secondary transport of large numbers of individuals via ballast water. Genetic structure of Round Goby in the Great Lakes principally resulted from long-distance secondary transport via ballast water with additional movement of individual via bait buckets and natural dispersal. The success of Round Gobies represents an interesting model for colonization characterization; however, those same attributes present significant challenges for conservation and fisheries management. Current management likely prevents many new species from arriving in the Great Lakes, but fails to address the transport of species within the lakes after they arrive; an issue of clear and pressing importance.
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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 | 0.000 | 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".