Potential connectivity among American lobster fisheries as a result of larval drift across the species’ range in eastern North America
Bibliographic record
Abstract
We used a biophysical model to estimate for the first time the effect of larval drift on potential connectivity among American lobster (Homarus americanus) fisheries management areas over the geographic range of the species. The model predicted drift of larvae over distances of 50–805 km (mean = 129 km), which connected many management areas and caused marked spatial heterogeneity in retention and self-seeding versus export and import of larvae by different fisheries areas. Including mortality functions in the model resulted in less drift and settlement and had complex effects on the amount, but not the incidence, of potential connectivity among fisheries. The model’s predictions received support from comparison of predicted settlement to landings 6 or 7 years later in some, but not all, parts of the model domain. Although improvements are still needed to capture larval behaviours and spatial variability in larval release and mortality across the species’ range, this information is important to lobster fisheries management because the amount and direction of connectivity among fisheries can inform cooperative management strategies to sustain interconnected fisheries.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".