Evaluating benthic impact of the Gulf of Maine lobster fishery using the Swept Area Seabed Impact (SASI) model
Bibliographic record
Abstract
The Magnuson–Stevens Fishery Conservation and Management Act mandates US fisheries minimize adverse effects of fishing on essential fish habitat (EFH). The Gulf of Maine (GoM) American lobster (Homarus americanus) fishery is the most valuable US fishery and can deploy more than three million traps annually. To date, the impact of this fishery on benthic EFH has not been addressed quantitatively. To evaluate the impact of the GoM lobster fishery on EFH, we incorporated lobster fishing effort into a model linking habitat susceptibility and recovery to area impacted by fishing gear: the Swept Area Seabed Impact model. Impact to EFH was localized along the coast and highest along midcoast Maine. Upwards of 13% of the benthos is in the process of recovery, but between 99.92% and 99.96% of initially affected habitat fully recovers. These estimates suggest that lobster fishing negligibly contributes to accumulation of EFH damage in the GoM due to the expansive area fished and the small footprint of each trap. Identifying areas of persistent impact is crucial in developing effective fisheries management for critical marine habitats.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".