Movement of American lobsters Homarus americanus and rock crabs Cancer irroratus around mussel farms in Malpeque Bay, Prince Edward Island, Canada
Bibliographic record
Abstract
A worldwide increase in aquaculture has focussed attention on the interactions between aquaculture activities and the surrounding habitats and ecosystems. In Atlantic Canada, mussel aquaculture occurs alongside static-gear fisheries for American lobster Homarus americanus and rock crab Cancer irroratus. Current knowledge gaps surround how lobsters and crabs utilise aquaculture sites and the potential impacts of this use on wild fisheries. During 2015 and 2016, at 3 mussel farms within Malpeque Bay, Prince Edward Island, Canada, a combination of diver surveys and acoustic telemetry positional arrays were used to investigate differences in the abundance of lobsters between farms and adjacent reference sites, the number and duration of lobster visits to a mussel farm, and the fine-scale movements of lobsters and crabs inside and outside of mussel farms. Although lobster abundance at mussel farms varied from June-September, abundance only differed between the farms and their associated reference sites in June. Disturbance due to handling may have led some lobsters in the acoustic telemetry study to leave the mussel farm after tagging; however, those that remained crossed the farm boundary frequently, and there was little evidence that the farm was a refuge for lobsters. Both lobsters and crabs appeared to move at significantly slower speeds inside the mussel farm, suggesting that both species used the mussel farms for foraging and/or sheltering; this was particularly evident for the rock crab. The results of this multi-approach field study are informative for spatial planning and provide important insight into how commercially and ecologically important species use aquaculture facilities.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".