Spatially structured interactions between lobsters and lobster fishers in a coastal habitat: fine-scale behaviour and survival estimated from acoustic telemetry
Bibliographic record
Abstract
Fishing can have profound impacts on the ecology and evolution of marine populations. Understanding population-level changes ultimately depends on knowledge about individual survival and how it varies in time and space. We used acoustic tags and a network of receivers to monitor individual behaviour and fate of European lobster (Homarus gammarus) exposed to commercial and recreational trap fisheries on the Norwegian Skagerrak coast. In August 2011, 50 male lobsters above minimum legal size were tagged and monitored before and during the lobster fishing season. We also quantified the spatial and temporal variation in fishing activity. There was no significant effect of home-range size on the probability of surviving the fishery. However, there was substantial fine-scale spatial variation in fishing activity, and lobsters with short-term home ranges positioned away from trap-dense areas had a significantly higher survival probability. Also, the overall survival probability of 16.7% suggests that fishing depletes the catchable lobster population at a high rate. The current harvesting regime may drive selection in favour of movement behaviours avoiding habitats typically targeted by fishers.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".