Spatial overlap, proximity, and interaction between lobsters revealed using acoustic telemetry
Bibliographic record
Abstract
The cryptic nature of Homarus lobsters has restricted past behavioural studies to aquaria, mesocosms, or shallow coves. As such, spatial overlap and interactions between free-ranging Homarus lobsters have received little attention. However, it is clear that dominance behaviours directly affect their probability of capture, negatively affecting catch and complicating population monitoring. This study describes lobster behaviour at a scale that could not be achieved in aquaria or mesocosms. Home-range overlap and contact rates among free-ranging, acoustically tagged H. gammarus (n = 44) were assessed at multiple spatial scales. Data were analysed as unique pairings of lobsters (dyads), which could be single- or mixed-sex pairings. If home-range overlap between tagged lobsters occurred, interactions between lobsters were classified as attraction or avoidance. The number of times a lobster overlapped with the home range of another lobster was related to the mean substrate hardness within the home range of the focal lobster. Fewer interactions occurred between female lobsters, compared to males and mixed-sex pairings. Interactions between lobsters that occurred at 10 m, and interactions between mixed-sex pairs at 5 m, were identified as attractions. Interactions between male lobsters at 5 m were largely identified as avoidance and may indicate small-scale spatial exclusion. Understanding the drivers of movement and behaviour in wild free-ranging lobster populations is relevant to stock assessments, disease management, protected areas designation, and the development of sustainable evidence-based 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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".