Home range of European lobster (<i>Homarus gammarus</i>) in a marine reserve: implications for future reserve design
Bibliographic record
Abstract
Marine reserves are perceived as a critical component in successful rebuilding of overharvested marine populations. Such efforts can be particularly successful in species with limited movement rates. However, long-term data on movement is sparse for most marine species. Here, we investigated space use in European lobster ( Homarus gammarus ) by ultrasonic tracking in a reserve on the Norwegian Skagerrak coast from September 2006 to August 2007. Over the period, 95% of tagged lobsters remained either within the reserve or near reserve boundaries. Home range estimates based on a kernel density estimator of the 95% utilization distribution ranged from 5728 to 41 548 m2 (mean 19 879 ± 2152 m2 standard error), representing 0.57%–4.15% of the reserve area (1 km2), with no significant difference among males, non-ovigerous females, and ovigerous females for an overlapping observation period of 242 days. Logistic regression predicted average time to reach 50% and 95% of minimum convex polygon home range area at 98 and 259 days, respectively. These results show that European lobsters can be resident with limited home ranges. Small coastal reserves can be designed to afford complete or partial protection by letting boundaries engulf or intersect patches of habitat preferred by this species.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".