Spawning Odds in Relation to Size of American Lobsters<i>Homarus americanus</i>
Bibliographic record
Abstract
In Newfoundland, the American lobster (Homarus americanus) fishery has considerable socioeconomic value. Concern about the sustainability of this fishery continues to be a concern as a result of high exploitation rates. Conservation initiatives (marine protected areas, a slot fishery, and v-notching) have been established in several lobster fishing areas (LFAs) in western Newfoundland to increase the number of large lobsters and fecundity (egg production) of populations. However, there has been concern by harvesters in western Newfoundland, where slot fisheries are in effect, that the large lobsters being caught are rarely ovigerous.We used extensive field data from 5 LFAs in western Newfoundland (LFA12, LFA13A, LFA13B, LFA14A, and LFA14B) to test whether the spawning odds depend on size in a slot fishery, where large females were present in sufficient numbers to allow reliable estimates. Three analyses of size-dependent spawning odds were conducted via logistic regression: 2 analyses by year for LFA14A and LFA14B from 2006 to 2011 and 1 spatial analysis for 5 LFAs (LFA12, 13A, 13B, 14A, and 14B) during the same year (2010). In 4 of 6 y, for both LFA14A and LFA14B, spawning odds increased with size, and for 3 of the 5 LFAs for the same year, spawning odds increased with size. We found no evidence of a decrease in spawning odds with size and, equivalently, no decrease in percent ovigerous with increasing size. Our results support the use of spawning odds to calculate the effects of sustainability measures in lobsters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 teacher head, 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".