Vertical distribution of snow crab (Chionoecetes opilio) pelagic stages in the Gulf of St. Lawrence (Canada) and effect of temperature on development and survival
Bibliographic record
Abstract
Abstract Knowledge of the vertical distribution, thermal habitat, and growth of the larvae of the cold stenothermic snow crab (Chionoecetes opilio) is incomplete and inconsistent. This study explored aspects of the vertical distribution and development rate of larvae from eastern Canada. In the Gulf of St. Lawrence (GSL), during 2002, the mean vertical positions of the snow crab zoeae I and II larvae were recorded within and above the permanent thermocline and in close association with the depth of strong density discontinuities in the stratified water column. No statistically significant differences were detected between nighttime and daytime vertical positions. The water temperatures at the centre of the larvae distributions were 2–3 °C in late May in the colder northern GSL and 7–8 °C in June in the warmer southern GSL. Data from the literature and from a rearing experiment in 2014 were used to develop functions linking development and survival to water temperature. Assuming the snow crab larvae remain in the upper mixed layer until final metamorphosis, development may last 2.2–4 months depending on hatch time and location. Development would be prolonged by several weeks if premolt megalopae move into and reside in the deeper, colder waters as appears to be the case. A relative survival index suggests that optimum temperature for development is around 10.8 °C, 9.5 °C, and 8.7 °C for snow crab zoea I, zoea II, and megalopa, respectively. These results should contribute to modelling efforts that aim to evaluate the extent of larval drift and location of potential settlement areas, as well as the potential impact of climate change on snow crab in the North Atlantic.
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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 | 0.000 |
| 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 | 0.000 |
| 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".