Environmental influences on the availability of smooth pink shrimp, <i>Pandalus jordani</i>, to commercial fishing gear off Vancouver Island, Canada
Bibliographic record
Abstract
Short time scale (less than seasonal) variability in commercial catch rates of smooth pink shrimp, Pandalus jordani, off the west coast of Vancouver Island, Canada, was examined in relation to changes in environmental conditions. Catch per unit of effort (CPUE) data were used as a proxy for catchability to identify environmental conditions affecting the availability of shrimp to the two main gear types in this fishery: otter trawls and beam trawls. Correlogram analyses of the 1996 CPUE (log‐transformed) data from each gear type, and autocorrelation analyses of wind stress, tidal current speed, sea surface temperature and salinity, and hours of bright sunshine (the latter three as residuals from their seasonal trends) for 1996 indicated a mean decorrelation time scale of 7.7 days. This was used to construct smoothed time series of these CPUE and environmental data for 1996. Multiple regression analyses with CPUE as the dependent variable and the environmental data as independent variables were significant, explaining 44% of the variability in otter‐trawl data and 35% of the beam‐trawl variability. Three hypotheses are proposed to explain these results, involving interactions between the shrimp’s behaviour and environmental conditions. A significant proportion of the within‐season variability in CPUE (and therefore in the availability of shrimp to fishing gear) for P. jordani off Vancouver Island can result from variations in environmental conditions which, if included in stock analyses, should reduce the variability of population abundance estimates.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.066 | 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".