Spatiotemporal modelling of northern shrimp Pandalus borealis distribution patterns throughout Canada’s subarctic and arctic regions
Bibliographic record
Abstract
Northern shrimp Pandalus borealis occur throughout Canada’s Atlantic Ocean, where they are thought to form a single population spanning from Baffin Bay to the tail of the Grand Bank. Here, they play an important role in the ecosystem as prey for many taxa and have been targeted by a lucrative large-scale fishery since the 1970s. Yet, we still understand little about which (and how) ecosystem and environmental factors influence their distribution and abundance. We used survey data collected over 29 yr throughout 23 degrees of latitude to develop a spatiotemporal model predicting northern shrimp density. We confirmed that both top-down drivers (e.g. predation pressure), as well as bottom-up drivers (e.g. bottom temperature) play important roles in determining both the presence and abundance of northern shrimp. The model was used to predict the density of northern shrimp throughout the entire study area from 2005 to 2022. Our results highlight the importance of understanding ecosystem and environmental dynamics in relation to northern shrimp population patterns and trends within resource assessments.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".