Rapid widespread declines of an abundant coastal shark
Bibliographic record
Abstract
Determining population trends is challenging for marine species with transboundary ranges, but increasingly important given the redistribution of species across international borders with climate change. Here, we use spatiotemporal models fit to data from 10 scientific surveys to evaluate trends in biomass, abundance, and distribution for Pacific Spiny Dogfish (Squalus suckleyi) across their entire eastern North Pacific Ocean range. We find a coastwide 51% (95% CI: 38%–61%) decline in Dogfish biomass from 2003–2023. Regional declines were steepest for the US West Coast and Canada: 79% (95% CI: 71%–85%) and 72% (95% CI: 58%–82%), respectively, while Alaskan declines were less steep at 37% (95% CI: 13%–54%). Mature females and immature Dogfish had the largest proportional declines. We find a deepening distribution on the US West Coast and Canada and an increase in the biomass-weighted temperature across most maturity groups on the US West Coast, but these patterns do not explain the overall declines. Contrary to prior hypotheses, we find no clear shift in biomass northward to Alaska. Further work investigating causal mechanisms of the decline is needed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".