Spatiotemporal variability of euphausiids in the California Current Ecosystem: insights from a recently developed time series
Bibliographic record
Abstract
Abstract Euphausiids, or krill, are important energy links between primary producers and higher trophic levels in the California Current Ecosystem (CCE), but a thorough understanding of their variability at the coast-wide scale is limited. Using fisheries acoustics data collected during biennial joint US–Canada Integrated Ecosystem and Acoustic Trawl Surveys for Pacific hake (Merluccius productus), we developed a time series (n = 8 years; 2007–2019 odd years inclusive, and 2012) of krill abundance and examined relationships with environmental factors. Krill were located in waters off the west coasts of the United States and Canada, primarily in shallow basins and on the continental shelf, with greatest kernel density estimates near Cape Mendocino and the Juan de Fuca eddy system. Coast-wide krill abundance was variable, and lowest in 2015 during an extended marine heat wave, when 91% were located in British Columbia. Using hierarchical generalized additive models, we predicted greatest krill abundance in cooler waters (0.2°C below the time series average), within 10–20 km of the shelf break, and in bottom depths between 200 and 400 m. This newly developed coast-wide time series of krill abundance and distribution will inform ecosystem-based fisheries management efforts, and offers additional opportunities for studies of krill-dependent fish, seabirds, and marine mammals.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".