Predicting Pacific Herring Spawn Events in the Howe Sound, British Columbia
Bibliographic record
Abstract
Pacific herring (Clupea pallasii) are a vital forage fish, supporting marine food webs and coastal fisheries while holding deep cultural significance for Indigenous communities. The timing of Pacific herring spawning is influenced by various environmental factors, yet the specific cues driving this behavior remain unclear. This study investigates the role of lunar cycles, sea surface temperature, and photoperiod in determining the timing of Pacific herring spawning events in the Howe Sound, British Columbia. Using data collected from 2021 to 2024 by the Marine Stewardship Initiative, alongside satellite-derived sea surface temperature and the environmental variables lunar phase and photoperiod, the study examines correlations between these factors and observed Pacific herring spawning events. The findings reveal that lunar cycles, particularly the Waxing Crescent phase, are the primary driver of spawn timing, with spawning events peaking during this phase. Sea surface temperature and photoperiod showed no significant correlation with spawn timing, suggesting that tidal conditions rather than temperature or light levels are more critical for herring reproduction in this region. These results have important implications for conservation efforts, indicating that spatial protections and management strategies should be aligned with lunar cycles to maximize spawning success. This study contributes to the understanding of environmental cues influencing herring spawning and highlights the need for further research into site-specific factors and additional environmental drivers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".