The punctuated seaward migration of Pacific lamprey (<i>Entosphenus tridentatus</i>): environmental cues and implications for streamflow management
Bibliographic record
Abstract
We investigated emigration timing of juvenile Pacific lamprey (Entosphenus tridentatus) over a 10-year period in the Sacramento River, California, USA. Emigration was punctuated with 90% of macrophthalmia in daily catches of at least 50 individuals. Macrophthalmia were observed primarily between November and May, with among-year variation in median emigration date over four times that of sympatric anadromous salmon. Our best model associating catch and environmental factors included days from rain event, temperature, and streamflow. We found strong evidence for an association of catch with days from rain events, a surrogate for streamflow, with 93% of emigrants caught during an event and the two subsequent days. Emigration was more likely during nighttime during subdaily sampling after accounting for the effects of factors significantly associated with daily catch. These results emphasize the importance of natural variation in streamflow regimes and provide insight for management practices that would benefit emigrating lampreys, such as synchronizing dam releases with winter and spring storms to reduce migration time, timing diversions to avoid entrainment during emigration windows, and ensuring streamflows are sufficient to reach the ocean, thereby avoiding mass stranding events.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".