Swimming performance of subarctic Calanus spp. facing downward currents
Bibliographic record
Abstract
Calanoid copepods dominate mesozooplankton communities in temperate and Nordic seas. The ability of copepods to remain and feed in productive surface waters depends on their ability to overcome downward flows. In this study, we assessed the swimming performance of subarctic Calanus spp. and tested how the copepods can retain their vertical position in a representative range of downward currents (between 0 and 5.4 cm s-1) simulated in a downwelling flume. Mean vertical and horizontal copepod swimming velocities and accelerations, movement periodicity and trajectory complexity were obtained by tracking individual trajectories in the field of view of 2 cameras. Copepod swimming velocity increased with increasing downward flow and matched downward flows up to 2 cm s-1. Beyond 2 cm s-1, animals were still able to significantly reduce their sinking rates, but their motions changed. Trajectories became simpler, swimming velocities changed on shorter time scales and instantaneous acceleration increased. These results are consistent with predictions of balancing depth retention against encounter rates with food and predators. Frequency distributions of vertical swimming speeds were mostly unimodal, with entire experimental populations responding in the same way. Coordination of movements and the ability to resist moderate downwelling flows can result in the accumulation of copepods in large surface swarms as observed in the field.
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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 | 0.000 |
| 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".