Internal waves and mixing in the epilimnion of a lake affects spatial patterns of zooplankton in a body‐size dependent manner
Bibliographic record
Abstract
Lay Abstract Wind‐driven internal gravity waves, oscillations of a fluid density surface, are a common feature within the strongly stratified thermocline region of mid‐latitude lakes. We demonstrate that internal waves can propagate within the surface waters, or epilimnion, of Lake Opeongo, Ontario, during periods of weak stratification. We also note that within the epilimnion, zooplankton are not uniformly distributed spatially but are often distributed in patches as a result of the combination of their own movements and the effect of water currents. Using field data from July and August 2009 and 2010 we report observations of the relationship between enhanced heterogeneity of distribution in zooplankton and the presence of internal waves in the epilimnion. To quantify this relationship we compare measurements of small‐scale spatial distributions of zooplankton with a measure of wave activity. For the smallest size ranges of zooplankton (284–450 μm) we find that spatial variability is statistically greatest when internal waves are most active, whereas no such relationship exists for the two larger zooplankton size classes. The vertical velocities associated with the movement of internal waves are estimated to be faster than the swimming speeds of small zooplankton, essentially rendering them passive. This supports our assertion that the movement of internal waves contributes to the increased spatial variability of zooplankton in lakes.
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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".