The effect of vorticity on the feeding of a freshwater grazer
Bibliographic record
Abstract
Abstract The transfer of energy through zooplankton grazing on phytoplankton is one of the most important interactions in aquatic ecosystems, yet the role of hydrodynamic forces is not fully understood. Factors that influence these interactions include algal size and shape and the interactions between grazer and alga dictated by hydrodynamic forces. Hydrodynamic forcing lead to unimodal relationships in grazer clearance rates (CR) because water motion and turbulence increases encounters but interferes with feeding at high levels. We expect higher CR on small algae due to increased encounter rates caused by vorticity generated in a horizontally oriented rotating cylinder to model increasing turbulence, whereas longer cells, tumbling in the flow, may be more difficult to handle. Ultimately, we expect that increased vorticity will interfere with zooplankton swimming. The CR of Daphnia magna followed the unimodal trend, with higher CR on the small, spherical Chlorella vulgaris than on larger, elongated, and colonial Scenedesmus quadricauda. This was likely due to lower handling time and higher concentration of the smaller cells in the feeding radius around D. magna. The normal hop‐sink swimming behavior of the Daphnia was affected by increasing vorticity; hop frequency decreased, displacement increased, and there was a loss of vertical orientation. This pattern in feeding and swimming were predicted by vorticity. These results for Daphnia differ from those obtained for copepods, which do not respond to vorticity. Given the importance of vorticity in nature, it is relevant to examine grazer feeding interactions under ecologically relevant hydrodynamic conditions.
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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".