Light effects on alewife‐mysid interactions in Lake Ontario: A combined sensory physiology, behavioral, and spatial approach
Bibliographic record
Abstract
An understanding of the effect of light on predator‐prey interactions in aquatic systems requires the integration of sensory physiology, behavioral ecology, and spatial distributions of predator and prey in the field. Here, we present such an integrative approach to a study on the interactions between the alewife, Alosa pseudoharengus, and the mysid shrimp, Mysis diluviana, (formerly M. relicta) in Lake Ontario at night, when it is unknown whether visual feeding is possible. Visual pigment analyses of alewife rod photoreceptors were used to derive an alewife‐specific unit of brightness—the ‘alelux’ (wavelength of maximum absorbance, λmax = 505 nm)—which formed the basic unit of light intensity in alewife feeding‐rate experiments and field applications. At light levels of 10−7 alelux (~ 10−4.1 lux) and greater in the laboratory, alewives engaged in visual search and strike behaviors and fed at rates that were significantly higher than those under completely dark conditions. Field observations from Lake Ontario showed that light levels at the upper edge of the mysid distribution were within the range of those required for visual feeding in the laboratory on a full moon night, but not on a new moon night. These increased light levels translated into feeding rates that were > 30 times higher on the full moon night, despite a larger degree of spatial separation of the two trophic levels. We hypothesize that observed increased water clarity in Lake Ontario in recent years has led to increased consumption of mysids by alewife at night and associated food‐web changes.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".