Interference competition in a planktivorous fish (Rutilus rutilus) at different prey densities and temperatures
Bibliographic record
Abstract
The effect of interference competition can be assessed by comparing the capture rate of a predator foraging alone with that of the predator within a group. Since such an effect could be prey density dependent, a constant density of prey must be maintained while assessing this effect, irrespective of the elimination of prey by predation. However, when studying a predator-harvester, such as a planktivorous fish, which collects zooplankton at a rate of up to 1 prey s −1 , instantaneous replacement of each consumed prey item is not feasible. This problem was solved in short-lasting mesocosm experiments by minute-by-minute supplementation to replace eliminated Daphnia and maintain a constant average prey density. Such experiments were performed with different numbers of foraging roach ( Rutilus rutilus ) at three prey densities and in two ranges of ambient temperature. The number of Daphnia required at the start of each experiment to establish the initial prey density and the number that it was necessary to add per minute were determined in experiments conducted without prey supplementation and in preliminary experiments with prey supplementation. The results of this study revealed that fish foraging in a group eat less, due to both exploitation and non-aggressive competition for space. Moreover, the effect of interference competition was stronger at higher temperatures, irrespective of the prey density, indicating that natural populations of roach foraging in shoals may suffer more from competitive interactions in warmer waters.
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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".