Costs and benefits of <i>Daphnia</i> defense against <i>Chaoborus</i> in nature
Bibliographic record
Abstract
To estimate costs and benefits of antipredator defenses in the ChaoborusDaphnia system, we employed lake enclosures wherein controls (C) had no predators, the predation (P) treatment had freely swimming Chaoborus, and the kairomone (K) treatment predators were sequestered in a mesh tube apart from the Daphnia. Population growth (r) of two Daphnia pulex clones, one responsive (RC) and the other nonresponsive (NRC) to Chaoborus kairomone, was estimated for each predator treatment. Cost of defense was calculated as r(C,RC) r(K,RC). Benefit was calculated as r(P,RC) r(P,NRC). Antipredator defenses of Daphnia towards Chaoborus kairomone led to a 32% reduction in population growth in nature. The benefit of the defense, however, was a short-term 68% enhanced population growth by a responsive over a nonresponsive clone in the presence of the actual predation threat. The benefit of the defense exceeded the cost, but cost was nevertheless substantial. Our results verify that the in situ effects of Chaoborus on Daphnia involve direct and indirect impacts.
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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".