Ecology of fear: environment-dependent parasite avoidance among ovipositing<i>Drosophila</i>
Bibliographic record
Abstract
Habitat avoidance is an anti-parasite behaviour exhibited by at-risk hosts that can minimize exposure to parasites. Because environments are often heterogeneous, host decision-making with regards to habitat use may be affected by the presence of parasites and habitat quality simultaneously. In this study we examine how the ovipositing behaviour of a cactiphilic fruit fly, Drosophila nigrospiracula, is affected by the presence of an ectoparasitic mite, Macrocheles subbadius, in conjunction with other environmental factors - specifically the presence or absence of conspecific eggs and host plant tissue. We hypothesized that the trade-off between site quality and parasite avoidance should favour ovipositing at mite-free sites even if it is of inferior quality. We found that although flies avoided mites in homogeneous environments (86% of eggs at mite-free sites), site quality overwhelmed mite avoidance. Both conspecific eggs (65% of eggs at infested sites with other Drosophila eggs) and host plant tissue (78% of eggs at infested sites with cactus) overpowered mite avoidance. Our results elucidate the context-dependent decision-making of hosts in response to the presence of parasites in variable environments, and suggest how the ecology of fear and associated trade-offs may influence the relative investment in anti-parasite behaviour in susceptible hosts.
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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".