<i>Notonecta</i> exhibit threat-sensitive, predator-induced dispersal
Bibliographic record
Abstract
Dispersal is a central process determining community structure in heterogeneous landscapes, and species interactions within habitats may be a major determinant of dispersal. Although the effects of species interactions on dispersal within habitats have been well studied, how species interactions affect the movement of individuals between habitats in a landscape has received less attention. We conducted two experiments to assess the extent to which predation risk affects dispersal from an aquatic habitat by a flight-capable semi-aquatic insect (Notonecta undulata). Exposure to non-lethal (caged) fish fed conspecifics increased dispersal rates in N. undulata. Moreover, dispersal rate was positively correlated with the level of risk imposed by the fish; the greater the number of notonectids consumed by the caged fish, the greater the dispersal rate from the habitat. These results suggest that risk within a habitat can affect dispersal among habitats in a landscape and thus affect community structure on a much greater scale than the direct effect of predation itself.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".