Relative importance of weather and density dependence on the dispersal and on‐plant activity of the predator <i>Orius minutus</i>
Bibliographic record
Abstract
Abstract The present study evaluated the relative effects of abiotic (weather: temperature, wind speed, and rain) and biotic (intra‐ and intertrophic density dependence: densities of conspecifics, prey per predator individual and leaves on plants) factors on the dispersal and on‐plant activity (foraging and oviposition) of the predatory bug, Orius minutus, under seminatural field conditions. Experiments were conducted at plots, each comprising 25 potted azuki bean plants, placed symmetrically in concentric circles, in 1998 and 1999. At the central pot within each plot, 5 marked females of O. minutus (with a male in 1998) were released, and their location and activity were recorded hourly up to 24 h. A total of 78 individuals were released. Stepwise multiple logistic regression was used to select among weather, density dependence, and time variables. Hourly dispersal probability of individuals was positively correlated with temperature and negatively with time since release and with prey density per individual O. minutus. Hourly probability of individuals being active was positively correlated with temperature and negatively with number of leaves of visited plants and conspecific density per leaf. Between‐year difference was observed in the probability of individuals being active, which was higher in 1998 than in 1999, probably generated by hunger and higher age. By contrast, diffusion rate was estimated to be lower in 1998, suggesting a trade‐off between foraging/oviposition and dispersal by flight. The results indicate that dispersal is affected by temperature and intra‐/intertrophic‐level density dependence within and between trophic levels, as are foraging/oviposition. The importance of incorporating both abiotic and biotic factors should be stressed when modeling predator–prey metapopulation dynamics on a greenhouse scale.
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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 | 0.001 |
| 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".