Rainforest habitat resistance to the migration of <i>Phytoseiulus persimilis</i> Athias‐Henriot (Acari: Phytoseiidae) in south‐eastern Queensland
Bibliographic record
Abstract
Abstract This paper tests the hypothesis that habitat differences affect the migratory ability of the Chilean predatory mite, Phytoseiulus persimilis, an introduced biological control agent of the spider mite, Tetranychus urticae. It is suggested that habitat resistance accounts for the species’ inability to invade rainforests in south‐eastern Queensland, Australia. Like its prey, P. persimilis migrates to distant plants on air currents. To test our hypothesis, populations of the Chilean predatory mite were established on potted bean plants in both remnant rainforest and adjacent open fields, and their migration monitored using sticky traps. Overall it was found that prey populations on leaves were similar in both habitats, but those of predators were about 20% lower in rainforest. However, the numbers of both predators and prey caught on sticky traps in rainforest were about 6% and 25%, respectively, of those caught in open fields, indicating a strongly reduced rate of aerial migration in the forest. The number of P. persimilis caught on the sticky traps increased with increasing populations of predators on foliage. Thus, dense vegetation inhibits the movement of air currents and inhibits colonisation by both predators and, to a lesser extent, spider mites. These results suggest that the inhibition of aerial migration is one reason for lower numbers of P. persimilis in forest habitats, both because its own vagility is restricted, and because its prey is less able to disperse.
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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) | 0.002 | 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".