Free-living mesostigmatic mites in Australia: their roles in biological control and bioindication
Bibliographic record
Abstract
The taxonomy, biology and ecology of free-living mesostigmatic mites in Australia and their current and potential use in biological control and bioindication is reviewed. Most current research on free-living Mesostigmata in Australia focuses on species with an established role in the biocontrol of crop pests, such as members of the family Phytoseiidae. Three introduced species and at least seven native species of Phytoseiidae are presently used for the control of phytophagous mites in Australia. The introduced phytoseiids are mostly specific to spider mites and have been selected for resistance to some of the common pesticides. Native species provide the advantage of being generalist feeders and are capable of using alternative food in the absence of mite pests. Therefore they can persist more effectively in the environment and contribute to the control of several pests. The reduced and selective use of pesticides, accompanied by scouting services, has allowed the successful control of phytophagous mites by native species in several Australian tree crops, especially grapevine and citrus. In soils, Mesostigmata are extremely abundant, species-rich and play significant ecological roles. They feed on a broad range of invertebrates, including phytophagous pests that spend part or most of their lives on or in the soil or root systems. However, the majority of mesostigmatic mite species are unknown in Australia. Nevertheless, recent research indicates that many species are habitat-specific, and that they may be sensitive to agricultural practices and other land management systems. Mesostigmata have great potential for biological control of pests, and as indicators of soil quality and sustainable agricultural practices. However, the current paucity of research and information on the taxonomy, life-history and ecology of native species in natural and managed landscapes will continue to hinder their use in biological control and as bioindicators.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".