Prospective evaluation of the biological control of vine mealybug: refuge effects and climate
Bibliographic record
Abstract
Summary Vine mealybug Planococcus ficus is an invasive pest of vineyards in many areas of the world. In California, USA, it infests all plant subunits and has a spatial refuge from natural enemies under the bark and on roots. A temporal refuge is created when ants tending the mealybug reduce the efficacy of natural enemies. Biological control of vine mealybug is only partially successful and varies among California grape‐growing regions. To improve control and help determine appropriate natural enemies for importation, the effects of weather on mealybug regulation by two parasitoids, Anagyrus pseudococci and Leptomastidea abnormis, and a coccinellid predator, Cryptolaemus montrouzieri, were examined across the ecological regions of California. Weather‐driven, physiologically based age–mass structured demographic models of the mealybug and its natural enemies were parameterized using laboratory data and field observations. Temperature was used to define the thermal limits and development rates of each species, and resource supply/demand ratios were used to scale daily per capita growth, fecundity and survivorship rates from maximal values at optimal conditions. The population dynamics of the mealybug and its natural enemies were simulated at 108 locations in California over a 10‐year period using observed weather. The simulation data were mapped using a geographical information system (GIS) and analysed using linear multiple regression and marginal analysis. The models predictions indicated that: (i) the parasitoid A. pseudococci has a larger impact on vine mealybug than either L. abnormis or C. montrouzieri; (ii) mealybug densities will be lowest in the hot desert regions of southern California and highest in the cooler areas of northern California; (iii) mealybug density increases with season length and the size of the combined spatial–temporal refuge; (iv) biological control of mealybug could be achieved by reducing the size of the spatial–temporal refuge. Synthesis and applications. Models, no matter how detailed, will always be incomplete; despite this, the complexity of tri‐trophic systems can be modelled and the effects of biotic factors and of weather separated. The predictions of our model coincided well with field observations on vine mealybug, and clearly showed why the biological control will require additional species of natural enemies and/or why the size of the spatial and temporal refuges must be reduced.
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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 | 0.001 | 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".