Global range expansion of pest Lepidoptera requires socially acceptable solutions
Bibliographic record
Abstract
Abstract Caterpillars of key moth pests can cause significant losses in cropping systems worldwide, and globalization is spreading such pests. Failure to control some species can jeopardise the economics of food production. A Global Eradication and Response Database ( http://b3.net.nz/gerda ) was reviewed on known government-level incursion response programs specific to invasive Lepidoptera. Geographic range expansion of Lepidoptera was evident from 144 incursion response programs targeting 28 species in 10 families. The countries involved in responses to Lepidoptera were USA (104), Australia (8), Canada (7), New Zealand (6), Italy (3), Mexico (2), with the remainder with one programme each (Brazil, Czech Republic, France, Hungary, and Spain). Most programs have been undertaken since the 1990’s. Control options exist for the long-term management of Lepidoptera, but most have issues of cost, efficacy or non-target impacts that reduce their acceptance. Pheromone-based technologies are increasingly available and are generally highly compatible with other tactics. The development of tactics for new targets is a major undertaking, although previous programs can be invaluable. New and improved socially-acceptable technologies are needed to counteract range expansion in Lepidoptera, and usually need to be used in combinations to achieve eradication. The sterile insect technique, which involves mass-rearing and release of sterile insects to reduce wild populations of the pest, has been used successfully against a number of lepidopteran species. Several sterile moth programs are under development. New technologies must have a social license to operate in urban areas, where new incursions are frequently detected. This factor is likely to reduce tactical flexibility and increase the complexity of insect eradication.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".