Biocontrol Arthropods: New Denizens of Canada’s Grassland Agroecosystems
Bibliographic record
Abstract
Abstract. Canada’s grassland ecosystems have undergone major changes since the arrival of European agriculture, ranging from near-complete replacement of native biodiversity with annual crops to the effects of overgrazing by cattle on remnant native grasslands. The majority of the “agroecosystems ” that have replaced the historical native grasslands now encompass completely new associations of plants and arthropods in what is typically a mix of introduced and native species. Some of these species are pests of crops and pastures and were accidentally introduced. Other species are natural enemies of these pests and were deliberately introduced as classical biological control (biocontrol) agents to control these pests. To control weeds, 76 arthropod species have been released against 24 target species in Canada since 1951, all of which also have been released in western Canada. Of these released species, 53 (70%) have become established, with 18 estimated to be reducing target weed populations. The biocontrol programs for leafy spurge in the prairie provinces and knapweeds in British Columbia have been the largest, each responsible for the establishment of 10 new arthropod species on rangelands. This chapter summarizes the ecological highlights of these programs and those for miscellaneous weeds. Compared with weed biocontrol on rangelands, classical biocontrol of arthropod crop pests by using arthropods lags far behind, mostly because of a preference to manage crop pests with chemicals. To date, only one arthropod has been documented as established from the intentional releases of 19 agent species from Eurasia. However, little effort has been devoted to postrelease
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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 | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".