Host plant resistance promotes a secondary pest population
Bibliographic record
Abstract
Abstract Insecticides can cause secondary pest outbreaks that weaken the benefit of chemical pest control. These detrimental nontarget effects motivate the use of alternative pest management strategies such as host plant resistance and intercropping. However, when alternative pest management strategies effectively suppress primary pests, they also have the potential to promote secondary pest populations via competitive release. The potato leafhopper (Empoasca fabae) is a key pest of alfalfa, and leafhopper‐resistant cultivars are being widely adopted by growers in the Midwest and Northeast United States. We conducted a field experiment comparing leafhopper‐susceptible alfalfa, leafhopper‐resistant alfalfa, and leafhopper‐resistant alfalfa intercropped with orchardgrass. Leafhopper‐resistant alfalfa reduced potato leafhopper abundance and protected the crop from protein loss, but there was no benefit of intercropping leafhopper‐resistant alfalfa with orchardgrass. Importantly, the abundance of a secondary pest, the pea aphid (Acyrthosiphon pisum), was twice as high in the leafhopper‐resistant plant treatments compared to the leafhopper‐susceptible treatment. Field sampling and microcosm experiments confirmed that the increase in pea aphids was caused, at least in part, by release from competition with leafhoppers. These results suggest that, when host plant resistance against insects is employed, efforts to monitor and manage secondary pest populations are warranted.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".