The impact of plant associations on<i>Macrosteles quadrilineatus</i>management in carrots
Bibliographic record
Abstract
Abstract Habitat diversification can influence the interactions of insects with plants and this can be used in agroecosystems for the management of pest populations. Plant diversification can be achieved through planting crops, such as trap crops, or by adjusting weed management. Aster leafhopper, Macrosteles quadrilineatus Forbes (Hemiptera: Cicadellidae), is a polyphagous species that uses cereals, vegetables, and weeds as host plants. The influence of weeds on M. quadrilineatus abundance was investigated experimentally in carrot [ Daucus carota L. cv. Canada (Apiaceae)] field plots by adjusting the level of management of two groups of weeds (broadleaf and grass) and by comparing it to weed‐free plots. The preference of M. quadrilineatus for different cereal and weed species relative to carrots was tested in choice test assays. Habitat context influenced the abundance of M. quadrilineatus in the field experiments. The presence of border crops such as oat, rye, barley, wheat, and triticale did not significantly attract or repel this insect to carrot plots compared to the no‐border treatment. However, spelt‐bordered plots had 42% fewer M. quadrilineatus than three treatments, triticale, wheat, and barley, that had the highest insect abundance. The type of weed management affected M. quadrilineatus abundance in carrot plots, but not the frequency of herbicide application. Plots that had carrot growing with broadleaf‐weeds had about 59% fewer M. quadrilineatus compared with those growing with crabgrass or carrot alone. In the greenhouse choice tests, grasses (e.g., cereals) attracted and broadleaf‐weeds repelled M. quadrilineatus relative to carrots. In summary, carrot growers may be able to manage this pest by reducing the interaction of cereal cover crops with carrots and eliminating grassy weeds in commercial production fields.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".