Sitona lineatus (Coleoptera: Curculionidae) Larval Feeding on Pisum sativum L. Affects Soil and Plant Nitrogen
Bibliographic record
Abstract
Adults of Sitona lineatus (pea leaf weevil, PLW) feed on foliage of several Fabaceae species but larvae prefer to feed on nodules of Pisum sativum L. and Vicia faba L. Indirectly, through their feeding on rhizobia, weevils can reduce soil and plant available nitrogen (N). However, initial soil N can reduce nodulation and damage by the weevil and reduce control requirements. Understanding these interactions is necessary to make integrated pest management recommendations for PLW. We conducted a greenhouse study to quantify nodulation, soil and plant N content, and nodule damage by weevil larvae in relation to soil N amendment with urea, thiamethoxam insecticide seed coating and crop stage. PLWs reduced the number of older tumescent (multilobed) nodules and thiamethoxam addition increased them regardless of other factors. Nitrogen amendment significantly increased soil available N (>99% nitrate) as expected and PLW presence was associated with significantly lower levels of soil N. PLW decreased plant N content at early flower and thiamethoxam increased it, particularly at late flower. The study illustrated the complexity of interactions that determine insect herbivory effects on plant and soil nutrition for invertebrates that feed on N-fixing root nodules. We conclude that effects of PLW on nodulation and subsequent effects on plant nitrogen are more pronounced during the early growth stages of the plant. This suggests the importance of timing of PLW infestation and may explain the lack of yield depression in relation to this pest observed in many field studies. Also, pea crops in soils with high levels of soil N are unlikely to be affected by this herbivore and should not require insecticide inputs.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".