A Multi-Approach Study to Delineate Interactions Between Carabid Beetles and Soybean Aphids
Bibliographic record
Abstract
In recent years, the soybean aphid, Aphis glycines Matsumura, has become the most important exotic pest of soybean, Glycine max (L.) Merrill, in North America. Given the significant yield losses that are reported, considerable effort has been expended to characterize the natural enemy community associated with this pest. Several indigenous and naturalized predators have been identified as potential biological control agents, and these include carabid beetles, an abundant and important family of aphid predators. The objectives of this study were to assess the incidence of field predation by Pterostichus melanarius (Illiger), the most common carabid species in Québec soybeans, using molecular gut-content analysis, and to quantify its impact on A. glycines populations through laboratory and field cage experiments. Throughout the growing season between 16.8% (during low aphid density) and 33.7% (at times of high aphid density) of P. melanarius tested positive for aphid DNA. Furthermore, although laboratory feeding trials confirmed that P. melanarius prey on A. glycines, short-term field cage experiments failed to demonstrate a significant reduction of A. glycines populations by carabid beetles. These results suggest a relatively weak interaction between P. melanarius and A. glycines when pest densities are high, but the high predation rate when aphid densities are particularly low suggests these natural enemies may function as important early-season predators.
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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 | 0.001 | 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) | 0.001 | 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".