Impact of plant architecture and extraguild prey density on intraguild predation in an agroecosystem
Bibliographic record
Abstract
Abstract Several models and experimental studies conducted in confined environments have shown that intraguild predation (IGP) can modulate population abundances and structure communities. A number of ecological and abiotic factors determine the nature and frequency of IGP. This study examined the effect of plant architecture and extraguild prey density, and their interactions, on the occurrence of IGP between two species of ladybird, Harmonia axyridis (Pallas) and Propylea quatuordecimpunctata L. (both Coleoptera: Coccinellidae). Theoretical concepts predict that IGP levels would increase with a decrease of both extraguild prey density and plant structural complexity. We conducted a factorial experiment in an open soybean field into which coccinellid larvae were introduced in experimental plots for a period of 5 days. We tested two levels of soybean aphid [Aphis glycines Matsumara (Hemiptera: Aphididae)] density, low and high (100 and 1 000 aphids per plot, respectively), and two levels of plant complexity, low (by removing half of the branches from the soybean plants) and high (by leaving plants intact). We used species‐specific molecular markers to detect the presence of P. quatuordecimpunctata in the digestive tract of H. axyridis. Molecular gut‐content analysis of H. axyridis revealed that rates of IGP were higher (20%) at low aphid density than at high aphid density (<6%). Decreased plant complexity did not impact the frequency of IGP. In accordance with existing literature, this study demonstrates that IGP is amplified at low extraguild prey density. We conclude that considering environmental factors, such as extraguild prey density, is crucial to improve our ability to predict the impact of intraguild predation on community structure and, from an applied perspective, biological control.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".