Efficacy of the European Earwig (Forficula auricularia) as a generalist biocontrol agent
Bibliographic record
Abstract
The European Earwig (Forficula auricularia) has been the subject of scientific curiosity and public disdain since its introduction to North America due to its controversial status as both a natural enemy of agricultural pests, and as a nuisance cohabitant of human dwellings. I aim to investigate the feasibility of utilizing the earwig as a biocontrol agent against target pests of organic apple orchards, as well as its efficacy as a generalist predator in the context of agricultural ecosystems. Through DNA gut-content analysis, and cross-seasonal field observations, I was able to confirm that earwigs are consuming apple orchard pests under natural conditions. These findings are corroborated upon further analysis of field data which show a negative association between earwig abundance and multiple species of pest prevalence at tree-level occupancy across the field season. I examine predation efficacy and consumptive thresholds of the earwig in the context of generalist predator traits through temperature controlled functional response laboratory experiments for two recognized apple pest species, the rosy apple aphid (Dysaphis plantaginea), and the oblique-banded leafroller (Choristoneura rosaceana). Earwig predation was independently affected by density and temperature, but no interaction effect was observed. Analysis of the data did not accurately describe a type II functional response relationship, showing the limitations of traditional predator-models for describing predation behaviour of generalists in biocontrol practice. The preponderance of evidence outlined in this thesis provides promising evidence for utilizing European earwigs in conservation biocontrol, elucidates their role as key predators in agroecosystems, as well as reconsiders how to approach the study of generalist predators in biocontrol research and traditional predator-prey models.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".