Mass Trapping Lepidopteran Pests with Light Traps, with Focus on Tortricid Forest Pests: What If?
Bibliographic record
Abstract
The management of Lepidopteran pests with light traps (LTs) is often achieved by luring adults to death at light sources (light trap-based mass trapping, or LTmt). Large-scale LTmt programs against agricultural pests initiated in the late 1920s in the United States were phased out in the 1970s, coinciding with the rise of pheromone-based management research. The interest in LTmt has surged in recent years with the advent of light emitting diodes, solar power sources, and intelligent design. The first step in implementing LTmt is to identify a trapping design that maximizes the capture of target pests and minimizes the capture of non-target beneficial insects—with a cautionary note that high captures in LTs are not equivalent to the feasibility of mass trapping: the ultimate objective of LTmt is to protect crop plants from pest damage, not to trap adults. The captures of egg-carrying females in light traps have a greater impact on the efficiency of LTmt than the captures of males. When LTmt is defined as a harvesting procedure, the biomass of females in LTs may be viewed as the best estimator of the mass trapping yield; biomass proxy has universal application in LTmt as every living organism can be defined on a per weight basis. While research has largely focused on agricultural pests, an attempt is made here to conceptualize LTmt as a pest management strategy in forest ecosystems, using spruce budworm as a case study. The mass trapping of female budworms is impossible to achieve in endemic populations due to the large spatial scale of forest landscapes (implying the deployment of a prohibitively large number of LTs); in addition, ovipositing female budworms do not respond to light sources at a low density of conspecifics. The light-based mass trapping of female budworms may provide a realistic management option for geographically isolated forest stands heavily infested with budworms, as a tool to prevent tree mortality. Somehow unexpectedly, however, one factor obscuring the feasibility of LTmt is as follows: the complex (‘unknowable’) economic valuation of forest stands as opposed to agricultural landscapes.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".