The Basis for Cutworm (Lepidoptera: Noctuidae) Integrated Pest Management: Understanding Crop-Pest Interaction and Moth Community Structure in Prairie Agroecosystems
Bibliographic record
Abstract
Cutworms and armyworms (Lepidoptera: Noctuidae) are part of a pest complex, native to North America, that causes sporadic economic damage to multiple annual crops grown across the Canadian Prairies. Both larvae and adults are generalist herbivores on a wide range of hosts from different plant families. Cutworm and armyworm life history and phenology has been well studied but the effects of agricultural practices on larval performance are unknown. Adults can disperse over long distances. There are no reliable monitoring tools developed to detect temporal or spatial changes in population density for most cutworm species. In order to develop an effective monitoring program, it is important to understand cutworm-crop interactions from both the individual and population levels. In this thesis, I take an Integrated Pest Management (IPM) approach to identify knowledge gaps on crop-cutworm interactions. The first component of this thesis focused on crop-cutworm interaction at the individual level. The influence of cereal crop variety (Poaceae) and fertilization regime were evaluated on the relationship between oviposition preference and larval performance of the true armyworm, Mythimna unipuncta (Haworth). Females prefer the lowest quality host, feed barley (Xena), that supported the lowest larval performance. The addition of fertilizer increased the nutrition quality of the host plants and enhanced the larval performance, however, females failed to assess the nutritional quality of the host and equally accepted fertilized and unfertilized hosts. The true armyworm does not exhibit the ‘mother know best’ principle on the tested hosts and potentially employs a bet-hedging strategy instead.The effect of crop species and fertilization regime on the larval performance and larval feeding preference were evaluated on the redbacked cutworm, Euxoa ochrogaster (Guenée), and pale western cutworm, Agrotis orthogonia (Morrison). Larval performance and preference were evaluated on three hosts: canola (Brassica napus L.) (Brassicaceae), field peas (Pisum sativum L.) (Fabaceae) and spring wheat (Triticum aestivum L.) (Poaceae). The redbacked cutworm has higher performance on canola and field peas, while pale western cutworm has higher performance on wheat. In multiple-choice feeding experiments, redbacked cutworm prefers canola over peas and wheat, while pale western cutworm prefers spring wheat over canola and peas. The effect of plant fertilization was tested using two plant hosts (canola and spring wheat) exposed to two fertilization regimes (unfertilized and fertilized). When fed unfertilized seedlings, redbacked cutworm has better performance on canola, whereas pale western cutworm has better performance on spring wheat. Fertilizer application enhanced the performance of both cutworms regardless of the crop species. Despite their generalist feeding behaviour, both cutworm species have larval feeding preferences that match the host plant with high performance. Canola-cereal crop is a common crop rotation schedule in the region, however, this tactic will not negatively impact cutworm performance.The second component of this thesis focused on crop-cutworm interactions at the population level, specifically on the adult stage of cutworms and the chemical ecology of feeding attractant volatiles. A series of field experiments were conducted to develop a food-based semiochemical to monitor the cutworm and armyworm pest complex with a single lure in Canadian Prairie agroecosystems. The combination of acetic acid and 3-methyl-1-butanol (AAMB) attracts noctuid pest moths. My approach was to enhance the attractiveness of the AAMB lure to monitor the redbacked cutworm moth in canola and wheat fields in central Alberta. I tested: 1) different release rates of AAMB released from different devices; and 2) the addition of other food-based semiochemicals to the AAMB lures. I also evaluated the attractiveness of volatile compounds released from Canada thistle as a potential lure to monitor noctuid pests; and 4) the influence of moth physiological state on the response to food-based semiochemicals. Results focus on food bait lure development to efficiently monitor multiple cutworm moth species with a single lure and reduced pollinator by-catch. Finally, I report on the diversity and abundance of noctuid moths trapped with food bait lures based on the volatile by-products of fermented sugar baits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".