Nontarget herbivory by a weed biocontrol insect is limited to spillover, reducing the chance of population‐level impacts
Bibliographic record
Abstract
Insects approved for classical biocontrol of weeds are often capable of using close relatives of their target weed for feeding, oviposition, or larval development, with reduced preference and performance. When nontarget herbivory occurs and is suspected to reduce survival, growth, or fecundity of individual plants, and insects are capable of reproducing on their nontarget host, characterization of spatial and temporal patterns of the occurrence and intensity of herbivory is valuable for predicting potential population-level effects. Here, we perform a novel post-release manipulative field experiment with a root-feeding biocontrol weevil, Mogulones crucifer, released in Canada to control the rangeland weed Cynoglossum officinale, to test for its ability to establish on the nontarget plant Hackelia micrantha. After Cynoglossum, M. crucifer exhibits its highest preference for and performance on Hackelia spp. We released M. crucifer on Canadian rangeland sites with naturally occurring populations of H. micrantha growing interspersed with the target weed or in the near absence of the target weed. Adult weevil feeding on surrounding plants was monitored for three summers after release (years 0, 1, and 2), and, subsequently, subsets of plants were destructively sampled to determine M. crucifer oviposition levels. Additional oviposition and larval development data were obtained from seven non-experimental sites where weevils were released zero, three, or four years earlier. M. crucifer was not detected on experimental sites without C. officinale after two years, and nontarget herbivory was restricted to rare, low-level spillover. Visible evidence of adult herbivory (i.e., scars on shoots) was associated with oviposition in 90% of targets but only 30% of nontarget plants. We infer, through ecological refuge theory, that nontarget population-level impacts from M. crucifer spillover are unlikely because of temporal, spatial, and probabilistic refuges from herbivory, and make recommendations for monitoring and management of biocontrol systems with similar attributes, such as removing target plants around nontarget populations of interest. Because M. crucifer is among the least host-specific of the modern weed biocontrol agents, and H. micrantha is likely one of its most highly preferred nontargets, these conclusions are, arguably, generally applicable to other nontarget plants and biocontrol systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".