Integrated Management of Canada Thistle (<i>Cirsium arvense</i>) with Insect Biological Control and Plant Competition under Variable Soil Nutrients
Bibliographic record
Abstract
Abstract Because of economic and environmental constraints, alternatives to chemical management of Canada thistle (Cirsium arvense) are frequently sought, but adequate nonchemical suppression of this invasive species remains elusive. Combining biological control with other tactics may be an effective approach to suppress Canada thistle, but more information is needed about how environmental conditions affect interspecific interactions. We investigated effects of a biocontrol agent (Hadroplontus litura, a stem-mining weevil) and a potential plant competitor (common sunflower, Helianthus annuus, native annual) on Canada thistle under two soil nutrient regimes in outdoor microcosms. Larval mining damage was relatively light, and weevils negatively impacted only main shoot height and flower number. All measures of Canada thistle performance were reduced when plants were grown with common sunflower or in reduced nutrients, although effects of the latter on root biomass were not significant. Effects of common sunflower and soil nutrients on Canada thistle were generally additive, though a marginally insignificant interaction indicated a trend for greatest flower number with high nutrients and absence of common sunflower. Effects of weevils and common sunflower on Canada thistle were also additive rather than interactive. Although larval damage ratings were significantly greater on plants grown in high-nutrient soil, under our experimental conditions weevils and soil nutrients did not have a significant interactive effect on Canada thistle plants. Our results indicate that H. litura is a relatively weak biological control agent, but when combined with competitive desirable vegetation, some level of Canada thistle suppression may be possible, especially if soil nutrient levels are not highly enriched from agricultural runoff. Assessing the true ecological impacts of Canada thistle infestations may be an important direction for future research.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".