Combining Herbicides and Fertilizers to Enhance Control of Leafy Spurge (Euphorbia virgata Wald & Kit)
Bibliographic record
Abstract
Across the Northern Great Plains, leafy spurge [Euphorbia virgata Wald & Kit (previously known as Euphorbia esula L.)], is a problematic invasive plant that contributes to the degradation of native ecosystems through displacement of indigenous vegetation. Controlling leafy spurge is extremely challenging, often requiring multiple herbicide applications for sustained suppression. Below ground, leafy spurge associates strongly with arbuscular mycorrhizal fungi (AMF) in a symbiotic plant-soil relationship that typically benefits both the host plant and the fungi by facilitating nutrient and resource exchange. However, in a nutrient rich environment, mycorrhizal associations can be altered such that fertilizers diminish the advantages of AMF, causing the relationship to become harmful to the host plant through depletion of essential fats and sugars. Consequently, the strategic application of fertilizer may be a tool in enhancing control of leafy spurge, effectively transforming the mycorrhizal association from beneficial to parasitic. When combined with herbicide treatments, this approach holds promise for addressing leafy spurge invasion more effectively and sustainably. Research plots were established in leafy spurge invaded native prairie across four locations in Saskatchewan. Fertilizer and herbicide treatments were applied in June 2022, with fertilizer reapplied in 2023. Herbicide treatments significantly reduced leafy spurge biomass and cover in year one, while in year two only Tordon and Navius significantly reduced leafy spurge. However, these herbicides also decreased species richness through native forb loss resulting in a shift in the plant community toward grass dominance. Select fertilizer treatments, specifically micronutrient and nitrogen, decreased leafy spurge cover but only at the plot level suggesting scale dependent effects. Herbicide and fertilizer effects on AMF were complex, where certain fertilizers, particularly micronutrient and phosphorus, decreased AMF colonization, but only when applied with select herbicides – 2,4-D combined with micronutrients and Tordon combined with phosphorus – suggesting that it is possible to manage AMF through use of fertilizers. Herbicide and fertilizer effects on forage quality were similarly dependent on specific treatment combinations, with crude protein and fiber content all responding to some combination of treatment. Given the complexity of these effects, more research is needed before recommendations can be made to producers.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".