Efficacy and non‐target effects of herbicides in foothills grassland restoration are short‐lived
Bibliographic record
Abstract
Abstract Questions Selective herbicides are frequently used in ecological restoration to control invasive non‐native forbs and recover plant communities. However, the long‐term efficacy of this practice, its non‐target effects on native plants, and its role in facilitating secondary invasions are not well understood. Similarly, little is known about the extent to which herbicide drift may affect native plant communities. Location Foothills grasslands of Montana, USA. Methods We conducted a 6‐year experiment to investigate changes in the abundance of a target invasive plant, knapweed ( Centaurea stoebe subsp. micranthos ) and plant community structure in response to the herbicides Tordon® (picloram) and Milestone® (aminopyralid), applied at a recommended rate and a diluted rate that simulated drift. Results Knapweed cover and the richness of native and non‐native forb species declined in the first 3 years in response to treatment at recommended rates, but not drift rates. Secondary invasion by non‐native monocots was significant but weak. The cover of native forbs and the cover and richness of native monocots did not differ among treatments but changed significantly with the year. Surprisingly, 6 years after treatments, there were no differences among treatments in the cover of the target invasive plant or community structure. Conclusions Our results demonstrate that the efficacy and non‐target effects of herbicides in grassland restoration can be short‐lived and idiosyncratic because of year effects. Restoration of knapweed invasions might require other active interventions, such as seeding or repeated spraying. Our study supports previous calls for long‐term monitoring of herbicides application in ecological restoration.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 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".