Environmental Impact of Triclopyr on Habitat Quality in Boreal Rights-of-Way
Bibliographic record
Abstract
The indirect effects of herbicides on habitat quality in boreal ecoregions remain poorly understood. Herbicides are commonly applied on boreal rights-of-way to control vegetation below power lines, where they can indirectly enter the soil ecosystem after leaf abscission. Key soil processes such as litter decomposition and soil nutrient cycling can be influenced by altering litter chemistry and/or impacting decomposer species. Disruption of these soil processes could lead to changes in ecosystem health of boreal systems. The indirect impacts of triclopyr on habitat quality of treated boreal rights-of-way were examined through litter mass loss and quality (carbon-to-nitrogen ratios) and the response of boreal invertebrates (Folsomia candida and Oppia nitens) in microcosms and avoidance tests. Litter breakdown rates were not significantly different within a year of treatment. However, we did observe nitrogen profile differences between field-treated and untreated samples, which likely resulted from triclopyr-induced repression of natural leaf senescence processes. At field application rates, there were no differences in survival and reproduction rates of F. candida, which is key in litter breakdown. The triclopyr concentrations that caused 50% of tested F. candida and O. nitens to avoid treated litter were above field application rates. Therefore, field application rates of triclopyr are not expected to impair habitat quality and ecosystem services of boreal ecoregions based on the parameters we evaluated. Our study improves understanding of the effects of herbicide application on habitat quality and is critical for responsible herbicide use on boreal rights-of-way. Environ Toxicol Chem 2022;41:2955-2967. © 2022 SETAC.
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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 | 0.000 | 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".