A Review of the Environmental Fate and Effects of Natural "Reduced-Risk" Pesticides in Canada
Bibliographic record
Abstract
Bioactive compounds derived from microbial, plant, or other natural sources are a largely untapped source of new pesticides. They are also widely considered to have characteristics conferring reduced risk to the environment and a high potential for use in modern integrated pest management strategies. In examining the "reduced-risk" hypothesis, the fundamental physico-chemical properties, mechanisms of dissipation and laboratory toxicity data for technical active ingredients phosphinothricin, azadirachtin, and spinosad were assessed. Hazard quotient analysis, which relates expected environmental concentrations to laboratory toxicity data, indicated little cause for concern in terms of predicted environmental fate but potential toxicological risks for certain non-target species such as bees, zooplankton, and aquatic plants. Environmental fate and ecotoxicological effects data for the derivative natural product pesticide formulations Ignite¯ and Herbiace¯, Neemix¯ 4.5 and Success¯, as derived from Canadian field studies, were also summarized. Results from the field studies generally confirm the hazard quotient risk analysis and demonstrate substantial ecotoxicological risks for formulated products based on phosphinothricin and azadirachtin active ingredients, particularly in freshwater aquatic ecosystems. Based on these evaluations, and in comparison to reference synthetic pesticides glyphosate and tebufenozide, we find no evidence to support the hypothesis that natural products pose inherently lower risk to the environment than these synthetic pesticides. While we fully support further research and development of natural product pesticides, we suggest that these or any other pest control product must be fully and comprehensively evaluated through a tiered research and environmental risk assessment process, culminating in controlled field studies, environmental monitoring and probabilistic risk analysis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".