Preciseness, rather than simplicity, is required to assess pesticide reduction strategies: Findings from rice production in Japan

• Published in: The Science of the total environment 2023-08, Vol.887, p.163636-163636, Article 163636
• Main Authors: Tang, Longlong, Hayashi, Kiyotada, Nagai, Takashi, Inao, Keiya
• Format: Article
• Language: English
• Subjects: Agriculture - methods; Farms; Fresh Water; Freshwater ecotoxicity; Japan; Life cycle impact assessment; Oryza; Pesticide; Pesticides - analysis; Rice field; Species sensitivity distribution
• ISSN: 0048-9697; 1879-1026
• DOI: 10.1016/j.scitotenv.2023.163636

Pesticide reduction is given high priority in the worldwide sustainability agenda. The reduction of pesticide impacts, rather than the reduction of application rates, has become a common criterion for monitoring policy progress. However, simplicity—an essential requirement in improving the applicability of pesticide impact assessment—may distort the accuracy of the evaluation and therefore prevent effective pesticide reduction. Here, we present contrasting results that underscore how the selection of evaluation methods that differ in simplicity affects the assessment results of pesticide reduction strategies. Briefly, we analysed the impact of conversion from conventional to low-input management adopting both a simplified linear-based method and a precise method that includes newly calculated nonlinear approach-based characterization factors for 109 active ingredients (AIs). The two methods were then used to estimate the freshwater ecotoxicity impact of eight rice farms in Japan where both conventional pesticide application and pesticide reduction strategies are practiced. The results show that the simplified method generated anomalies at the farm level through overestimation and underestimation of the individual AI impacts. Patterns that contributed to extreme changes of impact at the farm level were also identified. These findings suggest a strong need for a precise evaluation method for effectively monitoring policy progress at the farm level. [Display omitted] •Simplicity may distort an evaluation method's accuracy & hinder pesticide reduction.•We used two evaluation methods: simplified linear-based & nonlinear-based precise.•Method simplification caused anomalies via AI impacts' over- & underestimation.•Low-input management reduced the overall impact of pesticide use.•Precise methods for effectively monitoring farm-level policy progress are needed.