<i>IEAM</i> Best Paper of 2024

As a result of spray drift and runoff from adjacent fields, soil living organisms in cultivated landscapes can be exposed unintentionally to pesticides.Current approaches to estimating such off-field exposure employ conservative, worst-case assumptions that do not account for real-world variability of exposure in space and time.Schad et al. ( 2024) develop a modeling approach, scenarios, and a case study to gain more realistic estimates of exposure, and hence risk, and to inform mitigation options.Their model is probabilistic and spatiotemporally explicit.It has the advantage of separating the factors influencing spray drift (e.g., wind, application timing and conditions, off-field soil patch dimensions, and spatial relationship to fields) and runoff (e.g., temporal relationship between product residues and precipitation as well as landscape morphology).Their results show that spatiotemporally explicit exposure patterns for spray drift and runoff are not simply additive.Their work demonstrates that landscape composition and structure clearly affect exposure to off-field soil organisms.Their model facilitates identification of local runoff hotspots that can be targeted for appropriate mitigation efforts.The approach is flexible and can operate at any desired spatial and temporal resolution, thus capturing variability of pesticide use, spray drift, and runoff to more accurately estimate off-field exposure patterns.The predicted exposure patterns can be directly linked with effect models to quantify risks related to specific protection goals.Because the authors have made the model available as open-source software, this should facilitate further model improvements and applications in the regulatory scientific community.