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A Multi-Scale Probabilistic Approach for the Identification of Potential Pesticide Use Sites for Ecological Risk Assessments.
Citation:
Paulukonis, E., K. McCaffrey, L. Oliver, Sandy Raimondo, S. Sinnathamby, AND Tom Purucker. A Multi-Scale Probabilistic Approach for the Identification of Potential Pesticide Use Sites for Ecological Risk Assessments. SETAC North America 42nd Annual meeting, Portland, OR, November 14 - 18, 2021. https://doi.org/10.23645/epacomptox.17117159
Impact/Purpose:
Ecological risk assessments are used to assess potential exposure of non-target species, and examine the potential overlap between chemical (most frequently pesticides) and these receptors; this is frequently called co-occurrence analysis. We expand upon a previously developed probabilistic approach to include multiple crop types, with improved crop specificity vs the current deterministic ERA approach. We additionally incorporate a multi-scale repeated sampling approach to define crop coverage at realistic field boundaries and capture variability in crop rotation schemes and potential area of application. We demonstrate the potential implications of this method for non-target bifenthrin exposure assessments using vernal pool critical habitat in a 5-county region in the central California valley.
Description:
Ecological risk assessment (ERA) requires estimating the overlap between chemical and receptor distribution to evaluate the impacts of exposure on nontarget organisms. Pesticide use estimation at field level is prone to error due to inconsistencies between ground-reporting and geospatial data coverage; attempts to rectify these inconsistencies have been limited in approach and rarely scaled to multiple crop types. We built upon a previously developed Bayesian approach to combine multiple crop types for a probabilistic determination of field-crop assignments and to examine co-occurrence of critical vernal pool habitats and bifenthrin application within a 5-county area in California (Madera, Merced, Sacramento, San Joaquin, and Stanislaus counties). We incorporated a multi-scale repeated sampling approach with an area constraint to both improve the delineation of field boundaries and better capture variability in crop assignments and rotation schemes. After comparing the accuracy of the spatial probabilistic approach to USDA Census of Agriculture crop acreage data, we found our approach allows more specificity in the combination of crop types represented by the potential application area and improves acreage estimates when compared to traditional deterministic approaches. In addition, our multi-scale sampling scheme improved spatial autocorrelation at finer scales and allowed for estimates of crop rotations that were previously uncaptured. Our approach could be leveraged for more realistic, spatially resolved exposure and effects models both in and outside of California.
URLs/Downloads:
DOI: A Multi-Scale Probabilistic Approach for the Identification of Potential Pesticide Use Sites for Ecological Risk Assessments.
PAULUKONIS_SETAC_2021_PLATFORM_INTERNAL_REVIEW_COMPLETE.PDF (PDF, NA pp, 2872.248 KB, about PDF)