Spatiotemporally derived agricultural field delineations for species effects assessments and environmental decision support

Rural landscapes are strongly defined by the spatial distribution of agricultural fields. GIS layers that capture this information have much utility in many decision support contexts, particularly with regards to the intersection of agricultural pesticide use and endangered species habitat. The United States Department of Agriculture's Cropland Data Layer (CDL) is a georeferenced, annual resource that often serves a crucial role in pesticide risk-related decision support applications. However, CDL agriculture timeseries data are not mapped to explicit field boundaries, contributing to increased uncertainty regarding differentiated crop type spatial homogeneity and geographic extent, inherently adding complexity to multi-temporal crop monitoring and analyses efforts. We describe the development and testing of an approach for field delineation based on timeseries information from the 2008–2021 CDL at spatial scales relevant for endangered species risk assessment. We validate and test the approach against quantitative crop information and contextualize the outputs as part of a case study reconstructing past agricultural pesticide exposures to non-target species to demonstrate the utility of the method for ecological risk assessment decision support. The approach resulted in delineated field unit boundaries that effectively incorporated the unmodified CDL crop type generalized spatial distribution patterns; derived metrics closely corresponded with reported crop metrics for landscapes with proportionally significant agriculture use. When modified to reflect areas of mixed/small crop acreages, the method can provide a useful framework for large-scale field delineation of the CDL, which can complement ongoing environmental risk assessment and conservation efforts in agricultural landscapes. [Display omitted] •A method to extract individual agricultural field delineations based on the USDA Cropland Data Layer was developed•The method effectively delineated field unit boundaries for generalized spatial distribution patterns of crops•Outcomes corresponded with reported crop metrics for areas with significant agricultural use•An endangered species case study demonstrated the method’s uses for ecological risk assessment of agricultural pesticides•This work has utility for many types of decision support analyses in agricultural and environmental sectors