Society demands enhanced ecosystem services from agricultural landscapes, but farmers’ desire to change land management is limited by perceived conflicts between ecologic and economic goals and ineffective management tools. To overcome these challenges, we combined a novel computational framework (Landscape Environmental Assessment Framework, LEAF) and a process-based biogeochemical model (DeNitrification-DeComposition, DNDC) to map subfield-scale polygons as potential management units. In each polygon, we estimated nitrogen dynamics with subfield changes in management, revealing opportunities to increase overall field-level environmental performance and profitability. Our analysis disaggregates previous approaches of county- or watershed-scale nitrogen balance down to a finer resolution and takes into account the biogeochemical processes driving nitrogen loss in agroecosystems. We used Iowa – an agriculturally homogeneous state representative of the Corn Belt – to demonstrate model integration and performance on corn and/or soybean fields between 2012 and 2015. We also analyzed potential land-use changes to address concerns for nitrogen loss associated with the Iowa Nutrient Reduction Strategy.
Results/Conclusions
We estimated that highly unprofitable cropland operating at a loss of US$ 250 ha−1 or more was negligible in 2012 at 400 000 ha (4% of row cropland), but rose to 2.8 and 2.2 Mha (30 and 23% of row cropland) in 2014 and 2015, respectively. Converting all subfield areas losing > US$ 150 ha-1 yr1 and leaching > 60 kg nitrate ha-1 yr-1 on average from 2012-2015 to a high-yielding perennial energy crop (e.g., switchgrass, Panicum virgatum) would result in a 12% state-wide reduction in nitrate leaching for Iowa. Aggregation of results to a broader level can reveal ‘hotspots’ for potential management change: within the Des Moines Lobe landform, most unprofitable subfield areas converted to switchgrass displayed nitrate leaching reductions of > 50%. Our approach differs substantially from ‘top-down’ mechanisms for addressing ecosystem service deficits in agricultural landscapes and instead aligns with profitability to harness farmer interest. While developed for Iowa, our modeling framework is globally applicable to well-developed agricultural systems.