Loss of biodiversity and degradation of ecosystem services from agricultural lands remain important challenges in the United States despite decades of spending on natural resource management. To date, conservation investment has emphasized engineering practices or vegetative strategies centered on monocultural plantings of nonnative plants, largely excluding native species from cropland. In a catchment-scale experiment, we quantified the multiple effects of integrating strips of native prairie species amid corn and soybean crops, with prairie strips arranged to arrest run-off on slopes. Replacing 10% of cropland with prairie strips increased biodiversity and ecosystem services with minimal impacts on crop production. Compared with catchments containing only crops, integrating prairie strips into cropland led to greater catchment-level insect taxa richness (2.6-fold), pollinator abundance (3.5-fold), native bird species richness (2.1-fold), and abundance of bird species of greatest conservation need (2.1-fold). Use of prairie strips also reduced total water runoff from catchments by 37%, resulting in retention of 20 times more soil and 4.3 times more phosphorus. Corn and soybean yields for catchments with prairie strips decreased only by the amount of the area taken out of crop production. Social survey results indicated demand among both farming and nonfarming populations for the environmental outcomes produced by prairie strips. If federal and state policies were aligned to promote prairie strips, the practice would be applicable to 3.9 million ha of cropland in Iowa alone.

No abstract

relationships can be developed between spatial yield patterns for a given year and soil properties such as Crop yields are frequently heterogeneous across space and time. texture, apparent electrical conductivity, organic matter We performed this study to determine if cluster analysis could be used to decipher the temporal and spatial patterns of corn (Zea mays content, or terrain attributes (Yang et al., 1998). HowL .) yield within a field. Nonhierarchal cluster analysis was applied to ever, the relationships are not the same among years 6 yr of corn yield data collected for 224 yield plots on a regular grid (Jaynes et al., 1995b; Halvorson and Doll, 1991), unless on the southern half of a 32-ha field. We were able to group the yield the yield data is divided into subsets based on growing observations into five temporal yield patterns or clusters. The clusters season climatic conditions or field attributes (Kaspar et were not randomly distributed across the field but instead formed al., 2003; Timlin et al., 1998). For example, Kaspar et contiguous areas roughly equivalent to landscape positions. Cluster al. (2003) were able to develop a multiple-regression membership was determined primarily by yield differences in years equation based on terrain attributes that accounted for with growing season precipitation greater than the 40-yr average. A 78% of the yield variability for 6 yr of corn grown on multiple discriminant analysis was used to predict the spatial occura 16-ha field by restricting the analysis to the 4 yr having rence of the clusters from easily determined field attributes: soil electrical conductivity, elevation, slope, and plan and profile curvature. below-normal seasonal precipitation. When they in-The multiple discriminant functions were unable to distinguish be-cluded the 2 yr with above-normal growing season pretween the two clusters located on the lowest portions of the landscape. cipitation, only 26% of the yield variability could be Because of similar temporal yield patterns in these two clusters, they accounted for by multiple regression. were combined and the multiple discriminant analysis repeated for Rather than trying to predict specific yields within a four clusters. Using a holdout sample approach, we achieved 76 and field, we may be more successful in identifying areas 80% success rates in classifying the yield plots into the correct yield within a field that behave similarly among years. Most clusters. If response curves for inputs such as N prove to be unique studies have approached this problem by first identifor the different yield clusters, then clustering of multiple-year yield fying areas of similar soil properties or terrain attributes data may prove an effective method for determining management and then testing for reduction in yield variability or yield zones within fields. response to inputs within these areas (Fraisse et al., 2001; Fleming et al., 2000). These methods rely on using general knowledge of crop production to identify the

Spatial data on soils, land use, and topography, combined with knowledge of conservation effectiveness, can be used to identify alternatives to reduce nutrient discharge from small (hydrologic unit code [HUC]12) watersheds. Databases comprising soil attributes, agricultural land use, and light detection and rangingderived elevation models were developed for two glaciated midwestern HUC12 watersheds: Iowa's Beaver Creek watershed has an older dissected landscape, and Lime Creek in Illinois is young and less dissected. Subsurface drainage is common in both watersheds. We identified locations for conservation practices, including in-field practices (grassed waterways), edgeof-field practices (nutrient-removal wetlands, saturated buffers), and drainage-water management, by applying terrain analyses, geographic criteria, and cross-classifications to field-and watershed-scale geographic data. Cover crops were randomly distributed to fields without geographic prioritization. A set of alternative planning scenarios was developed to represent a variety of extents of implementation among these practices. The scenarios were assessed for nutrient reduction potential using a spreadsheet approach to calculate the average nutrient-removal efficiency required among the practices included in each scenario to achieve a 40% NO 3 -N reduction. Results were evaluated in the context of the Iowa Nutrient Reduction Strategy, which reviewed nutrient-removal efficiencies of practices and established the 40% NO 3 -N reduction as Iowa's target for Gulf of Mexico hypoxia mitigation by agriculture. In both test watersheds, planning scenarios that could potentially achieve the targeted NO 3 -N reduction but remove <5% of cropland from production were identified. Cover crops and nutrient removal wetlands were common to these scenarios. This approach provides an interim technology to assist local watershed planning and could provide planning scenarios to evaluate using watershed simulation models. A set of ArcGIS tools is being released to enable transfer of this mapping technology. A gricultural producers in the midwesternUnited States are being asked to significantly reduce nutrient (N and P) loads to surface waters and thereby mitigate major ecological impacts on aquatic systems in the Gulf of Mexico and the Great Lakes (Michalak et al., 2013;Turner et al., 2012). Although these problems are continental in scope, the challenge in addressing them lies in the management of thousands of small agricultural watersheds and millions of individual farm fields across the Midwest. To be successful, any general strategy must be adaptable to the array of unique combinations of landscape, farm management systems, and the conservation preferences of individuals who own and/or operate farm businesses across this broad region of agricultural production. Although scientific approaches based on watershed modeling and monitoring of conservation effectiveness will be necessary to inform all the management decisions and land use changes that can lead to...