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State policies can support renewable energy development by driving markets, providing certainty in the investment market, and incorporating the external benefits of the technologies into cost/benefit calculations. Using statistical analyses and policy design best practices, this paper quantifies the impact of state-level policies on renewable energy development in order to better understand the role of policy on development and inform policy makers on the policy mechanisms that provide maximum benefit. The results include the identification of connections between state policies and renewable energy development, as well as a discussion placing state policy efforts in context with other factors that influence the...
Conclusions:Owls avoided agricultural lands (due to prey availability), used grass-forb areas for foraging, and avoided croplands and grazed pasture. 95% of all movements occurred within 600 meters of the nest burrows.Thresholds/Learnings:At a minimum, a 600m radius should be maintained around burrowing owl nests in order to ensure the survival of burrowing owls
Conclusions:Wetland extent, proximity of wetlands to the sampling station, and the position of a wetland in a watershed (downstream wetlands have greater influence on water quality) influence water quality.Thresholds/Learnings:
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Synopsis: This study evaluates whether previous observations of a higher percentage of parasitism and parasitoid diversity in a complex agricultural landscape, relative to a simple landscape, represent a general phenomenon. Rates of parasitism and parasitoid diversity of the armyworm (Pseudaletia unipuncta) were assessed in three replicate (Onondaga, Ingham, and Benton) regions in southern Michigan. Within each region, a simple landscape (primarily cropland) and a complex landscape (cropland intermixed with mid and late successional noncrop habitats) were identified through analysis of aerial photographs. In each landscape, three maize fields were selected, and second to fourth instar P. unipuncta were released...
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Rental rates for non-irrigated cropland in 2016, clipped to Midwest Grasslands Network Focal Area
Nuisance blooms of heterocystous Cyanobacteria in Lake Winnipeg have nearly doubled in size since the mid 1990s. The increases are the result of a recent rapid increase in loading and concentration of phosphorus. The rapid increase in phosphorus is largely the result of two factors. The first factor is the result of rapidly increased livestock production and use of synthetic fertilizer in the Red River Valley, with smaller contributions of phosphorus from the city of Winnipeg and other human development in the Red and Winnipeg river basins. The second factor is the increased frequency and intensity of spring floods in the Red River watershed in recent years, which have greatly enhanced the transfer of phosphorus...
Six small, predominantly agricultural (> 70%) watersheds in the Conesus Lake catchment of New York State, USA, were selected to test the impact of Best Management Practices (BMPs) on mitigation of nonpoint nutrient sources and soil loss from farms to downstream aquatic systems. Over a 5-year period, intensive stream water monitoring and analysis of covariance provided estimates of marginal means of concentration and loading for each year weighted by covariate discharge. Significant reductions in total phosphorus, soluble reactive phosphorus, nitrate, total Kjeldahl nitrogen, and total suspended solids concentration and flux occurred by the second year and third year of implementation. At Graywood Gully, where Whole...
The purpose of the Conservation Effects Assessment Project (CEAP) cropland national assessment is to quantify the environmental benefits of conservation programs at the regional and national levels, which include both onsite and instream water quality benefits. Modeling is an effective tool for environmental assessment at the regional and national scale due to the complexities in nature at this scale. Two simulation models, the Agricultural Policy Environmental extender (APEX) and the Soil and Water Assessment Tool (SWAT), were used for the CEAP cropland national assessment. A subset of National Resources Inventory (NRI) sample points was selected to serve as "representative fields" for the CEAP cropland survey...
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The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The 2010 CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 5 TM sensor, Landsat 7 ETM+ sensor, and the Indian Remote Sensing RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS) collected during the current growing season.Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the USGS National Land Cover Dataset 2001 (NLCD 2001), and the National Aeronautics and Space Administration...
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National Land Cover Database 2001 (NLCD2001) is a 16-class (additional four classes in Alaska only) land cover classification scheme that has been applied consistently across all 50 United States and Puerto Rico at a spatial resolution of 30 meters. NLCD2001 is based primarily on the unsupervised classification of Landsat Enhanced Thematic Mapper+ (ETM+) circa 2001 satellite data. NLCD2001 improves on NLCD92 in that it is comprised of three different elements: land cover, percent developed impervious surface and percent tree canopy density. NLCD2001 also uses improved classification algorithms, which have resulted in data with more precise rending of spatial boundaries between the land cover classes.
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The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer with a ground resolution of 56 meters. The CDL is produced using satellite imagery from the Indian Remote Sensing RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS) collected during the current growing season. Some Cropland Data Layer states used Landsat 5 TM and/or Landsat 7 ETM+ satellite imagery to supplement the classification. Ancillary classification inputs include: the United States Geological Survey (USGS) National Elevation Dataset (NED), the USGS National Land Cover Dataset 2001 (NLCD 2001), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer...
map background search result map search result map USDA, National Agricultural Statistics Service, 2009 Cropland Data Layer Wyoming Does agricultural landscape structure affect parasistism and parasitoid diversity? 2001 NLCD Rogue Agricultural Lands USDA-NASS, 2010 Cropland Data Layer, Nevada Crop Rental Rates 2016 2001 NLCD Rogue Agricultural Lands Does agricultural landscape structure affect parasistism and parasitoid diversity? USDA, National Agricultural Statistics Service, 2009 Cropland Data Layer Wyoming USDA-NASS, 2010 Cropland Data Layer, Nevada Crop Rental Rates 2016