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Logging and mill residues are currently the largest sources of woody biomass for bioenergy in the US, but short-rotation woody crops (SRWCs) are expected to become a larger contributor to biomass production, primarily on lands marginal for food production. However, there are very few studies on the environmental effects of SRWCs, and most have been conducted at stand rather than at watershed scales.

Corn’s (Zea mays L.) stover is a potential nonfood, herbaceous bioenergy feedstock. A vital aspect of utilizing stover for bioenergy production is to establish sustainable harvest criteria that avoid exacerbating soil erosion or degrading soil organic carbon (SOC) levels. Our goal is to empirically estimate the minimum residue return rate required to sustain SOC levels at numerous locations and to identify which macroscale factors affect empirical estimates.

To prepare for a 2014 launch of commercial scale cellulosic ethanol production from corn/maize (Zea mays L.) stover, POET-DSM near Emmetsburg, IA has been working with farmers, researchers, and equipment dealers through “Project Liberty” on harvest, transportation, and storage logistics of corn stover for the past several years. Our objective was to evaluate seven stover harvest strategies within a 50-ha (125 acres) site on very deep, moderately well to poorly drained Mollisols, developed in calcareous glacial till.

Agricultural residues have been identified as a significant potential resource for bioenergy production, but serious questions remain about the sustainability of harvesting residues. Agricultural residues play an important role in limiting soil erosion from wind and water and in maintaining soil organic carbon. Because of this, multiple factors must be considered when assessing sustainable residue harvest limits.

Corn (Zea mays L.) stover is a potential bioenergy feedstock, but little is known about the impacts of reducing stover return on yield and soil quality in the Northern US Corn Belt. Our study objectives were to measure the impact of three stover return rates (Full (~7.8 Mg ha−1 yr−1), Moderate (~3.8 Mg ha−1 yr−1) or Low (~1.5 Mg ha yr−1) Return) on corn and soybean (Glycine max. L [Merr.]) yields and on soil dynamic properties on a chisel-tilled (Chisel) field, and well- (NT1995) or newly- (NT2005) established no-till managed fields.

Net benefits of bioenergy crops, including maize and perennial grasses such as switchgrass, are a function of several factors including the soil organic carbon (SOC) sequestered by these crops. Life cycle assessments (LCA) for bioenergy crops have been conducted using models in which SOC information is usually from the top 30 to 40 cm. Information on the effects of crop management practices on SOC has been limited so LCA models have largely not included any management practice effects.

This paper was presented at the 2012 International Congress on Environmental Modelling and Software in Leipzig, Germany on July 15, 2012.

Accurate and up-to-date global land cover data sets are necessary for various global change research studies including climate change, biodiversity conservation, ecosystem assessment, and environmental modeling. In recent years, substantial advancement has been achieved in generating such data products. Yet, we are far from producing geospatially consistent high-quality data at an operational level.

Many investigators need and use global land cover maps for a wide variety of purposes. Ironically, after many years of very limited availability, there are now multiple global land cover maps and it is not readily apparent (1) which is most useful for particular applications or (2) how to combine the different maps to provide an improved dataset. The existing global land cover maps at 1 km spatial resolution have arisen from different initiatives and are based on different remote sensing data and employed different methodologies. Perhaps more significantly, they have different legends.

Two of the most widely used land-cover data sets for the United States are the National Land-Cover Data (NLCD) at 30-m resolution and the Global Land- Cover Characteristics (GLCC) at 1-km nominal resolution. Both data sets were produced around 1992 and expected to provide similar land-cover information. This study investigated the spatial distribution of NLCD within major GLCC classes at 1-km unit over a total of 11 agricultural-related eco-regions across the continental United States.