The broad impacts of corn stover and wheat straw removal for biofuel production on crop productivity,soil health and greenhouse gas emissions: A review

Biofuel production from crop residues is widely recognized as an essential component of developing a bioeconomy, but the removal of crop residues still raises many questions about the sustainability of the cropping system. Therefore, this study reviews the sustainability effects of crop residues removal for biofuel production in terms of crop production, soil health and greenhouse gas emissions. Most studies found little evidence that residue management had long‐term impacts on grain yield unless the available water is limited. In years when water was not limiting, corn and wheat removal rates ≥90% produced similar or greater grain yield than no removal in most studies. Conversely, when water was limiting, corn grain yield decreased up to 21% with stover removal ≥90% in some studies. Changes in soil organic fractions and nutrients depended largely on the amount of residue returned, soil depth and texture, slope and tillage. Reductions in organic fractions occurred primarily with complete stover removal, in the top 15–30 cm in fine‐textured soils. Soil erosion, water runoff and leaching of nutrients such as total nitrogen (N) and extractable soil potassium decreased when no more than 30% of crop residues were removed. Stover management effects on soil bulk density varied considerably depending on soil layer, and residue and tillage management, with removal rates of less than 50% helping to maintain the soil aggregate stability. Reductions in CO₂ and N₂O fluxes typically occurred following complete residue removal. The use of wheat straw typically increased CH₄ emissions, and above or equal to 8 Mg/ha wheat straw led to the largest CO₂ and N₂O emissions, regardless of N rates. Before using crop residues for biofuel production, it should therefore always be checked whether neutral to positive sustainability effects can be maintained under the site‐specific conditions.     

Modeling wildlife and other trade‐offs with biofuel crop production

Biofuels from agricultural sources are an important part of California's strategy to reduce greenhouse gas emissions and dependence on foreign oil. Land conversion for agricultural and urban uses has already imperiled many animal species in the state. This study investigated the potential impacts on wildlife of shifts in agricultural activity to increase biomass production for transportation fuels. We applied knowledge of the suitability of California's agricultural landscapes for wildlife species to evaluate wildlife effects associated with plausible scenarios of expanded production of three potential biofuel crops (sugar beets, bermudagrass, and canola). We also generated alternative, spatially explicit scenarios that minimized loss of habitat for the same level of biofuel production. We explored trade‐offs to compare the marginal changes per unit of energy for transportation costs, wildlife, land and water‐use, and total energy produced, and found that all five factors were influenced by crop choice. Sugar beet scenarios require the least land area: 3.5 times less land per liter of gasoline equivalent than bermudagrass and five times less than canola. Canola scenarios had the largest impacts on wildlife but the greatest reduction in water use. Bermudagrass scenarios resulted in a slight overall improvement for wildlife over the current situation. Relatively minor redistribution of lands converted to biofuel crops could produce the same energy yield with much less impact on wildlife and very small increases in transportation costs. This framework provides a means to systematically evaluate potential wildlife impacts of alternative production scenarios and could be a useful complement to other frameworks that assess impacts on ecosystem services and greenhouse gas emissions.     

Global simulation of bioenergy crop productivity: analytical framework and case study for switchgrass

A global energy crop productivity model that provides geospatially explicit quantitative details on biomass potential and factors affecting sustainability would be useful, but does not exist now. This study describes a modeling platform capable of meeting many challenges associated with global‐scale agro‐ecosystem modeling. We designed an analytical framework for bioenergy crops consisting of six major components: (i) standardized natural resources datasets, (ii) global field‐trial data and crop management practices, (iii) simulation units and management scenarios, (iv) model calibration and validation, (v) high‐performance computing (HPC) simulation, and (vi) simulation output processing and analysis. The HPC‐Environmental Policy Integrated Climate (HPC‐EPIC) model simulated a perennial bioenergy crop, switchgrass (Panicum virgatum L.), estimating feedstock production potentials and effects across the globe. This modeling platform can assess soil C sequestration, net greenhouse gas (GHG) emissions, nonpoint source pollution (e.g., nutrient and pesticide loss), and energy exchange with the atmosphere. It can be expanded to include additional bioenergy crops (e.g., miscanthus, energy cane, and agave) and food crops under different management scenarios. The platform and switchgrass field‐trial dataset are available to support global analysis of biomass feedstock production potential and corresponding metrics of sustainability.     

Projecting future grassland productivity to assess the sustainability of potential biofuel feedstock areas in the Greater Platte River Basin

This study projects future (e.g., 2050 and 2099) grassland productivities in the Greater Platte River Basin (GPRB) using ecosystem performance (EP, a surrogate for measuring ecosystem productivity) models and future climate projections. The EP models developed from a previous study were based on the satellite vegetation index, site geophysical and biophysical features, and weather and climate drivers. The future climate data used in this study were derived from the National Center for Atmospheric Research Community Climate System Model 3.0 ‘SRES A1B’ (a ‘middle’ emissions path). The main objective of this study is to assess the future sustainability of the potential biofuel feedstock areas identified in a previous study. Results show that the potential biofuel feedstock areas (the more mesic eastern part of the GPRB) will remain productive (i.e., aboveground grassland biomass productivity >2750 kg ha^?1 year^?1) with a slight increasing trend in the future. The spatially averaged EPs for these areas are 3519, 3432, 3557, 3605, 3752, and 3583 kg ha^?1 year^?1 for current site potential (2000–2008 average), 2020, 2030, 2040, 2050, and 2099, respectively. Therefore, the identified potential biofuel feedstock areas will likely continue to be sustainable for future biofuel development. On the other hand, grasslands identified as having no biofuel potential in the drier western part of the GPRB would be expected to stay unproductive in the future (spatially averaged EPs are 1822, 1691, 1896, 2306, 1994, and 2169 kg ha^?1 year^?1 for site potential, 2020, 2030, 2040, 2050, and 2099). These areas should continue to be unsuitable for biofuel feedstock development in the future. These future grassland productivity estimation maps can help land managers to understand and adapt to the expected changes in future EP in the GPRB and to assess the future sustainability and feasibility of potential biofuel feedstock areas.     

The greenhouse gas intensity and potential biofuel production capacity of maize stover harvest in the US Midwest

Agricultural residues are important sources of feedstock for a cellulosic biofuels industry that is being developed to reduce greenhouse gas emissions and improve energy independence. While the US Midwest has been recognized as key to providing maize stover for meeting near‐term cellulosic biofuel production goals, there is uncertainty that such feedstocks can produce biofuels that meet federal cellulosic standards. Here, we conducted extensive site‐level calibration of the Environmental Policy Integrated Climate (EPIC) terrestrial ecosystems model and applied the model at high spatial resolution across the US Midwest to improve estimates of the maximum production potential and greenhouse gas emissions expected from continuous maize residue‐derived biofuels. A comparison of methodologies for calculating the soil carbon impacts of residue harvesting demonstrates the large impact of study duration, depth of soil considered, and inclusion of litter carbon in soil carbon change calculations on the estimated greenhouse gas intensity of maize stover‐derived biofuels. Using the most representative methodology for assessing long‐term residue harvesting impacts, we estimate that only 5.3 billion liters per year (bly) of ethanol, or 8.7% of the near‐term US cellulosic biofuel demand, could be met under common no‐till farming practices. However, appreciably more feedstock becomes available at modestly higher emissions levels, with potential for 89.0 bly of ethanol production meeting US advanced biofuel standards. Adjustments to management practices, such as adding cover crops to no‐till management, will be required to produce sufficient quantities of residue meeting the greenhouse gas emission reduction standard for cellulosic biofuels. Considering the rapid increase in residue availability with modest relaxations in GHG reduction level, it is expected that management practices with modest benefits to soil carbon would allow considerable expansion of potential cellulosic biofuel production.     

A county‐level estimation of renewable surface water and groundwater availability associated with potential large‐scale bioenergy feedstock production scenarios in the United States

This study examines fresh renewable water resources available for bioenergy feedstock production in the United States. The impacts of feedstock irrigation on surface and groundwater resources available to nonbioenergy sectors were quantified using a pair of water availability indexes: streamflow availability index and percolation flow availability index. The two metrics were applied to both historical (2008) and three possible future biomass production scenarios from the 2016 U.S. Billion‐Ton Report at the county level. For both historical and future scenarios, we found that the consumptive irrigation requirements for bioenergy feedstock account for <0.01% of annual streamflow in all but three counties in Nebraska. Results suggest that the irrigation demand of future biomass production could be supplied by annual renewable groundwater flow in about 94% of feedstock‐growing counties that use groundwater for irrigation, representing about 92% of production tonnage. Counties that require irrigation from nonrenewable groundwater resources are mostly located in the Northern Plains and Pacific regions. We also evaluated the sensitivity of crop water footprint estimation to soil moisture carryover by comparing blue water estimates from six different empirical and process‐based methods. Our findings suggest that accounting for preseason soil moisture is critical for representative blue water estimation, so that the irrigation water consumption is not overestimated. This is especially true in the Corn Belt region, where blue water estimates with and without preseason soil moisture would be about 1.9 versus 45.5 billion m³/year under the historical scenario. This difference is smaller in semiarid regions like the High Plains, but the blue water estimate can still triple if soil moisture is not considered. From the perspective of renewable surface water and groundwater resources, scaling feedstock production up in the High Plains and California will require careful planning integrated with water management strategies to improve water resource conservation.     

Impacts of land use change due to biofuel crops on carbon balance,bioenergy production,and agricultural yield,in the conterminous United States

Growing concerns about energy and the environment have led to worldwide use of bioenergy. Switching from food crops to biofuel crops is an option to meet the fast‐growing need for biofuel feedstocks. This land use change consequently affects the ecosystem carbon balance. In this study, we used a biogeochemistry model, the Terrestrial Ecosystem Model, to evaluate the impacts of this change on the carbon balance, bioenergy production, and agricultural yield, assuming that several land use change scenarios from corn, soybean, and wheat to biofuel crops of switchgrass and Miscanthus will occur. We found that biofuel crops have much higher net primary production (NPP) than soybean and wheat crops. When food crops from current agricultural lands were changed to different biofuel crops, the national total NPP increased in all cases by a range of 0.14–0.88 Pg C yr^?1, except while switching from corn to switchgrass when a decrease of 14% was observed. Miscanthus is more productive than switchgrass, producing about 2.5 times the NPP of switchgrass. The net carbon loss ranges from 1.0 to 6.3 Tg C yr^?1 if food crops are changed to switchgrass, and from 0.4 to 6.7 Tg C yr^?1 if changed to Miscanthus. The largest loss was observed when soybean crops were replaced with biofuel crops. Soil organic carbon increased significantly when land use changed, reaching 100 Mg C ha^?1 in biofuel crop ecosystems. When switching from food crops to Miscanthus, the per unit area croplands produced a larger amount of ethanol than that of original food crops. In comparison, the land use change from wheat to Miscanthus produced more biomass and sequestrated more carbon. Our study suggests that Miscanthus could better serve as an energy crop than food crops or switchgrass, considering both economic and environmental benefits.     

Application of a process‐based model for predicting the productivity of Eucalyptus nitens bioenergy plantations in Spain

The feasibility of using plantation‐grown biomass to fuel bioenergy plants is in part dependent on the ability to predict the capacity of surrounding forests to maintain a sustainable supply. In this study, the potential productivity of Eucalyptus nitens (Deane and Maiden) Maiden plantations grown for bioenergy in a region of north‐west Spain was quantified using the 3‐PG process‐based model. The model was calibrated using detailed measurements from five permanent sample plots and validated using data from thirty‐five additional permanent sample plots; both sets represented the variability of climate and soils of the region. Plot scale analysis showed that the model was able to reasonably estimate above‐ground biomass and water use when compared with the observed data. Using a representative loam soil characteristic, a spatial analysis was then carried out to predict the potential productivity of E. nitens for bioenergy across a potential area for plantation establishment of 2550 km² and to evaluate different management scenarios related to rotation length and stocking. An increase of only 1.9% in mean annual increment (MAI) of above‐ground biomass (W_AGB) was found between stockings of 3000 and 5000 trees ha^?1; for the lower stocking, MAI of W_AGB increased 4% for rotation lengths between 6 and 8 years. Production was reduced by low summer rainfall and to a lesser extent by high summer and low winter temperatures, and vapour pressure deficit. Above‐ground biomass production was higher by around 12% when average rather than actual climate data were applied. The information from this study can be used to optimize forest management, determine regional relative potential productivity and contribute to decision‐making for bioenergy production from E. nitens plantations in north‐west Spain.     

Use of a geographic information system data base to measure and evaluate wetland changes in the St. Marys River,Michigan

A digital data base was constructed by photo interpretation, mapping, and digitizing seven dates of aerial photography on the St. Marys River, Michigan, USA. The data base was used in conjunction with geographic information system software to examine historical changes in wetland area. Total wetland area between 1939 and 1985 ranged from 7 200 to 7 317 ha over a 46-year period of high and low water. There was greatest variation in areas of emergent wetland and scrub-shrub wetland, which appeared to be responding primarily to changes in water level.     

A user‐friendly means to scale from the biochemistry of photosynthesis to whole crop canopies and production in time and space – development of Java WIMOVAC

Windows Intuitive Model of Vegetation response to Atmosphere and Climate Change (WIMOVAC) has been used widely as a generic modular mechanistically rich model of plant production. It can predict the responses of leaf and canopy carbon balance, as well as production in different environmental conditions, in particular those relevant to global change. Here, we introduce an open source Java user‐friendly version of WIMOVAC. This software is platform independent and can be easily downloaded to a laptop and used without any prior programming skills. In this article, we describe the structure, equations and user guide and illustrate some potential applications of WIMOVAC.