An integrative modeling framework to evaluate the productivity and sustainability of biofuel crop production systems

Abstract

The potential expansion of biofuel production raises food, energy, and environmental challenges that require careful assessment of the impact of biofuel production on greenhouse gas (GHG) emissions, soil erosion, nutrient loading, and water quality. In this study, we describe a spatially explicit integrative modeling framework (SEIMF) to understand and quantify the environmental impacts of different biomass cropping systems. This SEIMF consists of three major components: (1) a geographic information system (GIS)-based data analysis system to define spatial modeling units with resolution of 56 m to address spatial variability, (2) the biophysical and biogeochemical model Environmental Policy Integrated Climate (EPIC) applied in a spatially-explicit way to predict biomass yield, GHG emissions, and other environmental impacts of different biofuel crops production systems, and (3) an evolutionary multiobjective optimization algorithm for exploring the trade-offs between biofuel energy production and unintended ecosystem-service responses. Simple examples illustrate the major functions of the SEIMF when applied to a nine-county Regional Intensive Modeling Area (RIMA) in SW Michigan to (1) simulate biofuel crop production, (2) compare impacts of management practices and local ecosystem settings, and (3) optimize the spatial configuration of different biofuel production systems by balancing energy production and other ecosystem-service variables. Potential applications of the SEIMF to support life cycle analysis and provide information on biodiversity evaluation and marginal-land identification are also discussed. The SEIMF developed in this study is expected to provide a useful tool for scientists and decision makers to understand sustainability issues associated with the production of biofuels at local, regional, and national scales.

Biofuels on the landscape: Is “land sharing” preferable to “land sparing”?

“…This will be particularly relevant when selecting optimal management practices for a specific bioenergy crop, and further research will be required to delineate the relationship between ES B and Y for the various bioenergy crops (for an analysis of this relationship for corn, see Zhang et al 2010). Both ethanol yield and ecosystem services depend upon management practices such as fertilization; for example, N fertilization may increase yield (Heaton et al 2004, Wang et al 2010, but it will also reduce GHGV by increasing N 2 O emissions (Zhang et al 2010, Hoben et al 2011. Although agricultural intensification has generally benefited the global GHG balance by averting deforestation (Burney et al 2010), excessive intensification may disproportionately reduce ES values in relation to Y (e.g., Hoben et al 2011), and reduce the benefits of the land-sparing strategy.…”

“…4B), a land-sharing strategy (LIHD prairie) is slightly favored in the case of the LIHD prairie-corn grain trade-off, whereas a land-sparing strategy (corn grain þ stover) is favored in the case of the LIHD prairie-corn grain þ stover trade-off. Therefore, when optimizing land use to meet the interconnected goals of bioenergy production and ecosystem services, it is important to consider the relationship between ES B and Y (Zhang et al 2010). This will be particularly relevant when selecting optimal management practices for a specific bioenergy crop, and further research will be required to delineate the relationship between ES B and Y for the various bioenergy crops (for an analysis of this relationship for corn, see Zhang et al 2010).…”

“…Therefore, when optimizing land use to meet the interconnected goals of bioenergy production and ecosystem services, it is important to consider the relationship between ES B and Y (Zhang et al 2010). This will be particularly relevant when selecting optimal management practices for a specific bioenergy crop, and further research will be required to delineate the relationship between ES B and Y for the various bioenergy crops (for an analysis of this relationship for corn, see Zhang et al 2010). Both ethanol yield and ecosystem services depend upon management practices such as fertilization; for example, N fertilization may increase yield (Heaton et al 2004, Wang et al 2010, but it will also reduce GHGV by increasing N 2 O emissions (Zhang et al 2010, Hoben et al 2011.…”

“…The landsharing approach favors ecosystems with high value in regulating greenhouse gases (GHGs); for example, crops with the potential to sequester soil carbon are valued for the climate mitigation potential (Anderson-Teixeira et al 2009, DeLuca andZabinski 2011). Unfortunately, there is often a trade-off between crop yield and protection of biodiversity and ecosystem services (Krebs et al 1999, Green et al 2005, Zhang et al 2010, Hoben et al 2011, and the land-sharing ideal would entail sacrificing yield when such a trade-off exists. Therefore, crops that represent the land-sharing ideal typically require more land to meet a given demand and may thereby place more pressure on natural ecosystems (Green et al 2005, Heaton et al 2008, Hodgson et al 2010.…”

National Geo-Database for Biofuel Simulations and Regional Analysis of Biorefinery Siting Based on Cellulosic Feedstock Grown on Marginal Lands

“…Zhang et al (2010) reported on SEIMF (Spatially Explicit Modeling Framework), a spatially explicit approach designed to model biomass productivity and environmental impacts of diverse biofuel crops. EgbendeweMondzozo et al (2011) expanded on the work by Zhang et al (2010) by developing a spatially explicit bioeconomic model of biomass supply from alternative cellulosic crops and crop residues as well as explored policy scenarios for handling various environmental outcomes. Current modeling work focuses on integrating the SEIMF approach with biogeochemical and biodiversity experiments together with LCA modeling.…”