GLBRC's Sustainability Research Area


Focusing on one attribute comes at a high price.

At the GLBRC, sustainability researchers are exploring complex issues in agricultural and industrial systems. Research focuses on understanding the attributes and mechanisms responsible for the environmental sustainability of biofuel production systems, such as environmental impacts — many of which may be positive — and socioeconomic factors including incentives and policy options

Learn about the Center's research approach

Sustainability Leadership

Scientific Director, Sustainability Lead

A crop and soil scientist and ecosystem ecologist, Robertson focuses much of his research on the role that agriculture plays in greenhouse gas dynamics, and he is internationally known for his expertise in this area. Robertson has been the director...

Sustainability Lead

Jackson’s program focuses on structure and function of managed, semi-natural and natural grassland ecosystems. Research in Jackson’s grassland ecology lab spans many levels of ecological organization, from grass identification at the DNA level to landscape diversity effects on alternative biofuels...

Project Overview

A device used for measuring plant utilization of solar radiation sits in front of plots of switchgrass, corn and poplar growing in the Great Lake Bioenergy Research Center's fields at the Arlington Agricultural Research Station in Arlington, WI.GLBRC Sustainability research ranges from the microbial community level to regional modeling, and researchers conduct fieldwork at different project sites to reflect this diversity of scale. Small plots at Kellogg Biological Station in Michigan and the Arlington Agricultural Research Station in Wisconsin provide locations for measurement-intensive experiments, while investigators work in larger scale-up fields to collect data on carbon balances and biogeochemical processes. Finally, researchers pursue ecosystem-level biodiversity questions across landscapes, including marginal lands, in central Michigan and Wisconsin.

Specific sustainability projects include:

  • Novel biofuel production systems
  • Microbial-plant interactions for improved biofuel production
  • Biogeochemical responses
  • Biodiversity responses
  • Economic responses
  • Modeling, design and testing of drop-in fuels
  • Process synthesis and technoeconomic evaluation for biomass-to-fuels technologies.


Sustainability Publications

Lactobacillus casei as a biocatalyst for biofuel production

Elena Vinay-Lara; Song Wang; Lina Bai; Ekkarat Phrommao; Jeff R. Broadbent; James L. Steele

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Microbial fermentation of sugars from plant biomass to alcohols represents an alternative to petroleum-based fuels. The optimal biocatalyst for such fermentations needs to overcome hurdles such as high concentrations of alcohols and toxic compounds. Lactic acid bacteria, especially lactobacilli, have high innate alcohol tolerance and are remarkably adaptive to harsh environments. This study assessed the potential of five Lactobacillus casei strains as biocatalysts for alcohol production. L. casei 12A was selected based upon its innate alcohol tolerance, high transformation efficiency and ability to utilize plant-derived carbohydrates. A 12A derivative engineered to produce ethanol (L. casei E1) was compared to two other bacterial biocatalysts. Maximal growth rate, maximal optical density and ethanol production were determined under conditions similar to those present during alcohol production from lignocellulosic feedstocks. L. casei E1 exhibited higher innate alcohol tolerance, better growth in the presence of corn stover hydrolysate stressors, and resulted in higher ethanol yields.

A superstructure-based framework for simultaneous process synthesis, heat integration, and utility plant design

Lingxun Kong; Murat Sen; Carlos A. Henao; James A. Dumesic; Christos T. Maravelias

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We propose a superstructure optimization framework for process synthesis with simultaneous heat integration and utility plant design. Processing units in the chemical plant can be modeled using rigorous unit models or surrogate models generated from experimental results or off-line calculations. The utility plant subsystem includes multiple steam types with variable temperature and pressure. For the heat integration subsystem, we consider variable heat loads of process streams as well as variable intervals for the utilities. To enhance the solution of the resulting mixed-integer nonlinear programming models, we develop (1) new methods for the calculation of steam properties, (2) algorithms for variable bound calculation, and (3) systematic methods for the generation of redundant constraints. The applicability of our framework is illustrated through a biofuel case study which includes a novel non-enzymatic hydrolysis technology and new separation technologies, both of which are modeled based on experimental results.

Accuracy of genomic prediction in switchgrass (Panicum virgatum L.) improved by accounting for linkage disequilibrium

Guillaume P. Ramstein; Joseph Evans; Shawn M. Kaeppler; Robert B. Mitchell; Kenneth P. Vogel; Robin Buell; Michael D. Casler

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Switchgrass is a relatively high-yielding and environmentally sustainable biomass crop, but further genetic gains in biomass yield must be achieved to make it an economically viable bioenergy feedstock. Genomic selection is an attractive technology to generate rapid genetic gains in switchgrass and meet the goals of a substantial displacement of petroleum use with biofuels in the near future. In this study, we empirically assessed prediction procedures for genomic selection in two different populations consisting of 137 and 110 half-sib families of switchgrass, tested in two locations in the United States for three agronomic traits: dry matter yield, plant height and heading date. Marker data was produced for the families' parents by exome capture sequencing, generating up to 141,030 polymorphic markers with available genomic-location and annotation information. We evaluated prediction procedures that varied not only by learning schemes and prediction models, but also by the way the data was preprocessed to account for redundancy in marker information. More complex genomic prediction procedures were generally not significantly more accurate than the simplest procedure, likely due to limited population sizes. Nevertheless, a highly significant gain in prediction accuracy was achieved by transforming the marker data through a marker correlation matrix. Our results suggest that marker-data transformations and, more generally, the account of linkage disequilibrium among markers, offer valuable opportunities for improving prediction procedures in genomic selection. Some of the achieved prediction accuracies should motivate implementation of genomic selection in switchgrass breeding programs./p>.

An essential role of caffeoyl shikimate esterase in monolignol biosynthesis in Medicago truncatula

Chan Ma Ha; Luis Escamilla-Trevino; Juan Carlos Ser Yarce; Hoon Kim; John Ralph; Fang Chen; Richard A. Dixon

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Biochemical and genetic analyses have identified caffeoyl shikimate esterase (CSE) as an enzyme in the monolignol biosynthesis pathway in Arabidopsis thaliana (Vanholme et al., 2013b), although the generality of this finding has been questioned. Here we show the presence of CSE genes and associated enzyme activity in barrel medic (Medicago truncatula, dicot, Leguminosae), poplar (Populus deltoides, dicot, Salicaceae), and switchgrass (Panicum virgatum, monocot, Poaceae). Loss of function of CSE in transposon insertion lines of M. truncatula results in severe dwarfing, altered development, reduction in lignin content, and preferential accumulation of hydroxyphenyl units in lignin, indicating that the CSE enzyme is critical for normal lignification in this species. However, the model grass Brachypodium distachyon and corn (Zea mays) do not possess orthologs of the currently characterized CSE genes, and crude protein extracts from stems of these species exhibit only week esterase activity with caffeoyl shikimate. Our results suggest that the reaction catalyzed by CSE may not be essential for lignification in all plant species. This article is protected by copyright. All rights reserved.

Balancing biofuel production and biodiversity: Harvesting frequency effects on production and community composition in planted tallgrass prairie

Karen A. Stahlheber; Bradley Watson; Timothy L. Dickson; Ryan Disney; Katherine L. Gross

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Native perennial grasslands have been proposed as a source of feedstocks for the production of second-generation lignocellulosic biofuels in the Midwestern USA. Although the consequences of some management decisions for biomass production and plant community composition are well understood (e.g. fertilization), less is known about the effects of harvesting frequency. We compared a once- and twice-annual harvesting regime at two restored prairies in southwestern Michigan established with identical seed mixtures as part of a large-scale bioenergy experiment. We determined biomass production and species composition in experimental plots and also measured the availability of light, inorganic nitrogen and soil moisture. The plant communities that established at the two sites differed markedly in composition and there was little evidence of convergence after five years. At the site dominated by warm-season C4 grasses, single harvests generally produced more biomass than double harvests. By contrast, biomass production was unaffected by harvesting at the more diverse site. Contrary to our prediction that a summer harvest would increase diversity, we found small and subtle effects on plant community composition. This may be due in part to the timing of our harvest treatment. Our results suggest that a single, end-of-season harvest is the best practice for maximizing biomass production in prairies, especially at sites where warm-season grasses dominate. However, at more diverse sites, two harvests can produce the same total biomass and may support other beneficial ecosystem services. This study indicates that in the short term, double harvests are unlikely to affect plant species diversity or community composition in prairie plantings.