Switchgrass Biomass Simulation at Diverse Sites in the Northern Great Plains of the U.S.

The Agricultural Land Management Alternatives with Numerical Assessment Criteria (ALMANAC) model, originally developed and tested in Texas, needs to be tested for switchgrass (Panicum virgatum L.) simulation in more northerly locations. The Northern Great Plains of the U.S. has regionally adapted native populations of switchgrass and has excellent potential for growing switchgrass as a biofuel crop. The objective of this study was to adjust switchgrass parameters (potential leaf area index (DMLA) and degree days to maturity (PHU)) for northern sites and populations and to validate the model against switchgrass data from diverse sites in this region. Three or 4 years of measured yield data were used from a ten field sites in North Dakota (ND), South Dakota (SD), and Nebraska (NE). ALMANAC realistically simulated mean annual switchgrass yields ranging from means of 4.75 to 9.13 Mg ha−1. Mean simulated yields were within 3%, 15%, and 9% of mean measured yields for NE, SD, and ND, respectively. Sensitivity analysis with temperature and rainfall demonstrated variable responses of potential yields depending on whether season duration, soil water, or soil nitrogen was the limiting factor at a site. ALMANAC shows promise as a useful tool for switchgrass evaluation and management in the northern Great Plains and in similar latitudes with low rainfall such as the East European Plain

Switchgrass Leaf Area Index and Light Extinction Coefficients

Much of recent interest in biofuel species modeling has been for switchgrass (Panicum virgatum L.). Such modeling requires accurate simulation of light interception. We investigated the stability of the light extinction coefficient (k) in Beer’s Law with data from Temple, TX; Lincoln, NE; and Elsberry, MO. Variability in k values was not related to fraction of light intercepted, time of day, or incident solar radiation. Only the magnitude of leaf area index (LAI) showed a significant impact on the k value. Th e mean k value (−0.37) for the ‘Alamo’ switchgrass data at Temple was similar to the previously published k value (−0.33) and similar to Alamo k values in Nebraska (−0.38) and Missouri (−0.31). Compared to Alamo, other switchgrass cultivars had similar k values in Nebraska but were higher in Missouri. This study gave guidance as to which factors are important for quantifying k with Beer’s Law for light interception of switchgrass

Edaphic controls of soil organic carbon in tropical agricultural landscapes

Predicting soil organic carbon (SOC) is problematic in tropical soils because mechanisms of SOC (de)stabilization are not resolved. We aimed to identify such storage mechanisms in a tropical soil landscape constrained by 100 years of similar soil inputs and agricultural disturbance under the production of sugarcane, a C-4 grass and bioenergy feedstock. We measured soil physicochemical parameters, SOC concentration, and SOC dynamics by soil horizon to one meter to identify soil parameters that can predict SOC outcomes. Applying correlative analyses, linear mixed model (LMM) regression, model selection by AICc, and hierarchical clustering we found that slow moving SOC was related to many soil parameters, while the fastest moving SOC was only related to soil surface charge. Our models explained 78-79%, 51-57%, 7-8% of variance in SOC concentration, slow pool decay, and fast pool decay, respectively. Top SOC predictors were roots, the ratio of organo-complexed iron (Fe) to aluminum (Al), water stable aggregates (WSagg), and cation exchange capacity (CEC). Using hierarchical clustering we also assessed SOC predictors across gradients of depth and rainfall with strong reductions in Roots, SOC, and slow pool decay associated with increasing depth, while increased rainfall was associated with increased Clay and WSagg and reduced CEC in surface soils. Increased negative surface charge, water stable aggregation, organo-Fe complexation, and root inputs were key SOC protection mechanisms despite high soil disturbance. Further development of these relationships is expected to improve understanding of SOC storage mechanisms and outcomes in similar tropical agricultural soils globally

Comparing Biomass Yields of Low-Input High-Diversity Communities with Managed Monocultures Across the Central United States

Biofuel cropping expansion is increasing pressure on food, grazing, and conservation lands. Debate over the efficacy of converting diverse native plant communities to managed monocultures prompted us to explore the extensive crop and ecological site productivity databases maintained by United States Department of Agriculture-Natural Resources Conservation Service. We compared annual net primary productivity (ANPP) of diverse native plant communities to ANPP of alfalfa (Medicago sativa L.) in Nebraska, Kansas, and Oklahoma; to coastal bermudagrass (Cynodon dactylon [L.] Pers.) in northern and central Texas; and to buffelgrass (Pennisetum ciliare [L.] Link.) in extreme southern Texas. In only 21% of the 1,238 sites in Nebraska, Kansas, and Oklahoma did native communities produce more or equivalent ANPP compared with managed alfalfa or coastal bermudagrass. In contrast, southern Texas native communities had greater ANPP than did buffelgrass at 81% of the sites. Regression analyses based on these results suggested that managed switchgrass (Panicum virgatum L.) ANPP would consistently exceed native community ANPP. We identified the type of sites that could remain in diverse communities or be converted to diverse communities and have productivity as great as or greater than highly managed monocultures of alfalfa, coastal bermudagrass, or buffelgrass. However, because of the low ANPP on these sites, biomass production may not be the optimal use of such sites. These lands may be better suited to providing other ecosystem services

Switchgrass Leaf Area Index and Light Extinction Coefficients

Much of recent interest in biofuel species modeling has been for switchgrass (Panicum virgatum L.). Such modeling requires accurate simulation of light interception. We investigated the stability of the light extinction coefficient (k) in Beer’s Law with data from Temple, TX; Lincoln, NE; and Elsberry, MO. Variability in k values was not related to fraction of light intercepted, time of day, or incident solar radiation. Only the magnitude of leaf area index (LAI) showed a significant impact on the k value. Th e mean k value (−0.37) for the ‘Alamo’ switchgrass data at Temple was similar to the previously published k value (−0.33) and similar to Alamo k values in Nebraska (−0.38) and Missouri (−0.31). Compared to Alamo, other switchgrass cultivars had similar k values in Nebraska but were higher in Missouri. This study gave guidance as to which factors are important for quantifying k with Beer’s Law for light interception of switchgrass

Anaerobic Digestion and Hot Water Pretreatment of Tropically Grown C4 Energy Grasses: Mass, Carbon, and Energy Conversions from Field Biomass to Fuels

The efficacy of C4 grasses as feedstocks for liquid fuel production and their climate mitigation potential remain unresolved in the tropics. To identify highly convertible C4 grasses, we measured final fuels and postprocess biomass produced in two laboratory-scale conversion pathways across 12 species and varieties within the Poaceae (grass) family. Total mass, carbon, and energy in final fuels and postprocess biomass were assessed based on field mass and area-based production. Two lignocellulosic processes were investigated: (1) anaerobic digestion (AD) to methane and (2) hot water pretreatment and enzymatic hydrolysis (HWP-EH) to ethanol. We found AD converted lignocellulose to methane more efficiently in terms of carbon and energy compared to ethanol production using HWP-EH, although improvements to and the optimization of each process could change these contrasts. The resulting data provide design limitations for agricultural production and biorefinery systems that regulate these systems as net carbon sources or sinks to the atmosphere. Median carbon recovery in final fuels and postprocess biomass from the studied C4 grasses were ~5 Mg C ha−1 year−1 for both methane and ethanol, while median energy recovery was ~200 MJ ha−1 year−1 for ethanol and ~275 MJ ha−1 year−1 for methane. The highest carbon and energy recovery from lignocellulose was achieved during methane production from a sugarcane hybrid called energycane, with ~10 Mg C ha−1 year−1 and ~450 MJ ha−1 year−1 of carbon and energy recovered, respectively, from fuels and post-process biomass combined. Carbon and energy recovery during ethanol production was also highest for energycane, with ~9 Mg C ha−1 year−1 and ~350 MJ ha−1 year−1 of carbon and energy recovered in fuels and postprocess biomass combined. Although several process streams remain unresolved, agricultural production and conversion of C4 grasses must operate within these carbon and energy limitations for biofuel and bioenergy production to be an atmospheric carbon sink