Final Report for LS09-219
Switchgrass and cottonwood cropping systems are able to provide a substantial amount of bioenergy feedstock when grown on marginal soils in the Lower Mississippi Alluvial Valley. However, establishment technologies associated with these crops will need to be refined to reduce the risk of establishment failures and improve their economic viability. The quality of the bioenergy feedstock produced by the cottonwood was slightly better than that by switchgrass. Establishing these bioenergy crops produces important ecosystem services valued by society. If a monetary value were associated with these ecosystem services, growing these cottonwood or switchgrass bioenergy crops may become more feasible.
The objectives of this project are to:
1. quantify biomass production, potential bioenergy (ethanol, syndiesel, etc.) yields, and economics of agroforest systems with a variety of cottonwood and switchgrass compositions.
2. quantify ecosystem services (carbon sequestration, nitrogen retention, wildlife habitat, and biodiversity) provided by agroforest systems with a variety of relative cottonwood and switchgrass compositions.
3. provide information to farmers, bioenergy industry professionals, county agents, natural resource managers, and regional public officials on the production potential, financial viability, and ecological impacts of cottonwood/switchgrass agroforest biofeedstock systems; demonstrate establishment, harvesting, and bioenergy conversion technologies appropriate to these agroforest systems; and establish a stakeholder research and outreach steering committee to direct current and future project activities concerning these cropping systems.
The purpose of this project is to develop economically viable agroforest systems for producing cellulosic
bioenergy crops that will also enhance water quality and provide wildlife habitat on low productivity agricultural land in the Lower Mississippi Alluvial Valley (LMAV). The LMAV has a high potential for bioenergy crop production due to its long growing season and well-developed agricultural infrastructure. However, crops currently used as biofuels also require high levels of resource inputs (fertilizer, water, pesticides, and/or machinery) to provide acceptable levels of biomass production on marginal agricultural soils. Agroforest systems utilizing crops that are better adapted to these soils could increase farm profitability while providing additional sources of bioenergy feedstocks in a more sustainable manner.
Marginal agricultural lands targeted by this study are poorly drained or have low inherent fertility and thus are not well suited for traditional agricultural crop production. During periods of low commodity prices, these lands are frequently enrolled in conservation reserve programs. Development of cropping systems that produce cellulosic feedstocks for fuel production while providing important ecosystem services could bolster the development of the biofuels industry in the LMAV, provide income from these less productive lands, and meet important conservation objectives.
Switchgrass (Panicum virgatum L.) and cottonwood (Populus deltoids Bartr. Ex Marsh.) trees are among the most promising species for bioenergy production, particularly on poor soils (Thorton et al. 1998; Stanturf et al. 2000). Switchgrass can be established from seed at low cost, grown with minimal fertilization, produces high yields even on marginal or suboptimal soils, and tolerates both drought and flooding. The ethanol production potential of switchgrass per unit area of land is more than twice that of corn, and current breeding efforts aim to further enhance energy output. Currently corn can produce average annual ethanol yields of 400 gallons/ac. Based on previous studies, switchgrass is capable of producing 600 to 1,150 gallons/acre (Ruark et al. 2006). Switchgrass requires less energy to produce than corn. The amount of energy required to grow and harvest a unit of energy in the form of ethanol is 3.78 times greater for corn than switchgrass (Pimentel and Patzek 2005). Switchgrass biomass can also be co-fired with coal as a cleaner-burning energy alternative to low-grade coal; each pound of switchgrass biomass contains ~7,500 BTU of energy (Burden, 2003).
Cottonwood is one of the fastest-growing native trees in the southern portion of the United States and attains its highest growth rates on wet soils in the Mississippi Valley. On these soils cottonwood can grow 4-6 feet in height each year. Due to its high biomass growth potential it is estimated that cottonwood trees could annually produce 500 to 700 gallons/ac of ethanol (Ruark et al. 2006). Numerous varieties and clones and hybrids of cottonwood have been developed to provide superior growth over a wide portion of its range (Land et al. 2001). In addition, breeding efforts are underway to modify cottonwood cellulose characteristics to increase its potential ethanol yield.
Agroforest systems that grow alleys of switchgrass between rows of cottonwood trees could be an ecologically and economically superior alternative to conventional agricultural cropping systems for producing biofuel on marginal agricultural land in the LMAV. Agroforest systems are among the most productive and environmentally benign agricultural systems. They are also designed to optimize the use of growing space, water, light, and nutrients. As such, agroforests are associated with numerous economic and environmental benefits, including: (1) greater total yields, (2) risk mitigation through crop diversification, (3) product diversity, (4) low fertilizer and herbicide costs, (5) improved soil nutrient usage and recycling, (6) improved soil and water quality, (7) enhanced plant, animal, and microbial biodiversity, and (8) greater sequestration of atmospheric carbon dioxide than conventional agricultural cropping systems and forests (Best et al. 1990, Garrett and McGraw 2000, Jose et al. 2004, Sharrow and Ismail 2004). Agroforests have been developed to provide an assortment of management alternatives for combining trees and grasses (e.g., silvopasture systems in which trees are managed within pastures) and for combining trees and annual or perennial crops (e.g., alley cropping systems where crops are planted between rows of trees)(Gold et al. 2000). However, agroforest systems for combining cottonwood and switchgrass for biofuel production have not been fully developed or evaluated.
Agroforest systems would be an especially attractive management option for small or moderate size landowners. This cropping system provides an assortment of management alternatives, a range of economic and social benefits, and important ecosystem services that can be implemented on a variety of field and farm scales. Growing switchgrass, which is annually harvested, along with cottonwood which is periodically harvested (every 5 to 8 years) in the same field, could allow small landowners to take advantage of changing markets by adjusting the year that cottonwood trees are harvested while receiving an annual return from switchgrass. Growing switchgrass and cottonwoods in these agroforest systems could also provide landowners additional revenue from emerging carbon markets. Rates of carbon sequestration and storage for switchgrass have been reported to be 20-30 times greater than row crops (McLaughlin and Walsh 1998). The majority of this carbon sequestration occurs in the soil. Soil carbon annual accrual rates in mesic, warm degraded sites have been estimated to be up to 0.62 tons/acre over a 10 year period (McLaughlin and Kazos 2005). Soil carbon accrual rates for hybrid poplar (developed from cottonwood genetic stock) are similar to that reported above for switchgrass (Hansen 1993). Growing these two crops together in an agroforest system may further increase carbon storage. Higher levels of carbon sequestration have been found in other agroforest systems such as silvopastures than in either forests or pastures alone (Sharrow and Ismail 2004). Increased carbon sequestration would not only potentially provide additional sources of income but improve the quality of these soils. Conversion of conventional agricultural crops to grass or tree biomass crops has been found to decrease bulk density, decrease soil resistance, and increase aggregate stability (Toblert et al. 1999). Thus carbon sequestration from these energy crops would not only provide an important ecosystem service but would increase the potential for financial gain to the landowner from the sale of carbon credits.
Introducing mixtures of switchgrass and cottonwood to the landscape of the LMAV would help protect waterways of the region from nutrient contamination. Past expansions in agricultural land and the current increased dependence on fertilizer in much of the LMAV has increased nitrogen transport to waterways which contributes to increased hypoxia within the Gulf of Mexico (Burkhart and James 1999). The amount of nitrate-N inputs to the Gulf of Mexico from the Lower Mississippi River Basin has been estimated to have increased by as much as 300% from 1955 to 1998 (Goolsby and Battaglin 2001). Growing conventional biofuel crops (corn and soybean) on marginal soils would likely require relatively high levels of nutrient amendments and increase the risk of nitrogen transport to waterways even with current management practices that minimize nutrient use and transport. Biofuel feedstock production of native grassland perennials (Tilman et al. 2006) and woody crops require significantly lower levels of agricultural chemical inputs than corn or soybeans. Pimentael and Patzek (2005) estimated that it would require about 26% of the nitrogen, 35%, of the herbicide, and less than 1% of the insecticides to produce the same amount of ethanol using switchgrass compared to corn. Comparisons of the nitrogen concentrations in soil water or nitrogen fluxes in runoff between energy crops and traditional agricultural crops in the southern US have frequently shown lower nitrogen losses from energy crops such as cottonwood and switchgrass than from conventional agricultural crops (Tolbert et al. 1999; Tolbert et al. 2000). Combining cottonwood and switchgrass in an agroforest system may further enhance N retention, since agroforests have been found to have higher nutrient retention capabilities than monoculture plantations or pastures.
A concern associated with the expansion of bioenergy feedstock production in the LMAV is that marginal land currently forested or managed for wildlife habitat in conservation programs, will be converted to corn or soybean production due to the high market values of these crops. Cottonwood-switchgrass agroforests could provide suitable habitat for a number of wildlife species on this type of land while providing needed bioenergy feedstocks. Wildlife species diversity (Schiller and Tolbert 1996), and, in particular, species that depend on early successional trees (Wesley 1981) would benefit from the presence of cottonwood trees within these systems and across the landscape. Christian (1997) found that avian abundance and richness were greater in short-rotation poplar plantations than in row crop or small grain fields. Inclusion of trees in biofuel cropping systems would enhance and diversify the vertical structure of these systems and thus increase the number of wildlife species. Switchgrass, which has been planted on farms as part of several conservation programs, can also provide additional overhead cover for wildlife. Initial trials investigating the use of switchgrass for biomass production have indicated that abundances of priority and grassland bird species in Iowa were greater in marginal croplands supporting production of switchgrass than conventional row crops (Murray et al. 2002).
Although past research suggests that these agroforests could provide a significant amount of bioenergy feedstocks as well as important ecosystems services, little or no testing of these systems has occurred in the LMAV. This project will develop economically and ecologically optimum management systems for growing switchgrass and cottonwood agroforests. It will also generate management guidelines and information on yield potentials, economic feasibility, and the ecological impacts associated with these cottonwood-switchgrass cropping systems. Currently farmers, natural resources professionals, biofuel companies, rural community leaders, and policy-makers are largely unaware of the bioenergy production potential and ecological benefits of these crops or systems. Dissemination of the information generated by this project would enable these individuals to make more informed decisions concerning alternative sources of biofuel feedstock production in the LMAV.
We developed test plots and study locations planted to various combinations of cottonwood-switchgrass agroforests as well as a conventional row cropping system to evaluate the impact of the biofuel production from these cottonwood and switchgrass cropping systems on biomass production, carbon sequestration, nitrogen retention, biofuel quality/yields, potential economic costs/returns, small mammal populations and small mammal habitat. In addition continuing education and outreach was performed to inform landowners and other interested parties about the viability of these systems and the potential for biofuel production in the region.
All cropping system test plots were established at three sites: 1) Pine Tree Branch Experiment Station, UA Division of Agriculture, Colt, AR- “PTBES” 2) the Southeast Research and Extension Center, UA Division of Agriculture at Rohwer, AR-“SREC” and 3) the Stevenson Farm in Archibald, LA-“SF” in the LMAV. The location of the three study sites is shown in Figure 1. During the past 10 years or longer, the PTBES and SREC study sites had been row cropped. Historically the SF study site had been row cropped but was placed into pasture management during the past decade and then left fallow for several years before study initiation. Soils at the SF, SREC, and PTBES sites were respectively a Foley and Gilbert-Egypt silt loam, Sharkey clay, Calloway and Henry silt loams.
At each study site, three blocks of test plots were established in 2009. Each plot in each block received one of five treatments (cropping systems); 1) 100% cottonwood (CW), 2) 100% switchgrass (SG), 3) 67% cottonwood and 33% switchgrass (CS), 4) 33% cottonwood and 67% switchgrass (SC), and 5) a control (CT) which consisted of a conventional soybean-grain sorghum rotation (Figure 2). Cottonwood and switchgrass in the combined treatments (3 and 4) were established in alternating 49 (15 m) and 98 ft (30 m) alleys (Figure 2) to provide the appropriate composition. The blocks are located at each site in such a way to capture potential soil variation. Two blocks have plots that are 98 x 295 ft (30 x 90 m) in size and the other block was established with 295 x 295 ft (90 x 90 m) plots. The larger plots were used to support small mammal monitoring as well as to estimate harvest costs in at a more “operational size” scale. In each of the plots in all three blocks a 49 x 148 ft (15 x 45 m) measurement plot was located to monitor vegetation biomass as well as other biotic and abiotic parameters. In the 295 x 295 ft plots, a 148 x 148 ft (45 x 45 m) interior plot was used for small mammal population and habitat measurements. Vegetation outside these measurement plots were used for destructive sampling when needed.
Site preparation and cottonwood planting were completed by March 14, 2009 on all three sites. Cuttings from three cottonwood clones were planted in each 100% cottonwood plot or portion of the combined plots allocated for cottonwood production. The clones were ST-66, S7C20, and a generic mix (Mix) of cottonwoods from the Louisiana Department of Agriculture and Forestry Nursery. Each clone was planted in a separate row. Cuttings were 15.7 in (40 cm) in length and had a minimum diameter of 0.4 in. (10 mm) at the small end. Cuttings were planted at a 4 x 6 ft spacing which provided a planting density of 1815 cuttings/ac (4,485 cuttings/ha). Planting areas were subsoiled and received site preparation herbicide applications prior to planting. Post-harvest herbicide applications were applied as needed on an individual site basis. Refer to Tables 1-3 for detailed establishment and management activities for this crop.
Switchgrass was seeded at a rate of 10 lb/ac (11.2 kg/ha) between late April and mid-May, 2009 in each 100% switchgrass or portion of combined plots allocated for switchgrass production. Where emergence or survival was not adequate additional planting and weed control occurred until adequate survival was obtained. Various herbicide applications and site preparation techniques were used prior to drilling in of the switchgrass seed to control competition and prepare the seedbed. Lime, P, and K amendments were made to the areas planted to switchgrass prior to planting if needed. Following the first growing season N, P, and K were applied if needed. Refer to Table 1-3 for detailed establishment and management activities for this crop.
The soybean and grain sorghum rotation cropping treatment consisted of the establishment of soybeans in 2009, grain sorghum in 2010, and soybeans again in 2011 and 2012. The scheduled rotation is two years of soybean followed by one year of grain sorghum. The grain sorghum is planted to reduce the build-up of root nematode populations that reduce soybean production. Since one of the sites had been planted to soybeans in 2008, grain sorghum was planted in 2010 rather than in 2011. Soybean and grain sorghum establishment and cropping management was performed using typical techniques utilized for each of the soils and sites in the study. Various seedbed preparation, herbicide/insecticide applications, fertilizer/liming applications were performed to provide viable crop establishment and production. Refer to Tables 1-3 for detailed establishment and management activities for this crop.
In the interior measurement plot of each treatment which contained trees, 9 rows of 10 trees (30 trees/clone) were tagged using an aluminum pin and numbered tag placed into the ground approximately 6 inches from the tree following planting. Furthermore, at the beginning and end of a row of 10 trees, 0.25 in. PVC pipe was placed with a tag that identified the plot and clone for that row. Tree identification from 2009-2012 has been very well controlled; less than 6 tree tags have gone missing on all three locations (2430 tagged trees). In treatments that were mixed cottonwood and switchgrass, measurement trees included edge trees to test the effects of the grass/tree edge on survival and growth of trees. Basal diameter and diameter at breast height (4.5 feet above ground) were measured by digital calipers annually. Total tree heights were measured annually with a height pole. When a tree had multiple live sprouts from the cutting, diameter and height was measured for each sprout. Biomass yields were calculated using individual tree dimensions and the biomass equations developed for each study site and clone.
In the summer of 2012, 30 trees of each clone were selected from each of the three study sites (270 trees total) and harvested. The trees were selected randomly and represented the range of diameter and height conditions prevalent at the three study sites in 2012. As the trees were harvested, they were separated into two components, main stem and branches with leaves. Using a portable measuring frame and a crane scale, the tree stems where weighed as was the entire crown. A representative sample of 6 branches with leaves was measured, and then from this subsample, the leaves were removed manually and the woody portion of the branches re-weighed. Samples were taken from the lower stem, middle stem, and upper stem as well as from the subsample of branches and sealed in pre-weighed and marked plastic bags for moisture content analysis. These samples were then dried at 221 degrees F (105 degrees C). From this data, yield equations of green and oven-dry stem and woody-crown biomass were developed. The yield equations were developed using linear regression of the general form:
Where: Yi = oven dry biomass
GLD = groundline diameter
DBH = diameter at breast height
THT – total tree height
Various yields (Yt) were fit to predict total aboveground oven dry biomass and also oven dry biomass of only the main bole or stem portion of the tree. Criteria for selection of the regression models included coefficient of determination, lack-of-fit sum of squares, and a test for normality of residuals. Because we were sampling from three different test sites, a Kolmogorov-Smirnov test was used to examine whether or not the data from all three sites could be combined to develop a single yield model.
Measurements of switchgrass production consisted of stand counts (basal ground cover) and biomass yield. All stand count measurements occurred in measurement plots. Stand counts consisted of counting the number of cells that contained at least one whole or portion of a switchgrass crown in a 25-cell 6.25 square ft grid quadrat (Figure 3). The number of quadrats located in each plot depended on the size of the switchgrass area within the measurement plot so that one quadrat/ 229 square foot (21.25 square meters) of switchgrass was surveyed. Locations of the quadrats were randomly located at least 1 m from the edge of the measurement plot or the edge of the switchgrass crop in the combinaed treatments. These counts occurred following the first and second growing seasons after establishment.
The first year following establishment (2009), the switchgrass was mowed but not sampled for yield. Biomass yield was determined in 2010 and 2011 by harvesting four 3 x 19.7 ft ( 0.9 x 6 m) subplots in each measurement plot within a treatment containing switchgrass. Sampling occurred in the fall following growth cessation. A BCS brand (from Italy), walk-behind, self-propelled, 3 ft (0.9 m) sickle-bar mower, with 4-inch high skids to control cutting height, was used to sever the switchgrass. All material was collected and weighed in the field to determine green biomass for each plot. Approximately 2.2 lbs (1 kg) was collected from the sampled switchgrass, returned to the laboratory, weighted, and dried at 60 oC to determine moisture content. In 2012 a Wintersteiger, Cibus S silage harvester was used to collect switchgrass samples and determine yield. In the 100% switchgrass (SG) treatment a total of four 4.3 x 32.8 ft (1.3 x 10 m) subplots within the measurement plot were harvested and weighed. In the combined cottonwood and switchgrass treatments (SW and WS) only two subplots were harvested and weighed. Again subsamples were collected for moisture content analysis. Following yield determination, the remaining switchgrass was cut, raked, and baled. Weights of one bale/SG plot was determined as well as the total number of bales.
In 2009 through 2012 at the PTBS and SREC study sites, soybean or grain sorghum was sampled using a plot harvester. In 2009 and 2010 a total of three 4.9 x 19.7 ft (1.5 x 6 m) or 4.5 x 19.7 ft (1.37 x 6 m) subplots (depending on make of plot harvester) were harvested within each measurement plot of each soybean-grain sorghum (CT) rotation treatment. Grain weights and moisture content were determined by the plot harvester. Tarps were attached to the back of the harvester to collect the crop residues ejected by the harvester. Residue subsamples were returned to the lab and dried at 221 degrees F (105 degrees C) to determine moisture content. In 2011-2012 one 4.9 x 295 ft (1.5 x 90 m) or 4.5 x 295 ft (1.37 x 6 m) subplot was harvested (depending on make of plot harvester) across the entire length each of the soybean-grain sorghum rotations treatment plots. During these years residues from only one 4.9 x 19.7 ft or 4.5 x 19.7 ft section of the plot was collected
At the SF site, samples were collected manually and then fed to a combine to separate grain from residues. In 2009, 2011, and 2012 when soybeans were grown, five 3.3 x 3.3 ft (1 m x 1 m) subplots were harvested in each soybean grain-sorghum (CT) rotation plot. During 2010 when grain sorghum was grown, a 6.7 x 20 ft (2 x 6.1 m) subplot was harvested. Seed heads were removed fed through the combine, and green weights or the grain and residues were determined. Subsamples were returned to the laboratory and dried at 221 degrees F (105 degrees C) to determine moisture content.
Throughout the study, all activities and materials related to the management and protection of the cottonwood, switchgrass, soybeans, and grain sorghum on all three sites were recorded. This included activities of site preparation, planting, planting stock, fertilization, herbicide, insecticide, and mowing treatments within plots. Activities and materials that were put in place only to measure and monitor the study were noted as well. All costs and materials that could be considered “operational” for the establishment, growth, and maintenance of these crops were used to determine the cost ($/oven dry ton) of producing the biomass or harvested grain. Because the harvest of trees will not occur until the fall of 2013, the data will report the cost of production of oven-dry biomass for each of the three tree types, and for switchgrass by each site for the end of year 2012.
Sample Collection and Preparation
Trees harvested for biomass equation determination were transported to the laboratory, chipped and dried at 140 degrees F (60 degrees C) to a moisture content of 15-20%. The wood chips were then processed through a hammer mill to a particle size of 0.2 in. (5 mm) or less. Materials from stems and branches were packaged separately into sealed plastic bins and shipped to a laboratory for biofuel analysis. Adequate samples were obtained from the stems of each cottonwood clone (S7C20, ST66, and Mix) from the SREC and SF study sites individually, a composite of the branches from each individual clone from these two study sites, and a composite of the stems and branches of the S7C20 clone from the PTBES study site. One bale from each SG treatment plot at the PTBES study site were also collected for biofuel analysis. A subsample of switchgrass from each bale was dried. Switchgrass samples were processed through a hammer mill to pass a 6 mesh (3.8 mm) screen and stored in 30 gal tubs until analysis.
Feedstock Physical Properties
Proximate analysis was performed to present an initial classification of the feedstock components; moisture, volatile organic matter, ash content, and fixed carbon. These tests are essential to make decisions regarding the drying requirements for this feedstock as well as to understand the suitability of the material as a bioenergy feedstock. These analyses were performed on three replicates taken from each crop subsample. The sample moisture content (wet basis) was determined by drying at 221 degrees F (105 degrees C) for 24 hours. Volatile matter was determined as percent weight loss from a dry sample when heated to 1,202 degrees F (650 degrees F) for 7 minutes. The quantity and composition of ash in a feedstock is crucial for determining efficiency of conversion of a material to energy. Ash content was determined by completely burning off the dry sample at 1382 degrees F (750 degrees C) for four hours. Fixed C was determined by the difference after determining both the volatile matter content and ash content. Three replicates were taken for each of the previous analyses. The results were averaged and tabulated along with a standard division.
Mean particle size was determined for the different crop subsamples after initial reduction by chippers or a cutting mill. To determine the mean particle size, a shake test has been conducted on a 0.22 lb (100 gram) sample using a set of shakers and a set of sieves with different opening sizes (ranging from 2,000 to 63 µm). The shake tests (10 minutes each) have been performed until the difference in weight retained on the sieve, between two consecutive shakes, is below 1%. The geometric mean particle size was then determined using opening size for each sieve and the weight correspondingly retained on each sieve according to the ASABE standard S319.4 (2008).
Feedstock Chemical and Thermochemical Properties
In this work, a cutting mill (Wiley®) used to reduce the particle size of switchgrass and cottonwood to pass through an 18 mesh (1 mm) screen in order to facilitate chemical properties analysis. Carbon, hydrogen, oxygen, and nitrogen concentrations of each feedstock were determined. CHN was determined using an elemental analyzer that uses a thermal conductivity detector to quantify these elements using the known thermal conductivities of their oxides. Oxygen was determined by difference. All elemental analysis was performed in an external lab (Huffman lab., Colorado).
The pH values of the dry, ground feedstock samples were determined by diluting the solids in distilled water with a ratio of one gram of solids to 10 ml of distilled water. The mixture was then vigorously shaken to homogenize the sample and then was left to sit for one hour before measurements. Following, a pH probe connected to an Omega pH meter was used to measure the pH levels.
Dry sample high heating value of each feedstock was determined using an oxygen bomb calorimeter (Parr® instruments). Subsamples of between 0.5 and 1.0 gram were utilized for this analysis. Thermogravimetric analysis (TGA) were determined using controlled devolatilization tests in which the weight is continuously monitored as the sample is heated at a fixed heating rate of 68 degrees F (20 degrees C)/ min. The temperature of the sample was increased until it reached 1472 degrees F (800 degrees C). These tests typically generate a series of time readings (time stamp), and the corresponding temperature readings and sample weight. Samples were devolatilized in an oxygen or nitrogen environment to represent gasification/combustion or pyrolysis processes.
Feedstock torrefaction was determined using a composite sample from each feedstock. Three one-gallon metal containers were filled from this sample. These samples were compacted to ensure that air within the voids is maintained at its minimum level and then sealed. This process ensured minimization of oxidation of the sample. Ten 1 mm holes were drilled in the lid of the container to allow the volatile matters to escape from the containers. The containers were placed in a muffle furnace at 752 degrees F (400 degrees C) for two hours. The weight loss of the sample was determined after allowing the sample to cool down. All the previously listed analyses for raw feedstock were repeated for the torrefied samples.
The three replicate samples from each switchgrass bale and cottonwood sample was gasified in an externally heated auger gasification system using air as a gasifying agent. The auger gasification unit (Figure 4) consists of the following subunits: (a) biomass-feeding unit, (b) air supply unit, (c) auger reactor, heating element and temperature controller unit, (d) char collection unit, (e) tar and water collection unit, (f) gas yield and analysis unit and (g) data acquisition unit. The auger gasifier was used to gasify switchgrass and cottonwood samples. The reactor temperature was maintained at 1562 degrees F (850 degrees C). The biomass feed rate was adjusted to 11 g/min and airflow rate was adjusted to 4 L/min. These adjustments maintained the equivalence ratios at 0.10 during gasification of the feedstocks. The performance of the auger gasifier was evaluated using the gas quality and quantity data, production rates of char, production rates of tar, and cold gas efficiency.
Aboveground Crop Biomass
Subsamples of cottonwood trees, switchgrass, grain, and grain harvesting residues were collected at the time of yield determination to determine carbon content of this biomass. Subsamples were dried at 140 degrees F (60 degrees C), ground to pass through an 18 mesh (1 mm) screen. Carbon and N was determined using the Dumas dry combustion method (Sparks 1996) for each sample. Where cottonwood mortality in a measurement plot was high or had a high degree variation, aboveground as well as belowground sampling for C and N occurred in 30 x 49 ft (9 x 15 m) areas of the measurement plots where cottonwood mortality was low and uniform.
Soil Surface Residues
The Oi and Oa soil horizons as well as the senesced non-woody vegetation from the CW treatment plots were collected using eight 1 x 3 ft (0.3 x 0.9 m) frames in December 2011 or January 2012 along the soil sampling transects. Frames were located within measurement plots along the transects established for the mineral soil sampling (see below) except four of the frames were centered within the tree rows and other four were centered between tree rows. Materials were composited by plot, weighed, dried at 140 degrees F (60 degrees C), and then ground to pass an 18 mesh (1 mm) screen for C and N analysis. The Dumas dry combustion method was used for C and N analysis (Sparks 1996).
Root sampling occurred following the end of the third year of the study in December of 2011 or January of 2012. Roots were collected using a 1.8 in. (4.8 cm) diameter impact core sampler to a depth of 1 foot (30 cm). Cores were collected at along two transects that traversed the length of the measurements plots or areas of adequate cottonwood survival. In the CW, SG, and CT treatment plots a total of 10 cores were collected. In the CS and SC treatment plots which had adequate cottonwood survival occured, 12 cores were collected (8 from the 30 m wide corridor and 4 from the 15 m wide corridor). In all treatment plots, cores were composited by crop.
Cores were returned to the lab where they were stored at 39.2 degrees F (4 degrees C) until the roots could be extracted using a Hydropneumatic Elutriation System. Living and dead roots materials which would not pass through a (0.02 in.) 530 micron screen were collected for analysis. These roots were than categorized in to three categories; dead (Dead Roots), living <2 mm in diameter (Fine Roots), and living > 2mm (Coarse Roots). Roots were dried at 140 degrees F (60 degrees C), and then ground to pass an 18 mesh (1 mm) screen for C and N analysis. The Dumas dry combustion method was used for C and N analysis (Sparks 1996).
Soil sampling occurred in 2009 prior to crop establishment and in December 2011 or January 2012 following the third growing season after initial crop establishment. Samples were collected with a 1 in. (2.5 cm) push probe or impact sampler to a depth of 12 in. (30 cm) along two transects located along the length of a measurement plot or area. Transect 1 was randomly located within 19.7 ft (6 m) of the center line along one side of the plot and Transect 2 within the same distance of the center line but on the other side of the plot (Figure 5). Locations were randomly selected at ~10 ft (3 m) intervals. Prior to inserting the sampler, all organic matter was removed from the surface so that only mineral soil was collected. In 2011 these transects at the PTBS and SF sites were moved in the CW treatment where mortality was high to correspond to the above and belowground cottonwood sampling locations indicated previously. In 2011 samples were collected separately for the cottonwood and switchgrass cropping areas in the SW and WS treatment plots. Where crop establishment or survival was not successful in one crop portion (cottonwood or switchgrass) of the SW or WS treatments, soils were not collected for that cropping location in 2011. Samples were composited by transect and plot, air dried, sieved to pass a 10 mesh (2 mm) screen, and analyzed for C and N using the Dumas dry combustion method (Sparks 1996) and P, Ca, Mg, and K using a Melich III extraction. For the samples collected in 2011, microbial biomass C, microbial activity, labile C, and potential C turnover rates were measured. Microbial biomass C was measured by fumigation incubation (Jenkinson and Powlson, 1976a,b), and microbial activity was measured by an assay of dehydrogenase activity (Lenhard, 1956; Alef, 1995). Soil labile C and potential C turnover rates were measured by sequential fumigation incubation (Zou et al., 2005).
Bulk density to a depth of 12 in. (30 cm) was determined for each treatment plot either in 2009 prior to crop establishment or in 2011. We assumed bulk density did not change during the three year period. Either 0.9 or 1.8 in. (2.4 or 4.8 cm) impact soil core samplers were used to collect six cores/measurement plot. Soil collected was air dried, sieved to pass a 10 mesh (2 mm) screen, and weighed. This gave an air dried bulk density which could be used with C, N, and other nutrient analyses to determine total mass of these elements in the soil. Since 0.9 in. (2.4 cm) samplers compact the soil to a greater degree than the larger samplers, we tested the differences in bulk density estimates between sampling methods to determine a correction factor. Bulk density calculated using the 1.8 in. (4.8 cm) samplers were 85-86% of those estimated with the 0.9 in. (2.4 cm) samplers. This correction factor was used to correct and reduced the bulk densities calculated by the 0.9 in. (2.4 cm) samplers.
Soil water was collected in the CW, SG, and CT treatment plots. Sampling occurred from January 2012-May 2012. A total of four tension lysimeters were located within each measurement plot in each treatment plot where the crop was adequately established. Like the soil sampling transects, the lysimeters in the PTBS and SF treatment (CW) plots were moved into locations to ensure adequate cottonwood survival in close proximity of the lysimeters. The lysimeters were installed at least 6 months before soil water collection commenced. Soil water samples were collected every two weeks from the tension lysimeters. A 45 centibar tension was placed on the lysimeters at the beginning of each two week sampling period. Soil water samples were analyzed for total N (persulfate digestion EPA Method 353.2), total C (EPA method 415.1), NO3-N (EPA Method 300.0), and NH4-N (EPA Method 350.1).
In addition eight ion exchange resin lysimeters (Susfalk and Johnson 2002) were installed in each plot at the PTBES and SREC study sites to estimate amount of NO3-N loss. Lysimeters were installed at a depth of 12 in. (30 cm) on April 5-7, 2011 and removed after 404 or 414 days. Following removal, NO3-N was extracted using a 100 mL solution of 2M KCl (Susfalk and Johnson 2002) and analyzed using EPA method 353.2. Leaching losses were determined by the accumulation of NO3-N extracted from the resins.
This portion of the project investigated small mammal community and habitat characteristics associated with compositional gradients of cottonwood-switchgrass agroforest systems established on marginal agricultural land within the Lower Mississippi Alluvial Valley (LMAV). Our objectives were to quantify and compare small mammal community and vegetation composition between the different cropping systems within the three study sites.
Small Mammal Sampling
We trapped small mammals at each of the three study sites four times in 2011: winter (February), spring (April), summer (July), and autumn (October). Each trapping session lasted 5 consecutive nights. Within 295 x 295 ft (90 x 90 m) treatment plots at each study site we placed 36 Sherman live traps (Sherman 1941) spaced 49 ft (15 m) apart (Figure 6). Each trap was baited with dry rolled oats. In winter, cotton was placed within each trap to aid in thermal regulation. Oats were used as bait within each trap to minimize the risk of attracting fire ants (Solenopsis invicta) to the traps. Traps were checked at dawn. To reduce heat-related mortality in summer, traps were closed each morning and reset and re-baited the following evening. All treatment plots within a study site were trapped concurrently. Each study site was trapped sequentially beginning at PTBS and ending at SF each season. Our sampling effort resulted in 900 trap nights per season per study site, yielding a total of 3,600 trap nights conducted per study site during this study.
For each captured animal, we recorded species (except for Peromyscus spp. and Reithrodontomys spp., which were identified to genus only), capture locality, sex, age, and body mass. Age (juvenile or adult) was based on body mass (Sealander and Heidt 1990). Uniquely numbered metal ear tags were used to mark each individual. Relative abundance for each species was standardized to number of individuals captured per trap night per 100 traps. One trap opened for 1 night = 1 trap night. All captured animals were released at the site of capture. Our methods of capture, handling, and tagging were in compliance with the American Society of Mammalogists guidelines (Sikes et al. 2011) and approved by the University of Arkansas-Monticello Institutional Animal Care and Use Committee (Research Permit #200601).
Within each treatment plot, vegetation sampling was conducted within 9 randomly placed 21.2 square ft (2 square m) quadrats. These vegetation plots were centered on the trap location and distributed proportionally within combination plots (Figure 6). Within each quadrat we estimated percentage cover of bare ground, litter (dead vegetation lying horizontally on the ground), graminoids, herbaceous vegetation, soybeans, stubble (both switchgrass and soybean), trees, vines, and shrubs using ocular estimates at 5% intervals.
Percentage canopy cover and vegetation height and density were also estimated within each 21.2 square ft (2 square m) quadrat. Using a spherical densitometer at plot center, percentage canopy coverage was estimated as the mean of four measurements obtained at the cardinal directions. Vegetation height was estimated as the mean of all vertically growing living vegetation within the plot. Vegetation density was measured vertically at 0.8, 4.1, and 7.4 ft (0.5, 1.25, and 2.25 m) above ground level using a 5.4 square ft (0.5 square m) density board placed at the center of each plot and observed 32.8 ft (10 m) away from a location perpendicular to plot transect. Density ranged from 0% (board completely visible) to 100% (board completely covered by vegetation). Centered within each 21.2 square ft (2 square m) quadrats we placed a 10.8 square ft (1 square m) quadrat. Within each these smaller quadrats we identified plants to species and ocularly estimated percentage cover for each species at 5% intervals.
Analysis Small Mammals
Due to the lack of replication of treatment plots within each study site, trapping results from each study site were analyzed independently. Total number of individuals of each species captured per 100 trap nights, Shannon’s diversity index (Shannon 1948), sex/age distributions, and proportion of captures by habitat type were calculated for each treatment during each season. Proportions of captures by habitat type were calculated by dividing the number of animals captured in each habitat type (i.e., cottonwoods, switchgrass, or soybeans) by the total number of captures.
Mean values for each vegetation variable from each study site were analyzed independently by season and treatment. As most of the vegetation variables were not normally distributed, each variable was compared with a Kruskal-Wallis test. Vegetation variables from capture plots (trap locations where small mammals were captured) were compared to non-capture plots (trap locations where small mammals were not captured) with a Wilcoxon Signed-Rank Sum. Small sample sizes prevented comparisons between season, treatment, and species. Statistical significance was assumed when the type I error was <0.05.
Several types of outreach activities and publications were developed during the study period. We focused our efforts on landowners, farmers, agriculture professionals, and entrepreneurs who were interested in initiating bioenergy businesses within the LMAV. In an effort to determine producer attitudes towards growing and using bioenergy, we surveyed attendees at bioenergy themed field days or workshops (at PTBES and SF study sites). These field days or workshops covered topics such as bioenergy crop production, bioenergy crop harvesting, and bioenergy products. At the conclusion of the PTBES field day, we surveyed attendees to determine their attitudes about bioenergy production and products. At the SF field day we performed pre- and post-surveys to assess changes in attitudes. Surveys covered basic demographic information about the attendee and their opinions about the topics covered. An additional subset of questions was designed to explore attendee attitudes, knowledge, and acceptance of bioenergy products and bioenergy production techniques. Portions of surveys also focused on attendee’s previous experience with bioenergy production and interest in becoming a bioenergy producer. At the PTBES field day, a final subset of questions was used to determine to what degree these attendees used bioenergy (primary biodiesel) in vehicles or equipment they operated. Examples of specific questions are included in Figures 7-8. Results from these surveys were tabulated and reported.
Initial cottonwood survival was acceptable on all three study sites (Table 4). All three study sites required two follow-on herbicide treatments, and the cottonwoods at the PTBES required a turf-roller application and mowing to control severe morning glory (Ipomoea spp.) infestation.
In the second year, all three sites received a banded application of ammonium nitrate (150 pounds/acre in the 3.6 ft bands for a total of 31.5 lbs N/acre). The SREC study site had substantial cottonwood leaf beetle (Chrysomela scripta Fabricius) that was treated successfully with a single aerial application of Provado (Imidacloprid) at 8 ounces per acre. Mortality at the SF study site was substantial in year two due to a severe drought and substantial competition from nut sedge (Cyperus esculentus). All three sites received a second application of pre-emergent herbicide at the beginning of the second growing season, and the SF study site required an additional herbicide treatment that was directed at controlling the nut sedge.
At PTBES, significant leaf curl and shoot mortality was observed each year starting in late May and early June. The pattern of damage was consistent with herbicide drift and the suspected agent was quinclorac, a commonly applied broadleaf herbicide using in rice production. Vegetation samples were taken and the State Plant Board contacted, but two separate sampling and testing attempts in 2010 and 2011 were unable to confirm quinclorac presence in cottonwood tissue samples. The resulting growth pattern for cottonwood at the PTBES study site resulted in a substantially larger proportion of aboveground biomass in branches and leaves than at the other two study sites (Table 5). The dieback of experienced at the PTBES study site has slowly increased mortality to 36%.
After the second growing season, good survival and shading from tree crown closure resulted in no additional herbicide treatments at PTBES and SREC study sites. The SF study site, however, did require two additional herbicide treatments in in each of the third and fourth growing seasons to control competition. Also, because of poor tree growth, another infestation of cottonwood leaf beetle required a control treatment using Brigade (Bifenthrin).
In general, the number of sprouts developing from each cottonwood cutting diminished rapidly as the tree grew (Table 4). Less than 5% of trees on all the sites have multiple stems after the fourth growing season. Average height of cottonwood trees after four growing seasons ranges from 10.2 ft (3.12 m) at the PTBES study site to 17.1 ft (5.2 m) at the SREC study site. At the SREC study site, ground line diameter averages 2.6 in. (6.5 cm) and diameter at breast height averages 1.5 in. (3.7 cm) (Table 4).
There are no significant differences within sites between the known cottonwood varieties and the nursery-run cottonwoods in terms of height, diameter, or biomass accumulation (Tables 4 and 6). There are significant differences between study sites, with the SREC site exhibiting significantly better survival, diameter growth, height growth, and biomass accumulation (Tables 4 and 6). The variation observed within PTBES and SF tree biomass characteristics make any differences in height, diameter, and biomass accumulation insignificant after four growing seasons.
The biomass values for all cottonwood varieties (Table 6) are based on Jenkins et al (2004) equations. We have fit and are testing several biomass equations developed from weight data taken on the site, but have not at the present time found a suitable equation. However, from the equations tested at this time, we are projecting aboveground cottonwood biomass oven dry weights that are 14% to 33% lower than the results of Jerkin’s equations.
The suspected causes of low tree productivity at the SF study site include severe herbaceous competition coupled with severe drought in 2010 (second growing season). Repeated herbicide drift at PTBES is the suspected cause of the low productivity at that location. Maximum observed productivity at SF and PTBES are approximately equal to the mean observed productivity at SREC (Table 6).
Switchgrass establishment requires two growing seasons before a harvestable crop can be obtained. Productivity rises in the third year production as the site becomes fully stocked and occupied by the grass. Production of switchgrass at the PTBES study site was excellent in the third year of the study (2011) but fell off by 41% in 2012 due to dry growing conditions (Table 7). At SF, the establishment and productivity of switchgrass doubled the previous year’s production in 2011 and 2012, reaching an average of 13,388 kg/ha of oven dry biomass in 2012 (Table 7). We expect that sustained productivity of the site will approximate the 2012 accumulation.
Switchgrass was very difficult to establish at the SREC study site. Five planting attempts were made, two in 2009 (spring and fall), and two more in 2010 and 2011. The soil at SREC is a Sharkey clay. The upper 0.5 in. (1 cm) of the soil would dry very quickly in 72-96 hours of dry weather, and the very fine seed of switchgrass was unable to penetrate the crust of the soil. However, since switchgrass germinates very slowly, we found that due to the mild winter of 2011-2012, a suitable crop of switchgrass had become established at SREC. The fall planting in 2009 established well, but was killed by a hard freeze in January of 2010. In the spring of 2012, approximately 37,000 switchgrass plants were started in a greenhouse and transplanted into gaps at Rohwer to finish the establishment. Most of these “gaps” were adjacent to the established cottonwood. No harvest of switchgrass was made in 2012; the first switchgrass harvest at SREC is scheduled for October of 2013.
Soybean-Grain Sorghum Rotation
A three year crop rotation using two years of soybeans, followed by a single year of grain sorghum was used as the control (CT) at each site. The grain sorghum was grown in 2010, with soybeans grown in 2009, 2011, and 2012. Table 8 shows the average oven dry yields of grain and plant residue for each year. Grain production is most consistent at PTBES, while both SREC and SF demonstrate large variation in the production of soybeans between 2009 and 2011-2012. Residue production with the grain sorghum was significantly greater on all three sites than soybean residue.
Grain crop biomass production after four years was not significantly different than switchgrass biomass production at the SF and PTBES study sites (Table 9). Biomass accumulation with the CW cropping system was significantly lower at all three sites than with either the SG or CT cropping systems. At the SREC study site where cottonwood production was greatest, trees accumulated 54% of the biomass production of the worst CT treatment (PTBES). However, the cottonwood biomass crop does not include any foliage that could be harvested with the trees at the end of a rotation. Thus, our estimates may slightly underestimate the total biomass that could be harvested from the CW cropping system.
The goal of this task was to assess the potential quality and quantity of the switchgrass and cottonwood feedstocks grown in this study. Bioenergy value of these feedstocks depends on their physical, chemical and thermochemical characteristics. Characterization of these feedstocks will provide information to assess handling logistics and develop thermochemical conversion processes. The most importance properties are the feedstock physical characteristics. Feedstock physical characteristics include bulk density, moisture content, volatile solids, and ash content. These parameters directly affect the design of the feeding systems. Feedstock chemical properties include chemical composition and pH value. These parameters determine the required amount of air for complete and partial combustion during gasification. Feedstock thermochemical properties include heating value and thermal decomposition which significantly affects the quality of the producer gas. The higher the feedstock heating value the better the quality of the producer gas. Thermal decomposition of the feedstock in a nitrogen environment using a thermogravimetric analyzer (TGA) represents a pyrolysis process. On the other hand, thermal decomposition of feedstock in oxygen environment represents gasification or combustion processes. For this report we focused on determining feedstock characteristics of the switchgrass collected from the PTBES study site and a composite of the branch and stems samples collected (from all study sites) for each the S7C20 and ST66 cottonwood clones
Raw and Torrefied Cottonwood/Switchgrass Physical Properties
Bulk Density: The bulk density of a feedstock affects the transportation costs. The higher the bulk density, the lower the transportation cost when transportation costs charged based on feedstock volume. Bulk densities of cottonwood and switchgrass samples were determined before and after thermal treatment, namely torrefaction. The highest cottonwood bulk density of 12.9 lb/cubic ft (205.9 kg/cubic m) was found with cottonwood ST66, while the lowest bulk density of 6.8 lb/cubic ft (108.8 kg/cubic m) was found with switchgrass samples (Figure 9). Switchgrass bulk density was significantly lower than that of cottonwood. Torrefaction, on the other hand, affected the feedstock bulk density negatively for the two cottonwood clones as well as the switchgrass samples. Thus, torrefaction could negatively impact the transportation cost. However, it was observed that the torrefied samples are frailer than the raw feedstock. This may be helpful if the final product will be used to make solid fuel pellets.
Moisture content and volatile solids: Average moisture content (wet-basis) for each type of cottonwood clone and switchgrass was plotted in Figure 10. Generally, the initial moisture content values of cottonwood S7C20 and ST66 samples were 7.5% and 6.3%, respectively. These values were significantly lower than the moisture content values of switchgrass (25.2%). This was expected as cottonwood samples were dried and ground prior to their delivery. It is noticeable that torrefaction reduced the moisture content for cottonwood S7C20, ST66 and switchgrass to 1.4%, 0.7% and 1.3%, respectively. The reduction of the feedstock moisture content would benefit the thermal treatment process, as less water needs to be evaporated during the treatment process. In addition, it would ease the handling and feeding processes of the feedstock to a gasifier or pyrolyzer.
Volatile matter was determined by heating the feedstock under controlled conditions and measuring the weight loss, excluding the weight of moisture driven for moisture content determination. Figure 11 illustrates volatile matter content as affected by torrefaction for the two cottonwood clones and switchgrass samples. The initial volatile matter content for cottonwood S7C20 and ST66 were 76.8% and 78.0, respectively; whereas the volatile solids of switchgrass was slightly lower (73.8%). Generally, torrefaction reduced the volatile solids content of the S7C20 clone, ST66 clone, and switchgrass (35.5%, 25.3%, and 25.9%, respectively). Torrefaction significantly reduced the volatile solids contents of biomass due to the release of hemi-cellulose and cellulose contents of the biomass.
Ash content and fixed carbon: Figures 12 and 13 show the effects of torrefaction treatment on the ash content and fixed carbon. Generally, both ash content and fixed carbon content increased for both the cottonwood and switchgrass samples since torrefaction drives off hemicellulose and cellulose. The reduction of the overall weight of the feedstock, which will be discussed later, led to an increase in the ash and fixed carbon contents. The ash content values increased from 2.5% to 6.5%, 1.8% to 5.8% and 4.9% to 10.6% for S7C20, ST66 and switchgrass, respectively. Fixed carbon also showed similar trends with the greatest change found with the cottonwood ST66 clone (20.2% to 68.6%). Switchgrass fixed carbon also increased from 21.2% to 63.5%.
Raw and Torrefied Cottonwood/Switchgrass Chemical and Thermochemical Properties
Ultimate analysis, chemical formula and stoichiometric air: Ultimate analysis was performed on the raw cottonwood clones and switchgrass samples to determine carbon, hydrogen oxygen and nitrogen contents of the raw materials as shown in Table 8. Carbon, hydrogen, oxygen, and nitrogen for S7C20, ST66 and switchgrass did not significantly differ. The values of the carbon, hydrogen, oxygen, and nitrogen contents were used to determine the empirical chemical formula. The stoichiometric air required for complete combustion was then calculated. The stoichiometric air did not vary significantly among the three feedstocks with the maximum and minimum values of 5.94 and 5.88 lb (air)/lb (biomass) for the cottonwood clones and 6.12 lb (air)/lb (biomass) for switchgrass.
pH: Raw cottonwood pH values were in the range of 5.2- 5.3 as shown in Figure 14. On the other hand, switchgrass pH value was slightly higher (6.6). All torrefied samples showed an increase in pH value, with the highest increase in cottonwood sample ST66. The pH value reached 10.0, highly alkaline values for switchgrass. This increase in pH value could be attributed to the reduction of hydrogen concentration in the biomass samples as affected by torrefaction process.
Heating Value: The average heating value for raw cottonwood S7C20, cottonwood ST66, and switchgrass samples were 7,582 BTU/lb (17.6 MJ/kg), 7,725 BTU/lb (18.0 MJ/kg), and 6,952 BTU/lb (16.1 MJ/kg), respectively. Figure 15 shows that torrefaction of cottonwood and switchgrass affected the heating values positively. The heating value of torrefied cottonwood S7C20, cottonwood ST66, and switchgrass increased to 12,025 BTU/lb (28.0 MJ/kg), 12,384 BTU/lb (28.8 MJ/kg), and 11,796 BTU/lb (27.4 MJ/kg), respectively. The increase in the energy concentration may be attributed to the release of unburned volatile solids in the biomass.
Remaining weight after thermal treatment: Biomass weight decreased with the thermal treatment. The remaining weight values were 54.2%, 33.8% and 36.3% for cottonwood S7C20, ST66, and switchgrass, respectively (Table 9). The reduction of the weight is attributed to the reduction of the moisture content and volatile solids. As mentioned earlier the heating value of the feedstock increased due to the increased concentration of the combustible components in the final product. The remaining weight values were multiplied by the final heating value to determine the remaining energy in the final product. The highest remaining heating value of 5,491 BTU/lb (12.8 MJ/kg) was observed with cottonwood S7C20. Cottonwood ST66 and switchgrass reached 4,573 BTU/lb (10.6 MJ/kg) and 4,561BTU/lb (10.6 MJ/kg), respectively.
Thermogravimetric study: Thermogravimetric analysis (TGA) was performed for cottonwood S7C20, ST66 and switchgrass to study the changes in weight with respect to change in temperature. In the present work, TGA was carried out in a Thermogravimetric Analyzer (Perkin-Elmer 4000) in nitrogen and oxygen medium to represent biomass pyrolysis and gasification, respectively. Sample size of 0.000044 lb (20 mg) was used and exposed to heating rates of 68 degree F/min (20 degree C/min) until the temperature reached 1472 degree F (800 degree C). The weight loss data was recorded as function of time and temperature. Figures 16 and 17 display the variations of weight loss (TGA curves) and derivative of mass-change (DTG curves) with respect to reaction temperature for cottonwood and switchgrass in nitrogen and oxygen environment.
The weight-loss curves of cottonwood and switchgrass pyrolysis show three distinctive stages over the temperature range of 212 degree F (100°C) to 1472 degree F (800°C). Each curve started with a heating zone 212 degree F – 572 degree F (100 degree C-300 degree C) followed by a sharp weight reduction zone 572 degree F-797 degree F (300 degree C- 425 degree C) and a slow weight reduction zone 797 degree F - 1472 degree F (425 degree C-800 degree C). It is clear that the first decomposition stage started at 572 degree F (300 degree C) for both cottonwood and switchgrass while the second stage started at 716 degree F (380 degree C) for cottonwood and 662 degree F (350 degree C) for switchgrass. Consequently, the DTG curves show these decomposition stages as two separate peaks for cottonwood and switchgrass pyrolysis. Normally the first peak represents hemicellulose decomposition whereas the second peak represents cellulose decomposition. In the case of switchgrass pyrolysis, the two peaks were obvious as compared with cottonwood pyrolysis. There is no clear peak to represent any lignin decomposition.
The reduction of biomass weight, measured as a function of temperature change, was higher with oxidation (oxygen environment) than pyrolysis (nitrogen environment) as evident by the slope of the TGA curves. Hemicellulose volatilized at 572 degree F (300 degree C) and 536 degree F (280 degree C) whereas; cellulose volatilized at 662 degree F (350 degree C) and 590 degree F (310 degree C) for cottonwood and switchgrass, respectively. Oxidation DTG curves did not show more than one clear peak for cottonwood and switchgrass which may be due to the rapid burning of the biomass in oxygen environment.
The DTG curves were used to determine essential values for thermochemical technologies. These values include the pre-exponential value; A, the activation energy; E, and the reaction order; n represented in Arrhenius equation. Linearization technique was used to determine the values of A, E and n. These values are needed to predict the decomposition rate under various operating conditions. Activation energy of cottonwood S7C20, ST66, and switchgrass in nitrogen environment ranged between 68.54 and 72.74 BTU/mol (Table 10). The maximum decomposition temperature reached 707 degree F (375 degree C) for cottonwood C7S20, 714 degree F (379 degree C) for ST66 and 691 degree F (366 degree C) for switchgrass. As a comparison, activation energy of cottonwood C7S20, ST66, and switchgrass in oxygen environment reached 167.78, 118.69, and 224.94 BTU/mol, respectively (Table 11). It was clear that gasification reaction presented higher activation energy and lower maximum decomposition temperature as compared with pyrolysis reaction.
Gasification of cottonwood and switchgrass- Cottonwood and switchgrass were gasified in the auger gasification system described earlier. Only one sample from each type of feedstock was gasified to evaluate the performance of the auger gasifier during gasification of feedstock. The experimental data obtained from the gasification experiments are presented in Table 12. The performance of the gasifier was evaluated by measuring the producer gas mole fractions, heating value and yield. In addition, char and tar production rates as well as the gasifier efficiency were taken into account.
Bed temperature was maintained at 1292 degree F (700 degree C) during the experimental run. Hydrogen, carbon monoxide, and methane mole fraction were 5.1%, 8.3%, and 6.5% respectively during the gasification of cottonwood whereas they reached 5.0%, 7.4%, and 4.8% respectively during the gasification of switchgrass. It is clear that cottonwood produced higher combustible gases than switchgrass. As a result, the producer gas heating value reached 110.0 BTU/cubic ft (4.1 MJ/cubic M) for cottonwood whereas it reached only 91.3 BTU/cubic ft (3.4 MJ/cubic m) for switchgrass. Tar and char production rates were noticeably high in this study. This may be due to the low level of reactor temperature and the short residence time in the auger gasifier.
It should be mentioned that switchgrass feeding encountered some challenges due to the nature of this biomass. Therefore, having the initial suggested route of torrefying switchgrass followed by gasification process may lead to simplification of the process and avoiding the feeding challenges.
Summary: There were little differences in biofuel quality between the two cottonwood clones. This indicates that the overall fuel quantity generated by cottonwood should be primarily attributed to the quantity of biomass produced. The potential biofuel quality of the switchgrass appears to be lower than that for the cottonwood. Measures of bulk density, volatile matter, and heating values were higher for cottonwood than switchgrass while ash contents were lower. Heating values of producer gases generated by gasification of cottonwood was approximately 20% greater than that derived from switchgrass. Torrefying of the feedstocks increased heating values of the feedstocks by between 59-70% which would benefit any thermochemical process that would occur following torrefaction.
Aboveground biomass C and N were separated into two categories; crop yield and surface residues. The crop yield included the amount of material harvested as grain in the CT treatment and the biomass yield of the switchgrass or cottonwood (stems and branches) in the other two treatments. The surface residues included harvest residues in the CT treatment and the surface biomass from the CW treatment collected at the end of the 2011 growing season. The total of these two categories for each cropping system was used to quantify the amount of C sequestered or N accumulated by aboveground biomass production of the three treatments by the end of 2011. Figure (18) shows the C and N in crop yields during this period. Amounts of C in the CW and SG cropping systems were greater than the CT cropping system while N in the CT yields were greater than that for the CW or SG yields. Total amount of C sequestered or N accumulated (Figure 19) shows similar relationships among the treatments. However with the inclusion of surface residues, the amounts of C in the CT treatments increase by 50-53% while the amounts of C in the CW treatment increase by approximately 170%. The residues measured in 2011 were a significant portion of the aboveground C sequestered by these crops. Inclusion of these residues has a minor impact on N accumulation of the CT treatments since residues have a much lower N concentration than that of the grain that was harvested. However, inclusion of the surface residues increased the total N accumulated by the CW treatment by approximately 250%.
Total root biomass (to a depth of 30 cm) averaged between 3.1 and 7.6 tons/acre (2.8 and 6.9 Mg/ha) in the CT, CW, and SG cropping systems at the three study sites (Table 13). Total root C ranged from 1.4 to 3.0 tons/acre (1.2 to 2.7 Mg/ha) while N ranged between 0.04 and 0.07 Mg/ha (Table 13). The type of roots collected varied considerably among the cropping systems (Figure 20). As one would expect, the majority of the root mass collected from the annual crops grown in the CT treatment were dead. Fine living roots comprised between 40 and 49% of the total root mass in the perennial SG and CW cropping systems.
Comparisons between the CT and SG treatments indicated that a significantly (p=0.10) greater amount of root mass and root carbon occurred with the SG than CT cropping system. Approximately 81% more root mass and 92% root carbon was collected in the SG cropping system than the CT cropping system. However, root mass and root carbon did not significantly (p=0.10) differ between the CW and CT cropping systems. Comparisons among sites indicated that root mass and carbon were higher in the CW than the CT treatments at the SF and SREC sites but not the PTBES site. The lack of differences at the PTBES site may reflect the high rates of cottonwood mortality at this site. There were no significant differences in root N content between the CT treatment and any of the other two treatments.
The low levels of roots and root C in the CT treatment likely reflects the greater root mortality and decomposition of the soybeans roots in this treatment. Average C:N ratios for fine living cottonwood, switchgrass, and soybean roots were respectively 32.6, 51.7, and 21.7. Following root death, the lower C:N ratios of the soybean roots would enhance decomposition rates, C respiration, and root C conversion to soil organic C with respect to that of the cottonwood and switchgrass roots. Thus the amount of C in this belowground component was generally lower than that in the CW or SG treatments. Storage of C in living roots or slowly decomposing roots would likely increase the ability of cottonwood and switchgrass to sequester C.
Soil C and N concentrations along with bulk density measurements were used to determine the mineral soil C and N content to a depth of 12 in. (30 cm) in 2009 prior to crop establishment and then in 2012 following the third growing season following establishment. Comparisons among treatments (Table 14) showed little change in N content in any of the three treatments. Soil C content appeared to have increased from 2009 to 2012 in the SG and CW treatments. However changes in C as well as N between 2009 and 2012 in these two cropping systems were not significantly greater than the changes in C or N within the CT cropping system (Table 14). Increases in mineral soil C tended to occur within the CW and/or SG treatments at the PTBES and SREC study sites but not the SF study site (Figure 21). Initial soil C content was higher at the SF than the other two study sites. The SF site had not been cropped for several years prior to the study while the other two sites had been cropped annually shortly before the initiation of the study. The establishment of the three cropping systems at the SF site may have reduced soil C at this site while the establishment of the CW and/or SG crops at the other two study sites may have increased soil C. These differences among study sites may have reduced our ability to detect any significant change in soil C among the cropping systems.
Soil microbial biomass, activity, labile C, and potential C turnover rates were all affected by treatments in 2011 (Table 15). The CW treatment had greater microbial biomass C and dehydrogenase activity and lower potential C turnover rates than the soybean-sorghum rotation. These results suggest that cottonwood fostered larger and more active soil microbial communities than those of the soybean-sorghum rotations typical of these sites, which may have contributed to the shorter potential C turnover rates observed for the CW treatment. Differences in these soil properties were not as pronounced between the SG and CT treatments. Only dehydrogenase activity differed between the treatments, with the SG treatment having greater activity. These soil parameters were chosen for observation in this study because of their sensitivity to changes in land management. Our results imply that converting these marginal agricultural sites to cottonwood has impacted soil microbial biomass, activity, and C turnover rates more than conversion to switchgrass. A possible implication of these results is that nutrient turnover rate potential has increased after conversion to cottonwood, possibly due to the lack of soil disturbance and biomass removal of this treatment relative to that of the CT and SG treatments.
Total Sequestered/Accumulated CN
The total sequestered C was determined by summing the; a) sequestered C in aboveground biomass during the study (crop yield 2009-2011), b) C in surface residual collected at time of harvest or at the end of the growing season in 2011 (surface residue 2011), c) C in the belowground biomass (roots) that were collected following the 2011 growing season (roots 2011) and d) the change in mineral soil C (depth of 30 cm) between the initial sample collection in 2009 and that following the 2011 growing season (soil 2011-2009). Total N accumulation was determined in the same way but by using the N rather than C estimates. Figure 22 shows the total average sequestered C and accumulated N for each cropping system and each of the four components used to compute these values (a-d). The CW and SG cropping systems generally sequestered 90-220% more C than the CT treatments. Differences in C among crop yields and changes in mineral soil C contributed to the higher C sequestering in the CW and SG cropping systems.
Collection of soil water samples began in mid-January and ended in May when soils dried and plant transpiration was increased due to warming climatic conditions. Nitrogen and C concentrations were summarized for the sampling dates of January 17 through May 9, 2012. Soil water concentrations of most N forms were greater in the CT than the CW or SG cropping systems during the entire collection period (Figure 23). However, only NO3-N and organic N concentrations were significantly (p<0.01) greater in the CT than the SG treatment while NO3-N, organic-N, and total N were significantly (p<0.01) greater in the CT than the CW treatment (Table 16). Average soil water NO3-N concentrations in the CT cropping system were 8-10 greater than those in the SG or CW cropping systems. Soil water C concentrations in the CT treatments were also higher than those in the SG or CW during the mid- to later portions of the collection period (Figure 24) but differences between the CT and other two cropping systems were not significant (Table 16).
Other studies have found higher losses of N from row crop agriculture compared to that associated with perennial grass production. McIsaac et al. (2010) found that NO3-N leaching from soils supporting a maize-soybean rotation were an order of magnitude greater than that from soils growing switchgrass. The nitrogen fixing ability of the soybeans in our study likely contributed to the higher soil water N concentrations of the CT treatment. Nitrogen inputs from fertilizer appeared to have little impact on soil water N concentrations since more N was applied to the SG treatment (105 N kg/ha) than the CT treatment (64 kg/ha) during the three year study period. In addition, soybeans and grain sorghum planted in the CT treatment are annual crops characterized by rapid decomposition of harvest residues and below-ground tissues. This decomposition would also contribute N to the soil. Comparisons of root biomass among the three cropping systems during the winter of 2012 indicated significantly higher levels of living roots in the SG and CW cropping systems 2.6-4.6 tons/acre (2.4-4.1 Mg/ha) than in the CT (0.41 tons/acre, 0.38 Mg/ha) cropping system. The maintenance of living cottonwood and switchgrass roots likely helped to absorb available N, reduce N inputs from decomposing roots, and thus increase N retention.
The flux of NO3-N losses below a depth of 12 in. (30 cm) is presented in Figure 25. Losses of NO3-N were an order of magnitude greater with the CT cropping system compared to that of the CW or SG cropping systems. Losses of N as NO3 in the SG and CT cropping systems were extremely small compared to the total N fertilizer inputs during 2010 and 2011 (CW=31.5 lbs/acre or 35.3 N kg/ha; SG=129 lbs/acre or 144 N kg/ha). Fertilizer N inputs to the CT treatment occurred only in 2010 when the grain sorghum was planted. N inputs to the CT cropping system during 2010 were 69 and 48 lbs/acre (77 and 54 N kg/ha) for the PTBES and SREC study sites respectively.
These results indicate that switchgrass and cottonwood are better able to retain N on site than the typical row crops grown on marginal soils in the LMAV. Conversion of these row cropping systems to cottonwood or switchgrass bioenergy crops could potentially reduce N losses to surface waters in the LMAV. Reductions of N losses likely reflect some reduction of inputs (either by fertilizer or N fixation by the soybean) but also increased uptake of available N by perennial crops.
PTBES: During 3,600 trap nights, I obtained 152 captures of 55 individual small mammals. I captured 5 species: hispid cotton rat (Sigmodon hispidus; 27.3% of individuals captured), Peromyscus spp. (60.0%), house mouse (Mus musculus; 3.6%), harvest mouse (Reithrodontomys spp.; 1.8%), and marsh rice rat (Oryzomys palustris; 7.3%) (Table 17). For all species and seasons combined, areas planted to switchgrass (located in the SG, CS, or SC treatments) produced the greatest proportion of captures (55%) and soybeans (CT) the least (9%) (Figure 26). Overall species diversity at the PTBES study site tended to be greatest with the cropping systems that combined the cottonwoods and switchgrass (CS and SC).
During winter, CW and SC produced the greatest number of individuals captured per 100 trap nights (2.22) and CT the least (0.56); species diversity was low in all treatments. For all species combined, switchgrass produced the highest proportion of captures (52%) and soybeans the least (2%).
During spring, SG produced the greatest number of individuals captured per 100 trap nights (2.22), with CW, CS, and CT producing the least (1.11); CS supported the greatest species diversity (0.69), while CW, SG, and CT supported the least (0.00). For all species combined, areas planted to cottonwoods (located in the CW, CS, and SC treatments) produced the highest proportion of captures (46%) and soybeans the least (15%).
During summer, SG produced the greatest number of individuals captured per 100 trap nights (6.11) and CW the least (0.00); SC supported the greatest species diversity (0.69). For all species combined, switchgrass produced the greatest proportion of captures (91%) and cottonwoods the least (0%).
During fall, CS produced the greatest number of individuals captured per 100 trap nights (2.22) and CW the least (0.00); CS and SC supported the greatest species diversity (0.69). For all species combined, cottonwoods produced the greatest proportion of captures (56%) and soybeans the least (6%).
SREC: During 3,600 trap nights, I obtained 309 captures of 183 individual small mammals. I captured 5 species: hispid cotton rat (13.7% of individuals captured), house mouse (62.8%), Reithrodontomys spp.; 1.6%), marsh rice rat; 20.8%), and least shrew (Cryptotis parva; 1.1%) (Table 18). For all species and seasons combined, areas planted to cottonwoods (in the CW, CS, or SC treatments) produced the highest proportion of captures (61%) and soybeans the least (17%) (Figure 27).
During winter, SG produced the greatest number of individuals captured per 100 trap nights (9.44) and SC the least (3.33); CW supported the greatest species diversity (0.99) and SG the least (0.00). For all species combined, cottonwoods produced the greatest proportion of captures (44%) and switchgrass the smallest (26%). The switchgrass crop was not successfully established in the SG, CS, or SC treatment at the SREC study site at this time, so these areas were primarily occupied by volunteer grasses and herbaceous vegetation.
During spring, CW produced the greatest number of individuals captured per 100 trap nights (3.89) and CT the least (0); CS supported the greatest species diversity (0.69). For all species combined, cottonwoods produced the greatest proportion of captures (0.75) and soybeans the smallest (0.02).
During summer, CT produced the greatest number of individuals captured per 100 trap nights (2.22), with SG and CS producing the least (1.11); CW supported the greatest species diversity (0.64). For all species combined, switchgrass produced the greatest proportion of captures (41%), while soybeans and cottonwoods produced the smallest (29%). As indicated for the fall measurements, switchgrass had not been successfully established and these areas were dominated by volunteer grasses and herbaceous vegetation.
During fall, CW produced the greatest number of individuals captured per 100 trap nights (21.67) and SG the least (3.33); CW supported the greatest species diversity (0.96), while SG and CT supported the least (0.00). Cottonwoods produced the greatest proportion of captures (74%) and soybeans the smallest (10%).
SF: During 3,600 trap nights, I obtained 99 captures of 51 individual small mammals. I captured 4 species: hispid cotton rat (27.4% of individuals captured), Peromyscus spp.; 3.9%), house mouse (56.9%), and woodland vole (Microtus pinetorum; 11.8%) (Table 19). For all species and seasons combined, the switchgrass crop growing in the SG, CS, and SC treatments produced the greatest proportion of captures (74%) and soybeans (CT treatment) the smallest (12%) (Figure 28). Overall species diversity at the SF study site tended to be greatest with the cropping systems that combined the cottonwoods and switchgrass (CS and SC).
During winter, CS produced the greatest number of individuals captured per 100 trap nights (4.44) and the greatest species diversity (1.39). For all species combined, switchgrass produced the greatest proportion of captures (52%) and soybeans the smallest (13%).
During spring, SG produced the greatest number of individuals captured per 100 trap nights (5.00); CW and CT producing the smallest (0.56). SG supported the greatest species diversity (0.64). For all species combined, switchgrass produced the greatest proportion of captures (94%) and cottonwoods the smallest (2%).
During summer, CT produced the greatest number of individuals captured per 100 trap nights (2.22), CS the smallest (0.00). For all species combined, switchgrass and soybeans produced the greatest proportion of captures (43%) and cottonwoods the smallest (14%).
During fall, SC produced the greatest number of individuals captured per 100 trap nights (1.11). For all species and seasons combined, switchgrass produced all captures.
Summary: Small mammal capture was typically greater in the cropping systems that included cottonwood and/or switchgrass (CW, SG, SC, CS) than the soybean-grain sorghum rotation (CT). These results suggest that converting conventional row cropping systems grown on these marginal soils to cottonwood and switchgrass bioenergy crops may increase small mammal populations and enhance the ecosystem functions provided by these small mammals. Although small mammal species diversity varied among seasons, at study sites where cottonwood and switchgrass was successfully established, diversity was generally greatest with the combined cottonwood and switchgrass cropping systems (CS, SC).
PTBES: With seasons and treatments combined, the PTBES was generally characterized by bare ground (34.2%), litter (27.8%), live graminoids (23.5%), and tall-growing herbaceous vegetation (20.6%) that produced cover (44.5%) up to 0.25 m in height. Percentage cover of bare ground, live graminoids, live tree, vertical vegetation density at 0.25, 1.25, and 2.25 m in height, canopy cover, and height of vegetation increased from winter to summer then decreased in the fall (Table 20). Litter and live vine coverage, dead graminoids and shrubs, dead trees, and herbaceous vegetation peaked in fall, winter, spring, and summer, respectively (Table 20). Soybeans were planted late due to unseasonably wet conditions; therefore, they were only present during the fall sampling period (Table 20).
Throughout the year, treatment CT was characterized by bare ground, SG by live graminoids, CW by herbaceous vegetation, SC by bare ground and live graminoids, and CS by bare ground and herbaceous vegetation (Table 21). Treatment CT had substantially less vertical vegetation structure at 0.82 ft (0.25 m) compared to all other treatments (Table 21).
Percent cover of live graminoids, dead trees, and live vines differed between small mammal capture and non-capture sites, when compared across all seasons,treatments, and species combined (Table 19). On average, captures sites were associated with 8.5% more live graminoids, 1.0% more dead trees, and 1.3% less live vines than non-capture sites (Table 22).
SREC: In general, across all seasons and treatments, the SREC was characterized by abundant bare ground (36.1%) and litter (39.3%) with a fair amount of live graminoids (19.1%) and live trees (16.0) that yielded adequate cover (39.1%) up to 0.82 ft (0.25 m) in height. Percentage cover of live trees and vertical vegetation density at 0.82 ft (0.25 m) in height increased from winter to summer and decreasing in fall (Table 20). Litter and herbaceous vegetation coverage peaked in fall, bare ground and dead graminoid in spring, and live graminoid, live tree, live vine, and vertical vegetation density at 0.82 ft (0.25 m) in height in summer (Table 23). Soybeans were planted in early summer and were only present during the summer trapping season (Table 23).
Throughout the year, treatments CT and SG were characterized by bare ground, CW by litter, SC by bare ground and litter, and CS by litter (Table 24). Treatment CW had substantially more vertical vegetation structure at 0.82 ft (0.25 m) in height compared to all other treatments (Table 24). The bare ground in the SG and areas planted to switchgrass in the SC treatment was due to the lack of swithgrass establishment at this study site.
Percentage cover of dead vines and vertical vegetation densities at 0.25, 1.25, and 2.25 m in height differed between small mammal capture and non-capture sites, when compared among all seasons, treatments and species combined (Table 25). On average, capture sites were associated with 0.5% more dead vines, 7.7% more vertical structure density at 0.82 ft (0.25 m), 7.5% more vertical structure density at 1.25 m, and 8.9% more vertical structure density at 7.38 ft (2.25 m) than non-capture sites (Table 25).
SF: In general, across all seasons and treatments, the SF was characterized by an abundance of live graminoids (40.2%) with litter (28.3%) yielding cover (54.5%) up to 0.25 m in height. Percentage cover of bare ground, live graminoid, live tree, live vine, vertical vegetation densities at 0.25, 1.25, and 2.25 m in height , canopy cover, and height of vegetation increased from winter to summer, and decreased by fall (Table 23). Litter coverage peaked in fall, dead graminoids and shrubs in winter, and herbaceous vegetation in spring (Table 26). Soybeans were planted in early summer thus they were only present during the summer sampling period (Table 26).
Throughout the year, treatment CT was characterized by herbaceous vegetation, SG and SC by litter and live graminoids, and CW and CS by live graminoids, with CT having substantially less vertical vegetation structure at 0.82 ft (0.25 m) compared to all other treatments (Table 27).
Percentage cover of bare ground, live graminoids, dead graminoids, canopy cover, and vertical vegetation density at 0.25 and 2.25 m in height differed between small mammal capture and non-capture sites, when compared across all seasons and treatments, for all species combined (Table 25). On average, capture sites were associated with 1.0% more bare ground, 20.6% more live graminoids, 7.1% less dead graminoids, 4.7% less canopy cover, 18.9% more vertical structure density at 0.25 m, and 7.9% less vertical vegetation density at 7.38 ft (2.25 m) in height than non-capture sites (Table 28).
Summary: Habitat characteristics varied greatly among seasons and study sites. The differences in these characteristics among study sites reflected the different success associated with crop establishment at the study sites as well as the timing of crop establishment in the CT treatment. These differences also contributed to the variability in habitats associated with small mammal capture. However at the study sites where switchgrass was successfully established (PTBES and SF), capture sites were significantly associated with greater amounts of live graminoids (8.5 and 20.6%). At the SREC study site which had the greatest cottonwood survival and growth, captures were positively related to the vertical density at 1.25 and 2.25 m. It seems likely that these habitat characteristics associated with switchgrass and cottonwood contribute to the greater capture success in these crops compared to that found with the soybean-grain sorghum rotation (CT).
Seventy three attended the PTBES field day. Twenty two people (30%) completed the post-event survey. This response to the survey was disappointing but was not a surprise after a long day of presentations. Twenty-one of those surveyed rated their knowledge of bioenergy. Before the training event, 11 participants rated their level of understanding at “beginner,” nine as “intermediate,” and one as “advanced.” After the event, the number of participants rating themselves as “beginner” dropped from 11 to three. The number of participants rating themselves as “intermediate” increased from nine to 16, and the number rating themselves as “advanced” increased from one to two.
Before the training event, the majority of participants rated themselves as a “beginner” with respect to knowledge of bioenergy. This is expected since they had received little training centered on bioenergy. After the training, the majority of participants rated themselves as having an “intermediate” or “advanced” understanding of bioenergy. This reveals that the training event met its goal of teaching landowners about the opportunities to produce bioenergy crops.
Past and potential future bioenergy crop production served as another indicator of the effectiveness of the training event. Two of those who participated in the survey stated that they had grown a bioenergy crop in the past. Nineteen stated that they had not. Of the two who had grown a bioenergy crop, one had grown 40 acres of canola, and the other had grown (or was growing) 800 acres of cottonwood. After learning about bioenergy, three participants stated that they would grow bioenergy crops in the future, citing switchgrass and sweet sorghum as the crops they would grow. Both of these crops were covered by presentations during the training event. After the field day, only one participant indicated an aversion to growing bioenergy crops. An additional 16 participants indicated that they were unsure whether they had been convinced to grow a bioenergy crop. Getting 95% of participants to at least consider growing a bioenergy crop met our goal for this event.
Of the 22 people who completed the survey, five indicated that they had used biodiesel fuel in highway vehicles; and 10 had used it in farm equipment. An additional 10 people indicated that they had not used biodiesel fuel. Since some of the guests for the field day were not producers, these 10 people may include some who do not own diesel engines.
Six people indicated that they would use biodiesel in highway vehicles and 12 in farm equipment after learning about biodiesel fuel. Four indicated that they still would not use biodiesel fuel. These four may be people who do not own diesel engines. The drop from 10 who had not used biodiesel fuel to four who refused after the field day, demonstrates that many producers are open to using biodiesel fuels after they learn what to expect from biodiesel fuel and how to use it properly.
The SF field tour was attended by 12 natural resource management professionals, farmers, and extension agents. Results showed a 4% increase in interest in growing switchgrass as a biofuel crop; 11 and 7% increases in directing more research to cultivating switchgrass and cottonwood, respectively, as biofuel crops; and a 4% decrease in interest in directing more extension programming efforts for growing switchgrass. The decreased interest in further extension programming devoted to these biofuel crops was driven by the perception that the absence of a current market for these fuels reduced the immediacy of need for an increased extension effort.
The results of these surveys indicate that producer attitudes towards bioenergy can be positively changed with training. Resistance to bioenergy usage may arise from several sources, including lack of opportunity, misinformation, poor experiences resulting from misuse, and ignorance. Education addressing misunderstandings and poor perceptions can increase the rate of bioenergy usage among producers. The lack of interest in increased extension programming for bioenergy revealed by one survey was due to a lack of bioenergy markets in that region at the time of the surveys; as markets develop it is likely that demands for extension programming would increase.
Educational & Outreach Activities
Pelkki, M.H. Renewable energy from forest biomass. Vo-Ag In-service, Bethesda Livestock and Forestry Branch Station, 24 June 2009.
Pelkki, M.H. Technological trends and production costs for forestry by products. Transition to a Bioeconomy: The Role of Extension. Little Rock, AR, June 30- July 1, 2009.
Liechty, H.O., C. Stuhlinger, M.A. Blazier, M.H. Pelkki, P. Tappe, C. West. 2009. Establishment of cottonwood/switchgrass bioenergy agroforests in the Lower Mississippi Alluvial Valley. North American Agroforestry Conference. May 31-June 3, 2009
Pelkki, M.H. America’s leaky bioenergy ark: holes in forest bioenergy policy. Society of American Foresters 2009 Annual Convention, Sept 27 – Oct 4, 2009, Orlando, FL.
Pelkki, M.H. Forest biomass feedstock supply in Arkansas. Arkansas Forest and Paper Council Annual Meeting. Chenal Country Club, Little Rock, AR. Oct 28 2009.
Pelkki, M.H. Carbon, biofuels, and traditional wood products – what’s the best fit for Arkansas’s Landowners? Caddo Chapter of Arkansas State Society of American Foresters, Arkadelphia, AR. Feb 18, 2010,
Liechty, H.O., K. Formby, and M.A. Blazier. Soil water chemistry during conversion of marginal Land to biomass crop production in the Lower Mississippi Alluvial Valley. Soil and Water Conservation Society, Annual Meeting. St. Louis, Mo. June 18-23, 2010
Pelkki, M.H. Decisions! Decisions! Carbon, biofuels, or wood: What should Arkansas landowners be producing for the future. Arkansas Forestry Association Annual Meeting. Oct 5-6, 2010, Little Rock, Arkansas.
Formby, K, H.O. Liechty, and M.A. Blazier, M. Monitoring soil water chemistry during establishment of bioenergy cropping systems with mixed Ion resins: Limitations and Potential Improvements. 2010 ASA-CSSA-SSSA Annual Meeting, Long Beach, Ca. 10/31/10-11/3/10.
Liechty, H.O. Bioenergy crop production and water quality in the Lower Mississippi Alluvial Valley. Arkansas Watershed Advisory Group Watershed Conference. Mt. Home, AR. Nov. 18-20, 2010.
Blazier, M.A and H.O. Liechty. Growing energy crops: An agroforestry approach. 2nd Annual Agroforestry Symposium. Columbia, Mo. Jan. 12, 2011.
Pelkki, M.H. Alternatives and risks for Arkansas’s landowners in the woody biomass markets. University of Arkansas Biomass Conference, Little Rock, AR, Aug 9, 2011.
Blazier M.A., R.P. Vlosky, H.O. Liechty, M.H. Pelkki, and E.L. Taylor. 2011. Extension programming to foster awareness of emerging agroforestry methods for producing biofuels in the Western Gulf Region. North American Agroforestry Conference, Athens, GA. June 4-9, 2011,
Blazier, M.A., H.O. Liechty, M.H. Pelkki, C. West, M. Alison, M. Establishing alley cropping systems for producing switchgrass and cottonwood on marginal agricultural soils of the Lower Mississippi Alluvial Valley. Annual North American Agroforestry Conference. Athens, GA. June 4-9, 2011,
Blazier, M.A., H.O. Liechty, M.H. Pelkki, C.P. West, J.J. Wang, J.L. Schuler, K.R. Brye. 2011. Carbon sequestration and greenhouse gas emission associated with cellulosic bioenergy feedstock production on marginal agricultural lands in the Lower Mississippi Alluvial Valley. Presented at USDA Agriculture and Food Research Initiative Director’s Meeting, Washington, DC. October 26, 2011
Blazier, M.A. Emerging crops for biofuels. Louisiana Soil and Water Conservation Society Annual Meeting. Alexandria, LA., November 18, 2011.
Blazier, M. Biofuels from forests: Management, Policy, and Economic Issues. Four-state Forestry on the Grow Meeting. Idabel, OK. . March 7, 2012.
Blazier, M. Biofuels from forests: Management, Policy, and Economic Issues. Mississippi Society of American Foresters Annual Meeting. Tupelo, MS. April 12, 2012
Pelkki, M. H. 2012. The tortoise and the hare of bioenergy development. 2012 Annual Meeting of the Arkansas Association of Facility Administrators. University of Arkansas at Monticello, Monticello, AR. April 5, 2012.
Blazier, M. and H.O. Liechty. 2012. Short-rotation forestry and growing biofuel crops between trees. NRCS landowner workshop. Bossier City, LA., August 10, 2012.
Liechty, H.O., M. Blazier, M. Pelkki, D. White Jr. and Z. Robinson. The Potential for Using Agroforests for Bioenergy Production in the Lower Mississippi Alluvial Valley . IUFRO 3.08.00 Small Scale Forestry Conference 2012: Science for Solutions. Amherst, Ma., Sept. 24-27. 2012.
Pelkki, M.H. , H. Liechty, M. Blazier, D. White Jr., and C. West. 2012. Building a better biomass ecosystem: cottonwood-switchgrass agroforests. Sungrant National Conference, New Orleans, LA., Oct. 2-5, 2012,
Liechty, H.O*. and M. Blazier. Soil carbon dynamics three years following conversion of marginal soils to cottonwood and switchgrass bioenergy crops. Sungrant National Conference, New Orleans, LA., Oct. 2-5, 2012.
Blazier, M, H.O. Liechty , Pelkki, M., C. West, K. Brye. 2012 Carbon sequestration and greenhouse gas emissions associated with cellulosic bioenergy feedstock production on marginal agricultural lands in the Lower Mississippi Alluvial Valley. Project Director Meeting for Agriculture and Natural Resources Science for Climate Variability and Change. Cincinnati, OH., Oct. 22, 2012
Liechty, H.O. and M. Blazier. 2012 Soil carbon, nitrogen, and water chemistry three years after conversion of marginal agricultural soils to switchgrass and cottonwood bioenergy cropping systems. ASA, SSSA, CSA 2012 annual meeting Cincinnati, OH, Oct. 21-25, 2012.
McElligott, K.M., H.O. Liechty, K. Brye, M. Blazier. 2012. Carbon Dynamics of Agroforest Systems in the Lower Mississippi Alluvial Valley. ASA, SSSA, CSA 2012 annual meeting Cincinnati, OH, Oct. 21-25, 2012.
Blazier, M. A., T. Clason, Z. Leggett, E. Sucre, S. Roberts, H. Liechty, M. Pelkki, P. Tappe, C. West, M. Alison , E. Vance. Alley cropping management systems for producing switchgrass as biofuel feedstock in the Southeast US. Society of American Forestry National Convention, Spokane, Washington. Oct. 24-28,2012.
Blazier, M., H.O. Liechty, M.H. Pelkki, 2012. Short-rotation forestry and growing biofuel crops between trees-LSU AgCenter “success stories” project highlights. LSU AgCenter Annual Conference. December 18, 2012.
Blazier, M., H.O. Liechty, M.H. Pelkki. 2012. Short-rotation forestry and growing biofuel crops between trees. USDA Natural Resource Conservation Service landowner workshop. Shreveport, LA. August 10, 2012.
Blazier, M., H.O. Liechty, K. McElligott, M.H. Pelkki, C. West, K. Brye, M. Alison. 2013. Carbon sequestration and greenhouse gas emissions associated with cellulosic bioenergy feedstock production on marginal agricultural lands in the lower Mississippi alluvial valley. 4th North American Carbon Program All-investigators meeting. Albuquerque, NM. February 4-7, 2013.
Blazier, M., H.O. Liechty, K. McElligott, M.H. Pelkki, C. West, K. Brye, M. Alison. 2013. Cottonwood and switchgrass bioenergy production systems in the lower Mississippi Alluvial Valley: impacts on soil carbon and nitrogen. Biennial Southern Silvicultural Research Conference. Shreveport, LA. March 4-6, 2013.
Blazier, M., T. Clason, H.O. Liechty, Z. Leggett, E. Sucre, S. Roberts, K. Krapfl. 2013. Soil carbon and nitrogen dynamics in switchgrass, loblolly pine, and cottonwood systems and in monoculture in the Southeast United States. North American Forest Soils Conference. Whitefish, MT. June 16-21, 2013.
Pelkki, M.H. 2009. Renewable and alternative sources of energy. LeadAR Class 14, Magnolia, AR. June 2009
Rohwer Bio-fuel Crop Day, Kelso, AR. July 30,2009.
SARE Grant Steering Committee meeting at SREC, Sept. 9, 2009.
SARE Grant Steering Committee meeting at PTBS, Feb, 5, 2010.
Blazier, M. Emerging markets for biofuels and bioproducts. Landowner workshop, Cleveland, Ms. July 27, 2010.
Blazier, M.A. Emerging markets for biofuels and bioproducts. Landowner workshop, Dean Lee Research Station, Alexandria, La. July 29, 2010
Blazier, M. Emerging markets for biofuels and bioproducts. Landowner workshop, Extension Office, Crowley, La. Sept. 29, 2010
Pine Tree Bioenergy Field Day. Pine Tree Branch Station, Pine Tree, AR. August 5, 2010.
SARE Grant Steering Committee meeting at PTBS, Jan. 20, 2011.
SARE Grant Steering Committee meeting at SREC, Jan. 20, 2011.
Blazier. M.A. Short-rotation forestry and growing biofuel crops between trees. Forest landowner meeting. Eldorado, AR, June 27, 2011.
Blazier, M. Forest biofuels workshop. LSU AgCenter Hammond Research Station. November 2, 2011. Hammond, LA.
Blazier, M.A. Biofuels in agriculture and forestry. LSU AgCenter Dean Lee Research Station. November 15, 2011. Alexandria, LA.
Rohwer Biofuels Field Day. Kelso, AR. Oct. 6, 2011.
Blazier, M.A. Biofuels in agriculture and forestry. LSU AgCenter Macon Ridge Research Station. Winnsboro, LA. November 29, 2011.
Pelkki, M. Interview with Mike Mueller, Monticello Advance for newspaper article on “Bio-energy research at the Arkansas Forest Resources Center”. October 3, 2011
Blazier, M. Short-rotation forestry and growing biofuel crops between trees. USDA Natural Resource Conservation Service landowner workshop. Shreveport, LA. August 10, 2012.
Blazier, M., R. Vlosky, H.O. Liechty, J. Johnson, M.H. Pelkki. 2013. Managing short-rotation woody crops in the Western Gulf region. Invited presentation given to Bankhaus Dome investors interested in locating biofuel facility in Western Gulf region. Baton Rouge, LA. February 28, 2013
Blazier, M. Perfect pair for biofuel: switchgrass and trees. Louisiana Agriculture. Fall 2009
Switchgrass and Cottonwood Agroforest Study: Bioenergy for the LMAV Fall Newsletter. 2010
Pelkki, M.H., H.O. Liechty, M.A. Blazier, D. White. Jr., and C. West. 2012. Building a better biomass ecosystem: Cottonwood-Switchgrass agroforests on marginal land. Proceedings from Sun Grant National Conference: Science for Biomass Feedstock Production and Utilization, New Orleans, LA. Retrieved from http://sungrant.tennessee.edu/NR/rdonlyres/3880A277-C502-4EC9-9DEB-C385186A5C85/3819/26Pelkki_Matthew.pdf
Robinson, Zackary. 2012. Small mammal occurrence and utilization of a cottonwood/switchgrass agroforest system in the Lower Mississippi Alluvial Valley. M.S. Thesis, University of Arkansas at Monticello, Monticello, Arkansas, USA.
Liechty, H.O., M. Blazier, M. Pelkki, D. White Jr. and Z. Robinson. 2012. The potential for using agroforests for bioenergy production in the Lower Mississippi Alluvial Valley. In: Meyer, S. R., ed. 2012. Proceedings of IUFRO 3.08.00 Small Scale Forestry Conference 2012: Science for Solutions. Sept. 24-27. Amherst, Ma. p 88-92.
Barry, J. 2012. Establishing cottonwood plantations. University of Arkansas, Division of Agriculture Research and Extension Factsheet. FSA5031-PD-9-12N
Wood, K.D. 2013. Small mammal habitat utilization of a feedstock agroforest system in the Mississippi Alluvial Plain. M.S. Thesis, University of Arkansas-Monticello, Monticello, Arkansas.
This project demonstrated a large variation in bioenergy crop establishment success and production levels among the three study sites. For example, establishment of switchgrass on the clay soils at the SREC study site was difficult. However, cottonwood production and establishment at this site was much greater than at the other two study sites. The SF study site which had been fallow for several years prior to study initiation had poor cottonwood establishment and survival, as well as the highest levels of herbicide application. Given the variability in characteristics and conditions of marginal soils in the LMAV, these results indicate that the specific bioenergy crop or establish procedures utilized will need to be carefully selected for a given location or soil. Even at the best sites, an extended establishment time (at least three years) may be needed before the bioenergy crop fully occupies the site and maximum biomass production levels are attained. Maximum cottonwood production may not occur until after the first harvest when the trees coppice and aboveground growth is accelerated.
Biofuel quality of the cottonwood appears to be slightly better than that for the switchgrass. It seems likely that cottonwood feedstocks may cost less to transport, provide a higher level of energy/unit weight, and produce less residual constituents (ash etc.) than switchgrass. In addition wood is currently used in several forms (pellets, chips, etc.) for energy production. If biomass production were similar for these two crops, cottonwood could be a superior feedstock compared to switchgrass.
Establishment of cottonwood and switchgrass do provide useful ecosystems services. Losses of nitrogen (leaching through soil) was an order of magnitude lower with cottonwood and switchgrass cropping systems than with typical row crop systems that are established on marginal soils in the LMAV (soybean-grain sorghum rotation). In addition the carbon sequestered by cottonwood or switchgrass (aboveground and belowground) was two to three times greater than that of the soybean-grain sorghum rotation. These services are valued by society and in some scenarios can provide a monetary value to the landowner. The cottonwood and switchgrass crops also appeared to provide important small mammal habitat and could increase the population of small mammals compared to more traditional cropping systems. Combining switchgrass and cottonwoods in an agroforest cropping system appears to increase the diversity of small mammals. Improvement of habitats and wildlife populations are important conservation goals in the LMAV.
Switchgrass and cottonwood bioenergy cropping systems are able to provide a substantial amount of bioenergy feedstock on marginal soils in the LMAV. However, establishment technologies associated with these bioenergy crops will need to be refined to reduce the risk of establishment failures when converting these marginal soils to bioenergy production. Establishing these bioenergy crops produces important ecosystem services valued by society which could generate a monetary value to landowners.
Soybean-Grain Sorghum Rotation
Dry land soybeans and sorghum input and production costs were obtained from USDA and LSU AgCenter (Deliberto and Salassi 2013). In these cases, the production costs include harvesting, but not transportation to grain storage or processing facilities. Production costs averaged ($796 and $756/ha) for soybeans and grain sorghum, respectively. From the per hectare costs and production quantities provided in Table 8, costs per oven dry ton of grain and grain + residue are given in Table 29. Based on observed moisture content and current market prices, soybeans have a value of approximately $525/oven dry (OD) ton ($476/OD Mg) delivered and grain sorghum a value of $325/ OD ton ($295/OD Mg). Given these values, the marginal nature of the three sites for row crop production is evident. Over the four year study period at three sites, 50% of the time the row crop planting was not profitable based on grain production alone (Table 29). Table 29 also shows the cost of biomass production using all the grain and residue for biomass, and in this case, only grain sorghum had an average cost of production under $100/OD ton (91/OD Mg). This estimate is optimistic, as it is based on 100% of residue recovery, which is unlikely.
The costs of cottonwood production are broken down into 1) the cost of the cuttings, 2) all activities related to the site preparation and initial establishment of the cuttings, and 3) all management activities that occurred following establishment until the trees are harvested. These costs occur over multiple years, and so they are all compounded over time at a 4% cost of capital to cumulative end of year four costs in Table 30.
Establishment of cottonwood using known, named clones incurred a substantial price premium. The cost of planting stock (cuttings) represented 26% to 63% of the total costs of production. Because of heavy grass and herbaceous weed competition on all three sites, substantial maintenance costs from repeated application of herbicides, mowing, and insecticide applications also occurred.
Since the cottonwood will regenerate by sprouting after harvest, we expect that there will be minimal need for planting cuttings. Due to mortality, we anticipate that with each rotation at most an additional 182 cuttings/acre (450 cuttings/ha) will need to be planted to maintain acceptable stocking levels. We have observed exceptional height growth on trees cut for the weight study, with first year growth of 10-14 ft (3-5) m. Some herbicide and insect control treatments will likely be applied following harvesting so the anticipated costs for the second rotation and beyond are provided in Table 31.
Based on the cost figures, and the accumulated biomass from Table 6, the average costs/OD weight of cottonwood production at the end of the first rotation is given in Table 32. These prices are “on the stump” costs and do not include harvest and haul costs to a bioenergy conversion facility. Cut and haul costs regionally for biomass are $15-17/green ton ($14-16/green Mg), or $30-35/OD ton ($27-32/OD Mg). Market value of woody biomass for combined heat and power at local wood processing facilities is $40-45/OD ton ($36-41/OD Mg).
However, if we assume that 1) four 4-year rotations of cottonwood can be produced from a single planting, 2) only 10% of the trees need to be replanted per rotation, and 3) biomass production rates reach the maximum (9.4 tons/ac or 21 Mg/ha) observed in the first rotation (Table 6), then the average discounted cost of 16 years of biomass production of nursery-run cottonwood clones (MIXED) is reduced to a stumpage cost of $20 to $26/OD ton ($18-23/OD Mg), and $35-41/ OD ton ($32-37/OD Mg) delivered to a biomass conversion facility. If the costs of known cottonwood clones could be similarly reduced to that of the nursery-run planting stock, then they, too, would have a similar average production cost. Even if the cost of the known clone cuttings remains high ($0.50/cutting), the average cost/OD ton of biomass over four rotations would be less than $30/OD ton ($27/OD Mg) on the stump and less than $45/OD ton ($41/OD Mg) delivered.
The economics of switchgrass production are a bit more complex since there are substantial costs of establishment during the first year but no harvest. After establishment, annual costs are relatively similar, but yields in year 2 are generally lower as the grass has not fully occupied the site. Yields are expected to stabilize at year 3, and should continue at these levels for 10-15 years. In our study, we apportioned the initial establishment costs across returns in years 2-4 assuming that we would have a minimum of 10 years of grass production before the stand would need re-establishment. Based on data collected from our management operations and published cost data (Popp 2007), the cost of switchgrass averages $80/ac ($198/ha) for a standing crop, ready to harvest. Harvesting costs for round baling on our three sites averaged $150/ac ($371/ha). Using these costs figures, Table 33 provides the cost of production per oven dry ton of switchgrass biomass.
The marginal nature of the three sites is reflected in the production and economic data. The costs of producing a ready to harvest ton of oven-dry biomass, is $65 to $914 ($59-824/ OD MG) for cottonwood and $13 to $56 ($12-50/OD Mg)for switchgrass. Grain production prices range from $189 to $4,488/OD ton ($17-4,403/ OD Mg). While using 100% of grain residue would lower production costs to $44-430/OD ton ($40-391/OD Mg), the removal of this residue may have a substantial negative impact on productivity and water quality. Additions of fertilizer to replace potential deficiencies in nutrients due to the removal of harvest residues would also raise production costs.
The cost of producing cottonwood may decrease following the initial harvest (after age 4). Increased cottonwood production and reduced establishment activities are likely to occur after the initial harvest and may lower woody biomass production costs to as low as $20-26/OD ton ($18-23/OD Mg). Additionally, if low-cost cuttings and better attention to the soil and site conditions are used when establishing cottonwood, marginal lands could support more rapid tree growth.
Only low levels of bioenergy crops are planted in this region. The low level of interest in establishing bioenergy crops reflects the lack of stable markets for these crops. Since cottonwood and switchgrass are perennial crops where production is maximized several years following establishment, landowners are reluctant to invest in planting these crops without long-term markets. Although farmers are curious about growing bioenergy crops, the lack of markets in this region reduce the perceived need for bioenergy education programs for farmers.
Areas needing additional study
In order to reduce the risk of bioenergy crop establishment failure and high costs associated with conversion of marginal soils in the LMAV to bioenergy crop production, better site selection tools and establishment procedures will need to be developed. These tools would determine what bioenergy crop is best suited to a given soil or location (cottonwood or switchgrass), the suite of activities that should be used to establish the crop with a minimal amount of risk, and the acceptable establishment/maintenance costs that could be utilized to obtain a profit from the harvested crops.
More long-term studies are needed to estimate the actual production rates, management costs, and the ecosystem services associated with these bioenergy crops. Our study occurred over a three-four year period but to better understand how these cropping systems impact ecosystem services or quantify the potential economic/production characteristics of these bioenergy crops, information during 6-10 year period is likely needed.