Carbon Cycling in Perennial Biofuel Management Systems Tracy M. Wilson and Jason G. Warren Graduate Student, Associate Professor, Department of Plant and Soil Sciences, Oklahoma State University, Stillwater, OK Results and Discussion Introduction Increasing demand for clean, renewable and sustainable fuel sources has stimulated interest in cellulosic biofuels Cellulosic biofuels can offset CO2 emissions Perennial biofuel feedstocks may also sequester C in soil However, few efforts have been made to assess the impact of species selection and harvest frequency on soil C sequestration in perennial biofuel feedstock production systems Experiment 1 In Exp. 1 there were no interactions for yield between harvest frequency and grass species, therefore data is pooled by species (Fig.1) and harvest frequency (Fig. 2). Harvest frequency was only significant in 2009, when the single harvest produced more yield, biomass C, residue and residue C (Fig. 2). In 2009 yields were low due to low rainfall in May and June (Fig. 3), therefore no significant differences were observed among species (Fig. 1). However, the carbon mass harvested from switchgrass was significantly greater that that in the eastern gammagrass. In 2010, miscanthus provided significantly greater yields than the remaining species. The same trend was seen in biomass C harvested (Fig. 1). Despite these differences in yield and residue, soil carbon was not affected by treatment (Table 1). Objectives The objective of this research is to evaluate the impact of species selection, harvest frequency, switchgrass variety on soil carbon sequestration under perennial biofuel feedstock production systems. Figure 2: The differences in yield between single harvest treatments and split harvest treatments in 2009. Means followed by different letters are significantly different at the 0.05 probability level. Methods In the spring of 2009, management was reestablished in a small plot study (originally initiated in to provide long-term monitoring of SOC sequestration Established on a Kirkland silt loam at the Oklahoma State University, Agronomy Farm in Stillwater, OK Experimental design is a randomized complete block design with 6 treatments and 4 replicates, each plot is 3m by 6m Treatments include 3 species: ‘Alamo’ switchgrass (Panicum virgatum) , miscanthus (Miscanthus spp.) and eastern gammagrass (Tripsacum dactyloides) The harvest frequency treatments were: Single harvest at the end of the growing season (Oct-Nov.) Split harvest treatment- harvested at mid season (Aug.) and again at the end of the growing season Yields were harvested from a 1m by 6m area of each plot Residue in each plot was taken from a 0.35m2 area. Biomass and residue subsamples were dried at 60°C for dry weight determination. Both biomass and residue were analyzed for total C and N. The second experiment (Exp. 2) was established in June 2006 to evaluate the impact of switchgrass variety selection on biomass yield. These plots are harvested annually after the growing season Soils were collected in early spring time with a hydraulic probe to a depth of 80 cm and section into 0-10, 10-20, 20-40, and 40-80 cm. Soils were analyzed for bulk density, total C, inorganic C, and organic carbon by their difference. Experiment 2 Differences in soil carbon mass below 10 cm were not observed among varieties (data not shown). Exp. 2 showed that soil carbon mass in the surface 10 cm was proportional to the previous growing season yields (Fig. 3). Soil carbon was also proportional to the 3 year average yields for these varieties, yet this relationship was weaker (R2=0.8884) than the relationship shown in Fig. 3. Soil carbon under 3 varieties did not show this relationship. The average carbon mass in soils under these varieties was 14.9 Mg C ha-1, which is similar to that found in the alleys (alleys were chemically fallowed for the duration of the experiment). Figure 1: The differences in mean yield between species in 2009 and 2010. Means followed by different letters are significantly different at the 0.05 probability level. Figure 3: Exp. 2. The relationship between the 2009 mean yield and soil C mass (0-10cm) in soils collected in spring 2010. (The alleys in this experiment contained 15 Mg C ha-1.) Conclusions Significant differences found between harvest frequency in 2009 but not in 2010 indicate there is an interaction between harvest frequency and environmental conditions during the growing season. The data also indicated that miscanthus can outperform switchgrass and E. gammagrass under favorable conditions but that switchgrass assimilates the most carbon of the three species under low yield conditions. Soil Carbon was not affected by species or harvest frequency, which may be explained by the lack of yield differences in the years prior to soil collection. Exp. 2 suggests that soil carbon is generally proportional to yield. However, this did not hold true for 3 varieties, indicating that additional mechanisms also influence soil carbon storage. These mechanisms may include differences in the distribution of organic carbon inputs or differences in soil respiration under these 3 varieties compared to the varieties under which soil carbon appears to have accumulated. Table 1: Cumulative soil organic carbon content in soils under each species and each harvest frequency treatment. Species Harvest Frequency ------------------Spring 2009------------------ ------------------Spring 2010------------------ 0-10cm† 0-20cm 0-40cm 0-80cm 0-10cm ----------------------------------------------------Mg ha-1----------------------------------------------------  Contrast Comparisons of Species Switchgrass 17a‡ 28a 47a 65a 17a 29a 46a 64a Miscanthus 18a 67a E. Gammagrass 62a 16a 27a 44a  Contrast Comparisons of Harvest Frequency Single 45a Split † The cumulative carbon mass is the carbon measured in each segment from the soil surface to the indicated depth. ‡ No significant interactions between species and harvest frequency were observed therefore contrast analysis were use for comparisons. Means followed by different letters are significantly different at the 0.05 probability level. Acknowledgements We thank Austin Hudson and Andrew Whitaker for research and technical support and the Oklahoma Bioenergy Center for financial support.