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Task 2. Development of a Global Energy Crop Productivity Model

Impact and Rationale. Evaluation of the bioenergy production potential from land made available via pasture intensification (Task 1) and various strategies incorporated into integrated analyses (Task 5 and Task 6) requires estimation of how much biomass could be produced on this land. Thus a model that calculates energy crop productivity (e.g., Mg/ha/yr) as a function of land properties in a given location is needed.

Approach. We propose to develop a global energy crop productivity model for perennial energy crops, which does not now exist. Since no one crop is best for all sites, the model will calculate the maximum productivity for several different crops as a function of local variables.

The selection of specific crops has not been finalized, but it is anticipated that C4-perennials will be emphasized in light of their inherently higher productivity and water use efficiency as compared to C3 plants (Nobel, 1991). CAM (crassulacean acid metabolism) plants will likely also be included in light of their very high water use efficiency, consequent ability to grow in semi-arid regions, and intriguing possibilities for producing bioenergy crops on land that has little value for food production and currently offers little economic return (Nobel, 2009; Sommerville et al., 2010). A possible set of representative energy crops might be sugar cane/energy cane, miscanthus, switchgrass, and agave.

Consistent with the forward-looking character of the GSB project, both current and potential future performance will be analyzed – including for example foreseeable development of plant varieties with increased drought or cold tolerance.

Well-developed productivity models exist for several energy crops including sugar cane/energy cane, miscanthus (Miguez et al., 2010), and switchgrass (Wullschlegger et al., 2010). Consistent with sugar cane's status as a commercial crop, models have benefitted from extensive calibration on multiple continents. More limited, although still substantial, calibration with field results is available for miscanthus and switchgrass. Productivity modeling and related calibration is the most limited for agave.

In addition to being a vital link in estimating bioenergy production potential, it is anticipated that developing a global energy crop model will enable mapping which crops are expected to offer the highest biomass yields at a given location as a function of geographically-distributed variables. This effort will necessarily involve projecting productivity for areas for which no data are available based on other areas, in some cases from the other side of the earth, with apparently similar values for model variables such as temperature and climate. Developing the global model will thus provide a valuable tool based on the best data available, and will also provide a framework for identifying key gaps in available data and modeling capability as well as a framework for incorporating future improvements.

Activities targeting evaluation and integration of global land use and land cover databases will be coordinated closely with Task 1.

Leadership. Task 2 activities are led by Keith Kline of Oak Ridge National Laboratory. Co-leaders may be added in the future.

References

Last Updated August 14, 2012