Kathrine D. Behrman, h* Manyowa N. Meki,[19] [20] Yanqi Wu[21]
and James R. Kiniry,’a

Introduction

Switchgrass (Panicum virgatum L.) is a highly productive, warm season, perennial, C4 grass that is native to most of the central and eastern U. S. (Sanderson et al. 1996). It has a high leaf area index (LAI) and rooting depths of more than 2.0 m, which provide access to large amounts of soil moisture and nutrients (Kiniry et al. 1999). Switchgrass is tolerant of poorly and well-drained soils, nutrient-depleted lands, and low pH, thus allowing it to produce reasonable biomass yields on marginal agricultural soils and under drought stress conditions (Moser and Vogel 1995; McLaughlin et al. 2006; Blanco-Canqui 2010). In addition, switchgrass requires fewer chemical

inputs (fertilizers and pesticides) than traditional row crops and miscanthus (Miscanthus x giganteus J. M. Greef & Deuter ex Hodk. & Renvoize) while maintaining relatively high yearly biomass yields (McLaughlin et al. 2006). These qualities make it one of the leading potential biofuel crops for the Southern and Northern Great Plains (Perlack et al. 2005).

The main objective of this chapter is to highlight five applications of process-oriented models of switchgrass growth and show how they can be used to generate a better understanding of large-scale switchgrass biomass production. Model differences are presented to give the reader an idea of the underlying assumptions and an understanding of why there are differences in model output. However, we are not trying to compare all the differences in model assumptions and functionality. Instead, see Surendran Nair et al.

(2012) for a comprehensive review of the differences between the models developed to estimate bioenergy crop production.

This chapter begins by describing the biology of switchgrass as a biofuel crop and introducing several types of crop models. Next, we show how process-oriented crop models have been used to estimate switchgrass biomass production and assess water use efficiency (WUE) of major switchgrass ecotypes in the U. S. Third, we highlight how mechanistic models can be used to determine the impact of different management scenarios on short-term yield production. Fourth, we show how models can be used to determine the long-term effects of biomass production on soil organic carbon (SOC), soil nutrients, erosion, and water quality. Lastly, we highlight studies that have analyzed the potential impacts of climate change on sustainable biomass production.