ARS | Publication request: Effect of landscape positions and their associated soil and terrain attributes on biomass crop yield and growth rates

Submitted to: Meeting Abstract
Publication Type: Abstract
Publication Acceptance Date: August 1, 2008
Publication Date: August 18, 2008
Citation: Johnson, G.A., Thelemann, R.T., Cai, H., Banerjee, S., Sheaffer, C.C., Jung, H.G., Petersen, K., Tschirner, U. 2008. Effect of landscape positions and their associated soil and terrain attributes on biomass crop yield and growth rates [abstract]. Short Rotation Crops International Conference: Biofuels, Bioenergy, and Bioproducts from Sustainable Agricultural and Forest Crops Proceedings, August 18-22, 2008, Bloomington, Minnesota. p. 20.

Technical Abstract: In order to advance the use of biomass crops as a feedstock for a wide range of bioindustrial applications, it is essential that we optimize the placement of crops at the field scale in a way that will maximize overall productivity and profitability while addressing critical environmental and ecological issues. The value gained by selective placement of dedicated biomass crops will come from an understanding of how crop growth and productivity is influenced by terrain, soil properties, and other attributes. The ability to predict optimal plant growth across species is critical in developing novel approaches to biomass crop management. We will present information from field research exploring 1) differences in plant growth and development between woody tree species (willow and poplar), a perennial forage legume (alfalfa), a warm-season perennial grass (switchgrass), and a warm-season annual grass (maize) as a function of landscape position and 2) the relationship between plant growth and environment across seven landscape positions. Results from 2 years of monitoring plant growth and the biomass yield show that landscape position does have an effect on plant growth and development. In addition, our analysis reveals that certain soil and terrain properties affect these yield values differently depending on the crop and/or landscape position. Our use of Bayesian statistical methods in addition to traditional approaches allows us to not only realize the effects of landscape position properties on biomass crops but also gives us the ability to predict yield when such landscape position properties are known.