Location: Natural Resource Management Research2009 Annual Report
1. Five year on-farm study documents significant increases in soil carbon under switchgrass. Environmental outcomes associated with switchgrass production require information on net greenhouse gas emissions, of which data on soil carbon change is a key component. To date, nearly all information on soil carbon change under switchgrass have been based on either modeled assumptions or small plot research. A five year on-farm study was conducted to determine change in soil carbon on 10 switchgrass fields in North Dakota, South Dakota, and Nebraska. Across sites, soil carbon increased significantly at the 0-1 ft and 0-4 ft soil depths, with accrual rates of 0.5 and 1.3 ton C/ac/yr, respectively. This study underscored the potential of switchgrass to serve as a carbon-negative bioenergy crop within the central and northern Great Plains.
2. Corn-soybean tillage economics. While no-till and minimum tillage systems could provide environmental benefits, use of these practices for corn and soybean production in the Northern Corn Belt has been limited due to the perception that they are less profitable than conventional tillage practices. Economic analysis was conducted at the Northern Great Plains Research Laboratory using data from a 7-year field study comparing 8 different tillage practices conducted near Morris, MN by researchers at the North Central Soil Conservation Research Laboratory. This research showed that average net returns could be increased by as much as $37 per acre by switching from moldboard plow tillage to a minimum tillage fall residue management system. Furthermore, all but one of the minimum tillage and no-till systems evaluated were less risky than the two conventional tillage systems commonly used in the area. This research provides information to producers that minimum tillage and no-till systems can be economically viable alternatives to conventional tillage practices, and could lead to greater adoption of these systems in the northern Corn Belt.
3. Drivers of Agricultural Production Systems. Understanding factors (drivers) that influence the structure of agricultural production systems is important for producers, researchers and policy makers. ARS scientists from four different locations are holding producer orientated workshops in different regions of the country to identify ‘Principles of Integrated Agricultural Systems’. One of the major outcomes, of the four workshops which have been held to this point, is identification of social, economic, technological and environmental drivers of agricultural systems. Identification of these drivers provides producers, researchers and policy makers the ability to identify factors that shape agricultural systems, a way to evaluate the impact different drivers have on shaping agricultural systems and a means to initiate assessment of the future direction of their agricultural system,
4. Land Allocation Model (LAM). One of the most basic and expensive resources in agricultural enterprises is land. Optimally allocating this valuable resource among different enterprises can be difficult and has substantial impacts on profitability and sustainability of the production system. LAM is the Land Allocation Model, a matrix model developed by the Northern Great Plains Research Laboratory, USDA-ARS to evaluate factors that drive land allocation decisions. The model utilizes producer derived information to evaluate environmental, economic, production and producer preference factors that underlie land allocation decisions between enterprises. The model utilizes information that is relevant and easily accessed by producers and ARS is currently working on developing an Excel spreadsheet version of the model. Although the current matrix only incorporates four enterprises, the matrix was designed so that additional benefits and parameters could be included. The model provides a means for producers to optimize land allocation, evaluate factors that impact land allocation and calculate specific net returns that may shift land allocation between enterprises.
5. Stella Model to Test Agricultural Sustainability. One of the major challenges for agriculture is to develop sustainable production systems. However, testing the sustainability of different production systems at a field scale is difficult because of enormous resource requirements. The Northern Great Plains Research Laboratory collaborated with scientists at other locations to develop a computer model in a Stella® modeling environment that compared the sustainability of conventional crop system, an extensive range livestock system and an integrated crop-livestock system. Different indicators were developed for the social, economics and environmental aspects of sustainability. Each of the systems affected the indicators differently illustrating that there is no single best system to enhance agricultural sustainability. The model gives us the opportunity to explore interactions within various production systems, and determine the relative impact of management inputs on indices.Liebig, M.A., Schmer, M.R., Vogel, K.P., Mitchell, R. 2008. Soil Carbon Storage by Switchgrass Grown for Bioenergy. BioEnergy Research. 1:215-222.