Performing Department
Natural Resources
Non Technical Summary
Biofuel production in the United States has increased dramatically in recent years, with production expanding from 1.6 billion gallons in 2000 to 9 billion gallons in 2008. This expansion has been driven, in part, by the surge in state and federal mandates to promote the industry. Despite this increase in production and consumption, however, the ultimate interactive effects on the economy and environment remain unclear. The Prairie Pothole Region (PPR) of the upper Midwest has emerged as the largest source of ethanol production in the country. In addition to the large amounts of corn produced throughout the region, perennial grasses (e.g., switchgrass) of the PPR are prime candidates for cellulosic ethanol production because of their high biomass production, tolerance to climatic conditions, compatibility with conventional farming practices, and minimal maintenance requirements. Additionally, the fibrous root systems of these grasses are essential for reducing runoff, increasing soil organic matter, sequestering carbon, and changing soil surface hydrology. However, perennial grasses, in addition to affecting hydrological dynamics, also make the region attractive to wildlife. The PPR is critical for waterfowl recruitment, producing 50-80% of the continent's duck populations, and providing breeding habitat for more than half of the total number of grassland bird species breeding in North America. Therefore, even small, incremental reductions in wildlife benefits due to misdirected policies for biofuels production may have significant, continental impacts on wildlife populations. If biofuel production and wildlife conservation are to be compatible, it will require careful management, robust science, and a decision making framework sensitive to the needs of producers and other stakeholders so as to balance the ecological, economic, and sociological principles of diverse agricultural systems. Members of the National Research Council recognize that more comprehensive systems frameworks are needed to examine the interconnected environmental, economic, and social impacts of biofuels development and to allow the outcomes of alternative systems to be consistently evaluated and compared. The National Resource Council has also noted that to ensure the sustainability of new fuels, economic incentives will need to be provided to farmers and developers to use a systems approach by addressing soil, water, and air quality; carbon sequestration; wildlife habitat; and rural development. The research presented here will improve our understanding of the linkages among processes for environmentally, socially, and economically sustainable production of biofuels at diverse spatial and temporal scales. Results of this work are anticipated to have local and regional significance in establishing "best management practices" for biofuel/bioenergy production while minimizing impacts to wildlife populations. Several peer-reviewed papers and both technical and non-technical reports are expected to be generated from research results.
Animal Health Component
(N/A)
Research Effort Categories
Basic
25%
Applied
75%
Developmental
(N/A)
Goals / Objectives
The objectives of this project are to: 1) Determine how different harvest strategies (cutting frequency/intensity)and establishment techniques (seeding rate, use of cover crops, etc.) affect biomass production/quality in native grasslands, 2) Determine how how different harvest strategies and establishment techniques for bioenergy production affect wildlife diversity (birds, small mammals) in South Dakota, 3) Provide an analysis of the economic trade-offs associated with biomass and wildlife production based on results obtained, and 4) Assist managers and the public with development of "best management practices" for sustainable harvest of cellulosic biofuels while minimizing negative impacts to wildlife populations.
Project Methods
Small mammal response to biofuel establishment strategies will be analyzed at Oak Lake Field Station outside of White, SD, using a split plot, repeated measures, randomized block design. Each block (n = 3) represents a separate year of the study and each will be comprised of twelve experimental plots. These plots will include four different treatments (switchgrass monoculture, mixed perennials, corn/switchgrass, and soybeans/alfalfa) - each repeated three times. The plots will be planted the spring of each year with the first year planted into residual wheat stubble. Half of each plot will be harvested in the fall of each year. Small mammals will be monitored 3 times per year from May until snowfall in each plot using a grid of 8 trapping points per plot. Four of these points will be within the harvested part of each plot, and the other four points will be in the non-harvested section of each plot. Each specimen will be identified to species and individually marked to allow for abundance and diversity estimates. Plant composition and yield will be analyzed by colleagues in the Department of Plant Sciences. Game and non-game birds response to different harvest strategies will be assessed in southeastern SD using a randomized block design with 4 blocks and 3 treatments (12" stubble, 4" stubble, and no-harvest control). Harvest treatments were applied in the fall of 2008, 2009, and 2010 with bird surveys happening in the summer following treatment. Songbirds are being surveyed using standard spot mapping techniques and game birds (waterfowl and pheasants) are being surveyed using nest dragging. Surveys are conducted 4 times per summer to assess total abundance and diversity of bird species. Waterfowl and pheasant nest success is also being monitored. Associated vegetation surveys will record plant species composition, biomass production (total yield) and composition (i.e., mineral content), and structural diversity (visual obstruction, dead and live height, etc.). Results of game bird surveys and biomass quality/quantity will then be used to complete associated economics analyses via the Department of Economics. Results will be analyzed using a mixed model Analysis of Variance (ANOVA) with fixed treatments and random block effects. Because measures of diversity do not follow normality assumptions, alternative techniques to robustly analyze those data are being explored. Several peer-reviewed manuscripts are anticipated from this work.