A data entry project conducted on behalf of Professor Ted Ferris, Department of Animal Sciences. The purpose of this research is to evaluate the impact of this program as a way to inform and educate the public regarding food production and dairy farming.
A web based survey of Michigan residents living in the Traverse Bay Watershed focusing on climate change and global warming. The research was conducted on behalf of Professor Patricia Norris, Department of Fisheries and Wildlife and funded through a Michigan Sea Grant.
Web based survey of Michigan residents and key policy stakeholders on the impact of bio-energy development in Michigan communities and the economic and environmental impact of bio-energy facilities in Michigan. This research was conducted on behalf of Weston Easton, PhD Candidate in the Department of Sociology and Dr. Stephen Gasteyer, Department of Sociology at Michigan State University.
Web-based survey using a purchased panel of Michigan adults to gather public opinions related to threats posed by Asian carp in Michigan’s Great Lakes and preferred responses to these threats. This research was conducted on behalf of Dr. Meredith Gore, Department of Fisheries and Wildlife, College of Agriculture and Natural Resources, and Dr. Mark Axelrod, James Madison College and was funded by a Michigan Applied Public Policy Research Grant.
Web-based survey of Michigan adults to gather public opinions related to threats posed by wolves in Michigan and preferred responses to these threats. This research was conducted on behalf of Dr. Meredith Gore, Department of Fisheries and Wildlife, College of Agriculture and Natural Resources, and Dr. Mark Axelrod, James Madison College and was funded by a Michigan Applied Public Policy Research Grant.
A multi-university research study designed to collect current information on weed management decision and practices from agricultural producers across the United States with specific focus on single and multi herbicidal resistant weeds. OSR is responsible for data collection using both a web-based and self-administered data collection approach.
