2018 Conference

Individual Paper Presentation

Previous research has found that place attachment and relationship with the landscape are important determinants for an individual’s support or opposition to a windfarm.  This research has largely suggested that those residents who value the landscape more for its utility (e.g., as a working landscape) and less for its scenic value are more supportive of wind energy (Hall et al., 2013; Otto and Leibenath, 2014; van der Horst, 2007; Veelen and Haggett, 2016).  Thus, understanding the relative proportion of each of these types of residents in a community may help to predict community acceptance.  Indeed, the extremely high support for wind energy in some communities—even among those who are not directly compensated—has been attributed to high proportions of residents who have a connection to agriculture or “the farmer community” (Slattery et al., 2012; Sowers, 2006).  Gathering individual-level survey data, however, to predict attitudes can be both time-consuming and expensive.  This paper considers the extent to which existing public datasets (e.g., U.S. Census, USDA Census of Agriculture) that measure community-level land-use characteristics such as population density, percentage of land in agricultural production, and percentage of seasonal (vacation) homes can be used to predict community acceptance of wind.  This exploratory study focuses on four Midwestern states (IL, IN, MI, MN) where rural communities run the spectrum from agriculture-centric to those comprised of heterogeneous interests including rural-to-urban commuters and amenity-based landowners.  We employ a survey of wind energy experts in each state to rank the relative level of contention associated with siting of each of the state’s utility-scale windfarms, and then consider whether there is any correlation with the census-derived land-use characteristics.