Date of Award
Level of Access
Doctor of Philosophy (PhD)
Ecology and Environmental Sciences
Kathleen P. Bell
Second Committee Member
Mario F. Teisl
Third Committee Member
Christopher S. Cronan
Land change processes are complex and intertwined, yet planning processes often consider land uses independently. Land use modeling can facilitate cohesive planning across land uses, particularly when stakeholders are involved. Scenarios — alternative visions of the future — can be created with land use models, enabling us to visualize change in a community or region. Scenarios can provide context for policy decisions, but they are also becoming a form of science communication, translating complex, uncertain relationships into stories for a broader audience. Increased use of scenarios as a communication tool creates a need to understand the impacts of scenarios on the general public, particularly around public participation. Most research on scenarios has focused on methods development, with scenario evaluation in its infancy. In this dissertation, I have developed a multi-land use model for exploring scenarios and conducted two social science experiments around personal relevance and citizen engagement with land use scenarios.
In Chapter 1, to develop a multiple land use allocation model that can allocate change for multiple land uses, integrate stakeholder-derived suitabilities from Bayesian network models, and create patch-scale land use transitions, I present a rule-based cellular automata land use model, Land Use Spatial Allocation Model (LUSAM), which can explore scenarios of land use change. Constructed in NetLogo, a cellular automata modeling platform, the Land Use Spatial Allocation Model, LUSAM, uses flexible model parameters to vary the spatial allocation of four land uses across the scenarios—i.e., Development, Conservation, Agriculture, and Forestry. These parameters alter the size, shape, and distribution of new land use patches. Based on stakeholder input, I constructed a series of land use change scenarios for the year 2036 in the Lower Penobscot River Watershed in central Maine, using LUSAM. I evaluated these scenarios with visual inspection and landscape metrics, finding differences in mean patch size, total edge, and clumpiness.
In Chapter 2, I test the effectiveness of the reduced Personal Involvement Inventory, as applied to scenario narratives, and examine relationships among personal relevance, scale of scenario presentation, and sense of community. To do this, I conducted a survey experiment of 150 undergraduate students to test the sensitivity of personal relevance to narrative scenarios presented at three geographic scales (town, county, and state). In Chapter 3, I investigate scenarios’ effects on citizen engagement, by conducting a survey experiment (n = 270) to test for effects of viewing scenario narratives on willingness to participate in land use planning activities. I tested three combinations of two scenarios (Current Trends plus one of three other scenarios) and two time periods (2033 and 2053), comparing survey responses of individuals reading a set of scenarios with individuals who did not read scenarios.
Results of the two social science experiments in Chapters 2 and 3 suggest scale of presentation does not affect individuals’ personal relevance of the scenario, in contrast to local/global message framing research. I did find differences in sense of community at the state level from town and county levels. Sense of community also was a predictor of personal relevance and viewing scenarios can affect one’s sense of community. I found reading scenario narratives affected willingness to participate in land use planning activities and perceived self-efficacy around participation. Interest and sense of community were other factors contributing to willingness to participate. I also tested an indirect mediation model, finding self-efficacy partially mediated the effect of viewing scenarios on willingness to participate.
Johnson, Michelle Leigh, "Engaging the Future with Land Use Scenarios" (2014). Electronic Theses and Dissertations. 2217.