Dorlisa Minnick, an affiliated scientist with SU’s Center for Land Use and Sustainability is currently analyzing the data from our basin-wide land use survey.
During summer 2016, a future land use survey was disseminated basin-wide to confirm or refute findings from our DRB2070 workshops. To date, our survey has received over 600 views and 180 entries. Of these entries, 122 responses provided sufficient information for analysis. A subset of questions and responses is provided below:
Survey Question: How influential do you believe each of these catalysts will be in future land development in the DRB (up to 2070)?
A development catalyst is something that will stimulate population growth, economic growth, or land development.
Survey Question: How influential do you believe each of these catalysts will be in land protection in the DRB (up to 2070)?
A catalyst for land protection is something that will lead to more protected land, such as land preservation programs or incentives to redevelop existing urban land.
Survey Question: Which example scenarios do you think are important to consider for the DRB in 2070?
Land use scenarios are stories about how a region may change over time. They begin by describing where the region is today and continue by recognizing the range of plausible choices that communities and stakeholders might make about how land, water, and other resources will be used.
Analysis- Employment Influence
In analyzing the DRB survey data from 122 respondents, we first categorized employment into 3 types (Private company, Educational setting, and Government) and collapsed age categories (18-35 y/o; 35-45 y/o; 45-55 y/o; 55+ y/o) before testing1 against dependent variables (SWOT statements; Development catalysts; Protection catalysts; and Future land use scenarios).
We were interested in whether employment type may have been influential in how individuals responded to survey questions. For 23 of the 27 dependent variables, there were no statistically significant differences in responses. However, responses differed in statistically significant ways on the following 7 variables:
Development Catalysts
- Distribution of casinos as a potential development catalyst were ranked statistically higher among the educational work setting group of respondents than the private company respondents.
- Expanded tourism as a potential development catalyst were ranked statistically higher among the educational work setting group of respondents than the private company respondents.
- Population growth as a potential development catalyst were ranked statistically higher among the educational work setting group of respondents than the private company respondents. Additionally, the educational work setting group of respondents ranked statistically higher than those working in government jobs when it came to viewing population growth as a potential catalyst.
- New energy infrastructure as a potential development catalyst were ranked statistically higher among the educational work setting group of respondents than the private company respondents.
Land Protection Catalysts
- Smart growth catalyst for land protection catalyst were ranked statistically higher among the educational work setting group of respondents ranked statistically higher than the private company respondents.
Land Protection Catalysts
- Land use scenario of recent trends were ranked statistically higher among the educational work setting group of respondents ranked statistically higher than the private company respondents.
- Land use scenario of using forest as infrastructure were ranked statistically higher among the educational work setting group of respondents ranked statistically higher than the private company respondents. Additionally, the educational work setting group of respondents ranked statistically higher than those working in government jobs when it came to using forest as infrastructure in land use scenarios.
Analysis- Age Influence
We were also interested in whether age influenced how individuals responded to survey questions. For 24 of the 27 dependent variables (SWOT statements; Development catalysts; Protection catalysts; and Future land use scenarios), there were no statistically significant differences in responses by age (18-35 y/o; 35-45 y/o; 45-55 y/o; 55+ y/o). However, responses differed in statistically significant ways on the following 3 variables:
Development Catalysts
- Transportation infrastructure as a potential development catalyst were ranked statistically higher among the 18-35 y/o than 55+ y/o group but were not statistically significant between the 35-45 y/o or 45-55 y/o group.
- New transportation technology as a potential development catalyst were ranked statistically higher among the 18-35 y/o than 55+ y/o group but were not statistically significant between the 35-45 y/o or 45-55 y/o group.
- Population growth as a potential development catalyst were ranked statistically higher among 18-35 y/o than 45-55 y/o group and the 18-35 y/o group ranked statistically higher than the 55+ y/o group.
Analysis- Geographic Influence
Additional analysis is forthcoming. We plan to analyze the dependent variables by dividing the DRB into three geographic regions (Appalachian, Piedmont, and Coastal Plain) and report those results. A preview of answers by geographic distribution is shown below:
1 = Statistical analysis made use of non-parametric Kruskal-Wallis H Tests using the Dunn (1964) procedure with Bonferroni corrections for multiple pairwise comparisons at p‹.05.
