Grantee Research Project Results
2001 Progress Report: Demographic Change in the New West: Exurban Development Around Nature Reserves
EPA Grant Number: R828786Title: Demographic Change in the New West: Exurban Development Around Nature Reserves
Investigators: Hansen, Andrew , Maxwell, Bruce , Rasker, Ray
Institution: Montana State University
EPA Project Officer: Hahn, Intaek
Project Period: May 1, 2001 through April 30, 2003 (Extended to April 30, 2004)
Project Period Covered by this Report: May 1, 2001 through April 30, 2002
Project Amount: $400,000
RFA: Futures Research in Socio-Economics (2001) RFA Text | Recipients Lists
Research Category: Environmental Justice
Objective:
The objective is to develop a means to model and evaluate future rural development in the Greater Yellowstone Ecosystem (GYE).Progress Summary:
The first objective of this project involves achieving a better understanding of which factors drive rural development. We have developed a suite of potential explanatory variables, including biophysical, socioeconomic, and demographic factors. Some of the variables that we are still in the process of collecting include: (1) climatic relationships such as annual temperatures and rates of precipitation; (2) access to utility lines; and (3) community measures of access to outdoor recreation. For each variable listed in the table, the data have been collected, formatted, and documented in a standardized manner. Each data layer must pass a quality assurance procedure consisting of checks for attribute inconsistencies, adequate spatial feature resolution, and reprojection (if necessary). The availability of relevant data varies in both extent and resolution. Therefore, to explore how the strength of drivers of rural development varies with scale, two analytical comparisons will be made. First, we will compare the explanatory power of statistical models built using community-level data versus models built using data that are available for the entire GYE. Examples of community level data that are either not available or too costly to acquire for the entire study area, include measures of viewsheds, outdoor recreation, and property values. Second, we will compare the explanatory power of statistical models built using data that are available at the Township Range Section level of resolution (one square mile) to models built using data that are available at county-level resolution. Examples of county-level data, that are not available at the resolution of one square mile, include economic information such as personal income by sector. For each of three time periods (1975-1985, 1985-1994, 1994-2000), we will quantify the amount of variation in growth in home density explained by the variables at community versus GYE extent, and Township Range Section versus county-level resolution. Poisson regression equations will be developed, and AIC and multivariate analysis will be conducted to analyze and select from the ?best models.? We also will use discriminant analysis to analyze the traits that best distinguish communities that fall within different growth categories. Twenty-five percent of private land will be excluded from the development of the regression equations, to be used later for model validation. We are currently nearing the end of data collection and processing. Summer 2002 will focus on completing data collection, ground-truthing the tax assessor home density dataset, and running statistical analyses.Future Activities:
During fall 2002, the statistical analyses will be completed, and the spatially explicit Rural Development Model will be developed to simulate future patterns of rural development within the GYE using the following inputs: (1) Development Potential - as determined by the "best model" for each community; (2) Allowable Development - as determined by zoning, setbacks, and easements; and (3) Population Projection - for each community, converted to an estimate of number of homes. The model inputs and outputs will be in ARC/INFO grid format, and the simulation algorithm will be implemented using the object-oriented Java language. For model validation, we will use contingency-table analyses to assess the degree of similarity between the simulated and observed home densities for the 25 percent of lands that were excluded previously from the analyses. All of data collection, data processing, statistical analyses, and model design and validation will be implemented on Sun[tm] systems running the Solaris 8 operating environment. Alternative future scenarios will be modelled by imposing restrictions in the Allowable Development input layer. The specific restrictions are to be determined in a workshop with land use planners and other interested parties. Our final analysis will focus on ecosystem vulnerability as indicated by the density of homes in proximity to the key habitats of native tree, shrub, and bird species that are most at risk of extinction. Vulnerability of these key habitats will be evaluated by quantifying home density in three zones of proximity to the habitats.Journal Articles:
No journal articles submitted with this report: View all 20 publications for this projectSupplemental Keywords:
Greater Yellowstone Ecosystem, rural development, land use change, GIS model., RFA, Scientific Discipline, Economic, Social, & Behavioral Science Research Program, Economics, decision-making, Ecology and Ecosystems, Ecological Risk Assessment, Urban and Regional Planning, Economics & Decision Making, demographic, assessing ecosystem vulnerability, exurban development simulator, biodiversity option values, economic research, futures, environmental policy, nature reserves, regression analysis, changing environmental conditions, land use, ecological predictorsRelevant Websites:
http://www.homepage.montana.edu/~hansen/hansen/lab/documents/researchinfo/demographic.htm Exit
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.