Grantee Research Project Results
2005 Progress Report: A Dynamic Spatial Socioeconomic and Ecological Landscape Model to Assess Environmental Impacts of Forest Change on the Southern Cumberland Plateau of Tennessee
EPA Grant Number: R829802Title: A Dynamic Spatial Socioeconomic and Ecological Landscape Model to Assess Environmental Impacts of Forest Change on the Southern Cumberland Plateau of Tennessee
Investigators: Gottfried, Robert , Haskell, David , Williams, Douglass , Evans, Jonathan
Institution: University of the South
EPA Project Officer: Hahn, Intaek
Project Period: September 1, 2002 through August 31, 2005 (Extended to August 31, 2006)
Project Period Covered by this Report: September 1, 2004 through August 31, 2005
Project Amount: $248,265
RFA: Futures: Research in Socio-Economics (2001) RFA Text
Research Category: Environmental Justice
Objective:
The objectives of this research project are to: (1) develop a spatial socioeconomic model of change in land use/land cover (LULC) for the Southern Cumberland Plateau for the period of 1980-2000; (2) integrate this model with the Small Area Assessment Forestry Demonstration Project’s bird, amphibian, and water-quality landscape models to understand the socioeconomic processes bringing about environmental change in the region; (3) use this understanding and the model to assess potential future environmental impacts of likely socioeconomic events or trends; and (4) investigate the impacts of possible policy responses.
Progress Summary:
During Year 3 of the project, we have made progress in data development, understanding of LULC changes in our study area, development of the basic approach to modeling that we will use, and continued econometric analysis.
Much of the work over the year involved generating new spatial information from what we already had. As part of this effort, we have developed LULC data files on a subparcel level so that we can examine LULC change over time within parcels. The study’s large area of interest and number of nonsimple features caused considerable computing time and brought out many shortcomings of the hardware as well as the software. The Python scripting language initially was chosen to create these tools because of its ability to interact with the ArcGIS environment. Unfortunately, this combination has some serious flaws that can cause it to be quite burdensome, and that development environment has since been abandoned. Currently, all previously created as well as new tools and procedures are being developed within the Visual Basic for Applications (VBA) environment. Although still having its limitations, this environment drastically is increasing processing speeds.
Further analysis of our LULC data has shown that the rate of conversion of native forest to grass/shrub (agriculture or residential land use) has far outstripped conversion to pine. The decline in the annual rate of pine conversion, as well as rising rates of conversion of pine to agricultural/residential, may have resulted from the disastrous southern pine beetle epidemic that started around 2000. Informal conversations with buyers of land divested by timber companies, developers, and county extension agents indicate that much of this conversion has been the result of agricultural expansion (hay/pasture).
Often landowners convert part of their parcel to another land cover while maintaining the remainder as before. Accordingly, we have developed LULC data files on a subparcel level so that we can examine LULC change over time within parcels. Any subparcel changes from 1981-2003 have been captured and made into distinct polygons that, de facto, reveal management units in a parcel.
During Year 3, the groundwork for the implementation of the model within the ArcGIS environment was built. The work to implement the model as an extension of ArcMap began in June of 2005. This model includes the spatial processing tools being developed in VBA as well as the econometric analysis.
Because of data difficulties, we decided to drop the process model and focus on the transitional probability model. During Year 3, we have developed various spatial variables for the regression analyses, particularly ones dealing with LULC in the area around a parcel. We largely have completed the logit analysis for home construction on parcels never before experiencing home construction and those already built on.
The logit analysis of homebuilding indicates that parcels over 90 acres in size behave differently from those 10 to 90 acres in size, and that the period after 1997 experienced a somewhat different dynamic from the earlier period. In general, the model produced the expected types of results. Parcels with greater proportions of grass/shrub coverage more likely experienced homebuilding relative to those with native forest, whereas parcels with greater proportions of pine experienced relatively less homebuilding compared to those with native forest. Neighborhood variables measuring the extent of homes nearby, value of housing, and distance to the nearest residential parcel all exerted significant effects on the probability of a home being built. Homebuilding probability also depended upon parcel ownership—parcels held by timber companies in the year 2000 were least likely to be built upon, followed by those owned by business owners prior to 1997, and then business owners after 1997. Homebuilders generally preferred isolation and unpaved roads.
Future Activities:
When the dataset is complete, we will begin multinomial probit analysis of the LULC conversion of subparcel polygons, with the building of a home as one of the independent variables. We anticipate analyzing conversions from native forest to pine plantation and to grass/shrub as the two conversions of interest. Including homebuilding as an independent variable will help us explore the degree to which homebuilding is leading to the conversion of native forest to grass/shrub cover.
Journal Articles:
No journal articles submitted with this report: View all 10 publications for this projectSupplemental Keywords:
forest conservation decisions, forest ecosystem, forest resources, landscape ecology, model-based analysis, remote sensing, social impact analysis,, RFA, Economic, Social, & Behavioral Science Research Program, Scientific Discipline, Geographic Area, Ecosystem Protection/Environmental Exposure & Risk, State, Forestry, Monitoring/Modeling, Environmental Monitoring, decision-making, Ecology and Ecosystems, Social Science, Economics & Decision Making, model-based analysis, monitoring, remote sensing, spatial landscape model, economic research, social impact analysis, remote sensing data, forest ecosystem, decision making, environmental decision making, forest conservation decisions, modeling, environmental impact, environmental impact comparison, forest reources, socioeconomics, landscape ecology, Tennesee (TN), forests, GIS, water quality, ecological models, decision support tool, land managementRelevant Websites:
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.