RECENT TIMBERING ACTIVITY AS A VARIABLE IN PREDICTIVE MODELING
Creators: name: Plent, Samuel Gerard
Publisher: name: Digital Repository at the University of Maryland
Year: 2023
Subjects: subject: Cultural resources management
subject: Archaeology
subject: Geographic information science and geodesy

description: This thesis explores how the presence of recent timbering activities affects the predictive power of predictive models in regard to precontact archaeological sites. Predictive models have been used to assess the likelihood of identifying cultural resources in a given area for decades. A county-wide predictive model has not been created for any county in the state of Georgia. This research applies what is known about predictive modeling to Henry County, Georgia and assesses its accuracy. It then seeks to test predictive power of another environmental variable in order to further refine the process of predicting the location of precontact archaeological sites. The thesis focuses its efforts in Henry County, Georgia, which has multiple instances of pine silviculture areas that have been surveyed for cultural resources after being harvested. Timber has been an important natural resource in Georgia since the nineteenth century. The management of forests for the timber industry began in 1875 with the establishment of the American Forestry Association. The timbering and replanting of these areas can occur as often as every 15 to 30 years. This process can disturb soils and buried resources. Elevation, soil, and hydrology data was collected from multiple public sources including the United State Geological Survey (USGS) and the United States Department of Agriculture Natural Resources Conservation Service (USDA, NRCS). Archaeological site and previous survey data was taken from the Georgia Natural Archaeological and Historic Resources Geographic Information Systems (GNAHRGIS). The environmental data was combined to create a set of predictive models for predicting the likelihood of an area to contain a precontact archaeological site using Geographic Information Systems (GIS). Each predictive model was tested for accuracy using previously collected archaeological data. The predictive model found to be most accurate was analyzed within multiple areas containing recent timbering activities that have been previously surveyed for cultural resources. It appears that the presence of recent timbering activities does not negatively affect the predictive power of a predictive model regarding precontact archaeological sites. This is demonstrated by showing that a predicative model for the entirety of Henry County, Georgia does not lose accuracy when applied to multiple areas that have been timbered prior to survey for cultural material. Predictive models can be powerful tools in the Cultural Resource Manager’s toolkit. However, many may be reticent to apply these tools to areas that have seen large-scale industrial ground disturbing activities. This thesis has demonstrated that predictive models can still be useful tools in areas recently affected by large-scale timbering activities. While systematic survey is still necessary, this can be helpful in matters of scoping, budgeting, and planning