• Morgan Grove, Northeastern Research Station, USDA Forest Service

We propose that "ecological prestige" drives household land management. We will develop and test this hypothesis by comparing 1) demographics (population density), 2) social stratification and environmental equity (income, education, and race), and 3) social identity and status using the Potential Rating Index for Zipcode Markets. However, because PRIZM does not capture all of a neighborhood's important social and ecological characteristics, we must extend these marketing data to include air and water quality, safety, presence of lawns, trees, and gardens (e.g., Weiss 2000). Determining whether these factors are associated with different PRIZM classes is crucial for understanding how social groups differentially affect ecological structure.
 
We propose the following hypotheses. First, PRIZM classes modified by social ecology data (PRIZM-SE) will better predict vegetation structure (HERCULES) than demographics (population density), social stratification or environmental equity (income, education, and race). The distribution of vegetation structure is temporally complex, with legacies and time lags. Thus, historic social neighborhood characteristics (sensu PRIZM-SE), will better predict the present distribution of vegetation structure than contemporary PRIZM-SE classifications. The distribution of vegetation structure is also organizationally complex, and measures of social stratification, which reflect access to public and private investments at the municipal level, will be better predictors of variations in woody vegetation structure on public lands and rights-of-way than PRIZM-SE at the neighborhood level. Also, historic measures of social stratification will be better predictors of variations in vegetation structure than present measures of social stratification. These questions also address organizational and temporal complexity (Pickett et al. in press - a). Finally, PRIZM-SE will be a better predictor of neighborhood stability, social identity, and social order than demographics, social stratification or environmental equity.
 
We will use our long term demographic and socioeconomic data from the US Census to measure changes in population density, income, education, and race at the neighborhood level (1900-2000). We will use variables from these datasets to create historic "pseudo-PRIZM" classifications comparable to current PRIZM classifications obtained from the Claritas Corporation. We will continue our field observation survey, stratified by PRIZM class, median housing age, and municipality. BES will purchase annual, parcel-level, property GIS data for the Baltimore Metropolitan Region from the Maryland Department of Planning. Finally, we will use "bottom-up" patch delineations using Geographic-Weighted Regressions (GWR) and hedonic analyses to cross-validate PRIZM-SE at the Census Block Group level.

We examined predictors of vegetative cover on private lands in Baltimore, MD. We generated two measures, based on analysis of high resolution data. “Possible stewardship” refers to the proportion of private land parcels lacking built structures, and hence plantable. “Realized stewardship” refers to the proportion of possible stewardship land upon which vegetation is growing, either through planting or succession. These measures were generated at the parcel level and averaged by US Census block group. Realized stewardship was further broken down by woody vegetation and grass proportions. Data about expenditures on yard supplies and services by block group were used to help better understand where current vegetation conditions appear to be the result of current activity, past legacies, or abandonment. PRIZM™ market segmentation data were first tested as predictors of possible and realized stewardship and yard expenditures at the block group level. PRIZM™ segmentations, hierarchically clustered into 5, 15, and 62 classes, categorize neighborhoods by population density, social stratification (income and education), and lifestyle, respectively. We found that PRIZM 15 best predicted variation in possible stewardship and PRIZM 62 best predicted variation in realized stewardship. These results were further analyzed by regressing each dependent variable against a set of continuous variables reflective of each of the three PRIZM groupings. Housing age, vacancy, and crime were found to be critical determinants of both stewardship metrics, although differences in the predictors of vegetation cover versus the predictors of yard expenditures indicate different pathways by which vegetation was established in different parts of the city.
 

Figure 1: Possible and realized stewardship	Figure 2: PRIZM 15 map of Baltimore, MD
Figure 3: Box plot of possible stewardship against PRIZM 15	Figure 4: Box plot of realized total stewardship against PRIZM 15
Figure 7: A sample streetscape in a neighborhood classified with the “Bohemian Mix” PRIZM Group in Baltimore (photograph by Jennifer Jenkins)	Figure 8: A sample streetscape in a neighborhood classified with the “Money and Brains” PRIZM Group in Baltimore (photograph by Austin Troy)

Grove, J.M., W. R. Burch and S.T.A. Pickett. 2005. "Social Mosaics and Urban Forestry in Baltimore, Maryland." Pp. 248-273 in Communities and Forests: Where People Meet the Land, edited by R. G. Lee and D. R. Field. Corvalis: Oregon State University Press.
 
Grove, J.M., M. Cadenasso, W.R. Burch, Jr., S.T.A. Pickett, J. P. M. O'Neil-Dunne, K. Schwarz, M. Wilson, A. R. Troy and C. Boone. 2006. "Data and Methods Comparing Social Structure and Vegetation Structure of Urban Neighborhoods in Baltimore, Maryland." Society & Natural Resources 19:117-136.
 
Grove, J. M., A. R. Troy, J. P. M. O'Neil-Dunne, W. R. Burch, M.L. Cadenasso and S. T. A. Pickett. 2006. "Characterization of Households and Its Implications for the Vegetation of Urban Ecosystems." Ecosystems:578-597.
 
Troy, A. R., J. M. Grove, J. P. M. O'Neil-Dunne, M. Cadenasso and S. T. A. Pickett. Accepted. "Predicting Patterns of Vegetation and Opportunities for Greening on Private Urban Lands." Environmental Management.
 
Cadenasso, M.L., S. T. A. Pickett and J. M. Grove. 2006. "Dimensions of Ecosystem Complexity: heterogeneity, connectivity, and history." Ecological Complexity:1-12.
 
Cadenasso, M.L., S. T. A. Pickett and J. M. Grove. 2006. "Integrative Approaches to Investigating Human-Natural Systems: The Baltimore Ecosystem Study." Natures, Sciences, Societes:4-14.