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Abstract
It is increasingly important to understand how household characteristics influence lawn characteristics, as lawns play an important ecological role in human-dominated landscapes. This article investigates household and neighborhood socioeconomic characteristics as predictors of residential lawn-care expenditures and lawn greenness. The study area is the Gwynns Falls watershed, which includes portions of Baltimore City and Baltimore County, MD. We examined indicators of population, social stratification (income, education and race), lifestyle behavior, and housing age as predictors of lawn-care expenditures and lawn greenness. We also tested the potential of PRIZM market cluster data as predictors for these two dependent variables. Lawn greenness was found to be significantly associated with lawn-care expenditures, but with a relatively weak positive correlation. We also found lifestyle behavior indicators to be the best predictors for both dependent variables. PRIZM data, especially the lifestyle segmentation, also proved to be useful predictors for both.
This research was funded by the Northern Research Station, USDA Forest Service, and the National Science Foundation Long-term Ecological Research (LTER) program (grant DEB-042376). We also thank the anonymous reviewers for their helpful comments.
Notes
∗Significant at the 90% confidence level; ∗∗significant at the 95% confidence level; ∗∗∗significant at the 99% confidence level.
∗Significant at the 90% confidence level; ∗∗significant at the 95% confidence level; ∗∗∗significant at the 99% confidence level.
∗Significant at the 90% confidence level; ∗∗significant at the 95% confidence level; ∗∗∗significant at the 99% confidence level.