Human Socioeconomic Factors and Avian Diversity: A Cross-Site Comparison
P. S. Warren, C.H. Nilon, J. M. Grove, A. P. Kinzig, M. Cox, C. Martin
A variety of measures have been advanced as predictors of biodiversity in urban areas, such as human population density, building density, and canopy cover. These measures, either singly or in combination, describe only a portion of the habitat structure that is important for wildlife. For example, neighborhoods with the same housing density can be landscaped with different kinds of plants. In our studies of small, residential parks in Phoenix, Arizona, we found that the socioeconomic status (SES) of the neighborhoods around the parks was one of the best predictors of bird community structure within them. Human behaviors, values, and resource consumption levels, which may vary by SES, can influence factors such as the habitat and food availability for other organisms. An advantage of using SESís over direct measures of the ecological factors influencing biotic communities is that information on SES is widely available. We tested whether human SES showed a similar correlation with avian species richness in parks in two cities: Phoenix and Baltimore, Maryland. We used PRIZM market cluster data to classify the SES of the neighborhoods surrounding the parks. Since PRIZM uses the census block group as its geographical unit, we treated the set of block groups immediately surrounding each park as its neighborhood, selecting only parks found in relatively homogeneous neighborhoods with respect to PRIZM market clusters. We found that bird species richness is indeed correlated with SES in both cities, but SES explains much higher proportions of the variance in Phoenix. Birds in Baltimore appear to be less sensitive to differences associated with human SES and more sensitive to overall human density than birds in Phoenix. In addition, bird diversity in Baltimore parks also appears to be more strongly area-dependent than in Phoenix. We propose several possible reasons for these differences between the two cities.
birds, socioeconomic status, area effects, urbanization gradients