Positioning Rust Belt cities for a sustainable future: Step 1, an evaluation of neighborhood socio-ecological metabolism

Background/Question/Methods: Long Term Socio-Ecological Research encompasses both the cultural and economic realms that comprise the human dimension of ecosystem studies. Socio-ecological metabolism analysis is a means of showing the connectivity, relative importance, and to some degree similarity of all city processes, whether strictly biophysical or social, in order to facilitate planning for a more secure urban future.   We hypothesize that the socio-ecological metabolism (SEM) of a North-Eastern rust belt city may be vulnerable to future external factors such as restrictions in oil availability, or both climate-induced heating and northward migration, and that city revitalization emphasizing natural ecosystem processes via green infrastructure can impact SEM positively at both the city/regional and the household/neighborhood level in the future.  At the neighborhood scale we calculate average ecological production based on LiCor 6400 in situ measurements and leaf area index (LAI) for different tree species. Ecological respiration is derived from home energy use statistics from local utilities, average household food consumption by income group, and Syracuse urban transportation statistics derived from the local Transportation Council. We combine 2000 census block data (US Census 2000) on income, age, and ethnicity, and tax parcel data on owner occupied homes, renter occupied homes and vacant homes to derive an estimate of sociological production. Results/Conclusions: We survey urban residents to determine their willingness to install green infrastructure (trees, rain gardens, rain barrels, etc) on their properties.  Through map overlay we illustrate by census block neighborhood SEM along gradients of green plant production and both biotic and fossil energy consumption (respiration) (both in MJ ha-1). Mapped projections based on citizen attitudes and biophysical capacity for GI implementation allow us to assess urban opportunities for potential SEM enhancement.  Our models will allow citizens and decision makers to see how SEM at this scale can change as a function of alternate LULC management options and changing energy inputs.