Many studies of urban ecosystem function have been based on mean values of structure for an entire urban ecosystem and models that use region-centric algorithms and assumptions. Often, these urban forest function modeling approaches do not include concepts of heterogeneity and scale in their analyses.  However, the urban ecosystem is not uniformly distributed across a city because of biophysical and social factors. Because of these differences in structural heterogeneity, urban ecosystem function should vary. Also region-specific parameters and assumptions used in these models might not be appropriate for use in biophysically disparate systems. The objectives of this study were to explore the role of structural heterogeneity, scale, and site specific allometrics in quantifying urban forest function.  We used the USDA Forest Service’s Urban Forest Effects model and its transpiration-deposition component to evaluate how the spatial heterogeneity of an urban ecosystem influences air pollution removal at the socioeconomic subregion scale in Santiago, Chile.  We also compared the urban forest structure components of the model with results we obtained using site specific urban tree allometric equations. 

Results/Conclusions

Study results show that air pollution removal rates among three socioeconomic subregions were different because of heterogeneous urban forest structure and pollution concentrations. Seasonal air quality improvement also differed among the subregions.   Leaf area and biomass estimates using equations developed with Santiago-specific data were significantly different than those estimated by the model for common urban tree species found in Santiago. Modeled urban tree carbon storage - sequestration estimates can also vary significantly if compared to estimates using different above ground whole-tree biomass equations. Results indicate that the use of different tree allometric algorithms and assumptions in the model could affect some urban forest function estimates significantly. Studies on the functionality of the urban ecosystem should consider spatial heterogeneity and scale when conducting region-wide analyses. Similarly, policies that are based on urban ecosystem structure and function should consider verification of algorithms when using models to advocate for urban tree plantings to improve environmental quality. Results from this study can be used to design management alternatives at finer administrative scales or key sites that maximize the environmental quality improvement by the urban forest in a subregion.