Urban forests are now recognized as essential components of sustainable cities, but there remains uncertainty
concerning how to stratify and classify urban landscapes into units of ecological significance at
spatial scales appropriate for management. Ecosystem classification is an approach that entails quantifying
the social and ecological processes that shape ecosystem conditions into logical and relatively
homogeneous management units, making the potential for ecosystem-based decision support available
to urban planners. The purpose of this study is to develop and propose a framework for urban forest
ecosystem classification (UFEC). The multifactor framework integrates 12 ecosystem components that
characterize the biophysical landscape, built environment, and human population. This framework is
then applied at the neighbourhood scale in Toronto, Canada, using hierarchical cluster analysis. The
analysis used 27 spatially-explicit variables to quantify the ecosystem components in Toronto. Twelve
ecosystem classes were identified in this UFEC application. Across the ecosystem classes, tree canopy
cover was positively related to economic wealth, especially income. However, education levels and
homeownership were occasionally inconsistent with the expected positive relationship with canopy
cover. Open green space and stocking had variable relationships with economic wealth and were more
closely related to population density, building intensity, and land use. The UFEC can provide ecosystembased
information for greening initiatives, tree planting, and the maintenance of the existing canopy.
Moreover, its use has the potential to inform the prioritization of limited municipal resources according
to ecological conditions and to concerns of social equity in the access to nature and distribution of
ecosystem service supply
Urban forests are now recognized as essential components of sustainable cities, but there remains uncertaintyconcerning how to stratify and classify urban landscapes into units of ecological significance atspatial scales appropriate for management. Ecosystem classification is an approach that entails quantifyingthe social and ecological processes that shape ecosystem conditions into logical and relativelyhomogeneous management units, making the potential for ecosystem-based decision support availableto urban planners. The purpose of this study is to develop and propose a framework for urban forestecosystem classification (UFEC). The multifactor framework integrates 12 ecosystem components thatcharacterize the biophysical landscape, built environment, and human population. This framework isthen applied at the neighbourhood scale in Toronto, Canada, using hierarchical cluster analysis. Theanalysis used 27 spatially-explicit variables to quantify the ecosystem components in Toronto. Twelveecosystem classes were identified in this UFEC application. Across the ecosystem classes, tree canopycover was positively related to economic wealth, especially income. However, education levels andhomeownership were occasionally inconsistent with the expected positive relationship with canopycover. Open green space and stocking had variable relationships with economic wealth and were moreclosely related to population density, building intensity, and land use. The UFEC can provide ecosystembasedinformation for greening initiatives, tree planting, and the maintenance of the existing canopy.Moreover, its use has the potential to inform the prioritization of limited municipal resources accordingto ecological conditions and to concerns of social equity in the access to nature and distribution ofecosystem service supply
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