title: Neighbourhood-scale urban forest ecosystem classification.
abstract: 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 ecosystem-based 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.
authors: Environmental Applied Science and Management, Ryerson University, 350 Victoria Street, Toronto, Ontario, M5B 2K3, Canada; Urban Forest Research & Ecological Disturbance (UFRED) Group, Department of Geography and Environmental Studies, Ryerson University, 350 Victoria Street, Toronto, Ontario, M5B 2K3, Canada. Electronic address: james.steenberg@ryerson.ca.
authors: James W N
authors: JW
authors: Steenberg
authors: Urban Forest Research & Ecological Disturbance (UFRED) Group, Department of Geography and Environmental Studies, Ryerson University, 350 Victoria Street, Toronto, Ontario, M5B 2K3, Canada. Electronic address: millward@GEOGRAPHY.ryerson.ca.
authors: Andrew A
authors: AA
authors: Millward
authors: School for Resource and Environmental Studies, Dalhousie University, 6100 University Avenue, Halifax, Nova Scotia, B3H 4R2, Canada. Electronic address: peter.duinker@dal.ca.
authors: Peter N
authors: PN
authors: Duinker
authors: Northern Research Station, USDA Forest Service, 5 Moon Library, SUNY-ESF, Syracuse, NY, 13210, USA. Electronic address: dnowak@fs.fed.us.
authors: David J
authors: DJ
authors: Nowak
authors: School of Urban and Regional Planning, Ryerson University, 350 Victoria Street, Toronto, Ontario, M5B 2K3, Canada. Electronic address: pamela.robinson@ryerson.ca.
authors: Pamela J
authors: PJ
authors: Robinson
mesh_terms: D002170:Canada; D002947:Cities; D016000:Cluster Analysis; D003661:Decision Support Techniques; D004463:Ecology / Q000145:classification / Q000379:methods*; D017753:Ecosystem; D065928:Forests; D006801:Humans; D011156:Population Density; D012111:Residence Characteristics; D014197:Trees
keywords: Cluster analysis; Ecosystem classification; Management; Neighbourhood; Urban forest