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While forest management commonly seeks to increase carbon (C) capture and sequestration, in some settings, a high density of C storage may be detrimental to other land uses and ecosystem services. We study a forested, drinking-water-supply watershed to determine the effects of forest management on C storage with the implicit understanding that greater storage of C will lead to increased quantity of carbon exported hydrologically into a source-water reservoir. Using a custom implementation of CBM-CFS3, a Canadian model to simulate C transformations and movement in forested systems, and a custom forest disturbance and management model, we simulate various management scenarios and their C outcomes. The largest forest C pool, mineral soils, is very slow to change and manipulating DOC export through this pool would likely not be feasible within human management timescales. Other pools, in which C has lower residence time and from which C is more readily mobilized, are a more promising area for future research into hydrologic DOC export under varying management regimes. Our findings indicate that management activities can serve to reduce forest C storage, but further research is required to connect these outcomes to hydrologic export., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

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., (Copyright © 2015 Elsevier Ltd. All rights reserved.)