Session: Social-Ecological Drivers of Change in Urban Forest Patches
Macro-scale analysis of forest patch canopy composition highlights syndromes of response to urbanization
Monday, August 2, 2021
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Lea R. Johnson, Division of Research and Conservation, Longwood Gardens, Kennett Square, PA, Lea R. Johnson, Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD, John Paul Schmit, National Capital Region Inventory and Monitoring Network, Office of Natural Resources and Science, US National Park Service, Washington, DC, Lindsay E. Darling, Chicago Region Trees Initiative, The Morton Aboretum, Lisle, IL, Dexter H. Locke, National Socio-Environmental Synthesis Center (SESYNC), Baltimore, MD, Dexter H. Locke and Nancy F. Sonti, Northern Research Station, Baltimore Urban Field Station, USDA Forest Service, Baltimore, MD, Matthew E. Baker, Geography & Environmental Systems, University of Maryland Baltimore County, Baltimore, MD, Robert Fahey, Natural Resources and the Environment, University of Connecticut, Storrs, CT, Myla F.J. Aronson, Department of Ecology, Evolution and Natural Resources, Rutgers University, New Brunswick, NJ, Michelle L. Johnson, Northern Research Station, NYC Urban Field Station, USDA Forest Service, Bayside, NY
Lea R. Johnson
Department of Plant Science and Landscape Architecture, University of Maryland Kennett Square, College Park, PA, MD, USA
Background/Question/Methods Urban forest patches can contribute to sustainable ecological function within cities and residents’ well-being, but little is known about social-ecological processes and feedbacks affecting their ecological condition. To understand relationships between complex multi-scale urban social-ecological systems and forest patch condition, we synthesized data from 19 national, regional, and local datasets sampling forest plant communities (> 4800 plots) across four metropolitan regions: Chicago, Baltimore/Washington, New York City, and Philadelphia. Our samples extended from US Census-defined Metropolitan Statistical Areas to include more rural forests, thus enabling analysis of multiple gradients of urbanization intensity. Here, we examine relationships between forest tree composition (basal area per hectare by species) and percent impervious cover within 1 km. Results/Conclusions Analysis of the overall dataset identified three groups of tree species that increase or decrease in abundance in response to impervious cover as a proxy indicator of urbanization: 1) tree species that decrease in abundance at low levels of urbanization, 2) species that increase at low levels of urbanization, and 3) species that increase at higher levels of urbanization. Species decreasing with urbanization were entirely native and included both rare and common canopy trees of the sampled regions. Installation of impervious surface and other changes associated with urbanization likely represent a novel environmental gradient that increasingly departs from conditions many species encountered in their recent evolutionary history. Some native species increased at low levels of urbanization and then decreased with higher levels; these species included shade intolerant to moderately tolerant early successional or gap phase trees that may experience competitive release with changes in land cover and disturbance regimes that shift resource availability. Species that increased at higher levels of urbanization were primarily, but not entirely, non-native and included weedy ruderals, fruit/nut trees, and many commonly planted street trees. Variation in the level of urbanization at which species increased may be associated with regional natural history and specific patterns of exotic introductions. This analysis is the first in a series that will test the importance of social and ecological drivers of forest condition along multiple gradients of urbanization intensity. This work advances understanding of urban forest patches as complex multi-scale social-ecological systems to support decision-making and improve outcomes of management actions.