A rapid urban site index for assessing the quality of street tree planting sites |
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| Institution: | 1. College of Natural Resources, University of Wisconsin-Stevens Point, 800 Reserve Street, Stevens Point, WI 54481, USA;2. The Morton Arboretum, 4100 Illinois Route 53, Lisle, IL 60532, USA;3. Department of Forest Resources, University of Minnesota, Green Hall, 2005 Upper Buford Circle, St. Paul, MN 55108, USA;4. Department of Geography, Environment, and Society, University of Minnesota, 414 Social Sciences 19th Avenue S., Minneapolis, MN 55455, USA;5. Department of Natural Resources and the Environment, University of Connecticut, 1376 Storrs Road, Storrs, CT 06269, USA;6. US Forest Service, Philadelphia Field Station, 100 N. 20th Street, Philadelphia, PA 19103, USA;7. Urban Horticulture Institute, Horticulture Section, School of Integrative Plant Science, Cornell University, 134A Plant Science, Ithaca, NY 14853, USA;8. Department of Environmental Conservation, University of Massachusetts, 160 Holdsworth Way, Amherst, MA 01003, USA;9. Ohio DNR Division of Forestry, Region 3, 11800 Buckeye Drive, Newbury, OH 44065, USA;10. Ohio DNR Division of Forestry, Region 4, 952-B Lima Avenue, Findlay, OH 45840, USA;11. Department of Earth & Environment, Boston University, 685 Commonwealth Avenue, Boston, MA 02215, USA;12. Department of Biology, Hofstra University, 227 Gittleson Hall, Hempstead, NY 11549, USA;1. State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China;2. Chang Jiang Water Resources Protection Institute, Wuhan 430051, Hubei, China;1. New Zealand School of Forestry, University of Canterbury, Private Bag 4800, Christchurch, New Zealand;2. Department of Environmental Horticulture, CLCE, IFAS, University of Florida – Gulf Coast Research and Education Center, Wimauma, FL, 33598, United States;1. Department of Planning and Landscape Architecture, University of Texas at Arlington, USA;2. Department of Earth and Environmental Science, University of Texas at Arlington, USA;3. USDA Forest Service, Pacific Southwest Research Station, Center for Urban Forest Research, USA;4. USDA Forest Service, Northern Research Station, Philadelphia Field Station, USA;1. University of Minnesota, Department of Forest Resources, 115 Green Hall, 1530 Cleveland Ave N, St. Paul, MN 55108, USA;2. Rubenstein School of Environment and Natural Resources, University of Vermont, 204E Aiken Center, Burlington, VT 05405, USA;3. University of Nebraska-Lincoln, School of Natural Resources, 3310 Holdrege Street, Lincoln, NE 68583, USA |
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| Abstract: | Urban trees experience site-induced stress and this leads to reduced growth and health. A site assessment tool would be useful for urban forest managers to better match species tolerances and site qualities, and to assess the efficacy of soil management actions. Toward this goal, a rapid urban site index (RUSI) model was created and tested for its ability to predict urban tree performance. The RUSI model is field-based assessment tool that scores 15 parameters in approximately five minutes. This research was conducted in eight cities throughout the Midwest and Northeast USA to test the efficacy of the RUSI model. The RUSI model accurately predicted urban tree health and growth metrics (P < 0.0001; R2 0.18–0.40). While the RUSI model did not accurately predict mean diameter growth, it was significantly correlated with recent diameter growth. Certain parameters in the RUSI model, such as estimated rooting area, soil structure and aggregate stability appeared to be more important than other parameters, such as growing degree days. Minimal improvements in the RUSI model were achieved by adding soil laboratory analyses. Field assessments in the RUSI model were significantly correlated with similar laboratory analyses. Other users may be able to use the RUSI model to assess urban tree planting sites (<5 min per site and no laboratory analyses fee), but training will be required to accurately utilize the model. Future work on the RUSI model will include developing training modules and testing across a wider geographic area with more urban tree species and urban sites. |
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| Keywords: | Right tree in the right site Urban forest planning Urban tree health Urban soil |
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