Assessing the utility of topographic variables in predicting structural complexity of tree stands in a reforested urban landscape |
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| Affiliation: | 1. Environmental Systems Analysis Group, Wageningen University, PO Box 47, 6700 AA, Wageningen, The Netherlands;2. National Institute for Public Health and the Environment, PO Box 1, 3720 BA, Bilthoven, The Netherlands;3. De Vlinderstichting, Mennonietenweg 10, Postbus 506, 6700 AM, Wageningen, The Netherlands;1. Hunan Province Key Laboratory of Coal Resources Clean-utilization and Mine Environment Protection, Hunan University of Science and Technology, Xiangtan 411201, China;2. College of Environment and Planning, Henan University, Kaifeng 475004, China;3. Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China;4. School of Life Science, Hunan University of Science and Technology, Xiangtan 411201, China;1. University of Vermont, Rubenstein School of Environment and Natural Resources, 81 Carrigan Drive, Burlington, VT, USA;2. Forest Ecosystem Monitoring Cooperative, 705 Spear Street, South Burlington, VT, USA;3. University of Vermont, Gund Institute for Environment, 617 Main Street, Burlington, VT, USA;4. Oregon State University, College of Forestry, 3100 SW Jefferson Way, Corvallis, OR, USA;5. USDA Forest Service, Northern Research Station, 81 Carrigan Drive, Burlington, VT, USA;1. CSS, 200 SW 35th Street, Corvallis, OR, 97333, USA;2. Amnis Opes Institute, 2895 SE Glenn, Corvallis, OR, 97333, USA;3. Department of Fisheries & Wildlife, Oregon State University, Corvallis, OR, 97331, USA;4. Office of Research and Development, Center for Public Health and Environmental Assessment, Pacific Ecological Systems Division, 200 SW 35th Street, Corvallis, OR, 97333, USA |
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| Abstract: | The transformation of natural landscapes into impervious built-up surfaces through urbanization is known to significantly interfere with the ecological integrity of urban landscapes and accelerate climate change and associated impacts. Although urban reforestation is widely recognised as an ideal mitigation practice against these impacts, it often has to compete with other lucrative land uses within an urban area. The often limited urban space provided for reforestation therefore necessitates the optimization of the ecological benefits, which demands spatially explicit information. The recent proliferation of tree stands structural complexity (SSC) and topographic data offer great potential for determining the ecological performance of reforested areas across an urban landscape. This study explores the potential of using topographic datasets to predict SSC in a reforested urban landscape and ranks the value of these topographic variables in determining SSC. Tree structural data from a reforested urban area was collected and fed into a tree stand structural complexity index, which was used to indicate ecological performance. Topographic variables (Topographic Wetness Index, slope, Area Solar Radiation and elevation)- were derived from a Digital Elevation Model (DEM) and used to predict SSC using the Partial Least Squares (PLS) regression technique. Results show that SSC varied significantly between the topographic variables. Results also show that the topographic variables could be used to reliably predict SSC. As expected, the Topographic Wetness Index and slope were the most important topographic determinants of SSC while elevation was the least valuable. These results provide valuable spatially explicit information about the ecological performance of the reforested areas within an urban landscape. Specifically, the study demonstrates the value of topographic data as aids to urban reforestation planning. |
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| Keywords: | Area solar radiation Elevation Partial least squares regression Slope Topographic wetness index Urban ecological integrity |
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