Arboriculture & Urban Forestry 38(5): September 2012 woodland-forest gradient corresponding to greater landscape- scale fire protection (Bowles et al. 1994; McBride and Bowles 2001). Bur oak (Quercus macrocarpa) and white oak (Q. alba) dominated savanna vegetation, while white oak, black oak (Q. velutina), and red oak (Q. rubra) dominated dry-mesic woodlands and forests. White oaks also had a tendency to dominate mesic forests, but sugar maple (Acer saccharum), white ash (Fraxinus americana), and basswood (Tilia americana) were also present. Forests in poorly drained habitats were dominated by swamp white oak (Q. bicolor), American elm (Ulmus americana), green ash (F. pennsylvanica), and soft maple (A. saccharinum). Data Sources Presettlement land survey data were collected by the Govern- ment Land Office Public Land Survey (PLS) in 1820–1837. This survey comprised a square-mile landscape grid where the identity, diameter, distance, and direction of one to four bear- ing trees were recorded at half-mile intervals. These data were accompanied by measures of vegetation intercepted along sec- tion lines, as well as township plats distinguishing timber, prai- rie, and other important landscape features. Despite evidence for biased or non-random selection of bearing trees (Manies et al. 2001), the PLS data and maps represent a large-scale veg- etation survey that can be used to reconstruct landscape-scale pre-European vegetation composition and pattern (Manies and Mladenoff 2000). A database and vegetation map shape files were prepared from the Chicago region PLS notes (http://plant conservation.us/plsmap.phtml) to calculate species basal area from bearing trees and to provide overlays of the following pre- settlement vegetation categories: barrens, lake, marsh, prairie, river, scattering timber, slough, swamp, timber, and wet prairie. Urban tree census data were collected by The Morton Arbo- retum in conjunction with the USDA Forest Service in the sum- mer of 2010. A set of 1400 plots were located within the seven county region (excluding the City of Chicago), plot locations were random, but stratified by county (number of plots was equal in each county regardless of area). Plots were 0.04 ha in area (11.3 m radius) and were established regardless of land use or condition. Data collection followed i-Tree Eco protocols (Nowak et al. 2008) and field crews recorded tree species, height, crown spread, crown base height, DBH, crown health/dieback, percent tree cover, shrub cover, and groundcover classes. Crews also classified each plot into one of the following land use catego- ries: agriculture, cemetery, commercial, golf course, industrial, institutional, multi-family residential, other, park (included natu- ral areas), residential, transportation, utility, vacant, and water/ wetland. Of the 1400 plots, 565 had trees present (~40%) and were of use in analysis of urban forest composition and structure. Data Analysis Question #1: What are the primary gradients in species composition and structure in the urban forest? To illustrate dominant gradients in tree species composition in the modern urban forest, non-metric multidimensional scaling (NMS) ordination was performed on a matrix containing tree census plots and basal area by species. Gradients in canopy struc- ture were evaluated using a principal components analysis (PCA) ordination. Details on ordination methods can be found in Mc- 183 Cune and Grace (2002). Variables describing canopy structure included total crown volume, average crown depth, total canopy depth, average crown area, maximum canopy height, average canopy height, variance in crown depth, percent tree cover, per- cent shrub cover, average height to live crown, minimum height to live crown, average crown width, maximum crown width, and crown light exposure. Potential drivers of species composition and structure (median income, housing density, distance to river, distance to road, presettlement density) were overlaid as biplots on both ordinations to assess their correlation with the solution. NMS ordination was conducted in PC-ORD v.5 (McCune and Mefford 2006) using the “slow and thorough” autopilot setting, which uses 250 runs of real data and 250 Monte Carlo random- izations of the data to assess the robustness of the solution. PCA was also conducted using PC-ORD with a correlation-based cross-products matrix and a randomization test to evaluate sig- nificance of principal components (McCune and Mefford 2006). To illustrate size structure, diameter distributions were created for all major species in tree census data. Regression analysis was used to test the relationship between log-transformed basal area and measures of canopy depth, maximum canopy height, and percent canopy cover. These tests were performed with data pooled across all land use categories, and within each category. Because basal area and canopy cover have a tendency to be strongly correlated, especially in open grown stands (Law et al. 1994; Buckley et al. 1999), it was expected that basal area would be an important driver of canopy characteristics in urban stands. Question #2: Do species composition and structure vary with modern land use, presettlement vegetation condition, and underlying geomorphology? Differences in species composition and structure among mod- ern land use categories, presettlement vegetation categories, and physiographic region were tested using a Multi-response Permutation Procedure (MRPP) using Sorensen’s distance in PC-ORD v.5 (McCune and Mefford 2006). To evaluate differences in size structure among land use categories, di- ameter distributions were created for each category (oak, native non-oak, non-native) and compared using χ2 tests. Question #3: How do original vegetation pattern and modern land use interact to affect composition and structure across the urban forest? A factorial analysis in a General Linear Model (GLM) was used to test null hypotheses that composition and structure of the urban forest did not differ among land use categories and presettlement vegetation types, and that these two groups had independent ef- fects. For this analysis, land use categories assigned by the Tree Census were pooled into agriculture (N = 33), developed land (N = 71; including commercial, industrial, institutional, trans- portation, utility), residential (N = 302; including multi-family residential), and parks (N = 71; included natural areas). The “va- cant” and “other” categories were not used because of their vague descriptions, while cemeteries, golf courses, and wetlands were not used because of their small sample sizes. The presettlement vegetation categories that were tested were prairie (N = 294) and timber (N = 183), all other categories were too rare to be used. GLM analysis was applied to basal area and dominance of three species groups (oaks, native non-oaks, and non-native species), ©2012 International Society of Arboriculture
September 2012
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