220 Scharenbroch and Catania: Soil Quality Attributes as Indicators of Urban Tree Performance Table 3. Principal component scores based on 32 variableszyx Principal component PC1 Eigenvalue Proportion Cumulative proportion SOM (%) N (%) C (%) Fine POM (g kg-1 Total POM (g kg-1 K (mg kg-1 WAS (%) ) DON (mg kg-1 Mg (mg kg-1 ) Root restriction depth (cm) Structure type MBN (mg kg-1 Silt (%) ) Nmin. (mg NH4 eCEC (cmol(+) GSM (%) NH4 Sand (%) RES (mg CO2 Ca (mg kg-1 ) VF/F roots (# cm-2 qCO2 PR (kPa) MBC/TOC Chroma EC (dS m-1 Clay (%) VWC (%) C/N pH Value ρb (Mg m-3 ) ) kg-1 d-1 ) + (mg kg-1 ) kg-1 + and NO3 ) - kg-1 d-1 ) ) ) ) 8.23 25.71 25.71 PC2 5.10 15.93 41.64 Scores of five rotated eigenvectors 0.90y 0.89y 0.80y 0.74y 0.70y 0.55y 0.53y 0.46 0.42 0.37 0.36 0.35 0.29 0.24 0.22 0.12 0.11 0.09 0.08 -0.27 -0.34 0.22 -0.08 0.00 -0.27 -0.33 -0.22 0.37 -0.37 -0.04 0.15 -0.39 -0.15 0.82y 0.02 0.43 ) -0.01 -0.05 -0.05 -0.07 -0.17 -0.25 -0.31 -0.33 -0.37 -0.44 -0.45 -0.47 -0.55y -0.18 0.06 0.84y 0.16 -0.02 -0.06 0.00 -0.35 0.72y 0.49 0.36 0.63y 0.83y -0.10 0.12 . Data from 84 plots in western suburban Chicago, IL. PC3 3.26 10.19 51.83 0.25 0.22 0.15 -0.07 -0.12 0.42 0.01 -0.14 0.15 0.59y 0.49 0.12 -0.01 -0.25 0.28 -0.83y -0.44 -0.25 -0.06 0.23 -0.01 -0.12 -0.87y 0.01 -0.47 -0.13 0.10 -0.71y -0.10 -0.02 -0.36 -0.39 z Only principal components with eigenvalues >1 and that explain >5% of the total variance were retained. y Parameters with significant loadings on the within column principal component. resistance (PR), microbial biomass C / total organic C (MBC/TOC) in 10-2 x Wet-aggregate stability (WAS), dissolved organic N (DON), microbial biomass N (MBN), N mineralization (Nmin), microbial respiration (RES), bulk density (ρb trical conductivity (EC), calcium (Ca), magnesium (Mg), potassium (K), effective cation exchange capacity (eCEC), gravimetric soil moisture (GSM), ammonia (NH4 nitrogen (N), carbon (C), soil organic matter (SOM), particulate organic matter (POM), metabolic quotient (qCO2 ) in 10-3 , very fine and fine roots (VF/F). 0.0001) (Table 4). Conductivity measurements are relatively easy and have lower costs compared to measurements of ex- changeable bases. Consequently, EC is the preferred inclusion in the MDS to assess urban soil quality. Exchangeable Na, Ca, Mg, and K can also be included in the MDS, but these pa- rameters are secondary inclusions given their potential redun- dancy, greater costs, and need for laboratory instrumentation. Soil texture is often included in other MDS for assess- ing soil quality (Doran and Parkin 1994). Loam-textured soils are preferable for plants compared to soils with higher proportions of clay or sand (Larson and Pierce 1994). Clay contents are relatively high in these urban soils, so greater amounts of silt and sand indicate higher soil quality. Loca- tion effects were significant and variation was low for per- centages of sand, silt, and clay. Percentages of sand and silt were heavily weighted in PCA. For these reasons, soil tex- ture is included in the MDS for assessing urban soil quality. Soil compaction is a major problem in urban soils (Gregory and pen- etration resistance (Doran and Parkin 1994; Larson and Pierce et al. 2006). Soil quality decreases with increasing ρb ©2012 International Society of Arboriculture 1994). Soil ρb (mg CO2 kg-1 d-1 / mg MBC g-1 ), penetration and penetration resistance were highly loaded in sion in the MDS for assessing urban soil quality. Soil penetra- tion resistance was significantly correlated with ρb 0.0000789 * penetration resistance, R2 = 0.19, P = 0.0004) (Ta- involve field collection and minimal laboratory work (Larson and Pierce 1994) and do not have inherent spatial or tempo- ral bias. For these reasons, ρb the PCA, and the ANOVA showed strong site effects for these measurements. Comparisons of penetration resistance across sites and time-frames are susceptible to interferences associated with soil texture and moisture content. Soil ρb measurements is suggested as a primary inclu- (ρb = 1.05 + ble 4). Soil penetration resistance may be included, but given its inaccuracies, it is only recommended as a secondary inclusion. Wet-aggregate stability (WAS) increases with tilth and is sug- gested as a necessary parameter in a soil quality MDS (Arshad and Coen 1992). Aggregate stability was heavily weighted in the overall PCA, and strong location effects were detected for WAS in the ANOVA. Aggregate stability is a measure that inte- grates physical, chemical, and biological properties. Aggregate stability was correlated with 21 of 48 total parameters (5 of 17 ), elec- +), PC4 2.40 7.49 59.32 0.12 0.05 -0.09 0.40 0.40 0.10 -0.02 -0.09 0.34 -0.19 0.22 0.77y 0.66y 0.24 0.14 0.18 0.14 -0.54y 0.16 -0.19 -0.24 -0.24 -0.06 0.87y -0.06 0.04 -0.50y 0.09 -0.25 0.01 0.13 -0.16 PC5 2.53 6.04 65.36 -0.09 -0.07 0.18 0.21 0.15 0.07 -0.33 0.20 -0.20 -0.19 -0.02 0.00 0.32 0.44 -0.16 -0.28 -0.22 0.06 0.82y 0.00 -0.04 -0.79y -0.07 -0.09 0.15 0.01 -0.36 -0.21 0.26 0.06 0.20 -0.38
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