326 Scharenbroch and Watson: Wood Chips and Compost Improve Soil Quality and Increase Growth WC compared to NULL. No significant differences were detected for medium and fine root biomass. Aſter five years in this compacted urban soil, total tree biomass was 170% greater with WC compared to control trees. Trees that received COMP and FERT grew 82% and 69%, respectively, more total biomass compared to control trees. These results provide strong evidence for the beneficial impacts of WC, COMP, and FERT for increasing tree growth in compacted urban soils. Many studies have identified positive improvements in tree growth with organic amendments and these findings have been summa- rized in two relatively recent literature reviews by Chalker-Scott (2007) and Scharenbroch (2009). The potential mechanisms for these observed increases in tree growth are presented and discussed in the preceding section of this paper. Trees that received ACT and CBP treatment did not differ in total bio- mass or any specific biomass fraction compared to control trees. These results provide evidence for the ineffectiveness of these treatments to stimulate tree growth in this compacted urban soil. Similar ineffectiveness of compost teas to stimulate tree growth in urban soils has been reported previously (Scharenbroch 2013; Scharenbroch et al. 2013). Researchers unexpectedly found that medium and fine root biomass did not respond in a similar fashion to coarse root biomass. Coarse roots grow by producing wood, like stem tissue; whereas, fine root growth is largely primary growth and more influenced by soil conditions (Shigo 1999). It is pos- sible that these treatments did not impact fine and medium root growth, but we feel this is unlikely given the significant responses in soil properties we observed. Soil responses would suggest that fine and medium root growth are equally or more responsive to these treatments than coarse roots. Relative to coarse roots, fine roots have a very low dry density. It is possible that these small dif- ferences in mass with fine and medium roots were not detected in statistical testing. In addition, roots outside of the tree-spaded hole were not included in this assessment. A subsampling of the soil out- side of the hole on 13 plots revealed that on average 0.054±0.041 kg of root biomass was not sampled, which is only 1%–2% of the total biomass mea- sured on the trees. It is recognized that the esti- mates of root biomass may be conservative due to sampling methodology; however, this underes- ©2014 International Society of Arboriculture timation is not likely to impact the main focus of the research, which was to examine the effects of these treatments on tree growth and soil quality. Another plausible explanation is that the sam- pling methodology masked treatment responses by damaging and removing fine and medium roots. To determine root biomass, trees were dug with a tree spade, and an air knife was used to remove the soil from the root balls. In removing the soil with the air knife, the fine and medium roots may have been removed. Attempts were made to mini- mize root damage during this process but fine and medium roots were visibly removed and it was not possible to quantify this effect. However, research- ers have no reason to suspect that the damage was unequal across treatments and/or species. Tree Growth Modeling Linear regressions among soil and tree responses showed significant and positive relationships with tree biomass and SOM, GSM, RES, N, P, and K (Table 4). A significant and negative relationship existed between bulk density and tree biomass. Soil pH was not significantly correlated with tree biomass. Although significant, correla- tions among soil and tree responses were gener- ally weak (r2 < 0.18). Of the soil responses, SOM was most strongly correlated with tree biomass. Stepwise regression modeling did not improve correlation with tree biomass. Forward, back- ward, and mixed modeling approaches all iden- tified SOM as the sole and most important predictor of tree biomass. A principal component analysis revealed that the first principal component explained 51.4% of the variation in soil responses. The first principal component was strongly cor- related with SOM (Eigenvector score of 0.4051). Soil organic matter was also significantly cor- related with all other soil properties (Table 5). All models suggest SOM to be the most impor- tant soil indicator of tree growth. Soil organic matter is a critical component of soil quality as it integrates physical, chemical, and biological properties (Doran and Parkin 1994). Soil organic matter is composed of living and dead flora and fauna. Soil organic matter is relatively lightweight, has a high surface area, and contains nutrients and microbes. Soil organic matter is known to improve biological condition of soil by increasing microbial
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