One-way analysis of variance (ANOVA) was used to test the effect
of canopy treatment on GLI. Split-plot ANOVA was used to test
the effects of canopy and cultural treatments on soil moisture, soil
temperature, and foliar nutrients in each year. Repeated measures
ANOVA was used to examine the changes in foliar nutrients over
time. Soil moisture data were log-transformed to improve normality
(Krebs, 1999). All analyses were performed using PROC MIXED
in SAS 9.1 (SAS Institute, 2004) with mixed-models and a random
block effect. In the case of a significant interaction between mainplot
and subplot effects, we used the SLICE statement to determine
significant effects of one treatment (i.e., canopy or cultural) within
each level of the other treatment. Tukey’s honestly significant difference
(HSD) test was used to determine differences in pairwise
comparison among the canopy and cultural treatments for each
variable. The level of statistical significance was set as a = 0.05.
One-way analysis of variance (ANOVA) was used to test the effectof canopy treatment on GLI. Split-plot ANOVA was used to testthe effects of canopy and cultural treatments on soil moisture, soiltemperature, and foliar nutrients in each year. Repeated measuresANOVA was used to examine the changes in foliar nutrients overtime. Soil moisture data were log-transformed to improve normality(Krebs, 1999). All analyses were performed using PROC MIXEDin SAS 9.1 (SAS Institute, 2004) with mixed-models and a randomblock effect. In the case of a significant interaction between mainplotand subplot effects, we used the SLICE statement to determinesignificant effects of one treatment (i.e., canopy or cultural) withineach level of the other treatment. Tukey’s honestly significant difference(HSD) test was used to determine differences in pairwisecomparison among the canopy and cultural treatments for eachvariable. The level of statistical significance was set as a = 0.05.
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