62 Staudhammer et al.: Change and Hurricane Impacts to Houston’s Urban Forest Structure and Zhao et al. (2010). Percent tree cover, percent crown dam- age, percent missing foliage, and the amount of damage caused by other trees or wind were estimated ocularly using methods outlined in the i-Tree Storm manual (i-Tree 2009). Recently re- moved trees, as indicated by fresh stumps and saw dust on-site, were assumed to have been downed and/or removed as a result of Hurricane Ike. Measurements of debris amounts, notes on exist- ing land use and visual observation of hurricane damage by trees, or wind to nearby buildings were also collected and are being used for a parallel study. For this analysis, original land covers were condensed into the following four: Woody Wetlands (WW); Developed Open Space (DO); Developed Low Intensity (DL); and Developed High Intensity (DH). Developed Low and High Intensity represent more urbanized land covers in the study area. Matching 2001–2002 and 2008 Plots and Individual Trees Sample data from 2001–2002 and the 2008 post-Hurricane Ike measurements were merged and trees present in both samples were matched. Trees were considered matched if 2001–2002 and 2008 tree measurements had the same direction and distance to plot center, same species and had a net increase in DBH. Annual DBH growth increments (cm/yr) were calculated by subtracting the 2001–2002 measurement from the 2008 and dividing by the years since measurement. Re-measurements using tree diameter tapes at breast height can differ from actual tree growth due to measurement error and changes in tree physiology (Avery and Burkhart 1983; Pastur et al. 2007). In addition, changes in the height of mulch and litter below a tree can change the location of the breast height measurement resulting in subsequent measure- ments taken at different heights. Although tree core increments are used to more precisely measure tree growth, in urban tree studies, tree coring is not practical due to tree aesthetics or liabili- ty issues associated with coring trees on private properties. While this study’s method may lead to more measurement error than coring, the study auhors believe this issue to be negligible over the time period of this study; furthermore, this approach has been used in other urban forest structure studies (Nowak et al. 2004). Since the DBH threshold in the 2001–2002 measurements was 12.7 cm, in-growth of a newly established tree into the population or trees was indicated by the presence of a tree with DBH > 12.7 cm in the 2008 measurement that was not origi- nally measured in 2001–2002. Thus, in-growth as defined in this study indicates either a newly planted tree on the plot or that a small tree on the plot grew to the DBH threshold of 12.7 cm. If a previously measured tree was either removed, dead, or downed due to reasons other than Hurricane Ike, it was considered absent from the plot re-measurement. For this study, absence and in- growth were considered the same as mortality and recruitment, respectively; it was assumed that no trees were moved (e.g., re- planted from outside the plot to inside the plot), or vice-versa. Statistical Analyses Statistical analyses of growth, mortality, and in-growth were con- ducted using the following plot level factors from the 2001–2002 measurements: land cover type, trees per acre, basal area per acre, and percent impervious groundcover. Tree level factors used in the analysis were: species, percent foliage, percent dieback, DBH, and crown light exposure from the 2001–2002 measurements. ©2011 International Society of Arboriculture Mortality and in-growth models were developed for this analysis using the plot-level mortality and in-growth data, respectively, as the dependent variables. A generalized lin- ear model was fit using the SAS procedure PROC GLIMMIX (SAS 2006) assuming a negative binomial distribution for the response and plot-level characteristics as predictor variables. Due to the frequency of near zero growth data values, growth rate values were transformed using a square root function to the reduce the variance and enable the modeling assumption of nor- mally distributed and homoscedastic residuals to be met. Growth rates were modeled using a general linear mixed model with the SAS procedure PROC MIXED (SAS 2006) with both plot and tree level characteristics as predictor variables. A random ef- fect was included to account for correlations between trees on the same plot. A Kenward-Rogers adjustment was made to the degrees of freedom to better reflect the effect of autocorrela- tion on the denominator degrees of freedom (Littel et al. 2006). The model results were examined using information cri- teria and P-values associated with each independent value. A type I error level of 0.05 and the Akaike’s information criteria (AIC) with second order correction (AICC) were used to elimi- nate nonsignificant effects and their interactions. The AICC is a small sample bias-corrected version of the AIC fit statis- tic which measures the goodness of fit of an estimated statisti- cal model. It is a relative measure that quantifies the tradeoff between bias and variance in a model. A model with lower AIC gives more evidence that the model arose from the data. While the absolute values of AIC are not meaningful in and of themselves, a difference of two units of AIC between com- peting models is usually taken to indicate a meaningful differ- ence between them (Burnham and Anderson 2002). The final models for growth, in-growth, and mortality included only sig- nificant effects and also had the lowest AICC values, indicat- ing substantial evidence that the data arose from this model. RESULTS Change in Urban Forest Structure When comparing trees within the 37 matched plots, there was an overall loss of an estimated nine trees and 0.24 square me- ters per ha of basal area per year. These re-measured plots con- tained 305 trees, of which 195 (63.9%) were matched and 110 (36.1%) were removed. Ninety seven (31.8%) of these trees were removed due to urbanization effects and 13 trees (4.3%) were removed due to hurricane effects. Plots in 2008 contained a total of 245 trees where 195 trees remained from the previ- ous measurement and 50 were new trees. Overall, the net change in number of live trees was an annual loss of 2.9%. Figure 2 indicates that the average percent change for all tree density measurements (e.g., basal area, trees per acre, and tree cover) decreased over time when comparing plots that were matched through re-measurement. A comparison between 2008 plots with original 2001 plots in terms of overall density is not pos- sible, because the post-hurricane plot selection criteria in 2008 targeted plots that contained trees only. Figure 3 shows annual plot density (e.g., number of trees/hectare) by land cover type. Plots on DL land cover showed an average annual increase in tree density while plots on WW land cover decreased over time.
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