Linear equations [f(x)], coefficients of determination (r 2 ), degrees of freedom (df), and p-value estimates were determined using Statistica 9.1 (StatSoft Inc., Tulsa, OK, USA).
Parameter estimates were determined by performing regression analysis with no intercept option.
Group estimates were determined by aggregating the individual estimates using the geometric mean of the individual estimates for each frequency parameter.
Tree cover estimates were determined for the LD, HD, and PJD plots by measuring the BCA of every tree in each plot.
Estimates were determined for the pharmacokinetic parameters: alpha half-life (t 1/2α), beta half-life (t 1/2β), area under the curve extrapolated to infinity (AUC0-∞) and mean residence time (MRT).
In addition, a number of other estimates were determined over a range of the variables of Young's Modulus, Poisson's Ratio, injection water temperature, and the difference in pressure between the reservoir pressure and flowing bottom hole pressure that were ran (Fig. 6).
The percent biases resulting from regression equation based and from BEF-based estimates were determined by Eq. (12) using an independent sample of 37 trees (trees not included in fitting the models): Biasleft(%right)=frac{{displaystyle sum P{B}_k-{displaystyle sum O{B}_k}}}{{displaystyle sum P{B}_k}}times 100 (100.
Accuracy of probability estimates were determined by calculating ninety five percent confidence intervals (95% CI).
The final parameter estimates were determined as the average across all five regression models.
Posterior probabilities of divergence time estimates were determined following a 100,000 cycle burn-in.
The diversity estimates were determined based on best-fit mathematical modeling, in this case to a logarithmic model.
