A STEM PROFILE MODEL CALIBRATED BY NONLINEAR MIXED-EFFECTS MODELING

A stem profile model was developed for black spruce (Picea mariana (Mill.) B.S.P.) trees in Alberta, Canada using a nonlinear mixed model approach. The model included two random parameters to capture between-subject variation and a general covariance structure to model within-subject residual autocorrelation. After evaluating various covariance structures, the 4-banded toeplitz and the spatial power structures were chosen for further evaluation. The 4-banded toeplitz structure provided a better fit. The model was further evaluated using an independent data set to examine its validation accuracy. Model validation results showed that the model was able to accurately predict stem diameters at the population and subject-specific levels. Both covariance structures produced reliable model predictions, but the spatial power structure was superior to the 4-banded toeplitz structure. One to four stem diameters were used to predict random parameters and to subsequently generate subject-specific predictions. At least three stem diameters were needed to achieve better subject-specific predictions than population-average predictions

Height-diameter models for maritime pine in Portugal: a comparison of basic, generalized and mixed-effects models

Tree height is a key variable in forest monitoring studies and for forest management. However, tree height measurement is time consuming, and the recommended procedure is to use estimates from height-diameter models. Here, we compare height-diameter model forms and approaches for predicting tree height (h) as a function of tree diameter at breast height (d) and additional stand level covariates. Four model forms were evaluated: (i) basic models (which only used d as predictor variable); (ii) generalized models (which used d and stand-level predictor variables); (iii) a mixed-effects model based on the best basic model; and (iv) a mixed-effects model based on the best generalized model. Several alternatives aimed at minimizing height measurement effort were tested in terms of accuracy and applicability. From a practical point of view, the selected generalized model is recommended for estimating the height of maritime pine in Portugal. The results also show that a calibrated basic mixed model provides more accurate results than a basic model locally fitted when the number of h-d observations is limited.S

Continuous forest inventory using multistage unequal probability sampling with partial replacement

Continuous forest inventory (CFI) with partial replacement of sampling units (SPR) has been established as an efficient inventory technique. Previous CFI with SPR theory was based on equal probability sampling which might not be as efficient as the unequal probability sampling that is now widely used in forest inventories. In this study, the general theory of multistage sampling combined with CFI using unequal probabilities in a SPR structure on two occasions is discussed. Estimators of the current means and the change in means for both one-stage and two-stage cases are given, along with the estimators for the overall variances. The estimators derived for estimating the current means take the same form as those developed by other researchers. However, the estimators proposed for predicting the change in means take simpler forms than those presented in the literature. This might result in greater simplicity when used in data processing. The application of CFI with SPR using multistage unequal probability sampling to a Chinese national forest inventory is presented for illustrative purposes. Some particular points are addressed regarding specific situations in China. Although no precise theoretical demonstration of the gains from using this method is given, the combination of highly efficient sampling with unequal probabilities and the very practical multistage sampling in CFI with SPR inventories can certainly provide an efficient alternative to traditional Chinese inventory systems.Forestry, Faculty ofGraduat

Climate-sensitive height–age models for top height trees in natural and reclaimed oil sands stands in Alberta, Canada

Climate sensitive height-age models were developed for top height trees of trembling aspen (Populus tremuloides Michx.), jack pine (Pinus banksiana) and white spruce (Picea glauca (Moench) Voss) in natural and reclaimed oil sands stands. Both stem analysis data collected from the Athabasca oil sands region in northern Alberta and climate data generated by the ClimateWNA model were used. Height-age trajectories differed between top height trees in natural and reclaimed stands for jack pine and white spruce, but not for aspen. At a given age, white spruce top height trees were taller and jack pine top height trees were shorter in reclaimed stands compared to those in natural stands, suggesting that it is easier to achieve similar forest productivity for oil sands sites reclaimed with white spruce stands, but more difficult for sites reclaimed with jack pine stands. The principal climate variables were growing season (May to September) precipitation averaged over the previous ten years for aspen and jack pine and summer (June to August) precipitation averaged over the previous ten years for white spruce, all having positive effects on the height-age trajectories.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author