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Forestry Advance Access published online on September 21, 2009
Forestry, doi:10.1093/forestry/cpp026
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© Institute of Chartered Foresters, 2009. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Development of a tree-specific stem profile model for white spruce: a nonlinear mixed model approach with a generalized covariance structure

Yuqing Yang*, Shongming Huang and Shawn X. Meng

Biometrics Unit, Forest Management Branch, Alberta Department of Sustainable Resource Development, 8th Floor, 9920-108 Street, Edmonton, AB, Canada T5K 2M4

* Corresponding author. E-mail: yuqing.yang{at}gov.ab.ca


  Abstract

A variable-exponent stem profile model was developed for white spruce (Picea glauca (Moench) Voss) trees in Alberta using a nonlinear mixed model approach. Between-tree variation in stem diameter was best captured by incorporating three random parameters into the model. Heterogeneous residual variances were modelled as a power function of tree breast height diameter. Within-tree residual autocorrelation was modelled through a covariance structure. Based on model fitting statistics, the four-banded toeplitz (TOEP(4)) and the spatial power structures were both selected for further evaluation. An independent validation dataset was used for evaluating the calibration accuracy of the final model in stem diameter and volume predictions. To make tree-specific calibrations, one or more prior diameter measures should be available from each tree. For this study, four scenarios were evaluated, in which one, two, three and four prior diameters were randomly selected for predicting random parameters by an approximate Bayesian estimator. Tree-specific calibrations were subsequently derived. Population-level predictions were also produced for comparison. The TOEP(4) structure was better in general than the spatial power structure for predicting stem diameter and total tree and section volumes.

Received 2 March 2009.
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