Accounting for bias and uncertainty in nonlinear stand density indices.
Abstract
Abstract
Several commonly used stand density indices, such as Reineke's stand density index, Few and Flewelling's relative density index, and Curtis's relative density index, depend in a nonlinear fashion on stand-level means of measured variables. Thus, the stand-level index value is not necessarily the mean of the plot-level index values. We show formally that this dependency introduces a bias that depends on the sample size or number of plots and on the variance-covariance structure of the measured variables. We then present formulas for estimating the bias and variance or standard error of estimated densities based on a priori knowledge of the variances and covariances or on observed samples data. We also present and compared bootstrap and jackknife methods of estimating the bias and variance associated with sample estimates. The results suggest that for some indices, the bias and variance arising from quick 'grab samples' may be large enough to be of practical significance. These results have strong implications for the development and interpretation of stocking guides derived from single plots or from measurement schemes other than those employed in practical applications.
Department
Natural Resources and the Environment
Publication Date
8-1999
Journal Title
Forest Science
Publisher
Society of American Foresters
Document Type
Article
Recommended Citation
Ducey, Mark J. and Larson, Bruce C., "Accounting for bias and uncertainty in nonlinear stand density indices." (1999). Forest Science. 35.
https://scholars.unh.edu/nren_facpub/35