Estimation of Forest Disturbance from Retrospective Observations in a Broad-Scale Inventory

Abstract

Understanding the extent and timing of forest disturbances and their impacts is critical to formulating effective management and policy responses. Broad-scale inventory programs provide key estimates of forest parameters that indicate the extent and severity of disturbance impacts. Here we review the use of a post-stratified estimator in a panelized design, in the context of disturbance observations that are collected retrospectively. We further develop a sample weight adjustment that is requisite for proper estimation of the extent and timing of disturbances. Using populations from areas of Arkansas, California, and Maine in the U.S., the weight adjustment technique was tested in a Monte Carlo simulation. We found that the estimated area of disturbance using the weight adjustment technique had satisfactory agreement with the true population values and performed considerably better than the conventional post-stratified estimation approach. The proliferation of panelized forest inventory designs globally suggests that accurate estimates of areal extent and timing of disturbances will often require that weighting adjustment techniques be employed in the estimation process.

  • Citation: Coulston, John W.; Edgar, Christopher B.; Westfall, James A.; Taylor, Marcus E. 2020. Estimation of Forest Disturbance from Retrospective Observations in a Broad-Scale Inventory. Forests. 11(12): 1298-. https://doi.org/10.3390/f11121298.
  • Keywords: post-stratified estimation, unequal probability, sample weights, forest inventory and analysis
  • Posted Date: December 7, 2020
  • Modified Date: December 8, 2020
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