Stand Table Projection for BC Interior Douglas-fir

Stand Table Projection for BC Interior Douglas-fir Banner

Author(s): Woongsoon Jang &
Bianca Eskelson, Peter Marshall, Ian Moss
Published in: Forest Ecology and Management, Elsevier (February, 2018)

A stand table projection system for interior Douglas-fir in British Columbia, Canada

The mountain pine beetle outbreak across the interior of British Columbia (BC) has resulted in substantial lodgepole pine mortality over the last 15 years, which, in turn, has led to changes in forest management and harvesting plans for associated forest types including interior Douglas-fir (IDF) forests. Forest growth and yield models provide a useful tool to decision makers for adjusting these plans through evaluating forest responses to changing management regimes. However, the primary growth and yield model available for IDF forests, PrognosisBC, is cumbersome to use in the forest-level models used to support forest management planning when harvest delays occur. Stand table projection models—a compromise between whole-stand and individual tree models—can be a feasible alternative in these circumstances. It requires less input data and computing procedures for simulations, and thus is implemented more easily and cost-effectively than individual-tree models while often producing more reliable outcomes.

Using input derived from 140 permanent sample plots, simulation data were obtained through PrognosisBC. First, a whole-stand attributes prediction model was constructed. Weibull parameters for the diameter distribution of the future stand were estimated from the predicted stand attributes using two parameter prediction methods and one parameter recovery method. The future stand table was projected with the estimated Weibull parameters and compared with two stand diameter distribution adjustment algorithms, yielding a total of nine parameter estimation-diameter adjustment combinations. The diameter class adjustment procedure applying tree mortality prior to growth, combined with the cumulative distribution parameter prediction method, performed best among the nine combinations we compared. The stand table projection system yielded similar results to PrognosisBC on the evaluation data. The simplicity of the presented stand table projection model means that it can be easily integrated into other modelling frameworks, including forest estate models.

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