Skip to main content

A Generalized Approach to Stand Table Projection

The full text article is temporarily unavailable.

We apologise for the inconvenience. Please try again later.

A new algorithm for stand table projection based on existing estimates of future basal area and survival is derived and demonstrated. An observed stand table is first projected by applying either an existing diameter growth equation or a growth equation derived from appropriate diameter distributional assumptions. The stand table is adjusted by an algorithm that equates the future stand table to existing estimate of basal area and survival. The algorithm does not use any species-specific parameters and can therefore be applied to any species for which future estimates of basal area and survival are available. This algorithm provides comparable estimates when the initial diameter distribution is close to the unimodal distribution assumed by parameter recovery procedures in diameter distribution growth and yield models. In fact, the algorithm reduces to the same future stand table when the initial stand table is actually generated by the diameter distribution derived by the parameter recovery procedure. However, if the observed stand table is multimodal, the prediction by this algorithm is better than predictions from the parameter recovery method alone. Favorable comparisons are also made with the stand table projection method introduced by Pienaar and Harrison (1988), for natural even-aged longleaf pine stands. For. Sci. 38(1):120-133.
No References
No Citations
No Supplementary Data
No Article Media
No Metrics

Keywords: Parameter recovery; Weibull distribution; diameter distribution; diameter growth equation; longleaf pine

Document Type: Journal Article

Affiliations: Assistant Professor, School of Forestry and Alabama Agricultural Experiment Station, Auburn University, Auburn, AL 36849-5418

Publication date: 01 February 1992

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more