The Geometric Mean Regression Line: A Method for Developing Site Index Conversion Equations for Species in Mixed Stands

$29.50 plus tax (Refund Policy)

Buy Article:


Models that provide analysts with the ability to predict the site index of one species in a mixed stand from the site index of a cohort are useful for site quality evaluation, growth and yield modeling, and timber management planning. A simple compatible system is needed to perform site index conversions, and thus linear regression is an unsuitable technique. In this study, a single-equation compatible system is developed using the geometric mean regression (GMR) line. The properties of the GMR line make it well suited for site index conversion equations. The GMR methodology was applied to mixed coastal Douglas-fir (Pseudotsuga menziesii [Mirb.] Franco)/western hemlock (Tsuga heterophylla [Raf.] Sarg.) and interior white spruce (Picea glauca [Moench] Voss)/lodgepole pine (Pinus contorta var. latifolia Dougl.) stands in British Columbia. Validation shows that these relationships are unbiased and expedient. Careful attention must be used when determining the suitability of Stands to which the relationship is applied. For. Sci. 41(1): 84-98.

Keywords: Douglas-fir; lodgepole pine; western hemlock; white spruce

Document Type: Journal Article

Affiliations: Biometrician, Growth and Yield, with the Research Branch, British Columbia Ministry of Forests, 31 Bastion Square, Victoria, British Columbia, Canada, V8W 3E7

Publication date: February 1, 1995

More about this publication?
  • Membership Information
  • ingentaconnect is not responsible for the content or availability of external websites
Related content



Share Content

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
ingentaconnect 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