B.C. Ministry of Forests Forest Science Program
				Abstract for Biometrics Information Handbook No. 3

		Guidelines for the Statistical Analysis of Forest Vegetation Management Data
		Branch: Research
		Author(s): Amanda F. Linnell Nemec
		Subject:  Biometrics
		Series:  Biometrics Information Handbooks
		Other details:  Published 1991, 84 pages.

Abstract

Pollack and Herring (1985) and Herring and Pollack (1985) provide a detailed set of guidelines for the design and analysis of Level A and Level B vegetation management trials. Both types of trials are used to investigate the effects of various treatments in the implementation of one of the three basic competition control strategies — site preparation, stand establishment, and stand release. Level A trials are less intensive than Level B trials and are generally used for screening new treatments, and for confirming previous treatment recommendations. Level B trials are used to carry out more comprehensive assessments of potentially useful treatments. The purpose of this report, which is intended as a supplement to Pollack and Herring (1985) and Herring and Pollack (1985), is to provide a general set of guidelines for the statistical analysis of Level A and Level B trials.

The design of a vegetation management study (i.e., the method of randomization and replication, the type of measurements, etc.) is obviously important in determining the appropriate method of analysis. The guidelines given in this report are based on the assumption that the design conforms to the recommenda-tions set forth by Pollack and Herring (1985) and Herring and Pollack (1985). The features of the design that affect the statistical analysis are discussed briefly in Section 2.

In addition to the design, the types of variables to be analysed must be considered in the selection of the statistical methods. The variables that are commonly encountered in vegetation management trials are summarized in Section 3. These include both continuous variables (e.g., height, diameter, cover) and categorical (or coded) variables (e.g., condition). In general, different methods must be employed for the statistical analysis of the two types of data.

The single most important consideration in any statistical analysis is the goal of the study. Pollack and Herring (1985) state that all forest vegetation management trials have the same basic objectives:

• "to identify site and stand treatments which manipulate vegetation on forest sites to favour the establishment and growth of commercial tree species, and to determine further research needs associated with their use" and

• "to determine the impact of these treatments on growth of commercial tree species and competing vegetation species or communities."

For the purposes of this report, a narrower objective will be defined. It will be assumed that the primary objective is to compare several treatments (including a control) in terms of their effect on the height, cover, condition, and occurrence of non-crop vegetation, and in terms of the direct (e.g., herbicide damage) and indirect (e.g., changes in the growth rate as a result of reduced competition) effects on crop trees. This objective is limited in that it does not require an investigation of the (causative) relationship between the response of the non-crop vegetation and that of the crop trees, or such other issues as the competition between the various non-crop species. Consequently, the general approach described here includes a separate analysis of the response of the non-crop vegetation and that of the crop trees. The recommended methods of analysis for the two responses are discussed in Section 4. A collection of generic SAS programs for performing the analyses is given in Appendix 1.

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