Alternatives to Incorporate Uncertainty and Risk Attitude in Multicriteria Evaluation of Forest Plans

Authors: Leskinen, Pekka¹; Viitanen, Jari¹; Kangas, Annika¹; Kangas, Jyrki¹

Source: Forest Science, Volume 52, Number 3, June 2006 , pp. 304-312(9)

Publisher: Society of American Foresters

Purchase options

The full text is free.

View now:

91.8kb
or

323.1kb

More about this publication?

More like this?

In this: publication
By this: publisher
In this Subject: Forestry
By this author: Leskinen, Pekka ; Viitanen, Jari ; Kangas, Annika ; Kangas, Jyrki

Content Key:

- Free

- New

- Open Access

- Subscribed

- Free Trial

Abstract:

This article studies alternative possibilities to incorporate uncertainty and risk attitude into multicriteria forest planning calculations. The interest is in studying the uncertainties involved in forest owner's subjective preferences, but the presented approach could be applied also more generally with measurement and modeling errors concerning forest inventory and forecasting, for example. The models applied are based on ratio scale pairwise comparisons of decision elements and their statistical regression analysis, which enables versatile possibilities to incorporate the uncertainty into decisionmaking. In traditional statistical inference, uncertainty is not used directly as a decision criterion that would be required to include risk attitude. However, the statistical approach can be used, for example, to derive pairwise winning probabilities for forest plans beating each other and rank probabilities for forest plans for attaining a given rank. Several types of indices can be derived from these probabilities enabling the incorporation of risk attitude, but a more promising approach was to reduce the decisionmaking problem to contain mean and SD of the utility distributions for each forest plan and provide them as decision support to the forest owner. The approach is based on classical mean-variance utility in portfolio theory. Also, weighted average of certain percentiles of the utility distributions or weighted average of rank probabilities have their advantages.

Keywords: Forest planning; multicriteria decision analysis; regression; statistical inference; uncertainty

Document Type: Research article

Affiliations: 1: Pekka Leskinen, Senior Researcher, Finnish Forest Research Institute, Joensuu Research Unit, PO Box 68, FIN-80101 Joensuu, Finland—Phone: +358-10-2113027; pekka.leskinen@metla.fi. Jari Viitanen, Researcher, Finnish Forest Research Institute, Joensuu Research Unit, PO Box 68, FIN-80101 Joensuu, Finland—Phone: +358-10-2113033; Fax: +358-10-2113001; jari.viitanen@metla.fi. Annika Kangas, Professor, University of Helsinki, Faculty of Agriculture and Forestry, Department of Forest Resource Management, PO Box 27, FIN-00014 University of Helsinki, Finland—Phone: +358-9-19158177; Fax: +358-9-19158159; annika.kangas@helsinki.fi. Jyrki Kangas, Professor, UPM Forest, PO Box 32, FIN-37601 Valkeakoski, Finland—Phone: +358-20-416121; Fax: +358-20-416120; jyrki.kangas@upm-kymmene.com., Fax: +358-10-2113113