Improving the quality of landscape ecological forest planning by utilising advanced decision-support tools

The quality of landscape ecological analyses and their integration with the multi-objective comparison of forest plans can be improved by making use of the decision-support methods, techniques, and tools produced by recent research on forest planning, as demonstrated in this study. Special attention is given to strengthening the ecological grounds of calculations through modelling expert knowledge, quantification of ecological evaluations, integration of different objectives and different phases of the planning process, and analysing the effects of uncertainty in ecological judgments on the final results. The planning process is illustrated by a case study. The landscape ecological approach is finding increasing application in practical forest planning, especially in boreal forestry. Unfortunately, gaps in the available ecological knowledge, and the inefficiency of the planning methods and tools used often lead to vague planning processes. In many cases, only methods originally developed for wood-production planning are still applied, and planning advances (e.g. multi-objective optimisation, Geographical Information Systems (GIS) tools, and modelling expert knowledge) are under-utilised. In this study, HERO heuristic multi-objective optimisation, GIS operations, pairwise comparisons techniques, and Bayesian analysis are applied in an integrated planning process. Efficient forest plan alternatives are generated for further consideration by utilising heuristic optimization and GIS. Given the multi-objective choice situation, the plans generated are holistically evaluated by means of multiple decision-support tools and techniques. (C) 2000 Elsevier Science B.V. All rights reserved.