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Report, 2020

Overview of the PlanWise application and examples of its use

Eggers, Jeannette; Öhman, Karin


There are many demands on forests today, such as producing wood and bioenergy, maintaining biodiversity, providing attractive recreational settings, and mitigating climate. These objectives are partly in conflict with each other, and management strategies differ in how much they contribute to each of these objectives. Therefore, there is a need to assess the long-term consequences of different management strategies on e.g. indicators for different ecosystem services and biodiversity.
One important tool to do such assessments are forest decision support systems (DSS), i.e. ‘computer-based systems that help decision makers to analyse and solve ill-structured problems’ (Vacik et al. 2015). Methodologically, DSS can be classified into three groups: DSS based on simulation, DSS based on optimization, and DSS used for multi-criteria decision analysis (MCDA). In this context, simulation means that forest management rules are specified, and the outcome is based on an application of these rules (Nobre et al. 2016). The simulator thus projects the likely development of the forest, and the resulting ecosystem services under pre-defined management rules. Simulators are useful for answering “what if” questions, i.e., for assessing the consequences of a limited set of pre-defined management alternatives. The advantage of simulation approaches lies in the relative ease of formulating the problem and interpreting the output. Simulation approaches are useful for projecting the consequences of a limited set of predefined scenarios. DSS based on optimization, in contrast, generate a large set of alternatives from which the best alternative is selected using an optimising algorithm based on the goals and constraints of the planning problem. These kinds of DSS can be used for answering “How to” questions, i.e., for finding the optimal way to reach certain objectives. Optimisation problems thus require that the user defines forest management goals and constraints rather than strict management rules. Both simulation and optimization approaches can be used to generate a number of scenarios, which can be used in a MCDA approach to identify the solution that best fits decision makers’ preference’s for different objectives. MCDA is the collective term for a set of mathematical methods and approaches used to find solutions to decision problems with multiple conflicting objectives.
In Sweden, the forest DSS most widely used in research, education and at forest companies for producing long-term plans and making analysis related to forest and forestry is Heureka. The Heureka forest DSS was developed at SLU and the first 1. Introduction 7 version was released in 2009 (Wikström et al. 2011). The system includes three applications that are designed to be used for different types of analysis and at different spatial levels and one application that helps compare scenarios (such as different long-term forest management plans) using MCDA. StandWise is an interactive simulator for stand-level analysis. PlanWise, which we focus on in this report, is a system for analyzing a large set of forest management options in order to identify the best alternative using optimization based on user-defined objectives and constraints. RegWise, on the other hand, is based on a simulation approach where users pre-define the management for e.g. different forest types and landowners through management rules. The advantage of using PlanWise is the possibility to find the most cost-effective solution among a nearly continuous scale of possible alternatives. On the other hand, problems with a high degree of stochasticity are difficult to formulate and solve with in the PlanWise application. For such problems, RegWise could be a better alternative. Finally, PlanEval is a MCDA application designed to evaluate and rank forest plans or scenarios created in PlanWise or RegWise. PlanEval is also available as a web version intended for participatory planning processes.
The aim of the report is to present how the Heureka PlanWise application can be used in different types of analysis for mapping and valuation of the future state of the forest, and forest-related indicators for ecosystem services and biodiversity. More specifically, we show which indicators can be assessed, how the type of input data determines what kind of analysis can be done, and how to assess trade-offs between conflicting objectives. We give several examples from recent research projects.


Ecosystem services, Heureka, decision support system, optimization, scenario analysis

Published in

Arbetsrapport / Sveriges lantbruksuniversitet, Institutionen för skoglig resurshushållning
2020, number: 514
Publisher: Department of Forest Resource Management, Swedish University of Agricultural Sciences