Incorporating stand level risk management options into forest decision support systems

Abstract

Aim of study: To examine methods of incorporating risk and uncertainty to stand level forest decisions.Area of study: A case study examines a small forest holding from Jonkoping, Sweden.Material and methods: We incorporate empirically estimated uncertainty into the simulation through a Monte Carlo approach when simulating the forest stands for the next 100 years. For the iterations of the Monte Carlo approach, errors were incorporated into the input data which was simulated according to the Heureka decision support system. Both the Value at Risk and the Conditional Value at Risk of the net present value are evaluated for each simulated stand.Main results: Visual representation of the errors can be used to highlight which decision would be most beneficial dependent on the decision maker's opinion of the forest inventory results. At a stand level, risk preferences can be rather easily incorporated into the current forest decision support software.Research highlights: Forest management operates under uncertainty and risk. Methods are available to describe this risk in an understandable fashion for the decision maker.

Keywords

risk preferences; forest management; inventory error; value at risk; conditional value at risk

Published in

Forest Systems
2017, Volume: 26, number: 3, article number: e013
Publisher: INST NACIONAL INVESTIGACION TECHNOLOGIA AGRARIA ALIMENTARIA

SLU Authors

• Saad, Rami

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    

• Eriksson, Ola

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Forest Science


Publication identifier

DOI: https://doi.org/10.5424/fs/2017263-10445

Permanent link to this page (URI)

https://res.slu.se/id/publ/94000