Science driven decision support systems for a multifunctional sustainable forest management

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Achieving sustainable use of forested lands by means of an optimal allocation of land resources to competing purposes is a major global challenge for the 21st century. The overall aim of my research program therefore is to develop, apply and validate a new suite of innovative approaches for a spatially explicit optimization of forest management under uncertainty. I will follow a number of critical lines of inquiry. Together with HQP I will undertake detailed analyses of existing model types for spatially explicit resource allocation, economic optimization and reduction of production risk. Second we will develop a new suite of innovative approaches using open interfaces and finally we will explore ways and deliver solutions for a constant enhancement of the database available for decision making. Our tools will be developed using algebraic modeling languages in combination with external modeling languages allowing a wide variety of applications. Once developed science driven decision support systems will help to find sustainable forest management strategies for Canada’s forest resource, capable of fulfilling multiple objectives and facilitating constant resource supply. The decision support systems we develop will help to achieve the goal of developing both a sustainable forest resource and sustainable enterprises that are less susceptible towards risks, ensuring long-term economic sustainability and a sustainable conservation of forest values by allowing managers to make informed decisions and enabling them to consider a range of forest uses within explicit risk regimes, such as non-timber bio-resources. The open source characteristics of the suite of innovative approaches that will be developed, as well as the strong focus on open interfaces will allow for a constant and ongoing advancement and adaption of the output the proposed work will deliver.