Forest management is currently under pressure to adapt to a changing climate at the same time as demands for both wood production and other ecosystem services are increasing. To face these challenges we need science and tools to understand and quantify future risks and opportunities –we need predictive models. Data will be available from experiments, field measurements, remote sensing, and laser scans but they can only help us predict the future if they are combined with the right type of model. To address future novel conditions the model must be based on universal ecological mechanisms rather than extrapolation of historical data. This will help us not only to make robust predictions but also to understand the underlying reasons of forests changes. This modeling work is a central component of the project “Science for enhanced forest productivity” funded by the K. and A. Wallenberg Foundation. A large team of researchers with support from the forest industry are addressing key questions for the future: How should tree species combinations and forest structure be adapted under future climate? How can precision management maximize tree survival and growth? What are the consequences of alternative management strategies for carbon sequestration and biodiversity?
You will become part of a cross-disciplinary team with both modelers and experimentalists, which requires good communications skills in English. There is some flexibility in the research tasks and approaches, but it is advantageous to have experience in model development and data analysis. Knowledge and interest in forest ecology and forestry science is also useful. Your must have received your PhD not more than five years ago. If you have any questions, please do not hesitate to contact us!