Planning and analysis in multifunctional forestry

The new international study programme “Planning and analysis in multifunctional forestry” started at the Estonian University of Life Sciences with five foreign students in autumn 2022. The aim of the study programme is to prepare specialists with deep knowledge in the management of forest and nature resources which enable them to work in international organisations, forest enterprises, and government agencies. The graduates will have skills and knowledge on decision-making in forestry using different methods, models and tools to analyse possible scenarios and make scenarios at strategic, tactical and operational levels.

Forest management is constantly under the impact of changing conditions in the environment, society demands and markets. The need for new tools to predict forest dynamics and to simulate possible management activities is supported by many new technologies, e.g. automatic data collection, remote sensing, modern analysis methods, etc. Artificial intelligence combined with virtual reality seems a very promising decision support for complex questions in forest management. These technologies are widely available nowadays, and have been used in different fields since the middle of the 20th century. However, the use of these technologies in forestry is quite new. Artificial intelligence is already applied in forest modelling with 3D point cloud data applications and in statistical forest data analysis, but it is not yet used that often in other fields and issues of forestry.

Quantitative methods are dominating in forestry planning and analysis. New trends of applying mathematics and computing arrived in Estonian forestry with Artur Nilson (1931–2022) when he was employed as Professor of forest management planning in 1969. Artur Nilson was promoting the use of mathematical methods in forestry and computer-aided approaches for many decades. His ideas about decision support, modern and virtual forestry are innovative and novel, many of which will still be applied in the future. We, his students and colleagues, miss his enthusiastic and rational view to forest research questions and try to implement his ideas and approaches in research and education.

Evidence-based forest management is also looking deeper into the details of preparing for the approach of precision forestry. Scaling up and down is a challenging task in many applications and leads to a more profound understanding of ecosystem processes at different levels. New advances in dendrochronology and in understanding tree growth physiology are constantly improving our modelling tools, as well as improving knowledge on ecosystem functioning, forest structural traits and management impacts will enable better provision of goods and services from forest ecosystems.