Project: Decision support for individual-tree-selection - aiming at profitability and biodiversity (DITS)
The project aims to develop decision support to determine the optimal harvesting time for individual trees. The decision support shall provide greatest possible benefit for profitability and biodiversity.
Project information
Project manager
Nils Fagerberg
Other project members
Karl-Olov Lindahl och Rikard Jakobsson, Linnaeus University. Line Djupström, Skogforsk. Timo Pukkala, East Finland Invest. Päivi Väänänen, Yrjö Nuutinen, Simone Bianchi och Jari Miina, Natural Resources Institute Finland. Andis Lazdins, Agris Zimelis, Raitis N Meļņiks, Santa Kalēja och Jänis Donis, Latvian State Forest Research Institute (Silava). Ahto Kangur, Andres Kiviste, Allar Padari och Eneli Põldveer, Estonian University of Life Sciences.
Participating organisations
Linnaeus University, Skogforsk, East Finland Invest, Natural Resources Institute Finland, Latvian State Forest Research Institute (Silava), Estonian University of Life Sciences
Funders
NordForsk and the joint funding bodies (the Research Council of Finland; Formas; the Research Council of Norway; the Estonian Research Council; and the Latvian Council of Science)
Timetable
1 Jan 2026 – 31 Dec 2029
Subject
Forestry and wood technology (Department of forestry and wood technology, Faculty of technology), mathematics (Department of Mathematics and Physics, Faculty of technology)
Reserach groups
Forest management and Small-scale Forestry
Linnaeus University Centre (Lnuc)
Linnaeus University Centre for Data Intensive Sciences and Applications
Knowledge Environment
Linnaeus Knowledge Environment: Green Knowledge Development
Funders
More about the project
Modern forest management is increasingly tasked with simultaneously meeting economic, ecological, and social objectives. At the same time, forestry faces new opportunities to make harvesting decisions more efficient, due to recent advancements in technology and digital analytics. This new technology can be used to describe a forest in detail, down to individual tree level. With this information, harvesting decisions can be made at the same level of detail. In forestry terms, that type of management planning is called individual tree selection (ITS). By permitting trees to mature at different sizes at different times, depending on factors affecting the value-production of the individual tree, stand structures often develop a large variation of tree sizes. Such uneven-sized forests represent structures that are uncommon in traditional forestry today, while in many cases mimicking more natural dynamics. Therefore, ITS offers the prospect of enhanced ecological benefits and improved long-term sustainability while simultaneously maintaining profitability. This is possible to the extent that detailed information about the forest is available, and thorough research has been conducted to determine optimal timepoint of harvest.
The proposed project is centered on developing decision-support tools tailored to ITS while balancing economic objectives with biodiversity aims. The focus is on the humid continental climate zones of Finland, Estonia, Latvia, and Sweden, where similar growing conditions prevail. The suggested plan for the project includes model development to improve growth simulation of the commercial species in the region. Two complementary optimization strategies will be applied. One strategy investigates the option of directly calculating which trees to remove in a specific stand. The other strategy employs optimization through comprehensive system simulations of representative stands, to produce more generalized tree-selection rules. Biodiversity is integrated into the optimization process by exploring and incorporating relevant variables.
By synthesizing high-resolution data with robust mathematical optimization and cross-disciplinary expertise, the project will apart from investigating the potential of ITS in the Nordic-Baltic region, foster cross-country capacity building, and promote sustainable management practices.
The project forms part of the research conducted within the research group Forest Management and Small-scale Forestry, as well as within the Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) and the Linnaeus Knowledge Environment: Green Sustainable Development.