MultiTree is a research project funded by the The Computational Science Research Programme of the Academy of Finland for the years 2012–2016. Dr. Harri Mäkinen at the Finnish Forest Research Institute is the coordinator of the project.

MultiTree research project combines competencies in forest ecophysiology and ecology, forest growth, machine learning and data mining into an inter-disciplinary research team.

The principal aim of the project is to quantify the effect of environmental factors, especially climate, on forest growth, and to develop new analytical methods for detecting the climatic signal in tree growth. This is accomplished by developing advanced computational methods from machine learning and data mining for combining large data sets. The methodology incorporates a priori ecological and physical information in form of ecophysiological models and allows for fast multi-resolution algorithms. The project applies time series analysis, variable selection, regression, projection methods, neural networks, and randomization techniques.

You can look at our research poster for an overview of the research.

Sites of the research

• Finnish Forest Research Institute, Finland
• Aalto University School of Science, Department of Information and Computer Science, Finland
• University of Helsinki, Department of Forest Science, Finland

People

• Harri Mäkinen, Finnish Forest Research Institute, Finland (coordinator)
• Pekka Nöjd, Finnish Forest Research Institute, Finland
• Tuula Jyske, Finnish Forest Research Institute, Finland
• Pertti Hari, University of Helsinki, Department of Forest Science, Finland
• Eero Nikinmaa, University of Helsinki, Department of Forest Science, Finland
• Teemu Hölttä, University of Helsinki, Department of Forest Science, Finland
• Jaakko Hollmén, Aalto University, Department of Information and Computer Science, Finland
• Mika Sulkava, MTT Agrifood Research Finland
• Mikko Korpela, Aalto University, Department of Information and Computer Science, Finland

Selected Publications

1. Mikko Korpela, Pekka Nöjd, Jaakko Hollmén, Harri Mäkinen, Mika Sulkava, Pertti Hari. Photosynthesis, temperature and radial growth of Scots Pine in northern Finland: identifying the influential time intervals, Trees — Structure and Function. 25(2):323–332, April, 2011. Supplement information
2. Kangas, A., Hurttala, H., Mäkinen, H., Lappi, J. 2012. Estimating the value of wood quality information in constrained optimisation. Canadian Journal of Forest Research 42(7): 1347-1358.
3. Kalliokoski, T., Mäkinen, H., Jyske, T., Nöjd, P., Linder, S. 2013. Effects of nutrient optimisation on intra-annual wood formation in Norway spruce. Tree Physiology 33: 1145-1155.
4. Yue, C., Mäkinen, H., Klädtke, J., Kohnle, U. 2014. An approach to assessing site index changes of Norway spruce based on spatially and temporally disjunct measurement series. Forest Ecology and Management 323(2014): 10-19.
5. Jyske, T., Mäkinen, H., Kalliokoski, T., Nöjd, P. 2014. Intra-annual tracheid production of Norway spruce and Scots pine across a latitudinal gradient in Finland. Agricultural and Forest Meteorology 194: 241-254.
6. Henttonen, H.M., Mäkinen, H., Heiskanen, J. Peltoniemi, M. Laurén, A., Hordo, M. 2014. Response of radial increment variation of Scots pine to temperature, precipitation and soil water content along a latitudinal gradient across Finland and Estonia. Agricultural and Forest Meteorology 198-199: 294-308.