Articles containing the keyword 'predictive modelling'

The seed crop of Norway spruce (Picea abies (L.) H. Karst.) and Scots pine (Pinus sylvestris L.) is predicted with the help of mean monthly temperatures during May–August one and two years before the flowering year. The prediction models were made separately for Lapland and for the rest of Finland. The models are based on 10-year periods of seed crop measurements and climatic data. The total number of time series was 59.

In Lapland, Norway spruce flowered abundantly and produced an abundant seed crop after warm July–August and two years after cool July–August. In other parts of Finland, warm June and July produced a good flowering year, especially if these months were cool two years before the flowering year.

In Lapland, Scots pine flowered abundantly if the whole previous growing season was warm. Elsewhere in Finland, a cool June preceded prolific flowering in the coming year if the rest of the growing season was considerably warmer than the average.

The prediction models explained 37–49 % of the variation in the size of the seed crop. The occurrence of good and poor seed years was usually predicted correctly. Using the presented models, the prediction of the seed crop is obtainable 1.5 year for Norway spruce and 2.5 year for Scots pine before the year of seed fall.

The PDF includes an abstract in English.

• Pukkala, E-mail: tp@mm.unknown

Despite the numerous studies on year-to-year variation of tree growth, the physiological mechanisms controlling annual variation in growth are still not understood in detail. We studied the applicability of data-driven approach i.e. different regression models in analysing high-dimensional data set including continuous and comprehensive measurements over meteorology, ecosystem-scale water and carbon fluxes and the annual variation in the growth of app. 50-year-old Scots pine stand in southern Finland. Even though our dataset covered only 16 years, it is the most extensive collection of interactions between a Scots pine ecosystem and atmosphere. The analysis revealed that height growth was favoured by high water potential of the tree and carbon gain during the bud forming period and high water potential during the elongation period. Diameter growth seemed to be favoured by a winter with high precipitation and deep snow cover and a spring with high carbon gain. The obtained models had low generalization performance and they would require more evaluation and iterative validation to achieve credibility perhaps as a mixture of data-driven and first principle modeling approaches.

• Kulmala, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: liisa.kulmala@helsinki.fi
• Žliobaitė, Aalto University, Department of Computer Science and Helsinki Institute for Information Technology, P.O. Box 11000, FI-00076 Aalto, Finland; University of Helsinki, Department of Geosciences and Geography, P.O. Box 64, FI-00014 University of Helsinki, Finland E-mail: zliobaite@gmail.com
• Nikinmaa, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: eero.nikinmaa@helsinki.fi
• Nöjd, Natural Resources Institute Finland (Luke), Bio-based business and industry, Tietotie 2, FI-02150 Espoo, Finland E-mail: pekka.nojd@luke.fi
• Kolari, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland; University of Helsinki, Department of Physics, P.O. Box 64, FI-00014 University of Helsinki, Finland E-mail: pasi.kolari@helsinki.fi
• Kabiri Koupaei, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: kourosh.kabiri@helsinki.fi
• Hollmén, Aalto University, Department of Computer Science and Helsinki Institute for Information Technology, P.O. Box 11000, FI-00076 Aalto, Finland; University of Helsinki, Department of Geosciences and Geography, P.O. Box 64, FI-00014 University of Helsinki, Finland E-mail: jaakko.hollmen@aalto.fi
• Mäkinen, Natural Resources Institute Finland (Luke), Bio-based business and industry, Tietotie 2, FI-02150 Espoo, Finland E-mail: harri.makinen@luke.fi