Prof. Vladimir Shishov

August, 2017 to September, 2018

LE STUDIUM / Marie Skłodowska-Curie Research Fellowship 


Siberian Federal University - Mathematical Methods and IT Department, Krasnoyarsk - RU

In residence at

BioForA, Centre INRAE Val-de-Loire / ONF - FR

Host scientist

Dr Philippe Rozenberg


Global Tree-Ring Growth Evolution Neural Network (VS-GENN)

The project addresses a fundamental problem of forest reaction forecast to the climate change and increasing concentrations of greenhouse gases for the terrestrial ecosystems of the Earth.

The problem of tree-ring response to possible climate change is one of the most urgent problems of the modern forest ecology. Despite the large number of papers concerning tree-ring response to different environmental changes (temperature increasing, drought, etc.) there is no reliable answer how woody plants will respond to environment changes in different forest stands and various physiographic zones.

The main target of the project is to produce a retrospective assessment and a short-term forecast of annual tree-ring productivity (seasonal cell production) of the major conifer plant species in terrestrial forest ecosystems around the World forced by climate and non-climatic factors. The analysis will be based on an Interactive Information platform “Global Tree-Ring Growth Evolution Neural Network” ( and available datasets developed for the European, Asian and South American  dendrochronological test-polygons. During the project we plan to use an original process-based tree-ring VS-model, on-line simulations and GIS applications developed by the author of the project and other research teams from France, Spain and UK.

The team intends to estimate the long-term annual tree-ring productivity (cell production) of woody plants impacted by the principal climatic and non-climatic factors, and to predict tree-ring productivity in the short-term context for the research regions. To achieve the goal of the project, we will test the VS-simulations based on direct long-term field observations for the well-documented tree-ring test-polygons in Europe, Asia and South America. We plan to apply state-of-art techniques, including  unique approaches developed by the authors.

The project has no analogues in Europe. All stated tasks are novel and extremely important for understanding global processes undergoing in the forest ecosystems under observed climatic changes and other disturbances.

Events organised by this fellow

An Artificial Intelligence in the Simulation of Tree-Ring Growth around the World
À la recherche du bois perdu : le bois archéologique, témoin de notre passé
Wood formation and tree adaptation to climate

Articles Published

  • Global Tree-Ring Growth Evolution Neural Network (VS-GENN)

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  • Wood formation and tree adaptation to climate

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