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

LE STUDIUM Multidisciplinary Journal, 2018, 2, 9-20

Vladimir V. Shishov1,2,5, Ivan I. Tychkov1, Margarita I. Popkova1, Minhui He3, Bao Yang4, Philippe Rozenberg5


1 Siberian Federal University, L.Prushinskoy st. 2, Krasnoyarsk, 660075, Russia

2 LE STUDIUM Institute for Advanced Studies, 45000 Orléans, France

3 Institute of Geography, University of Erlangen-Nürnberg, 91058 Erlangen, Germany

4 Key Laboratory of Desert and Desertification, Northwest Institute of Eco-Environment and Resources,

Chinese Academy of Sciences, Lanzhou 730000, China

5 Biologie Intégrée Pour la Valorisation de la Diversité des Arbres et de la Forêt (BioForA) - UMR 058, INRA (Institut National de la Recherche Agronomique), 2163 Avenue de la pomme de pin, 45075 Ardon, Orléans, France


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 main target 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 Eurasia forced by climate and non-climatic factors. The analysis is based on an Interactive Information platform “Global Tree-Ring Growth Evolution Neural Network” ( and datasets available for the European and Asian dendroecological test-polygons. To achieve the goal of the project, we testified the Vaganov-Shaskin model and its parametrization, as a part of the developing IT system, based on direct long-term field observations for the tree-ring sites in Europe and Asia. As a result of the fellowship four papers were published in high impacted ISI journals. Moreover, a special issue of the ISI journal “Annals of Forest Science” is prepared.


Tree-ring response
Climate change
Process-based models
Neural networks
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LE STUDIUM Multidisciplinary Journal