He has 15 years research experience in large scale global carbon cycle, vegetation and fire modelling. A Masters degree at in mathematics at University of Vienna (1999) was followed by a PhD in Ecology at the Agricultural University of Vienna (2001), which examined large scale interactions of fires, vegetation dynamics and permafrost in Siberia. He was a postdoctoral researcher at the International Institute for Applied System Analysis, Laxenburg Austria, Potsdam Institute for Climate Research, Germany and Frontier Research for Global Climate Change, Yokohama, Japan. SV worked with the Hadley Centre for Climate Predictions, Exeter, UK, where he was responsible for implementation of large scale fire models into the Hadley GCMs (general atmospheric circulation models). He suggested a first mechanistic model of vegetation diversity at global scale and was first to implement large scale fire models into different state-of-the–art dynamic global vegetation models. He participated in several EU Projects including ETEMA, DART, AETEM, SIBERIA-II, several national projects in Russia and an international project on sustainability of Siberian Forests (15 Russian, 2 North American and 6 European institutions).  SV is the lead author of North Eastern Eurasian Scientific Project Initiative, run by NASA and the Russian Academy of Sciences. SV has authored over 25 papers in peer-reviewed journals including two highly cited – on dynamic global vegetation model LPJ DGVM (Sitch. Et al, 2003, - over 700 citations) and on carbon in the permafrost zone (Shuur, et.al, 2008 - over 200 citations).

 

 

Dynamic global vegetation model SEVER-DGVM is introduced as a major tool for simulation of global terrestrial carbon cycle and hydrology is introduced. Procedure of regionalisation of this global model for continental scale (on example of Russia) using remote sensing data is presented. Implementation of wildfires into dynamic global vegetation model is described. Features of permafrost hydrology affecting carbon cycle are built in the continental scale SEVER-DGVM. Independent global vegetation diversity model based solely on climate factors is designed and applied for recent and future climate scenarios. Identification of national biodiversity hotspots is suggested using vegetation diversity model. Situation with wildfires in Russian biodiversity hotspots is reconstructed with the dynamic global vegetation model. Perspectives of application of described simulation tools and methods for China is discussed.