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Until recently knowledge about post-fire tree mortality in Russia was fragmentary and limited, despite significant  quantity  and  area  of  wildfires  in  our  country  and  serious  ecological  and  socio-economical  damage  inflicted  by  them.  Over  the  last  few  years  widespread  implementation  of  remote  sensing  methods  allowed  regular  estimation  of  post-fire  tree  mortality  for  the  whole  territory  of  Russia.  This  development  made  it  possible  to  create a data bank with annual geospatial data on fire severity in the forests of Russia, identify new patterns in as
sociated tree mortality, and form a basis for regular monitoring of post-fire effects on forest ecosystem. This data bank  spans  the  period  from  2006  to  2017  and  offers  unique  source  of  information  for  the  development  of  new  models  of  fire  induced  mortality  that  account  for  fire  conditions  and  other  natural  factors.  This  type  of  models in turn provides new opportunities to develop methods for prediction of post-fire tree mortality. Predictions provided by those methods can play important part in the decision-making process regarding wildfire protection in Russia. Analysis provided in this paper shows significant spatiotemporal variability in fire-induced changes in forests of Russia, existence of trends in fire regimes, and consistent seasonal patterns in probabilities of post-fire mortality  for  various  tree  species.  Those  patterns  form  a  basis  for  new  methodology  of  probabilistic  prediction  and  real  time  estimation  of  post-fire  tree  mortality.  Predictions  and  estimates  produced  by  new  methodology show high skill, and thus can be used to make decisions about firefighting planning and post-fire management.