Objective  Accurate prediction of tree mortality is a very important part of forest growth and yield model system. Constructing a tree survival model based on mixed effect model and survival analysis method can improve the precision of tree mortality model.

  Method  Taking the data of 20 sample plots of mixed stands of Larix olgensis, Abies nephrolepis and Picea jazoensis in Wangqing Forestry Bureau of Jilin Province, northeastern China as the example, the tree mortality and survival model was constructed based on 6 parameter distribution models of survival analysis method (exponential distribution, Weibull distribution, log-normal distribution, log-Logistic distribution, Gompertz distribution, Gamma distribution), stand factor and site factor were added into the model as covariates. The sample plot’s random effect was considered and compared with the simulation effect of the traditional model.

  Result  With the increase of initial DBH, the risk of tree mortality decreased and the survival rate increased; with the increase of BAL, the risk of mortality increased and the survival rate decreased; with the increase of stand density per hectare, the probability of tree mortality increased and the survival rate decreased; the good-fitness of Weibull distribution model was the best; compared with the fixed effect model, the simulation accuracy of Weibull distribution model was greatly improved after considering the sample plot’s random effect, and reached a very significant degree.

  Conclusion  In forest management, if we want to improve the survival rate of trees, we should adopt scientific and reasonable management methods and management time to avoid excessive stand density.