Objective  The tree height curve of main tree species was established based on tree classification, which provided reference for studying the growth law of Larix gmelinii, and provided technical support for forest sustainable management in Daxing’anling Mountains of northeastern China.

  Method  Based on the data of 56 fixed sample plots in Cuigang Forest farm of Daxing’anling Mountains, trees were divided into three grades of dominant, average and crushed trees according to the relative diameter (d) of individual trees. Based on the maximum adjusted coefficient (R² _adj), minimum root mean square error (RMSE) and the minimum red pool information (AIC), the optimal tree height curve basic model of different grades of natural Larix gmelinii was screened out, and the effects of quantile regression and dummy variable regression on the simulation accuracy of tree height curve models of different grades of Larix gmelinii were further evaluated and compared.

  Result  The optimal basic model of Larix gmelinii height curves was Wykoff equation. When the dumb variables of stand classification were added to parameters a and b of Wykoff equation, the model had the best fitting effect. R² _adj, RMSE and AIC of Larix gmelinii tree species curve model were 0.858 8, 1.642 4 and 2 081.902, respectively. There was no difference between the optimal quantile model and the whole stand of Larix gmelinii, and the median model was optimal (τ = 0.5). The three statistics of height curve of the deciduous pine were 0.849 8, 1.693 8 and 2 211.037, respectively. Through comparative analysis, the tree height curve model with tree classification as dummy variable had the best fitting effect.

  Conclusion  The height curve model of Larix gmelinii in the Daxing’anling Mountains, which contains dummy variables for tree classification, has better fitting performance than the basic model, and has good prediction accuracy and adaptability. It can reflect the growth differences of tree height and DBH under different tree grades, and can provide a theoretical basis for the management and growth prediction of Larix gmelinii in the Daxing’anling Mountains region.