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Aims Spatial structure is important in describing forest stand structure and change. We present a new method for the quantitative analysis of forest spatial structure based on the relationship of nearest neighbour tree groups. Location Six hundred m a.s.l., Dongdapo Natural Reserve, Jiaohe, Jilin Province, China Methods Six plots in three common stand types of natural Korean pine broad‐leaved forest in northeast China were used to validate the method. Each plot measured 100 × 100 m, and all trees with DBH ≥5 cm were marked and located using a Total Station. We calculated bivariate distribution of the structural parameters, uniform angle index, mingling and dominance using Winkelmass and Excel software. Results Most trees in the forest were highly mixed by species and randomly distributed. Individuals with high DBH values were typically surrounded by other species; trees within stochastic distribution patterns were usually surrounded by different species; and medium‐sized trees were randomly distributed. Conclusions The bivariate distribution of structural parameters can provide more direct and useful information about the heterogeneity of spatial structure than can univariate distributions or other conventional stand descriptors. This could be helpful for selective thinning in continuous cover forest management and in modelling and restoring forests.

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