A model bridging distance-dependent and distance-independent tree models to simulate the growth of mixed forests

• It is widely believed that distance-independent tree models fail to take into account the complexity of mixed stands due to the fact that spatial structure often has a greater impact on growth and dynamics in mixed stands than in pure stands. On the other hand, distance-dependent tree models are difficult to use because they require a map of the stand, which is not only very costly but also impracticable in a routine management context. • This paper reports the development of a model bridging distance-dependent and distanceindependent tree models, and that is designed to simulate the growth of a mixed forest. The model used distributions of the number of neighbours to reconstruct tree neighbourhoods and compute the competition indices needed as inputs to the growth model. • Data were collected from a mixed forest of sessile oak and Scots pine in central France. The study showed that local competition indices explained a significant proportion of growth variability and that intraspecific competition was greater than interspecific competition. The model based on neighbourhood distributions gave consistent predictions compared to a distance-dependent model. • This type of model could be used instead of distance-dependent models in management contexts.