Analysing the spatial and temporal dynamics of species interactions in mixed-species forests and the effects of stand density using the 3-PG model

The growth dynamics and ecosystem services from mixed-species stands are often difficult to predict because the way a given combination of species interacts changes as resource availability or climatic conditions change from site to site or as stands develop over time. Empirical data for many of these situations is often nonexistent. The forest growth model 3-PG was adapted for mixed-species forests and for thinned stands by modifying the light-absorption routine and allowing for within-canopy vertical gradients in climate in the water balance routine. It was also adapted for deciduous species and to predict diameter distributions. The resulting model, 3-PG(mix),, was used to examine the growth dynamics of subtropical mixed-species forests containing Castanopsis sclerophylla, Cunninghamia lanceolata and Liquidambar formosana, with a wide range of stand densities in Shitai County, Anhui Province, China. After parameterizing and calibrating 3-PG(mix) using data from monocultures, its predictions of leaf and stem biomass, basal area and light absorption by each species within the mixture were highly correlated with measured values. 3-PG(mix), also predicted spatial and temporal changes in complementarity, expressed as the relative differences in growth of a given species in mixture compared with its monoculture. Complementarity was predicted to change as the stands developed, across gradients in fertility and rainfall, and also at different stand densities. Such information could be used to suggest potential species compositions, species proportions and thinning regimes for new mixed-species plantations or the responses of existing mixtures to changes in species proportions, stand density and climate. 3-PG is widely used as a routine management tool for monospecific stands and this study shows that it could potentially be used for mixed-species stands as well. (C) 2015 Elsevier B.V. All rights reserved.