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Mixed-species stands have been studied extensively due to their potentially superior productivity, multi-functionality benefits and high ecological value compared to pure stands. The higher structural heterogeneity in mixed stands that can emerge from species interactions could be linked to the relationship between species diversity and ecosystem functions. We tested whether changes in stand structure also occur in mixtures of species with similar traits and whether they explain over-yielding patterns. Based on research with 12 triplets of Scots pine (Pinus sylvestris L.) and Maritime pine (Pinus pinaster Ait.) in the northern Iberian Peninsula (Spain), we provide evidence that species mixing increased structural heterogeneity and may induce over-yielding in mixed-species stands compared to monospecific stands. In this mixture of two light-demanding species, we observed that (i) stand composition influenced the inter-specific crown allometric variation, (ii) structural heterogeneity in mixed stands was caused by both specie-specific traits and species interactions, and (iii) intraspecific and interspecific differences in both crown size plasticity and size-distribution differentiation were associated with the increased relative productivity of mixed stands. We detected that crown complementarity and vertical stratification in the canopy space is a crucial mechanism for enhancing ecosystem productivity in light-demanding species and could be related to light interception and light-use. This work improves our understanding of emerging properties in mixed stands and introduces considerations for properly scaling and tracing mixing effects at individual tree, size distribution and stand levels.

Models that incorporate known species-mixing effects on tree growth are essential tools to properly design silvicultural guidelines for mixed-species stands. Here, we developed generalized height–diameter (h-d) and basal area growth models for mixed stands of two main forest species in Spain: Scots pine (Pinus sylvestris L.) and Maritime pine (Pinus pinaster Ait.). Mixed-effects models were fitted from plot measurement and tree rings data from 726 Scots pine and 693 Maritime pine trees from mixed and pure stands in the Northern Iberian Range in Spain, with the primary objective of representing interactions between the species where they are interspersed in mixtures of varying proportions. An independent dataset was used to test the performance of the h-d models against models previously fitted for monospecific stands of both species. Basal area increment models were evaluated using a 10-fold block cross-validation procedure. We found that species mixing had contrasting effects on the species in both models. In h-d models, the species-mixing proportion determined the effect of species interactions. Basal area growth models showed that interspecific competition was influential only for Maritime pine; however, these effects differed depending on the mode of competition. For Scots pine, tree growth was not restricted by interspecies competition. The combination of mixed-effect models and the inclusion of parameters expressing species-mixing enhanced estimates of tree height and basal area growth compared with the available models previously developed for pure stands. Although the species-mixing effects were successfully represented in the fitted models, additional model components for accurately simulating the stand dynamics of mixtures with Scots pine and Maritime pine and other species mixtures require similar model refinements. Upon the completion of analyses required for these model refinements, the degree of improvement in simulating growth in species mixtures, including the effects of different management options, can be evaluated.

a b s t r a c tAgroforestry land-use systems in the Andean region have great socioeconomical and biophysical relevance due to the abundance of products and services they provide. Biomass estimation in these systems constitutes a priority concern as it facilitates assessment of carbon sink potential and functionality for biomass production. In this paper, a set of equations were fitted to enable easy and reliable estimation of the total aboveground biomass of four frequently used species in Andean agroforestry systems: Acacia melanoxylon L., Alnus acuminata Kunth., Buddleja coriacea Remy. and Polylepis racemosa Ruiz&Pav. The best models for each biomass component (stem, thick branches, thin branches and leaves) per species were fitted simultaneously according to SUR methodology (seemingly unrelated regressions). All models showed high goodness of fit statistics and more than 70% of the observed variation in biomass components was explained by the independent variables. The inclusion of height as a predictive variable in the models improved their predictive reliability and expanded the application range. The models developed here are useful for assessing the sustainability of agroforestry systems and could support governmental or non-governmental forest conservation incentive programs and initiatives.