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Interactions between tree species determine the dynamics of forest communities. Spatial and temporal changes in resource availability, variation in species composition and spatial distribution of trees may alter competitive interactions between species and, therefore, affect tree growth and forest productivity. In this study, we analyzed the intra and inter-specific interactions between European beech (Fagus sylvatica L.) and silver fir (Abies alba Mill.) in southern Italy (Molise and Calabria regions), and how these interactions affect basal area increments in mixed-species and pure stands. Results showed that intraspecific interactions have a negative effect on the basal area increment, both in pure and mixed-species stands of Molise and Calabria. Basal area increment was higher influenced by intra-specific interactions in pure stands than in mixed-species stands. Silver fir in Molise showed higher basal area increment in mixed-species stand, probably in relation with stand structure and space occupation that resulted in less competition between individual trees. European beech showed high values of intra-specific interactions in pure stands, likely related to the low self-tolerance of this species and to the spatial arrangement of trees, due to canopy closure. The absence of inter-specific interactions in mixed-species stands could be explained by the sub-dominant position of European beech, which may have limited the benefit derived from niche separation and complementarity for silver fir. [ABSTRACT FROM AUTHOR]

Competitive interactions are important predictors of tree growth. Spatial and temporal changes in resource availability, and variation in species and spatial patterning of trees alter competitive interactions, thus affecting tree growth and, hence, biomass. Competition indices are used to quantify the level of competition among trees. As these indices are normally computed only over small areas, where field measurements are done, it would be useful to have a tool to predict them over large areas. On this regard, remote sensing, and in particular light detection and ranging (lidar) data, could be the perfect tool. The objective of this study was to use lidar metrics to predict competition (on the basis of distance-dependent competition indices) of individual trees and to relate them with tree aboveground biomass (AGB). The selected study area was a mountain forest area located in the Italian Alps. The analyses focused on the two dominant species of the area: Silver fir (Abies alba Mill.) and Norway spruce (Picea abies (L.) H. Karst). The results showed that lidar metrics could be used to predict competition indices of individual trees (R2 above 0.66). Moreover, AGB decreased as competition increased, suggesting that variations in the availability of resources in the soil, and the ability of plants to withstand competition for light may influence the partitioning of biomass. [ABSTRACT FROM AUTHOR]