Abstract

Vertical forest structure is closely linked to multiple ecosystem characteristics, such as biodiversity, habitat, and productivity. Mixing tree species in planted forests has the potential to create diverse vertical forest structures due to the different physiological and morphological traits of the composing tree species. However, the relative importance of species richness, species identity and species interactions for the variation in vertical forest structure remains unclear, mainly because traditional forest inventories do not observe vertical stand structure in detail. Terrestrial laser scanning (TLS), however, allows to study vertical forest structure in an unprecedented way. Therefore, we used TLS single scan data from 126 plots across three experimental planted forests of a large-scale tree diversity experiment in Belgium to study the drivers of vertical forest structure. These plots were 9–11 years old young pure and mixed forests, characterized by four levels of tree species richness ranging from monocultures to four-species mixtures, across twenty composition levels. We generated vertical plant profiles from the TLS data and derived six stand structural variables. Linear mixed models were used to test the effect of species richness on structural variables. Employing a hierarchical diversity interaction modelling framework, we further assessed species identity effect and various species interaction effects on the six stand structural variables. Our results showed that species richness did not significantly influence most of the stand structure variables, except for canopy height and foliage height diversity. Species identity on the other hand exhibited a significant impact on vertical forest structure across all sites. Species interaction effects were observed to be site-dependent due to varying site conditions and species pools, and rapidly growing tree species tend to dominate these interactions. Overall, our results highlighted the importance of considering both species identity and interaction effects in choosing suitable species combinations for forest management practices aimed at enhancing vertical forest structure.

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