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Light is one of the most critical factors controlling tree survival and growth. Limited light availability induces phenotypic plasticity, thus enabling plants to adapt to suboptimal conditions. The plastic responses are species-specific and are thought to largely depend on species' shade tolerance. This study aims to add to existing research by trying to disentangle the effects of light, species identity, and shade tolerance on growth, biomass partitioning, and morphology of seedlings of seven common European tree species. For that purpose, we set up a shading experiment where seedlings were grown under three levels of light availability (15%, 35%, and 100%). A destructive harvest was carried out for the assessment of biomass allocation and structural complexity of plant architecture after a year of exposure to limited light. The specific leaf area increased with decreasing light availability for all species. However, we found little to no changes in relative height and diameter growth, biomass allocation to aboveground tree compartments, and structural complexity along the light gradient. We argue that because trees were grown under open field conditions, both in the nursery and for the first year of the experiment, it might have resulted in a delayed response to limited light availability. Assuming the delayed reaction of less plastic plant organs, we expect that the morphological adaptations of the tree species and intra- and interspecific differences will become more pronounced, as the trees grow older. [ABSTRACT FROM AUTHOR]

The position and size of trees is basic information available for most forest-research sites. Based on such information, various stand structural indices and measures can be calculated that describe the two-dimensional or three-dimensional forest structure. We used fractal analysis to calculate the box-dimension (D b ) as a measure of structural complexity that can be derived from stem positions and stem diameters. D b is supposed to combine information on tree size, tree distribution and stem density in a single meaningful measure. We wanted to know how powerful the method is if applied to two-dimensional stem distribution maps. Based on 125 research plots (coniferous, deciduous and mixed stands) we found that across typical forest systems in Germany there is no benefit from using the box-dimension. Stem number and mean tree diameter determined D b values and there was almost no sensitivity observed for existing differences in stem distribution pattern. We conclude that D b is a measure of stand density but, for the investigated forests, it does not provide information on tree distribution pattern if applied to the stem base maps. [ABSTRACT FROM AUTHOR]

The three-dimensional forest structure affects many ecosystem functions and services provided by forests. As forests are made of trees it seems reasonable to approach their structure by investigating individual tree structure. Based on three-dimensional point clouds from laser scanning, a newly developed holistic approach is presented that enables to calculate the box dimension as a measure of structural complexity of individual trees using fractal analysis. It was found that the box dimension of trees was significantly different among the tested species, among trees belonging to the same species but exposed to different growing conditions (at gap vs. forest interior) or to different kinds of competition (intraspecific vs. interspecific). Furthermore, it was shown that the box dimension is positively related to the trees' growth rate. The box dimension was identified as an easy to calculate measure that integrates the effect of several external drivers of tree structure, such as competition strength and type, while simultaneously providing information on structure-related properties, like tree growth. [ABSTRACT FROM AUTHOR]

One of the main goals of modern silviculture is to emulate the structural complexity of old-growth forests. In this context, it is of advantage to identify a target state of structural complexity at the stand level and to analyze the spatial characteristics that led to the desired complexity of forest structures in primary forest references. In this study, we used 3D forest scenes captured by terrestrial laser scanning (TLS) to identify spatial patterns of structural complexity of differently managed and unmanaged European forests dominated by beech (Fagus sylvatica L.). We scanned in managed even-aged and uneven-aged stands, as well as in formerly managed forests (National Parks) and primary forests. For three different forest strata, representing the understory, the midstory, and the overstory of a forest stand, we determined the structural complexity mathematically using fractal analysis. Beyond that, we analyzed the density, as well as the horizontal and vertical distribution of plant material. For all three forest strata, we observed differences in structural complexity between the different forest types. Within the lower and middle strata, the investigated primary forests showed a random to regular distribution of plant material, as well as a complex understory structure as a result of pronounced natural decay. Compared to the primary forests, the managed uneven-aged stands showed quite similar spatial patterns of distribution of plant material, but on average a higher space occupation in the lower and middle forest stratum. Our results suggest that single tree or group selection cutting is a useful management tool to imitate old-growth structures of undisturbed beech-dominated forests. [ABSTRACT FROM AUTHOR]

The three-dimensional forest structure is an important driver of several ecosystem functions and services. Recent advancements in laser scanning technologies have set the path to measuring structural complexity directly from 3D point clouds. Here, we show that the box-dimension (Db) from fractal analysis, a measure of structural complexity, can be obtained from airborne laser scanning data. Based on 66 plots across different forest types in Germany, each 1 ha in size, we tested the performance of the Db by evaluating it against conventional ground-based measures of forest structure and commonly used stand characteristics. We found that the Db was related (0.34 < R < 0.51) to stand age, management intensity, microclimatic stability, and several measures characterizing the overall stand structural complexity. For the basal area, we could not find a significant relationship, indicating that structural complexity is not tied to the basal area of a forest. We also showed that Db derived from airborne data holds the potential to distinguish forest types, management types, and the developmental phases of forests. We conclude that the box-dimension is a promising measure to describe the structural complexity of forests in an ecologically meaningful way. [ABSTRACT FROM AUTHOR]

• High tree structural complexity is beneficial to high stand structural complexity. • Most tested measures we observed showed scale dependency. • We found no patterns of emergence for structural complexity in forests. • Structural complexity plateaus already with 20 trees grouped together. Management for complexity has become an important paradigm for European and North American forestry. Recent advancements in data processing allow for a detailed, three-dimensional and objective quantification of structural complexity in forests based on terrestrial laser scanning data. In our study, we used such 3D data from an exemplary temperate broad-leaved forest in Thuringia, Germany, to gain insights to the relationship between tree-level structural complexity and stand-level structural complexity. From our study site, which was 80 by 80 m in extent with a total of 215 trees growing in it, we created a dataset that contained each tree as an independent point cloud. Random sample plots of varying size (10 × 10 m; 15 × 15 m; 20 × 20 m) where used to create sub-plots (sampling with replacement) and to enable for the investigation of effects of scale. Our study revealed that plot-level complexity of plots up to 20 × 20 m is largely determined by the complexity of the most complex-structured tree individual. Furthermore, a high tree complexity and variability thereof in the stand was generally beneficial to stand structural complexity. Other individual tree characteristics, such as a large crowns, were also identified to have positive effects on plot-level complexity. We conclude that management for complexity should focus on large-crowned, highly-complex tree individuals as key elements of stand structural complexity. This indicates that large and old trees may not only be of great importance as habitat trees potentially increasing biodiversity, but also due to their contribution to the overall stand-level complexity. [ABSTRACT FROM AUTHOR]

Individual tree architecture and the composition of tree species play a vital role for many ecosystem functions and services provided by a forest, such as timber value, habitat diversity, and ecosystem resilience. However, knowledge is limited when it comes to understanding how tree architecture changes in response to competition. Using 3D-laser scanning data from the German Biodiversity Exploratories, we investigated the detailed three-dimensional architecture of 24 beech (Fagus sylvatica L.) trees that grew under different levels of competition pressure. We created detailed quantitative structure models (QSMs) for all study trees to describe their branching architecture. Furthermore, structural complexity and architectural self-similarity were measured using the box-dimension approach from fractal analysis. Relating these measures to the strength of competition, the trees are exposed to reveal strong responses for a wide range of tree architectural measures indicating that competition strongly changes the branching architecture of trees. The strongest response to competition (rho = −0.78) was observed for a new measure introduced here, the intercept of the regression used to determine the box-dimension. This measure was discovered as an integrating descriptor of the size of the complexity-bearing part of the tree, namely the crown, and proven to be even more sensitive to competition than the box-dimension itself. Future studies may use fractal analysis to investigate and quantify the response of tree individuals to competition. [ABSTRACT FROM AUTHOR]