Advanced Aboveground Spatial Analysis as Proxy for the Competitive Environment Affecting Sapling Development

Abstract

Tree saplings are exposed to a competitive growth environment in which resources are limited and the ability to adapt determines general vitality and specific growth performance. In this study we analyzed the aboveground spatial neighborhood of oak [ Quercus petraea (Matt.) Liebl.] and beech ( Fagus sylvatica L.) saplings growing in Germany, by using hemispherical photography and terrestrial laser scanning as proxy for the competitive pressure saplings were exposed to. The hemispherical images were used to analyze the light availability and the three-dimensional (3D) point clouds from the laser scanning were used to assess the space and forest structure around the saplings. The aim was to increase the precision with which the biomass allocation, growth, and morphology of the saplings could be predicted by including more detailed information of their environment. The predictive strength of the models was especially increased through direct neighborhood variables (e.g., relative space filling), next to the light availability being the most important predictor variable. The biomass allocation patterns within the more light demanding oak were strongly driven by the space availability around the saplings. Diameter and height growth variables of both species reacted significantly to changes in light availability, and partly also to the neighborhood variables. The leaf morphology [as leaf-area ratio (LAR)] was also driven by light availability and decreased with increasing light availability. However, the branch morphology (as mean branch weight) could not be explained for oak and the model outcome for beech was hard to interpret. The results could show that individuals of the same species perform differently under constant light conditions but differing neighborhoods. Assessing the neighborhood of trees with highly precise measurement devices, like terrestrial laser scanners, proved to be useful. However, the primary response to a dense neighborhood seemed to be coping with a reduction of the lateral light availability aboveground, rather than responding to an increase of competition belowground. The results suggest continuing efforts to increase the precision with which plant environments can be described through innovative and efficient methods, like terrestrial laser scanning.

On the knowns and unknowns of natural regeneration of silviculturally managed sessile oak (Quercus petraea (Matt.) Liebl.) forests—a literature review

“…The adjustment of light conditions to achieve the desired tree regeneration is a central aspect of silvicultural systems (Diaci et al 2008;Röhrig et al 2006). In addition to the direct effects of light on young trees, indirect influences such as the effect on the establishment and development of competing vegetation are also very important (Annighöfer et al 2019;Wagner et al 2011). Higher light levels, as found in larger canopy openings, may create growing conditions that favour other ground flora species over the one desired by management.…”

“…Wagner 1999). For example, young sessile oak saplings on a sandy site in northwest Germany appeared to be less sensitive to low overstorey light levels than to reductions in lateral light availability caused by the direct neighbourhood vegetation (Annighöfer et al 2019). There are only few studies in which reduction in light levels for oak regeneration through vegetation of competing species has been quantified (e.g.…”

Tree Regeneration Characteristics in Limestone Forests of the Cat Ba National Park, Vietnam

“…We built linear mixed effect models with the ve ratios as response variables, the PCs as xed effects and the study area as random effect using the function "lme()" [117,118]. The rst model was built with all three PCs, then backward elimination of PCs was done using a p-value at a 5% level of signi cance [50]. From these we selected the best t model using the "model.sl()" function in "MuMIn" package [119].…”

“…The regeneration layer is known to be in uenced by overstory composition [48,49], abiotic factors [9,50], and biotic factors [4]. Here we investigated natural forest regeneration in Cat Ba National Park (CBNP), located on limestone islands in Vietnam [51][52][53].…”

Quantifying Understory Complexity in Unmanaged Forests Using TLS and Identifying Some of Its Major Drivers

“…Particularly, the amount of light passing through the crowns of overstory trees was intensively studied as a key driver of regeneration and understory layer development [16][17][18]. However, other drivers of understory layer development have also been investigated, such as soil nitrogen and nutrient availability [17,19], competition for growing space [20], soil water content [21], and effects of fertilization [22], to name a few examples.…”