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

Abstract

The structural complexity of the understory layer of forests or shrub layer vegetation in open shrublands affects many ecosystem functions and services provided by these ecosystems. We investigated how the basal area of the overstory layer, annual and seasonal precipitation, annual mean temperature, as well as light availability affect the structural complexity of the understory layer along a gradient from closed forests to open shrubland with only scattered trees. Using terrestrial laser scanning data and the understory complexity index (UCI), we measured the structural complexity of sites across a wide range of precipitation and temperature, also covering a gradient in light availability and basal area. We found significant relationships between the UCI and tree basal area as well as canopy openness. Structural equation models (SEMs) confirmed significant direct effects of seasonal precipitation on the UCI without mediation through basal area or canopy openness. However, annual precipitation and temperature effects on the UCI are mediated through canopy openness and basal area, respectively. Understory complexity is, despite clear dependencies on the available light and overall stand density, significantly and directly driven by climatic parameters, particularly the amount of precipitation during the driest month.

Exploring the Potential of Mobile Laser Scanning to Quantify Forest Structural Complexity

“…The remaining task, the integration of the spatial data into tangible indices, has been addressed in the last years. For example, canopy structural complexity, expressed as rugosity (Hardiman et al, 2011;Atkins et al, 2018), overall stand structural complexity, expressed as stand structural complexity index (SSCI; Ehbrecht et al, 2017) or boxdimension (D b ; Seidel, 2018), as well as understory structural complexity, expressed by the understory complexity index (UCI; Willim et al, 2019;Seidel et al, 2021) were all derived from 3D forest data and all integrate thousands to millions of measurements of spatial structures into a single number. While some of the new indices fundamentally rely on the use of specific instruments or measurement platforms, the box-dimension can be determined using data from any kind of measurement device or platforms, as long as it results in a 3D point cloud of the object or scene of interest (Seidel, 2018).…”

Silviculture of South American temperate native forests

“…3-77%) for N. alpina (Soto et al 2017). The topsoil scarification should be practised carefully, since bamboos provide soil protection, functional diversity and complexity to the forest understories (Soto & Puettmann 2018, Seidel et al 2021. Figure 8 summarises the main findings of these works in terms of the regeneration niche of N. alpina and N. dombeyi.…”

Automatic Assessment of Individual Stem Shape Parameters in Forest Stands from TLS Point Clouds: Application in Pinus pinaster

“…The comparison was done both visually and numerically. Numerical analysis was carried out by analyzing the statistics of both variables and through a Tukey-Kramer test [34,35] that compares the individual means from an analysis of variance of several samples with different characteristics.…”