Same Viewpoint Different Perspectives—A Comparison of Expert Ratings with a TLS Derived Forest Stand Structural Complexity Index

Abstract

Forests are one of the most important terrestrial ecosystems for the protection of biodiversity, but at the same time they are under heavy production pressures. In many cases, management optimized for timber production leads to a simplification of forest structures, which is associated with species loss. In recent decades, the concept of retention forestry has been implemented in many parts of the world to mitigate this loss, by increasing structure in managed stands. Although this concept is widely adapted, our understanding what forest structure is and how to reliably measure and quantify it is still lacking. Thus, more insights into the assessment of biodiversity-relevant structures are needed, when aiming to implement retention practices in forest management to reach ambitious conservation goals. In this study we compare expert ratings on forest structural richness with a modern light detection and ranging (LiDAR) -based index, based on 52 research sites, where terrestrial laser scanning (TLS) data and 360° photos have been taken. Using an online survey (n = 444) with interactive 360° panoramic image viewers, we sought to investigate expert opinions on forest structure and learn to what degree measures of structure from terrestrial laser scans mirror experts’ estimates. We found that the experts’ ratings have large standard deviance and therefore little agreement. Nevertheless, when averaging the large number of participants, they distinguish stands according to their structural richness significantly. The stand structural complexity index (SSCI) was computed for each site from the LiDAR scan data, and this was shown to reflect some of the variation of expert ratings (p = 0.02). Together with covariates describing participants’ personal background, image properties and terrain variables, we reached a conditional R2 of 0.44 using a linear mixed effect model. The education of the participants had no influence on their ratings, but practical experience showed a clear effect. Because the SSCI and expert opinion align to a significant degree, we conclude that the SSCI is a valuable tool to support forest managers in the selection of retention patches.

On the structural complexity of central European agroforestry systems: a quantitative assessment using terrestrial laser scanning in single-scan mode

“…The index proved to be valuable in various earlier studies. For example, it was successfully used to quantify impacts of forest management on forest structure (Ehbrecht et al 2017;Stiers et al 2018), to quantify the effect of mixture on forest structure (Juchheim et al 2020), to assess tree microhabitats (Frey et al 2020), it was closely related to the forest microclimate (Ehbrecht et al 2019), and it was even a good predictor of ant species richness (Greve et al 2018) or conventional expert ratings on stand structural complexity from visual assessment (Frey et al 2019). In a recent study focusing on primary forests across the globe, the index was used to relate the stand structural complexity of forests to the climatic conditions of different biomes (Ehbrecht et al 2021) and it was shown to correlate to conventional measures of structural heterogeneity (Ehbrecht et al 2017).…”

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

“…Another holistic measure of complexity, the box-dimension, was shown to be related to the degree of crown overlapping in a stand, as well as to the number of trees present, the overall space occupation and finally also to central tendencies of several architectural characteristics of the trees in a stand [36,39]. Furthermore, holistic measures such as the SSCI aligned with expert ratings of structural complexity [40]. These new tools allow one to directly investigate the drivers of vegetation complexity, rather than using surrogates to estimate it.…”

“…At each site, we placed between three and nine sample plots, each consisting of five measurement positions for scanning with a spatial arrangement resembling a five on a dice (quadratic layout with an additional central position, see Figure 2) as introduced in [40] for a similar task. Avoiding hiking trails, as well as topographical issues such as canyons, steep slopes, or rivers, we selected the location of the plots by beginning at a random starting point without such issues in the area of interest and defined it as the center of the first plot.…”

Evaluating the effectiveness of retention forestry to enhance biodiversity in production forests of Central Europe using an interdisciplinary, multi‐scale approach

“…Based on meta‐analyses, ConFoBi researchers confirmed that crown‐damaged trees improve nesting opportunities for cavity‐nesting birds (Gutzat & Dormann, ) and that woodpeckers select cavitiesby relative rather than absolute tree size (Basile, Mikusinski, & Storch, ), but found that bird guilds are affected differently by forestry measures including retention, according to their life history, biome, and forest type (Basile, Mikusinski, & Storch, ). A joint study by social and remote‐sensing scientists of ConFoBi found expert ratings of forest structure, despite large individual bias, were on average significantly related to technical structural complexity indices based on terrestrial laser scanning (Frey, Joa, Schraml, & Koch, ), and a review concluded that local ecological knowledge holds significant promise for integrating conservation objectives into forest management under changing environmental conditions (Joa, Winkel, & Primmer, ; Joa & Schraml, ). Analyses of the opportunity costs arising from retention forestry suggest that conservation practices, such as habitat networks of deadwood islands, will only marginally impact profitability when conservation and production goals are balanced through suitable planning tools (Augustynczik, Yousefpour, Rodriguez, & Hanewinkel, ).…”