Patterns and Drivers of 3D Space Exploration in European Tree Species

Trees in forests plastically explore three-dimensional space in response to competition and other environmental drivers. Above-ground space exploration involves several mechanisms, including stem leaning and bending, differential growth and survival of lateral branches, and vertical growth. These mechanisms collectively shape tree morphology and influence a multitude of ecological processes at the tree and stand level, such as resource acquisition, competitive dynamics, and microclimate. Species may differ in their level of plasticity and in general space exploration patterns, i.e. the mechanisms shaping their morphology. For example, European beech exhibits strong plasticity via lateral branch growth, whereas other species like Scots Pine may rely more on stem leaning.

Although advances in Terrestrial Laser Scanning (TLS) now enable detailed and accurate assessments of tree structural information, comprehensive studies that consider several space exploration mechanisms in a three-dimensional context remain scarce. Consequently, species-specific space exploration patterns and their drivers remain poorly understood. Therefore, enhanced descriptions of tree space exploration could support more accurate representations of tree structure in forest growth models. Further, increased knowledge of space exploration patterns could inform silvicultural interventions, such as planting patterns or thinning, to promote desired stand structures and boost productivity, habitat diversity, and forest resilience.

Within this research, we apply TLS to capture detailed three-dimensional data on the stem and crown structure of sample trees from four major European tree species. Based on this data, we address the following research questions: (1) What are species-specific patterns of space exploration? and (2) How do intrinsic and environmental drivers impact the space exploration patterns? We analyse several sites in Central Europe with different dominant species, namely European beech, Norway spruce, Scots pine, and Douglas fir. We compute various space exploration metrics describing stem leaning and bending, crown size and shape, crown shyness, and tree slenderness. We apply principal component analysis to identify species-specific space exploration patterns. Further, we conduct regression modelling and circular statistics to assess the influence of drivers, such as competition, slope, and tree size.  

The findings of this study offer valuable insights on species-specific space exploration patterns. Thereby, we improve our understanding of how tree and stand structures develop, and how different species deploy distinct mechanisms to optimize light capture, enhance mechanical stability, and compete with neighbours. These insights shed light on niche differentiation and coexistence in diverse forests.