As a consequence of climate change, the occurrence of severe droughts is increasing in several parts of the world (Trenberth et al. 2014; Settele et al. 2015). While forest systems are susceptible to a variety of severe climatic conditions, drought and its concomitant disruptions have the largest impact worldwide (Reichstein et al. 2013). It is the most common stressor impacting the forest carbon balance globally, potentially generating a sharp decline in net primary productivity at regional and global levels (Ciais et al. 2005; Lewis et al. 2011). There has been increasing concern that warmer temperatures may cause more extended and intense droughts, highlighting the need for accurate projections of drought impacts on forest ecosystems (Rousi et al. 2022). In addition, studies reveal that drought-related mass tree death is not limited to drier locations (Anderegg et al. 2012; Hammond et al. 2022). It has been reported in a range of forest biomes, including cold temperate (Nardini et al. 2013; Schuldt et al. 2020) and tropical forests (Rowland et al. 2018). As droughts severely impact tree structure and function (Nepstad et al. 2007; Phillips et al. 2010), the potential of trees to adapt to dry climates will determine the future state of forests in the face of climate change (Bittencourt et al. 2020). Therefore, it is of paramount importance to understand the relationship between tree architecture, forest structure and drought tolerance.
The structure and function of a forest ecosystem are ultimately tied to the species composition and the structures of the individual trees (West et al. 2009; Seidel et al. 2019a). Various ecological functions and services offered by a forest, such as wood value (Ishii et al. 2004), recreational value (Ribe et al. 2009), or ecosystem resilience (Neill and Puettmann 2013) depend on the structural characteristics and the species composition in the stand.
Tree structure and form are not the results of stochastic growth (Valladares and Niinemets 2007). They are, in fact, the result of the interaction between the genetic growth plan and the biotic and abiotic environment (Scorza et al. 2002; Busov et al. 2008). Environmental factors like the wind (Watt et al. 2005), sunlight angle (Kuuluvainen 1992), seed dispersal strategy (Dorji et al. 2021), water availability (Niinemets and Kull 1995), and competition (Dorji et al. 2019) determine the final shape of a tree. The plasticity of tree geometry in response to environmental agents was considered to be the outcome of an individual’s drive to maximize strength in a certain area (Borchert and Slade 1981), such as reproductive potential or sunlight absorption (Hollender and Dardick 2015).
The study of 3D tree structure and form was shown to be of importance for a variety of disciplines, such as tree phylogenetics, remote sensing of forest landscapes, ecosystem modeling, and carbon stock computation (Chave et al. 2005; Arseniou et al. 2021a, b). Despite this great importance, the three-dimensional quantification of tree architecture was a challenging task in the past (destructive, laborious, and time-consuming). So far, the assessment has been limited to only small trees (Moore et al. 2008; Bentley et al. 2013). Therefore, a lack of sufficient data has hampered the development and testing of theory, specifically linking tree structures with their physiological role and mechanism (Malhi et al. 2018).
The arrival of Laser scanning technology has transformed the way we perceive trees and quantify their structures (Gonzalez de Tanago et al. 2018). Besides conventional tree size attributes, TLS is also used to derive tree branching patterns (branch angles, lengths, volumes) with precision levels exceeding those of leading international allometric models (Liang et al. 2018; Demol et al. 2022). Thus, this has provided an avenue to analyze and understand how tree architecture and forest structure change in response to various factors like competition, drought, light availability and utilization (e.g., Dassot et al. 2011).
Our grasp of how plants adapt to dry spells and how drought-induced tree mortality occurs depends on understanding tree hydraulic traits (Choat et al. 2018). As one of the most commonly reported metrics of xylem vulnerability to hydraulic failure (Anderegg et al. 2016), hydraulic safety is often quantified by the water potential at which 12%, 50% and 88% loss of hydraulic conductivity occur. Embolisms form when water potentials in conduits drop to levels that promote embolism formation (Tyree and Zimmermann 2002). As a result, tree dieback seems predictable by hydraulic thresholds related to xylem dysfunction (Britton et al. 2022; Hajek et al. 2022). Therefore, plant hydraulic characteristics play an important role in drought survivability and carbon fluxes (Chen et al. 2021; McDowell et al. 2022).
Since water is conducted throughout the whole architectural system of the tree, fractal analysis offers a unique approach to addressing it. Benoit Mandelbrot, in the 1970s, developed the concept of fractal geometry to characterize and explain the complexity of a wide variety of objects based on how they fill space (Mandelbrot 1977). With the advances in 3D modeling of tree architecture, the application of fractal geometry has become possible in a comprehensive analysis of tree architecture (Seidel 2018; Dorji et al. 2021). Several “fractal”-based theories have been propounded to comprehend tree structure and function, e.g., pipe-model theory (Valentine 1985) and metabolic scaling theory (West et al. 1997; Martin-Ducup et al. 2020). The fractal-like geometry of trees, according to these concepts, is a direct representation of both intrinsic and malleable morphological features that influence tree development and survival. Furthermore, fractal approaches are increasingly used to analyze nonlinear, unevenly structured elements, including landscape-level ecological phenomena (Hasting and Sugihara 1993; Halley et al. 2004). Today, the box-dimension (Db) is a fractal analysis metric readily available to quantify the structural complexity of trees (e.g., Arseniou et al. 2021a; Saarinen et al. 2021).
We employed the box-dimension paradigm in this research to quantify the overall tree architectural complexity. We assessed how this complexity relates to the hydraulic thresholds of xylem safety across a range of temperate tree species. Specifically, we used detailed tree architectural measures related to branching patterns (up to the 3rd order branching orders) to address the following hypotheses: 1) The box-dimension (Db), as a proxy for the overall tree structural complexity, directly relates to the drought tolerance represented by xylem pressure at loss of hydraulic conductivity. 2) Branch angles and lengths of the tree species have a significant relationship with xylem safety since the branching pattern directly relates to the hydraulic network. 3) Tree structural complexity (Db) is more closely related to xylem safety than height and DBH since Db is a holistic measure that incorporates overall tree architectural patterns and networks rather than selected single characteristics.