Abstract
Aboveground tree architecture is neither fully deterministic nor random. It is likely the result of mechanisms that balance static requirements and light‐capturing efficiency. Here, we used terrestrial laser scanning data to investigate the relationship between tree architecture, here addressed using the box‐dimension (D b), and the architectural benefit‐to‐cost ratio, the light availability, and the growth of trees. We detected a clear relationship between D b and the benefit‐to‐cost ratio for the tested three temperate forest tree species (Fagus sylvatica L., Fraxinus excelsior L., and Acer pseudoplatanus L.). In addition, we could also show that D b is positively related to the growth performance of several tropical tree species. Finally, we observed a negative relationship between the strength of competition enforced on red oak (Quercus rubra L.) trees and their D b. We therefore argue that D b is a meaningful and integrative measure that describes the structural complexity of the aboveground compartments of a plant as well as its relation to structural efficiency (benefit‐to‐cost ratio), productivity, and growing conditions (competition or availability of light).
Highlights
We detected a clear relationship between determined the aboveground box‐dimension (Db) and the benefit‐to‐cost ratio for the tested three temperate forest tree species (Fagus sylvatica L., Fraxinus excelsior L., and Acer pseudoplatanus L.)
We could show that Db is positively related to the growth performance of several tropical tree species
We detected a clear relationship between Db and the benefit‐to‐cost ratio of trees, here approximated from terrestrial laser scanning data using the ratio between the crown surface area and the volume of the woody skeleton
Summary
The ability of trees to adjust their shape to the envi‐ ronmental conditions, known as adaptive geometry (Borchert & Slade, 1981; Horn, 1971), is likely a mechanism that balances static requirements (tree stability) and light‐capturing efficiency (Honda & Fisher, 1978; Kuuluvainen, 1992; Valladares & Niinemets, 2007). We argue that fractal analysis can be of great help to gain a better understanding of individual tree shape This was already suggested by Mandelbrot (1977) and a small number of studies that focused on the issue (e.g., Zeide & Pfeifer, 1991), but only with the recent availability of 3D data on tree architecture, it became possi‐ ble to exploit the methodology.
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