From tree to stand-level structural complexity — Which properties make a forest stand complex?

Dominik Seidel, Martin Ehbrecht, P. Annighöfer, Christian Ammer

Research output: Contribution to journalArticlepeer-review

41 Scopus citations


Management for complexity has become an important paradigm for European and North American forestry. Recent advancements in data processing allow for a detailed, three-dimensional and objective quantification of structural complexity in forests based on terrestrial laser scanning data. In our study, we used such 3D data from an exemplary temperate broad-leaved forest in Thuringia, Germany, to gain insights to the relationship between tree-level structural complexity and stand-level structural complexity. From our study site, which was 80 by 80 m in extent with a total of 215 trees growing in it, we created a dataset that contained each tree as an independent point cloud. Random sample plots of varying size (10 × 10 m; 15 × 15 m; 20 × 20 m) where used to create sub-plots (sampling with replacement) and to enable for the investigation of effects of scale. Our study revealed that plot-level complexity of plots up to 20 × 20 m is largely determined by the complexity of the most complex-structured tree individual. Furthermore, a high tree complexity and variability thereof in the stand was generally beneficial to stand structural complexity. Other individual tree characteristics, such as a large crowns, were also identified to have positive effects on plot-level complexity. We conclude that management for complexity should focus on large-crowned, highly-complex tree individuals as key elements of stand structural complexity. This indicates that large and old trees may not only be of great importance as habitat trees potentially increasing biodiversity, but also due to their contribution to the overall stand-level complexity.

Original languageEnglish
Article number107699
JournalAgricultural and Forest Meteorology
StatePublished - 15 Nov 2019
Externally publishedYes


  • Forest structure
  • Fractal analysis
  • Hainich national Park
  • LiDAR
  • Scaling
  • Tree architecture


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