No abstract

Background and aims Terrestrial LiDAR scanning (TLS) data are of great interest in forest ecology and management because they provide detailed 3D information on tree structure. Automated pipelines are increasingly used to process TLS data and extract various tree- and plot-level metrics. With these developments comes the risk of unknown reliability due to an absence of systematic output control. In the present study, we evaluated the estimation errors of various metrics, such as the wood volume, at the tree and plot levels for four automated pipelines. Methods We used TLS data collected from a 1-ha plot of tropical forest, from which 391 trees above 10 cm in diameter were fully processed using human assistance to obtain control data for tree- and plot-level metrics. Key results Our results showed that fully automated pipelines led to median relative errors in the quantitative structural model (QSM) volume ranging from 39% to 115% at the tree level and 10% to 134% at the 1-ha plot level. For tree-level metrics, the median error for the crown-projected area ranged from 46% to 59%, and that for the crown-hull volume varied from 72% to 88%. This result suggests that the tree isolation step is the weak link in automated pipeline methods. We further analysed how human assistance with automated pipelines can help reduce the error in the final QSM volume. At the tree scale, we found that isolating trees using human assistance reduced the error in the wood volume by a factor of ten. At the 1-ha plot scale, locating trees with human assistance reduced the error by a factor of three. Conclusions Our results suggest that in complex tropical forests, fully automated pipelines may provide relatively unreliable metrics at the tree and plot levels, but limited human assistance inputs can significantly reduce errors.

1. To fulfil their growth and reproductive functions, trees develop a threedimensional structure that is subject to both internal and external constraints. This is reflected by the unique architecture of each individual at a given time. Addressing the crown dimensions and topological structure of large tropical trees is challenging considering their complexity, size and longevity. Terrestrial laser scanning (TLS) technology offers a new opportunity for characterising and comparing these properties across a large number of individuals and species. 2. In the present study, we specifically developed topology and geometry metrics of crown architecture from TLS data and investigated how they correlated with metrics of tree and crown form, crown position and shade tolerance. 3. Fifty-nine trees belonging to 14 coexisting canopy species in semideciduous forests of Cameroon were scanned with TLS and reconstructed using quantitative structural models (QSMs). The species belonged to different shade-tolerance groups and were sampled in different crown positions. Crown-form metrics and branch topology metrics were quantified from the TLS data, and principal component analysis (PCA) was used to study how the 59 sampled trees were distributed along axes of architectural diversity. Allometric scaling parameters derived from West Brown and Enquist (WBE) metabolic theory were also quantified from the QSMs, and their correlations with the PCA axes were evaluated. 4. The results revealed that the branch topology and crown-form metrics were not correlated since similar topologies could lead to contrasting crown forms. Crown form, but not branch topology, changed with tree shade tolerance, while convergence in tree topology and towards expected WBE parameters was observed for all trees reaching dominant crown positions independent of species shade tolerance. 5. This convergence is interpreted as resulting from a liberation effect of canopy trees from side-shading constraints, leading to crown development processes through sequential reiteration.