Understanding global trends in 3D tree architecture

Abstract:

Quantifying the drivers of individual tree architecture in broad (e.g. climatic) and local (e.g. competition) terms is critical for accurately estimating productivity, competition, global carbon stocks, forest growth and sequestration potential, and fundamental principles of ecological theory (e.g. Metabolic Scaling Theory) – all of which directly impact mechanistic forest ecosystem models.

Recent advances in close-range remote sensing have brought about a revolution of three-dimensional tree-level LiDAR measurements using terrestrial laser scanning (TLS), but the inherently local nature of TLS limits scalability for large-scale ecological questions. In recent years, the number of TLS studies capturing forest structure have exploded, covering a wide range of ecosystems and forest types. Leveraging a recently released Global TLS Metadata Database that brings together years of past TLS campaigns and thousands of tree models, we analyze variations in tree architecture at a global scale with a suite of site-specific and climatic variables.

The Global TLS Metadata Database enables previously unprecedented analyses of single-tree architecture at a global scale. The current set of TLS acquisitions cover 10 biomes with more than 1000 plots, but more data are needed to explain architectural variability within individual regions. Community involvement and contributions will make this database capable of filling gaps in our current spatial extent, enabling more detailed analyses. Our results highlight potential avenues for improving understanding of forest function through more robust allometric relationships, global remote sensing calibration and validation, and ecological models.