Abstract
Forest biomass is currently among the most important and most researched target variables in forest monitoring. The common approach of observing individual tree biomass in forest inventory is to assign the total tree biomass to the dimensionless point of the tree position. However, the tree biomass, in particular in the crown, is horizontally distributed above the crown projection area. This horizontal distribution of individual tree biomass (HBD) has not attracted much attention—but if quantified, it can improve biomass estimation and help to better represent the spatial distribution of forest fuel. In this study, we derive a first empirical model of the branch HBD for individual trees of European beech (Fagus sylvatica L.). We destructively measured 23 beech trees to derive an empirical model for the branch HBD. We then applied Terrestrial Laser Scanning (TLS) to a subset of 17 trees to test a simple point cloud metric predicting the branch HBD. We observed similarities between a branch HBD and commonly applied taper functions, which inspired our HBD model formulations. The models performed well in representing the HBD both for the measured biomass, and the TLS-based metric. Our models may be used as first approximations to the HBD of individual trees—while our methodological approach may extend to trees of different sizes and species.
Highlights
Tree biomass and carbon are important for forest management and ecological studies at all geographical scales
The goal of this study is to build a model for individual tree branch horizontal distribution of individual tree biomass (HBD) from destructively sampled data, and to evaluate the potential of a Terrestrial Laser Scanning (TLS) data metric to serve as an expedient and cheaper proxy of an otherwise costly and impractical empirical HBD
To approximate the branch HBD, we developed a new TLS-based metric that we name Standardized Composite Histogram (SCH), which is generated from the crown laser returns
Summary
Tree biomass and carbon are important for forest management and ecological studies at all geographical scales. Tree biomass is defined as the dry weight of the living mass of a tree, and cannot be determined in situ during a forest inventory. Prediction of tree biomass in operational forest inventories relies on allometric biomass models to predict tree biomass. Total above ground biomass (AGB) is the target variable in those models, and for estimating AGB per unit area this prediction is assigned to the trees position; that is, to a dimensionless point. This simplification suffices for most conventional applications, but a more realistic approach to the biomass distribution across an area of interest may be required for other purposes.
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