Sampling and Upscaling of Crown Biomass

As stated earlier sampling of foliage and branch biomass is usually done as a regression sampling process, because foliage and branches should be separated

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Fig. 3.5 Branch level regression to model branchwood and foliage biomass from branch diameter (N = 245 branches of P radiata from 11 trees; Seifert unpublished)

for biomass, nutrient/ash content, and eco-physiological calculations. However, manually separating a tree’s foliage from the twigs is a task that can only be done for small trees with reasonable effort. Therefore a regression sampling is employed to estimate branch and foliage biomass from branch diameter. Consequently, all branches of the tree are measured in diameter for upscaling later on. A sub-sample is then cut and sampled in detail in the lab or field lab. In this context it is relevant whether the branch diameters are measured perpendicularly to the main stem axis or with the axis, since the measurement perpendicular to the stem axis usually yields smaller values. The difference in branch diameter for 14-year-old Pinus radiata was about 2.0 % (estimated from on 245 branches of 11 trees; Seifert, unpublished). It is therefore important that the measurements of the sample branches and the total branches are taken consistently in the same direction. Depth of branches in the crown, defined as the distance of the branch insertion from the tip, provides an additional variable that can improve the estimation of the proportions of branchwood and foliage. Thus, the position along the stem could be a second variable to be determined in the field. After separating the foliage from the branches and drying it, a regression model is established to estimate foliage and branch biomass from branch diameter or branch circumference. A possible method to limit branch sampling is to establish the branch biomass functions based on a data set where all sample branch data of one plot are pooled. An example is presented in Fig. 3.5. This way a more robust function can be established if several trees per plot are sampled. The clustered data structure with the inherent inter — and intra-tree variability can be taken into account with mixed models (Pearce et al. 2010).

Based on this methods a dry biomass for the stem, the branches and the foliage can be obtained.