Abstract
Key message: Relative biomass of tree compartments is dependent on plant size and stand density, with stand density being an important predictor, especially for belowground biomass and at high stand densities. Abstract: Estimation of biomass production is an important issue against the background of climate change and carbon storage. Even though many studies investigated the biomass productivity of trees or single compartments, only few considered the belowground biomass. Further, there is a lack of studies focusing on young trees and considering further influencing factors such as the prevailing stand density. In the present study, young Quercus robur trees were sampled on Nelder trials, which comprise different stand densities, on four European sites differing in climatic conditions. Besides the estimation of logarithmically transformed power equations, Dirichlet regressions were applied for deriving biomass functions for the single compartments leaves, branches, stem and roots. Thereby, the dependence of total and compartment biomass allocation on diameter at root collar (d0), tree height and stand density is tested. The results show that besides d0, the local Stand Density Index (SDIl) is an important predictor for biomass. Especially, the belowground biomass shows a significant relation to the SDIl, which is less the case for the aboveground biomass. Not considering the SDIl leads to an overestimation of the biomass productivity, especially when the stand density is high. Furthermore, the results show that the belowground biomass is lower than the aboveground biomass, but with 50–80% of the aboveground biomass still of considerable size. This indicates the importance of including stand characteristics when estimating above- and belowground tree biomass in future studies.
| Original language | English |
|---|---|
| Pages (from-to) | 1811-1826 |
| Number of pages | 16 |
| Journal | Trees - Structure and Function |
| Volume | 31 |
| Issue number | 6 |
| DOIs | |
| State | Published - 1 Dec 2017 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 13 Climate Action
Keywords
- Biomass compartments
- Dirichlet regression
- Nelder trials
- Quercus robur
- Root biomass
- Tree allometry
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