Journal
JOURNAL OF ARID ENVIRONMENTS
Volume 180, Issue -, Pages -Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jaridenv.2020.104205
Keywords
Senegalia; Vachellia, Seemingly Unrelated Regressions (SUR); crown area; carbon stock; savanna
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Funding
- UNDESERT (Understanding and Combating Desertification to Mitigate its Impact on Ecosystem Services) (EU-FP7) [243906]
- BK21 PLUS Program (Brain Korea 21 Program for Leading Universities)
- TWAS-DFG
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Reliable estimates of carbon stocks for drylands are constrained by a limited number of biomass models for predicting accurately the biomass of dominant tree and shrub species. In this study, 119 trees with a diameter at breast height (dbh) between 3.82 and 45.48 cm were destructively sampled to evaluate aboveground biomass (AGB) allocation and prediction for four dryland species (Senegalia dudgeonii, Senegalia gourmaensis, Vachellia nilotica and Vachellia torahs) commonly found in the Sudanian and Sahelian zones of Burkina Faso. Biomass allocation to leaf, branch and stem was examined using a classmometric analysis. Allometric equations relating biomass to dbh alone, and to dbh in combination with height and/or crown area were developed with and without consideration of the additivity property. Branches stored the largest (up to 90%) proportion of AGB. For three of the species, the branch mass fraction increased with increasing tree size at the expense of stem and leaf mass fractions. The statistical evaluations of the selected additive and non-additive models were satisfactory with no severe deficiencies. Diagnostics of model performance revealed that non-additive models performed better than additive models. The biomass models developed can be used for improved quantification of carbon stock and dynamics in dry savanna ecosystems.
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