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Allometric equations from a non-destructive approach for biomass prediction in natural forest and plantation in West Africa

Author:
Kora, SA Hamzath, Guendehou, GH Sabin, Goussanou, Cédric A, Assogbadjo, Achille E, Sinsin, Brice
Source:
Southern forests 2019 v.81 no.2 pp. 111-122
ISSN:
2070-2639
Subject:
Acacia auriculiformis, allometry, biomass, equations, forest ecosystems, forests, models, prediction, statistical analysis, trees, wood, Benin
Abstract:
Allometric equations are required for a rapid estimation of commercial timber volume and forest biomass stocks. In order to preserve the forest ecosystem, this study applied a non-destructive sampling approach to measure biophysical properties of living trees. From these measurements, volume and biomass models were developed for 11 dominant tree species in a semi-deciduous natural forest and for Acacia auriculiformis in a plantation located in southern Benin. The observations were combined to develop also generic models applicable to non-dominant tree species. Wood samples of the tree species were collected with an increment borer and analysed in the laboratory to determine species-specific wood densities. The sample size was composed of 243 trees in natural forest and 21 trees in plantation. The measurements were conducted in 30 plots of 50 m × 50 m. The graphical assessment of correlation between model outputs (biomass and volume) and variables (diameter and height) and the statistical analysis confirmed that the logarithmic model with two variables had the best predictions. The assessment also confirmed that the model using diameter only as a variable had good predictions when observations on height were unavailable. The comparative analysis of model predictions showed that the generic model in this study over-estimated biomass by up to 74.80% for certain species and under-estimated biomass by 21.18% for other species. The study shows that there are no statistically significant differences between the wood densities in this research and that published in previous studies.
Agid:
6431781