Allometric prediction of above-ground biomass of eleven woody tree species in the Sudanian savanna-woodland of West Africa

Sawadogo Louis, Savadogo Patrice, Tiveau Didier, Djibril Dayamba Sidzabda, Zida Didier, Nouvellet Yves, Oden Per Christer, Guinko Sita. 2010. Allometric prediction of above-ground biomass of eleven woody tree species in the Sudanian savanna-woodland of West Africa. Journal of Forestry Research, 21 (4) : pp. 475-481.

Journal article ; Article de revue à comité de lecture
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Abstract : Allometric models are necessary for estimating biomass in terrestrial ecosystems. Generalized allometric relationship exists for many tropical trees, but species- and region-specific models are often lacking. We developed species-specific allometric models to predict aboveground biomass for 11 native tree species of the Sudanian savannawoodlands. Diameters at the base and at breast height, with species means ranging respectively from 11 to 28 cm and 9 to 19 cm, and the height of the trees were used as predictor variables. Sampled trees spanned a wide range of sizes including the largest sizes these species can reach. As a response variable, the biomass of the trees was obtained through destructive sampling of 4 754 trees during wood harvesting. We used a stepwise multiple regression analysis with backward elimination procedure to develop models separately predicting, total biomass of the trees, stem biomass, and biomass of branches and twigs. All speciesspecific regression models relating biomass with measured tree dimensions were highly significant (p < 0.001). The biomass of branches and twigs was less predictable compared to stem biomass and total biomass, although their models required fewer predictors and predictor interactions. The best-fit equations for total above-ground biomass and stem biomass had R2 > 0.70, except for the Acacia species; for branches including twig biomass, R2-values varied from 0.749 for Anogeissus leiocarpa to 0.183 for Acacia macrostachya. The use of these equations in estimating available biomass will avoid destructive sampling, and aid in planning for sustainable use of these species. (Résumé d'auteur)

Mots-clés Agrovoc : Biomasse, Savane, Mesure, Organisme indigène, Modélisation environnementale, gestion des ressources naturelles, Zone tropicale, Arbre forestier, Écosystème, Allométrie, Modèle mathématique, Modèle de simulation, Bois énergie

Mots-clés géographiques Agrovoc : Soudan

Classification Agris : K10 - Forestry production
U10 - Computer science, mathematics and statistics
P06 - Renewable energy resources

Champ stratégique Cirad : Axe 1 (2005-2013) - Intensification écologique

Auteurs et affiliations

  • Sawadogo Louis, INERA (BFA)
  • Savadogo Patrice, Swedish University of Agricultural Sciences (SWE)
  • Tiveau Didier, Ambassade (Suède) (COD)
  • Djibril Dayamba Sidzabda, Swedish University of Agricultural Sciences (SWE)
  • Zida Didier, INERA (BFA)
  • Nouvellet Yves, CIRAD-ES-UPR BSef (FRA)
  • Oden Per Christer, Swedish University of Agricultural Sciences (SWE)
  • Guinko Sita, Université de Ouagadougou (BFA)

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