Should tree biomass allometry be restricted to power models?

Picard Nicolas, Rutishauser Ervan, Ploton Pierre, Ngomanda Alfred, Henry Matieu. 2015. Should tree biomass allometry be restricted to power models?. Forest Ecology and Management, 353 : pp. 156-163.

Journal article ; Article de revue à facteur d'impact
[img] Published version - Anglais
Access restricted to CIRAD agents
Use under authorization by the author or CIRAD.

Télécharger (406kB) | Request a copy

Quartile : Q1, Sujet : FORESTRY

Abstract : The increasing number of model types that are used to predict tree biomass from diameter, height and wood density has brought questioning about the biological relevance of complex allometries (i.e. non-power models). Statistical issues such as collinearity among predictors and unreliable coefficient estimates have also been associated with complex allometric models. Using a data set of 225 trees from central Africa, we assessed the relevance of simple allometry (i.e. power model) versus complex allometry to predict tree biomass. A complex allometric model of biomass was developed based on a model of resource partition between dbh and height growths. Although being a good model for biomass prediction, the power model was outperformed by the complex allometric model. A careful examination showed that the power model could be segmented into two pieces of power models. Using tree diameter and height as separated predictors improved the biomass prediction, irrespective of the collinearity between these two predictors. A critical value of 25% for the PRSE statistic used to assess the reliability of coefficient estimates corresponded to a significance level of 10-510-5–10-410-4 and was thus unreasonably low. We conclude that growth theories should be developed to explain allometric models, but that the arbitration between these models should ultimately rely on observed data, not on theories. (Résumé d'auteur)

Mots-clés Agrovoc : forêt tropicale, Biomasse, Allométrie, Production forestière, Modèle de simulation, Méthode statistique, Croissance, Dynamique des populations, Diamètre, Densité, Mesure, Bioinformatique

Mots-clés géographiques Agrovoc : Afrique centrale

Classification Agris : K01 - Forestry - General aspects
F62 - Plant physiology - Growth and development
U10 - Computer science, mathematics and statistics

Champ stratégique Cirad : Axe 6 (2014-2018) - Sociétés, natures et territoires

Auteurs et affiliations

  • Picard Nicolas, CIRAD-ES-UPR BSef (CMR)
  • Rutishauser Ervan, Carbofor-Expert (CHE)
  • Ploton Pierre, IRD (FRA)
  • Ngomanda Alfred, IRET (GAB)
  • Henry Matieu, FAO (ITA)

Source : Cirad-Agritrop (

View Item (staff only) View Item (staff only)

[ Page générée et mise en cache le 2021-03-09 ]