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International Journal of Forestry Research
Volume 2016, Article ID 8076271, 13 pages
Research Article

Allometric Models for Estimating Tree Volume and Aboveground Biomass in Lowland Forests of Tanzania

1Tanzania Forestry Research Institute (TAFORI), P.O. Box 1854, Morogoro, Tanzania
2Department of Forest Biology, Sokoine University of Agriculture, P.O. Box 3010, Morogoro, Tanzania
3Department of Forest Mensuration and Management, Sokoine University of Agriculture, P.O. Box 3013, Morogoro, Tanzania
4Department of Forest Engineering, Sokoine University of Agriculture, P.O. Box 3012, Morogoro, Tanzania
5UN-REDD Programme, Food and Agriculture Organization of the United Nations (FAO), Viale delle Terme di Caracalla, 00153 Rome, Italy
6Forest Training Institute, Olmotonyi, P.O. Box 943, Arusha, Tanzania

Received 24 July 2015; Revised 7 December 2015; Accepted 17 December 2015

Academic Editor: Timothy Martin

Copyright © 2016 Wilson Ancelm Mugasha et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Models to assist management of lowland forests in Tanzania are in most cases lacking. Using a sample of 60 trees which were destructively harvested from both dry and wet lowland forests of Dindili in Morogoro Region (30 trees) and Rondo in Lindi Region (30 trees), respectively, this study developed site specific and general models for estimating total tree volume and aboveground biomass. Specifically the study developed (i) height-diameter (ht-dbh) models for trees found in the two sites, (ii) total, merchantable, and branches volume models, and (iii) total and sectional aboveground biomass models of trees found in the two study sites. The findings show that site specific ht-dbh model appears to be suitable in estimating tree height since the tree allometry was found to differ significantly between studied forests. The developed general volume models yielded unbiased mean prediction error and hence can adequately be applied to estimate tree volume in dry and wet lowland forests in Tanzania. General aboveground biomass model appears to yield biased estimates; hence, it is not suitable when accurate results are required. In this case, site specific biomass allometric models are recommended. Biomass allometric models which include basic wood density are highly recommended for improved estimates accuracy when such information is available.