Allometric Models for Estimating Tree Volume and Aboveground Biomass in Lowland Forests of Tanzania
2016
Mugasha, Wilson Ancelm(Tanzania Forestry Research Institute (TAFORI), P.O. Box 1854) | Mwakalukwa, Ezekiel Edward(Department of Forest Biology, Sokoine University of Agriculture) | Luoga, Emannuel(Department of Forest Mensuration and Management, Sokoine University of Agriculture) | Malimbwi, Rogers Ernest(Department of Forest Mensuration and Management, Sokoine University of Agriculture) | Zahabu, Eliakimu(Department of Forest Mensuration and Management, Sokoine University of Agriculture) | Silayo, Dos Santos(Department of Forest Engineering, Sokoine University of Agriculture) | Sola, Gael(UN-REDD Programme, Food and Agriculture Organization of the United Nations (FAO)) | Crete, Philippe(UN-REDD Programme, Food and Agriculture Organization of the United Nations (FAO)) | Henry, Matieu(UN-REDD Programme, Food and Agriculture Organization of the United Nations (FAO)) | Kashindye, Almas(Forest Training Institute, Olmotonyi)
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.
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