Tools to accurately estimate tree volume and biomass are scarce for most forest types in East Africa, including Tanzania. Based on a sample of 142 trees and 57 shrubs from a 6,065 ha area of dry miombo woodland in Iringa rural district in Tanzania, regression models were developed for volume and biomass of three important species, Brachystegia spiciformis Benth. ( ), Combretum molle G. Don ( ), and Dalbergia arbutifolia Baker ( ) separately, and for broader samples of trees (28 species, ), shrubs (16 species, ), and trees and shrubs combined (44 species, ). Applied independent variables were log-transformed diameter, height, and wood basic density, and in each case a range of different models were tested. The general tendency among the final models is that the fit improved when height and wood basic density were included. Also the precision and accuracy of the predictions tended to increase from general to species-specific models. Except for a few volume and biomass models developed for shrubs, all models had values of 96–99%. Thus, the models appear robust and should be applicable to forests with similar site conditions, species, and diameter ranges. 1. Introduction Standing volume and aboveground biomass (AGB) are the two main measures of forest stocking that are typically considered within the framework of sustainable forest management and for carbon accounting purposes [1, 2]. Accurate estimation of tree volume and forest biomass is not only crucial for assessing expected yields from commercial and subsistence harvesting. It is also important for carbon storage assessment in relation to global climate change mitigation measures [3, 4]. For this purpose, forest biomass can be applied to estimate carbon stocks and carbon fluxes when measured repeatedly, thus providing means for estimating the amount of carbon dioxide released into or removed from the atmosphere. However, direct measurement of volume and AGB is time consuming, costly, and usually destructive by nature. Therefore, the general practice is to estimate volume and AGB from tree dendrometric characteristics such as diameter and height, using established, general, or site-specific allometric equations [1, 3, 5, 6]. The selection of an appropriate allometric equation is a key element in the accurate estimation of forest yield and stand productivity as well as carbon stocks and changes in stocks [7, 8]. Unfortunately, such equations often produce biased results when applied outside the forest area or region where they were developed. If high accuracy is required for quantification and
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