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Author Biographies
Ernest W Mauya
Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, Ås, Norway
Wilson A Mugasha
Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, Ås, Norway
Eliakimu Zahabu
Department of Forest Mensuration and Management, Sokoine University of Agriculture, Morogoro, Tanzania
Ole M Bollandsås
Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, Ås, Norway
Tron Eid
Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, Ås, Norway
Main Article Content
Models for estimation of tree volume in the miombo woodlands of Tanzania
Ernest W Mauya
Wilson A Mugasha
Eliakimu Zahabu
Ole M Bollandsås
Tron Eid
Abstract
Volume of trees is an important parameter in forest management, but only volume models with limited geographical and tree size coverage have previously been developed for Tanzanian miombo woodlands. This study developed models for estimating total, merchantable stem and branches volume applicable for the entire miombo woodlands of Tanzania. We used data from 158 destructively sampled trees, including 55 tree species collected from wide geographical and biophysical ranges. We developed general and site-specific models with diameter at breast height only as the independent variable, together with models with both diameter at breast height and tree height. Leave-one-out cross-validation was used to evaluate the models. The total tree volume models that included diameter at breast height and tree height had appropriate predictive capabilities with relative root mean square errors (RMSEr) ranging from 30.5% to 47.6%. The RMSEr for total tree volume models with diameter at breast height only ranged from 39.9% to 48.0%. The site-specific models had slightly lower RMSEr values relative to the general models. The relative mean prediction error of the general total tree volume model with diameter at breast height and tree height was lower (0.6%) than those of the previously developed models (−30.7% to 31.2%). Based on the evaluations, we recommend the general total tree models to be applied over a wide range of geographical and biophysical conditions in Tanzania.
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