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Shabani A.O. Chamshama

Researcher at Sokoine University of Agriculture

Publications -  70
Citations -  1054

Shabani A.O. Chamshama is an academic researcher from Sokoine University of Agriculture. The author has contributed to research in topics: Diameter at breast height & Pinus patula. The author has an hindex of 15, co-authored 69 publications receiving 954 citations. Previous affiliations of Shabani A.O. Chamshama include University of Dar es Salaam.

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Allometric models for prediction of above- and belowground biomass of trees in the miombo woodlands of Tanzania

TL;DR: In this paper, the authors developed above and belowground allometric general and site-specific models for trees in miombo woodland in Tanzania and compared the results with previously developed models and showed that these models can probably also be applied for miombo woodlands elsewhere in southeastern Africa if not used beyond the tree size range of the model data.
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Stand Biomass and Volume Estimation for Miombo Woodlands at Kitulangalo, Morogoro, Tanzania

TL;DR: Tree species composition and regeneration status revealed that though disturbed, the public land species composition is not different from the other two strata and the developed volume and biomass models are recommended to be used for the miombo woodlands at Kitulangalo area.
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Competition between maize and pigeonpea in semi-arid Tanzania: Effect on yields and nutrition of crops

TL;DR: Yield reductions suggest that the intercropped pigeonpea did not recover from competition after maize harvesting that reduced competition, and applications can be reduced by half under the improved fallow system due to alleviating interspecific competition.
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Towards transferable functions for extraction of Non-timber Forest Products: A case study on charcoal production in Tanzania

TL;DR: In this paper, the authors developed a modeling approach for the economic valuation of annual Non-Timber Forest Product (NTFP) extraction at a large spatial scale, which has four main strengths: (1) it is based on household production functions using data of actual household behaviour, it is spatially sensitive, using a range of explanatory variables related to socio-demographic characteristics, population density, resource availability and accessibility, and it is generic and can therefore be up-scaled across nonsurveyed areas.