Browsing by Author "Njana, Marco Andrew"

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Above- and belowground tree biomass models for three mangrove species in Tanzania: a nonlinear mixed effects modelling approach
(Springer, 2015-10) Njana, Marco Andrew; Bollandsås, Ole Martin; Eid, Tron; Malimbwi, Rogers Ernest; Zahabu, Eliakimu
& Key message Tested on data from Tanzania, both existing species-specific and common biomass models developed elsewhere revealed statistically significant large prediction errors. Species-specific and common above- and below- ground biomass models for three mangrove species were therefore developed. The species-specific models fitted bet- ter to data than the common models. The former models are recommended for accurate estimation of biomass stored in mangrove forests of Tanzania. & Context Mangroves are essential for climate change mitiga- tion through carbon storage and sequestration. Biomass models are important tools for quantifying biomass and car- bon stock. While numerous aboveground biomass models exist, very few studies have focused on belowground biomass, and among these, mangroves of Africa are hardly or not represented.
Carbon stocks for different land cover types in Mainland Tanzania
(2019-04) Malimbwi, Rogers; Zahabu, Eliakimu; Njana, Marco Andrew; Mugasha, Wilson Ancelm; Mauya, Ernest William
Background: Developing countries participating in the mitigation mechanism of reducing emissions from defor- estation and forest degradation (REDD+), are required to establish a forest reference emission level (FREL), if they wish to seek financial support to reduce carbon emissions from deforestation and forest degradation. However, establish- ment of FREL relies heavily on the accurate estimates of carbon stock as one of the input variable for computation of the emission factors (EFs). The product of an EF and activity data, such as the area of deforestation, results in the total emissions needed for establishment of FREL. This study presents the carbon stock estimates for different land cover classes based on an analysis of Tanzania’s national forest inventory data generated through the National Forest Resources Monitoring and Assessment (NAFORMA). Results: Carbon stocks were estimated in three carbon pools, namely aboveground, belowground, and deadwood for each of the three land cover classes (i.e. Forest, non-forest, and wetland). The weighted average carbon stock was 33.35 t C ha −1 for forest land, 4.28 t ha −1 for wetland and 5.81 t ha −1 for non-forest land. The uncertainty values were 0.9% for forest land, 11.3% for wetland and 1.8% for non-forest land. Average carbon stocks for land cover sub-classes, which make up the above mentioned major land cover classes, are also presented in our study. Conclusions: The values presented in this paper correspond to IPCC tier 3 and can be used for carbon estimation at the national scale for the respective major primary vegetation type for various purposes including REDD+. However, if local based estimates values are needed, the use of auxiliary data to enhance the precision of the area of interest is recommended. Keywords: Carbon stock, REDD+, FREL, Emission factor, Uncertainty
Procedures for quantification of belowground biomass of three mangrove tree species
(Springer Science, 2015-02) Njana, Marco Andrew; Eid, Tron; Zahabu, Eliakimu; Malimbwi, Rogers
A review of studies on belowground biomass (BGB) of mangroves revealed that proce- dures for excavation and determination of dry weight are insufficiently documented. The main objective of this study was therefore to describe procedures for quantification of tree BGB for Avicennia marina (Forssk.), Sonneratia alba J. Smith and Rhizophora mucronata Lam. The study covered four sites in Tanzania where 30 trees were sampled (10 for each species). A new root sampling procedure applied for A. marina and S. alba seemed to work adequately. Dry to fresh weight ratios (DF-ratios) varied between tree species, between tree sizes and between root compo- nents. Therefore, for each tree species, tree- and root component-specific DF-ratios were applied for dry weight determination. For A. marina and S. alba trees, a significant proportion of total tree BGB is stored in the root crown (34 and 10 % respectively). Future studies should therefore ensure inclusion of root crown when accounting for total tree BGB.