Browsing by Author "Malimbwi, Rogers Ernest"

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Above- and belowground tree biomass models for three mangrove species in Tanzania: a nonlinear mixed effects modelling approach
(Springer) Njana, Marco Andrew; Bollandsås, Ole Martin; Eid, Tron; Malimbwi, Rogers Ernest; Zahabu, Eliakimu
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.
Allometric models for estimating tree volume and aboveground biomass in lowland forests of Tanzania
(International Journal of Forestry Research) Mugasha, Wilson Ancelm; Mwakalukwa, Ezekiel Edward; Luoga, Emannuel; Malimbwi, Rogers Ernest; Zahabu, Eliakimu; Silayo, Dos Santos; Sola, Gael; Crete, Philippe; Henry, Matieu; Kashindye, Almas
Allometric models for estimating tree volume and aboveground biomass in lowland forests of Tanzania
(International Journal of Forestry Research, 2016) Mugasha, Wilson Ancelm; Mwakalukwa, Ezekiel Edward; Luoga, Emannuel; Malimbwi, Rogers Ernest; Zahabu, Eliakimu; Silayo, Dos Santos; Sola, Gael; Crete, Philippe; Henry, Matieu; Kashindye, Almas
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.
Biomass and volume models based on stump diameter for assessing degradation of Miombo woodlands in Tanzania
(Hindawi) Manyanda, Bernardol John; Mugasha, Wilson Ancelm; Nzunda, Emannuel F; Malimbwi, Rogers Ernest
Biomass and volume models based on stump diameter for assessing degradation of Miombo woodlands in Tanzania
(Hindawi, 2019) Manyanda, Bernardol John; Mugasha, Wilson Ancelm; Nzunda, Emannuel F; Malimbwi, Rogers Ernest
Models to estimate forest degradation in terms of removed volume and biomass from the extraction of wood fuel and logging using stump diameter (SD) are lacking. The common method of estimating removals is through estimating diameter at breast height (D) by applying equations relating measured D and SD. The estimated D is then used to estimate biomass and volume by means of allometric equations, which utilize D. Through this sequence of procedures, it is apparent that there is an accumulation of errors. This study developed equations for estimating volume, aboveground biomass (ABG), and belowground biomass (BGB) using SD in miombo woodlands of mainland Tanzania. Volume models were developed from 114 sample trees while AGB and BGB models were developed from 127 and 57 sample trees, respectively. Both site specific and regional models were developed. Over 70% of the variations in BGB, AGB, and volume were explained by SD. It was apparent that SD is inferior compared to measured D in explaining variation in volume and BGB but not AGB. However, the accuracy of BGB and volume estimates emanating directly from SD were far better than those obtained indirectly, i.e., volume or BGB estimates obtained from estimated D from SD, since the latter is affected by accumulation of regression equation errors. For improved accuracy of ABG, BGB, and volume estimates, we recommend the use of site specific models. However, for areas with no site specific models, application of regional models is recommended. The developed models will facilitate the addition of forest degradation as a REDD+ activity into the forthcoming FREL.
Drivers and their influences on variation of aboveground carbon removals in miombo woodlands of mainland Tanzania
(BMC [Commercial Publisher]) Manyanda, Bernardol John; Nzunda, Emmanuel Fred; Mugasha, Wilson Ancelm; Malimbwi, Rogers Ernest
Effect of spacing regimes on growth, yield, and wood properties of tectona grandis at Longuza forest plantation, Tanzania
(International Journal of Forestry Research) Zahabu, Eliakimu; Raphael, Tumaini; Chamshama, Shabani Athumani Omari; Iddi, Said; Malimbwi, Rogers Ernest
Effect of spacing regimes on growth, yield, and wood properties of tectona grandis at Longuza forest plantation, Tanzania
(International Journal of Forestry Research, 2015) Zahabu, Eliakimu; Raphael, Tumaini; Chamshama, Shabani Athumani Omari; Iddi, Said; Malimbwi, Rogers Ernest
This study examined the effects of planting spacing on growth, yield, and wood properties of teak planted at square spacing regimes of 2 m, 3 m, and 4 m at Longuza Forest Plantation, Tanzania. To achieve this, tree, stand, and wood properties were studied at age of 14 years. Results showed that diameter at breast height and total height increased with increasing spacing. Mean annual increment increased significantly with increasing spacing while spacing did not have significant effect on total volume production and basal area. Basic density is also not affected by spacing while heartwood proportion increases as planting spacing increases. All studied wood properties (modulus of rupture, modulus of elasticity, compression strength tangential to grain, and shear tangential to the grain) except cleavage tangential to grain were not significantly affected by increasing spacing. It is recommended to use the spacing of 3 × 3 m, but if thinning can be done before onset of competition at 5 years, the currently used spacing of 2.5 × 2.5 m can still be used. However, the use of a spacing of 4 × 4 m can give at least 50% heartwood at shorter rotation age of 30 years.
Effects of drivers and their variations on the number of stems and aboveground carbon removals in miombo woodlands of mainland Tanzania
(BMC) Manyanda, Bernardol John; Nzunda, Emmanuel F; Mugasha, Wilson Ancelm; Malimbwi, Rogers Ernest
Effects of field plot size on prediction accuracy of aboveground biomass in airborne laser scanning-assisted inventories in tropical rain forests of Tanzania
(Springer) Mauya, Ernest William; Hansen, Endre Hofstad; Gobakken, Terje; Bollandsås, Ole Martin; Malimbwi, Rogers Ernest; Næsset, Erik
Effects of field plot size on prediction accuracy of aboveground biomass in airborne laser scanning-assisted inventories in tropical rain forests of Tanzania
(Springer, 2015) Mauya, Ernest William; Hansen, Endre Hofstad; Gobakken, Terje; Bollandsås, Ole Martin; Malimbwi, Rogers Ernest; Næsset, Erik
Background: Airborne laser scanning (ALS) has recently emerged as a promising tool to acquire auxiliary information for improving aboveground biomass (AGB) estimation in sample-based forest inventories. Under design-based and model-assisted inferential frameworks, the estimation relies on a model that relates the auxiliary ALS metrics to AGB estimated on ground plots. The size of the field plots has been identified as one source of model uncertainty because of the so-called boundary effects which increases with decreasing plot size. Recent re- search in tropical forests has aimed to quantify the boundary effects on model prediction accuracy, but evidence of the consequences for the final AGB estimates is lacking. In this study we analyzed the effect of field plot size on model prediction accuracy and its implication when used in a model-assisted inferential framework. Results: The results showed that the prediction accuracy of the model improved as the plot size increased. The adjusted R 2 increased from 0.35 to 0.74 while the relative root mean square error decreased from 63.6 to 29.2%. Indicators of boundary effects were identified and confirmed to have significant effects on the model residuals. Variance estimates of model-assisted mean AGB relative to corresponding variance estimates of pure field-based AGB, decreased with increasing plot size in the range from 200 to 3000 m 2 . The variance ratio of field-based esti- mates relative to model-assisted variance ranged from 1.7 to 7.7. Conclusions: This study showed that the relative improvement in precision of AGB estimation when increasing field-plot size, was greater for an ALS-assisted inventory compared to that of a pure field-based inventory.
Estimates of volume and carbon stock removals in miombo Woodlands of mainland Tanzania
Manyanda, Bernardol John; Nzunda, Emmanuel F; Mugasha, Wilson Ancelm; Malimbwi, Rogers Ernest
Modelling aboveground forest biomass using airborne laser scanner data in the miombo woodlands of Tanzania
(Springer) Mauya, Ernest William; Ene, Liviu Theodor; Bollandsås, Ole Martin; Gobakken, Terje; Næsset, Erik; Malimbwi, Rogers Ernest; Zahabu, Eliakimu
Modelling aboveground forest biomass using airborne laser scanner data in the miombo woodlands of Tanzania
(Springer, 2015) Mauya, Ernest William; Ene, Liviu Theodor; Bollandsås, Ole Martin; Gobakken, Terje; Næsset, Erik; Malimbwi, Rogers Ernest; Zahabu, Eliakimu
Background: Airborne laser scanning (ALS) has emerged as one of the most promising remote sensing technologies for estimating aboveground biomass (AGB) in forests. Use of ALS data in area-based forest inventories relies on the development of statistical models that relate AGB and metrics derived from ALS. Such models are firstly calibrated on a sample of corresponding field- and ALS observations, and then used to predict AGB over the entire area covered by ALS data. Several statistical methods, both parametric and non-parametric, have been applied in ALS-based forest inventories, but studies that compare different methods in tropical forests in particular are few in number and less fre- quent than studies reported in temperate and boreal forests. We compared parametric and non-parametric methods, specifically linear mixed effects model (LMM) and k-nearest neighbor (k-NN). Results: The results showed that the prediction accuracy obtained when using LMM was slightly better than when using the k-NN approach. Relative root mean square errors from the cross validation was 46.8 % for the LMM and 58.1 % for the k-NN. Post-stratification according to vegetation types improved the prediction accuracy of LMM more as compared to post-stratification by using land use types. Conclusion: Although there were differences in prediction accuracy between the two methods, their accuracies indicated that both of methods have potentials to be used for estimation of AGB using ALS data in the miombo woodlands. Future studies on effects of field plot size and the errors due to allometric models on the prediction accu- racy are recommended. Keywords: Parametric models, Prediction accuracy, Non-parametric models, LMM, k-NN, Sampling design
Stump height: a potential escalator of wood volume and carbon removals in miombo woodlands of mainland Tanzania
(Springer) Manyanda, Bernardol John; Malimbwi, Rogers Ernest; Mugasha, Wilson Ancelm; Nzunda, Emmanuel F.
Stump height: a potential escalator of wood volume and carbon removals in miombo woodlands of mainland Tanzania
(Springer, 2022-04) Manyanda, Bernardol John; Malimbwi, Rogers Ernest; Mugasha, Wilson Ancelm; Nzunda, Emmanuel F.
Mitigation and adaptation to climate change in developing countries require sustainable forest management through either retaining the forest unharvested, i.e., conservation or an increased need for proper tree harvesting. However, significant number of trees harvested in miombo woodland of mainland Tanzania are not cut at the specified stump height, i.e., 15 cm from the ground. Leaving extra stump height (ESH) would escalate wood vol- ume removals and hence carbon emissions. Better insights on the extent of wood volume and carbon emissions of ESH in miombo woodlands are apparently needed. This study intended to estimate volume and carbon of ESH in miombo woodland of mainland Tan- zania. Based on a sample of 5 264 stumps collected in miombo woodlands of Mainland Tanzania, total annual volume and annual carbon per hectare of ESH were estimated by using equation applicable to cylinder in R software. Result revealed that total annual vol- ume, annual volume and carbon per hectare lost through ESH were 3 800 000 m −3 year −1 , 0.098 ± 0.034m 3 ha −1 year −1 and 0.028 ± 0.009 tCha −1 year −1 , respectively. The volume and carbon loss from ESH per hectare per year escalate 6% and 5% of more volume and car- bon removals, respectively, in the entire miombo woodlands and its categories in mainland Tanzania. Since annual volume loss of ESH is almost 1⁄4 of annual volume deficit of 19.5 million m 3 year −1 , the deficit and further removals could be lowered through adhering to appropriate harvesting regulations.
Volume models for single trees in tropical rainforests in Tanzania
(Journal of Energy and Natural Resources) Masota, Abel Malyango; Zahabu, Eliakimu; Malimbwi, Rogers Ernest; Bollandsås, Ole Martin; Eid, Tron Haakon