Browsing by Author "Mugasha, W. A."

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Allometric Biomass and Volume Models for Coconut Trees
(E&D Vision Publishing Ltd, 2018-05-12) Zahabu, E.; Mugasha, W. A.; Malimbwi, R. E.; Katani, J. Z.
Allometric models for prediction of above- and belowground biomass of trees in the miombo woodlands of Tanzania
(Elservier, 2013-08-02) Mugasha, W. A.; Mugasha, W. A.; Eid, T.; Bollandsås, O. M.; Malimbwi, R. E.; Chamshama, S. A. O.; Zahabu, E.; Katani, J. Z.
Miombo woodland is a significant forest type occupying about 9% of the African land area and forms a dominant vegetation type in many southeastern African countries including Tanzania. Quantification of the amount of carbon stored in forests presently is an important component in the implementation of the emerging carbon credit market mechanisms. This calls for appropriate allometric models predicting biomass which currently are scarce. The aim of this study was to develop above- and belowground allometric general and site-specific models for trees in miombo woodland. The data were collected from four sites in Tanzania and covers a wide range of conditions and tree sizes (diameters at breast height from 1.1 to 110 cm). Above- and belowground biomass models were developed from 167 and 80 sample trees, respectively. The model fitting showed that large parts of the variation (up to 97%) in biomass were explained by diameter at breast height and tree height. Since including tree height only marginally increased the explanation of the biomass variation (from 95% to 96–97% for aboveground biomass), the general recommendation is to apply the models with diameter at breast height only as an independent variable. The results also showed that the general models can be applied over a wide range of conditions in Tanzania. The comparison with previously developed models revealed that these models can probably also be applied for miombo woodland elsewhere in southeastern Africa if not used beyond the tree size range of the model data.
Biomass and volume models for different vegetation types of Tanzania
(E&D Vision Publishing Ltd, 2016) Malimbwi, R. E.; Mauya, E. W.; Zahabu, E.; Katani, J. Z.; Chamshama, S. A. O.; Eid, T.; Bollandsås, O. M.; Maliondo, S. M. S.; Mugasha, W. A.; Masota, A. M.; Njana, M.; Makero, J. S.; Mshana, J. S.; Luganga, H.; Mathias, A.; Msalika, P.; Mwangi, J.; Mlagalila, H. E.
Climate change and high rates of global carbon dioxide (CO2) emissions have increased the attention paid to the need for high-quality monitoring systems to assess how much carbon (C) is present in terrestrial systems and how these change over time. The choice of a system to adopt relies heavily on the accuracy of the method for quantifying biomass and volume as important primary variables for computing C stock and changes over time. Methods based on ground forest inventory and remote sensing data have commonly been applied in the recent decade to estimate biomass and volume in the tropical forests. However, regardless of the method, accurate tree level biomass and volume models are needed to translate field or remotely sensed data into estimates of forest biomass and volume. Therefore, the main goal of this study was to develop biomass and volume models for the forests, woodlands, thickets, agroforestry systems and some selected tree species in Tanzania. Data from destructively sampled trees were used to develop volume and above- and below-ground biomass models. Different statistical criteria, including coefficient of determination (R2), relative root mean square error (RMSE %) and Akaike Information Criterion (AIC), were used to assess the quality of the model fits. The models selected showed good prediction accuracy and, therefore, are recommended not only to support the ongoing initiatives on forest C Measurement, Reporting and Verificatio (MRV) processes but also for general forest management in Tanzania.
Decision-support tool for management of miombo woodlands: a matrix model approach
(SOUTHERN FORESTS, 2017-03-06) Mugasha, W. A.; Bollandsås, O. M.; Gobakken, T.; Zahabu, E.; Katani, J. Z.; Eid, T.
Rational forest management planning requires information on the present forest state and on future development. However, forest management planning in Tanzania has often been done without any information on forest development because appropriate tools are lacking. This study presents a matrix model that combines distance-independent growth and mortality models, area-based recruitment models, and allometric models for prediction of volume and biomass. In this way forest development can be simulated according to different treatment options. A shortterm (seven years) test of the matrix model using independent data from permanent sample plots showed that the overall difference between predicted and observed basal area was small (6.5%). Long-term simulations (1 000 years) with the model showed that it was able to attain, irrespective of initial conditions, similar steady-state conditions (i.e. basal area, volume and biomass of 13 m2 ha−1, 130 m3 ha−1 and 90 t ha−1, respectively), which also correspond well to biological expectations in the ‘real’ miombo woodlands of the country. The flexibility of the model as a decision-support tool was demonstrated by simulating three harvesting options aiming at different combinations of charcoal and timber production. The model complexity is well adapted to the data quality and abundance, and it is dependent on proxies of some main drivers of the dynamic processes. The development of the matrix model is a step forward facilitating better decisions in the management of miombo woodlands. However, data ranges used for calibrating the submodels are limited in time and space, and future efforts should focus on tests and recalibrations based on extended data ranges. Presently, therefore, applications of the matrix model should be limited to the data ranges of the modelling data from the Iringa and Manyara regions.
Distribution, population structure and carbon storage of bamboo species in Tanzania
(INFORES project, 2019) Aloyce, E.; Manyanda, B. J.; Macrice, S. A.; Mugasha, W. A.; Malimbwi, R. E.
Sustainable management of forest resources requires information regarding quantities and quality of the resources. Despite this fact, the existing information for bamboo forest resources in Tanzania regarding abundance, distribution along altitudinal ranges, density, basal areas and carbon stocks is inadequate, site specific and fragmented. Based on 696 plots out of 30 773 plots surveyed by the National Forest Resources Assessment and Monitoring (NAFORMA), the present study assessed the distribution, abundance and carbon storage of bamboo species in Tanzania in R software. Results indicates that, 11 bamboo species from five genera and two tribes were recorded in Tanzania. They are dominated by Arundinaria alpina and Oxytenanthera abyssinica that constitutes 55.9% of the total bamboo population and are distributed in only 11 administrative regions of the country. They occur at altitude of 76 m.a.s.l to 2592 m.a.s.l, whereby about 85.2% of bamboo population are distributed below 1500 m.a.s.l. Moreover, bamboo occurs more abundantly in woodland (66%) and least in open land (0.1%). Similarly, most of the bamboo is in the production forests (44.7%) followed by Agriculture land (19.5%) while wetlands have the least (0.4%). Results further indicates that bamboo species have a mean stocking, basal area and carbon stocks of 2460 culms/ha, 2.391 m 2 /ha and 1.566 tC/ha respectively. Since most of the carbon is stored by Arundinaria alpina and Oxytenanthera abyssinica that contributes 58.2% of the total carbon stored by bamboo species in the country, efforts should be strengthened to manage these species. Likewise, for mitigating climate change bamboo species should be planted in altitude below 1500 m a.s.l. Due to lack of bamboo allometric biomass models in Tanzania, the models used in this study was borrowed from Kenya and Ethiopia, indicating the need to develop such models for Tanzanian bamboo.
Forest Protection
(E&D Vision Publishing Limited, 2019-05-01) Katani, J. Z.; Mawinda, S.; Mugasha, W. A.
Forest protection is a practice of preventing and controlling both biotic and abiotic agents, which affect forests and their associated products. There are two agents responsible for tree injury and diseases namely non-pathogenic and pathogenic, they are also known as abiotic and biotic respectively. Non-pathogenic agents include fire, climatic conditions (e.g. wind, drought, rain, and heat), soil conditions and air pollutants. Pathogenic agents cause diseases and they include viruses, bacteria, fungi, mycoplasmas (e.g. protozoa and algae); parasitic plants (e.g. mistletoes), nematodes, arthropods (e.g. insects), birds and mammals. Forest fire, pathology and entomology are discussed in detail in this chapter.
Forest Resources Assessment
(E&D Vision Publishing Limited, 2019-05-01) Mugasha, W. A.; Kashindye, A.; Katani, J. Z.; Giliba, R. A.; Kingwere, S. R. J.; Zahabu, E.
Forest resource assessment is fundamental in decision making to provide essential data and information for forest managers and decision makers to ensure sustainable forest management. This chapter has described objectives and importance of forest resource assessment, forest inventory planning and methods/designs and important descriptive statistics which should be applied when describing forest parameters of interest. Other essential aspects which also guide and compliment forest resource assessment, i.e. survey and mapping; and remote sensing are described. Application of remote sensing and GIS in forestry has also been covered.
Forests and Climate Change Mitigation
(Mkuki na Nyota Publishers Ltd, Dar es Salaam, 2017) Mugasha, W. A.; Woiso, D.A.; Katani, J. Z.
Forest ecosystems are increasingly being recognized for their important role in climate change mitigation because of their ability to regulate the carbon cycle. As a result, national and global initiatives such as afforestation/reforestation under CDM and REDD+ have been initiated to enhance the role of forests in climate change mitigation. Understanding the relationship between forests and climate change mitigation is necessary to enable the meaningful participation of forest practitioners in forest carbon projects and programmes. This chapter explores and highlights aspects of climate change mitigation as linked to forestry by explaining the meaning of climate change mitigation while also introducing various types of GHG sinks. Also covered in the chapter are relevant national strategies and policies in addition to available forest and non-forest based options for participating in mitigation activities. The chapter ends by giving an overview of M & E methods available for mitigation projects.
Modelling diameter growth, mortality and recruitment of trees in miombo woodlands of Tanzania
(Southern Forests, 2016-11-24) Tron, E.; Mugasha, W. A.; Bollandsås, O. M.; Mbwambo, L.
Miombo woodlands cover large areas in Tanzania but very little reliable data on forest dynamics for the woodlands exist. The main objective of this study was to develop a model system describing such dynamics based on easily measurable tree variables. Individual tree diameter growth and mortality models and area-based recruitment models were developed. The modelling was based on data from 117 permanent sample plots established between 1997 and 2009 on seven sites in the Iringa and Manyara regions. The data set comprised 2 314 trees at establishment and 4 758 observations of individual tree growth, and covered a large number of species (141). Based on diameter growth and by using a model-based clustering procedure, three tree species groups were developed. Several model forms with different independent variables were tested. Simple and robust models with few independent variables, which agreed with expected biological behaviour, were finally selected. Although biological behaviour was the principal model selection criterion, the models also performed well statistically. The developed model system, which is the first of its kind for miombo woodlands in Africa, may be used to develop a decision-support tool for practical forest management planning in the country.