Soil carbon monitoring using surveys and modelling. General description and application in the United Republic of Tanzania

This publication describes the application of survey- and modelling-based methods for monitoring soil organic carbon stock and its changes on a national scale. The report presents i) a design of the first inventory of soil organic carbon, including discussion on factors that affect the reliability of carbon stock estimates; and ii) a design of a modelling-based approach, including links to national forest inventory data and discussion on alternative soil organic carbon models. Both approaches can provide necessary information on soil carbon changes for a national greenhouse gas (GHG) inventory. Forest soils constitute a large pool of carbon and releases of carbon from this pool, caused by anthropogenic activities such as deforestation and forest degradation, may significantly increase the concentration of GHGs in the atmosphere. Therefore, estimating and reducing emissions from these activities have become timely issues. Currently, reliable estimates of soil organic carbon stock and stock changes are needed for REDO (Reducing Emissions from Deforestation and Forest Degradation in Developing Countries) and GHG reporting under the United Nations Framework Convention on Climate Change (UNFCCC).The document is available in print formMinistry for foreign affairs of Finlan

Above- and belowground tree biomass models for three mangrove species in Tanzania: a nonlinear mixed effects modelling approach

International audienceAbstractKey messageTested 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 belowground biomass models for three mangrove species were therefore developed. The species-specific models fitted better to data than the common models. The former models are recommended for accurate estimation of biomass stored in mangrove forests of Tanzania.ContextMangroves are essential for climate change mitigation through carbon storage and sequestration. Biomass models are important tools for quantifying biomass and carbon 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.AimsThe aims of the study were to develop above- and belowground biomass models and to evaluate the predictive accuracy of existing aboveground biomass models developed for mangroves in other regions and neighboring countries when applied on data from Tanzania.MethodsData was collected through destructive sampling of 120 trees (aboveground biomass), among these 30 trees were sampled for belowground biomass. The data originated from four sites along the Tanzanian coastline covering three dominant species: Avicennia marina (Forssk.) Vierh, Sonneratia alba J. Smith, and Rhizophora mucronata Lam. The biomass models were developed through mixed modelling leading to fixed effects/common models and random effects/species-specific models.ResultsBoth the above- and belowground biomass models improved when random effects (species) were considered. Inclusion of total tree height as predictor variable, in addition to diameter at breast height alone, further improved the model predictive accuracy. The tests of existing models from other regions on our data generally showed large and significant prediction errors for aboveground tree biomass.ConclusionInclusion of random effects resulted into improved goodness of fit for both above- and belowground biomass models. Species-specific models therefore are recommended for accurate biomass estimation of mangrove forests in Tanzania for both management and ecological applications. For belowground biomass (S. alba) however, the fixed effects/common model is recommended

Household Tree Planting In Kilosa District, Tanzania

The objective of this study was to assess household tree planting efforts and to investigate current constraints to afforestation in Kilosa District, Tanzania. The results of the study showed that 77 % of farmers in the district have planted trees in their farms, whether by themselves or previous farm owners. The average total number of planted trees was estimated to be 40 + 7 (SE) trees per household. Men headed household tended to have more planted trees [44 + 9 (SE)] than female headed households [31 + 11 (SE)]. Middle age households had planted more trees [49 + 14 (SE)] than younger [29 + 13 (SE)] and elder households [33 + 8 (SE)]. Tree planting appeared to be positively influenced by farm size and education. Fruit trees dominated in the home gardens (53 %) while non-fruits trees were more abundant far away from homestead. An investigation of constraints to tree planting and tending revealed that lack of seedlings (32 % of respondents), shortage of designated planting sites (24 %) and uncertainty over land ownership appeared to be the most important obstacles to tree planting in the district. It was surprising that land shortage became as the second leading constraint to tree planting despite the apparent low density of human population (32 people per km2 in 2000). The study concludes by recommending that in order to promote tree planting in the country\'s rural areas, farmers have to be assisted in production of seedlings. Other necessary prerequisites are effective land-use planning and clear secured tenure over land. TJFNC Vol. 75 2004: pp. 99-10

Effects of Income and Price on Household's Charcoal Consumption in Three Cities of Tanzania

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Charcoal Supply In Dar Es Salaam City, Tanzania

In Tanzania, charcoal is the primary source of energy particularly in urban areas. Dar es Salaam, being the largest urban center in the country, is also the largest consumer of charcoal. Assuming that all charcoal transported in the city is consumed, an investigation to estimate the amount of charcoal supplied daily was undertaken through monitoring at checkpoints the amount of charcoal transported daily to the city of Dar es Salaam. The study reveals that on average about 6,000 bags of charcoal are transported daily to the city. The figure may be an underestimation by four fold as most charcoal enters the city unrecorded. The highest amount of charcoal comes from North-West (34 %) and South (31 %) of Dar es Salaam. Open trucks transport the highest amount of charcoal (88 %) into the city. However, bicycles are the most frequent means of charcoal transportation constituting on average about 64 % of all individuals engaged daily in charcoal transportation. Though there are some new vehicles, the greatest percentage of vehicles involved in charcoal transportation are old (mainly registered in the 1980's). Most of the charcoal is transported during morning hours (56 %). Most of the charcoal transported to the city is for commercial use. The revenues from charcoal transportation taxes contribute a significant amount of money to both Local and Central Governments. If properly collected and used, they can effectively contribute to the development of the country and sustainable management of the catchment areas for charcoal. TJFNC Vol. 75 2004: pp. 108-11

Infective mitral valve myxoma with coronary artery embolization: Surgical intervention followed by prolonged survival

Mauyaetal.CarbonBalanceandManagement (2015) 10:10 DOI 10.1186/s13021-015-0021-x © 2015 Mauya et al.; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.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

Scenarios of land use and land cover change and their multiple impacts on natural capital in Tanzania

REDD+ (reducing emissions from deforestation, and forest degradation, plus the conservation of forest carbon stocks, sustainable management of forests, and enhancement of forest carbon stocks, in developing countries) requires information on land use and land cover changes (LULCC) and carbon emissions trends from the past to the present and into the future. Here we use the results of participatory scenario development in Tanzania, to assess the potential interacting impacts on carbon stock, biodiversity and water yield of alternative scenarios where REDD+ is effectively implemented or not by 2025, the green economy (GE) and the business as usual (BAU) respectively. Under the BAU scenario, land use and land cover changes causes 296 MtC national stock loss by 2025, reduces the extent of suitable habitats for endemic and rare species, mainly in encroached protected mountain forests, and produce changes of water yields. In the GE scenario, national stock loss decreases to 133 MtC. In this scenario, consistent LULCC impacts occur within small forest patches with high carbon density, water catchment capacity and biodiversity richness. Opportunities for maximising carbon emissions reductions nationally are largely related to sustainable woodland management but also contain trade-offs with biodiversity conservation and changes in water availability

Ecosystem services from Southern African woodlands and their future under global change

Miombo and mopane woodlands are the dominant land cover in southern Africa. Ecosystem services from these woodlands support the livelihoods of 100 M rural people and 50 M urban dwellers, and others beyond the region. Provisioning services contribute $9 ± 2 billion yr(−1) to rural livelihoods; 76$780 M. Woodlands support much of the region's agriculture through transfers of nutrients to fields and shifting cultivation. Woodlands store 18–24 PgC carbon, and harbour a unique and diverse flora and fauna that provides spiritual succour and attracts tourists. Longstanding processes that will impact service provision are the expansion of croplands (0.1 M km(2); 2000–2014), harvesting of woodfuels (93 M tonnes yr(−1)) and changing access arrangements. Novel, exogenous changes include large-scale land acquisitions (0.07 M km(2); 2000–2015), climate change and rising CO(2). The net ecological response to these changes is poorly constrained, as they act in different directions, and differentially on trees and grasses, leading to uncertainty in future service provision. Land-use change and socio-political dynamics are likely to be dominant forces of change in the short term, but important land-use dynamics remain unquantified. This article is part of the themed issue ‘Tropical grassy biomes: linking ecology, human use and conservation’