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The aim of this study was to determine the changes in forest carbon in three village forests in Tanzania during - using participatory forest carbon assessment, and to evaluate the capability of the local communities to undertake the assessment, and the costs involved. The results show that forest degradation is caused not only by disturbance as a result of anthropogenic activities; other causes include natural mortality of small trees as a result of canopy closure, and the attraction of wild animals to closed-canopy forests. Thus, mechanisms are required to compensate communities for carbon loss that is beyond their control. However, an increase in the abundance of elephants Loxodonta africana and other fauna should not be considered negatively by local communities and other stakeholders, and the importance of improved biodiversity in the context of carbon stocks should be emphasized by those promoting REDD+ (Reduced Emissions from Deforestation and Forest Degradation). This case study also shows that the cost per ha of USD ,  for participatory forest carbon assessment is less than that reported for Tanzania and elsewhere (USD -); this is attributed to the large area of forest studied. However, the cost of data analysis and reporting in  (USD ,) was significantly higher than the baseline cost (USD ,) established in  because of the involvement of external experts.

Over the past 40+ years, evolution of water institutions responsible for allocation and distribution of water has been enormous. This paper analyzes the evolution of both formal and informal water management institutions and how they affect today's processes of allocating and distributing water in farmer-managed irrigation schemes (FMISs). It also assesses how farmers translate and modify introduced formal institutions in the rights of the existing informal institution while trying to solve water management challenges based on the local conditions. In-depth and focus group data for the study were collected using a checklist of questions administered to 40 informants, one group discussion per village in Itunundu, Mboliboli, Mkula and Magombera villages, Tanzania. The basic argument of this paper is that water institutions have changed over time. Drawing from study findings, the evolution process of water institutions might be understood as an outcome of the government efforts to address emerging challenges with respect to increasing water demand and multi-use. However, institutional evolution is accompanied by some negatives outcomes, as they weaken social norms and threaten sound water management. The experiences from the irrigation schemes highlight the need to include locally evolved institutions while re-crafting formal institutions. Such interventions may well have significant outcomes for efficient, equity and power relations among water users.

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BackgroundSoil carbon and biomass depletion can be used to identify and quantify degraded soils, and by using remote sensing, there is potential to map soil conditions over large areas. Landsat 8 Operational Land Imager satellite data and airborne laser scanning data were evaluated separately and in combination for modeling soil organic carbon, above ground tree biomass and below ground tree biomass. The test site is situated in the Liwale district in southeastern Tanzania and is dominated by Miombo woodlands. Tree data from 15 m radius field-surveyed plots and samples of soil carbon down to a depth of 30 cm were used as reference data for tree biomass and soil carbon estimations.ResultsCross-validated plot level error (RMSE) for predicting soil organic carbon was 28% using only Landsat 8, 26% using laser only, and 23% for the combination of the two. The plot level error for above ground tree biomass was 66% when using only Landsat 8, 50% for laser and 49% for the combination of Landsat 8 and laser data. Results for below ground tree biomass were similar to above ground biomass. Additionally it was found that an early dry season satellite image was preferable for modelling biomass while images from later in the dry season were better for modelling soil carbon.ConclusionThe results show that laser data is superior to Landsat 8 when predicting both soil carbon and biomass above and below ground in landscapes dominated by Miombo woodlands. Furthermore, the combination of laser data and Landsat data were marginally better than using laser data only.Electronic supplementary materialThe online version of this article (doi:10.1186/s13021-017-0076-y) contains supplementary material, which is available to authorized users.