Designing and implementing biodiversity-based value chains can be a complex undertaking, especially in places where outcomes are uncertain and risks of project failure and cost overruns are high. We used the Stochastic Impact Evaluation (SIE) approach to guide the Intergovernmental Authority on Development (IGAD) on viable investment options in honey value chains, which the agency considered implementing as an economic incentive for communities along the Kenya-Somalia border to conserve biodiversity. The SIE approach allows for holistic analysis of project cost, benefit, and risk variables, including those with uncertain and missing information. It also identifies areas that pose critical uncertainties in the project. We started by conducting a baseline survey in Witu and Awer in Lamu County, Kenya. The aim of the survey was to establish the current farm income from beekeeping as a baseline, against which the prospective impacts of intervention options could be measured. We then developed an intervention decision model that was populated with all cost, benefit and risk variables relevant to beekeeping. After receiving training in making quantitative estimates, four subject-matter experts expressed their uncertainty about the proposed variables in the model by specifying probability distributions for them. We then used Monte Carlo simulation to project decision outcomes. We also identified variables that projected decision outcomes were most sensitive to, and we determined the value of information for each variable. The variable with the highest information value to the decision-maker in Witu was the honey price. In Awer, no additional information on any of the variables would change the recommendation to invest in honey value chains in the region. The analysis demonstrates a novel and comprehensive approach to decision-making for different stakeholders in a project where decision outcomes are uncertain.

Rural communities value Faidherbia albida in farming systems and pastoralism. Faidherbia albida provides products such as medicine, fodder, fuel, wood, food and services such as shade, soil fertility and nutrient cycling. Excessive browsing by animals, branch lopping and pod harvesting, have critically reduced the natural regeneration in some areas which exposes it to challenges due to dependence upon natural regeneration. The objective of this research was to evaluate response of Faidherbia albida provenances from eastern (Taveta Wangingombe) and southern Africa (Lupaso, Kuiseb Manapools) to different watering regimes to aid in selection of provenances for domestication. The observed difference in growth was analyzed to determine whether they are genetic or environmentally induced. Genotype  ×  interaction were significant at (p≤0.001, p≤0.05) in seedling height, diameter and leaf numbers. Seedling height (r=0.94 p=0.001) recorded the highest correlation coefficient among all the growth variables analyzed. The growth variation was greater for seedling height than that of diameter and leaf numbers (h2=0.97). Hierarchical cluster analysis grouped the provenances into three clusters with cluster iii consisting of Taveta, Kuiseb and Lupaso while cluster ii and i composed of Wangingombe and Manapools respectively. Manapools recorded the highest genetic distance from Taveta, Kuiseb and Lupaso at 84.55 units. Wangingombe and Manapools are closely related genetically at a distance of 7.32. The maximum inter-cluster distance between cluster i and iii indicated wider genetic diversity between the provenances in these clusters and selection should be from this clusters for hybridization program to achieve novel breeds.

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Increasing climate variability and change coupled with steady population growth is threatening water resources and livelihoods of communities living in the Wami-Ruvu and Rufiji basins in Tanzania. These basins are host to three large urban centers, namely Dar es Salaam, Dodoma and Morogoro, with a combined total of more than 7 million people. Increased demand for ecosystem services from the available surface water resources and a decreasing supply of clean and safe water are exacerbating the vulnerability of communities in these basins. Several studies have analyzed climate projects in the two basins but little attention has been paid to identify locations that have vulnerable communities in a spatially-explicit form. To address this gap, we worked with stakeholders from national and local government agencies, basin water boards and the Water Resources Integration Development Initiative (WARIDI) project funded by USAID to map the vulnerability of communities to climate variability and change in the two basins. A generalized methodology for mapping social vulnerability to climate change was used to integrate biophysical and socioeconomic indicators of exposure, sensitivity and adaptive capacity and produced climate vulnerability index maps. Our analysis identified vulnerability “hotspots” where communities are at a greater risk from climate stressors. The results from this study were used to identify priority sites and adaptation measures for the implementation of resilience building interventions and to train local government agencies and communities on climate change adaptation measures in the two basins.