96 research outputs found

    Insights into the Importance of Ecosystem Services to Human Well-being in Reservoir Landscapes

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    Smallholder famers in West Africa use multiple ecosystem services (ES) in their day-to-day lives. The contribution that these services make to human well-being (HWB), and therefore to development outcomes, is not well understood. We analyse smallholder farmer perceptions of ES, ecosystem disservices (ED), and their HWB importance around community-managed reservoirs in four semi-arid landscapes in West Africa, using participatory mapping, focus groups and face-to-face surveys. Farmers identified what nature-based benefits (ES) and problems (ED) they perceived across each landscape and rated the importance of each service and disservice for their HWB. Our results indicate that ES make an important contribution to HWB in our study sites. More than 80% of farmers rated benefits from plant-based foods, domestic and agricultural water supplies, biofuel, medicinal plants, and fertile soil, and problems associated with human disease vectors, as of high or very high importance for HWB. Multiple ES were identified as contributing to each dimension of HWB, and ED as detracting from health and material well-being. Perceptions of the importance of several ES and ED varied significantly with socio-economic group, highlighting the need for careful consideration of trade-offs between HWB outcomes and stakeholders in ecosystem management decisions to support sustainable development

    Big data and multiple methods for mapping small reservoirs: comparing accuracies for applications in agricultural landscapes

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    Whether or not reservoirs contain water throughout the dry season is critical to avoiding late season crop failure in seasonally-arid agricultural landscapes. Locations, volumes, and temporal dynamics, particularly of small (<1 Mm3) reservoirs are poorly documented globally, thus making it difficult to identify geographic and intra-annual gaps in reservoir water availability. Yet, small reservoirs are the most vulnerable to drying out and often service the poorest of farmers. Using the transboundary Volta River Basin (~413,000 sq km) in West Africa as a case study, we present a novel method to map reservoirs and quantify the uncertainty of Landsat derived reservoir area estimates, which can be readily applied anywhere in the globe. We applied our method to compare the accuracy of reservoir areas that are derived from the Global Surface Water Monthly Water History (GSW) dataset to those that are derived when surface water is classified on Landsat 8 OLI imagery using the Normalised Difference Water Index (NDWI), Modified NDWI with band 6 (MNDWI1), and Modified NDWI with band 7 (MNDWI2). We quantified how the areal accuracies of reservoir size estimates vary with the water classification method, reservoir properties, and environmental context, and assessed the options and limitations of using uncertain reservoir area estimates to monitor reservoir dynamics in an agricultural context. Results show that reservoir area estimates that are derived from the GSW data are 19% less accurate for our study site than MNDWI1 derived estimates, for a sample of 272 reservoir extents of 0.09 to 72 ha. The accuracy of Landsat-derived estimates improves with reservoir size and perimeter-area ratio, while accuracy may decline as surface vegetation increases. We show that GSW derived reservoir area estimates can provide an upper limit for current reservoir capacity and seasonal dynamics of larger reservoirs. Data gaps and uncertainties make GSW derived reservoir extents unsuitable for monitoring reservoirs that are smaller than 5.1 ha (holding ~49,759 m3), which constitute 674 (56%) reservoirs in the Volta basin, or monitoring seasonal fluctuations of most small reservoirs, limiting its utility for agricultural planning. This study is one of the first to test the utility and limitations of the newly available GSW dataset and provides guidance on the conditions under which this, and other Landsat-based surface water maps, can be reliably used to monitor reservoir resources

    Report on the main activities undertaken and preliminary findings emerging from research on the CGIAR Targeting Agricultural Innovations and Ecosystem Services in the northern Volta basin (TAI) project

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    The CGIAR Water, Land and Ecosystems research project on Targeting Agricultural Innovations and Ecosystem Services in the northern Volta basin (TAI) is a two year project (2014-2016) led by Bioversity International in collaboration with 11 institutes: CIAT, CIRAD, International Water Management Institute (IWMI), King’s College London (KCL), SNV World Burkina Faso (SNV), Stanford University, Stockholm Resilience Centre (SRC), University of Development Studies Ghana (UDS), University of Minnesota, University of Washington, and the World Agroforestry Institute. We are working with communities across Centre-Est Burkina Faso and Upper-East Ghana to gather empirical data, test research methodologies and co-develop knowledge on solutions to ecosystem service management challenges. Results from the project are still emerging and will continue to do so into 2017 as the team finish analysing the data and writing up their findings. This report presents the main activities accomplished and preliminary headline messages from the first 18 months of the project. Final results from the project will be made available in 2017 on the WLE website
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