No abstract

Achieving sustainable development goals requires targeting and monitoring sustainable solutions tailored to different social and ecological contexts. A social-ecological systems (SESs) framework was developed to help diagnose problems, identify complex interactions, and solutions tailored to each SES. Here we develop a data-driven method for upscaling the SES framework and apply it to a context where data is scarce, but also where solutions towards sustainable development are needed. The purpose of upscaling the framework is to create a tool that facilitates decision-making in data-scarce contexts. We mapped SES by applying the framework to poverty alleviation and food security issues in the Volta River basin in Ghana and Burkina Faso. We found archetypical configurations of SES in space, and discuss where agricultural innovations such as water reservoirs might have a stronger impact at increasing food availability and therefore alleviating poverty and hunger. We conclude by outlining how the method can be used in other SES comparative studies.

Most current approaches to landscape scale ecosystem service assessments rely on detailed secondary data. This type of data is seldom available in regions with high levels of poverty and strong local dependence on provisioning ecosystem services for livelihoods. We develop a method to extrapolate results from a previously published village scale ecosystem services assessment to a higher administrative level, relevant for land use decision making. The method combines remote sensing (using a hybrid classification method) and interviews with community members. The resulting landscape scale maps show the spatial distribution of five different livelihood benefits (nutritional diversity, income, insurance/saving, material assets and energy, and crops for consumption) that illustrate the strong multifunctionality of the Sahelian landscapes. The maps highlight the importance of a diverse set of sub-units of the landscape in supporting Sahelian livelihoods. We see a large potential in using the resulting type of livelihood benefit maps for guiding future land use decisions in the Sahel.