Identifying globally relevant learnings from Africa's challenges and solutions to climate change and air pollution-related health impacts: a data science scoping review protocol.

INTRODUCTION: Leveraging data science could significantly advance the understanding of the health impacts of climate change and air pollution to meet health systems' needs and improve public health in Africa. This scoping review will aim to identify and synthesise evidence on the use of data science as an intervention to address climate change and air pollution-related health challenges in Africa. METHODS AND ANALYSIS: The search strategy will be developed, and the search will be conducted in the Web of Science, Scopus, CAB Abstracts, MEDLINE and EMBASE electronic databases. We will also search the reference lists of eligible articles for additional records. We will screen titles, technical reports, abstracts and full texts and select studies reporting the use of data science in relation to the health effects and interventions associated with climate change and air pollution in Africa. ETHICS AND DISSEMINATION: There are no formal ethics requirements as we are not collecting primary data. Results, once published, will be disseminated via conferences and shared with policy-makers and public health, air pollution and climate change key stakeholders in Africa.

Shea (Vitellaria paradoxa Gaertn C. F.) fruit yield assessment and management by farm households in the Atacora district of Benin.

Vitellaria paradoxa (Gaertn C. F.), or shea tree, remains one of the most valuable trees for farmers in the Atacora district of northern Benin, where rural communities depend on shea products for both food and income. To optimize productivity and management of shea agroforestry systems, or "parklands," accurate and up-to-date data are needed. For this purpose, we monitored120 fruiting shea trees for two years under three land-use scenarios and different soil groups in Atacora, coupled with a farm household survey to elicit information on decision making and management practices. To examine the local pattern of shea tree productivity and relationships between morphological factors and yields, we used a randomized branch sampling method and applied a regression analysis to build a shea yield model based on dendrometric, soil and land-use variables. We also compared potential shea yields based on farm household socio-economic characteristics and management practices derived from the survey data. Soil and land-use variables were the most important determinants of shea fruit yield. In terms of land use, shea trees growing on farmland plots exhibited the highest yields (i.e., fruit quantity and mass) while trees growing on Lixisols performed better than those of the other soil group. Contrary to our expectations, dendrometric parameters had weak relationships with fruit yield regardless of land-use and soil group. There is an inter-annual variability in fruit yield in both soil groups and land-use type. In addition to observed inter-annual yield variability, there was a high degree of variability in production among individual shea trees. Furthermore, household socioeconomic characteristics such as road accessibility, landholding size, and gross annual income influence shea fruit yield. The use of fallow areas is an important land management practice in the study area that influences both conservation and shea yield.

Use of isotopes to study floodplain wetland and river flow interaction in the White Volta River basin, Ghana.

Floodplain wetlands influence the timing and magnitude of stream responses to rainfall. In managing and sustaining the level of water resource usage in any river catchment as well as when modelling hydrological processes, it is essential that the role of floodplain wetlands in stream flows is recognised and understood. Existing studies on hydrology within the Volta River basin have not adequately represented the variability of wetland hydrological processes and their contribution to the sustenance of river flow. In order to quantify the extent of floodwater storage within riparian wetlands and their contribution to subsequent river discharges, a series of complementary studies were conducted by utilising stable isotopes, physical monitoring of groundwater levels and numerical modelling. The water samples were collected near Pwalugu on the White Volta River and at three wetland sites adjacent to the river using the grab sampling technique. These were analysed for (18)O and (2)H. The analysis provided an estimate of the contribution of pre-event water to overall stream flow. In addition, the variation in the isotopic composition in the river and wetland water samples, respectively, revealed the pattern of flow and exchange of water between the wetlands and the main river system.