ABSTRACT
Africa is vulnerable to the impacts of climate change, particularly in terms of its agriculture and crop production. The majority of climate models project a negative impact of future climate change on crop production, with maize being particularly vulnerable. However, the magnitude of this change remains uncertain. Therefore, it is important to reduce the uncertainties related to the anticipated changes to guide adaptation options. This study uses a combination of local and large-scale empirical orthogonal function (EOF) predictors as a novel approach to model the impacts of future climate change on crop yields in West, East and Central Africa. Here a cross-validated Bayesian model was developed using predictors derived from the regional climate model REMO for the period 1982-2100. On average, the combined local and large-scale EOF predictors explained around 28 % of maize yield variability from 1982 to 2016 of the entire study regions. Notably, climate predictors played a significant role in West Africa, explaining up to 51 % of the maize yield variability. Large-scale climate EOF predictors contributed most to the explained variance, reflecting the role of regional climate in future maize yield variability. Under a high-emissions scenario (RCP8.5), maize yield is projected to decrease over the entire study region by 20 % by the end of the century. However, a minor increase is projected in eastern Africa. This study highlights the importance of incorporating climate predictors at various scales into crop yield modeling. Furthermore, the findings will offer valuable guidance to decision-makers in shaping adaptation options.
ABSTRACT
Since the 1990s, children of the Gbagyi tribe in Northern Nigeria have been suffering severe rickets with an incidence of up to 40% in the children's generation. The disease seems to be prevalent in an area of approximately 100 km(2) south-east of Kaduna. According to broad medical studies in that area, there is no evidence for a genetic disposition but for a nutritional cause of the disease. A lack of calcium was found in blood and was calculated to originate from diet. We therefore checked parent material, soil, maize cobs (Zea mays) and drinking water for their specific Ca contents from a region with rickets problem (study area A) and compared the results to Ca amounts in similar samples from a region where rickets is unknown among the Gbagyi population (study area B). It thereby became apparent that there are no differences in mineralogical composition of the parent material between the study areas, but that Ca contents in soil, maize cobs and drinking water are 47.6%, 26.6%, respectively, 79.1% lower in study area A compared to study area B. This result suggests that there may indeed be a nutritionally and/or environmentally influence on rickets disease. Nevertheless, further research on this topic is required.
