No abstract

At present, our ability to comprehend the dynamics of food systems and the consequences of their rapid 'transformations' is limited. In this paper, we propose to address this gap by exploring the interactions between the sustainability of food systems and a set of key drivers at the global scale. For this we compile a metric of 12 key drivers of food system from a globally-representative set of low, middle, and high-income countries and analyze the relationships between these drivers and a composite index that integrates the four key dimensions of food system sustainability, namely: food security & nutrition, environment, social, and economic dimensions. The two metrics highlight the important data gap that characterizes national systems' statistics-in particular in relation to transformation, transport, retail and distribution. Spearman correlations and Principal Component Analysis are then used to explore associations between levels of sustainability and drivers. With the exception of one economic driver (trade flows in merchandise and services), the majority of the statistically significant correlations found between food system sustainability and drivers appear to be negative. The fact that most of these negative drivers are closely related to the global demographic transition that is currently affecting the world population highlights the magnitude of the challenges ahead. This analysis is the first one that provides quantitative evidence at the global scale about correlations between the four dimensions of sustainability of our food systems and specific drivers.

Low crop yields in Sub-Saharan Africa are associated with low fertilizer use. To better understand patterns of, and opportunities for, fertilizer use, location specific fertilizer price data may be relevant. We compiled local market price data for urea fertilizer, a source of inorganic nitrogen, in 1729 locations in eighteen countries in two regions (West and East Africa) from 2010-2018 to understand patterns in the spatial variation in fertilizer prices. The average national price was lowest in Ghana (0.80 USD kg -1 ), Kenya (0.97 USD kg -1 ), and Nigeria (0.99 USD kg -1 ). Urea was most expensive in three landlocked countries (Burundi: 1.51, Uganda: 1.49, and Burkina Faso: 1.49 USD kg -1 ). Our study uncovers considerable spatial variation in fertilizer prices within African countries. We show that in many countries this variation can be predicted for unsampled locations by fitting models of prices as a function of longitude, latitude, and additional predictor variables that capture aspects of market access, demand and environmental conditions. Predicted within-country urea price variation (as a fraction of the median price) was particularly high in Kenya (0.77-1.12), Nigeria (0.83-1.34), Senegal (0.73-1.40), Tanzania (0.90-1.29) and Uganda (0.93-1.30), but much lower in Burkina Faso (0.96-1.04), Burundi (0.95-1.05), and Togo (0.94-1.05). The correlation coefficient of the country level models was between 0.17 to 0.83 (mean 0.52) and the RMSE varies from 0.005 to 0.188 (mean 0.095). In 10 countries, predictions were at least 25% better than a null-model that assumes no spatial variation. Our work indicates new opportunities for incorporating spatial variation in prices into efforts to understand the profitability of agricultural technologies across rural areas in Sub-Saharan Africa.

rop yields in sub-Saharan Africa (SSA) are generally much lower than elsewhere. For instance, average maize yield in SSA is 1,446 kg ha −1 , whereas average global maize yield, excluding SSA, is 5,783 kg ha −1 (refs. 1,2 ), and increasing agricultural productivity in SSA could improve food security and rural welfare [3][4][5][6][7][8] . Increasing staple crop yield, the amount produced per unit cropland area, is also considered an important strategy to mitigate crop area expansion, and thus spare land for nature 9 . It is technically possible to strongly increase crop yields in many regions of SSA because there are large 'ecological yield gaps' , the differences between the actual crop yields and the crop yields that could be attained given available technology and the soil and weather conditions 3,4 . Reported national average ecological yield gaps for rainfed maize are as high as 4,800 kg ha −1 for Tanzania and Burkina Faso and over 9,000 kg ha −1 for Nigeria and Ethiopia 10 .To achieve such substantially higher crop yields, farmers would need to intensify their production systems in several ways. While there are different approaches to increase yields, in all cases farmers would need to use much more fertilizer than they currently do [11][12][13] , and it is not clear if and/or where this would be economically sensible from the farmers' perspectives. The profitability of fertilizer use depends on the effective local price of fertilizer and crop outputs, and on the local crop response to fertilizer. Reported maize responses to nitrogen fertilizer across SSA vary between 5 and 53 kg grain per kg N applied (refs. [14][15][16][17][18][19] ), and fertilizer use has been found to be profitable in some regions [20][21][22][23][24] , but not in others 25,26 , with considerable variation within countries. It is a challenge to generalize such reports because of the spatial variation in input and output prices, as well as in crop responses to fertilizer.To better understand opportunities for increasing staple food production in SSA through increased use of fertilizers, we evaluated location-specific ecological and economic conditions and how they affect crop responses to and economic returns on fertilizer investments. We compiled high-spatial-resolution data on soils, weather and local prices of fertilizer and maize grain. To predict crop response to fertilizer, we used an empirical machine-learning model derived from 12,081 observations from maize trials in 1,141 unique locations across SSA, and a mechanistic (rule-based) fertilizer response model called QUEFTS. Both models were used to predict maize yield in response to 539 different fertilizer applications combinations of nitrogen (0-200 kg ha −1 ), phosphorus and potassium (0-100 kg ha −1 ) for all 9 × 9 km spatial resolution grid cells of maize production in SSA.