A critical question for agricultural production and food security is how water demand for staple crops will respond to climate and carbon dioxide (CO2) changes1, especially in light of the expected increases in extreme heat exposure2. To quantify the trade-offs between the effects of climate and CO2 on water demand, we use a ‘sink-strength’ model of demand3,4 which relies on the vapour-pressure deficit (VPD), incident radiation and the efficiencies of canopy-radiation use and canopy transpiration; the latter two are both dependent on CO2. This model is applied to a global data set of gridded monthly weather data over the cropping regions of maize, soybean, wheat and rice during the years 1948–2013. We find that this approach agrees well with Penman–Monteith potential evapotranspiration (PM) for the C3 crops of soybean, wheat and rice, where the competing CO2 effects largely cancel each other out, but that water demand in maize is significantly overstated by a demand measure that does not include CO2, such as the PM. We find the largest changes in wheat, for which water demand has increased since 1981 over 86% of the global cropping area and by 2.3–3.6 percentage points per decade in different regions.

Policies that promote biofuels in major agricultural economies raise important questions for food prices and food security at local to global scales. Global biofuel output rose from 38 billion liters to 131 billion liters between 2005 and 2015, boosting the demand for annual- and perennial-crop feedstocks such as maize, sugar, soy, rapeseed, and palm oil. Although ethanol volume was three times that of biodiesel in 2015, the share of biodiesel in total biofuel output rose from 10% to almost 25% over the course of the decade (EIA, n.d.; REN21, 2016). Biodiesel production increased 700% between 2005 and 2015 and is expected to rise by another 35% by 2025 (OECD/FAO, 2014). In this paper, we examine the linkages between biodiesel, oil crop, and energy markets, and ask: What are the food security implications of biodiesel policies in major agricultural economies? How do governments adjust biodiesel policies in response to international commodity prices, trade opportunities, and their changing economic and environmental priorities?

Elevated atmospheric CO2 concentrations ([CO2]) are expected to increase C3 crop yield through the CO2 fertilization effect (CFE) by stimulating photosynthesis and by reducing stomatal conductance and transpiration. The latter effect is widely believed to lead to greater benefits in dry rather than wet conditions, although some recent experimental evidence challenges this view. Here we used a process-based crop model, the Agricultural Production Systems sIMulator (APSIM), to quantify the contemporary and future CFE on soybean in one of its primary production area of the US Midwest. APSIM accurately reproduced experimental data from the Soybean Free-Air CO2 Enrichment site showing that the CFE declined with increasing drought stress. This resulted from greater radiation use efficiency (RUE) and above-ground biomass production at elevated [CO2] that outpaced gains in transpiration efficiency (TE). Using an ensemble of eight climate model projections, we found that drought frequency in the US Midwest is projected to increase from once every 5 years currently to once every other year by 2050. In addition to directly driving yield loss, greater drought also significantly limited the benefit from rising [CO2]. This study provides a link between localized experiments and regional-scale modeling to highlight that increased drought frequency and severity pose a formidable challenge to maintaining soybean yield progress that is not offset by rising [CO2] as previously anticipated. Evaluating the relative sensitivity of RUE and TE to elevated [CO2] will be an important target for future modeling and experimental studies of climate change impacts and adaptation in C3 crops.

Food security will be increasingly challenged by climate change, natural resource degradation, and population growth. Wheat yields, in particular, have already stagnated in many regions and will be further affected by warming temperatures. Despite these challenges, wheat yields can be increased by improving management practices in regions with existing yield gaps. To identify the magnitude and causes of current yield gaps in India, one of the largest wheat producers globally, we produced 30 meter resolution yield maps from 2001 to 2015 across the Indo-Gangetic Plains (IGP), the nation's main wheat belt. Yield maps were derived using a new method that translates satellite vegetation indices to yield estimates using crop model simulations, bypassing the need for ground calibration data. This is one of the first attempts to apply this method to a smallholder agriculture system, where ground calibration data are rarely available. We find that yields can be increased by 11% on average and up to 32% in the eastern IGP by improving management to current best practices within a given district. Additionally, if current best practices from the highest-yielding state of Punjab are implemented in the eastern IGP, yields could increase by almost 110%. Considering the factors that most influence yields, later sow dates and warmer temperatures are most associated with low yields across the IGP. This suggests that strategies to reduce the negative effects of heat stress, like earlier sowing and planting heat-tolerant wheat varieties, are critical to increasing wheat yields in this globally-important agricultural region.

Although development organizations agree that reliable access to energy and energy services—one of the 17 Sustainable Development Goals—is likely to have profound and perhaps disproportionate impacts on women, few studies have directly empirically estimated the impact of energy access on women's empowerment. This is a result of both a relative dearth of energy access evaluations in general and a lack of clarity on how to quantify gender impacts of development projects. Here we present an evaluation of the impacts of the Solar Market Garden—a distributed photovoltaic irrigation project—on the level and structure of women's empowerment in Benin, West Africa. We use a quasi-experimental design (matched-pair villages) to estimate changes in empowerment for project beneficiaries after one year of Solar Market Garden production relative to non-beneficiaries in both treatment and comparison villages (n = 771). To create an empowerment metric, we constructed a set of general questions based on existing theories of empowerment, and then used latent variable analysis to understand the underlying structure of empowerment locally. We repeated this analysis at follow-up to understand whether the structure of empowerment had changed over time, and then measured changes in both the levels and likelihood of empowerment over time. We show that the Solar Market Garden significantly positively impacted women's empowerment, particularly through the domain of economic independence. In addition to providing rigorous evidence for the impact of a rural renewable energy project on women's empowerment, our work lays out a methodology that can be used in the future to benchmark the gender impacts of energy projects.

Large-scale crop monitoring and yield estimation are important for both scientific research and practical applications. Satellite remote sensing provides an effective means for regional and global cropland monitoring, particularly in data-sparse regions that lack reliable ground observations and reporting. The conventional approach of using visible and near-infrared based vegetation index (VI) observations has prevailed for decades since the onset of the global satellite era. However, other satellite data encompass diverse spectral ranges that may contain complementary information on crop growth and yield, but have been largely understudied and underused. Here we conducted one of the first attempts at synergizing multiple satellite data spanning a diverse spectral range, including visible, near-infrared, thermal and microwave, into one framework to estimate crop yield for the U.S. Corn Belt, one of the world's most important food baskets. Overall, using satellite data from various spectral bands significantly improves regional crop yield predictions. The additional use of ancillary climate data (e.g. precipitation and temperature) further improves model skill, in part because the crop reproductive stage related to harvest index is highly sensitive to environmental stresses but they are not fully captured by the satellite data used in our study. We conclude that using satellite data across various spectral ranges can improve monitoring of large-scale crop growth and yield beyond what can be achieved from individual sensors. These results also inform the synergistic use and development of current and next generation satellite missions, including NASA ECOSTRESS, SMAP, and OCO-2, for agricultural applications.