The Center on Food Security and the Environment is a joint effort of the Freeman Spogli Institute for International Studies and the Stanford Woods Institute for the Environment.
David Lobell discusses Stanford study of cover crops' impacts.
Research has consistently identified firearm availability as a risk factor for suicide. However, existing studies are relatively small in scale, estimates vary widely, and no study appears to have tracked risks from commencement of firearm ownership.
Machine learning and satellite data of crops shows that farms that till the soil less can increase yields of corn and soybeans and improve the health of the soil. Farmers have resisted a switch to reduced tilling because it was believed to reduce yields. Instead, it may increase yields while lowering production costs and reducing soil erosion.
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.
One of the greatest challenges in monitoring food security is to provide reliable crop yield information that is temporally consistent and spatially scalable. An ideal yield dataset would not only extend globally and across multiple years, but would also have enough spatial granularity to characterize productivity at the field and subfield level. Rapid increases in satellite data acquisition and platforms such as Google Earth Engine that can efficiently access and process vast archives of new and historical data offer an opportunity to map yields globally, but require efficient and robust algorithms to combine various data streams into yield estimates. We recently introduced a Scalable satellite-based Crop Yield Mapper (SCYM) that combines crop models simulations with imagery and weather data to generate 30 m resolution yield estimates without the need for ground calibration. In this study, we tested new large-scale implementations of SCYM, focusing on three regions with varying crops, field sizes and landscape heterogeneity: maize in the U.S. corn belt (390,000 km2), maize in Southern Zambia (86,000 km2), and wheat in northern India (450,000 km2). As a benchmark, we also tested a simpler empirical approach (PEAKVI) that relates yield to the peak value of a time series of spatially aggregated vegetation indices, similar to methods used in current operational monitoring. Both SCYM and PEAKVI were applied to data from all Landsat's sensors and MODIS for more than a decade in each region, and evaluated against ground-based estimates at the finest available administrative level (e.g., counties in the U.S.). We found consistently high correlations (R2 ≥ 0.5) between the spatial pattern of ground- and satellite-based estimates in both U.S. maize and India wheat, with small differences between methods and source of satellite data. In the U.S., SCYM outperformed PEAKVI in tracking temporal yield variations, likely owing to its explicit consideration of weather. In India, both methods failed to track temporal yield changes, with various possible explanations discussed. In Zambia, the PEAKVI approach applied to MODIS tracked yield variations much better (R2 > 0.5) than any other yield estimate, likely because the frequent cloud cover in this region confounds the other approaches. Overall, this study demonstrates successful approaches to yield estimation in each region, and illustrates the importance of distinguishing between accuracy for spatial and temporal variation. The 30 m resolution of Landsat-based SCYM does not appear to offer large benefits for tracking aggregate yields, but enables finer scale analyses than possible with the other approaches.
Temperature data are commonly used to estimate the sensitivity of many societally relevant outcomes, including crop yields, mortality, and economic output, to ongoing climate changes. In many tropical regions, however, temperature measures are often very sparse and unreliable, limiting our ability to understand climate change impacts. Here we evaluate satellite measures of near-surface temperature (Ts) as an alternative to traditional air temperatures (Ta) from weather stations, and in particular their ability to replace Ta in econometric estimation of climate response functions. We show that for maize yields in Africa and the United States, and for economic output in the United States, regressions that use Ts produce very similar results to those using Ta, despite the fact that daily correlation between the two temperature measures is often low. Moreover, for regions such as Africa with poor station coverage, we find that models with Ts outperform models with Ta, as measured by both R 2 values and out-of-sample prediction error. The results indicate that Ts can be used to study climate impacts in areas with limited station data, and should enable faster progress in assessing risks and adaptation needs in these regions.
Corn yields in the central United States have become more sensitive to drought conditions in the past two decades, according to a new study in the journal Science from a team led FSE associate director David Lobell.
"The Corn Belt is phenomenally productive," Lobell said, referring to the region of Midwestern states where much of the country's corn is grown. "But in the past two decades we saw very small yield gains in non-irrigated corn under the hottest conditions. This suggests farmers may be pushing the limits of what's possible under these conditions."
He predicted that at current levels of temperature sensitivity, crops could lose 15 percent of their yield within 50 years, or as much as 30 percent if crops continue the trend of becoming more sensitive over time.
As Lobell explained, the quest to maximize crop yields has been a driving force behind agricultural research as the world's population grows and climate change puts pressure on global food production. One big challenge for climate science is whether crops can adapt to climate change by becoming less sensitive to hotter and drier weather.
"The data clearly indicate that drought stress for corn and soy comes partly from low rain, but even more so from hot and dry air. Plants have to trade water to get carbon from the air to grow, and the terms of that trade become much less favorable when it's hot," said Lobell, also the lead author for a chapter in the U.N. Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report, which details a consensus view on the current state and fate of the world's climate.
The United States produces 40 percent of the world's corn, mostly in Iowa, Illinois, and Indiana. As more than 80 percent of U.S. agricultural land relies on natural rainfall rather than irrigation, corn farmers in these regions depend on precipitation, air temperature and humidity for optimal plant growth.
According to the research, over the last few decades, corn in the United States has been modified with new traits, like more effective roots that better access water and built-in pest resistance to protect against soil insects. These traits allow farmers to plant seeds closer together in a field, and have helped farmers steadily raise yields in typical years.
But in drought conditions, densely planted corn can suffer higher stress and produce lower yields. In contrast, soybeans have not been planted more densely in recent decades and show no signs of increased sensitivity to drought, the report noted.
Drought conditions are expected to become even more challenging as temperatures continue to rise throughout the 21st century, the researchers said.
Lobell said, "Recent yield progress is overall a good news story. But because farm yields are improving fastest in favorable weather, the stakes for having such weather are rising. In other words, the negative impacts of hot and dry weather are rising at the same time that climate change is expected to bring more such weather."
Lobell's team examined an unprecedented amount of detailed field data from more than 1 million USDA crop insurance records between 1995 and 2012.
"The idea was pretty simple," he said. "We determined which conditions really matter for corn and soy yields, and then tracked how farmers were doing at different levels of these conditions over time. But to do that well, you really need a lot of data, and this dataset was a beauty."
Lobell said he hopes that the research can help inform researchers and policymakers so they can make better decisions.
"I think it's exciting that data like this now exist to see what's actually happening in fields. By taking advantage of this data, we can learn a lot fairly quickly," he said. "Of course, our hope is to improve the situation. But these results challenge the idea that U.S. agriculture will just easily adapt to climate changes because we invest a lot and are really high-tech."
Lobell and colleagues are also looking at ways crops may perform better under increasingly hot conditions. "But I wouldn't expect any miracles," he said. "It will take targeted efforts, and even then gains could be modest. There's only so much a plant can do when it is hot and dry."
This animation shows the increasing sensitivity of U.S. corn to drought over time. Animation by Carlo Di Bonito.
A key question for climate change adaptation is whether existing cropping systems can become less sensitive to climate variations. We use a field-level dataset on maize and soybean yields in the central United States for 1995 through 2012 to examine changes in drought sensitivity. Although yields have increased in absolute value under all levels of stress for both crops, the sensitivity of maize yields to drought stress associated with high vapor pressure deficits has increased. The greater sensitivity has occurred despite cultivar improvements and increased CO2, and reflects the agronomic trend toward higher sowing densities. The results suggest that agronomic changes tend to translate improved drought tolerance of plants to higher average yields, but not to decreasing drought sensitivity of yields at the field scale.
The full text of the article, abstract, and reprint are available via Science.
Growing agave and other carefully chosen plants amid photovoltaic panels could allow solar farms not only to collect sunlight for electricity but also to produce crops for biofuels, according to new computer models by Stanford scientists.
This colocation approach could prove especially useful in sunny, arid regions such as the southwestern United States where water is scarce, said Sujith Ravi, who is conducting postdoctoral research with professors David Lobell and Chris Field, both on faculty in environmental Earth system science and senior fellows at the Stanford Woods Institute for the Environment. David Lobell is associate director and Chris Field is a core faculty affiliate at the Center on Food Security and the Environment.
“Colocated solar-biofuel systems could be a novel strategy for generating two forms of energy from uncultivable lands: electricity from solar infrastructure and easily transportable liquid fuel from biofuel cultivation,” said Ravi, lead author of a new study published in a recent issue of the journal Environmental Science & Technology that details the idea.
Photovoltaic (PV) solar farms run on sunlight, but water is required to remove dust and dirt from the panels to ensure they operate at maximum efficiency. Water is also used to dampen the ground to prevent the buildup and spread of dust. Crops planted beneath the solar panels would capture the runoff water used for cleaning the PV panels, thus helping to optimize the land. The plants’ roots would also help anchor the soil, and their foliage would help reduce the ability of wind to kick up dust.
Computer simulations of a hypothetical colocation solar farm in California’s San Bernardino County by Ravi and colleagues suggest that these two factors together could lead to a reduction in the overall amount of water solar farms need to operate. "It could be a win-win situation," Ravi said. “Water is already limited in many areas and could be a major constraint in the future. This approach could allow us to produce energy and agriculture with the same water.”
But which crops to use? Many solar farms operate in sunny but arid regions that are very not hospitable to most food crops. But there is one valuable plant that thrives at high temperatures and in poor soil: agave. Native to North and South America, the prickly plant can be used to produce liquid ethanol, a biofuel that can be mixed with gasoline or used to power ethanol vehicles. "Unlike corn or other grains, most of the agave plant can be converted to ethanol," Ravi said.
The team plans to test the colocation approach around the world to determine the ideal plants to use and to gather realistic estimates for crop yield and economic incentives.
“Sujith’s work is a great example of how thinking beyond a single challenge like water or food or energy sometimes leads to creative solutions,” said Lobell, who is a coauthor on the new study. “Of course, creative solutions don’t always work in the real world, but this one at least seems worthy of much more exploration.”
Ker Than is associate director of communications for the School of Earth Sciences.
Contact: Sujith Ravi, 703-581-8186, sujith@stanford.edu; Ker Than, 646-673-4558, kerthan@stanford.edu
FSE’s David Lobell finds that an increase of more than two degrees Celsius in average global temperature is likely to cause yields of wheat, rice and maize to fall throughout the 21st century. Early adaptation could increase projected yields by up to 15 percent.
If global temperatures continue to rise, the amount of crops farmers can harvest will sharply decline during the next 100 years.
Stanford professor David Lobell and an international team of climate scientists modeled future crop yields under several global climate scenarios throughout the 21st century. They found that if average global temperatures rise by more than two degrees Celsius, farmers are likely to get less wheat, rice and maize out of each plot of land. Yields are expected to fall by an average of 4.9 percent for every one degree Celsius rise in average temperature. Year-to-year variability of harvests is also expected to rise, as drought and flooding become more frequent. Crop yield losses will speed up throughout the century, with declines in yield beginning around 2030 and with the fastest drop happening in the second half of the century.
Lobell, an associate professor of Environmental Earth System Science and the associate director of the Center on Food Security and the Environment at Stanford, reviewed over 1,700 published studies with a team of climate scientists from the United States, United Kingdom and Australia. The team found that if farmers adapt to climate change within the next few years, they have a better chance of avoiding or even reversing the predicted decline of wheat and rice yields in some regions. Agricultural adaptation strategies like irrigating fields and developing new crop breeds could increase projected yields between 7 percent and 15 percent.
The new study also highlights the need for better data on the potential future impacts of other factors that affect crop yields, like the prevalence of pests and plant diseases, and the availability of water supply. A full version of the study can be found online at Nature Climate Change.