Climate change can reduce crop yields and thereby threaten food security. The current measures used to adapt to climate change involve avoiding crops yield decrease, however, the limitations of such measures due to water and other resources scarcity have not been well understood. Here, we quantify how the sensitivity of maize to water availability has increased because of the shift toward longer-maturing varieties during last three decades in the Chinese Maize Belt (CMB). We report that modern, longer-maturing varieties have extended the growing period by an average of 8 days and have significantly offset the negative impacts of climate change on yield. However, the sensitivity of maize production to water has increased: maize yield across the CMB was 5% lower with rainfed than with irrigated maize in the 1980s and was 10% lower (and even >20% lower in some areas) in the 2000s because of both warming and the increased requirement for water by the longer-maturing varieties. Of the maize area in China, 40% now fails to receive the precipitation required to attain the full yield potential. Opportunities for water saving in maize systems exist, but water scarcity in China remains a serious problem.
In this paper we discuss the scope of the adaptation challenge facing world agriculture in the coming decades. Due to rising temperatures throughout the tropics, pressures for adaptation will be greatest in some of the poorest parts of the world where the adaptive capacity is least abundant. We discuss both autonomous (market driven) and planned adaptations, distinguishing: (a) those that can be undertaken with existing technology, (b) those that involve development of new technologies, and (c) those that involve institutional/market and policy reforms. The paper then proceeds to identify which of these adaptations are currently modeled in integrated assessment studies and related analyses at global scale. This, in turn, gives rise to recommendations about how these models should be modified in order to more effectively capture climate change adaptation in the farm and food sector. In general, we find that existing integrated assessment models are better suited to analyzing adaptation by relatively well-endowed producers operating in market-integrated, developed countries. They likely understate climate impacts on agriculture in developing countries, while overstating the potential adaptations. This is troubling, since the need for adaptation will be greatest amongst the lower income producers in the poorest tropical countries. This is also where policies and public investments are likely to have the highest payoff. We conclude with a discussion of opportunities for improving the empirical foundations of integrated assessment modeling with an emphasis on the poorest countries.
Growing knowledge that the climate is changing has far outpaced our knowledge of how these changes might impact economic outcomes that we care about. Does climate change constitute one of the most important development challenges facing humanity over the next century, as is sometimes claimed, or is it a minor concern relative to other determinants of economic prosperity? Our proposed work will use modern econometric techniques and new data to quantify how poverty has responded to historical shifts in
We assess the benefits of climate change mitigation for global maize and wheat production over the 21st century by comparing outcomes under RCP4.5 and RCP8.5 as simulated by two large initial condition ensembles from NCAR’s Community Earth System Model. We use models of the relation between climate variables, CO2 concentrations, and yields built on observations and then project this relation on the basis of simulated future temperature and precipitation and CO2 trajectories under the two scenarios, for short (2021–2040), medium (2041–2060) and long (2061–2080) time horizons. We focus on projected mean yield impacts, chances of significant slowdowns in yield, and exposure to damaging heat during critical periods of the growing seasons, the last of which is not explicitly considered in yield impacts by most models, including ours. We find that substantial benefits from mitigation would be achieved throughout the 21st century for maize, in terms of reducing (1) the size of average yield impacts, with mean losses for maize under RCP8.5 reduced under RCP4.5 by about 25 %, 40 % and 50 % as the time horizon lengthens over the 21st century; (2) the risk of major slowdowns over a 10 or 20 year period, with maize chances under RCP4.5 being reduced up to ~75 % by the end of the century compared to those estimated under RCP8.5; and (3) exposure to critical or “lethal” heat extremes, with the number of extremely hot days under RCP8.5 roughly triple current levels by end of century, compared to a doubling for RCP4.5. For wheat, we project small or occasionally negative effects of mitigation for projected yields, because of stronger CO2 fertilization effects than in maize, but substantial benefits of mitigation remain in terms of exposure to extremely high temperatures.
Quantitative estimates of the impacts of climate change on economic outcomes are important for public policy. We show that the vast majority of estimates fail to account for well-established uncertainty in future temperature and rainfall changes, leading to potentially misleading projections. We reexamine seven well-cited studies and show that accounting for climate uncertainty leads to a much larger range of projected climate impacts and a greater likelihood of worst-case outcomes, an important policy parameter. Incorporating climate uncertainty into future economic impact assessments will be critical for providing the best possible information on potential impacts.
We review the emerging literature on climate and conflict. We consider multiple types of human conflict, including both interpersonal conflict, such as assault and murder, and intergroup conflict, including riots and civil war. We discuss key methodological issues in estimating causal relationships and largely focus on natural experiments that exploit variation in climate over time. Using a hierarchical meta-analysis that allows us to both estimate the mean effect and quantify the degree of variability across 55 studies, we find that deviations from moderate temperatures and precipitation patterns systematically increase conflict risk. Contemporaneous temperature has the largest average impact, with each 1σ increase in temperature increasing interpersonal conflict by 2.4% and intergroup conflict by 11.3%. We conclude by highlighting research priorities, including a better understanding of the mechanisms linking climate to conflict, societies’ ability to adapt to climatic changes, and the likely impacts of future global warming.
Growing evidence demonstrates that climatic conditions can have a profound impact on the functioning of modern human societies, but effects on economic activity appear inconsistent. Fundamental productive elements of modern economies, such as workers and crops, exhibit highly non-linear responses to local temperature even in wealthy countries. In contrast, aggregate macroeconomic productivity of entire wealthy countries is reported not to respond to temperature= while poor countries respond only linearly. Resolving this conflict between micro and macro observations is critical to understanding the role of wealth in coupled human–natural systems and to anticipating the global impact of climate change. Here we unify these seemingly contradictory results by accounting for non-linearity at the macro scale. We show that overall economic productivity is non-linear in temperature for all countries, with productivity peaking at an annual average temperature of 13 °C and declining strongly at higher temperatures. The relationship is globally generalizable, unchanged since 1960, and apparent for agricultural and non-agricultural activity in both rich and poor countries. These results provide the first evidence that economic activity in all regions is coupled to the global climate and establish a new empirical foundation for modelling economic loss in response to climate change, with important implications. If future adaptation mimics past adaptation, unmitigated warming is expected to reshape the global economy by reducing average global incomes roughly 23% by 2100 and widening global income inequality, relative to scenarios without climate change. In contrast to prior estimates, expected global losses are approximately linear in global mean temperature, with median losses many times larger than leading models indicate.
Large-scale monitoring of crop growth and yield has important value for forecasting food production and prices and ensuring regional food security. A newly emerging satellite retrieval, solar-induced fluorescence (SIF) of chlorophyll, provides for the first time a direct measurement related to plant photosynthetic activity (i.e. electron transport rate). Here, we provide a framework to link SIF retrievals and crop yield, accounting for stoichiometry, photosynthetic pathways, and respiration losses. We apply this framework to estimate United States crop productivity for 2007–2012, where we use the spaceborne SIF retrievals from the Global Ozone Monitoring Experiment-2 satellite, benchmarked with county-level crop yield statistics, and compare it with various traditional crop monitoring approaches. We find that a SIF-based approach accounting for photosynthetic pathways (i.e. C3 and C4 crops) provides the best measure of crop productivity among these approaches, despite the fact that SIF sensors are not yet optimized for terrestrial applications. We further show that SIF provides the ability to infer the impacts of environmental stresses on autotrophic respiration and carbon-use-efficiency, with a substantial sensitivity of both to high temperatures. These results indicate new opportunities for improved mechanistic understanding of crop yield responses to climate variability and change.
A Stanford-led team has discovered how to estimate crop yields with more accuracy than ever before with satellites that measure a special form of light emitted by plants. This breakthrough will help scientists study how crops respond to climate change.
As Earth's population grows toward a projected 9 billion by 2050 and climate change puts growing pressure on the world's agriculture, researchers are turning to technology to help safeguard the global food supply.
A research team, led by Kaiyu Guan, a postdoctoral fellow in Earth system science at Stanford's School of Earth, Energy, & Environmental Sciences, has developed a method to estimate crop yields using satellites that can measure solar-induced fluorescence, a light emitted by growing plants. The team published its results in the journal Global Change Biology.
Scientists have used satellites to collect agricultural data since 1972, when the National Aeronautics and Space Administration (NASA) pioneered the practice of using the color – or "greenness" – of reflected sunlight to map plant cover over the entire globe.
"This was an amazing breakthrough that fundamentally changed the way we view our planet," said Joe Berry, professor of global ecology at the Carnegie Institution for Science and a co-author of the study. "However, these vegetation maps are not ideal predictors of crop productivity. What we need to know is growth rate rather than greenness.
The growth rate can tell researchers what size yield to expect from crops by the end of the growing season. The higher the growth rate of a soybean plant or stalk of corn, for instance, the greater the harvest from a mature plant.
"What we need to measure is flux – the carbon dioxide that is exchanged between plants and the atmosphere – to understand photosynthesis and plant growth," Guan said. "How do you use color to infer flux? That's a big gap."
Solar-induced fluorescence
Recently, researchers at NASA and several European institutes discovered how to measure this flux, called solar-induced fluorescence, from satellites that were originally designed for measuring ozone and other gases in the atmosphere.
A plant uses most of the energy it absorbs from the sun to grow via photosynthesis, and dissipates unused energy as heat. It also passively releases between 1 and 2 percent of the original solar energy absorbed by the plant back into the atmosphere as fluorescent light. Guan's team worked out how to distinguish the tiny flow of specific fluorescence from the abundance of reflected sunlight that also arrives at the satellite.
"I think of it like crumbs falling to the ground as people are eating. It's a very small trail," said co-author David Lobell, associate professor of Earth system science at Stanford's School of Earth, Energy, & Environmental Science. "This glow that plants have seems to be very proportional to how fast they're growing. So the more they're growing, the more photosynthesis they're doing, and the brighter they're fluorescing." Lobell is also deputy director of the Center on Food Security and the Environment.
The research team saw an opportunity to use this new data to close the knowledge gap about crop growth, beginning with a major corn- and soybean-producing region of the U.S. Midwest.
"With the fluorescence breakthrough, we can start to directly measure photosynthesis instead of color," Guan said.
The fact that fluorescence can now be detected from space allows researchers to measure plant growth across much larger areas and over long periods of time, giving a much clearer picture of how yields fluctuate under changing weather conditions.
"One of the really cool things about fluorescence is that it opens up a whole new set of questions that we can ask about vegetation, and often times it's these new measurements that drive the science forward," Lobell said.
Next steps
The research team has already identified a number of potential uses of this approach by agricultural scientists, farmers, crop insurance providers and government agencies concerned with agricultural productivity.
If there is a day when the plant is really stressed, the fluorescence will drop significantly, Lobell said. Capturing these short-term responses to environmental changes will help scientists understand what factors plants are responding to on the daily time scale.
"That helps us, for example, figure out what we need to worry about in terms of stresses that crops are responding to," Lobell said. "What should we really be focusing on in terms of the next generation of cropping systems? What should they be able to withstand that the current crops can't withstand?"
At this early stage, fluorescence measurements are relatively low-resolution (a single measurement covers about 50 square kilometers) and because it is only collected once per day, cloudy skies can interfere with the fluorescence signal. For now, researchers have to supplement the data with other information and with on-the-ground observations to refine the measurements.
"Now that we have demonstrated the concept, we hope to soon be orbiting some new satellites specifically designed to make fluorescence measurements with better spatial and temporal resolution," Berry said.
The team plans to continue its research on U.S. crop yields while expanding measurements to other parts of the world.
"In the future, we hope to directly use this technology to monitor global food production, for example in China or Brazil, or even in your backyard," Guan said.
David Lobell is also deputy director of the Center on Food Security and the Environment, and William Wrigley Senior Fellow at the Freeman Spogli Institute for International Studies and the Stanford Woods Institute for the Environment. The study was also co-authored by Youngguan Zhang of the International Institute for Earth System Sciences at Nanjing University and the German Research Center for Geosciences (GFZ); Joanna Joiner of the NASA Goddard Space Flight Center Laboratory for Atmospheric Chemistry and Dynamics; Luis Guanter of GFZ; and Grayson Badgley of Stanford's Department of Earth System Science and Department of Global Ecology at the Carnegie Institution for Science.
CONTACTS:
p> Kaiyu Guan, Stanford School of Earth, Energy, & Environmental Sciences: kaiyug@stanford.edu
Laura Seaman, Stanford's Center on Food Security and the Environment: lseaman@stanford.edu, (650) 723-4920
