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Low-intensity tillage has become more popular among farmers in the United States and many other regions. However, accurate data on when and where low-intensity tillage methods are being used remain scarce, and this scarcity impedes understanding of the factors affecting the adoption and the agronomic or environmental impacts of these practices. In this study, we used composites of satellite imagery from Landsat 5, 7, and 8, and Sentinel-1 in combination with producer data from about 5900 georeferenced fields to train a random forest classifier and generate annual large-scale maps of tillage intensity from 2005 to 2016. We tested different combinations of hyper-parameters using cross-validation, splitting the training and testing data alternatively by field, year, and state to assess the influence of clustering on validation results and evaluate the generalizability of the classification model. We found that the best model was able to map tillage practices across the entire North Central US region at 30 m-resolution with accuracies spanning between 75% and 79%, depending on the validation approach. We also found that although Sentinel-1 provides an independent measure that should be sensitive to surface moisture and roughness, it currently adds relatively little to classification performance beyond what is possible with Landsat. When aggregated to the state level, the satellite estimates of percentage low- and high-intensity tillage agreed well with a USDA survey on tillage practices in 2006 (R2 = 0.55). The satellite data also revealed clear increases in low-intensity tillage area for most counties in the past decade. Overall, the ability to accurately map spatial and temporal patterns in tillage should facilitate further study of this important practice in the United States, as well as other regions with fewer survey-based estimates.

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Remote Sensing of Environment
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George Azzari
Patricio Grassini, Juan Ignaci, Rattalino Edreira, Shawn Conley, Spyridon Mourtzinis
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Michelle Horton (221293)
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By comparing historical temperature and suicide data, researchers found a strong correlation between warm weather and increased suicides. They estimate climate change could lead to suicide rate increases across the U.S. and Mexico.

Suicide rates are likely to rise as the earth warms, according to new research published July 23 in Nature Climate Change. The study, led by Stanford economist Marshall Burke, finds that projected temperature increases through 2050 could lead to an additional 21,000 suicides in the United States and Mexico.

“When talking about climate change, it’s often easy to think in abstractions. But the thousands of additional suicides that are likely to occur as a result of unmitigated climate change are not just a number, they represent tragic losses for families across the country,” said Burke, assistant professor of Earth system science in the School of Earth, Energy & Environmental Sciences at Stanford.

Researchers have recognized for centuries that suicides tend to peak during warmer months. But, many factors beyond temperature also vary seasonally – such as unemployment rates or the amount of daylight – and up to this point it has been difficult to disentangle the role of temperature from other risk factors.

“Suicide is one of the leading causes of death globally, and suicide rates in the U.S. have risen dramatically over the last 15 years. So better understanding the causes of suicide is a public health priority,” Burke said.

Heat and suicide

To tease out the role of temperature from other factors, the researchers compared historical temperature and suicide data across thousands of U.S. counties and Mexican municipalities over several decades. The team also analyzed the language in over half a billion Twitter updates or tweets to further determine whether hotter temperatures affect mental well-being. They analyzed, for example, whether tweets contain language such as “lonely,” “trapped” or “suicidal” more often during hot spells.

The researchers found strong evidence that hotter weather increases both suicide rates and the use of depressive language on social media.

“Surprisingly, these effects differ very little based on how rich populations are or if they are used to warm weather,” Burke said.

For example, the effects in Texas are some of the highest in the country. Suicide rates have not declined over recent decades, even with the introduction and wide adaptation of air conditioning. If anything, the researchers say, the effect has grown stronger over time.

Effect of climate change

To understand how future climate change might affect suicide rates, the team used projections from global climate models. They calculate that temperature increases by 2050 could increase suicide rates by 1.4 percent in the U.S. and 2.3 percent in Mexico. These effects are roughly as large in size as the influence of economic recessions (which increase the rate) or suicide prevention programs and gun restriction laws (which decrease the rate).

Graph Showing Effects of historical temperature changes on suicide rates are shown for the U.S. and Mexico. Effects of historical temperature changes on suicide rates are shown for the U.S. and Mexico. (Image credit: Marshall Burke)
Effects of historical temperature changes on suicide rates are shown for the U.S. and Mexico. (Image credit: Marshall Burke)

“We’ve been studying the effects of warming on conflict and violence for years, finding that people fight more when it’s hot. Now we see that in addition to hurting others, some individuals hurt themselves. It appears that heat profoundly affects the human mind and how we decide to inflict harm,” said Solomon Hsiang, study co-author and associate professor at the University of California, Berkeley.

The authors stress that rising temperature and climate change should not be viewed as direct motivations for suicide. Instead, they point out that temperature and climate may increase the risk of suicide by affecting the likelihood that an individual situation leads to an attempt at self-harm.

“Hotter temperatures are clearly not the only, nor the most important, risk factor for suicide,” Burke emphasized. “But our findings suggest that warming can have a surprisingly large impact on suicide risk, and this matters for both our understanding of mental health as well as for what we should expect as temperatures continue to warm.”

Marshall Burke is also a fellow at the Center on Food Security and the EnvironmentStanford Woods Institute for the EnvironmentFreeman Spogli Institute for International Studies, and Stanford Institute for Economic Policy Research. Solomon Hsiang is also a faculty research fellow at the National Bureau of Economic Research. Other Stanford co-authors include Sanjay Basu, assistant professor of medicine, and Sam Heft-Neal, research scholar at the Stanford Center on Food Security and the Environment. Additional co-authors are from Pontificia Universidad Católica de ChileVancouver School of Economics, and the University of California, Berkeley. The research was partially supported by the Stanford Woods Institute for the Environment.

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Linkages between climate and mental health are often theorized, but remain poorly quantified. In particular, it is unknown whether the rate of suicide, a leading cause of death globally, is systematically affected by climatic conditions. Using comprehensive data from multiple decades for both the United States and Mexico, we find that suicide rates rise 0.7% in US counties and 2.1% in Mexican municipalities for a 1 °C increase in monthly average temperature. This effect is similar in hotter versus cooler regions and has not diminished over time, indicating limited historical adaptation. Analysis of depressive language in > 600 million social media updates further suggests that mental well-being deteriorates during warmer periods. We project that unmitigated climate change (RCP8.5) could result in a combined 9–40 thousand additional suicides (95% confidence interval) across the United States and Mexico by 2050, representing a change in suicide rates comparable to the estimated impact of economic recessions, suicide prevention programs or gun restriction laws.

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Nature Climate Change
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Marshall Burke
Felipe González
Sam Heft-Neal
Ceren Baysan, Sanjay Basu, and Solomon Hsiang
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Walter P. Falcon
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Walter Falcon, the Helen Farnsworth Professor of International Agricultural Policy in Economics (emeritus), writes from an unusual perspective. During the academic year he serves as a senior fellow with the Freeman Spogli Institute for International Studies and the Stanford Woods Institute for the Environment. He spends the summers on his family farm near Marion, Iowa. He returns to campus each year with reflections on the challenges and rewards of faming life in his "Almanac Report." Falcon is former deputy director of the Center on Food Security and the Environment. 

September means that it is time again for my annual Iowa farm report, the sixth edition in this series. As readers of prior postings will remember, my day job is Professor of International Agricultural Policy at Stanford University. However, my wife and I also own a 200-acre farm near Marion, Iowa, where we spend summers watching over corn, soybean, and alfalfa fields, and gazing out at a growing cow-calf herd.

After all these years, it is still difficult for me to describe the differences in pace, politics, and age structure in Iowa relative to California. I am now 81, and at Stanford I feel ancient; in Iowa, I am just one of the boys, since 41 percent of farm owners are 75 or older. 

This summer’s weather, especially rainfall, has been almost perfect for crops in our area. Although western Iowa and the northern Great Plains experienced drought, we are expecting record yields of both corn and soybeans, possibly reaching 225 and 55 bushels per acre, respectively. Unfortunately, December corn prices are only about $3.50 per bushel. This level is just half of what it was five years ago. The old adage that farmers should raise more hell and less corn has taken on new meaning. Average prices of Iowa farmland have slipped from about $9,000 to $7,000 per acre during the past five years (though still remarkably high relative to the $2,000 that prevailed in 2000). Renters of land are also feeling price pressures. Average cash rents have fallen about 10 percent over the past two years and now average about $230 per acre in our part of the state.

The difference between the “almost perfect” weather described above and an absolute disaster measured about three miles this year. During much of June, our area was hit with very unstable air. The worst episode was on June 28 when an EF-2 tornado came barreling right at our farm. The picture below was taken out of the west window before we scampered down to the safe room in our basement. At the last minute, the tornado veered slightly, going just between our farm and the bustling county fair (also shown) four miles to the north. The tornado then touched down a few miles to our east, crushed the historic Brown farm, and mostly destroyed the small town of Prairieburg. Amazingly, both our farm and the fair were completely spared except for a few broken tree limbs.

There is an interesting footnote on risk to this story. When I show the tornado picture to my California friends they cannot understand why I would live in such a risky place; however, my Iowa friends frequently remark that they cannot comprehend how I can live in the risky state of California with its earthquakes. Risk, like beauty, is sometimes in the eyes of the beholder.

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Photo: Karla Hogan (just to the west of our house)

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Photo: David Roll (fair)

Not everything from the sky was bad this year, although one other episode also turned out to be a non-event. Our region was to have had 90 percent coverage during the eclipse. We were completely socked in by clouds, however, and could see absolutely nothing on this historic occasion. On the other hand, airplane applications of fungicides and pesticides were greater than I can ever remember. A combination of new weeds to the region (water hemp and Palmer amaranth) and growing weed resistance in Roundup-ready soybeans are causing increased problems for farmers. As for the applicators, I never cease to be impressed by the skill (craziness?) of those pilots who fly at 50 feet or less, dodging power lines, while managing controls of the spray equipment as well as the plane.

Describing another “sky” event at the farm requires that I first remove considerable amounts of egg from my face. Stanford sits in the middle of Silicon Valley, and over the past decade perhaps a dozen firms have visited my office regarding agricultural applications. Particularly in the earlier years, I assured them that precision agriculture was overrated and that drones would never have a place in agriculture. Those were not among my better forecasts!

My conjecture is that more than 90 percent of the fields in Iowa have now been laid out with GPS grid maps that permit automatic steering of tractors and harvesters. Famers rarely steer or look ahead; rather they mostly look backward at planters and other equipment. From gauge-filled cabs that resemble cockpits, farmers monitor yields, seed-planting rates, and fertilizer applications in ways that produce field maps for each 10x10 meter sub-plot. In some sense, producers already have more data than they can assimilate, so one could reasonably ask, can drones really help? It turns out that they can, and they can do so for only a small investment.

The high quality drone shown below, complete with two 30-minute batteries, costs about $2,000, with quality determined mostly by the precision of its camera. (That sum may not be petty cash, but it is not in the same league as a $600,000 combine-harvester either.) For mapping work, drones are connected to an off-site service center that costs about $100 per month. They produce video in real-time, snap images as well, and are proving useful in determining if the number of emergent plants (really the lack of plants) on areas that may require replanting; in checking fields for “wet spots” after rains for indicators of future tiling needs; and watching the cow herd from the back porch, as is also shown below. Applications are ever underway that can take the temperatures of animals via intricate heat-sensing devices.

Once corn grows to chest high, it is impossible to walk or drive through fields to isolate areas with particular weed problems or to view pest damage. These drones are also tied in with GPS systems, so that entire fields can be mapped “automatically” at very high resolution. A 100-acre field can be mapped within the 25 minutes of a single battery-powered flight. (The further good news is that the machines are smart enough to return to their takeoff point before losing power.) Drones seem to be here to stay because they save labor, generate useful data, and help improve farm-management practices

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Photo: Margaret Meythaler (drone demo)

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Photo: Mitch Meythaler (field map by drone—August 5th corn plant health (potential yield); red is low, green is high; dark red areas are waterways and fence rows; sandy soils show red to the north, and red streaks indicate water erosion.)

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Photo: Mitch Meythaler (part of cow herd by drone)

Drones, however, have not affected my image of the old limestone “restaurant” where neighborhood farmers gather about 8 a.m. Most of the “action” is around the big table where truly terrible coffee is self-served. Payment is on the honor system, since there is rarely a waitress around. Maybe it was just my imagination, but farmer discussions seemed more somber and narrower this year, despite the good weather. Perhaps it is the third successive year of low prices, or the uncertainty about corn exports to Mexico and China, or the general chaos in Washington, D.C. Perhaps it also reflects the ethnic and religious homogeneity of the local population. Stanford’s undergraduate student body, for example, is only 45 percent white. However, during the course of all of my personal interactions during four months in Iowa, I encountered only three minority persons – two medical doctors at the local hospital whose families came from India, and one African-American. Homogeneity and diversity make for different worldviews and different conversations – neither being necessarily better or worse, but certainly different.

The most animated discussion I participated in concerned technology gone astray. Large chemical companies, such as Monsanto and DuPont, have purchased many seed companies, thereby assuring markets for their particular brand of chemicals. In the case of corn, for example, a particular GMO variety has been bred such that, when sprayed by a particular brand, all plants are killed except for the corn. Spraying these herbicides requires training and specialized equipment, and herbicide applications are frequently hired – typically for about $8 per acre, plus the cost of chemicals. As part of the new technology, the specific corn variety and the particular brand of spray are entered into the software that then uses GPS maps to control the actual spraying. But what happens when the hired vendor, in this case a local co-operative, enters the wrong variety into the computer, as happened to two of our neighbors? The spray killed the weeds, but it also killed the corn. At that point, it was too late in the season to replant. These fields were sorry looking messes, and the debate still continues as to who is liable and for how much.

Another hot button item this year centered on the purchase of farmland for housing developments. Farmers almost universally regard such investments as unwarranted intrusions into their space. (The proposed relocation of the county landfill generated even more vehement responses.) The housing argument typically took two forms: more houses mean more children and therefore higher property taxes for schools; and theses houses take “all of the good Iowa farmland”, which is needed to feed the world. There is some correctness to the former argument, but as to the latter assertion – not so much. I argued that for the last five years, total acres of corn and soybeans in Iowa had trended upward rather than downward, and that furthermore, both current and future problems of hunger were driven primarily by poverty, not the lack of corn and soybean supplies. This comment was not regarded as being helpful to the coffee-crowd discussion!

Politics are rarely discussed in these conversations – at least in my presence. However, I sense several things. Although Iowans voted for Donald Trump, I think it was because they generally disliked him less than they disliked Hilary Clinton. Most of my neighbors now simply seem embarrassed by what is happening. My California friends continue to ask me about what Iowans think and what they believe in. There is not much open discussion about these matters either, which made a July poll of the Des Moines Register all the more interesting. When given a choice of 17 options of whom they believed, the top six in order were: the armed forces, God, the Iowa Department of Natural Resources, local schools, the Farm Bureau, and the FBI. The three options they believed in least, also in order from the bottom, were the U.S. Congress, the media, and the President. I do not know what a comparable survey in California would look like, but I believe that it would be considerably different.

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Photo: Daryl Hamey (2016 calves — the red heifer is now bred, and the black baldy steer is now in the freezer!)

At the end of last year’s report, I left readers hanging with the question of whether our seemingly disinterested yearling bull would produce a crop of calves. It turns out that my fears were misplaced, and that he was indeed working the night shift. Our problems were in fact on the female side—our best cow did not conceive, and another of our good cows produced a sickly calf that ended up being bottle-fed by my wife. To compete the story, we again rented a red Angus bull – the same one in fact that we had last year – and he is now a much larger two-year old. But he is still no competition for “Upward”, the strangely named Angus super-bull winner at the Iowa State Fair that weighed 2,798 pounds.

I leave in a week for yet another year of teaching and research at Stanford. I have only a limited number of lectures scheduled, and most of my time will be directed toward research on the growing importance of tropical vegetable oils, particularly from oil palm in Indonesia. Palm oil has recently replaced soybean oil as the most important in world commerce, so even when I am in California, there remain important and unusual Iowa connections.

My neighbor says that I must leave Iowa soon – because of the upcoming weather. In true Almanac fashion, he confidently predicts an early and harsh winter ahead. His evidence – the deer are weaning their young at an early date, and are busy consuming great quantities of corn from our fields, so as to layer on fat for the winter. We might even be able to see the extent of their gluttony on our autumn yield maps!

 

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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.

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Remote Sensing of Environment
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David Lobell
Jin Wu, John S.Kimball, Marth C. Anderson, Steve Frolking Bo Li, Christopher Hain
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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.

 

 

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Remote Sensing of Environment
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George Azzari
David Lobell
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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.

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Environmental Research Letters
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Sam Heft-Neal
David Lobell
Marshall Burke
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The future trajectory of crop yields in the United States will influence food supply and land use worldwide. We examine maize and soybean yields for 2000–2015 in the Midwestern U.S. using a new satellite-based dataset on crop yields at 30m resolution. We quantify heterogeneity both within and between fields, and find that the difference between average and top yielding fields is typically below 30% for both maize and soybean, as expected in advanced agricultural regions. In most counties, within-field heterogeneity is at least half as large as overall heterogeneity, illustrating the importance of non-management factors such as soil and landscape position. Surprisingly, we find that yield heterogeneity is rising in maize, both between and within fields, with average yield differences between the best and worst soils more than doubling since 2000. Heterogeneity trends were insignificant for soybean. The findings are consistent both with recent adoption of precision agriculture technologies and with recent trends toward denser sowing in maize, which disproportionately raise yields on better soils. The results imply that yield gains in the region are increasingly derived from the more productive land, and that sub-field precision management of nutrients and other inputs is increasingly warranted.

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Environmental Research Letters
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David Lobell
George Azzari
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The potential impacts of climate change on crop productivity are of widespread interest to those concerned with addressing climate change and improving global food security. Two common approaches to assess these impacts are process-based simulation models, which attempt to represent key dynamic processes affecting crop yields, and statistical models, which estimate functional relationships between historical observations of weather and yields. Examples of both approaches are increasingly found in the scientific literature, although often published in different disciplinary journals. Here we compare published sensitivities to changes in temperature, precipitation, carbon dioxide (CO2), and ozone from each approach for the subset of crops, locations, and climate scenarios for which both have been applied. Despite a common perception that statistical models are more pessimistic, we find no systematic differences between the predicted sensitivities to warming from process-based and statistical models up to +2 °C, with limited evidence at higher levels of warming. For precipitation, there are many reasons why estimates could be expected to differ, but few estimates exist to develop robust comparisons, and precipitation changes are rarely the dominant factor for predicting impacts given the prominent role of temperature, CO2, and ozone changes. A common difference between process-based and statistical studies is that the former tend to include the effects of CO2 increases that accompany warming, whereas statistical models typically do not. Major needs moving forward include incorporating CO2 effects into statistical studies, improving both approaches' treatment of ozone, and increasing the use of both methods within the same study. At the same time, those who fund or use crop model projections should understand that in the short-term, both approaches when done well are likely to provide similar estimates of warming impacts, with statistical models generally requiring fewer resources to produce robust estimates, especially when applied to crops beyond the major grains.

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Environmental Research Letters
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David Lobell
Senthold Asseng
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