Complex models now assess the impact of climate change on global food production. The Results Are ‘Alarming’

Inside dozens of bankers boxes, stacked high in a storage locker in New York City, Cynthia Rosenzweig has stashed the work of decades: Legal pads covered in blue-inked cursive with doodles in the margins, file folders marked “potato,” graph paper with notations of rainfall in Nebraska and Kansas.

Rosenzweig has worked at NASA’s Goddard Institute for Space Studies (GISS) at Columbia University since the 1980s, when researchers were delving deeper into the growing science demonstrating that human activity is warming the planet. Rosenzweig was an agronomist and began to wonder what the changing climate would mean for crops.

Her first published work, an obscure paper showing that North American wheat growers would be more northerly if carbon dioxide levels were higher, is among the thousands of pages she has stashed. Rosenzweig was a pioneer in the use of simulation models to examine the specific effects of climate change on agriculture.

The idea of climate change was only emerging in the public consciousness at the time. Rosenzweig’s boss at NASA, James Hansen, was about to tell Congress, in seminal testimony, about the looming perils of the warming planet. Rosenzweig sent Hansen a note in his characteristic pluck before the hearing to inform him that scientists were overlooking an important threat. 

“We needed to model CO2 and precipitation,” she recalled in a recent interview. “We needed to understand the full impact of climate change on food.”

At the time, there was scant research on the intersection of climate change and agriculture, and what did exist—including Rosenzwieg’s own work—suggested that rising levels of carbon dioxide could have a “fertilizing” effect on some plants. That finding would ultimately become an enduring point in the effort to undermine climate science broadly—a “positive” seized upon by politicians and industry lobbyists as they sought to minimize the climate emergency.

However, as climate and crop modeling developed, the models began to point out more concerning possible outcomes. Millions of people could die if crops fail, especially in multiple breadbasket regions, as some models suggested.   

And while famine and malnutrition are complicated problems, in the decades since these models began to examine the projected impact of global warming on food production, it’s become increasingly clear that climate change is a “threat multiplier,” making hunger emergencies worse. It could be the primary reason in some cases. 

Nearly 1 Billion people were malnourished or went hungry last year, and that number is expected to rise in 2018. 

Prompted in part by Rosenzweig’s work, a growing cadre of researchers started looking at combinations of other variables—including rain, soil quality, fertilizers, pests, carbon dioxide levels, crop varieties. The data improved. The models became more sophisticated. These scientists eventually began to work together. 

In 2008, at a conference in Florida on water use in farming, Rosenzweig began to round up fellow scientists for what would eventually become the world’s biggest and most ambitious joint modeling effort to understand how climate change jeopardizes the agricultural systems that humans depend on for survival. 

Four years later, AgMIP researchers published their first major paper.

The research that the models “agreed” that the detrimental effects from climate change—mostly in developing countries around the planet’s midsection where more extreme weather events could batter crops—would be worse than previous research had suggested. It also highlighted that the results were not certain.

After six years of research, AgMIP researchers now have the ability to confirm their findings. Their Latest major papers which rests on improved models and updated climate data, projects a more alarming picture—one that will appear even sooner.

“More crops are predicted to react negatively,” said Jonas Jägermeyr, the lead author of the paper, which was published late last year in Nature Food.

Jägermeyr, a crop modeler and climate scientist, also at GISS, noted that the projected yields of corn dropped by more than 20 percent globally compared to current production levels. “That’s a completely new realm,” he said. “Across the world and in many bread basket regions, this is going to occur in the next couple years. The main message here is: This is right around the corner.”

The most recent major report by the Intergovernmental Panel on Climate Change, published in February, found that climate change has already lowered crop productivity  in vulnerable regions in the tropics. It also relied upon the AgMIP research to conclude that more food security crises would occur sooner and more often.

“Without these models it’s almost impossible to conclude anything,” said Toshihiro Hasegawa, who co-authored the IPCC report’s chapter on food security. 

Noting that the AgMIP modelers looked at roughly 8,000 simulations, Hasegawa said, “that gives us a better confidence.”

But even though researchers are increasingly confident that crop yields will falter, they say there’s a lot of work to be done in the modeling discipline. The world’s population will hit 10 billion people in 2050 when hotter temperatures and increased flooding will make feeding them more challenging. Knowing when and where the declines will happen—getting a full view of the risks—will be critical to preventing famine and malnutrition. 

“Modeling is essentially a way of creating transparency. In essence it gives us a view of something that we wouldn’t be able to see and couldn’t quantify without models,” said Molly Jahn, a plant geneticist, then a deputy secretary at the USDA, now at the Defense Advanced Research Project Agency (DARPA). “These models are not necessarily the right kind of models to do risk modeling.”

Food insecurity is a complex problem. It is not only a result of drops in yields from major crops but also of politics, governance, and economics. It is becoming more complex and urgent due to climate change. The current models don’t account for all these factors yet.

Joshua Elliott, a DARPA program manger who specializes in complex modeling, is one of the many researchers working to develop a new crop modeling system. This model goes beyond crop yield projections, and considers other factors like political conflict and population flows.

“Our goal is to be able to improve the models,” Elliott said. “There’s just a massive amount of uncertainty. These are incredibly complex problems.”

The United Nations declared January 283 Million people were in the country last year. in 80 countries went hungry or were at high risk of going hungry—a record number—and more than 800 million were malnourished. Humanitarian aid groups warned that 2022 will see an increase in hunger emergencies. Increasingly likely. 

The models can’t yet say where or how much.

Getting serious about crop research, modeling, and other agricultural issues

If there’s a point at which the relatively esoteric Science of cropModeling moved beyond its discipline. It was in the 1970s, decades before AgMIP. The Soviet Union made a big deal to purchase billions of dollars worth of U.S. Wheat at low prices due to government subsidies.

U.S. negotiators at the time hadn’t realized that the Soviet Union’s wheat crops had failed and the deal took them by surprise, causing wheat shortages and a global price spike. 

After the “Great Grain Robbery,” as it was dubbed, the U.S. government started getting more serious about crop research and modeling in particular.  

Most projections up to this point were based on mathematical or statistical models, which looked at historical yields. After the Russian grain purchase, however, the government created models that were based on remote satellite sensing and could make strategic forecasts regarding crop yields. 

Over the next 20 years, interest in crop modelling grew.  

“The heyday was in the ‘80s and ‘90s,” said David Fleisher, an agricultural engineer with the USDA who helps develop crop models. “There was tremendous development.”

Jerry Hatfield is a long-standing USDA researcher who was also the original AgMIP cofounder. He remembers the moment in 1990 when the IPCC published the first international report on climate change.

“The IPCC originally came out and focused on rising CO2 levels and crop productivity and made a statement that all crops love CO2 so there won’t be a problem,” Hatfield said. “A lot of us sat around thinking: Let’s look at this system a little more holistically.”

Agricultural modeling needed a global approach—like the one the IPCC was taking for climate change writ large, the group of researchers concluded. In order to understand how climate change could shift or reduce the planet’s food supply, they needed to compare all the various models out there and, ultimately, improve them to get a clearer picture of the future.

“The results were too helter-skelter,” Rosenzweig said. “Different groups and scientists were saying, ‘We’re doing this scenario and we’re doing this baseline and we’re doing these projections and this model and that model.’ The IPCC was having a very hard time assessing the results of all those findings.”

The idea behind AgMIP was to put all the models into a harmonized “ensemble” and then feed them the same inputs (or data points) and parameters. 

“We found there wasn’t any single model that could help us predict what was happening in terms of productivity,” Hatfield said. “But if you took an ensemble of models—about 10 at a time—and you take the averages, they start to tell you something.”

Like the IPCC climate models, these crop models “talk” to each other.

“AgMIP was conceived to do for agriculture modeling” what these climate models did, said Sonali McDermid, a professor of environmental studies at New York University and an AgMIP researcher “The big IPCC reports that come out every four years—the science in those are informed by the [climate modeling] project that brings together all the world’s climate models, developed independently, and compares them.” 

These climate models are used by AgMIP layers, which use their projections to approximate the same for agriculture. The AgMIP researchers published a study last November that showed greater certainty that major crops would see lower yields. However, northern latitudes may see a rise in wheat yields in the near future. The increased heat can cause harvest damage and yield declines in some regions.

“Once you execute all these models, you get a prediction, and this prediction is alarming,” said Bruno Basso, a professor of earth and environmental sciences at Michigan State University who specializes in crop and modeling research. “The threat is immense.”

But the AgMIP research, at least so far, doesn’t tell the whole story. It doesn’t yet account for steps farmers could take to adapt to changing climates, nor does it factor in economic incentives that could help push farmers to change their farming practices. Researchers note that more research is being done.

“The thing about AgMIP that was transformative is, we were looking at models in the same way that a meteorologist would look at the path of a hurricane. You have a line,” said Lew Ziska, a former USDA plant physiologist, now a professor at Columbia University. “But when you put these models together, you get a much better forecast. That’s exactly what AgMIP does with respect to climate and food. That’s the good side of the coin.”

But, Ziska added, “the areas that need further elucidation are: What’s going to happen to food nutrition, what’s going to happen in terms of contamination of food, how might climate change affect pathogens. There is strong evidence that climate change will negatively affect pesticides. It’s a good first step, but it isn’t a full description of all the challenges that need to be met.”

Some critics They also suggested that smaller-scale, statistical models—those based on historical crop yield, rather than projections made via simulations and supercomputing—are more useful because they You will get results quickerThese are less expensive.  Others That is what you should say AgMIP uses a variety of global models don’t fully captureThe effects of climate change upon wheat and rice

Even the AgMIP research found that yields of rice and soybeans drop in some regions, but that the models don’t “agree” on the overall global impact.

Rosenzweig is acutely aware of these limitations. “The ‘I’ is for improvement,” she jokes, referring to the AgMIP acronym.

There are important next-steps. “What we really need at this point is to link the people out in the field, who know what’s going on in their region and the location realities, with the somewhat disconnected global climate communities and modeling community,” Jägermeyr, lead author of AgMIP’s latest paper, said. 

Other researchers agree. 

“It’s no good just running models and publishing results, or even communicating results to policy/society/industry,” Andrew Challinor, a professor at the University of Leeds and crop modeler, wrote in an email. “The stakeholders need to be involved right from the start.”

One major worry in the research community is about climate-induced “food shocks”—a sudden loss of a harvest that brings on a food shortage—that are more difficult to predict than the more gradual decline in crop yields that AgMIP has so far focused on.  

“In addition to the challenge of producing enough food on a global scale in 2050, we’re also going to be looking at a climate where we have much more year-to-year variability and we’re going to face a lot more agricultural production shocks in a lot of countries,”  said Chris Funk, director of the Climate Hazards Center at the University of California, Santa Barbara. “We used to have one crisis a year. Now we’re having three or four serious crises at the same time.”