SIAM News Blog

Assessing Risks to Global Food Security

How Mathematicians Can Help

By James Case

The inaugural SIAM Conference on Mathematics of Planet Earth, held last September in Philadelphia, Pa., featured a public lecture by Molly Jahn of the University of Wisconsin, Madison (UW-Madison). Jahn, whose talk was entitled “Risks and Resilience in Global Food Systems: An Invitation for Mathematicians,” holds appointments in the Department of Agronomy, the Global Health Institute, and the Center for Sustainability and the Global Environment. She has served as dean of the university’s College of Agriculture and Life Sciences, director of the Wisconsin Agricultural Experiment Station, and Deputy and Acting Under Secretary of Research, Education, and Economics at the U.S. Department of Agriculture.

Jahn began her lecture by conceding that the current agricultural establishment (farmers, agribusinesses, and the agricultural research community) has been “stunningly successful” in improving agricultural productivity and efficiency. How else could we possibly be feeding a global population that has grown from under 2 billion to over 7 billion in the last century? She hastened to add, however, that the existing food delivery system is by no means ideal. It leaves some 800 million people undernourished, while 1.5 billion are overweight or obese. Meanwhile, estimates indicate that 1.4 billion tons of food are wasted each year. Though this is a small fraction of the total quantity produced, it is still significant – more than enough to feed the 1.4 billion people subsisting on $1.25 per day, or the 1.5 billion people who reside on degrading land. According to the Commission on Sustainable Agriculture and Climate Change (CSACC), more than 30 million acres of agricultural land are degraded each year due to overgrazing and other poor agricultural practices, climate change, groundwater depletion, urban sprawl, and additional human activities.

Cropland degradation, however, is not the only way in which current practices are overtaxing the planet. According to Jahn, the historic focus of research and intensive inputs on maximizing crop yield has obscured the extent and vulnerability of globalized and regionalized food delivery systems: large parts of the world no longer do—and presumably no longer can—feed themselves. Crop failures or food system interruptions, especially due to multiple major events in a single annual growing cycle in either North or South America, could bring large parts of Europe and Asia to the brink of starvation (see Figure 1). Interruption of ocean transport, a cyber disaster, or major telecommunication networks could do the same. How great, one wonders, are the risks of such disasters?

Figure 1. Main trade flows of corn, wheat, soybean complex, and palm oil. Image credit: Rabobank.

Food security is inalterably connected to other forms of security, including energy, water, physical (infrastructure), environmental, economic, and human (personal) security. New intelligence paradigms involving multiscale tools that distinguish between, for instance, slow and fast-moving trends are altering our understanding of these interconnections and the way that shocks propagate through the system.

The CSACC has issued a series of seven recommendations for achieving global food security. Some are fairly predictable, including #2: Significantly raise the level of global investment in sustainable agriculture and food systems in the next decade, and #4: Develop specific programmes and policies to assist populations and sectors that are most vulnerable to climate changes and food insecurity. However, Jahn focused on the last one, recommendation #7: Create comprehensive, shared, integrated information systems that encompass human and ecological dimensions [of agricultural and food systems].

Why, she asked, does this recommendation deserve special attention? To answer this question, Jahn presented two maps of India with brightly colored areas indicating irrigated lands. One map showed some 279 million acres of irrigated land, while the other displayed little more than half as many. Jahn said that the representations were from two mainstream institutions in the country, reinforcing the limitations of such visualizations. Which figure should be included in an integrated information system intended to inform the policy process?

Integrated (and interactive) near-real-time information systems already exist. Figure 2 shows the homepage of one such system, which can track production sites, transport vessels, weather conditions, infrastructure, and more. Yet it reflects only currently-available data, including dubious estimates of many important quantities and no estimates at all of some others.

Information concerning the demand for food is particularly fragmented and incomplete. Ultimately, displays like the one in Figure 2 will depict the flow of energy, including that of human beings, from place to place. Current available representations, however, fail to portray energy flows with sufficient clarity. Might it one day be possible to produce a dynamic and comprehensive display—akin to a weather map—of energy flows throughout the global food delivery system, with an indication of the level of uncertainty?

Figure 2. Near-real-time interactive maps track vessels, weather conditions, and infrastructure. Image credit: Thomson Reuters Eikon.

As matters stand, the world has a severely incomplete understanding of risks that could result in food system instability or breakdown. A number of unconventional partnerships have recently formed to address the issue – by assembling trustworthy bodies of information suitable for planning purposes and making them available to the public. Jahn spoke of a nascent collaboration between Oak Ridge National Laboratory and the International Maize and Wheat Improvement Center (better known by its Spanish acronym, CIMMYT), aided by Thomson Reuters’ platform Eikon and the Multi-Agency Collaboration Environment. She also mentioned the work of a group of insurance practitioners, who convened at Lloyd’s of London in 2015 to assess the cascade of impacts that could result from a plausible scenario (developed by the Jahn Research Group of UW-Madison, in conjunction with the U.K./U.S. Task Force on Resilience of the Global Food Supply Chain to Extreme Events) of a shock to the worldwide production of certain staple food crops. The group concluded that food insecurity will be among the largest risks to global society over the next ten years, and that climate change will be one of the most important supply-side drivers of that insecurity. They quantified the economic impact of the shock in question as follows: U.S. stocks lose 5% of their value, E.U. stocks lose 19% of their value, global rice production falls 7%, maize production falls 10%, soybean production falls 11%, and rice prices rise 500%.

These and related factors create both risk and opportunity for certain types of businesses. For example, food and beverage companies are painfully exposed to supply risks, which have grown with the extension of their supply chains. To reduce such risks, certain features of the global food delivery system will need to change. Global conditions will force governments to prohibit some currently-profitable activities, such as the depletion of fossil water reserves in the mighty (but non-regenerating) Ogallala Aquifer to grow grain for sale in Southeast Asia. In so doing, they will incur the wrath of those whose profits diminish, in league with a swarm of supply-side economists.

Mathematicians can help improve global food security by familiarizing themselves with economic models other than the “supply-side” model so favored by the Ronald Reagan administration. It differs in name only from the long-dominant “neoclassical model” of economic behavior. Jahn quoted Ha-Joon Chang, a gadfly in the economics profession, whose book [1] furnishes an eminently readable (if somewhat incomplete) guide to alternative schools of economic thought. Because the dominant model favors inaction in almost every circumstance, mathematicians can hasten Jahn’s “needed change” by contributing to the development of more reliable economic models. Yet the incorporation of unfamiliar models in the policy process will likely take decades.

A quicker way for mathematicians to enter the fray against food insecurity is by improving the quality and utility of available information through enhanced data mining techniques, the resolution of conflicting data, and interpolation where gaps occur. Though a great deal of information is already being collected in or near real time, much of it is fragmented and disorganized, possibly delaying recognition of credible threats. Even small contributions to the campaign against food insecurity could significantly impact human wellbeing.1

1 In a corresponding article entitled "Modeling Food Systems," Hans Kaper and Mary Lou Zeeman illustrate how mathematical and computational skills can help model food systems.

[1] Chang, H.-J. (2014). Economics: The User’s Guide. New York, NY: Bloomsbury Press.

James Case writes from Baltimore, Maryland.

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