Multi-peril Pest Analysis

Agriculture is an intrinsically risky business. Farmers the world over deal with drought, hail, heat, and a plethora of pests and diseases that vary from location to location and year to year. Importantly, these production risks not only affect the livelihoods of farm families. They also have large downstream consequences for numerous and intricate local-to-global supply chains for food, feed and fiber.

The preponderance of prior food-security studies focus on the availability rather than the vulnerability of global food and feed supplies. Those scientific studies that did focus on the risks faced by farmers typically only looked at one risk factor at a time. But as a practical matter, crop breeders and farmers alike must make tradeoffs in dealing with all types of risks to maximize the productivity potential of the crops they are developing and growing. With these practical realities in mind, GEMS has a suit of modularize, flexible analytical workflows under construction that measure, model and assess the multi-peril risks confronting global agriculture.

Biotic Multi-peril Risk for Maize and Wheat

Maize and wheat are pivotal to sustaining the planet’s population, directly accounting for 5% and 18% of the world’s average per capita daily calorie intake respectively (and much more than that when the animal feed component of both crops, especially maize, is factored in).

Wheat tends to be a temperate crop, while maize is grown the world over, although the preponderance of both crops tend to concentrate in particular locales each subject to distinctive and varying risk exposures. Here we illustrate the application of our risk analytics to assess the worldwide, albeit spatially sensitive, multi-peril risk implications of 11 of the principal pest and diseases for maize and 13 for wheat.

Workflow—Agricultural Risk Analytics

The GEMShare platform enables the integration of different data elements, such as genomic, crop production and environmental data, into a data stack that is co-analyzable. Using GEMSTools, a workflow linking the interoperable data to our novel risk analytic methods substantially streamlines the data processing required to estimate (and validate) mutli-peril biotic risk measures at varying spatial and temporal scales.

Measuring Multi-peril Pest Risk

The maps below illustrate two applications of the pest risk analytics package in GEMSTools.

Relative Pest Risk in Present Production Areas

Here we map our assessment of the relative pest risk exposure (high to low) faced by farmers within the present extent of maize and wheat production.


A Portfolio of Maize and Wheat Pests and Diseases

Data and analysis workflow

  • Globally, areas with high maize output on average face lesser multi-peril pest occurrence risk than the overall global maize coverage.
  • Globally wheat growing areas generally face lesser multi-peril pest occurrence risk than maize growing areas.
  • Among the top 3 maize producing countries, the average acre in US and China face similar multi-peril maize risk, while in Brazil the average acre faces 3 time more multi-peril maize pest occurrence risk.
Relative Pest Risk Worldwide

The location of crop production has changed markedly over time (see Moving Matters Use Case). Consequently, where a particular crop is presently grown is not necessarily an indication of where that crop might be grown in the future.

Here we map our assessment of the relative pest risk exposure (rank ordered from “slightly risky” to “most risk”) for maize and wheat production worldwide, irrespective of the present footprint of wheat and maize production.

  • There is a tendency for low-income countries to be more exposed to maize and wheat multi-peril occurrence risk than high and upper middle-income countries due to their geographical location.
  • Globally low-income countries are on average exposed to twice as much maize multi-peril risk than high income countries.