How climate change is already affecting global food production

How climate change is already affecting global food production
© iStock/smolaw11

The University of Minnesota’s Institute on the Environment has used high resolution global crop statistics to identify how climate change is affecting global food production already.

The high resolution crop statistics indicate which geographical areas and crops are most at risk and how global food production could continue to be affected.

Global food production

The world’s top ten crops supply 83 percent of all calories produced on cropland combined. These are:

  • Barley;
  • Cassava;
  • Maize;
  • Oil palm;
  • Rapeseed;
  • Rice;
  • Sorghum;
  • Soybean;
  • Sugarcane; and
  • Wheat.

Climate change has already affected the production of these key sources of global food. The lead author Deepak Ray, from the University of Minnesota’s Institute on the Environment, commented: “The research documents how change is already happening, not just in some future time.”

Ray explained: “There are winners and losers, and some countries that are already food insecure fare worse.”

How climate change is affecting yields

The researchers reported that:

•”Observed climate change causes a significant yield variation in the world’s top 10 crops, ranging from a decrease of 13.4 percent for oil palm to an increase of 3.5 percent for soybean, and resulting in an average reduction of approximately one percent (-3.5 X 10e13 kcal/year) of consumable food calories from these top 10 crops;”

• “Impacts of climate change on global food production are mostly negative in Europe, Southern Africa, and Australia, generally positive in Latin America, and mixed in Asia and Northern and Central America;”

• “Half of all food-insecure countries are experiencing decreases in crop production — and soare some affluent industrialized countries in Western Europe;” and

• “Contrastingly, recent climate change has increased the yields of certain crops in some areas of the upper Midwest United States.”

The co-author Snigdhansu Chatterjee of the University of Minnesota’s School of Statistics, added: “This is a very complex system, so a careful statistical and data science modelling component is crucial to understand the dependencies and cascading effects of small or large changes.”

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