Causes and implications of the unforeseen 2016 extreme yield loss in the breadbasket of France

TLDR

In 2016 France experienced its most severe wheat yield loss in over 50 years, highlighting a rising risk of compound extreme events that challenge existing farming and forecasting systems. A binomial logistic regression incorporating late‑autumn temperatures and spring precipitation successfully reproduces key yield loss events since 1959. Yield forecasting systems did not anticipate the 2016 loss, which stemmed from a novel compound extreme of warm autumns and wet springs, and climate projections indicate such conditions will become more common.

Abstract

In 2016, France, one of the leading wheat-producing and wheat-exporting regions in the world suffered its most extreme yield loss in over half a century. Yet, yield forecasting systems failed to anticipate this event. We show that this unprecedented event is a new type of compound extreme with a conjunction of abnormally warm temperatures in late autumn and abnormally wet conditions in the following spring. A binomial logistic regression accounting for fall and spring conditions is able to capture key yield loss events since 1959. Based on climate projections, we show that the conditions that led to the 2016 wheat yield loss are projected to become more frequent in the future. The increased likelihood of such compound extreme events poses a challenge: farming systems and yield forecasting systems, which often support them, must adapt.