Attempts to measure the impacts of climate change on agriculture must invariably rely on models that translate changes in climate to changes in agricultural outcomes. This need for models exists even when assessing the impacts of climate trends that have already occurred, since simultaneous changes in other factors that affect agriculture, such as technologies and government policies, preclude direct observations of impacts. Over several decades, many approaches to developing these models have evolved, with most falling into one of two camps.

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%.