How do various maize crop models vary in their responses to climate change factors?

TLDR

Mechanistic crop simulation models can be used to study the potential consequences of climate change on crop production, but it is unclear whether different maize models diverge in grain yield responses to climatic changes or agree on general trends in phenology, growth, and yield. The study presents the largest maize crop model intercomparison to date, aiming to analyze how simulated yields respond to temperature and atmospheric CO₂ changes across 23 models. The 23 models were evaluated at four diverse maize‑growing sites—Lusignan, France; Ames, USA; Rio Verde, Brazil; and Morogoro, Tanzania—to assess yield sensitivity to temperature and CO₂. The intercomparison revealed that while individual models varied widely in absolute yield predictions, an ensemble of a few models accurately simulated yields across all sites; temperature rise reduced yields by about 0.5 Mg ha⁻¹ per °C, whereas doubling CO₂ increased yields by ~7.5 % on average, making temperature the dominant driver of future maize yield changes, with substantial uncertainty in CO₂ responses that was unaffected by calibration detail.

Abstract

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2 ], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(-1) per °C. Doubling [CO2 ] from 360 to 720 μmol mol(-1) increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2 ] among models. Model responses to temperature and [CO2 ] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.