Pierre Martre

TL;DR: The authors systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 degrees C to 32 degrees C, including experiments with artificial heating.

TL;DR: Investigating the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales.

TL;DR: In this article, the authors present the largest standardized model intercomparison for climate change impacts so far, finding that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient.

TL;DR: Six complementary approaches are proposed, namely: optimizing developmental pattern to maximize spike fertility and grain number, optimizing spike growth to maximize grain number and dry matter harvest index, improving spike fertility through desensitizing floret abortion to environmental cues, and improving potential grain size and grain filling.

TL;DR: It is concluded that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics, and argued that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.