Abstract: Increased climate variability and higher mean temperatures are expected across many world regions, both of which will contribute to more frequent extreme high temperatures events. Empirical evidence increasingly shows that short episodes of high temperature experienced around flowering can have large negative impacts on cereal grain yields, a phenomenon increasingly referred to as heat stress. Crop models are currently the best tools available to investigate how crops will grow under future climatic conditions, though the need to include heat stress effects has been recognized only relatively recently. We reviewed literature on both how key crop physiological processes and the observed yields under production conditions are impacted by high temperatures occurring particularly in the flowering and grain filling phases for wheat, maize and rice. This state of the art in crop response to heat stress was then contrasted with generic approaches to simulate the impacts of high temperatures in crop growth models. We found that the observed impacts of heat stress on crop yield are the end result of the integration of many processes, not all of which will be affected by a “high temperature” regime. This complexity confirms an important role for crop models in systematizing the effects of high temperatures on many processes under a range of environments and realizations of crop phenology. Four generic approaches to simulate high temperature impacts on yield were identified: (1) empirical reduction of final yield, (2) empirical reduction in daily increment in harvest index, (3) empirical reduction in grain number, and (4) semi-deterministic models of sink and source limitation. Consideration of canopy temperature is suggested as a promising approach to concurrently account for heat and drought stress, which are likely to occur simultaneously. Improving crop models’ response to high temperature impacts on cereal yields will require experimental data representative of field production and should be designed to connect what is already known about physiological responses and observed yield impacts. (C) 2014 Elsevier B.V. All rights reserved.

Abstract: The frequency and intensity of extreme high temperature events are expected to increase with climate change. Higher temperatures near anthesis have a large negative effect on maize (Zea mays, L.) grain yield. While crop growth models are commonly used to assess climate change impacts on maize and other crops, it is only recently that they have accounted for such heat stress effects, despite limited field data availability for model evaluation. There is also increasing awareness but limited testing of the importance of canopy temperature as compared to air temperature for heat stress impact simulations. In this study, four independent irrigated field trials with controlled heating imposed using polyethylene shelters were used to develop and evaluate a heat stress response function in the crop modeling framework SIMPLACE, in which the Lintul5 crop model was combined with a canopy temperature model. A dataset from Argentina with the temperate hybrid Nidera AX 842 MG (RM 119) was used to develop a yield reduction function based on accumulated hourly stress thermal time above a critical temperature of 34 degrees C. A second dataset from Spain with a FAO 700 cultivar was used to evaluate the model with daily weather inputs in two sets of simulations. The first was used to calibrate SIMPLACE for conditions with no heat stress, and the second was used to evaluate SIMPLACE under conditions of heat stress using the reduction factor obtained with the Argentine dataset. Both sets of simulations were conducted twice; with the heat stress function alternatively driven with air and simulated canopy temperature. Grain yield simulated under heat stress conditions improved when canopy temperature was used instead of air temperature (RMSE equal to 175 and 309 g m(-2), respectively). For the irrigated and high radiative conditions, raising the critical threshold temperature for heat stress to 39 degrees C improved yield simulation using air temperature (RMSE: 221 gm(-2)) without the need to simulate canopy temperature (RMSE: 175 gm(-2)). However, this approach of adjusting thresholds is only likely to work in environments where climatic variables and the level of soil water deficit are constant, such as irrigated conditions and are not appropriate for rainfed production conditions. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: Despite widespread application in studying climate change impacts, most crop models ignore complex interactions among air temperature, crop and soil water status, CO2 concentration and atmospheric conditions that influence crop canopy temperature. The current study extended previous studies by evaluating Tc simulations from nine crop models at six locations across environmental and production conditions. Each crop model implemented one of an empirical (EMP), an energy balance assuming neutral stability (EBN) or an energy balance correcting for atmospheric stability conditions (EBSC) approach to simulate Tc. Model performance in predicting Tc was evaluated for two experiments in continental North America with various water, nitrogen and CO2 treatments. An empirical model fit to one dataset had the best performance, followed by the EBSC models. Stability conditions explained much of the differences between modeling approaches. More accurate simulation of heat stress will likely require use of energy balance approaches that consider atmospheric stability conditions.