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Webber, H., White, J. W., Kimball, B. A., Ewert, F., Asseng, S., Rezaei, E. E., et al. (2018). Physical robustness of canopy temperature models for crop heat stress simulation across environments and production conditions. Field Crops Research, 216, 75–88.
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.
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Webber, H., Martre, P., Asseng, S., Kimball, B., White, J., Ottman, M., et al. (2017). Canopy temperature for simulation of heat stress in irrigated wheat in a semi-arid environment: A multi-model comparison. Field Crops Research, 202, 21–35.
Abstract: Even brief periods of high temperatures occurring around flowering and during grain filling can severely reduce grain yield in cereals. Recently, ecophysiological and crop models have begun to represent such phenomena. Most models use air temperature (Tair) in their heat stress responses despite evidence that crop canopy temperature (Tc) better explains grain yield losses. Tc can deviate significantly from Tair based on climatic factors and the crop water status. The broad objective of this study was to evaluate whether simulation of Tc improves the ability of crop models to simulate heat stress impacts on wheat under irrigated conditions. Nine process-based models, each using one of three broad approaches (empirical, EMP; energy balance assuming neutral atmospheric stability, EBN; and energy balance correcting for the atmospheric stability conditions, EBSC) to simulate Tc, simulated grain yield under a range of temperature conditions. The models varied widely in their ability to reproduce the measured Tc with the commonly used EBN models performing much worse than either EMP or EBSC. Use of Tc to account for heat stress effects did improve simulations compared to using only Tair to a relatively minor extent, but the models that additionally use Tc on various other processes as well did not have better yield simulations. Models that simulated yield well under heat stress had varying skill in simulating Tc. For example, the EBN models had very poor simulations of Tc but performed very well in simulating grain yield. These results highlight the need to more systematically understand and model heat stress events in wheat.
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Webber, H., Ewert, F., Kimball, B. A., Siebert, S., White, J. W., Wall, G. W., et al. (2016). Simulating canopy temperature for modelling heat stress in cereals. Env. Model. Softw., 77, 143–155.
Abstract: Crop models must be improved to account for the effects of heat stress events on crop yields. To date, most approaches in crop models use air temperature to define heat stress intensity as the cumulative sum of thermal times (TT) above a high temperature threshold during a sensitive period for yield formation. However, observational evidence indicates that crop canopy temperature better explains yield reductions associated with high temperature events than air temperature does. This study presents a canopy level energy balance using Monin ObukhovSimilarity Theory (MOST) with simplifications about the canopy resistance that render it suitable for application in crop models and other models of the plant environment. The model is evaluated for a uniform irrigated wheat canopy in Arizona and rainfed maize in Burkina Faso. No single variable regression relationships for key explanatory variables were found that were consistent across sowing dates to explain the deviation of canopy temperature from air temperature. Finally, thermal times determined with simulated canopy temperatures were able to reproduce thermal times calculated with observed canopy temperature, whereas those determined with air temperatures were not. (C) 2015 Elsevier Ltd. All rights reserved.
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Vitali, A., Felici, A., Esposito, S., Bernabucci, U., Bertocchi, L., Maresca, C., et al. (2015). The effect of heat waves on dairy cow mortality. J. Dairy Sci., 98(7), 4572–4579.
Abstract: This study investigated the mortality of dairy cows during heat waves. Mortality data (46,610 cases) referred to dairy cows older than 24 mo that died on a farm from all causes from May 1 to September 30 during a 6-yr period (2002-2007). Weather data were obtained from 12 weather stations located in different areas of Italy. Heat waves were defined for each weather station as a period of at least 3 consecutive days, from May 1 to September 30 (2002-2007), when the daily maximum temperature exceeded the 90th percentile of the reference distribution (1971-2000). Summer days were classified as days in heat wave (HW) or not in heat wave (nHW). Days in HW were numbered to evaluate the relationship between mortality and length of the wave. Finally, the first 3 nHW days after the end of a heat wave were also considered to account for potential prolonged effects. The mortality risk was evaluated using a case-crossover design. A conditional logistic regression model was used to calculate odds ratio and 95% confidence interval for mortality recorded in HW compared with that recorded in nHW days pooled and stratified by duration of exposure, age of cows, and month of occurrence. Dairy cows mortality was greater during HW compared with nHW days. Furthermore, compared with nHW days, the risk of mortality continued to be higher during the 3 d after the end of HW. Mortality increased with the length of the HW. Considering deaths stratified by age, cows up to 28 mo were not affected by HW, whereas all the other age categories of older cows (29-60, 61-96, and >96 mo) showed a greater mortality when exposed to HW. The risk of death during HW was higher in early summer months. In particular, the highest risk of mortality was observed during June HW. Present results strongly support the implementation of adaptation strategies which may limit heat stress-related impairment of animal welfare and economic losses in dairy cow farm during HW.
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Tao, F., Xiao, D., Zhang, S., Zhang, Z., & Roetter, R. P. (2017). Wheat yield benefited from increases in minimum temperature in the Huang-Huai-Hai Plain of China in the past three decades. Agricultural and Forest Meteorology, 239, 1–14.
Abstract: Our understanding of climate impacts and adaptations on crop growth and productivity can be accelerated by analyzing historical data over the past few decades. We used crop trial and climate data from 1981 to 2009 at 34 national agro-meteorological stations in the Huang-Huai-Hai Plain (HHHP) of China to investigate the impacts of climate factors during different growth stages on the growth and yields of winter wheat, accounting for the adaptations such as shifts in sowing dates, cultivars, and agronomic management. Maximum (T-max) and minimum temperature (T-min) during the growth period of winter wheat increased significantly, by 0.4 and 0.6 degrees C/decade, respectively, from 1981 to 2009, while solar radiation decreased significantly by 0.2 MJ/m(2)/day and precipitation did not change significantly. The trends in climate shifted wheat phenology significantly at 21 stations and affected wheat yields significantly at five stations. The impacts of T-max and T-min differed in different growth stages of winter wheat. Across the stations, during 1981-2009, wheat yields increased on average by 14.5% with increasing trends in T-min over the whole growth period, which reduced frost damage, however, decreased by 3.0% with the decreasing trends in solar radiation. Trends in Tmax and precipitation had comparatively smaller impacts on wheat yields. From 1981 to 2009, climate trends were associated with a <= 30% (or <= 1.0% per year) wheat yield increase at 23 stations in eastern and southern parts of HHHP; however with a <= 30% (or <= 1.0% per year) reduction at 11 other stations, mainly in western part of HHHP. We also found that wheat reproductive growth duration increased due to shifts in cultivars and flowering date, and the duration was significantly and positively correlated with wheat yield. This study highlights the different impacts of T-max and T-min in different growth stages of winter wheat, as well as the importance of management (e.g. shift of sowing date) and cultivars shift in adapting to climate change in the major wheat production region. (C) 2017 Elsevier B.V. All rights reserved.
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