Abstract: Understanding the drivers of yield levels under climate change is required to support adaptation planning and respond to changing production risks. This study uses an ensemble of crop models applied on a spatial grid to quantify the contributions of various climatic drivers to past yield variability in grain maize and winter wheat of European cropping systems (1984-2009) and drivers of climate change impacts to 2050. Results reveal that for the current genotypes and mix of irrigated and rainfed production, climate change would lead to yield losses for grain maize and gains for winter wheat. Across Europe, on average heat stress does not increase for either crop in rainfed systems, while drought stress intensifies for maize only. In low-yielding years, drought stress persists as the main driver of losses for both crops, with elevated CO2 offering no yield benefit in these years.

Abstract: Maize (Zea mays L) is one of the most important food crops and very common in all parts of sub-Saharan Africa. In 2010 53 million tons of maize were produced in sub-Saharan Africa on about one third of the total harvested cropland area (similar to 33 million ha). Our aim is to identify the limiting agroclimatic variable for maize growth and development in sub-Saharan Africa by analyzing the separated and combined effects of temperature and precipitation. Under changing climate, both climate variables are projected to change severely, and their impacts on crop yields are frequently assessed using process-based crop models. However it is often unclear which agroclimatic variable will have the strongest influence on crop growth and development under climate change and previous studies disagree over this question. We create synthetic climate data in order to study the effect of large changes in the length of the wet season and the amount of precipitation during the wet season both separately and in combination with changes in temperature. The dynamic global vegetation model for managed land LPJmL is used to simulate maize yields under current and future climatic conditions for the two 10-year periods 2056-2065 and 2081-2090 for three climate scenarios for the A1b emission scenario but without considering the beneficial CO2 fertilization effect. The importance of temperature and precipitation effects on maize yields varies spatially and we identify four groups of crop yield changes: regions with strong negative effects resulting from climate change (<-33% yield change), regions with moderate (-33% to -10% yield change) or slight negative effects (-10% to +6% yield change), and regions with positive effects arising from climate change mainly in currently temperature-limited high altitudes (>+6% yield change). In the first three groups temperature increases lead to maize yield reductions of 3 to 20%, with the exception of mountainous and thus cooler regions in South and East Africa. A reduction of the wet season precipitation causes decreases in maize yield of at least 30% and prevails over the effect of increased temperatures in southern parts of Mozambique and Zambia, the Sahel and parts of eastern Africa in the two projection periods. This knowledge about the limiting abiotic stress factor in each region will help to prioritize future research needs in modeling of agricultural systems as well as in drought and heat stress breeding programs and to identify adaption options in agricultural development projects. On the other hand the study enhances the understanding of temperature and water stress effects on crop yields in a global vegetation model in order to identify future research and model development needs. (C) 2013 Elsevier B.V. All rights reserved.

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.