Abstract: The work carried out under LiveM, L1.2 and described herein was based on construction and query of large databases which included multiannual productive and health field data. Productive data referred to dairy cows and included milk yield and composition, whereas health data were relative both to dairy cows and pigs. The analysis established the THI values above which a significant decline in the performance and health of dairy cows or pigs is to be expected. These results may help to adopt management environmental strategies which may permit to limit THI increase under farming conditions and/or to provide animals with interventions which may reduce heat load and/or increase dissipation of heat. No Label

Abstract: Different datasets have been completed and are now available for the analysis of interannual  and seasonal variations of productive, reproductive or health data relative to  intensively dairy cows and also to establish the relationships between temperature  humidity index (THI) and dairy cow performances. Datasets are referred to different  European countries (Italy, Belgium, Luxembourg and Slovenia) with different climatic  features. All these datasets have data relative to Animal Pedigree (Cow ID, Birth date,  Breed, Sire ID and Dam ID), Test-day records (Cow ID, Herd ID, Parity, Calving date, Test  date, Milk yield, Milk fat and protein (%), Milk somatic cell score), Reproductive events  (Cow ID, Herd ID, Parity, Calving date, AI date, Sire ID, Days Open, NRR-56 day), and Daily  meteorological records (Meteo station ID, Zip code of the meteo station, Observation date,  Max temperature, Min temperature, Mean temperature, Max relative humidity, Min  relative humidity, Mean relative humidity, Solar radiation, Wind speed). The dataset  relative to Italy includes also Mortality data (Animal ID, Herd ID, Death date) and Bulk milk  quality data (Herd ID, Test date, Fat & protein (%), Somatic cell score, Bacterial count,  Herd latitude, Herd longitude, Herd elevation). An additional database is still under  construction and will be based on Spanish data from organic dairy farms. No Label

Abstract: The case study area (54,000 ha) is located at Oristano, Italy. The main cropping systems are based on forages (silage maize, Italian ryegrass and alfalfa under irrigation, winter cereals and grasslands under rainfed conditions), rainfed cereals (durum wheat, barley), vegetables (e.g. artichokes), rice, citrus, olives and vineyards. Some 36,000 ha are served by irrigation. The area includes the dairy cows cooperative system of Arborea (30,000 cows, 5500 ha, nitrate vulnerable zone). The rainfed dairy sheep includes 372,000 sheep and a number of small milk processing plants. The research aims to support adaptive responses to climate change through the combination of modeling approaches and stakeholder engagement. Present (2000-2010) and future (2020-2030) climatic scenarios were developed by combining global climate models with Regional Atmospheric Modelling Systems to produce calibrated time series of daily temperature and precipitation for the case study. The EPIC model was calibrated to simulate the impact of climate scenarios on the main cropping systems. The impact of THIndex on milk yield, milk quality and mortality was also simulated for dairy cows. A territorial farm-type Discrete Stochastic Programming model was implemented to simulate choices for thirteen farming typologies as influenced by crop yields and water consumptions. Participatory activities, including field experiments, interviews, focus groups and interactive workshops, involved farmers and other stakeholders in the most critical phases of the research. The assessment of uncertainties and opportunities were proposed as a basis for discussion with policy makers to identify priorities for agro-climatic measures in 2014-2020.