Abstract: The aim of this presentation is to illustrate the activities performed by the LiveM-Task L1.2. group based at the University of Tuscia, Viterbo, Italy. Three different pluriannual databases were built to perform retrospective studies aimed at establishing the relationships between temperature humidity index (THI) and parameters of interest for dairy cow farms. The THI combines temperature and humidity in a single value and has been widely used to quantify heat stress in farm animals. The first database was built to assess the relationships between THI and mortality over a 6 yr period (2002-2007); the second one was a 7 yr database (2001-2007) which was built to establish the relationships between THI and milk yield; the last database included THI, milk somatic cell counts, total bacterial counts, fat and protein percentages data collected over a 7 yr period (2003-2009). The analysis of the three databases provided several equations which demonstrated and quantified an increase of mortality, reduction of milk yield and a worsening of milk quality in hot environment. Results of these analyzes authorized speculations about risks for dairy cows and their productivity in a warming planet. Furthermore, the same results are being utilized by economists also working within MACSUR at the University of Tuscia for an integrated study aimed at establishing the economic impact of climate change in the dairy sector. Combining this information with climate change regional scenarios might permit prediction of the impact of global warming and identification of adaptation measures that are appropriate for specific contexts. No Label

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, whereas health data were relative both to dairy cows and pigs. The analysis pointed out significant seasonal variations of parameters under study. In synthesis, summer/hot season was associated with significant worsening of dairy cows milk composition and with significant higher risk of death in pigs. These results may help to predict consequences of climate change in economically important sectors of the livestock industry and also to identify and target adaptation options that are appropriate for specific contexts, and that can contribute to environmental sustainability as well as to economic development. 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