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Author  |
Korhonen, P. |
| Title |
Intercomparison of timothy models in northern countries |
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| Year |
2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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5 |
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Sp5-31 |
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| Abstract |
Forage-based livestock and dairy production are the economic backbone of agriculture in many northern countries. In northern Europe and eastern Canada, forage grasses are commonly grown intensively for silage and hay as a part of crop rotation. In those regions, timothy (Phleum pratense L.) is one of the most widely grown grass species. Models that simulate the development of yield and nutritive quality have been developed for timothy, but the performance of different models has not been compared so far.In this study, we compare the performance of the models BASGRA, CATIMO, and STICS for the predictions of timothy yield at 7 sites located in Finland, Norway, Sweden, and Canada. In addition to yield, model predictions of additional variables, such as leaf area index, specific leaf area, and nutritive quality are gathered on a daily basis. Observed data will be used for two distinct calibrations: 1) Cultivar-specific and 2) ”global”, using all cultivars. The performance of the models will be tested by simulating all sites and years with both the 5 cultivar-specific parameter sets and the global parameter set.The first results of the comparison will be presented with a particular emphasis on dry matter yield predictions.The results will provide information about the uncertainties related to yield predictions of different timothy models and calibrations, the strengths and weaknesses of different modelling approaches, and the sensitivity of models to cultivar-specific parameters. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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no |
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MA @ admin @ |
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2146 |
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| Author |
Kuhnert, M. |
| Title |
Impact of climate aggregation over different scales on regional NPP modelling |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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5 |
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Sp5-32 |
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In spatial modelling of Net Primary Productivity (NPP), predictability and uncertainty depends on the availability of input data, as well as on the scale of the available data sets. Therefore, the study presented here quantifies the impact of aggregation effect of input data of different scales for a regional modelling approach using 5 different resolutions. As part of this study, the presentation focuses on the impact of the climate aggregation on the simulation of NPP. The effect is investigated on the model results of 11 different crop and biogeochemical models simulating NPP for wheat and maize for the area of the German state of North Rhine-Westphalia. The focus of the study is on the impact of drought effects across the scales considered. The data are analysed on annual time steps we followed two approaches to investigate the impact of water limitation on primary production: First, two model runs, one considers water limitation and the other one ignores the impacts of water limitation on plant production second, an external definition of dry conditions by a drought index, only considering climate data, enables a separation of grid-cells and years with drought impacts, independent of the model internal functions. The results show hardly any difference between the overall average NPP across the scales, but some variability for the impact of extreme weather conditions on the simulated NPP. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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no |
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MA @ admin @ |
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2147 |
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Lacetera, N. |
| Title |
National and transnational dairy cows biometeorological datasets linked to productive, reproductive and health performances data |
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2013 |
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FACCE MACSUR Reports |
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1 |
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D-L1.2.1 |
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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 |
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MA @ admin @ |
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2256 |
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| Author |
Lacetera, N. |
| Title |
Season and temperature humidity index related changes of productive and health parameters in dairy cows and pigs |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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5 |
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Sp5-33 |
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The work described herein was based on construction and query of four different large databases which included multiannual (5-7 years) meteorological, productive and health data from the field. Productive data were referred to dairy cows and included milk yield and composition (total bacterial count, fat and protein percentages) whereas health data were relative both to dairy cows (milk somatic cell counts and mortality data) and pigs (mortality data during transport and at lairage). The analysis pointed out significant seasonal variations of parameters under study. In synthesis, summer/hot season was associated with significant worsening of cows’ milk composition and with significant higher risk of death in pigs. The analysis also permitted to establish the themperature humidity index values above which a significant decline of performance and health of dairy cows or pigs has to expected. These results may help to predict the consequences of climate change in economically important sectors of the livestock industry, 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 |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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no |
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MA @ admin @ |
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2148 |
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Lacetera, N.; Vitali, A.; Bernabucci, U.; Nardone, A. |
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Relationships between temperature humidity index, mortality, milk yield and composition in Italian dairy cows |
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Report |
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2014 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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3 |
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Sp3-3 |
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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 |
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MA @ admin @ |
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2220 |
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