|
|
Özkan, á¹¢., Bonesmo, H., Østerås, O., & Harstad, O. M. (2014). Effect of Increased Somatic Cell Count and Replacement Rate on Greenhouse Gas Emissions in Norwegian Dairy Herds (Vol. 3).
Abstract: Dairy sector contributes around 4% of global greenhouse gas (GHG) emissions, of which 2/3 and 1/3 are attributed to milk and meat production, respectively. The main GHGs released from dairy farms are methane, nitrous oxide and carbon dioxide. The increased trend in emissions has stimulated research evaluating alternative mitigation options. Much of the work to date has focused on animal breeding, dietary factors and rumen manipulation. There have been little studies assessing the impact of secondary factors such as animal health on emissions at farm level. Production losses associated with udder health are significant. Somatic cell count (SCC) is an indicator on udder health. In Norway, around 45, 60 and 70% of cows in a dairy herd at first, second and third lactation are expected to have SCC of 50,000 cells/ml and above. Another indirect factor is replacement rate. Increasing the replacement rate due to health disorders, infertility and reduced milk yield is likely to increase the total farm emissions if the milking heifer replacements are kept in the herd.In this study, the impact of elevated SCC (200,000 cells/ml and above) and replacement rate on farm GHG emissions was evaluated. HolosNor, a farm scale model adapting IPCC methodology was used to estimate net farm GHG emissions. Preliminary results indicate an increasing trend in emissions (per kg milk and meat) as the SCC increases. Results suggest that animal health should be considered as an indirect mitigation strategy; however, further studies are required to enable comparisons of different farming systems. No Label
|
|
|
|
Wallach, D., & Rivington, M. (2014). A framework structure to integrate improved methods for uncertainty evaluation, and protocols for methods application (Vol. 3).
|
|
|
|
Hutchings, N., & Kipling, R. (2014). Inventory of farm-scale models within LiveM (Vol. 3).
Abstract: The aim of WP3 is to improve the assessment of the impact of climate change on livestock and grassland systems at the farm-scale. The first step in this process is to understand the current state of the art in farm-scale modelling, and the resources available within the MACSUR knowledge hub. Here, an inventory of the farm-scale models available within LiveM is presented, along with a summary of the types of model represented. Thirteen farm-scale models were identified, three of which focus on environmental aspects of farm systems (GHG emissions etc.) and ten of which focus on management strategies (productivity, economics etc.).
|
|
|
|
Zimmermann, A., Witzke, H. - P., & Heckelei, T. (2013). Filling gaps: AgMIP scenario results from CAPRI (Vol. 2).
Abstract: Climate change impacts on food production, socioeconomic changes (population and income growth in large parts of the world) and biofuel policies affecting demand quantities have risen scientific, political and public interest in long-term forecasts on food security. Whereas first quantitative analyses from global economic models are starting to appear (e.g. (von Lampe et al., under review)), similar studies on smaller regional scales are not yet available. However, acknowledging that climate change affects crop yields differently across scales and regions (e.g. (Reidsma et al., 2007)) and considering the specific political setting given through the Common Agricultural Policy (CAP) in Europe, the MACSUR project focuses on the impact of climate change and socioeconomic changes on European agriculture and its contribution to global food security. We present a Europe-wide analysis of the effect of selected climate and socioeconomic scenarios on food security in terms of food prices using the Common Agricultural Policy Regionalised Impact modelling system (CAPRI). No Label
|
|
|
|
Bellocchi, G., Ma, S., Köchy, M., & Braunmiller, K. (2013). Datasets classification and criteria for data requirements (Vol. 2).
Abstract: This deliverable focuses on the collation, screening, and consolidation of data for selected grassland sites in Europe and peri-Mediterranean regions. No Label
|
|
