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Bellocchi, G., Ma, S., Köchy, M., & Braunmiller, K. (2013). Identified grassland-livestock production systems and related models (Vol. 2).
Abstract: This report describes grassland-livestock production systems, as selected for model-basedstudies. A list of grassland models was identified for evaluation against such datasets(WP2) and application at reference farm (WP3) and regions (WP4) across Europe and peri-European countries. No Label
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Baum, Z., & Palatnik, R. R. (2013). Assessing the Impact of Climate Change on the Israeli Water Economy via a Linked CGE and Farm-Level Model..
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Baum, Z. (2013). Assessing the impact of climate change on agriculture and a water economy with a diverse mix of water types – the Israeli case study..
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Bartley, D. (2013). Identification of datasets on climate change in relation to livestock productivity (production and fitness traits) and livestock infectious disease (Vol. 1).
Abstract: Datasets from Germany and the United Kingdom containing information on geographic (European Union 27 countries), climatic, meteorological, host and infectious agents’ parameters (figure 2) have been completed and are now available for preliminary analysis relating to data quality and consistency. Data set information will continue to be added over the next 12 months. No Label
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Barnes, A., & Moran, D. (2013). Modelling Food Security and Climate Change: Scenario Analysis (Vol. 1).
Abstract: Developing scenarios is a common interest within MACSUR researchers. This report outlines the main results of a survey of TRADE-M participants with respect to the scenarios used within modelling, the time frame and the importance of factors in their development. Most researchers are generating their own regionally defined scenarios, though some are basing these on IPCC scenarios. Generally, they adopt a short-term time frame of up to 2020 to estimate impacts. Most see food production as the main driver behind the scenarios followed by climate change mitigation and adaptation. The main weakness seems to be lack of interest in modelling variability due to weather effects, these may be an argument for stronger cross-collaboration between different MACSUR consortia within the crops and animals groups. No Label
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