Kipling, R. P., & Scollan, N. G. (2014). Livestock production and the feed challenge. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: It is predicted that world population will reach nine billion by 2050 (Godfray et al., 2010) with the biggest increases occurring in the developing world (Guyomard et al., 2013, Thornton, 2010). This growth is expected to dramatically increase the demand for meat and animal products (Tilman et al., 2002) with a requirement by 2050 for 73 % more meat and 58 % more milk than produced in 2010 (FAO, 2011). In order to meet this growing demand, the supply of livestock products must rise to an extent comparable with that of the ‘Green Revolution’ (Tilman et al., 2002). This must occur in the context of serious global challenges related to climate change, resource availability, inequality, and biodiversity loss. At present many European livestock production systems are heavily reliant on a small number of feed products to provide protein, with imported soya accounting for 55 % of the 2.6 million tonnes of plant-derived protein fed to animals in the UK. This reliance on a small number of imported products leaves supply vulnerable to economic and climatic change. There is increased research into alternatives to South American soybean in the European feed supply chain, including improving the nutritional and agronomic characteristics of such alternatives, and exploring the use of new sources of potential feed material. This presents an opportunity for collaboration between experimental researchers and modellers to investigate the potential impacts of alternative feeds on livestock system productivity, robustness to climate change and levels of GHG emissions.
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François, L., Jacquemin, I., Fontaine, C., Minet, J., Dury, M., & Tychon, B. (2014). Implementing agricultural land-use in the CARAIB dynamic vegetation model. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: CARAIB (Dury et al., 2011) is a state-of-the-art dynamic vegetation model with various modules dealing with (i) soil hydrology, (ii) photosynthesis/stomatal regulation, (iii) carbon allocation and biomass growth, (iv) litter/soil carbon dynamics, (v) vegetation cover dynamics, (vi) seed dispersal, and (vii) vegetation fires. Climate and atmospheric CO2 are the primary inputs. The model calculates all major water and CO2/carbon fluxes and pools. It can be run with plant functional types or species (up to 100 different species) at various spatial scales, from the municipality to country or continental levels. Within the VOTES project (Fontaine et al., 2013), the model has been improved to include crops and meadows, and some modules have been written to translate model outputs into quantitative indicators of ecosystem services (e.g., evaluate crop yield from net primary productivity or calculate soil erosion from runoff, slope, grown species and various soil attributes). The model was run over an area covering four municipalities in central Belgium, where land-use is dominated by crops, meadows, housing and some forests and was introduced in the model at the land parcel level. Simulations were also performed for the future. In these simulations, CARAIB was combined with the Aporia Agent-Based Model, to project land-use changes up to 2050. This approach is currently extended within the MASC project (funded by Belgian Science Policy, BELSPO) to the whole Belgian territory (at 1 km2) and to Western Europe (at 20 km x 20 km).
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Schönhart, M. (2014). Uncertainty analysis and management in the regional pilot case study ‘Mostviertel region. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: An integrated modelling framework (IMF) is developed to analyse impacts of climate andpolicy changes on farm welfare and the environment. The IMF is applied on two contrasting grassland (south) and cropland (north) dominated Austrian landscapes. The IMF combines the crop rotation model CropRota, the bio-physical process model EPIC and the bio-economic farm model FAMOS[space] and applies combined climate change and policy scenarios. Changing policies reduce farm gross margins by -36% and -5% in the two landscapes respectively. Climate change increases gross margins and farms can reach pre-reform levels on average. Climate induced intensification such as removing of landscape elements andincreasing fertilization can be moderated by an agri-environmental program (AEP). However, productivity gains from climate change increase the opportunity costs for AEP participation.
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Lehtonen, H. S., Kässi, P., Korhonen, P., Niskanen, O., Rötter, R., Palosuo, T., et al. (2014). Problems and opportunities in climate change adaptation in North Savo region. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Crop production for feed dominates land use in North Savo in eastern Finland. The value of dairy and beef production is appr. 70 % of the total value of agricultural production of the region. In climate change adaptation research we are especially interested in dairy and meat sectors, which are directly dependent on the development of productivity of crop production. Climate change implies changes in cereals and forage crop yields and nutritive quality. There are most likely increasing problems and risks related to overwintering and growing periods. Grass silage is mainly self-produced on farms and most often there is no market for silage. Silage production and use are vulnerable to changes in local climate, because lost yield cannot be easily replaced from market. Risks and costs due to increasing inter-annual yield volatility can be reduced by good management practices, such as crop rotation, plant protection, soil improvements and better crop protection against plant diseases.However the profitability of such measures is dependent on market and policy conditions. Nevertheless new cultivars and species, as well as various options for production and risk management, are most likely needed in future climate. Some adaptations may have multiple benefits which however may realize only in medium or long run. It is important to safeguard the most important and obviously needed adaptations, and identify market and socio-economic conditions which inhibit farmers from necessary adaptations and lead to reduced productivity and increased production costs.
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Roggero, P. P., Seddaiu, G., Ledda, L., Doro, L., Deligios, P., Nguyen, T. P. L., et al. (2014). Combining modeling and stakeholder involvement to build community adaptive responses to climate change in a Mediterranean agricultural district. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
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.
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