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Zander, P., Schuler, J., Porwollik, V., & Hecker, J. - M. (2014). Modelling approach and first results on irrigation as climate change adaptation strategy of the project NaLaMa-nT. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The project NaLaMa-nT examines in the context of climate change sustainable development paths of land use in four different rural districts in Northern Germany. These districts were chosen along a soil-climate gradient from west to east with increasing water deficit for plant growth caused by both: decreasing rain fall and decreasing soil quality. In front of this background different trends and developments of agricultural production can be derived from analysing, modelling and comparing existing production systems and conditions of the different regions. One assumption developed from existing climate projections is that climate change will cause increasing water deficits for plant growth – especially in the eastern part of Germany. An obvious solution is to intensify agricultural production using existing irrigation methods that can reduce the yield risk and thus stabilize income from agriculture by avoiding yield failures and increasing the overall yield level. Therefore we build a modelling approach which allows an economic analysis both on the crop production activity level as well on the farm level. The data base comprises data representing recent production techniques and added optional irrigation techniques. The yields and input level changes are derived from literature studies and expert interviews. The farm structure is represented and modeled based on typical farms chosen from an IACS-data farm typology with different production potentials and patterns. First results will be presented in April.
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Toscano, P., Genesio, L., Crisci, A., Vaccari, F. P., Ferrari, E., La Cava, P., et al. (2015). Empirical modelling of regional and national durum wheat quality. Agricultural and Forest Meteorology, 204, 67–78.
Abstract: The production of durum wheat in the Mediterranean basin is expected to experience increased variability in yield and quality as a consequence of climate change. To assess how environmental variables and agronomic practices affect grain protein content (GPC), a novel approach based on monthly gridded input data has been implemented to develop empirical model, and validated on historical time series to assess its capability to reproduce observed spatial and inter-annual GPC variability. The model was applied in four Italian regions and at the whole national scale and proved reliable and usable for operational purposes also in a forecast ‘real-time’ mode before harvesting. Precipitable water during autumn to winter and air temperature from anthesis to harvest were extremely important influences on GPC; these and additional variables, included in a linear model, were able to account for 95% of the variability in GPC that has occurred in the last 15 years in Italy. Our results are a unique example of the use of modelling as a predictive real-time platform and are a useful tool to understand better and forecast the impacts of future climate change projections on durum wheat production and quality.
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Jing, Q., Bélanger, G., Baron, V., Bonesmo, H., & Virkajärvi, P. (2013). Simulating the Nutritive Value of Timothy Summer Regrowth. Agronomy Journal, 105(3), 563.
Abstract: The process-based grass model, CATIMO, simulates the spring growth and nutritive value of timothy (Phleum pratense L.), a forage species widely grown in Scandinavia and Canada, but the nutritive value of the summer regrowth has never been simulated. Our objective was to improve CATIMO for simulating the N concentration, neutral detergent fiber (NDF), in vitro digestibility of NDF (dNDF), and in vitro true digestibility of dry matter (IVTD) of summer regrowth. Daily changes in summer regrowth nutritive value were simulated by modifying key crop parameters that differed from spring growth. More specifically, the partitioning fraction to leaf blades was increased to increase the leaf-to-weight ratio, and daily changes in NDF and dNDF of leaf blades and stems were reduced. The modified CATIMO model was evaluated with data from four independent experiments in eastern and western Canada and Finland. The model performed better for eastern Canada than for the other locations, but the nutritive value attributes of the summer regrowth across locations (range of normalized RMSE = 8-25%, slope < 0.17, R-2 < 0.10) were not simulated as well as those of the spring growth (range of normalized RMSE = 4-16%, 0.85 < slope < 1.07, R-2 > 0.61). These modeling results highlight knowledge gaps in timothy summer regrowth and prospective research directions: improved knowledge of factors controlling the nutritive value of the timothy summer regrowth and experimental measurements of leaf-to-weight ratio and of the nutritive value of leaves and stems.
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Özkan Gülzari, Ş., & Kipling, R. (2017). Understanding the potential of existing models to characterize animal health conditions and estimate greenhouse gas emissions (Vol. 10).
Abstract: The primary objective of this study was to assess the status and priorities for future development in modelling of the impacts of animal health on greenhouse gas (GHG) emissions. It also aimed to facilitate communication between experimental researchers and modellers by defining a list of parameters that are needed to model livestock health and disease, and the impact of health conditions on GHG emissions. The summary presented here provides a brief overview of ongoing work, which the L2.1/L2.2 partners, with support from the Global Research Alliance Animal Health Network (GRA AHN), is currently developing into a paper for publication in a peer reviewed journal.
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Schönhart, M. (2014). Regional Pilot Case Study: Mostviertal – AT, upcoming project phase. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The presentation indicates our plans for activities in the Mostviertel region in the next project phase.
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