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Dalgaard, T., Kjeldsen, C., Meyer-Aurich, A., Özkan, S., Rolinski, S., Köchy, M., et al. (2014). Farming systems models for regional scale impact assessment in Europe – case studies of N-losses and greenhouse gas emissions..
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Van den Pol-van Dasselaar, A., Bellocchi, G., Hutchings, N., Olesen, J., & Saetnan, E. (2014). AnimalChange. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The EU-FP7 project AnimalChange (AN Integration of Mitigation and Adaptation options for sustainable Livestock production under climate CHANGE, http://www.animalchange.eu, 2011-2015) addresses mitigation and adaptation options and provides scientific guidance for their integration in sustainable development pathways for livestock production under climate change in Europe, Northern and Sub-Saharan Africa, and Latin America. The project provides insights, innovations, tools and models for livestock production incorporating socio-economic and environmental (particularly GHG emission) variables. Scenario studies are carried out at scales ranging from animal and pasture, to farm and to region, for given management options. A wide range of livestock production systems is included in the project. The core analytical spine of the project is a series of coupled biophysical and socio-economic models combined with experimentation. This allows exploring future scenarios for the livestock sector under baseline and atmospheric CO2 stabilization scenarios. These scenarios are first constructed and then elaborated and enriched by breakthrough mitigation and adaptation options at field and animal scales, integrated and evaluated at farm scale and finally used to assess policy options and their socio-economic consequences. The modelling results are useful for governments, agricultural and food industry and the agricultural sector (farmers). There are many synergies between the European activities of AnimalChange and those of the LiveM theme of MACSUR, in particular with respect to access to livestock production datasets, dialogue with stakeholders and comparison and integration of grassland and livestock models with crop and socio-economic models in pilot studies at a variety of scales.
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Kipling, R. P., Saetnan, E. R., Van den Pol-van Dasselaar, A., & Scollan, N. G. (2014). Building modelling capacity for livestock systems: progress in LiveM. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: MACSUR provides an opportunity to connect disparate research groups and disciplines in livestock and grassland modelling. Within the livestock theme (LiveM) of MACSUR, grassland modelling capabilities have been significantly improved through joint modelling exercises, and grassland modellers have exploited their methodological overlaps with CropM to make important contributions to regional pilot studies. Animal health researchers have been contributing to the southern regional pilot, and modelling resources have been identified for livestock systems at the animal and farm-scales. Here, the priorities for the next steps for livestock and grassland modelling are discussed, and for the role of MACSUR in addressing the challenges facing the sector. While crop and grassland modelling deals with primary production, livestock modelling examines the complexity of secondary production. The unique position of livestock modelling presents challenges and opportunities. The diversity of livestock models (in scale and approach) makes model inter-comparisons and collaborative work challenging, while the range of variables involved in livestock systems provide many opportunities for increasing systemic efficiency and robustness to the impacts of climate change. Closer integration of experimental research and modelling teams also has the potential to increase the capability of livestock and grassland models to predict the impact of European adaptation strategies on livestock farming systems, and on the contribution of these systems to global food security.
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Köchy, M., Banse, M., Tiffin, R., Ewert, F., Rötter, R., Van den Pol-van Dasselaar, A., et al. (2014). General outline of plans for an extension phase of MACSUR. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: FACCE MACSUR has indicated a possible extension of funding by two years until May 2017 (phase 2).For phase 2, hub and theme coordinators suggest the following main activities, that will be discussed during the remainder of the meeting and in the coming months.Evolution, upscaling, and transfer of knowledge gained in regional case studies.Assessment of additional scenarios of socio-economic and climate trends.Further development of an interdisciplinary scientific community.Extending scaling methods for crop models to the European and global scale.Intensification of feed quality and animal health modelling with climate change.Economic models from farm to global level capable of reflecting climate change.
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Van den Pol-van Dasselaar, A., Evers, A., & De Haan, M. (2014). Modelling emissions of greenhouse gases from dairy farms in the Netherlands using DairyWise. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The DairyWise model (Schils et al., 2007) is an empirical model that simulates technical, environmental, and financial processes on a dairy farm. The central component is the FeedSupply model that balances the herd requirements, as generated by the DairyHerd model, and the supply of home-grown feeds, as generated by the crop models for grassland and silage maize. The GrassGrowth model predicts the daily rate of DM accumulation of grass, including several feed quality parameters. Depending on (daily) grazing, the amount of grass silage is calculated which also leads to the purchase (or sale) of roughage. The final output is a farm plan describing cattle performance, crop yield, grazing, feeding, and nutrient flows and the consequences on the environment and economy. The capabilities of DairyWise will be illustrated at the MACSUR meeting in Sassari with results of dairy farming in the Netherlands: farm characteristics, economics, NPK balances and greenhouse gas emissions.
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