MACSUR Literature Database -- Query Results

Kipling, P., Saetnan, E., Scollan, D., Bartley, D., Bellocchi, G., Hutchings, J., et al. (2014). Modelling livestock and grassland systems under climate change.. Keywords: LiveM http://reference.macsur.eu/show.php?record=2535
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.. Keywords: LiveM http://reference.macsur.eu/show.php?record=2380
Kipling, R. P., Bannink, A., Bellocchi, G., Dalgaard, T., Fox, N. J., Hutchings, N. J., et al. (2016). Modeling European ruminant production systems: Facing the challenges of climate change. Agricultural Systems, 147, 24–37. Abstract: Ruminant production systems are important producers of food, support rural communities and culture, and help to maintain a range of ecosystem services including the sequestering of carbon in grassland soils. However, these systems also contribute signiﬁcantly to climate change through greenhouse gas (GHG) emissions, while intensi- ﬁcation of production has driven biodiversity and nutrient loss, and soil degradation. Modeling can offer insights into the complexity underlying the relationships between climate change, management and policy choices, food production, and the maintenance of ecosystem services. This paper 1) provides an overview of how ruminant systems modeling supports the efforts of stakeholders and policymakers to predict, mitigate and adapt to climate change and 2) provides ideas for enhancing modeling to fulﬁl this role. Many grassland models can predict plant growth, yield and GHG emissions from mono-speciﬁc swards, but modeling multi-species swards, grassland quality and the impact of management changes requires further development. Current livestock models provide a good basis for predicting animal production; linking these with models of animal health and disease is a prior- ity. Farm-scale modeling provides tools for policymakers to predict the emissions of GHG and other pollutants from livestock farms, and to support the management decisions of farmers from environmental and economic standpoints. Other models focus on how policy and associated management changes affect a range of economic and environmental variables at regional, national and European scales. Models at larger scales generally utilise more empirical approaches than those applied at animal, ﬁeld and farm-scales and include assumptions which may not be valid under climate change conditions. It is therefore important to continue to develop more realistic representations of processes in regional and global models, using the understanding gained from ﬁner-scale modeling. An iterative process of model development, in which lessons learnt from mechanistic models are ap- plied to develop ‘smart’ empirical modeling, may overcome the trade-off between complexity and usability. De- veloping the modeling capacity to tackle the complex challenges related to climate change, is reliant on closer links between modelers and experimental researchers, and also requires knowledge-sharing and increasing technical compatibility across modeling disciplines. Stakeholder engagement throughout the process of model development and application is vital for the creation of relevant models, and important in reducing problems re- lated to the interpretation of modeling outcomes. Enabling modeling to meet the demands of policymakers and other stakeholders under climate change will require collaboration within adequately-resourced, long-term inter-disciplinary research networks Keywords: Food security; Livestock systems; Modeling; Pastoral systems; Policy support; Ruminants http://reference.macsur.eu/show.php?record=4734
Dalgaard, T. (2015). Models for regional scale farming system evaluation of climate change mitigation options and environmental impact assessment (Vol. 5). Abstract: The aim of the present paper is to exemplify and discuss the importance of farm scale modeling in relation to The EU Joint Programming Initiative (JPI-FACCE) knowledge hub on Agriculture, Food Security and Climate Change project.In particular, livestock production systems include complex interactions, with non-linear relationships between input factors, production, emissions, local climate as well as natural resources (e.g. soil types, rotational land versus permanent grasslands etc.). Moreover, management options pursued by the different types of farmers and other relevant decision makers are important to integrate. Consequently, results of regional scale impact assessments depend on the farming systems model approach, the approach to upscale results, and the inclusion of the relevant stakeholders and decision makers at the scales considered.Different farming systems models are reviewed, including the existing dynamic and static biophysical models. Finally, procedures for upscaling and validity testing of synthesized model results at regional scales are presented. Based on a discussion of these procedures, recommendations for hot-spot analyses in farming systems with regard to integrated climate change adaptation and mitigation for a sustainable food production are synthesized, and the potentials for integration of recommended policies and farm management options into overarching models in order to assess their impact on the regional to global scales are discussed. No Label http://reference.macsur.eu/show.php?record=2130
Dalgaard, T., Kjeldsen, C., & Graversgard, M. (2015). Review of regional scale models in the EU and methods commonly used when modelling outcomes of the implementation of the climate change mitigation policies (Vol. 6). Abstract: Management of Nitrogen (N) losses and the related greenhouse gas emissions is one of the most important environmental issues related to agriculture. This report shows examples of an integrated model tool, developed to quantify the N-dynamics at the complex interface between agriculture and the environment, and quantify effects of different management practices. Based on results from the EU funded research projects NitroEurope (www.NitroEurope.eu) and MEAscope (www.MEA-scope.org), examples from the quantification of farm N-losses in European agricultural landscapes are demonstrated. Applications of the dynamic whole farm model FASSET (www.FASSET.dk), and the Farm-N tool (www.farm-N.dk/FarmNTool) to calculate farm N balances, and distribute the surplus N between different types of N-losses (volatilisation, denitrification, leaching), and the related greenhouse gas emissions, show significant variation between landscapes and management practices. Moreover, significant effects of the nonlinearities, appearing when integrating over time, and scaling up from farm to landscape, are demonstrated. Finally, perspectives for stakeholder involvement is included and general recommendations for landscape level management of farm related nitrogen and greenhouse gas fluxes are made, and discussed in relation to ongoing research in the European research projects. No Label http://reference.macsur.eu/show.php?record=2110

Kipling, P., Saetnan, E., Scollan, D., Bartley, D., Bellocchi, G., Hutchings, J., et al. (2014). Modelling livestock and grassland systems under climate change..

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..

Kipling, R. P., Bannink, A., Bellocchi, G., Dalgaard, T., Fox, N. J., Hutchings, N. J., et al. (2016). Modeling European ruminant production systems: Facing the challenges of climate change. Agricultural Systems, 147, 24–37.

Abstract: Ruminant production systems are important producers of food, support rural communities and culture, and help to maintain a range of ecosystem services including the sequestering of carbon in grassland soils. However, these systems also contribute signiﬁcantly to climate change through greenhouse gas (GHG) emissions, while intensi- ﬁcation of production has driven biodiversity and nutrient loss, and soil degradation. Modeling can offer insights into the complexity underlying the relationships between climate change, management and policy choices, food production, and the maintenance of ecosystem services. This paper 1) provides an overview of how ruminant systems modeling supports the efforts of stakeholders and policymakers to predict, mitigate and adapt to climate change and 2) provides ideas for enhancing modeling to fulﬁl this role. Many grassland models can predict plant growth, yield and GHG emissions from mono-speciﬁc swards, but modeling multi-species swards, grassland quality and the impact of management changes requires further development. Current livestock models provide a good basis for predicting animal production; linking these with models of animal health and disease is a prior- ity. Farm-scale modeling provides tools for policymakers to predict the emissions of GHG and other pollutants from livestock farms, and to support the management decisions of farmers from environmental and economic standpoints. Other models focus on how policy and associated management changes affect a range of economic and environmental variables at regional, national and European scales. Models at larger scales generally utilise more empirical approaches than those applied at animal, ﬁeld and farm-scales and include assumptions which may not be valid under climate change conditions. It is therefore important to continue to develop more realistic representations of processes in regional and global models, using the understanding gained from ﬁner-scale modeling. An iterative process of model development, in which lessons learnt from mechanistic models are ap- plied to develop ‘smart’ empirical modeling, may overcome the trade-off between complexity and usability. De- veloping the modeling capacity to tackle the complex challenges related to climate change, is reliant on closer links between modelers and experimental researchers, and also requires knowledge-sharing and increasing technical compatibility across modeling disciplines. Stakeholder engagement throughout the process of model development and application is vital for the creation of relevant models, and important in reducing problems re- lated to the interpretation of modeling outcomes. Enabling modeling to meet the demands of policymakers and other stakeholders under climate change will require collaboration within adequately-resourced, long-term inter-disciplinary research networks

Keywords: Food security; Livestock systems; Modeling; Pastoral systems; Policy support; Ruminants

http://reference.macsur.eu/show.php?record=4734

Dalgaard, T. (2015). Models for regional scale farming system evaluation of climate change mitigation options and environmental impact assessment (Vol. 5).

Dalgaard, T., Kjeldsen, C., & Graversgard, M. (2015). Review of regional scale models in the EU and methods commonly used when modelling outcomes of the implementation of the climate change mitigation policies (Vol. 6).