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Kipling, R.P.; Topp, C.F.E.; Bannink, A.; Bartley, D.J.; Blanco-Penedo, I.; Cortignani, R.; del Prado, A.; Dono, G.; Faverdin, P.; Graux, A.-I.; Hutchings, N.J.; Lauwers, L.; Gulzari, S.O.; Reidsma, P.; Rolinski, S.; Ruiz-Ramos, M.; Sandars, D.L.; Sandor, R.; Schoenhart, M.; Seddaiu, G.; van Middelkoop, J.; Shrestha, S.; Weindl, I.; Eory, V. |
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Title |
To what extent is climate change adaptation a novel challenge for agricultural modellers |
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Journal Article |
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Year |
2019 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
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120 |
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Unsp 104492 |
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Keywords |
Adaptation; Agricultural modelling; Climate change; Research challenges; greenhouse-gas emissions; farm-level adaptation; land-use; food; security; adapting agriculture; livestock production; decision-making; change impacts; dairy farms; crop |
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Abstract |
Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change. |
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2020-02-14 |
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1364-8152 |
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LiveM, ft_macsur |
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MA @ admin @ |
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5223 |
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Kipling, R.P.; Virkajärvi, P.; Breitsameter, L.; Curnel, Y.; De Swaef, T.; Gustavsson, A.-M.; Hennart, S.; Höglind, M.; Järvenranta, K.; Minet, J.; Nendel, C.; Persson, T.; Picon-Cochard, C.; Rolinski, S.; Sandars, D.L.; Scollan, N.D.; Sebek, L.; Seddaiu, G.; Topp, C.F.E.; Twardy, S.; Van Middelkoop, J.; Wu, L.; Bellocchi, G. |
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Title |
Key challenges and priorities for modelling European grasslands under climate change |
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Journal Article |
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Year |
2016 |
Publication |
Science of the Total Environment |
Abbreviated Journal |
Science of the Total Environment |
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566-567 |
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851-864 |
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Keywords |
Climate change; Grasslands; Horizon scanning; Livestock production; Models; Research agenda |
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Grassland-based ruminant production systems are integral to sustainable food production in Europe, converting plant materials indigestible to humans into nutritious food, while providing a range of environmental and cultural benefits. Climate change poses significant challenges for such systems, their productivity and the wider benefits they supply. In this context, grassland models have an important role in predicting and understanding the impacts of climate change on grassland systems, and assessing the efficacy of potential adaptation and mitigation strategies. In order to identify the key challenges for European grassland modelling under climate change, modellers and researchers from across Europe were consulted via workshop and questionnaire. Participants identified fifteen challenges and considered the current state of modelling and priorities for future research in relation to each. A review of literature was undertaken to corroborate and enrich the information provided during the horizon scanning activities. Challenges were in four categories relating to: 1) the direct and indirect effects of climate change on the sward 2) climate change effects on grassland systems outputs 3) mediation of climate change impacts by site, system and management and 4) cross-cutting methodological issues. While research priorities differed between challenges, an underlying theme was the need for accessible, shared inventories of models, approaches and data, as a resource for stakeholders and to stimulate new research. Developing grassland models to effectively support efforts to tackle climate change impacts, while increasing productivity and enhancing ecosystem services, will require engagement with stakeholders and policy-makers, as well as modellers and experimental researchers across many disciplines. The challenges and priorities identified are intended to be a resource 1) for grassland modellers and experimental researchers, to stimulate the development of new research directions and collaborative opportunities, and 2) for policy-makers involved in shaping the research agenda for European grassland modelling under climate change. |
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0048-9697 |
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LiveM, ft_macsur |
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MA @ admin @ |
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4761 |
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Köchy, M.; Aberton, M.; Bannink, A.; Banse, M.; Brouwer, F.; Brüser, K.; Ewert, F.; Foyer, C.; Jorgenson, J.S.; Kipling, R.; Meijs, J.; Rötter, R.; Scollan, N.; Sinabell, F.; Tiffin, R.; van den Pol-van Dasselaar, A. |
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MACSUR — Summary of research results, phase 1: 2012-2015 |
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Report |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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6 |
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D-H3.3 |
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Hub |
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MACSUR — Modelling European Agriculture with Climate Change for Food Security — is a knowledge hub that was formally created in June 2012 as a European scientific network. The strategic aim of the knowledge hub is to create a coordinated and globally visible network of European researchers and research groups, with intra- and interdisciplinary interaction and shared expertise creating synergies for the development of scientific resources (data, models, methods) to model the impacts of climate change on agriculture and related issues. This objective encompasses a wide range of political and sociological aspects, as well as the technical development of modelling capacity through impact assessments at different scales and assessing uncertainties in model outcomes. We achieve this through model intercomparisons and model improvements, harmonization and exchange of data sets, training in the selection and use of models, assessment of benefits of ensemble modelling, and cross-disciplinary linkages of models and tools. The project engages with a diverse range of stakeholder groups and to support the development of resources for capacity building of individuals and countries. Commensurate with this broad challenge, a network of currently 300 scientists (measured by the number of individuals on the central e-mail list) from 18 countries evolved from the original set of research groups selected by FACCE. In the spirit of creating and maintaining a network for intra- and interdisciplinary knowledge exchange, network activities focused on meetings of researchers for sharing expertise and, depending on group resources (both financial and personnel), development of collaborative research activities. The outcome of these activities is the enhanced knowledge of the individual researchers within the network, contributions to conference presentations and scholarly papers, input to stakeholders and the general public, organised courses for students, junior and senior scientists. The most visible outcome are the scientific results of the network activities, represented in the contributions of MACSUR members to the impressive number of more than 200 collaborative papers in peer-reviewed publications. Here, we present a selection of overview and cross-disciplinary papers which include contributions from MACSUR members. It highlights the major scientific challenges addressed, and the methodological solutions and insights obtained. Over and above these highlights, major achievements have been reached regarding data collection, data processing, evaluation, model testing, modelling assessments of the effects of agriculture on ecosystem services, policy, and development of scenarios. Details on these achievements in the context of MACSUR can be found in our online publication FACCE MACSUR Reports at http://ojs.macsur.eu. |
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MA @ admin @ |
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2086 |
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Köchy, M.; Bannink, A.; Banse, M.; Brouwer, F.; Brüser, K.; Ewert, F.; Foyer, C.; Kipling, R.; Rötter, R.; Scollan, N.; Sinabell, F. |
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Title |
MACSUR Phase 1 Final Administrative Report: Public release |
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Report |
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Year |
2015 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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6 |
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D-H3.5.3 |
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Hub; |
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MACSUR’s foremost charge is improving the methodology for integrative inter-disciplinary modelling of European agriculture. In addition to technical changes, improvements include the involvement of stakeholders for setting research priorities, scenarios (if-then evaluations), and model parameters to more realistic or region-specific values. The Knowledge Hub currently brings together 300 members from 18 countries and has generated 300 scientific papers, over 500 presentations and 20 workshops and conferences within the first three years. Scientific results are communicated in conferences and workshops, where policymakers take part by invitation or because of professional interest. These events also provide opportunities for direct dialogues between policymakers and scientists. The primary form of output of the research network is scientific publications that are cited in policy documents by relevant administrative departments, ministries, intergovernmental agencies, and directorate-generals, and non-governmental interest groups. MACSUR members also contribute directly to policy documents as authors, e.g. the EEA’s indicator report on CC impacts or the IPCC’s 5th assessment report’s chapter on food security. |
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MA @ admin @ |
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2080 |
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Köchy, M.; Banse, M.; Tiffin, R.; Ewert, F.; Rötter, R.; Van den Pol-van Dasselaar, A.; Brouwer, F.; Sinabell, F.; Jorgenson, J.; Sætnan, E.; Kipling, R. |
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General outline of plans for an extension phase of MACSUR |
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2014 |
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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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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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MA @ admin @ |
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5084 |
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