Abstract: 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.

Abstract: 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.

Abstract: The precise spatially explicit knowledge about crop yield potentials and yield gaps is essential to guide sustainable intensification of agriculture. In this study, the maize yield potentials from 1980 to 2008 across the major maize production regions of China were firstly estimated by county using ensemble simulation of a well-validated large scale crop model, i.e., MCWLA-Maize model. Then, the temporal and spatial patterns of maize yield potentials and yield gaps during 1980-2008 were presented and analyzed. The results showed that maize yields became stagnated at 32.4% of maize-growing areas during the period. In the major maize production regions, i.e., northeastern China, the North China Plain (NCP) and southwestern China, yield gap percentages were generally less than 40% and particularly less than 20% in some areas. By contrast, in northern and southern China, where actual yields were relatively lower, yield gap percentages were generally larger than 40%. The areas with yield gap percentages less than 20% and less than 40% accounted for 8.2% and 27.6% of maize-growing areas, respectively. During the period, yield potentials decreased in the NCP and southwestern China due to increase in temperature and decrease in solar radiation; by contrast, increased in northern, northeastern and southeastern China due to increases in both temperature and solar radiation. Yield gap percentages decreased generally by 2% per year across the major maize production regions, although increased in some areas in northern and northeastern China. The shrinking of yield gap was due to increases in actual yields and decreases in yield potentials in the NCP and southwestern China; and due to larger increases in actual yields than in yield potentials in northeastern and southeastern China. The results highlight the importance of sustainable intensification of agriculture to close yield gaps, as well as breeding new cultivars to increase yield potentials, to meet the increasing food demand. (C) 2015 Elsevier B.V. All rights reserved.