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Braunmiller, K., & Köchy, M. (2013). Background information on Shared Socioeconomic Pathways for use in MACSUR case studies (Vol. 2).
Abstract: This document is intended to aid in the development of regional Representative Agricultural Pathways in Europe for use in MACSUR case studies, especially the regional pilot studies. We present overviews of existing characterisations of RCPs, SSPs, SPAs, RAPs and more detailed descriptions of the scenarios and assumptions relevant for MACSUR. No Label
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Palosuo, T. (2013). Data format for model in- and output (Vol. 2).
Abstract: A common format for model input variables and model output variables has been defined to be distributed to modellers participating in the model inter-comparison and improvement. The aim of common formats is to support the communication between the modellers, those providing empirical data of the experiments and those analysing the simulation results. The input format facilitates the model application in a way that each cropping-system to be modelled will be defined in the same way. Data will be delivered in EXCEL sheets with sub-tables for each block of inputs. Tables are mostly organized in a way that allows export and sequential read-in by the models. The common output format enables effective processing of results estimating model performance indicators. No Label
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Köchy, M., & Zimmermann, A. (2013). Workshop on Regional Pilot Studies, 5-7 June 2013, Braunschweig (Vol. 2).
Abstract: The workshop was called to define an overarching question to be answered by all Regional Pilot Studies and to select from the existing studies those that fit best to the aims of MACSUR. The question that evolved from the discussions is “What would be the different contributions of different European adaptation strategies to ensure global food security until 2050 at different scales (farm to EU) while keeping the GHG targets?” Workshop participants agreed to use the newest climate simulations related to Representative Concentration Pathways that were also used by the AgMIP and ISI-MIP projects. There was also agreement to use a subset of the AgMIP scenarios (S2-S6) for impact assessments, with AgMIP scenario S1 as the reference scenario, for details see Table 3 below. The selection of Regional Pilot Studies was discussed separately for European Grand Regions, but there was no concluding decision taken. The Project Steering Committee will finally decide on showcase studies at a meeting in the first week of July based on characterisations sent in by interested members. Questionnaires for characterising the Regional Pilot Studies will be sent by the Hub to the regional contact persons mentioned in Table 2 to fill in. The characterization list can be extended. The questionnaires should be filled in by the end of June. Stakeholder meetings are planned for October 2013 in each region where preliminary/sample outputs of the regional pilot studies should be presented. Results will be presented at the mid-term meeting in April 2014. The last year of MACSUR is then available to improve the studies.The geographic extent of the Regional Pilot Studies is approximately county level – representing the area of the studies they are based on. The Regional Pilot Studies will be linked within the grand regions (northern, central, southern Europe) by consistent regional and continental Representative Agricultural Pathways (RAP). These regional RAPs will feed into the RAP process underway at AgMIP. Through the common RAPs the Regional Pilot Studies will reflect the common challenges of the greater region and by having several Regional Pilot Studies the diversity of the environment, farming systems, and political systems is represented. The workshop was a first step into further planning and performing the Regional Pilot Studies that will fine-tune the results of the workshop. No Label
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Nendel, C., Wieland, R., Mirschel, W., Specka, X., Guddat, C., & Kersebaum, K. C. (2013). Simulating regional winter wheat yields using input data of different spatial resolution. Field Crops Research, 145, 67–77.
Abstract: The success of using agro-ecosystem models for the high-resolution simulation of agricultural yields for larger areas is often hampered by a lack of input data. We investigated the effect of different spatially resolved soil and weather data used as input for the MONICA model on its ability to reproduce winter wheat yields in the Federal State of Thuringia, Germany (16,172 km(2)). The combination of one representative soil and one weather station was insufficient to reproduce the observed mean yield of 6.66 +/- 0.87 t ha(-1) for the federal state. Use of a 100 m x 100 m grid of soil and relief information combined with just one representative weather station yielded a good estimator (7.01 +/- 1.47 t ha(-1)). The soil and relief data grid used in combination with weather information from 14 weather stations in a nearest neighbour approach produced even better results (6.60 +/- 1.37 t ha(-1)); the same grid used with 39 additional rain gauges and an interpolation algorithm that included an altitude correction of temperature data slightly overpredicted the observed mean (7.36 +/- 1.17 t ha(-1)). It was concluded that the apparent success of the first two high-resolution approaches over the latter was based on two effects that cancelled each other out: the calibration of MONICA to match high-yield experimental data and the growth-defining and -limiting effect of weather data that is not representative for large parts of the region. At the county and farm level the MONICA model failed to reproduce the 1992-2010 time series of yields, which is partly explained by the fact that many growth-reducing factors were not considered in the model. (C) 2013 Elsevier B.V. All rights reserved.
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Semenov, M. A., & Stratonovitch, P. (2013). Designing high-yielding wheat ideotypes for a changing climate. Food Energy Secur., 2(3), 185–196.
Abstract: Global warming is characterized by shifts in weather patterns and increases in climatic variability and extreme events. New wheat cultivars will be required for a rapidly changing environment, putting severe pressure on breeders who must select for climate conditions which can only be predicted with a great degree of uncertainty. To assist breeders to identify key wheat traits for improvements under climate change, wheat ideotypes can be designed and tested in silico using a wheat simulation model for a wide range of future climate scenarios predicted by global climate models. A wheat ideotype is represented by a set of cultivar parameters in a model, which could be optimized for best wheat performance under projected climate change. As an example, high-yielding wheat ideotypes were designed at two contrasting European sites for the 2050 (A1B) climate scenario. Simulations showed that wheat yield potential can be substantially increased for new ideotypes compared with current wheat varieties under climate change. The main factors contributing to yield increase were improvement in light conversion efficiency, extended duration of grain filling resulting in a higher harvest index, and optimal phenology.
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