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Nieróbca, A., Kozyra, J., Doroszewski, A., & Zylowska, K. (2014). The agro-meteorological model for yields of winter triticale..
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Nikolic, U., Mitter, H., Schmid, E., & F., S. (2014). Stand und Perspektiven des Sojaanbaues in Serbien (situation and outlook of soy bean production in Serbia)..
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Olesen, J. E. (2014). Rainfed intensive crop systems. In J. Fuhrer, & P. J. Gregory (Eds.),. Climate Change Impact and Adaptation in Agricultural Systems. Wallingford: Cabi.
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Schönhart, M. (2016). Uncertainties from Climate Change on Farms and Ecosystem Services of a Grassland Dominated Austrian Landscape (Vol. 9 C6 -).
Abstract: MACSUR 1: development of a method to analysefarm and landscape scale impacts of CC, mitigationand adaptation effects– cropland dominated landscape, crop choice and soilmanagement– climate model uncertainty• Now: test and improve the robustness of the method– grassland landscape, cropland expansion and livestock– uncertainty analysis– variability of weather conditions High spatial resolution creates interfaces to disciplinarymodels and indicators• Challenging data & modelling demand• Increasing productivity can increase intensification pressures• Threatened permanent (extensive) grasslands and landscape elements, but• subject to resource constraints, costs and prices• Future RDP and environmental policy design (e.g. WFD) may need to takechanging productivity into account• Future research: analyze uncertainties & environmentalimpacts• Ensembles of crop and grassland models• Sensitivity analysis on economic input parameters• Qualitative surveys with agricultural experts and farmers
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Nendel, C., Wieland, R., Mirschel, W., Specka, X., & Kersebaum, K. C. (2012). The simulation of winter wheat yields in Thuringia, Germany, using meteorological data with different spatial resolution..
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