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Mitter, H., Schönhart, M., Meyer, I., Mechtler, K., Schmid, E., Sinabell, F., et al. (2015). Agriculture. In K. Steininger, M. König, B. Bednar-Friedl, L. Kranzl, W. Loibl, & F. Prettenthaler (Eds.), (pp. 121–144). Economic Evaluation of Climate Change Impacts. Development of a Cross-Sectoral Framework and Results for Austria. Vienna.
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Sinabell, F., Schönhart, M., & Schmid, E. (2015). Austrian Agriculture 2010-2050. Quantitative Effects of Climate Change Mitigation Measures. An analysis of the scenarios WEM, WAM, WAM+ and a sensitivity analysis of scenario WEM. Vienna, Austria.
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Mitter, H., Schmid, E., & Schneider, U. A. (2014). Modelling impacts of drought and adaptation scenarios on crop production in Austria (Modellierung von Auswirkungen verschiedener Dürre- und Anpassungsszenarien auf die agrarische Pflanzenproduktion in Österreich). In Jahrbuch der ÖGA (Vol. 24, pp. 223–234).
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Mitter, H., Sinabell, F., & Schmid, E. (2015). Impacts of climate and policy change on Austrian protein crop supply balances. In Jahrbuch der ÖGA (Vol. 23, pp. 131–140).
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Piontek, F., Müller, C., Pugh, T. A., Clark, D. B., Deryng, D., Elliott, J., et al. (2014). Multisectoral climate impact hotspots in a warming world. Proc. Natl. Acad. Sci. U. S. A., 111(9), 3233–3238.
Abstract: The impacts of global climate change on different aspects of humanity’s diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case studies on vulnerability and multifaceted adaptation strategies. We consider impacts related to water, agriculture, ecosystems, and malaria at different levels of global warming. Multisectoral overlap starts to be seen robustly at a mean global warming of 3 °C above the 1980-2010 mean, with 11% of the world population subject to severe impacts in at least two of the four impact sectors at 4 °C. Despite these general conclusions, we find that uncertainty arising from the impact models is considerable, and larger than that from the climate models. In a low probability-high impact worst-case assessment, almost the whole inhabited world is at risk for multisectoral pressures. Hence, there is a pressing need for an increased research effort to develop a more comprehensive understanding of impacts, as well as for the development of policy measures under existing uncertainty.
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