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Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making.
Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.
Interleukin (IL)-22 is a STAT3-activating cytokine displaying characteristic AU-rich elements (ARE) in the 3'-untranslated region (3'-UTR) of its mRNA. This architecture suggests gene regulation by modulation of mRNA stability. Since related cytokines undergo post-transcriptional regulation by ARE-binding tristetraprolin (TTP), the role of this destabilizing protein in IL-22 production was investigated. Herein, we demonstrate that TTP-deficient mice display augmented serum IL-22. Likewise, IL-22 mRNA was enhanced in TTP-deficient splenocytes and isolated primary T cells. A pivotal role for TTP is underscored by an extended IL-22 mRNA half-life detectable in TTP-deficient T cells. Luciferase-reporter assays performed in human Jurkat T cells proved the destabilizing potential of the human IL-22-3'-UTR. Furthermore, overexpression of TTP in HEK293 cells substantially decreased luciferase activity directed by the IL-22-3'-UTR. Transcript destabilization by TTP was nullified upon cellular activation by TPA/A23187, an effect dependent on MEK1/2 activity. Accordingly, IL-22 mRNA half-life as determined in TPA/A23187-stimulated Jurkat T cells decreased under the influence of the MEK1/2 inhibitor U0126. Altogether, data indicate that TTP directly controls IL-22 production, a process counteracted by MEK1/2. The TTP-dependent regulatory pathway described herein likely contributes to the role of IL-22 in inflammation and cancer and may evolve as novel target for pharmacological IL-22 modulation.