The Paris Agreement established the 1.5 and 2°C targets based on the recognition Bthat this would significantly reduce the risks and impacts of climate change^. We tested this assertion by comparing impacts at the regional scale between low-end (< 2°C; RCP2.6) and high-end (> 4°C; RCP8.5) climate change scenarios accounting for interactions across six sectors (agriculture, forestry, biodiversity, water, coasts and urban) using an integrated assessment model. Results show that there are only minor differences in most impact indicators for the 2020s time slice, but impacts are considerably greater under high-end than low-end climate change in the 2050s and 2080s. For example, for the 2080s, mitigation consistent with the Paris Agreement would reduce aggregate Europe-wide impacts on the area of intensive agriculture by 21% (on average across climate models), on the area of managed forests by 34%, on water stress by 14%, on people flooded by 10% and on biodiversity vulnerability by 16%. Including socioeconomic scenarios (SSPs 1, 3, 4, 5) results in considerably greater variation in the magnitude, range and direction of change of the majority of impact indicators than climate change alone. In particular, socioeconomic factors much more strongly drive changes in land use and food production than changes in climate, sometimes overriding the differences due to low-end and high-end climate change. Such impacts pose significant challenges for adaptation and highlight the importance of searching for synergies between adaptation and mitigation and linking them to sustainable development goals.

Climate change will affect all sectors of society and the environment at all scales, ranging from the continental to the national and local. Decision-makers and other interested citizens need to be able to access reliable sciencebased information to help them respond to the risks of climate change impacts and assess opportunities for adaptation. Participatory integrated assessment (IA) tools combine knowledge from diverse scientific disciplines, take account of the value and importance of stakeholder 'lay insight' and facilitate a two-way iterative process of exploration of 'what if's' to enable decision-makers to test ideas and improve their understanding of the complex issues surrounding adaptation to climate change. This paper describes the conceptual design of a participatory IA tool, the CLIMSAVE IA Platform, based on a professionally facilitated stakeholder engagement process. The CLIMSAVE (climate change integrated methodology for cross-sectoral adaptation and vulnerability in Europe) Platform is a user-friendly, interactive web-based tool that allows stakeholders to assess climate change impacts and vulnerabilities for a range of sectors, including agriculture, forests, biodiversity, coasts, water resources and urban development. The linking of models for the different sectors enables stakeholders to see how their interactions could affect European landscape change. The relationship between choice, uncertainty and constraints is a key cross-cutting theme in the conduct of past participatory IA. Integrating scenario development processes with an interactive modelling platform is shown to allow the exploration of future uncertainty as a structural feature of such complex problems, encouraging stakeholders to explore adaptation choices within real-world constraints of future resource availability and environmental and institutional capacities, rather than seeking the 'right' answers.

Given scenarios describing future climates and socio-techno-economics, this study estimates the consequences for agricultural land use, combining models of crop growth and farm decision making to predict profitability over the whole of Europe, driven solely by soil and climate at each location. Each location is then classified by its profitability as intensive or extensive agriculture or not suitable for agriculture.The main effects of both climate and socio-economics were in the agriculturally marginal areas of Europe. The results showed the effect of different climates is relatively small, whereas there are large variations when economic scenarios are included. Only Finland's agricultural area significantly responds to climate by increasing at the expense of forests in several scenarios. Several locations show more difference due to climate model (PCM vs HADCM3) than emission scenario, because of large differences in predicted precipitation, notably the Ardennes switching to arable in HADCM3. . Scenario modelling has identified several such regions where there is a need to be watchful, but few where all of the scenario results agree, suggesting great uncertainty in future projections. Thus it has not been able to predict any futures, though all results agree that in central Europe, changes are likely to be relatively small.

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