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14 pages, 6 figures, supplementary information .-- Data availability. Simulation data from gridded impact models is available through https://esg.pik-potsdam.de/projects/isimip2a/ and citable using the following DOIs: https://doi.org/10.5880/PIK.2017.002 (terrestrial ecosystems); https://doi.org/10.5880/PIK.2017.006 (agriculture); https://doi.org/10.5880/PIK.2017.010 (hydrology); https://doi.org/10.5880/PIK.2018.004 (marine ecosystems, regional); https://doi.org/10.5880/PIK.2018.005 (marine ecosystems, global). The city-level mortality model data and country-level hydropower model data are available from the authors upon request, Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought, The work was supported within the framework of the Leibniz Competition (SAW-2013-PIK-5), the EU FP7 project HELIX (grant no. FP7–603864–2), the FP7 project IMPACT2C (grant agreement#282746) and by the German Federal Ministry of Education and Research (BMBF, grant no. 01LS1201A1)

Blennow, K., Persson, J., Gonçalves, L. M. S., Borys, A., Dutcǎ, I., Hynynen, J., Janeczko, E., Lyubenova, M., Merganič, J., Merganičová, K., Peltoniemi, M., Petr, M., Reboredo, F., Vacchiano, G., & Reyer, C. P. O. (2020). The role of beliefs, expectations and values in decision-making favoring climate change adaptation : Implications for communications with European forest professionals. Environmental Research Letters, 15(11), 1-10. [114061]. https://doi.org/10.1088/1748-9326/abc2fa Beliefs, expectations and values are often assumed to drive decisions about climate change adaptation. We tested hypotheses based on this assumption using survey responses from 508 European forest professionals in ten countries. We used the survey results to identify communication needs and the decision strategies at play, and to develop guidelines on adequate communications about climate change adaptation. We observed polarization in the positive and negative values associated with climate change impacts accepted by survey respondents. We identified a mechanism creating the polarization that we call the 'blocked belief' effect. We found that polarized values did not correlate with decisions about climate change adaptation. Strong belief in the local impacts of climate change on the forest was, however, a prerequisite of decision-making favoring adaptation. Decision-making in favor of adaptation to climate change also correlated with net values of expected specific impacts on the forest and generally increased with the absolute value of these in the absence of 'tipping point' behavior. Tipping point behavior occurs when adaptation is not pursued in spite of the strongly negative or positive net value of expected climate change impacts. We observed negative and positive tipping point behavior, mainly in SW Europe and N-NE Europe, respectively. In addition we found that advice on effective adaptation may inhibit adaptation when the receiver is aware of effective adaptation measures unless it is balanced with information explaining how climate change leads to negative impacts. Forest professionals with weak expectations of impacts require communications on climate change and its impacts on forests before any advice on adaptation measures can be effective. We develop evidence-based guidelines on communications using a new methodology which includes Bayesian machine learning modeling of the equivalent of an expected utility function for the adaptation decision problem. publishersversion published

Beliefs, expectations and values are often assumed to drive decisions about climate change adaptation. We tested hypotheses based on this assumption using survey responses from 508 European forest professionals in ten countries. We used the survey results to identify communication needs and the decision strategies at play, and to develop guidelines on adequate communications about climate change adaptation. We observed polarization in the positive and negative values associated with climate change impacts accepted by survey respondents. We identified a mechanism creating the polarization that we call the 'blocked belief' effect. We found that polarized values did not correlate with decisions about climate change adaptation. Strong belief in the local impacts of climate change on the forest was, however, a prerequisite of decision-making favoring adaptation. Decision-making in favor of adaptation to climate change also correlated with net values of expected specific impacts on the forest and generally increased with the absolute value of these in the absence of 'tipping point' behavior. Tipping point behavior occurs when adaptation is not pursued in spite of the strongly negative or positive net value of expected climate change impacts. We observed negative and positive tipping point behavior, mainly in SW Europe and N-NE Europe, respectively. In addition we found that advice on effective adaptation may inhibit adaptation when the receiver is aware of effective adaptation measures unless it is balanced with information explaining how climate change leads to negative impacts. Forest professionals with weak expectations of impacts require communications on climate change and its impacts on forests before any advice on adaptation measures can be effective. We develop evidence-based guidelines on communications using a new methodology which includes Bayesian machine learning modeling of the equivalent of an expected utility function for the adaptation decision problem.

Petr, M., Vacchiano, G., Thom, D., Mairota, P., Kautz, M., Gonçalves, L. M. D. S., ... Reyer, C. P. O. (2019). Inconsistent recognition of uncertainty in studies of climate change impacts on forests. Environmental Research Letters, 14(11), 1-13. [113003]. https://doi.org/10.1088/1748-9326/ab4670 Background. Uncertainty about climate change impacts on forests can hinder mitigation and adaptation actions. Scientific enquiry typically involves assessments of uncertainties, yet different uncertainty components emerge in different studies. Consequently, inconsistent understanding of uncertainty among different climate impact studies (from the impact analysis to implementing solutions) can be an additional reason for delaying action. In this review we (a) expanded existing uncertainty assessment frameworks into one harmonised framework for characterizing uncertainty, (b) used this framework to identify and classify uncertainties in climate change impacts studies on forests, and (c) summarised the uncertainty assessment methods applied in those studies. Methods. We systematically reviewed climate change impact studies published between 1994 and 2016. We separated these studies into those generating information about climate change impacts on forests using models -'modelling studies', and those that used this information to design management actions-'decision-making studies'. We classified uncertainty across three dimensions: nature, level, and location, which can be further categorised into specific uncertainty types. Results. We found that different uncertainties prevail in modelling versus decision-making studies. Epistemic uncertainty is the most common nature of uncertainty covered by both types of studies, whereas ambiguity plays a pronounced role only in decision-making studies. Modelling studies equally investigate all levels of uncertainty, whereas decision-making studies mainly address scenario uncertainty and recognised ignorance. Finally, the main location of uncertainty for both modelling and decision-making studies is within the driving forces-representing, e.g. socioeconomic or policy changes. The most frequently used methods to assess uncertainty are expert elicitation, sensitivity and scenario analysis, but a full suite of methods exists that seems currently underutilized. Discussion & Synthesis. The misalignment of uncertainty types addressed by modelling and decision-making studies may complicate adaptation actions early in the implementation pathway. Furthermore, these differences can be a potential barrier for communicating research findings to decision-makers. publishersversion published

The data show that dramatic climate changes, heat and weather extremes are already impacting people, damaging crops and coastlines and putting food, water, and energy security at risk. Across the three regions studied in this report, record-breaking temperatures are occurring more frequently, rainfall has increased in intensity in some places, while drought-prone regions are getting dryer. In an overview of social vulnerability, the poor and underprivileged, as well as the elderly and children, are found to be often hit the hardest. There is growing evidence, that even with very ambitious mitigation action, warming close to 1.5°C above pre-industrial levels by mid-century is already locked-in to the Earth’s atmospheric system and climate change impacts such as extreme heat events may now be unavoidable.1 If the planet continues warming to 4°C, climatic conditions, heat and other weather extremes considered highly unusual or unprecedented today would become the new climate normal—a world of increased risks and instability. The consequences for development would be severe as crop yields decline, water resources change, diseases move into new ranges, and sea levels rise. The task of promoting human development, of ending poverty, increasing global prosperity, and reducing global inequality will be very challenging in a 2°C world, but in a 4°C world there is serious doubt whether this can be achieved at all. Immediate steps are needed to help countries adapt to the climate impacts being felt today and the unavoidable consequences of a rapidly warming world. The benefits of strong, early action on climate change, action that follows clean, low carbon pathways and avoids locking in unsustainable growth strategies, far outweigh the costs. Many of the worst projected climate impacts could still be avoided by holding warming to below 2°C. But, the time to act is now. This report focuses on the risks of climate change to development in Latin America and the Caribbean, the Middle East and North Africa, and parts of Europe and Central Asia. Building on earlier Turn Down the Heat reports this new scientific analysis examines the likely impacts of present day (0.8°C), 2°C and 4°C warming above pre-industrial temperatures on agricultural production, water resources, ecosystem services and coastal vulnerability for affected populations.

Located in a relatively dry region and characterized by mainly sandy soils, the German Federal State of Brandenburg (surrounding the capital city of Berlin) is especially vulnerable to climate change impacts (e.g. summer droughts) and cascading effects on ecological systems (e.g. decreasing ground water tables, water stress, fire risk, productivity losses) with socioeconomic implications. Furthermore, a complex interplay of unemployment, rural exodus, and an aging population challenges this structurally weak region. We discuss adaptation measures that are either implemented or planned, as well as research into adaptation strategies to climate change for the sectors forestry, agriculture, and water management as well as in nature conservation in the light of socioeconomic and ecological challenges and benefits. In doing so, we adopt a systemic view of Brandenburg where the sectors discussed are seen as subsystems embedded in a larger regional system. This at least partially holarchical approach enables the identification of conflicts between adaptation measures, but also of synergies among the sectors that pertain to successful adaptation to climate change. The insights gained ultimately highlight the need for cross-sectoral, adaptive management practices that jointly target a sustainable regional development.

The process-based forest growth model 4C (FORESEE - FORESt Ecosystems in a Changing Environment) was used to analyze the growth of a mixed oak-pine stand [Quercus petraea (Mattuschka) Liebl., Pinus sylvestris L.]. The oak-pine stand is typical for the ongoing forest transformation in the north-eastern lowlands. The pine and the oak trees are 104 and 9 years old, respectively. Three different management scenarios (A, B, C) with different thinning grades and a thinning interval of five years were simulated. Every management scenario was simulated under three different climate scenarios (0K, 2K, 3K) compiled by the regional statistical climate model STAR 2.0 (PIK). For each climate scenario 100 different realisations were generated. The realisations of the climate scenarios encompass the period 2036-2060 and exhibit an increase of mean annual temperature of zero, two and three Kelvin until 2060, respectively. We selected 9 model outputs concerning biomass, growth and harvest which were aggregated to a single total performance index (TPI). The TPI was used to assess the management scenarios with regard to three management objectives (carbon sequestration, intermediate, timber yield) under climate change until 2060. We found out that management scenario A led to the highest TPI concerning the carbon sequestration objective and management scenario C performed best concerning the two other objectives. The analysis of variance in the growth related model outputs showed an increase of climate uncertainty with increasing climate warming. Interestingly, the increase of climate induced uncertainty is much higher from 2 to 3 K than from 0 to 2 K., Se ha utilizado un modelo forestal basado en procesos denominado 4C (FORESEE - FORESt Ecosystems in a Changing Environment) para analizar el crecimiento de un masa forestal con mezcla de Quercus petraea y Pinus sylvestris. Ésta es una mezcla típica en las áreas de transformación forestal en las zonas bajas del noreste de Alemania. Los pinos y los robles tienen una edad de 104 y 9 años respectivamente. Se simularon tres escenarios diferentes de manejo (A, B, C) con diferentes grados de claras e intervalos de clara de 5 años. Cada escenario de manejo fue simulado bajo tres escenarios climáticos (0K, 2K, 3K) los cuales se calcularon por el modelo regional climático estadístico STAR 2.0 (PIK). Se generaron 100 diferentes realizaciones para cada escenario climático. Las realizaciones incluyen el período 2036-2060 y presentan un aumento de la temperatura anual de cero, dos y tres grados Kelvin hasta el año 2060, respectivamente. Seleccionamos 9 salidas del modelo relacionadas con la biomasa, crecimiento y rendimiento que se combinaron en un único índice de rendimiento total (TPI, total performance index). El TPI fue analizado para investigar los escenarios de manejo con respecto a tres objetivos de manejo (secuestro de carbono, máximo rendimiento maderero, y un escenario intermedio a ambos) bajo la influencia de cambio climático hasta el año 2060. Nuestros resultados indican que el escenario A muestra el TPI más alto con respecto al secuestro de carbono, y el escenario C tuvo el mejor resultado respecto a los otros dos objetivos. El análisis de varianza en las salidas relativas al crecimiento mostró que mientras más evoluciona el calentamiento global, más crece la incertidumbre climática. Cabe destacar que el aumento de la incertidumbre inducida por el clima es mucho mayor al aumentar de 2 a 3 K que de 0 a 2 K.

Forest ecosystems, their products and services play an important role in achieving ambitious climate change mitigation objectives at the same time requiring profound adaptation to climate change. Forest management schemes to support climate action have to be developed within their regional context but also have to be aligned with national or EU-level climate, forest and sustainability policies. The conference on “Managing forests in the 21st century” is the final conference of the FORMASAM, REFORCE and FOREXCLIM research projects. The conference brings together scientific experts on forest management from all over Europe facing very specific management challenges. The aim is to discuss and improve the understanding the role of forests and forest management in the context of climate change. The conference addresses climate change impacts, as well as needs for mitigation and adaptation especially with regard to the following scientific questions: 1. What are the impacts of climate extremes and disturbances? 2. What are the management challenges (and options) for resilient forests? 3. What can we do to increase the contribution of forest management to climate change mitigation?

Planning for adaptation to climate change is often regarded to be a local imperative and considered to be more effective if grounded on a solid evidence base and recognisant of relevant climate projections. Research has already documented some of the challenges of making climate information usable in decision-making but has not yet sufficiently reflected on the role of the wider institutional and regulatory context. This article examines the impact of the external institutional context on the use and usability of climate projections in local government through an analysis of 44 planning and climate change (adaptation) documents and 54 semi-structured interviews with planners in England and Germany conducted between July 2013 and May 2014. We show that there is little demand for climate projections in local adaptation planning in either country due to existing policy, legal and regulatory frameworks. Local government in England has not only experienced a decline in use of climate projections, but also the waning of the climate change adaptation agenda more widely, amidst changes in the planning and regulatory framework and severe budget cuts. In Germany, spatial planning makes substantial use of past and present climate data, but the strictly regulated nature of planning prevents the use of climate projections, due to their inherent uncertainties. Findings from the two countries highlight that if we are to better understand the usability of climate projections, we need to be more aware of the institutional context within which planning decisions are made. Otherwise we run the risk of continuing to provide tools and information that are of limited use within their intended context. Electronic supplementary material The online version of this article (doi:10.1007/s10113-016-1030-3) contains supplementary material, which is available to authorized users.