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COVID-19 has revealed how challenging it is to manage global, systemic and compounding crises. Like COVID-19, climate change impacts, and maladaptive responses to them, have potential to disrupt societies at multiple scales via networks of trade, finance, mobility and communication, and to impact hardest on the most vulnerable. However, these complex systems can also facilitate resilience if managed effectively. This review aims to distil lessons related to the transboundary management of systemic risks from the COVID-19 experience, to inform climate change policy and resilience building. Evidence from diverse fields is synthesised to illustrate the nature of systemic risks and our evolving understanding of resilience. We describe research methods that aim to capture systemic complexity to inform better management practices and increase resilience to crises. Finally, we recommend specific, practical actions for improving transboundary climate risk management and resilience building. These include mapping the direct, cross-border and cross-sectoral impacts of potential climate extremes, adopting adaptive risk management strategies that embrace heterogenous decision-making and uncertainty, and taking a broader approach to resilience which elevates human wellbeing, including societal and ecological resilience.

Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (−2 to +9°C) and precipitation (−50 to +50%). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed th

Adaptation of crops to climate change has to be addressed locally due to the variability of soil, climate and the specific socio-economic settings influencing farm management decisions. Adaptation of rainfed cropping systems in the Mediterranean is especially challenging due to the projected decline in precipitation in the coming decades, which will increase the risk of droughts. Methods that can help explore uncertainties in climate projections and crop modelling, such as impact response surfaces (IRSs) and ensemble modelling, can then be valuable for identifying effective adaptations. Here, an ensemble of 17 crop models was used to simulate a total of 54 adaptation options for rainfed winter wheat (Triticum aestivum) at Lleida (NE Spain). To support the ensemble building, an ex post quality check of model simulations based on several criteria was performed. Those criteria were based on the "According to Our Current Knowledge" (AOCK) concept, which has been formalized here. Adaptations were based on changes in cultivars and management regarding phenology, vernalization, sowing date and irrigation. The effects of adaptation options under changed precipitation (P), temperature (T), [CO2] and soil type were analysed by constructing response surfaces, which we termed, in accordance with their specific purpose, adaptation response surfaces (ARSs). These were created to assess the effect of adaptations through a range of plausible P, T and [CO2] perturbations. The results indicated that impacts of altered climate were predominantly negative. No single adaptation was capable of overcoming the detrimental effect of the complex interactions imposed by the P, T and [CO2] perturbations except for supplementary irrigation (sI), which reduced the potential impacts under most of the perturbations. Yet, a combination of adaptations for dealing with climate change demonstrated that effective adaptation is possible at Lleida. Combinations based o

This study explored the utility of the impact response surface (IRS) approach for investigating model ensemble crop yield responses under a large range of changes in climate. IRSs of spring and winter wheat Triticum aestivum yields were constructed from a 26-member ensemble of process-based crop simulation models for sites in Finland, Germany and Spain across a latitudinal transect. The sensitivity of modelled yield to systematic increments of changes in temperature (-2 to +9°C) and precipitation (-50 to +50%) was tested by modifying values of baseline (1981 to 2010) daily weather, with CO2 concentration fixed at 360 ppm. The IRS approach offers an effective method of portraying model behaviour under changing climate as well as advantages for analysing, comparing and presenting results from multi-model ensemble simulations. Though individual model behaviour occasionally departed markedly from the average, ensemble median responses across sites and crop varieties indicated that yields decline with higher temperatures and decreased precipitation and increase with higher precipitation. Across the uncertainty ranges defined for the IRSs, yields were more sensitive to temperature than precipitation changes at the Finnish site while sensitivities were mixed at the German and Spanish sites. Precipitation effects diminished under higher temperature changes. While the bivariate and multi-model characteristics of the analysis impose some limits to interpretation, the IRS approach nonetheless provides additional insights into sensitivities to inter-model and inter-annual variability. Taken together, these sensitivities may help to pinpoint processes such as heat stress, vernalisation or drought effects requiring refinement in future model development.

Climate change is already affecting many natural systems and human environments worldwide, like the semiarid Guadiana Basin in Spain. This paper illustrates a systematic analysis of climate change adaptation in the Guadiana irrigation farming region. The study applies a solution-oriented diagnostic framework structured along a series of sequential analytical steps. An initial stage integrates economic and hydrologic modeling to evaluate the effects of climate change on the agriculture and water sectors. Next, adaptation measures are identified and prioritized through a stakeholder-based multi-criteria analysis. Finally, a social network analysis identifies key actors and their relationships in climate change adaptation. The study shows that under a severe climate change scenario, water availability could be substantially decreased and drought occurrence will augment. In consequence, farmers will adapt their crops to a lesser amount of water and income gains will diminish, particularly for smallholder farms. Among the various adaptation measures considered, those related to private farming (new crop varieties and modern irrigation technologies) are ranked highest, whereas public-funded hard measures (reservoirs) are lowest and public soft measures (insurance) are ranked middle. In addition, stakeholders highlighted that the most relevant criteria for selecting adaptation plans are environmental protection, financial feasibility and employment creation. Nonetheless, the social network analysis evidenced the need to strengthen the links among the different stakeholder groups to facilitate the implementation of adaptation processes. In sum, the diagnostic framework applied in this research can be considered a valuable tool for guiding and supporting decision making in climate change adaptation and communicating scientific results.

Species ranges are expected to move polewards following the changing climate, which poses novel challenges to the protected area network, particularly at northern latitudes. Here we study how well protected areas are likely to sustain populations of birds of conservation concern under a changing climate in northern Europe, in Finland. We fitted bioclimatic envelope models generated for 100 bird species to climate scenario data for the years 2051–2080 and three alternative emission scenarios in a 10-km grid system to predict changes in the species probability of occurrence. We related the projected changes in the climatic suitability to the amount of protected preferred habitat for the study species in the 10-km grid cells, and based on the cover of four main CORINE Land Cover classes in each conservation area in Finland. The probability of occurrence of all species (except marshland birds) decreased according to all scenarios, the decline being greatest in southern and smallest in northern boreal zones. This decline was slightly greater in unprotected than in protected areas for species of forests, mires and mountain habitats. The climatically suitable areas for the species were predicted to shift northwards, but the potential gain of southern species of conservation concern appears not to compensate for the loss of northern species. Thus, a representative protected area network is needed in all boreal zones. Overall, our results show that species-specific habitat preferences and habitat availability should be taken into account when assessing the efficiency of a protected area network in a changing climate.

Aim This paper describes a set of integrative scenarios developed in the ALARM (Assessing LArge-scale environmental Risks for biodiversity with tested Methods) project. The ultimate aim of ALARM was to develop and test methods and protocols for the assessment of large-scale environmental risks to biodiversity and to evaluate mitigation options. Scenarios provide a tool for exploring such risks and the policy options to mitigate them; therefore they play a central role within the ALARM project.Methods Three integrative scenarios (liberalization, business as might be usual, sustainability) were developed and illustrated using the econometric model described in a subsequent paper. They are contextualized with projections from climate models and provide the input for model-based assessments of biodiversity trends. Additionally, three shock scenarios were developed (Gulf Stream collapse, peak oil, pandemic) to demonstrate the limits of linear extrapolation. As these extend beyond model capabilities, they are discussed semi-quantitatively based on modelling insights.Results Although the policy impacts on biodiversity are different for different pressures, biomes and species groups, some general trends could be identified. An extension of current EU policies will act as a brake on current trends by slowing down the loss of biodiversity in many cases and in most biomes, but it will be capable of neither halting nor of reversing the loss. Liberalization has the effect of accelerating biodiversity loss across the board, with few exceptions. A coherent sustainability scenario is clearly the most effective at preserving biodiversity, but the variant tested here still does not halt losses in all cases.Main conclusions Current EU policies for protecting biodiversity appear to be insufficient to reverse ongoing losses. Coherent sustainability strategies are effective at conserving biodiversity, but in order to assess losses and then reverse them, measures would need to be intr

Aim To assess the extent to which climate change might cause changes in potential natural vegetation (PNV) across Europe.Location Europe.Method We parameterized a generalized dynamic vegetation model (LPJ-GUESS) for the most common European tree species, and, for the first time, modelled large-scale vegetation dynamics using a process-based model explicitly representing tree species, age cohorts, gap dynamics and biogeochemical cycles in a single framework. For projections, the model was driven with climate scenario data from two atmosphere–ocean general circulation models (AOGCMs), downscaled to 10 × 10′ spatial resolution (c. 18.5 × 12 km at 50° N).Results At a general level, modelled present-day PNV corresponded better with an expert reconstruction of the PNV than most earlier plant functional type (PFT)-based simulations, but at a finer scale the model and the expert map showed substantial discrepancies in some areas. Simulations until 2085 showed considerable successional shifts in vegetation types in most areas: 31–42% of the total area of Europe was projected to be covered by a different vegetation type by the year 2085. In the long term, equilibrium changes are substantially larger: simulations with one climate scenario suggest that 76–80% of the European land surface could exist within another PNV if climate was stabilized by the end of the century and vegetation had unlimited time to achieve equilibrium with the new climate. ‘Hotspots’ of change include arctic and alpine ecosystems, where trees replace tundra in the model, and the transition zone between temperate broad-leaved and boreal conifer forest. In southern Europe, the model projected widespread shifts from forest to shrublands as a result of drought.Main conclusions The model presents a considerable advance in modelling dynamic changes in natural vegetation across Europe. Climate change might cause substantial changes in PNV across Europe, which should be considered in the management

Vulnerability of 100 European butterfly species to climate change was assessed using 13 different criteria and data on species distributions, climate, land cover and topography from 1,608 grid squares 30' × 60' in size, and species characteristics increasing the susceptibility to climate change. Four bioclimatic model-based criteria were developed for each species by comparing the present-day distribution and climatic suitability of the occupied grid cells with projected distribution and suitability in the future using the HadCM3-A2 climate scenario for 2051-2080. The proportions of disadvantageous land cover types (bare areas, water, snow and ice, artificial surfaces) and cultivated and managed land in the occupied grid squares and their surroundings were measured to indicate the amount of unfavourable land cover and dispersal barriers for butterflies, and topographical heterogeneity to indicate the availability of potential climatic refugia. Vulnerability was also assessed based on species dispersal ability, geographical localization and habitat specialization. Northern European species appeared to be amongst the most vulnerable European butterflies. However, there is much species-to-species variation, and species appear to be threatened due to different combinations of critical characteristics. Inclusion of additional criteria, such as life-history species characteristics, topography and land cover to complement the bioclimatic model-based species vulnerability measures can significantly deepen the assessments of species susceptibility to climate change.

The field site network (FSN) plays a central role in conducting joint research within all Assessing Large-scale Risks for biodiversity with tested Methods (ALARM) modules and provides a mechanism for integrating research on different topics in ALARM on the same site for measuring multiple impacts on biodiversity. The network covers most European climates and biogeographic regions, from Mediterranean through central European and boreal to subarctic. The project links databases with the European-wide field site network FSN, including geographic information system (GIS)-based information to characterise the test location for ALARM researchers for joint on-site research. Maps are provided in a standardised way and merged with other site-specific information. The application of GIS for these field sites and the information management promotes the use of the FSN for research and to disseminate the results. We conclude that ALARM FSN sites together with other research sites in Europe jointly could be used as a future backbone for research proposals.

Aim To assess whether the water availability measures commonly used in species distribution models might be misleading because they do not account for the hydrological effects of changes in vegetation structure and functioning.Location Europe.Methods We compared different methods for estimating water availability in species distribution models with the soil water content predicted by a process-based ecosystem model. The latter also accounted for the hydrological effects of dynamic changes in vegetation structure and functioning, including potential physiological effects of increasing CO2.Results All proxies showed similar patterns of water availability across Europe for current climate, but when projected into the future, the changes in the simpler water availability measures showed no correlation with those projected by the more complex ecosystem model, even if CO2 effects were switched off.Main conclusions Results from species distribution modelling studies concerning future changes in species ranges and biodiversity should be interpreted with caution, and more process-based representations of the water balance of terrestrial ecosystems should be considered within these models.

The field site network (FSN) plays a central role in conducting joint research within all Assessing Large-scale Risks for biodiversity with tested Methods (ALARM) modules and provides a mechanism for integrating research on different topics in ALARM on the same site for measuring multiple impacts on biodiversity. The network covers most European climates and biogeographic regions, from Mediterranean through central European and boreal to subarctic. The project links databases with the European-wide field site network FSN, including geographic information system (GIS)-based information to characterise the test location for ALARM researchers for joint on-site research. Maps are provided in a standardised way and merged with other site-specific information. The application of GIS for these field sites and the information management promotes the use of the FSN for research and to disseminate the results. We conclude that ALARM FSN sites together with other research sites in Europe jointly could be used as a future backbone for research proposals