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Warming climate and precipitation changes induce notable shifts in climate zones. In this study, the latest generation of global climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the previous generation CMIP5 under high‐emission scenarios are used together with observations and applied to the Köppen‐Geiger climate classification. The aim is to shed light on how projected warming and changes in precipitation will influence future climate zones and their associated ecosystems while revealing differences between the two model generations. Compared to CMIP5 models, CMIP6 models exhibit slightly improved performance in replicating the observed Köppen‐Geiger map for the historical (1976–2005) period and similar inter‐model agreement for the future. The models show major changes in climate zones with a range of projections depending on which ensemble subset is used: 37.9%–48.1% of the global land area is projected to change climate zone by the end of the century, with the most pronounced changes expected over Europe (71.4%–88.6%) and North America (51.2%–65.8%). CMIP6 models project a higher rate of areal climate zone change (km2/year) throughout the 21st century, which is mainly driven by their greater global land warming rates. Using a likely equilibrium climate sensitivity subset of CMIP6 models that is consistent with the latest evidence constrains the climate zone shifts, and their projections better match the results of CMIP5 simulations. Although the high warming rates of some CMIP6 models are less credible, the risks associated with them are greater, and they heighten the need for urgent action to preserve terrestrial ecosystems. Plain Language Summary: Köppen‐Geiger climate classification is a tool to map regional climate zones based on a region's temperature and precipitation. In recent decades, increasing temperatures and changing precipitation trends have started to affect the distribution of those climate zones, and more extensive changes are expected throughout the 21st century. In this paper, we assess the observed and expected changes in the global distribution of Köppen‐Geiger climate zones using observations along with the latest and the previous generation of global climate model projections. We find that shifts in climate zones are more pronounced in the latest generation of models due to their questionable greater global warming rate projections. Depending on which subset of model projections is used, up to half of the Earth's land area faces the risk of shifting to a different climate zone by the end of the century, with the greatest changes expected in Europe and North America. The rate of change (affected area per year) is also projected to accelerate through the 21st century, suggesting that vulnerable species and agricultural practices might have less time to adapt to changes in climate zones than previously projected. Key Points: Coupled Model Intercomparison Project Phase 6 (CMIP6) exhibits slightly improved performance in simulating the globally observed historical Köppen‐Geiger climate zones compared to CMIP5By the end of the century, 38%–48% of the global land area is projected to be in a different climate zone than todayThe rate of climate zone change is projected to accelerate, with more pronounced rates in CMIP6 due to considerably higher warming rates [ABSTRACT FROM AUTHOR]

While the importance of permanent grasslands (PG) for the conservation of high nature value habitats is often acknowledged, their role in most of the main sustainable food system scenarios published in the last few years is less explicit. In the best case, the place of permanent grassland in scenarios and policy agendas is their conservation; in the worst one, they are simply replaced by afforested land or cropland, considered as a better option when the focus is on GHG emissions only. In this paper, we defend the idea that several misinterpretations of the positive and negative impacts of ruminants, the 'natural' users of PG, explain why ruminants are poorly addressed by most scenarios. Based on the findings of an agroecological scenario for Europe—TYFA, standing for Ten Years For Agroecology—in which extensive permanent grassland and ruminants together play a prominent role for biodiversity conservation, nitrogen cycling and climate change mitigation and adaptation, we call for a research agenda that would better inform the specific role of PG in the provision of ecosystem services—and in particular those that depend on nitrogen management. [ABSTRACT FROM AUTHOR]

Statistical downscaling methods (SDMs) are techniques used to downscale and/or bias‐correct climate model results to regional or local scales. The European network VALUE developed a framework to evaluate and inter‐compare SDMs. One of VALUE's experiments is the perfect predictor experiment that uses reanalysis predictors to isolate downscaling skill. Most evaluation papers for SDMs employ simple statistical diagnostics and do not follow a process‐based rationale. Thus, in this paper, a process‐based evaluation has been conducted for the more than 40 participating model output statistics (MOS, mostly bias correction) and perfect prognosis (PP) methods, for temperature and precipitation at 86 weather stations across Europe. The SDMs are analysed following the so‐called "regime‐oriented" technique, focussing on relevant features of the atmospheric circulation at large to local scales. These features comprise the North Atlantic Oscillation, blocking and selected Lamb weather types and at local scales the bora wind and the western Iberian coastal‐low level jet. The representation of the local weather response to the selected features depends strongly on the method class. As expected, MOS is unable to generate process sensitivity when it is not simulated by the predictors (ERA‐Interim). Moreover, MOS often suffers from an inflation effect when a predictor is used for more than one station. The PP performance is very diverse and depends strongly on the implementation. Although conditioned on predictors that typically describe the large‐scale circulation, PP often fails in capturing the process sensitivity correctly. Stochastic generalized linear models supported by well‐chosen predictors show improved skill to represent the sensitivities. [ABSTRACT FROM AUTHOR]

Aim: The Expansion‐Contraction model has been used to explain the responses of species to climatic changes. During periods of unfavourable climatic conditions, species retreat to refugia from where they may later expand. This paper focuses on the palaeoecology of red deer over the past 54 ka across Europe and the Urals, to reveal patterns of change in their range and explore the role of environmental conditions in determining their distribution. Location: Europe and western Asia to 63°E. Taxon: Red deer (Cervus elaphus). Methods: We collected 984 records of radiocarbon‐dated red deer subfossils from the Late Pleistocene and the Holocene, including 93 original dates. For each deer sample we compiled climatic and biome type data for the corresponding time intervals. Results: During the last 54 ka changes in red deer range in Europe and the Urals were asynchronous and differed between western and eastern Europe and western Asia due to different environmental conditions in those regions. The range of suitable areas for deer during the Last Glacial Maximum (LGM) was larger than previously thought and covered vast regions not only in southern but also in western and eastern Europe. Throughout the period investigated the majority of specimens inhabited forests in the temperate climatic zone. The contribution of forests in deer localities significantly decreased during the last 4 ka, due to deforestation of Europe caused by humans. Mean January temperature was the main limiting factor for species distribution. Over 90% of the samples were found in areas where mean January temperature was above −10°C. Main conclusions: Red deer response to climatic oscillations are in agreement with the Expansion‐Contraction model but in contradiction to the statement of only the southernmost LGM refugia of the species. During the last 54 ka red deer occurred mostly in forests of the temperate climatic zone. [ABSTRACT FROM AUTHOR]

This paper explores how deliberative workshops might enhance social learning about climate change adaptation among land managers in northwest Europe (Scotland). To date, methods for enhancing social learning in the context of adaptation and climate change have been neglected. In this study, location specific agro-meteorological indicators for both observed and future climate data were produced. The indicators were used as a basis for discussion in four deliberative workshops. The workshops sought to raise awareness of climate change issues, ensure the validity and utility of the indicators, stimulate thinking about adaptive responses and increase land managers' capacity to adapt. Land managers' adaptations to climate change fell into four broad categories: changing what they do, how they do it, when they do it or the frequency with which they do it. This paper therefore reflects on the use of deliberative workshops as an effective technique to enhance social learning regarding adapting to climate change. Copyright © 2009 John Wiley & Sons, Ltd and ERP Environment. [ABSTRACT FROM AUTHOR]

This paper presents results from a large multi-country study focusing on public perceptions of climate change and relevant mitigation and adaptation policies in Spain, Netherlands, UK and Germany. The purpose of this paper is two-fold: first, to understand the nature of public perceptions of global climate change in different countries; and secondly, to gauge the public's support of climate change measures in terms of mitigation and adaptation policies. Our analysis shows high levels of public indecisiveness regarding the danger climate change poses, which source of climate change information to trust and whether to support any mitigation or adaptation strategies. The high levels of uncertainty present an opportunity to increase policy support and foster behavioural changes in the future through well-designed communication programmes. Therefore, this study has identified several aspects that need to be considered in future communication programmes. Copyright © 2015 John Wiley & Sons, Ltd and ERP Environment [ABSTRACT FROM AUTHOR]

Researchers from various disciplines have built impressive but distinct compendia on climate change; the defining challenge for humanity. In the spirit of Lord Dahrendorf, this paper represents the output of interdisciplinary collaboration and integrates state-of-the-art academic expertise from the fields of philosophy, economics and governance. Our focus is on Europe, which is widely perceived as a leader in climate change mitigation and adaptation. However, leadership weakness on climate over recent years, largely due to recession and political vacillation, is eroding this perception. What is needed is a firm justification for strong climate action, acknowledgement of the available tools, awareness of the reasons for our failures to date, and a realistic, but goal-oriented strategy for an integrated climate policy. We therefore present current normative insights from climate justice research highlighting the need to make institutions responsive to those most vulnerable; we discuss the economics of the transition to a low-carbon economy, pointing to key policy instruments and post-2020 climate targets for the EU; we contrast the normative and quantitative synoptic principles with the particularistic implementation schemes and politics of (not) implementing measures on the ground; and we suggest a careful coordination of European climate policies with acute challenges that could increase both climate justice and political feasibility. [ABSTRACT FROM AUTHOR]

Growing season length (GSL) indices derived from surface air temperature are frequently used in climate monitoring applications. The widely used Expert Team on Climate Change Detection and Indices (ETCCDI) definition aims to give a broadly applicable measure of the GSL that is indicative of the duration of the mild part of the year. In this paper long‐term trends in that index are compared with an alternative measure calculated using a time series decomposition technique (empirical ensemble mode decomposition [EEMD]). It is demonstrated that the ETCCDI index departs from the mild‐season definition as its start and end dates are determined by temperature events operating within the synoptic timescale; this raises the inter‐annual variance of the index. The EEMD‐derived index provides a less noisy and more realistic index of the GSL by filtering out the synoptic‐scale variance and capturing the annual‐cycle and longer timescale variability. Long‐term trends in the GSL are comparable between the two indices, with an average increase in length of around 5 days/decade observed for the period 1965–2016. However, the results using the EEMD index display a more coherent picture of significant trends than has been previously observed. Furthermore, the EEMD‐derived growing season parameters are more closely related to variations in seasonal‐mean hemispheric‐scale atmospheric circulation patterns, with around 57% of the inter‐annual variation in the start of the growing season being connected to the North Atlantic Oscillation and East Atlantic patterns, and around 55% of variation in the end of the growing season being associated with East Atlantic/west Russia‐type patterns. Long‐term trends and inter‐annual variability of the thermal growing season length across Europe are compared by comparing two indices: the ETCCDI definition and a new index calculated using a time series decomposition technique (EEMD). Long‐term trends are comparable between the two indices. However, the EEMD index displays a much more coherent picture of significant trends than has been previously observed, and a much closer relationship to hemispheric modes of atmospheric circulation variability. [ABSTRACT FROM AUTHOR]

ABSTRACT Projection of future changes in river flow regimes and their impact on river ecosystem health is a major research challenge. This paper assesses the implications of projected future shifts in river flows on in-stream and riparian ecosystems at the pan-European scale by developing a new methodology to quantify ecological risk due to flow alteration (ERFA). The river network was modelled as 33 668 cells (5′ longitude × 5′ latitude). For each cell, modelled monthly flows were generated for an ensemble of 10 scenarios for the 2050s and for the study baseline (naturalized flows for 1961-1990). These future scenarios consist of combinations of two climate scenarios and four socio-economic water-use scenarios (with a main driver of economy, policy, security or sustainability). Environmental flow implications are assessed using the new ERFA methodology, based on a set of monthly flow regime indicators (MFRIs). Differences in MFRIs between scenarios and baseline are calculated to derive ERFA classes (no, low, medium and high risk), which are based on the number of indicators significantly different from the baseline. ERFA classes are presented as colour-coded pan-European maps. Results are consistent between scenarios and show that European river ecosystems are under significant threat with about two-thirds at medium or high risk of change. Four main zones were identified (from highest to lowest risk severity): (i) Mediterranean rim, southwest part of Eastern Europe and Western Asia; (ii) Northern Europe and northeast part of Eastern Europe; (iii) Western and Eastern Europe; and (iv) inland North Africa. Patterns of flow alteration risk are driven by climate-induced change, with socio-economics as a secondary factor. These flow alterations could be manifested as changes to species and communities, and loss of current ecosystem functions and services. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT Cities and municipalities are vital actors in addressing climate change. Because they are directly affected by the consequences of environmental transformations, cities are motivated to shape adaptation and mitigation. This paper looks at the possible mechanisms which cities can use to engage in climate change issues without decoupling themselves from the national or sub-national level and while remaining consistent with other local initiatives. The paper analyses the European approach towards transnational municipal networks (TMNs) and community collective efforts and assesses its possible application in other jurisdictions. We argue that while TMNs are the institutional foundation for a concerted effort in climate change within and between countries; they are also subject to provisions from national and regional governments, which might hamper their benefits. Based on a typology of TMNs and an analysis of the national contexts, the paper finds that those networks that target a specific region and are supported by government have the most benefits for climate change. Copyright © 2013 John Wiley & Sons, Ltd and ERP Environment. [ABSTRACT FROM AUTHOR]

In a changing climate, it is likely that precipitation patterns will experience shifts in amount and seasonality, with a tendency towards increased drought in many parts of Europe. In order to investigate what could be some of the feedbacks of dry conditions on temperature, this paper has investigated close to 30 European locations to assess the influence of observed dry summer days on daily maximum temperature ( Tmax) as well as a clustering of rainless days, and finally the temperature impact related to drought conditions as defined by the Standardized Precipitation Index. The results show that for the three main European climatic regions investigated ('Mediterranean', 'Maritime', 'Continental'), the influence of rainless days is discernible, with an average difference between mean summer Tmax and Tmax during rainless days only of up to 1.5 °C. A further aim of the study is to determine whether recent shifts in the occurrence of rainless days during the summer have a bearing on temperature trends. Results show that shifts in rainless days explain only a fraction of the observed temperature change at the locations studied, thereby hinting that the enhanced greenhouse effect remains the dominant mechanism for temperature change. Finally, using a regional climate model, very preliminary insight into a 'greenhouse climate' highlights the fact that changes in dry conditions seem to confirm the findings for current climate, i.e. they account for only a fraction of the increase in temperatures. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

This paper provides an overview of the existing systems of natural hazard insurance in Europe, their structural characteristics and peculiarities. It also 0discusses the difficulties of adaptation of these systems to climate change and the growing number of natural disasters. Using Germany, Austria and Switzerland as examples, the paper demonstrates that based on the status quo, the Swiss monopoly insurance system, which is embedded within a unique direct voting environment, is most able to reduce micro- and macroeconomic disruptions resulting from natural hazards. 'Change in diversity' is seen to offer the best chance to arrive at insurance systems that are prepared for climate change while being adapted to local particularities. Efforts to harmonize national and regional systems as well as top-down EU initiatives are argued to be inadequate. Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment. [ABSTRACT FROM AUTHOR]

Climate change is already having impacts on biodiversity within Europe, with habitats and species needing to change and adapt to rising global temperatures and shifts in bio-climatic zones. Spatial planning represents an important intervention to further European, national and local biodiversity objectives for climate change adaptation. Drawing on case-studies of plans for inland and coastal areas, and involving stakeholder workshops, this paper reports on a trans-national study examining the scope of spatial plans in the Netherlands, England and France in addressing the impact of climate change. It concludes that spatial planning is making provision for biodiversity and dynamic natural processes. However, while good practice in planning for biodiversity under conditions of climate change is developing, systematic use is not being made of available procedures. The paper examines some of the barriers to implementation of this new policy commitment to climate change adaptation. Recommendations are made covering policy development to include climate change impacts upon biodiversity, modified procedures for plan-making and the appraisal of plans and projects. Amongst the specific measures recommended are the climate-proofing of projects and plans through the use of EIA and SEA; the integration of plans through adoption of common objectives and review of time horizons and boundaries; and an ecosystem-based planning approach. Copyright © 2008 John Wiley & Sons, Ltd and ERP Environment. [ABSTRACT FROM AUTHOR]

SummaryUnder the Kyoto Protocol, the European Union is committed to a reduction in CO2 emissions to 92% of baseline (1990) levels during the first commitment period (2008–2012). The Kyoto Protocol allows carbon emissions to be offset by demonstrable removal of carbon from the atmosphere. Thus, land-use/land-management change and forestry activities that are shown to reduce atmospheric CO2 levels can be included in the Kyoto targets. These activities include afforestation, reforestation and deforestation (article 3.3 of the Kyoto Protocol) and the improved management of agricultural soils (article 3.4). In this paper, we estimate the carbon mitigation potential of various agricultural land-management strategies and examine the consequences of European policy options on carbon mitigation potential, by examining combinations of changes in agricultural land-use/land-management. We show that no single land-management change in isolation can mitigate all of the carbon needed to meet Europe's climate change commitments, but integrated combinations of land-management strategies show considerable potential for carbon mitigation. Three of the combined scenarios, one of which is an optimal realistic scenario, are by themselves able to meet Europe's emission limitation or reduction commitments. Through combined land-management scenarios, we show that the most important resource for carbon mitigation in agriculture is the surplus arable land. We conclude that in order to fully exploit the potential of arable land for carbon mitigation, policies will need to be implemented to allow surplus arable land to be put into alternative long-term land-use. Of all options examined, bioenergy crops show the greatest potential for carbon mitigation. Bioenergy crop production also shows an indefinite mitigation potential compared to other options where the mitigation potential is finite. We suggest that in order to exploit fully the bioenergy option, the... [ABSTRACT FROM AUTHOR]

The connections of climatic variables to zoonotic and wildlife diseases remain uncertain. Here, we compiled a systematic database for the prevalence of 121 pathogenic microbial taxa in birds (ca 376 species) and bats (ca 39 species), including 11 939 observations from over 450 000 individuals across Europe and surrounding regions. We modelled the potential connection of climatic variables with the prevalence of 75 pathogenic microbial taxa at a multi‐pathogenic‐taxa level and of 17 most‐studied pathogenic taxa at a single‐pathogenic‐taxon level. According to the multi‐taxa model, the prevalence of bacterial taxa was positively associated with temperature, while this association was significantly weaker for eukaryotes and viruses. The prevalence of bacterial taxa was negatively associated with rainfall, while viruses showed a positive association with rainfall. These associations between climatic variables and prevalence of pathogenic taxa were not different between bird and bat hosts. According to the single‐taxon models, the prevalence of influenza A viruses, Plasmodium, and several bacterial taxa in birds and bats was positively associated with temperature. Rainfall showed positive associations with the prevalence of Usutu, Sindbis and Influenza A viruses but the directions of significant associations varied among bacterial taxa. Strikingly, this was evidenced also between bacterial taxa that share hosts and transmission mechanism hinting towards hitherto unknown features on pathogen ecology, e.g. Salmonella versus Campylobacter and Anaplasma versus Borrelia. Our results suggest that rising temperature and increasing precipitation will accelerate the threat of bird‐ and bat‐associated bacterial and viral pathogens to wildlife, domesticated animals and humans, respectively. However, the idiosyncratic relationships with climatic conditions among pathogenic taxa highlight the need for pathogen‐specific predictive models to understand future pathogen distributions. [ABSTRACT FROM AUTHOR]

Aim: Poleward range shifts of species are among the most obvious effects of climate change on biodiversity. As a consequence of these range shifts, species communities are predicted to become increasingly composed of warm‐dwelling species, but this has only been studied for a limited number of taxa, mainly birds, butterflies and plants. As species groups may vary considerably in their adaptation to climate change, it is desirable to expand these studies to other groups, from different ecosystems. Freshwater macroinvertebrates, such as dragonflies (Odonata), have been ranked among the species groups with highest priority. In this paper, we investigate how the occurrence of dragonflies in Europe has changed in recent decades, and if these changes are in parallel with climate change. Location: Europe. Methods: We use data from 10 European geographical regions to calculate occupancy indices and trends for 99 (69%) of the European species. Next, we combine these regional indices to calculate European indices. To determine if changes in regional dragonfly communities in Europe reflect climatic warming, we calculate Species Temperature Indices (STI), Multi‐species Indicators (MSI) and Community Temperature Indices (CTI). Results: 55 of 99 considered species increased in occupancy at European level, 32 species remained stable, and none declined. Trends for 12 species are uncertain. MSI of cold‐dwelling and warm‐dwelling species differ in some of the regions, but increased at a similar rate at European level. CTI increased in all regions, except Cyprus. The European CTI increased slightly. Main conclusions: European dragonflies, in general, have expanded their distribution in response to climate change, even though their CTI lags behind the increase in temperature. Furthermore, dragonflies proved to be a suitable species group for monitoring changes in communities, both at regional and continental level. [ABSTRACT FROM AUTHOR]

The paper summarises materials on the mammal remains in northeastern Europe, dated by radiocarbon. Altogether, 23 local faunas of small mammals and 47 local faunas of large mammals were analysed. Multidimensional statistical analysis shows a strong correlation between changes in small mammal fauna composition and climate changes throughout time. The correlations with the spatial gradients, however, are less pronounced. The faunas are classified into three groups: (1) faunas of Holocene age; (2) Late Pleistocene 'stadial' assemblages; and (3) Late Pleistocene 'interstadial' assemblages. In some cases, changes in species abundance are better understood in terms of biotic interrelations rather than of climatic effects. The most pronounced change in small mammal fauna composition and structure occurred at the Preboreal/ Boreal boundary, and a less conspicuous alteration took place at the LGM/Lateglacial transition. The most noticeable transformation in the large mammal fauna composition is dated to the early Holocene. Less significant changes are observed at the Middle Weichselian/ LGM transition and at the LGM/Lateglacial transition. It is safely concluded that variations in the faunas of small and large mammals recorded in NE Europe during the last 35 000 years occurred synchronously and unidirectionally. [ABSTRACT FROM AUTHOR]

According to Gloger's rule, animal colouration is expected to be darker in wetter and warmer climates. Such environmental clines are predicted to occur in colour polymorphic species and to be shaped by selection if colour morphs represent adaptations to different environments. We studied if the distribution of the colour polymorphic tawny owl (Strix aluco) morphs (a pheomelanic brown and a pale grey) across Europe follow the predictions of Gloger's rule and if there is a temporal change in the geographical patterns corresponding to regional variations in climate change. We used data on tawny owl museum skin specimen collections. First, we investigated long‐term spatiotemporal variation in the probability of observing the colour morphs in different climate zones. Second, we studied if the probability of observing the colour morphs was associated with general climatic conditions. Third, we studied if weather fluctuations prior to the finding year of an owl explain colour morph in each climate zone. The brown tawny owl morph was historically more common than the grey morph in every studied climate zone. Over time, the brown morph has become rarer in the temperate and Mediterranean zone, whereas it has first become rarer but then again more common in the boreal zone. Based on general climatic conditions, winter and summer temperatures were positively and negatively associated with the proportion of brown morph, respectively. Winter precipitation was negatively associated with the proportion of brown morph. The effects of 5‐year means of weather on the probability to observe a brown morph differed between climate zones, indicating region‐dependent effect of climate change and weather on tawny owl colouration. To conclude, tawny owl colouration does not explicitly follow Gloger's rule, implying a time and space‐dependent complex system shaped by many factors. We provide novel insights into how the geographic distribution of pheomelanin‐based colour polymorphism is changing. [ABSTRACT FROM AUTHOR]

We estimate the potential predictability of European winter temperature using factors based on physical studies of their influences on European winter climate. These influences include sea surface temperature patterns in different oceans, major tropical volcanoes, the quasi-biennial oscillation in the tropical stratosphere, and anthropogenic climate change. We first assess the predictive skill for winter mean temperature in northern Europe by evaluating statistical hindcasts made using multiple regression models of temperature for Europe for winter and the January-February season. We follow this up by extending the methodology to all of Europe on a 5° × 5° grid and include rainfall for completeness. These results can form the basis of practical prediction methods. However, our main aim is to develop ideas to act as a benchmark for improving the performance of dynamical climate models. Because we consider only potential predictability, many of the predictors have estimated values coincident with the winter season being forecast. However, in each case, these values are predictable on average with considerable skill in advance of the winter season. A key conclusion is that to reproduce the results of this paper, dynamical forecasting models will require a fully resolved stratosphere. Copyright © 2011 Royal Meteorological Society and British Crown copyright, the Met Office [ABSTRACT FROM AUTHOR]

ABSTRACT 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 introduced that extend beyond the steps tested in the ALARM sustainability scenario. [ABSTRACT FROM AUTHOR]

Lichens are thought to be sensitive indicators of global warming, as the spread of several thermophilous epiphytes in north-western Central Europe has been attributed to late 20th century warming. In the present paper, the potential contribution of late 20th century warming to the decline of arctic-alpine and boreal-montane lichen species is analyzed. Relevant ecological groups of lichens include terricolous heathland species, saxicolous species of exposed rock outcrops and boulder fields as well as epiphytes of mountain forests. These three groups of lichens experienced significant declines before the onset of late 20th century warming in the 1970s. These declines can be attributed to the abandonment of traditional land use systems in the case of the heathland lichens, increased recreational use of the exposed summits usually inhabited by cold-tolerant saxicolous lichens, and to high atmospheric SO2 levels in the mid-20th century, but are probably not directly connected to global warming. [ABSTRACT FROM AUTHOR]

Migration is a widespread strategy that enables animals to escape harsh winter conditions. It has been well documented that migration phenology in birds is changing in response to recent climate warming in the northern hemisphere. Despite the existence of large temporal and geographical scale ringing data on birds in Europe, changes in migration strategies in relation to climate warming have not been well studied, mainly because of a lack of appropriate statistical methods. In this paper, we develop a method that enables us to investigate temporal changes in migration strategies from recoveries of dead ringed birds. We estimated migration probability as the ratio between recovery probabilities of conspecific birds originating from different countries but potentially wintering in the same country. We applied this method to two European thrushes: the entirely migrant redwing Turdus iliacus, and the partially migrant blackbird T. Merula. We tested for an immediate and a 1-year lagged relationship between our migration probability and climatic covariates (i. E. Mean winter temperature in France and the North Atlantic Oscillation). Using ringing-recovery data collected in Finland, Germany, Switzerland and France from 1970 to 1999, we detected contrasting responses in these two species, likely related to their different migratory behaviours. Both species showed a decline in the probability for northern and eastern birds to winter in France. The entirely migratory redwing exhibited a year-to-year plastic response to climate, whereas the decline in the partially migrant blackbird was smooth, suggesting underlying genetic processes. The proposed method, thus, allows us to identify useful indicators of climatic impacts on migration strategies, as well as highlighting differences between closely related species. [ABSTRACT FROM AUTHOR]

Human emissions of greenhouse gases are already changing our climate. This paper provides an overview of the relation between climate change and weather extremes, and examines three specific cases where recent acute events have stimulated debate on the potential role of climate change: the European heatwave of 2003; the risk of inland flooding, such as recently in Central Europe and Great Britain; and the harsh Atlantic hurricane seasons of 2004 and 2005. Furthermore, it briefly assesses the relation between climate change and El Niño, and the potential of abrupt climate change. Several trends in weather extremes are sufficiently clear to inform risk reduction efforts. In many instances, however, the potential increases in extreme events due to climate change come on top of alarming rises in vulnerability. Hence, the additional risks due to climate change should not be analysed or treated in isolation, but instead integrated into broader efforts to reduce the risk of natural disasters. [ABSTRACT FROM AUTHOR]

This paper presents a probabilistic method of pollen spectra analysis. The method relies on a pollen taxon characterization using biotic and abiotic plant attribute modes, and their occurrence in a given pollen spectrum at a specific site. This type of analysis can provide an interpretation, which can lead to the reconstruction of the biome and, to an extent, of the abiotic conditions at the site.The analysis has been carried out at the European scale using data provided by the European Pollen Database for about 1000 sites. This dataset contains about 50,000 pollen spectra from the last 21 ka. In these spectra, each pollen taxon has been characterized by a set of 10 chosen attributes. These have been selected with regard to their relevance in biome reconstruction, but also on the basis of available literature. By using the probability of occurrence of each taxon in a given pollen spectrum, it is possible to calculate an affinity index for the spectrum to the attribute considered. To overcome difficulties caused by pollen identification in low diversified pollen spectra, a co-occurrence concept has been used to give more information.The method has been validated on a set of 1327 modern surface samples by comparing the results to the major climatic and environmental variables that control the distribution of the vegetation. A reconstruction exercise on various characteristics of the plants was then carried out on a 6-ka dataset. This confirmed previous studies by showing a strong dominance of deciduous forest over most of Europe, related to a milder climate than at present in the north and a wetter and colder climate than at present in the south. By analysing the change in pollen/seed dispersion strategies and the light requirement, we show that the history of vegetation dynamics in relation to human influences can be assessed using this method.Our results show that the probabilistic method is an objective tool for pollen assemblage analysis. It allows reconstruction of various characteristics of the vegetation at the continental and global scale for periods and sites with significantly different climate conditions. This method can also be used to compare maps of vegetation attributes for the validation of the new generalized dynamic ecosystems models. [ABSTRACT FROM AUTHOR]

Global change is expected to have complex effects on the distribution and transmission patterns of zoonotic parasites. Modelling habitat suitability for parasites with complex life cycles is essential to further our understanding of how disease systems respond to environmental changes, and to make spatial predictions of their future distributions. However, the limited availability of high quality occurrence data with high spatial resolution often constrains these investigations. Using 449 reliable occurrence records for Echinococcus multilocularis from across Europe published over the last 35 years, we modelled habitat suitability for this parasite, the aetiological agent of alveolar echinococcosis, in order to describe its environmental niche, predict its current and future distribution under three global change scenarios, and quantify the probability of occurrence for each European country. Using a machine learning approach, we developed large‐scale (25 × 25 km) species distribution models based on seven sets of predictors, each set representing a distinct biological hypothesis supported by current knowledge of the autecology of the parasite. The best‐supported hypothesis included climatic, orographic and land‐use/land‐cover variables such as the temperature of the coldest quarter, forest cover, urban cover and the precipitation seasonality. Future projections suggested the appearance of highly suitable areas for E. multilocularis towards northern latitudes and in the whole Alpine region under all scenarios, while decreases in habitat suitability were predicted for central Europe. Our spatially explicit predictions of habitat suitability shed light on the complex responses of parasites to ongoing global changes. [ABSTRACT FROM AUTHOR]

Aim: Climate change regulates autumn leaf senescence date (LSD), exhibiting a strong phenological control of plant carbon uptake. Unlike the delaying effect of daily mean temperature (Tmean) on LSD, the impact of warming asymmetry in daytime and nighttime, as evidenced by variations of the diurnal temperature range (DTR), remains elusive. The objectives of this study were to investigate physiological and ecological impacts of DTR on LSD using long‐term in situ observations and to predict the future trends of LSD under warming. Location: Europe. Time period: 1950–2015. Major taxa studied: Plant phenology. Methods: We used partial correlation analysis, multiple linear regression and ridge regression to explore the impacts of DTR on LSD. To quantify the importance of potential drivers of LSD, we trained random forest models and applied the SHapley Additive exPlanations method to isolate the marginal contributions of each predictor on LSD. For LSD modelling and projection, we first evaluated two temperature‐driven LSD models [i.e., cooling‐degree‐day (CDD, without DTR effect) and day–night‐temperature CDD (DNCDD, with DTR effect)], then applied them to predict future LSDs. Results: We found that observational increases in Tmean and DTR had contrasting effects on LSD. Increased Tmean delayed the LSD, whereas larger DTR overall had an advancing effect. Considering the DTR effect, the Tmean sensitivity of LSD was 14% lower than presently estimated (2.4 vs. 2.8 days °C−1). Warming asymmetry‐related drought stress and plant functional traits (i.e., plant isohydricity and water‐use efficiency) potentially explained the advancing effect of DTR on LSD. We found that current projections of future LSD are overestimated because the DTR effect is discounted, suggesting the need for an adequate understanding of how plant phenology responds to warming asymmetry. Main conclusions: Our findings highlight the importance of DTR in controlling LSD variations with an advancing‐dominant effect and call for the improvement of phenology modelling incorporating the DTR effect. Given that DTR showed a globally narrowing trend over the last several decades, more efforts are needed to understand the potential ecological impacts of warming asymmetry and vegetation response to climate change. [ABSTRACT FROM AUTHOR]

Standing deadwood is an important structural component of forest ecosystems. Its occurrence and dynamics influence both carbon fluxes and the availability of habitats for many species. However, deadwood is greatly reduced in managed, and even in many currently unmanaged temperate forests in Europe. To date, few studies have examined how environmental factors, forest management and changing climate affect the availability of standing deadwood and its dynamics.Data from five periods of the Austrian National Forest Inventory (1981–2009) were used to (I) analyse standing deadwood volume in relation to living volume stock, elevation, eco‐region, forest type, ownership and management intensity, (II) investigate the influence of forest ownership and management intensity on snag persistence and (III) define drivers of standing deadwood volume loss for seven tree genera (Abies, Alnus, Fagus, Larix, Picea, Pinus and Quercus) using tree‐related, site‐related and climate‐related variables, and predict volume loss under two climate change scenarios.Standing deadwood volume was mainly determined by living volume stock and elevation, resulting in different distributions between eco‐regions. While forest type and management intensity influenced standing deadwood volume only slightly, the latter exhibited a significant effect on persistence. Snag persistence was shorter in intensively managed forests than in extensively managed forests and shorter in private than in public forests.Standing deadwood volume loss was driven by a combination of diameter at breast height, elevation, as well as temperature, precipitation and relative humidity. Volume loss under climate change predictions revealed constant rates for moderate climate change (RCP2.6) by the end of the 21st century. Under severe climate change conditions (RCP8.5), volume loss increased for most tree genera, with Quercus, Alnus and Picea showing different predictions depending on the model used as the baseline scenario. We observed trends towards faster volume loss at higher temperatures and lower elevations and slower volume loss at high precipitation levels. The tree genera most susceptible to climate change were Pinus and Fagus, while Abies was least susceptible.Synthesis and applications. We recommend to protect standing dead trees from regular harvesting to ensure the full decomposition process. The consequences for decomposition‐dependent species must be taken into account to evaluate the influences of management and climate change on standing deadwood dynamics. [ABSTRACT FROM AUTHOR]

Giant reed (GR) and reed canary grass (RCG) have emerged as promising perennial industrial crops for providing sustainable bioenergy from marginal land. However, there is great uncertainty among farmers and researchers about where these crops can be grown in the future due to climate change, which complicates a timely transition to a bioeconomy. Therefore, this study quantifies marginal land and suitable cropping areas for GR and RCG in Europe, as well as their overlap. To derive these areas, the present (1991–2020) and future (2071–2100, RCP8.5) growing degree days, growing season length, annual precipitation, and aridity index were analyzed using the E‐OBS observational dataset and EURO‐CORDEX regional climate simulations. The study concludes that while marginal land will decrease by ~18%, GR and RCG will profit from the changing European climate, increasing by ~24% and ~13%, respectively. Looking at regions of overlap between marginal land and the selected crops, a decrease of ~87% and an increase of ~462% is projected for RCG and GR, respectively. This is due to marginal land shifting southward, benefitting the warm‐season grass GR, while RCG prefers cooler climates. [ABSTRACT FROM AUTHOR]

Over the last decades, the natural disturbance is increasingly putting pressure on European forests. Shifts in disturbance regimes may compromise forest functioning and the continuous provisioning of ecosystem services to society, including their climate change mitigation potential. Although forests are central to many European policies, we lack the long‐term empirical data needed for thoroughly understanding disturbance dynamics, modeling them, and developing adaptive management strategies. Here, we present a unique database of >170,000 records of ground‐based natural disturbance observations in European forests from 1950 to 2019. Reported data confirm a significant increase in forest disturbance in 34 European countries, causing on an average of 43.8 million m3 of disturbed timber volume per year over the 70‐year study period. This value is likely a conservative estimate due to under‐reporting, especially of small‐scale disturbances. We used machine learning techniques for assessing the magnitude of unreported disturbances, which are estimated to be between 8.6 and 18.3 million m3/year. In the last 20 years, disturbances on average accounted for 16% of the mean annual harvest in Europe. Wind was the most important disturbance agent over the study period (46% of total damage), followed by fire (24%) and bark beetles (17%). Bark beetle disturbance doubled its share of the total damage in the last 20 years. Forest disturbances can profoundly impact ecosystem services (e.g., climate change mitigation), affect regional forest resource provisioning and consequently disrupt long‐term management planning objectives and timber markets. We conclude that adaptation to changing disturbance regimes must be placed at the core of the European forest management and policy debate. Furthermore, a coherent and homogeneous monitoring system of natural disturbances is urgently needed in Europe, to better observe and respond to the ongoing changes in forest disturbance regimes. [ABSTRACT FROM AUTHOR]

Large‐scale bioenergy plays a key role in climate change mitigation scenarios, but its efficacy is uncertain. This study aims to quantify that uncertainty by contrasting the results of three different types of models under the same mitigation scenario (RCP2.6‐SSP2), consistent with a 2°C temperature target. This analysis focuses on a single bioenergy feedstock, Miscanthus × giganteus, and contrasts projections for its yields and environmental effects from an integrated assessment model (IMAGE), a land surface and dynamic global vegetation model tailored to Miscanthus bioenergy (JULES) and a bioenergy crop model (MiscanFor). Under the present climate, JULES, IMAGE and MiscanFor capture the observed magnitude and variability in Miscanthus yields across Europe; yet in the tropics JULES and IMAGE predict high yields, whereas MiscanFor predicts widespread drought‐related diebacks. 2040–2049 projections show there is a rapid scale up of over 200 Mha bioenergy cropping area in the tropics. Resulting biomass yield ranges from 12 (MiscanFor) to 39 (JULES) Gt dry matter over that decade. Change in soil carbon ranges from +0.7 Pg C (MiscanFor) to −2.8 Pg C (JULES), depending on preceding land cover and soil carbon.2090–99 projections show large‐scale biomass energy with carbon capture and storage (BECCS) is projected in Europe. The models agree that <2°C global warming will increase yields in the higher latitudes, but drought stress in the Mediterranean region could produce low yields (MiscanFor), and significant losses of soil carbon (JULES and IMAGE). These results highlight the uncertainty in rapidly scaling‐up biomass energy supply, especially in dry tropical climates and in regions where future climate change could result in drier conditions. This has important policy implications—because prominently used scenarios to limit warming to 'well below 2°C' (including the one explored here) depend upon its effectiveness. [ABSTRACT FROM AUTHOR]

Summary: Plants produce a wide diversity of metabolites. Yet, our understanding of how shifts in plant metabolites as a response to climate change feedback on ecosystem processes remains scarce. Here, we test to what extent climate warming shifts the seasonality of metabolites produced by Sphagnum mosses, and what are the consequences of these shifts for peatland C uptake.We used a reciprocal transplant experiment along a climate gradient in Europe to simulate climate change. We evaluated the responses of primary and secondary metabolites in five Sphagnum species and related their responses to gross ecosystem productivity (GEP).When transplanted to a warmer climate, Sphagnum species showed consistent responses to warming, with an upregulation of either their primary or secondary metabolite according to seasons. Moreover, these shifts were correlated to changes in GEP, especially in spring and autumn.Our results indicate that the Sphagnum metabolome is very plastic and sensitive to warming. We also show that warming‐induced changes in the seasonality of Sphagnum metabolites have consequences on peatland GEP. Our findings demonstrate the capacity for plant metabolic plasticity to impact ecosystem C processes and reveal a further mechanism through which Sphagnum could shape peatland responses to climate change. [ABSTRACT FROM AUTHOR]

Wind erosion from agricultural land is an underrated and understudied environmental challenge in Europe. Its societal and policy relevance will likely increase in the near future due to climate change and associated increases in the frequency, severity and patterns of atmospheric events such as droughts.We review the research on this issue and find it to be fragmented, siloed and dominated by natural sciences, leaving important research gaps. The most important gaps that circumscribe a research agenda for the future include specific effects of future climate change on wind erosion, the relevance of wind erosion for public health and ecosystem functioning, farmers' behaviour affecting erosion risk and feedback between land management and environmental change, and appropriate policy approaches to address wind erosion risks. Social science contributions are thus required to make wind erosion research relevant for addressing the related societally most pressing questions.We provide a social–environmental systems perspective to highlight the potential of inter‐ and transdisciplinary research into wind erosion in times of climate change and the increasingly recognized need to transform agriculture towards more sustainability and climate resilience. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

The world needs more than double its current agricultural productivity by 2050 to produce enough food and feed, as well as to provide feedstock for the bioeconomy. These future increases will not only need to be sustainable but without comprommising the nutritional quality, and ideally also need to decrease greenhouse gas emissions and increase carbon sequestration to help mitigate the consequences of global climate change. These challenges could be tackled by developing and integrating new future‐proof crops into our food system. The H2020 CropBooster‐P project sets out plant‐centered breeding approaches guided by a broad socio‐economic and societal support. First, the potential approaches for breeding crops with sustainably increased yields adapted to the future climate of Europe are identified. These crop‐breeding options are subsequently prioritized and their adoption considered by experts across the agri‐food system and the wider public, taking into account environmental, economic and other technical criteria. In this way, a specific research agenda to future‐proof our crops was developed, supported by an eventual implementation plan. [ABSTRACT FROM AUTHOR]

The response of the Euro‐Atlantic wintertime circulation to climate change is deeply uncertain. The Atlantic jet is caught in a "tug‐of‐war" between rapid warming trends in both the tropics and the Arctic leading to debate over the changing "waviness" of the jet, which is subject to strong non‐linearity and internal variability. From the complementary perspective of weather regimes, there is considerable uncertainty in how atmospheric blocking will alter under climate change. By applying the hybrid approach of geopotential‐jet regimes to 6th phase of the coupled model inter‐comparison project projections, we show that the centers of action of anticyclonic regimes hardly alter even under severe warming. Instead, regimes are expected to become less persistent, with zonal flow conditions becoming more prevalent, although models disagree on the details of regime changes. Finally, we show the regime response can be captured qualitatively in a simple Lorenz‐like model, emphasizing the conceptual link between observed regimes and those in basic mathematical systems. Plain Language Summary: The impact of climate change on European weather can be broken into two components: a thermodynamic part relating to increasing air temperature and humidity, and a dynamic part relating to changes in the atmospheric circulation such as the direction and strength of prevailing winds. While the thermodynamic part is relatively well understood, the dynamic part is very uncertain and this is a major problem in constraining European climate projections. Looking at the winter season, we study the dynamic response of CMIP6 models under climate change using so‐called "regimes," and show that the types of prevailing circulation are not predicted to change strongly. However the regimes are projected to be less long lived. We also show that these features can be well captured in a simple 5 equation model of regime dynamics, providing a potentially useful tool for understanding regime systems in more detail. Key Points: The spatial structure of anticyclonic circulations over Europe are projected to stay the same under climate changeThe persistence of anticyclonic circulations are in general expected to decrease, although there is considerable inter‐model variabilityWe show that these qualitative features of the atmospheric response can be reproduced in a simple forced regime model [ABSTRACT FROM AUTHOR]

Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state‐of‐the‐art, stand‐scale forest models against field measurements of forest structure and eddy‐covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models' performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi‐model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe's common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests. [ABSTRACT FROM AUTHOR]

Here, published crop disease risk simulations are summarized, which were driven by climate change scenarios on a timescale terminating between 2001 and 2100. Thirty different agricultural and horticultural crops were specifically considered. Wheat diseases (mainly leaf rust) were most often simulated, followed by rice diseases (mainly leaf blast), grapevine diseases (mainly downy mildew) and potato diseases (mainly late blight). Most simulations suggest that within the projection period simulated, crop disease risk will more often increase (86 simulations) than decrease (45 simulations) or remain similar (12 simulations). The majority of crop disease risk simulations focus on Europe and Brazil. For example, there is agreement across crop disease risk simulations that in Europe the risk of leaf rust of wheat will increase. In other cases, there is disagreement across crop disease risk simulations, for example, due to contemporary climatic differences of locations. Therefore, it is risky to extrapolate results across locations. Mitigation and adaptation methods should be more often integrated in the crop disease risk simulations in order to inform about potential methods to reduce disease risk in future. [ABSTRACT FROM AUTHOR]

Climate services have emerged as a research and operational field in recent years. This development has been underpinned and supported by significant research, funding and agenda‐setting efforts such as the Global Framework for Climate Services internationally and the Roadmap for Climate Services and the Copernicus Climate Change Service in Europe. The fast pace at which this field is developing raises a number of key challenges that need to be critically examined and addressed to ensure the future development and sustainability of climate services in Europe. This opinion piece highlights a number of challenges currently threatening the viability of climate services including the complexity of the concept of climate services; the complex landscape of complementary research and development areas relevant to climate services; existing rights to freely access and use climate services; current limitations to funding structures and mechanisms and how that impacts on the development of climate services; the emphasis on co‐production as a precondition to climate services development; and the limited role of the social sciences in the research and operational field of climate services. Effectively addressing these challenges will require a commitment from the scientific and practitioner communities to engage in critical and reflective debates around the future conceptualization and operationalization of climate services in Europe. This paper aims to provide critical input to stimulate a necessary and overdue debate around the sustainability and future of climate services in Europe. This article is categorized under: Social Status of Climate Change Knowledge > Knowledge and Practice [ABSTRACT FROM AUTHOR]

While long‐term changes in measures of central tendency of climate elements, that is, mean temperature, are well acknowledged, studies of trends in measures of their variability are much less common. This is despite the fact that trends in variability can have higher effect on climate extremes than trends in mean. Here, four measures of intraseasonal variability are examined: (a) standard deviation of mean daily temperature, (b) the range between the 90th and 10th quantile of mean daily temperature, (c) mean absolute value of day‐to‐day temperature change, and (d) one‐day lagged temporal autocorrelation. ECA&D daily data from 168 stations and linear regression method are utilized to calculate trends of these characteristics in period from 1961 to 2018. Significant trends (positive and negative) are revealed with substantial differences between seasons, regions and measures. The most considerable decreases in temperature variability were recorded in winter, for temporal autocorrelation in eastern Europe and for variance‐based measures in northern Europe. For example, the standard deviation has decreased by more than 10% in the Arctic Ocean. This can indicate a decrease in the frequency of cold extremes in Scandinavia. On the contrary, increasing persistence may suggest a greater likelihood of cold extremes in the East European Plain. Increases in variability prevail only in summer, but not for all measures and not as clearly as decreases in winter. Trends in temporal autocorrelation and day‐to‐day change appear to be sensitive to data issues, such as inhomogeneities and changes in observational procedures. [ABSTRACT FROM AUTHOR]

Soils store vast amounts of carbon (C) on land, and increasing soil organic carbon (SOC) stocks in already managed soils such as croplands may be one way to remove C from the atmosphere, thereby limiting subsequent warming. The main objective of this study was to estimate the amount of additional C input needed to annually increase SOC stocks by 4‰ at 16 long‐term agricultural experiments in Europe, including exogenous organic matter (EOM) additions. We used an ensemble of six SOC models and ran them under two configurations: (1) with default parametrization and (2) with parameters calibrated site‐by‐site to fit the evolution of SOC stocks in the control treatments (without EOM). We compared model simulations and analysed the factors generating variability across models. The calibrated ensemble was able to reproduce the SOC stock evolution in the unfertilised control treatments. We found that, on average, the experimental sites needed an additional 1.5 ± 1.2 Mg C ha−1 year−1 to increase SOC stocks by 4‰ per year over 30 years, compared to the C input in the control treatments (multi‐model median ± median standard deviation across sites). That is, a 119% increase compared to the control. While mean annual temperature, initial SOC stocks and initial C input had a significant effect on the variability of the predicted C input in the default configuration (i.e., the relative standard deviation of the predicted C input from the mean), only water‐related variables (i.e., mean annual precipitation and potential evapotranspiration) explained the divergence between models when calibrated. Our work highlights the challenge of increasing SOC stocks in agriculture and accentuates the need to increasingly lean on multi‐model ensembles when predicting SOC stock trends and related processes. To increase the reliability of SOC models under future climate change, we suggest model developers to better constrain the effect of water‐related variables on SOC decomposition. Highlights: The feasibility of the 4‰ target was studied at 16 long‐term agricultural experiments.An ensemble of soil organic carbon models was used to estimate the uncertainty of the predictions.On average across the sites, carbon input had to increase by 119% compared to initial conditions.High uncertainty of the simulations was mainly driven by water‐related variables. [ABSTRACT FROM AUTHOR]

Recent global warming affects species compositions at an unprecedented rate. To predict climate‐induced changes in species assemblages, a better understanding of the link between species occurrence and climate is needed. Macrofungal fruit body assemblages are correlated with the thermal environment at the European scale. However, it is still unknown whether macrofungal communities are also phylogenetically structured by thermal environments. Thermal environments are characterized by annual temperature means but also by intra‐annual temperature variability (hereafter termed temperature seasonality), which are both considered in this study. Here, we used distribution data of 2882 species based on fruit body records across Europe to address two main questions: 1) are mushroom assemblages at the extremes of the mean (warm and cold) and seasonal (high intra‐annual variability, i.e. continental) climate gradient phylogenetically more similar than expected (phylogenetic alpha diversity); 2) are mushroom assemblages, that are subject to different mean and seasonal temperature conditions, composed of different lineages (phylogenetic beta diversity). Our phylogenetic alpha diversity analysis shows that mushroom assemblages are phylogenetically structured by warm and cold environments, indicating that phylogenetically related species with similar traits thrive under more extreme conditions. In contrast, assemblages are phylogenetically more dissimilar (overdispersed) in temperature seasonal environments, indicating limiting similarity. Phylogenetic beta diversity was significantly correlated with mean and seasonal temperature differences, a response mainly driven by a few genera. Our results show that macrofungal assemblages are phylogenetically structured by temperature across Europe, suggesting phylogenetically constrained specialization towards temperature extremes. Predicted anthropogenic warming is likely to affect species composition and phylogenetic diversity with additional consequences for the carbon‐ and nutrient cycles. [ABSTRACT FROM AUTHOR]

Globally, the impacts of climate change can vary across different regions. This study uses a probability framework to evaluate recent historical (1976–2016) and near‐future projected (until 2049) climate change across Europe using Climate Research Unit and ensemble climate model datasets (under RCPs 2.6 and 8.5). A historical assessment shows that although the east and west of the domain experienced the largest and smallest increase in temperature, changes in precipitation are not as smooth as temperature. Results indicate that the maximum changes between distributions of the variables (temperature and precipitation) mainly occur at extreme percentiles (e.g., 10% and 90%). A group analysis of four subregions of Europe, namely east (G1), north (G2), west/south (G3), and UK/Ireland (G4), shows that G1 and G4 are expected to have the largest increase in temperature and precipitation extremes, respectively. Although maximum increases in temperature in G3 and G4 occur at larger percentiles, G1 and G2 experience maximum increases at both large and small percentiles. The maximum increase of precipitation over the study domain, however, occurs mainly at larger extremes. To quantify changes in the distribution of projection (2020–2049) relative to the historical reference (1976–2005), two measures are defined, namely a change in occurrences (KS statistic) and intensities at different quantiles (Δ). Results confirm that the temperature distribution tends to shift to higher temperatures. Changes in distribution and extremes of precipitation are spatially variable. Furthermore, extremes are expected to be intensified under RCP 8.5. The quantile analysis and defined measures reveal changes in the entire probability distribution, reflecting possible climate changes in the future. [ABSTRACT FROM AUTHOR]

The past two decades in Europe have been characterized by numerous major heat waves, with record‐breaking temperatures reported also during the summer of 2021. While most previous studies on heat waves were based on land‐only datasets (station or gridded), we use the ERA5 reanalysis to capture also heat wave characteristics over water bodies. An up‐to‐date list of major European heat waves since 1950 is presented, and the 2021 heat wave is evaluated in this long‐term context. This event was record‐breaking in length at the European scale, and in many other aspects (spatial extent, magnitude) comparable to the 2003 and 2010 major heat waves. The summer of 2021 was unprecedented over Europe according to the number of hot days (63) and the earliest start of a major heat wave (June 19), while the 2019 heat wave with record‐breaking temperatures across Western Europe stands out as to its intensity. Another recent major heat wave in 2018 ranked fourth in terms of magnitude. The spatial pattern in occurrence of the most severe heat wave since 1950 in individual parts of Europe is dominated by the 2003 (Western Europe), 2010 (Eastern Europe), 2018 (Scandinavia), and 2021 (Mediterranean) major heat waves. Overall, 83% of the domain area experienced the most severe heat wave in the past two decades (2002–2021), which demonstrates a rapidly changing summer climate in Europe. Plain Language Summary: Heat waves, characterized as several days to weeks long periods with excessively hot weather in summer, have negative effects on environment and society. The severity of heat waves has increased in the past two decades and record‐breaking temperatures were observed during the recent summer of 2021 over the Mediterranean. We used the climate reanalysis (ERA5) to create an up‐to‐date list of major European heat waves since 1950 and assess the severity of the 2021 heat wave in the long‐term context. The 2021 heat wave was found to be comparable to the 2003 and 2010 major heat waves in terms of magnitude and spatial extent and record‐breaking in length. Maps depicting the record‐breaking heat waves over European regions differ substantially between the 1950–2001 and 1950–2021 periods. The latter map is dominated by the 2003, 2010, 2018, and 2021 heat waves, demonstrating a rapidly changing summer climate in Europe. Key Points: Spatio‐temporal characteristics of major heat waves are studied over land and sea combined using the ERA5 reanalysisThe 2021 heat wave was the longest since 1950 and comparable to the 2003 and 2010 events in terms of magnitude and spatial extentThe map of the most severe heat waves in individual parts of Europe has been almost completely redrawn in the past two decades [ABSTRACT FROM AUTHOR]

Since the early 2000s, populist radical right parties (PRRPs) have more than doubled their electoral support in Europe. Previous research found that PRRPs impact migration policy. However, little is known about whether they also impact other fields of domestic and foreign policy. Using a cross‐country panel analysis, we test to what extent the rise of PRRPs has influenced European foreign aid spending. We find that while the rise of PRRPs has not been associated with an overall reduction in foreign aid, it has led to changes in how aid moneys are spent. PRRP strength is linked to a higher share of aid for migration‐containment objectives, and less aid for addressing climate change and for multilateral organizations. Our analysis thereby provides evidence that the 'electoral threat' of PRRPs puts mainstream parties under pressure not only with regard to migration but also in relation to the climate–development nexus and aid for multilateralism. [ABSTRACT FROM AUTHOR]

Long‐term satellite land surface temperature (LST) data are desirable to augment 2m air temperatures (T2m) measured in situ and as an independent measure of surface temperature change. However, previous studies show variable agreement between LST and T2m time series. The objective of this study is to assess the stability and trends in six new LST data sets from the European Space Agency's Climate Change Initiative for LST (LST_cci). LST anomalies are compared with homogenized station T2m anomalies over Europe, which verifies all six data sets are well coupled (LST vs T2m anomaly correlations and slopes: 0.6–0.9). The temporal stability of the LST_cci data is assessed through a comparison with the T2m anomaly time series. Only the LST_cci data sets for the MODerate resolution Imaging Spectroradiometer (MODIS) onboard Aqua and the Advanced Along‐Track Scanning Radiometer (AATSR) appear stable; the MODIS/Terra, ATSR‐2, and multisensor InfraRed and MicroWave data sets show non‐climatic discontinuities associated with changes in sensor and/or drift over time. For MODIS/Aqua (2002–2018), significant trends in LST of 0.64–0.66 K/decade compare well with the equivalent T2m trends of 0.52–0.59 K/decade. The LST and T2m trends for AATSR (2002–2012) are found to be statistically insignificant, likely due to the comparatively short study period and specific years available for analysis. No evidence is found to suggest that trends calculated using cloud‐free InfraRed observations are affected by clear‐sky bias. This study suggests that satellite LST data can be used to assess warming trends over land and for other climate applications if the required homogeneity is assured. Plain Language Summary: Long‐term changes in surface temperature due to climate change are usually studied using near‐surface air temperatures (T2m) from weather stations. However, these data are not available everywhere and changes in T2m are poorly understood in some regions (e.g., parts of Africa). This study assesses the potential for satellite‐observed land surface temperatures (LST) to help fill these gaps. The study finds that LST and T2m provide very similar information on surface temperatures and therefore LST can provide useful information where T2m data are unavailable. However, some of the LST data sets are found to be "unstable" and suffer from jumps and changes over time that result from for example, changes in satellite instrument or a change in the orbit of the satellite platform. These unstable LST data sets cannot be used to measure changes in surface temperature. However, the study finds that for "stable" LST data sets, which do not suffer from these non‐climatic jumps and changes, the changes in LST over time are very similar to, or even the same as, the changes in T2m. Therefore, this work suggests that satellite LST data could be used to measure changes in surface temperature where there are not enough stations to make these measurements using T2m. Key Points: The stability of six satellite land surface temperature data sets is assessed using homogenized station air temperatures over EuropeOnly two data sets are stable; the other four show non‐climatic discontinuities associated with a change in sensor and/or drift over timeSignificant trends in land surface temperature of ∼0.65 K/decade over Europe are found for one of the stable data sets over 2002–2018 [ABSTRACT FROM AUTHOR]

Inter‐variable dependencies are key properties to characterize many climate phenomena—such as compound events—and their future changes. Yet, climate simulations often have statistical biases. Hence, univariate (1dBC) and multivariate bias correction (MBC) methods are regularly applied. Inter‐variable properties (e.g., correlations) can be altered by BC corrections. Then, it is necessary to assess how underlying assumptions of BC methods on climate change affect the adjustments. This can lead to better choices of BC methods. Here, we investigate whether an MBC method should try reproducing, preserving or modifying the changes in rank correlations between daily temperature and precipitation over Europe. An original "perfect model experiment" is set up and applied to two different climate simulation ensembles over 2001–2100: 40 runs from the Community Earth System Model (CESM) global climate model and 11 runs from the Coupled Models Intercomparison Project (CMIP6) exercise. The results highlight that, within the multi‐run single Global Climate Models ensemble (CESM), accounting for correlation changes brings valuable information for long‐term projections but that a stationarity assumption provides less biased correlations, up to medium‐term projections (2060). For the multi‐model ensemble (CMIP6), the non‐stationarity assumption provides larger biases than the stationarity approach, up to the end of the century. Not correcting the model rank correlations (1dBC) provides the worst results. Whenever an ensemble is available, the best results come from accounting for the "robust" part of the change signal (i.e., average change from different runs). This pleads for using ensembles and their robust information, in order to perform robust bias corrections. Key Points: Multivariate bias correction methods can account for changes in correlations in climate simulations or can consider that they are stationaryA perfect model experiment is set up to evaluate consequences of these choices in terms of temperature versus precipitation rank correlationsResults on two ensembles show that both approaches are meaningful, depending on the underlying confidence put on climate simulations [ABSTRACT FROM AUTHOR]

Mountain ecosystems have special significance for biodiversity and are vulnerable to climate and other environmental changes. However, few assessments of drivers of change have been conducted in these areas in comparison to other more accessible biomes. In this study, we developed an objective and broad definition of a mountain bird, and systematically reviewed the existing literature for the 34 European mountain and upland species identified in order to quantify which drivers of environmental change have been most consistently associated with positive or negative demographic responses. Raptors and gamebirds were the most‐studied species, whereas mountain specialists and arctic–alpine species were little studied. Using a standardized threat classification, the analyses reported significant negative impacts of hunting, collision with energy‐generation infrastructures, predation by competitive species, human disturbance and poisoning. There were significant positive effects for management of non‐target species, but less support for effects of drivers operating over longer timescales, such as climate and land‐use changes. Analysis of trends in drivers found evidence of increasing temperatures and vegetation encroachment, whereas agricultural impacts decreased, which was largely related to abandonment of grazing. A lack of fine‐grained studies investigating ecological mechanisms and population responses to widespread impacts were highlighted. We have found that some drivers are well studied, but we need to collect more detailed and longer‐term data on species requirements and on the impacts that bird populations face to devise priorities for conservation action and research for mountain and upland birds. [ABSTRACT FROM AUTHOR]

Summary: Today plants often flower earlier due to climate warming. Herbarium specimens are excellent witnesses of such long‐term changes. However, the magnitude of phenological shifts may vary geographically, and the data are often clustered. Therefore, large‐scale analyses of herbarium data are prone to pseudoreplication and geographical biases.We studied over 6000 herbarium specimens of 20 spring‐flowering forest understory herbs from Europe to understand how their phenology had changed during the last century. We estimated phenology trends with or without taking spatial autocorrelation into account.On average plants now flowered over 6 d earlier than at the beginning of the last century. These changes were strongly associated with warmer spring temperatures. Flowering time advanced 3.6 d per 1°C warming. Spatial modelling showed that, in some parts of Europe, plants flowered earlier or later than expected. Without accounting for this, the estimates of phenological shifts were biased and model fits were poor.Our study indicates that forest wildflowers in Europe strongly advanced their phenology in response to climate change. However, these phenological shifts differ geographically. This shows that it is crucial to combine the analysis of herbarium data with spatial modelling when testing for long‐term phenology trends across large spatial scales. [ABSTRACT FROM AUTHOR]

A detailed, well‐dated record of pollen and sedimentary ancient DNA (sedaDNA) for the period 15 000–9500 cal a bp describes changes at Lake Bolshoye Shchuchye in the Polar Ural Mountains, located far east of the classical Lateglacial sites in western Europe. Arctic tundra rapidly changed to lusher vegetation, possibly including both dwarf (Betula nana) and tree birch (B. pubescens), dated in our record to take place 14 565 cal a bp, coincident with the onset of the Bølling in western Europe; this was paralleled by increased summer temperatures. A striking feature is an early decline in Betula pollen and sedaDNA reads 300 years before the onset of the Younger Dryas (YD) in western Europe. Given the solid site chronology, this could indicate that the YD cooling started in Siberia and propagated westwards, or that the vegetation reacted to the inter‐Allerød cooling at 13 100 cal a bp and did not recover during the late Allerød. During the YD, increases in steppe taxa such as Artemisia and Chenopodiaceae suggest drier conditions. At the onset of the Holocene, the vegetation around the lake reacted fast to the warmer conditions, as seen in the increase of arboreal taxa, especially Betula, and a decrease in herbs such as Artemisia and Cyperaceae. [ABSTRACT FROM AUTHOR]

Aim: The aims of this study were to evaluate the changes in the length of the time period between leaf‐out and flowering across temperate tree species, and associate these changes with potential physiological and environmental drivers to enhance mechanistic insight into these phenomena. Location: Central Europe. Time period: 1980–2016. Major taxa studied: Six temperate woody species. Methods: Statistical analyses were carried out based on long‐term ground observations of both spring leaf‐out and flowering across temperate tree species during 1980–2016, a period characterized by rapid warming. Results: The temperature sensitivity of flowering (−5.4 ± 0.04 days/℃, mean ± SE) was higher than that of leaf‐out (−4.6 ± 0.04 days/℃) across all species, regardless of whether leaf‐out occurred before or after flowering. This study postulates a hypothesis attributing the different temperature sensitivities to different thermal sensitivities, thermal requirements, and photoperiodic controls. Main conclusions: The larger temperature sensitivity of flowering than leaf‐out resulted in an extended time period between flowering and leaf‐out in species that bloom before leafing out, but a shorter time period between these phenophases in species with the opposite strategy. We would like to emphasize the importance of changes in time period between different phenophases, and we recommend conducting experimental research to reveal the underlying mechanisms of plant phenology response to climate change, and to explore its potential ecological implications. [ABSTRACT FROM AUTHOR]

Large‐scale ecological restoration is crucial for effective biodiversity conservation and combating climate change. However, perspectives on the goals and values of restoration are highly diverse, as are the different approaches to restoration e.g. ranging from the restoration of cultural ecosystems to rewilding. We assess how the future of nature is envisioned in participatory scenarios, focusing on which elements of rewilding and nature contributions to people have been considered in scenario narratives across Europe. We used the Nature Futures Framework archetypes as a template to synthesize pluralistic perspectives of nature. We found that different values of nature are often represented as counteracting elements and fail to integrate the plural views of nature. Nature as Culture was the main archetype found in the scenarios, usually associated with positive impacts on the non‐material benefits to people. Intrinsic values of nature (i.e., Nature forNature) were associated with positive impacts on regulating benefits and negative impacts on material benefits, being the only archetype of future associated with positive impacts on all three components of rewilding. Nature for Society was associated with moderate positive impacts on material and regulatory nature contributions to people. Business as usual futures were associated with negative impacts on regulating and non‐material benefits to people and on all three components of rewilding. Our results highlight two major gaps in the scenarios that should be addressed in participatory restoration planning and models. Firstly, there is a paucity of spatially explicit approaches, with most studies failing to transform the results of participatory scenario planning into model projections. Secondly, we found scenarios that explored co‐benefits between multiple nature perspectives were overall missing from the literature. Novel scenario narratives and approaches that explore synergies among different nature values are needed to design future large‐scale restoration where biodiversity recovery and human well‐being are intrinsically linked and fostered. [ABSTRACT FROM AUTHOR]