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The Inter-Sectoral Impact Model Intercomparison Project offers a framework to compare climate impact projections in different sectors and at different scales. Consistent climate and socio-economic input data provide the basis for a cross-sectoral integration of impact projections. The project is designed to enable quantitative synthesis of climate change impacts at different levels of global warming. This report briefly outlines the objectives and framework of the first, fast-tracked phase of Inter-Sectoral Impact Model Intercomparison Project, based on global impact models, and provides an overview of the participating models, input data, and scenario set-up.

Heat-related mortality has been identified as one of the key climate extremes posing a risk to human health. Current research focuses largely on how heat mortality increases with mean global temperature rise, but it is unclear how much climate change will increase the frequency and severity of extreme summer seasons with high impact on human health. In this probabilistic analysis, we combined empirical heat-mortality relationships for 748 locations from 47 countries with climate model large ensemble data to identify probable past and future highly impactful summer seasons. Across most locations, heat mortality counts of a 1-in-100 year season in the climate of 2000 would be expected once every ten to twenty years in the climate of 2020. These return periods are projected to further shorten under warming levels of 1.5 °C and 2 °C, where heat-mortality extremes of the past climate will eventually become commonplace if no adaptation occurs. Our findings highlight the urgent need for strong mitigation and adaptation to reduce impacts on human lives. The risk of heat-mortality is increasing sharply. The authors report that heat-mortality levels of a 1-in-100-year summer in the climate of 2000 can be expected once every ten to twenty years in the current climate and at least once in five years with 2 °C of global warming.

Few studies have used empirical evidence of past adaptation to project temperature-related excess mortality under climate change. Here, we assess adaptation in future projections of temperature-related excess mortality by employing evidence of shifting minimum mortality temperatures (MMTs) concurrent with climate warming of recent decades. The study is based on daily non-external mortality and daily mean temperature time-series from 11 Spanish cities covering four decades (1978–2017). It employs distributed lag non-linear models (DLNMs) to describe temperature-mortality associations, and multivariate mixed-effect meta-regression models to derive city- and subperiod-specific MMTs, and subsequently MMT associations with climatic indicators. We use temperature projections for one low- and one high-emission scenario (ssp126, ssp370) derived from five global climate models. Our results show that MMTs have closely tracked mean summer temperatures (MSTs) over time and space, with meta-regression models suggesting that the MMTs increased by 0.73 °C (95%CI: 0.65, 0.80) per 1 °C rise in MST over time, and by 0.84 °C (95%CI: 0.76, 0.92) per 1 °C rise in MST across cities. Future projections, which include adaptation by shifting MMTs according to observed temporal changes, result in 63.5% (95%CI: 50.0, 81.2) lower heat-related excess mortality, 63.7% (95%CI: 30.2, 166.7) higher cold-related excess mortality, and 11.2% (95%CI: −5.5, 39.5) lower total temperature-related excess mortality in the 2090s for ssp370 compared to estimates that do not account for adaptation. For ssp126, assumptions on adaptation have a comparatively small impact on excess mortality estimates. Elucidating the adaptive capacities of societies can motivate strengthened efforts to implement specific adaptation measures directed at reducing heat stress under climate change.

The aim was to compare the relationship between somatic symptom disorder (SSD), anxiety, depression, clinical symptoms, and daily life impairment (DLI) in post-COVID syndrome (PCS), asthma and chronic obstructive pulmonary disease (COPD). In a cross-sectional study, 371 patients (161 PCS, 121 asthma, 89 COPD) of a pulmonary rehabilitation clinic received the questionnaires PHQ-15 (Patient Health Questionnaire-15) and SSD-12 (Somatic Symptom Disorder-12) to determine SSD, GAD-7 (Generalized Anxiety Disorder-7) to determine anxiety disorder, and PHQ-9 (Patient Health Questionnaire-9) to determine depression. Lung function was estimated using whole-body plethysmography. Predictors for DLI were assessed by regression models and ROC analyses. Association of SSD with DLI was stronger in PCS (odds ratio 13.8; 95% confidence interval 1.7-109.9) than in asthma (8.5; 2.4–30.1), and was not significant in COPD (1.9; 0.5–7.5). In asthma and COPD, strongest predictors were GAD-7 (15.0; 1.9-116.8) and PHQ-9 (8.9; 1.1–71.8), respectively. Diffusion capacity was predictive in COPD (0.947; 0.916–0.979) and asthma (0.967; 0.943–0.993), but not in PCS. To conclude, SSD appears to have greater impact on DLI in PCS than asthma or COPD patients. This should be recognized appropriately during rehabilitation. Furthermore, increased psychological comorbidity should also be considered and adequately treated in asthma and COPD if necessary.

Previous attribution studies of heat-related excess mortality have given limited attention to temporal trends in vulnerability and their non-climatic drivers. Here, we address this gap by combining counterfactual temperature data derived from multidecadal reanalysis series with time-varying warm-season temperature-mortality associations for the 15 most populous cities in Germany over 1993-2022. We find that declining vulnerability, associated with improvements in life expectancy, has led to decreasing trends in heat-related excess mortality in most cities despite summer warming. In contrast, if life expectancies had not improved, climate change would have induced increasing trends in the heat-related death burden. The growing anthropogenic fingerprint also emerges in the relative proportion of heat-related excess mortality attributable to climate change, which increased by 5.6% per decade (95% confidence interval: 2.6%, 8.6%), averaging 53.6 % (49.8%, 58.9%) across the study period. Our results underline the importance of accounting for evolving vulnerability when attributing human health outcomes to climate change. The study shows that rising life expectancy has masked the impact of climate change on heat-related mortality in Germany. It highlights the need to consider non-climatic factors underlying vulnerability in attribution studies of health outcomes.

Globally, the further expansion of cropland is limited by the availability of adequate land and by the necessity to spare land for nature conservation and carbon sequestration. Analyzing the causes of past land-use changes can help to better understand the potential drivers of land scarcities of the future. Using the FAOSTAT database, we quantify the contribution of four major factors, namely human population growth, rising per-capita caloric consumption (including food intake and household waste), processing losses (including conversion of vegetal into animal products and non-food use of crops), and yield gains, to cropland expansion rates of the past (1961-2007). We employ a Kaya-type decomposition method that we have adapted to be applicable to drivers of cropland expansion at global and national level. Our results indicate that, all else equal, without the yield gains observed globally since 1961, additional land of the size of Australia would have been put under the plough by 2007. Under this scenario the planetary boundary on global cropland use would have already been transgressed today. By contrast, without rising per-capita caloric consumption and population growth since 1961, an area as large as nearly half and all of Australia could have been spared, respectively. Yield gains, with strongest contributions from maize, wheat and rice, have approximately offset the increasing demand of a growing world population. Analyses at the national scale reveal different modes of land-use transitions dependent on development stage, dietary standards, and international trade intensity of the countries. Despite some well-acknowledged caveats regarding the non-independence of decomposition factors, these results contribute to the empirical ranking of different drivers needed to set research priorities and prepare well-informed projections of land-use change until 2050 and beyond.

Despite the recognition of the importance of seasonal forcing in nature, remarkably few studies have theoretically explored periodically forced community dynamics. Here we employ a novel approach called \"successional state dynamics\" (SSD) to model a seasonally forced predator-prey system. We first generated analytical predictions of the effects of altered seasonality on species persistence and the timing of community state transitions. We then parameterized the model using a zooplankton-phytoplankton system and tested quantitative predictions using controlled experiments. In the majority of cases, timing of zooplankton and algal population peaks matched model predictions. Decreases in growing-period length delayed algal blooms, consequently delaying peaks in zooplankton abundance. Predictions of increased probability of predator extinction at low growing-period lengths were also upheld experimentally. Our results highlight the utility of the SSD modeling approach as a framework for predicting the effects of altered seasonality on the structure and dynamics of multitrophic communities.

Past heat waves are considered harbingers of future climate change. In this study, we have evaluated the effects of two recent Central European summer heat waves (2003 and 2006) on cyanobacterial blooms in a eutrophic, shallow lake. While a bloom of cyanobacteria developed in 2006, consistent with our expectations, cyanobacterial biomass surprisingly remained at a record-low during the entire summer of 2003. Critical thresholds of abiotic drivers extracted from the long-term (1993-2007) data set of the studied lake using classification tree analysis (CTA) proved suitable to explain these observations. We found that cyanobacterial blooms were especially favoured in 2006 because thermal stratification was critically intense (Schmidt stability >44 g cm cm⁻²) and long-lasting (>3 weeks). Our results also suggest that some cyanobacterial species (Anabaena sp.) benefitted directly from the stable water column, whereas other species (Planktothrix sp.) took advantage of stratification-induced internal nutrient loading. In 2003, conditions were less favourable for cyanobacteria due to a spell of lower temperatures and stronger winds in midsummer; as a result, the identified thresholds of thermal stratification were hardly ever reached. Overall, our study shows that extracting critical thresholds of environmental drivers from long-term records is a promising avenue for predicting ecosystem responses to future climate warming. Specifically, our results emphasize that not average temperature increase but changes in short-term meteorological variability will determine whether cyanobacteria will bloom more often in a warmer world.

Several economic assessments of climate change build on the assumption that reductions of cold-related mortality will overcompensate increases in heat-related mortality at least for moderate levels of global warming. Due to the lack of suitable epidemiological studies with sufficient spatial coverage, many of these assessments rely on one particular dataset: projections of temperature-related mortality in 17 countries published almost 20 years ago. Here, we reanalyse this dataset with a focus on cardiovascular mortality and present evidence for two flaws in the original analysis, which would imply a significant bias towards finding net mortality benefits from climate change: (i) the combination of mortality data for all ages with data specific to the elderly and (ii) the confounding of seasonal effects with direct temperature effects on mortality. This bias appears to be further amplified in the integrated assessment models FUND and ENVISAGE, and related economic assessment tools relying on the same calibration scheme, because heat-related cardiovascular mortality is assumed to affect urban populations only in these models. In an exemplary calculation, we show that while FUND currently projects a net reduction of approximately 380,000 deaths from cardiovascular diseases globally per year at 1 °C of global warming, correcting for the two potential flaws and assuming equal vulnerability of urban and rural populations would result in a net increase of cardiovascular mortality, with approximately 150,000 net additional deaths globally per year. Our findings point to the urgent need of renewing damage functions on temperature-related mortality currently applied in some of the most widely used integrated assessment models.

Previous health impact assessments of temperature-related mortality in Europe indicated that the mortality burden attributable to cold is much larger than for heat. Questions remain as to whether climate change can result in a net decrease in temperature-related mortality. In this study, we estimated how climate change could affect future heat-related and cold-related mortality in 854 European urban areas, under several climate, demographic and adaptation scenarios. We showed that, with no adaptation to heat, the increase in heat-related deaths consistently exceeds any decrease in cold-related deaths across all considered scenarios in Europe. Under the lowest mitigation and adaptation scenario (SSP3-7.0), we estimate a net death burden due to climate change increasing by 49.9% and cumulating 2,345,410 (95% confidence interval = 327,603 to 4,775,853) climate change-related deaths between 2015 and 2099. This net effect would remain positive even under high adaptation scenarios, whereby a risk attenuation of 50% is still insufficient to reverse the trend under SSP3-7.0. Regional differences suggest a slight net decrease of death rates in Northern European countries but high vulnerability of the Mediterranean region and Eastern Europe areas. Unless strong mitigation and adaptation measures are implemented, most European cities should experience an increase of their temperature-related mortality burden. Modeled analyses of 854 European cities show that net temperature-related mortality will increase because of an increase in heat-related mortality exceeding future reductions in cold-related mortality under current climate change projections and even in the presence of high adaptation scenarios.