SiCLIMA: High-resolution hydroclimate and temperature dataset for Aragón (northeast Spain).

A new high-resolution climatic gridded dataset was built for Aragón (northeast Spain) using a large collection of daily precipitation and temperature observations from more than 3000 weather stations. The grid covers, at the unprecedented spatial resolution of 0.25 km2, daily maximum and minimum temperatures and precipitation in the 1950-2020 period. The complex orography (from 70 to 3,400 m.a.s.l.) of the medium-sized region (∼48,000 km2) required a climate modelling method based on a spatially-dense weather monitoring network and local predictors. The 3-step workflow for grid creation consisted of: 1) a comprehensive quality control of raw observations, based on a spatial comparison with nearest data; 2) a climate reconstruction based on the creation of reference values, through multivariate linear regressions, for every day and location, based on the observed climate and terrain-based environmental variables; and 3) the prediction of precipitation and temperature values in a regular 500 × 500 m grid, based on the reconstructed data series. The resulting dataset improves the spatial representativity of climate and allows for a detailed analyses at landscape scale not only in climate studies but also in related disciplines such as hydrology or biogeography, amongst others.

Variations of compound warm, dry, wet, and cold climate extremes in India during 1951 to 2014.

The simultaneous occurrence of climate extremes significantly impacts ecosystems, increasing the vulnerability to physical risks. Despite extensive research on hot extremes and droughts globally, there remains a significant gap in comprehending the occurrence, magnitude, spatial extent, and associated risks of compound extremes, encompassing scenarios like warm/dry, cold/dry, warm/wet, and cold/wet. This study investigates various compound extreme scenarios by examining combinations of maximum temperature (Tx) and the Standardized Precipitation Evapotranspiration Index (SPEI) using monthly data from 1951 to 2014 acquired from the India Meteorological Department (IMD) for Indian landmass. From the results, the spatial extent of warm/dry events has increased at 1.8 % per decade, while cold/wet events decreased by 1.1 % over India. The warm/wet events have shown an increased trend of about 0.3 %, and cold/dry events at modest rise of 0.7 % per decade. Furthermore, compound warm/dry and cold/wet extremes over India exhibit extreme frequency and shorter return periods, posing greater risk. Conversely, compound cold/dry and warm/wet extremes occur less often, indicating longer return periods and lower risk. Across much of the country, the frequency of warm/dry, cold/dry, warm/wet, and cold/wet extremes ranges from 30 to 45, 15-30, 20-30, and 25-45 months, respectively. Notably, warm/dry conditions exhibit increased frequency in the recent period (1983-2014) with 31 years compared to the base period (1951-1982) which had approximately 24 years for a spatial extent exceeding 5 %. The findings of this study contribute to an enhanced understanding of the changes in compound climate extremes from a multivariate perspective.

Using climate envelopes and earth system model simulations for assessing climate change induced forest vulnerability.

Changing climatic conditions threaten forest ecosystems. Drought, disease and infestation, are leading to forest die-offs which cause substantial economic and ecological losses. In central Europe, this is especially relevant for commercially important coniferous tree species. This study uses climate envelope exceedance (CEE) to approximate species risk under different future climate scenarios. To achieve this, we used current species presence-absence and historical climate data, coupled with future climate scenarios from various Earth System Models. Climate scenarios tended towards drier and warmer conditions, causing strong CEEs especially for spruce. However, we show that annual averages of temperature and precipitation obscure climate extremes. Including climate extremes reveals a broader increase in CEEs across all tree species. Our study shows that the consideration of climate extremes, which cannot be adequately reflected in annual averages, leads to a different assessment of the risk of forests and thus the options for adapting to climate change.

Nitrogen deposition differentially regulates the sensitivity of gross primary productivity to extreme drought versus wetness.

Global hydroclimatic variability is increasing with more frequent extreme dry and wet years, severely destabilizing terrestrial ecosystem productivity. However, what regulates the consequence of precipitation extremes on productivity remains unclear. Based on a 9-year field manipulation experiment on the Qinghai-Tibetan Plateau, we found that the responses of gross primary productivity (GPP) to extreme drought and wetness were differentially regulated by nitrogen (N) deposition. Over increasing N deposition, extreme dry events reduced GPP more. Among the 12 biotic and abiotic factors examined, this was mostly explained by the increased plant canopy height and proportion of drought-sensitive species under N deposition, making photosynthesis more sensitive to hydraulic stress. While extreme wet events increased GPP, their effect did not shift over N deposition. These site observations were complemented by a global synthesis derived from the GOSIF GPP dataset, which showed that GPP sensitivity to extreme drought was larger in ecosystems with higher N deposition, but GPP sensitivity to extreme wetness did not change with N deposition. Our findings indicate that intensified hydroclimatic variability would lead to a greater loss of land carbon sinks in the context of increasing N deposition, due to that GPP losses during extreme dry years are more pronounced, yet without a synchronous increase in GPP gains during extreme wet years. The study implies that the conservation and management against climate extremes merit particular attention in ecosystems subject to N deposition.

Community assembly influences plant trait economic spectra and functional trade-offs at ecosystem scales.

Plant functional traits hold the potential to greatly improve the understanding and prediction of climate impacts on ecosystems and carbon cycle feedback to climate change. Traits are commonly used to place species along a global conservative-acquisitive trade-off, yet how and if functional traits and conservative-acquisitive trade-offs scale up to mediate community and ecosystem fluxes is largely unknown. Here, we combine functional trait datasets and multibiome datasets of forest water and carbon fluxes at the species, community, and ecosystem-levels to quantify the scaling of the tradeoff between maximum flux and sensitivity to vapor pressure deficit. We find a strong conservative-acquisitive trade-off at the species scale, which weakens modestly at the community scale and largely disappears at the ecosystem scale. Functional traits, particularly plant water transport (hydraulic) traits, are strongly associated with the key dimensions of the conservative-acquisitive trade-off at community and ecosystem scales, highlighting that trait composition appears to influence community and ecosystem flux dynamics. Our findings provide a foundation for improving carbon cycle models by revealing i) that plant hydraulic traits are most strongly associated with community- and ecosystem scale flux dynamics and ii) community assembly dynamics likely need to be considered explicitly, as they give rise to ecosystem-level flux dynamics that differ substantially from trade-offs identified at the species-level.

Unveiling the landscape predictors of resilient vegetation in coastal wetlands to inform conservation in the face of climate extremes.

Unveiling spatial variation in vegetation resilience to climate extremes can inform effective conservation planning under climate change. Although many conservation efforts are implemented on landscape scales, they often remain blind to landscape variation in vegetation resilience. We explored the distribution of drought-resilient vegetation (i.e., vegetation that could withstand and quickly recover from drought) and its predictors across a heterogeneous coastal landscape under long-term wetland conversion, through a series of high-resolution satellite image interpretations, spatial analyses, and nonlinear modelling. We found that vegetation varied greatly in drought resilience across the coastal wetland landscape and that drought-resilient vegetation could be predicted with distances to coastline and tidal channel. Specifically, drought-resilient vegetation exhibited a nearly bimodal distribution and had a seaward optimum at ~2 km from coastline (corresponding to an inundation frequency of ~30%), a pattern particularly pronounced in areas further away from tidal channels. Furthermore, we found that areas with drought-resilient vegetation were more likely to be eliminated by wetland conversion. Even in protected areas where wetland conversion was slowed, drought-resilient vegetation was increasingly lost to wetland conversion at its landward optimum in combination with rapid plant invasions at its seaward optimum. Our study highlights that the distribution of drought-resilient vegetation can be predicted using landscape features but without incorporating this predictive understanding, conservation efforts may risk failing in the face of climate extremes.

Broad-scale acoustic monitoring of koala populations suggests metapopulation stability, but varying bellow rate, in the face of major disturbances and climate extremes.

Population trends are lacking for most threatened species, especially those that are cryptic and difficult to survey. Recent developments in passive acoustics and semi-automated call recognition provide a cost-effective option to systematically monitor populations of vocal species. We assessed recent trends for the koala Phascolarctos cinereus, an iconic marsupial, based on 7 years of acoustic monitoring across 224 forested sites. The study period overlapped with a severe drought and extensive megafires in 2019 followed by 2 years of extremely high rainfall. Dynamic occupancy modelling with a range of covariates at multiple landscape scales found that initial occupancy was related to elevation (-ve), NDVI (+ve) and previous selective harvesting (16-30-year age class; weakly +ve). Extinction probability increased with the extent of high-severity fire. Colonisation probability was related to a range of factors, with the top model showing a decrease with increasing lagged annual rainfall. However, the null model was also supported, suggesting weak associations for colonisation. Using these relationships, koala occupancy was found to be high and stable over the study period. Fire did not influence regional trends because koalas often persisted with low- to moderate-severity fire and because high-severity fire was limited to 11% of their habitat. In contrast, bellow rate varied across years, being initially low and declining immediately after the 2019 fires, with the driver of these changes unclear. Neither timber harvesting nor low-severity fire influenced koala occupancy or bellow rate. Given the extensive area of koala habitat in the region, our results point to the presence of a large population in these public forests, and in recent years, stable occupancy (albeit with site-scale reductions in density with high-severity fire). Ongoing monitoring is crucial for tracking future changes, especially with predictions of more frequent, severe forest fires due to climate change.

Plant diversity and community age stabilize ecosystem multifunctionality.

It is well known that biodiversity positively affects ecosystem functioning, leading to enhanced ecosystem stability. However, this knowledge is mainly based on analyses using single ecosystem functions, while studies focusing on the stability of ecosystem multifunctionality (EMF) are rare. Taking advantage of a long-term grassland biodiversity experiment, we studied the effect of plant diversity (1-60 species) on EMF over 5 years, its temporal stability, as well as multifunctional resistance and resilience to a 2-year drought event. Using split-plot treatments, we further tested whether a shared history of plants and soil influences the studied relationships. We calculated EMF based on functions related to plants and higher-trophic levels. Plant diversity enhanced EMF in all studied years, and this effect strengthened over the study period. Moreover, plant diversity increased the temporal stability of EMF and fostered resistance to reoccurring drought events. Old plant communities with shared plant and soil history showed a stronger plant diversity-multifunctionality relationship and higher temporal stability of EMF than younger communities without shared histories. Our results highlight the importance of old and biodiverse plant communities for EMF and its stability to extreme climate events in a world increasingly threatened by global change.

Spatial variation in avian bill size is associated with temperature extremes in a major radiation of Australian passerines.

Morphology is integral to body temperature regulation. Recent advances in understanding of thermal physiology suggest a role of the avian bill in thermoregulation. To explore the adaptive significance of bill size for thermoregulation we characterized relationships between bill size and climate extremes. Most previous studies focused on climate means, ignoring frequencies of extremes, and do not reflect thermoregulatory costs experienced over shorter time scales. Using 79 species (9847 museum specimens), we explore how bill size variation is associated with temperature extremes in a large and diverse radiation of Australasian birds, Meliphagides, testing a series of predictions. Overall, across the continent, bill size variation was associated with both climate extremes and means and was most strongly associated with winter temperatures; associations at the level of climate zones differed from continent-wide associations and were complex, yet consistent with physiology and a thermoregulatory role for avian bills. Responses to high summer temperatures were nonlinear suggesting they may be difficult to detect in large-scale continental analyses using previous methodologies. We provide strong evidence that climate extremes have contributed to the evolution of bill morphology in relation to thermoregulation and show the importance of including extremes to understand fine-scale trait variation across space.

The coincidence of climate extremes with sensitive crop growth phases: Projected impact on sustainable crop water use and crop yield in the IGB river basins.

Increased climate variability and extremes are unequivocal with unprecedented impacts on water resources and agriculture production systems. However, little is known about the impacts of climate extremes at the intra-seasonal level which remained largely unexplored. We investigated the coincidence of climate extremes with sensitive crop growth phases of wheat and rice in the Indus, Ganges and Brahmaputra (IGB) river basins of South Asia. We also quantified the related impacts on irrigation water demand (IWD), gross primary production (GPP) and crop yields (CY) simulated by a hydrological-vegetation model (LPJmL) during 1981-2100 using RCP4.5-SSP1 and RCP8.5-SSP3 framework. The climate extremes revealed a higher frequency and intensity during crop growth phases with significant increasing trends in future. Diverse changes in IWD, GPP and CY are projected in future under the influence of crop phase-specific extremes. The crop phase-specific changes in the IWD of wheat and rice will intensify in the future. More than 50 % of the change in future wheat irrigation is caused by warm and dry extremes during the ripening phase. Whereas, increase in IWD for rice is mainly associated with warm extremes only. The crop phase-specific GPP shows a decreasing trend in future for both wheat and rice in the Western part of IGB with the largest decrease during the reproductive phase of wheat (up to 36 %) and vegetative phase of rice (>20 %). This decrease is clearly reflected in seasonal yields i.e., both wheat (20 %) and rice (12 %) showed a decrease in future linked with warm and dry extremes. However, in the Eastern part of IGB, the GPP will mostly increase in future during the three crop phases of wheat and rice. These results can be used to help develop efficient adaptation strategies considering seasonal changes and sensitive crop phases for sustained food and water security in South Asia.

Climate change causes declines and greater extremes in wetland inundation in a region important for wetland birds.

Wetland ecosystems are vital for maintaining global biodiversity, as they provide important stopover sites for many species of migrating wetland-associated birds. However, because weather determines their hydrologic cycles, wetlands are highly vulnerable to effects of climate change. Although changes in temperature and precipitation resulting from climate change are expected to reduce inundation of wetlands, few efforts have been made to quantify how these changes will influence the availability of stopover sites for migratory wetland birds. Additionally, few studies have evaluated how climate change will influence interannual variability or the frequency of extremes in wetland availability. For spring and fall bird migration in seven ecoregions in the south-central Great Plains of North America, we developed predictive models associating abundance of inundated wetlands with a suite of weather and land cover variables. We then used these models to generate predictions of wetland inundation at the end of the century (2069-2099) under future climate change scenarios. Climate models predicted the average number of inundated wetlands will likely decline during both spring and fall migration periods, with declines being greatest in the eastern ecoregions of the southern Great Plains. However, the magnitude of predicted declines varied considerably across climate models and ecoregions, with uncertainty among climate models being greatest in the High Plains ecoregion. Most ecoregions also were predicted to experience more-frequent extremely dry years (i.e., years with extremely low wetland abundances), but the projected change in interannual variability of wetland inundation was relatively small and varied across ecoregions and seasons. Because the south-central Great Plains represents an important link along the migratory routes of many wetland-dependent avian species, future declines in wetland inundation and more frequent periods of only a few wetlands being inundated will result in an uncertain future for migratory birds as they experience reduced availability of wetland stopover habitat across their migration pathways.

Data on Investigating the resilience of female smallholder livestock farmers to agricultural drought in South Africa's Northern Cape Province.

The resilience to agricultural drought of female smallholder livestock farmers in the Northern Cape province of South Africa was examined using the Abbreviated Women's Empowerment in Agriculture Index (A-WEAI). The A-WEAI consists of the 5DE index (five domains of empowerment) and the GPI (gender parity index). The total population interviewed was 154 participants (61 women in long-term relationships plus their male partners and 32 women who are single, divorced, or widowed). Researchers and policymakers can use the dataset to identify critical areas that need to be addressed to enhance women's empowerment in agriculture, which will increase their resilience to climate extremes such as agricultural drought.

Deeper topsoils enhance ecosystem productivity and climate resilience in arid regions, but not in humid regions.

Understanding the controlling mechanisms of soil properties on ecosystem productivity is essential for sustaining productivity and increasing resilience under a changing climate. Here we investigate the control of topsoil depth (e.g., A horizons) on long-term ecosystem productivity. We used nationwide observations (n = 2401) of topsoil depth and multiple scaled datasets of gross primary productivity (GPP) for five ecosystems (cropland, forest, grassland, pasture, shrubland) over 36 years (1986-2021) across the conterminous USA. The relationship between topsoil depth and GPP is primarily associated with water availability, which is particularly significant in arid regions under grassland, shrubland, and cropland (r = .37, .32, .15, respectively, p < .0001). For every 10 cm increase in topsoil depth, the GPP increased by 114 to 128 g C m-2 year-1 in arid regions (r = .33 and .45, p < .0001). Paired comparison of relatively shallow and deep topsoils while holding other variables (climate, vegetation, parent material, soil type) constant showed that the positive control of topsoil depth on GPP occurred primarily in cropland (0.73, confidence interval of 0.57-0.84) and shrubland (0.75, confidence interval of 0.40-0.94). The GPP difference between deep and shallow topsoils was small and not statistically significant. Despite the positive control of topsoil depth on productivity in arid regions, its contribution (coefficients: .09-.33) was similar to that of heat (coefficients: .06-.39) but less than that of water (coefficients: .07-.87). The resilience of ecosystem productivity to climate extremes varied in different ecosystems and climatic regions. Deeper topsoils increased stability and decreased the variability of GPP under climate extremes in most ecosystems, especially in shrubland and grassland. The conservation of topsoil in arid regions and improvements of soil depth representation and moisture-retention mechanisms are critical for carbon-sequestration ecosystem services under a changing climate. These findings and relationships should also be included in Earth system models.

Vegetation cover change and its response to climate extremes in the Yellow River Basin.

Extreme climate events have increased in frequency and severity under the background of climate change, with vegetation growth exhibiting a sensitive response to them. By assimilating GIMMS NDVI and MODIS NDVI using the Residual Network, we obtained a long time series and high resolution NDVI dataset of the Yellow River Basin (YRB). The dataset was utilized for examining the spatiotemporal variability of NDVI and analyzing the response of vegetation cover to climate extremes with meteorological data. Our findings reveal the following: (1) A significant rise in NDVI was seen in the YRB, displaying a mean growth rate of 0.019/10a (p < 0.001). However, seasonal differences exist. The mean NDVI of multi-year declines from southeast to northwest, while the overall trend of vegetation cover improves. (2) The NDVI response to extreme temperature exhibits noticeable spatiotemporal differences. Daytime extreme high temperature in the northern YRB is negatively correlated with NDVI, while they are positively correlated in the lower YRB and the southern part of the middle YRB. Nighttime extreme high temperature exhibits a positive correlation with NDVI. Overall, NDVI displays a stronger response to extreme precipitation than to extreme temperature, with a negative correlation with CWD and a positive correlation with PRCPTOT. (3) The NDVI demonstrates a lagged response to climate extremes in the YRB, with a greater lag in response to extreme temperature than extreme precipitation. The research findings can provide scientific support for the future management and planning of vegetation in the YRB, as well as contribute to the promotion of ecological environment regulation and sustainable development.

Drought risk probabilistic models based on extreme value theory.

The article presents original, probabilistic models for the quantification of drought risk, based on generalized distribution functions for the distribution of maximum values as well as the standardized precipitation index. Using the models, a probabilistic measurement of drought risk has been made for three regions over four 5-year periods for each region. Three measurement points located in Poland were selected as a case study. The study provides an innovative approach in the field of probabilistic models of quantification; moreover, drought risk levels have been calculated for the selected locations. Furthermore, the method may be used for creating indexes for any climatic region subject to study.

Performance of regional water purification plants during extreme weather events: three case studies from New South Wales, Australia.

Climate change is altering weather patterns, which affects water supply systems globally. More frequent extreme weather events like floods, droughts, and heatwaves are impacting the availability of raw water sources that supply cities. These events can lead to less water, higher demand, and potential infrastructure damage. Water agencies and utilities must develop resilient and adaptable systems to withstand shocks and stresses. Case studies demonstrating the impact of extreme weather on water quality are important for developing resilient water supply systems. This paper documents the challenges faced by regional New South Wales (NSW) in managing water quality and supply during extreme weather events. Effective treatment processes, such as ozone treatment and adsorption, are used to maintain drinking water standards during extreme weather. Water-efficient alternatives are provided, and critical water networks are inspected to identify leaks and reduce system demand. Local government areas must collaborate and share resources to ensure that towns can cope with future extreme weather events. Systematic investigation is needed to understand system capacity and identify surplus resources to be shared when demand cannot be met. Pooling resources could benefit regional towns experiencing both floods and droughts. With expected population growth in the area, regional NSW councils will require a significant increase in water filtration infrastructure to handle increased system loading. Continuous research, regular strategy reviews, and innovative approaches are essential to ensure a secure and reliable water supply during future extreme weather events.

Sub-zero temperatures and large-scale weather patterns induce tooth damage in Icelandic arctic foxes.

Tooth damage in carnivores can reflect shifts in both diet and feeding habits, and in large carnivores, it is associated with increased bone consumption. Variation in tooth condition in Icelandic arctic foxes, a mesocarnivore, was recorded from 854 individual foxes spanning 29 years. We hypothesized that annual climatic variations, which can influence food abundance and accessibility, will influence tooth condition by causing dietary shifts toward less edible prey. We examined tooth condition in relation to four climatic predictors: mean annual winter temperature, indices of both the El Niño anomaly and North Atlantic subpolar gyre (SPG), and the number of rain-on-snow days (ROS). We found unequivocal evidence for a strong effect of annual climate on tooth condition. Teeth of Icelandic foxes were in better condition when winter temperatures were higher, when the SPG was more positive, and when the number of ROS was low. We also found a substantial subregional effect with foxes from northeastern Iceland having lower tooth damage than those from two western sites. Contradicting our original hypothesis that foxes from northeastern Iceland, where foxes are known to scavenge on large mammal remains (e.g., sheep and horses), would show the highest tooth damage, we suggest that western coastal sites exhibited greater tooth damage because cold winter temperatures lowered the availability of seabirds, causing a shift in diet toward abrasive marine subsidies (e.g., bivalves) and frozen beach wrack. Our study shows that monitoring tooth breakage and wear can be a useful tool for evaluating the impact of climate on carnivore populations and that climate change may influence the condition and fitness of carnivores in complex and potentially conflicting ways.

Toward Earth system modeling with resolved clouds and ocean submesoscales on heterogeneous many-core HPCs.

With the aid of the newly developed 'Sunway' heterogeneous-architecture supercomputer, which has world-leading HPC (high-performance computer) capability, a series of high-resolution coupled Earth system models (SW-HRESMs) with up to 5 km of atmosphere and 3 km of ocean have been developed. These models can meet the needs of multiscale interaction studies with different computational costs. Here we describe the progress of SW-HRESMs development, with an overview of the major advancements made by the international Earth science community in HR-ESMs. We also show the preliminary results of SW-HRESMs with regard to capturing major weather-climate extremes in the atmosphere and ocean, stressing the importance of permitted clouds and ocean submesoscale eddies in modeling tropical cyclones and eddy-mean flow interactions, and paving the way for further model development to resolve finer scales with even higher resolution and more realistic physics. Finally, in addition to increasing model resolution, the development procedure for a non-hydrostatic cloud and ocean submesoscale resolved ESM is discussed, laying out the major scientific directions of such a huge modeling advancement.

Immediate and carry-over effects of late-spring frost and growing season drought on forest gross primary productivity capacity in the Northern Hemisphere.

Forests are increasingly exposed to extreme global warming-induced climatic events. However, the immediate and carry-over effects of extreme events on forests are still poorly understood. Gross primary productivity (GPP) capacity is regarded as a good proxy of the ecosystem's functional stability, reflecting its physiological response to its surroundings. Using eddy covariance data from 34 forest sites in the Northern Hemisphere, we analyzed the immediate and carry-over effects of late-spring frost (LSF) and growing season drought on needle-leaf and broadleaf forests. Path analysis was applied to reveal the plausible reasons behind the varied responses of forests to extreme events. The results show that LSF had clear immediate effects on the GPP capacity of both needle-leaf and broadleaf forests. However, GPP capacity in needle-leaf forests was more sensitive to drought than in broadleaf forests. There was no interaction between LSF and drought in either needle-leaf or broadleaf forests. Drought effects were still visible when LSF and drought coexisted in needle-leaf forests. Path analysis further showed that the response of GPP capacity to drought differed between needle-leaf and broadleaf forests, mainly due to the difference in the sensitivity of canopy conductance. Moreover, LSF had a more severe and long-lasting carry-over effect on forests than drought. These results enrich our understanding of the mechanisms of forest response to extreme events across forest types.

Climate change threats to the global functional diversity of freshwater fish.

Climate change impacts on freshwater ecosystems and freshwater biodiversity show strong spatial variability, highlighting the importance of a global perspective. While previous studies on biodiversity mostly focused on species richness, functional diversity, which is a better predictor of ecosystem functioning, has received much less attention. This study aims to comprehensively assess climate change threats to the functional diversity of freshwater fish across the world, considering three complementary metrics-functional richness, evenness and divergence. We built on existing spatially explicit projections of geographical ranges for 11,425 riverine fish species as affected by changes in streamflow and water temperature extremes at four warming levels (1.5°C, 2.0°C, 3.2°C and 4.5°C). To estimate functional diversity, we considered the following four continuous, morphological and physiological traits: relative head length, relative body depth, trophic level and relative growth rate. Together, these traits cover five ecological functions. We treated missing trait values in two different ways: we either removed species with missing trait values or imputed them. Depending on the warming level, 6%-25% of the locations globally face a complete loss of functional diversity when assuming no dispersal (6%-17% when assuming maximal dispersal), with hotspots in the Amazon and Paraná River basins. The three facets of functional diversity do not always follow the same pattern. Sometimes, functional richness is not yet affected despite species loss, while functional evenness and divergence are already reducing. Other times, functional richness reduces, while functional evenness and/or divergence increase instead. The contrasting patterns of the three facets of functional diversity show their complementarity among each other and their added value compared to species richness. With increasing climate change, impacts on freshwater communities accelerate, making early mitigation critically important.