Uncertainty in climate projections is driven by three components: scenario uncertainty, intermodel uncertainty, and internal variability. Although socioeconomic climate impact studies increasingly take into account the first two components, little attention has been paid to the role of internal variability, although underestimating this uncertainty may lead to underestimating the socioeconomic costs of climate change. Using large ensembles from seven coupled general circulation models with a total of 414 model runs, we partition the climate uncertainty in classic dose-response models relating county-level corn yield, mortality, and per-capita gross domestic product to temperature in the continental United States. The partitioning of uncertainty depends on the time frame of projection, the impact model, and the geographic region. Internal variability represents more than 50% of the total climate uncertainty in certain projections, including mortality projections for the early 21st century, although its relative influence decreases over time. We recommend including uncertainty due to internal variability for many projections of temperature-driven impacts, including early-century and midcentury projections, projections in regions with high internal variability such as the Upper Midwest United States, and impacts driven by nonlinear relationships.

Plants will experience considerable changes in climate within their geographic ranges over the next several decades. They may respond by exhibiting niche flexibility and adapting to changing climates. Alternatively, plant taxa may exhibit climate fidelity, shifting their geographic distributions to track their preferred climates. Here, we examine the responses of plant taxa to changing climates over the past 18,000 y to evaluate the extent to which the 16 dominant plant taxa of North America have exhibited climate fidelity. We find that 75% of plant taxa consistently exhibit climate fidelity over the past 18,000 y, even during the times of most extreme climate change. Of the four taxa that do not consistently exhibit climate fidelity, three-elm (Ulmus), beech (Fagus), and ash (Fraxinus)-experience a long-term shift in their realized climatic niche between the early Holocene and present day. Plant taxa that migrate longer distances better maintain consistent climatic niches across transition periods during times of the most extreme climate change. Today, plant communities with the highest climate fidelity are found in regions with high topographic and microclimate heterogeneity that are expected to exhibit high climate resilience, allowing plants to shift distributions locally and adjust to some amount of climate change. However, once the climate change buffering of the region is exceeded, these plant communities will need to track climates across broader landscapes but be challenged to do so because of the low habitat connectivity of the regions.

Terrestrial vegetation and soils hold three times more carbon than the atmosphere. Much debate concerns how anthropogenic activity will perturb these surface reservoirs, potentially exacerbating ongoing changes to the climate system. Uncertainties specifically persist in extrapolating point-source observations to ecosystem-scale budgets and fluxes, which require consideration of vertical and lateral processes on multiple temporal and spatial scales. To explore controls on organic carbon (OC) turnover at the river basin scale, we present radiocarbon (14C) ages on two groups of molecular tracers of plant-derived carbon-leaf-wax lipids and lignin phenols-from a globally distributed suite of rivers. We find significant negative relationships between the 14C age of these biomarkers and mean annual temperature and precipitation. Moreover, riverine biospheric-carbon ages scale proportionally with basin-wide soil carbon turnover times and soil 14C ages, implicating OC cycling within soils as a primary control on exported biomarker ages and revealing a broad distribution of soil OC reactivities. The ubiquitous occurrence of a long-lived soil OC pool suggests soil OC is globally vulnerable to perturbations by future temperature and precipitation increase. Scaling of riverine biospheric-carbon ages with soil OC turnover shows the former can constrain the sensitivity of carbon dynamics to environmental controls on broad spatial scales. Extracting this information from fluvially dominated sedimentary sequences may inform past variations in soil OC turnover in response to anthropogenic and/or climate perturbations. In turn, monitoring riverine OC composition may help detect future climate-change-induced perturbations of soil OC turnover and stocks.

Food security relies on the resilience of staple food crops to climatic variability and extremes, but the climate resilience of European wheat is unknown. A diversity of responses to disturbance is considered a key determinant of resilience. The capacity of a sole crop genotype to perform well under climatic variability is limited; therefore, a set of cultivars with diverse responses to weather conditions critical to crop yield is required. Here, we show a decline in the response diversity of wheat in farmers' fields in most European countries after 2002-2009 based on 101,000 cultivar yield observations. Similar responses to weather were identified in cultivar trials among central European countries and southern European countries. A response diversity hotspot appeared in the trials in Slovakia, while response diversity "deserts" were identified in Czechia and Germany and for durum wheat in southern Europe. Positive responses to abundant precipitation were lacking. This assessment suggests that current breeding programs and cultivar selection practices do not sufficiently prepare for climatic uncertainty and variability. Consequently, the demand for climate resilience of staple food crops such as wheat must be better articulated. Assessments and communication of response diversity enable collective learning across supply chains. Increased awareness could foster governance of resilience through research and breeding programs, incentives, and regulation.

Record-breaking summer forest fires have become a regular occurrence in California. Observations indicate a fivefold increase in summer burned area (BA) in forests in northern and central California during 1996 to 2021 relative to 1971 to 1995. While the higher temperature and increased dryness have been suggested to be the leading causes of increased BA, the extent to which BA changes are due to natural variability or anthropogenic climate change remains unresolved. Here, we develop a climate-driven model of summer BA evolution in California and combine it with natural-only and historical climate simulations to assess the importance of anthropogenic climate change on increased BA. Our results indicate that nearly all the observed increase in BA is due to anthropogenic climate change as historical model simulations accounting for anthropogenic forcing yield 172% (range 84 to 310%) more area burned than simulations with natural forcing only. We detect the signal of combined historical forcing on the observed BA emerging in 2001 with no detectable influence of the natural forcing alone. In addition, even when considering fuel limitations from fire-fuel feedbacks, a 3 to 52% increase in BA relative to the last decades is expected in the next decades (2031 to 2050), highlighting the need for proactive adaptations.

Deficiencies of micronutrients, including essential trace elements, affect up to 3 billion people worldwide. The dietary availability of trace elements is determined largely by their soil concentrations. Until now, the mechanisms governing soil concentrations have been evaluated in small-scale studies, which identify soil physicochemical properties as governing variables. However, global concentrations of trace elements and the factors controlling their distributions are virtually unknown. We used 33,241 soil data points to model recent (1980-1999) global distributions of Selenium (Se), an essential trace element that is required for humans. Worldwide, up to one in seven people have been estimated to have low dietary Se intake. Contrary to small-scale studies, soil Se concentrations were dominated by climate-soil interactions. Using moderate climate-change scenarios for 2080-2099, we predicted that changes in climate and soil organic carbon content will lead to overall decreased soil Se concentrations, particularly in agricultural areas; these decreases could increase the prevalence of Se deficiency. The importance of climate-soil interactions to Se distributions suggests that other trace elements with similar retention mechanisms will be similarly affected by climate change.

The rapid increase of the potent greenhouse gas methane in the atmosphere creates great urgency to develop and deploy technologies for methane mitigation. One approach to removing methane is to use bacteria for which methane is their carbon and energy source (methanotrophs). Such bacteria naturally convert methane to CO2 and biomass, a value-added product and a cobenefit of methane removal. Typically, methanotrophs grow best at around 5,000 to 10,000 ppm methane, but methane in the atmosphere is 1.9 ppm. Air above emission sites such as landfills, anaerobic digestor effluents, rice paddy effluents, and oil and gas wells contains elevated methane in the 500 ppm range. If such sites are targeted for methane removal, technology harnessing aerobic methanotroph metabolism has the potential to become economically and environmentally viable. The first step in developing such methane removal technology is to identify methanotrophs with enhanced ability to grow and consume methane at 500 ppm and lower. We report here that some existing methanotrophic strains grow well at 500 ppm methane, and one of them, Methylotuvimicrobium buryatense 5GB1C, consumes such low methane at enhanced rates compared to previously published values. Analyses of bioreactor-based performance and RNAseq-based transcriptomics suggest that this ability to utilize low methane is based at least in part on extremely low non-growth-associated maintenance energy and on high methane specific affinity. This bacterium is a candidate to develop technology for methane removal at emission sites. If appropriately scaled, such technology has the potential to slow global warming by 2050.

The responses of tropical forests to environmental change are critical uncertainties in predicting the future impacts of climate change. The positive phase of the 2015-2016 El Niño Southern Oscillation resulted in unprecedented heat and low precipitation in the tropics with substantial impacts on the global carbon cycle. The role of African tropical forests is uncertain as their responses to short-term drought and temperature anomalies have yet to be determined using on-the-ground measurements. African tropical forests may be particularly sensitive because they exist in relatively dry conditions compared with Amazonian or Asian forests, or they may be more resistant because of an abundance of drought-adapted species. Here, we report responses of structurally intact old-growth lowland tropical forests inventoried within the African Tropical Rainforest Observatory Network (AfriTRON). We use 100 long-term inventory plots from six countries each measured at least twice prior to and once following the 2015-2016 El Niño event. These plots experienced the highest temperatures and driest conditions on record. The record temperature did not significantly reduce carbon gains from tree growth or significantly increase carbon losses from tree mortality, but the record drought did significantly decrease net carbon uptake. Overall, the long-term biomass increase of these forests was reduced due to the El Niño event, but these plots remained a live biomass carbon sink (0.51 ± 0.40 Mg C ha-1 y-1) despite extreme environmental conditions. Our analyses, while limited to African tropical forests, suggest they may be more resistant to climatic extremes than Amazonian and Asian forests.

Primary productivity response to climatic drivers varies temporally, indicating state-dependent interactions between climate and productivity. Previous studies primarily employed equation-based approaches to clarify this relationship, ignoring the state-dependent nature of ecological dynamics. Here, using 40 y of climate and productivity data from 48 grassland sites across Mongolia, we applied an equation-free, nonlinear time-series analysis to reveal sensitivity patterns of productivity to climate change and variability and clarify underlying mechanisms. We showed that productivity responded positively to annual precipitation in mesic regions but negatively in arid regions, with the opposite pattern observed for annual mean temperature. Furthermore, productivity responded negatively to decreasing annual aridity that integrated precipitation and temperature across Mongolia. Productivity responded negatively to interannual variability in precipitation and aridity in mesic regions but positively in arid regions. Overall, interannual temperature variability enhanced productivity. These response patterns are largely unrecognized; however, two mechanisms are inferable. First, time-delayed climate effects modify annual productivity responses to annual climate conditions. Notably, our results suggest that the sensitivity of annual productivity to increasing annual precipitation and decreasing annual aridity can even be negative when the negative time-delayed effects of annual precipitation and aridity on productivity prevail across time. Second, the proportion of plant species resistant to water and temperature stresses at a site determines the sensitivity of productivity to climate variability. Thus, we highlight the importance of nonlinear, state-dependent sensitivity of productivity to climate change and variability, accurately forecasting potential biosphere feedback to the climate system.

Climate change is driving widespread changes in ecological communities. Warming temperatures often shift community composition toward more heat-tolerant taxa. The factors influencing the rate of this "thermophilization" process remain unclear. Using 10-y census data from an extensive forest plot network, we show that mature tree communities of the western United States have undergone thermophilization. The mean magnitude of climate warming over the 10-y study interval was 0.32 °C, whereas the mean magnitude of thermophilization was 0.039 °C. Differential tree mortality was the strongest demographic driver of thermophilization, rather than growth or recruitment. Thermophilization rates are associated with recent changes in temperature and hydrologic variables, as well as topography and disturbance, with insect damage showing the strongest standardized effect on thermophilization rates. On average, thermophilization occurred more rapidly on cool, north-facing hillslopes. Our results demonstrate that warming temperatures are outpacing the composition of western US forest tree communities, and that climate change may erode biodiversity patterns structured by topographic variation.

Underlying sociopolitical factors have emerged as important determinants of wildlife population trends and the effectiveness of conservation action. Despite mounting research into the impacts of climate change on nature, there has been little consideration of the human context in which these impacts occur, particularly at the global scale. We investigate this in two ways. First, by modeling the climatic niches of terrestrial mammals and birds globally, we show that projected species loss under climate change is greatest in countries with weaker governance and lower Gross Domestic Product, with loss of mammal species projected to be greater in countries with lower CO2 emissions. Therefore, climate change impacts on species may be disproportionately significant in countries with lower capacity for effective conservation and lower greenhouse gas emissions, raising important questions of international justice. Second, we consider the redistribution of species in the context of political boundaries since the global importance of transboundary conservation under climate change is poorly understood. Under a high-emissions scenario, we find that 35% of mammals and 29% of birds are projected to have over half of their 2070 climatic niche in countries in which they are not currently found. We map these transboundary range shifts globally, identifying borders across which international coordination might most benefit conservation and where physical border barriers, such as walls and fences, may be an overlooked obstacle to climate adaptation. Our work highlights the importance of sociopolitical context and the utility of a supranational perspective for 21st century nature conservation.

Climate change is expected to affect crop production worldwide, particularly in rain-fed agricultural regions. It is still unknown how irrigation water needs will change in a warmer planet and where freshwater will be locally available to expand irrigation without depleting freshwater resources. Here, we identify the rain-fed cropping systems that hold the greatest potential for investment in irrigation expansion because water will likely be available to suffice irrigation water demand. Using projections of renewable water availability and irrigation water demand under warming scenarios, we identify target regions where irrigation expansion may sustain crop production under climate change. Our results also show that global rain-fed croplands hold significant potential for sustainable irrigation expansion and that different irrigation strategies have different irrigation expansion potentials. Under a 3 °C warming, we find that a soft-path irrigation expansion with small monthly water storage and deficit irrigation has the potential to expand irrigated land by 70 million hectares and feed 300 million more people globally. We also find that a hard-path irrigation expansion with large annual water storage can sustainably expand irrigation up to 350 million hectares, while producing food for 1.4 billion more people globally. By identifying where irrigation can be expanded under a warmer climate, this work may serve as a starting point for investigating socioeconomic factors of irrigation expansion and may guide future research and resources toward those agricultural communities and water management institutions that will most need to adapt to climate change.

Climate change triggers poleward shifts in species distribution leading to changes in biogeography. In the marine environment, fish respond quickly to warming, causing community-wide reorganizations, which result in profound changes in ecosystem functioning. Functional biogeography provides a framework to address how ecosystem functioning may be affected by climate change over large spatial scales. However, there are few studies on functional biogeography in the marine environment, and none in the Arctic, where climate-driven changes are most rapid and extensive. We investigated the impact of climate warming on the functional biogeography of the Barents Sea, which is characterized by a sharp zoogeographic divide separating boreal from Arctic species. Our unique dataset covered 52 fish species, 15 functional traits, and 3,660 stations sampled during the recent warming period. We found that the functional traits characterizing Arctic fish communities, mainly composed of small-sized bottom-dwelling benthivores, are being rapidly replaced by traits of incoming boreal species, particularly the larger, longer lived, and more piscivorous species. The changes in functional traits detected in the Arctic can be predicted based on the characteristics of species expected to undergo quick poleward shifts in response to warming. These are the large, generalist, motile species, such as cod and haddock. We show how functional biogeography can provide important insights into the relationship between species composition, diversity, ecosystem functioning, and environmental drivers. This represents invaluable knowledge in a period when communities and ecosystems experience rapid climate-driven changes across biogeographical regions.

Behavioral change is essential to mitigate climate change. To advance current knowledge, we synthesize research on interventions aiming to promote climate change mitigation behaviors in field settings. In a preregistered second-order meta-analysis, we assess the overall effect of 10 meta-analyses, incorporating a total of 430 primary studies. In addition, we assess subgroup analyses for six types of interventions, five behaviors, and three publication bias adjustments. Results showed that climate change mitigation interventions were generally effective (dunadjusted = 0.31, 95% CI [0.30, 0.32]). A follow-up analysis using only unique primary studies, adjusted for publication bias, provides a more conservative overall estimate (d = 0.18, 95% CI [0.13, 0.24]). This translates into a mean treatment effect of 7 percentage points. Furthermore, in a subsample of adequately powered large-scale interventions (n > 9,000, k = 32), the effect was adjusted downward to approximately 2 percentage points. This discrepancy might be because large-scale interventions often target nonvoluntary participants by less direct techniques (e.g., "home energy reports") while small-scale interventions often target voluntary participants by more direct techniques (e.g., face-to-face interactions). Subgroup analyses showed that interventions based on social comparisons or financial incentives were the most effective, while education or feedback was the least effective. These results provide a comprehensive state-of-the-art summary of climate change mitigation interventions, guiding both future research and practice.

Forcing due to solar and volcanic variability, on the natural side, and greenhouse gas and aerosol emissions, on the anthropogenic side, are the main inputs to climate models. Reliable climate model simulations of past and future climate change depend crucially upon them. Here we analyze large ensembles of simulations using a comprehensive Earth System Model to quantify uncertainties in global climate change attributable to differences in prescribed forcings. The different forcings considered here are those used in the two most recent phases of the Coupled Model Intercomparison Project (CMIP), namely CMIP5 and CMIP6. We show significant differences in simulated global surface air temperature due to volcanic aerosol forcing in the second half of the 19th century and in the early 21st century. The latter arise from small-to-moderate eruptions incorporated in CMIP6 simulations but not in CMIP5 simulations. We also find significant differences in global surface air temperature and Arctic sea ice area due to anthropogenic aerosol forcing in the second half of the 20th century and early 21st century. These differences are as large as those obtained in different versions of an Earth System Model employing identical forcings. In simulations from 2015 to 2100, we find significant differences in the rates of projected global warming arising from CMIP5 and CMIP6 concentration pathways that differ slightly but are equivalent in terms of their nominal radiative forcing levels in 2100. Our results highlight the influence of assumptions about natural and anthropogenic aerosol loadings on carbon budgets, the likelihood of meeting Paris targets, and the equivalence of future forcing scenarios.

Future population growth is uncertain and matters for climate policy: higher growth entails more emissions and means more people will be vulnerable to climate-related impacts. We show that how future population is valued importantly determines mitigation decisions. Using the Dynamic Integrated Climate-Economy model, we explore two approaches to valuing population: a discounted version of total utilitarianism (TU), which considers total wellbeing and is standard in social cost of carbon dioxide (SCC) models, and of average utilitarianism (AU), which ignores population size and sums only each time period's discounted average wellbeing. Under both approaches, as population increases the SCC increases, but optimal peak temperature decreases. The effect is larger under TU, because it responds to the fact that a larger population means climate change hurts more people: for example, in 2025, assuming the United Nations (UN)-high rather than UN-low population scenario entails an increase in the SCC of 85% under TU vs. 5% under AU. The difference in the SCC between the two population scenarios under TU is comparable to commonly debated decisions regarding time discounting. Additionally, we estimate the avoided mitigation costs implied by plausible reductions in population growth, finding that large near-term savings ($billions annually) occur under TU; savings under AU emerge in the more distant future. These savings are larger than spending shortfalls for human development policies that may lower fertility. Finally, we show that whether lowering population growth entails overall improvements in wellbeing-rather than merely cost savings-again depends on the ethical approach to valuing population.

Sedimentological records provide the only accessible archive for unraveling Earth’s orbital variations in the remote geological past. These variations modulate Earth’s climate system and provide essential constraints on gravitational parameters used in solar system modeling. However, geologic documentation of midlatitude response to orbital climate forcing remains poorly resolved compared to that of the low-latitude tropics, especially before 50 Mya, the limit of reliable extrapolation from the present. Here, we compare the climate response to orbital variations in a Late Triassic midlatitude temperate setting in Jameson Land, East Greenland (∼43°N paleolatitude) and the tropical low paleolatitude setting of the Newark Basin, with independent time horizons provided by common magnetostratigraphic boundaries whose timing has been corroborated by uranium-lead (U-Pb) zircon dating in correlative strata on the Colorado Plateau. An integrated cyclostratigraphic and magnetostratigraphic age model revealed long-term climate cycles with periods of 850,000 and 1,700,000 y ascribed to the Mars–Earth grand orbital cycles. This indicates a 2:1 resonance between modulation of orbital obliquity and eccentricity variations more than 200 Mya and whose periodicities are inconsistent with astronomical solutions and indicate chaotic diffusion of the solar system. Our findings also demonstrate antiphasing in climate response between low and midlatitudes that has implications for precise global correlation of geological records.

Poikilothermic animals comprise most species on Earth and are especially sensitive to changes in environmental temperatures. Species conservation in a changing climate relies upon predictions of species responses to future conditions, yet predicting species responses to climate change when temperatures exceed the bounds of observed data is fraught with challenges. We present a physiologically guided abundance (PGA) model that combines observations of species abundance and environmental conditions with laboratory-derived data on the physiological response of poikilotherms to temperature to predict species geographical distributions and abundance in response to climate change. The model incorporates uncertainty in laboratory-derived thermal response curves and provides estimates of thermal habitat suitability and extinction probability based on site-specific conditions. We show that temperature-driven changes in distributions, local extinction, and abundance of cold, cool, and warm-adapted species vary substantially when physiological information is incorporated. Notably, cold-adapted species were predicted by the PGA model to be extirpated in 61% of locations that they currently inhabit, while extirpation was never predicted by a correlative niche model. Failure to account for species-specific physiological constraints could lead to unrealistic predictions under a warming climate, including underestimates of local extirpation for cold-adapted species near the edges of their climate niche space and overoptimistic predictions of warm-adapted species.

Diagnosing dynamical changes in the climate system, such as those in atmospheric circulation patterns, remains challenging. Here, we study 1950 to 2021 trends in the frequency of occurrence of atmospheric circulation patterns over the North Atlantic. Roughly 7% of atmospheric circulation patterns display significant occurrence trends, yet they have major impacts on surface climate. Increasingly frequent patterns drive heatwaves across Europe and enhanced wintertime storminess in the northern part of the continent. Over 91% of recent heatwave-related deaths and 33% of high-impact windstorms in Europe were concurrent with increasingly frequent atmospheric circulation patterns. While the trends identified are statistically significant, they are not necessarily anthropogenic. Atmospheric patterns which are becoming rarer correspond instead to wet, cool summer conditions over northern Europe and wet winter conditions over continental Europe. The combined effect of these circulation changes is that of a strong, dynamically driven year-round warming over most of the continent and large regional and seasonal changes in precipitation and surface wind.

Seasonal tropical environments are among those regions that are the most affected by shifts in temperature and rainfall regimes under climate change, with potentially severe consequences for wildlife population persistence. This persistence is ultimately determined by complex demographic responses to multiple climatic drivers, yet these complexities have been little explored in tropical mammals. We use long-term, individual-based demographic data (1994 to 2020) from a short-lived primate in western Madagascar, the gray mouse lemur (Microcebus murinus), to investigate the demographic drivers of population persistence under observed shifts in seasonal temperature and rainfall. While rainfall during the wet season has been declining over the years, dry season temperatures have been increasing, with these trends projected to continue. These environmental changes resulted in lower survival and higher recruitment rates over time for gray mouse lemurs. Although the contrasting changes have prevented the study population from collapsing, the resulting increase in life-history speed has destabilized an otherwise stable population. Population projections under more recent rainfall and temperature levels predict an increase in population fluctuations and a corresponding increase in the extinction risk over the next five decades. Our analyses show that a relatively short-lived mammal with high reproductive output, representing a life history that is expected to closely track changes in its environment, can nonetheless be threatened by climate change.