Catalogue of abrupt shifts in Intergovernmental Panel on Climate Change climate models

Early warning signals of the termination of the African Humid Period(s)

The transition from a humid green Sahara to today's hyperarid conditions in northern Africa ~5.5 thousand years ago shows the dramatic environmental change to which human societies were exposed and had to adapt to. In this work, we show that in the 620,000-year environmental record from the Chew Bahir basin in the southern Ethiopian Rift, with its decadal resolution, this one thousand year long transition is particularly well documented, along with 20-80 year long droughts, recurring every ~160 years, as possible early warnings. Together with events of extreme wetness at the end of the transition, these droughts form a pronounced climate "flickering", which can be simulated in climate models and is also present in earlier climate transitions in the Chew Bahir environmental record, indicating that transitions with flickering are characteristic of this region.

Critical transitions in the Amazon forest system

The possibility that the Amazon forest system could soon reach a tipping point, inducing large-scale collapse, has raised global concern1-3. For 65 million years, Amazonian forests remained relatively resilient to climatic variability. Now, the region is increasingly exposed to unprecedented stress from warming temperatures, extreme droughts, deforestation and fires, even in central and remote parts of the system1. Long existing feedbacks between the forest and environmental conditions are being replaced by novel feedbacks that modify ecosystem resilience, increasing the risk of critical transition. Here we analyse existing evidence for five major drivers of water stress on Amazonian forests, as well as potential critical thresholds of those drivers that, if crossed, could trigger local, regional or even biome-wide forest collapse. By combining spatial information on various disturbances, we estimate that by 2050, 10% to 47% of Amazonian forests will be exposed to compounding disturbances that may trigger unexpected ecosystem transitions and potentially exacerbate regional climate change. Using examples of disturbed forests across the Amazon, we identify the three most plausible ecosystem trajectories, involving different feedbacks and environmental conditions. We discuss how the inherent complexity of the Amazon adds uncertainty about future dynamics, but also reveals opportunities for action. Keeping the Amazon forest resilient in the Anthropocene will depend on a combination of local efforts to end deforestation and degradation and to expand restoration, with global efforts to stop greenhouse gas emissions.

Early warning signals have limited applicability to empirical lake data

Research aimed at identifying indicators of persistent abrupt shifts in ecological communities, a.k.a regime shifts, has led to the development of a suite of early warning signals (EWSs). As these often perform inaccurately when applied to real-world observational data, it remains unclear whether critical transitions are the dominant mechanism of regime shifts and, if so, which EWS methods can predict them. Here, using multi-trophic planktonic data on multiple lakes from around the world, we classify both lake dynamics and the reliability of classic and second generation EWSs methods to predict whole-ecosystem change. We find few instances of critical transitions, with different trophic levels often expressing different forms of abrupt change. The ability to predict this change is highly processing dependant, with most indicators not performing better than chance, multivariate EWSs being weakly superior to univariate, and a recent machine learning model performing poorly. Our results suggest that predictive ecology should start to move away from the concept of critical transitions, developing methods suitable for predicting resilience loss not limited to the strict bounds of bifurcation theory.

Systematic analysis and optimization of early warning signals for critical transitions using distribution data

Abrupt shifts between alternative regimes occur in complex systems, from cell regulation to brain functions to ecosystems. Several model-free early warning signals (EWS) have been proposed to detect impending transitions, but failure or poor performance in some systems have called for better investigation of their generic applicability. Notably, there are still ongoing debates whether such signals can be successfully extracted from data in particular from biological experiments. In this work, we systematically investigate properties and performance of dynamical EWS in different deteriorating conditions, and we propose an optimized combination to trigger warnings as early as possible, eventually verified on experimental data from microbiological populations. Our results explain discrepancies observed in the literature between warning signs extracted from simulated models and from real data, provide guidance for EWS selection based on desired systems and suggest an optimized composite indicator to alert for impending critical transitions using distribution data.

Quantitative characterization of drying-induced cracks and permeability of granite residual soil using micron-sized X-ray computed tomography

Drying-induced cracks negatively impacts the performance of soils in the context of global warming. Traditional testing approaches used for the cracking characterization of soils are mainly based on surface observation and qualitative inspections. In this study, a temporal investigation of micron-sized X-ray computed tomography (Micro-CT) tests was performed on the granite residual soil (GRS) during desiccation for the first time. Through three-dimensional (3D) reconstructions and seepage simulations, the dynamic evolution of drying-induced cracks and permeability that evolved (0 to 120 h) was visually characterized and intensively quantified. Experimental results show that the averaged area-porosity ratio varies as an increasing trend, appearing fast at first and slowly thereafter during desiccation.. Observed by 3D reconstruction models, connected cracks rapidly propagated through the samples while isolated cracks occupied small volumes and remained almost unchanged. The pore-diameter distribution of GRS reveals that the propagation of connected cracks is essential in influencing soil cracking. The simulated permeability is generally comparable with measuring ones with an acceptable error margin, demonstrating the accuracy of seepage models. The increasing permeability from both experiments and numerical simulations indicates the desiccation process severely impacts the hydraulic properties of soils. This study provides an adamant evidence that the Micro-CT is an effective and feasible tool for the elucidation of drying-induced crack evolutions and in building numerical models for permeability validation.

Panarchy theory for convergence

Coping with surprise and uncertainty resulting from the emergence of undesired and unexpected novelty or the sudden reorganization of systems at multiple spatiotemporal scales requires both a scientific process that can incorporate diverse expertise and viewpoints, and a scientific framework that can account for the structure and dynamics of interacting social-ecological systems (SES) and the inherent uncertainty of what might emerge in the future. We argue that combining a convergence scientific process with a panarchy framework provides a pathway for improving our understanding of, and response to, emergence. Emergent phenomena are often unexpected (e.g., pandemics, regime shifts) and can be highly disruptive, so can pose a significant challenge to the development of sustainable and resilient SES. Convergence science is a new approach promoted by the U.S. National Science Foundation for tackling complex problems confronting humanity through the integration of multiple perspectives, expertise, methods, tools, and analytical approaches. Panarchy theory is a framework useful for studying emergence, because it characterizes complex systems of people and nature as dynamically organized and structured within and across scales of space and time. It accounts for the fundamental tenets of complex systems and explicitly grapples with emergence, including the emergence of novelty, and the emergent property of social-ecological resilience. We provide an overview of panarchy, convergence science, and emergence. We discuss the significant data and methodological challenges of using panarchy in a convergence approach to address emergent phenomena, as well as state-of-the-art methods for overcoming them. We present two examples that would benefit from such an approach: climate change and its impacts on social-ecological systems, and the relationships between infectious disease and social-ecological systems.

Direct competition and potential displacement involving managed Trogoderma stored product pests

The establishment of an exotic pest may require displacing local species with a similar niche. The potential of Trogoderma granarium to displace Trogoderma inclusum was explored in a stored product setting. We performed direct competition experiments varying commodity and temperature over different durations. At nine weeks T. inclusum outproduced T. granarium on all commodities at any temperature. However the proportion of T. granarium versus T. inclusum was greater at 32 °C compared to 25 °C. The nine-week production of T. granarium was best on wheat, while rice was optimal for T. inclusum. After 25 weeks, when adults were used at the start of competition, T. inclusum maintained an advantage in the direct competition. If larvae were used to initiate the competition for 25 weeks, the two species coexisted well at 25 °C, but T. granarium nearly excluded T. inclusum at 32 °C. Thus T. inclusum performs better in competition over shorter intervals when resources are plentiful, but T. granarium can be more successful over longer time periods, particularly when late instar larvae are involved. The finding suggests a real threat of introductions of T. granarium larvae to establish populations within grain storage infrastructure where T. inclusum is common.

Using machine learning to anticipate tipping points and extrapolate to post-tipping dynamics of non-stationary dynamical systems

The ability of machine learning (ML) models to "extrapolate" to situations outside of the range spanned by their training data is crucial for predicting the long-term behavior of non-stationary dynamical systems (e.g., prediction of terrestrial climate change), since the future trajectories of such systems may (perhaps after crossing a tipping point) explore regions of state space which were not explored in past time-series measurements used as training data. We investigate the extent to which ML methods can yield useful results by extrapolation of such training data in the task of forecasting non-stationary dynamics, as well as conditions under which such methods fail. In general, we find that ML can be surprisingly effective even in situations that might appear to be extremely challenging, but do (as one would expect) fail when "too much" extrapolation is required. For the latter case, we show that good results can potentially be obtained by combining the ML approach with an available inaccurate conventional model based on scientific knowledge.

Climate response and sensitivity: time scales and late tipping points

Climate response metrics are used to quantify the Earth’s climate response to anthropogenic changes of atmospheric CO 2 . Equilibrium climate sensitivity (ECS) is one such metric that measures the equilibrium response to CO 2 doubling. However, both in their estimation and their usage, such metrics make assumptions on the linearity of climate response, although it is known that, especially for larger forcing levels, response can be nonlinear. Such nonlinear responses may become visible immediately in response to a larger perturbation, or may only become apparent after a long transient period. In this paper, we illustrate some potential problems and caveats when estimating ECS from transient simulations. We highlight ways that very slow time scales may lead to poor estimation of ECS even if there is seemingly good fit to linear response over moderate time scales. Moreover, such slow processes might lead to late abrupt responses (late tipping points) associated with a system’s nonlinearities. We illustrate these ideas using simulations on a global energy balance model with dynamic albedo. We also discuss the implications for estimating ECS for global climate models, highlighting that it is likely to remain difficult to make definitive statements about the simulation times needed to reach an equilibrium.

Abrupt loss and uncertain recovery from fires of Amazon forests under low climate mitigation scenarios

Tropical forests contribute a major sink for anthropogenic carbon emissions essential to slowing down the buildup of atmospheric CO₂ and buffering climate change impacts. However, the response of tropical forests to more frequent weather extremes and long-recovery disturbances like fires remains uncertain. Analyses of field data and ecological theory raise concerns about the possibility of the Amazon crossing a tipping point leading to catastrophic tropical forest loss. In contrast, climate models consistently project an enhanced tropical sink. Here, we show a heterogeneous response of Amazonian carbon stocks in GFDL-ESM4.1, an Earth System Model (ESM) featuring dynamic disturbances and height-structured tree-grass competition. Enhanced productivity due to CO₂ fertilization promotes increases in forest biomass that, under low emission scenarios, last until the end of the century. Under high emissions, positive trends reverse after 2060, when simulated fires prompt forest loss that results in a 40% decline in tropical forest biomass by 2100. Projected fires occur under dry conditions associated with El Niño Southern Oscillation and the Atlantic Multidecadal Oscillation, a response observed under current climate conditions, but exacerbated by an overall decline in precipitation. Following the initial disturbance, grassland dominance promotes recurrent fires and tree competitive exclusion, which prevents forest recovery. EC-Earth3-Veg, an ESM with a dynamic vegetation model of similar complexity, projected comparable wildfire forest loss under high emissions but faster postfire recovery rates. Our results reveal the importance of complex nonlinear responses to assessing climate change impacts and the urgent need to research postfire recovery and its representation in ESMs.

Spatial correlation reverses the compound effect of multiple stressors on rocky shore biofilm

Understanding how multifactorial fluctuating environments affect species and communities remains one of the major challenges in ecology. The spatial configuration of the environment is known to generate complex patterns of correlation among multiple stressors. However, to what extent the spatial correlation between simultaneously fluctuating variables affects ecological assemblages in real‐world conditions remains poorly understood. Here, we use field experiments and simulations to assess the influence of spatial correlation of two relevant climate variables – warming and sediment deposition following heavy precipitation – on the biomass and photosynthetic activity of rocky intertidal biofilm. First, we used a response‐surface design experiment to establish the relation between biofilm, warming, and sediment deposition in the field. Second, we used the response surface to generate predictions of biofilm performance under different scenarios of warming and sediment correlation. Finally, we tested the predicted outcomes by manipulating the degree of correlation between the two climate variables in a second field experiment. Simulations stemming from the experimentally derived response surface showed how the degree and direction (positive or negative) of spatial correlation between warming and sediment deposition ultimately determined the nonlinear response of biofilm biomass (but not photosynthetic activity) to fluctuating levels of the two climate variables. Experimental results corroborated these predictions, probing the buffering effect of negative spatial correlation against extreme levels of warming and sediment deposition. Together, these results indicate that consideration of nonlinear response functions and local‐scale patterns of correlation between climate drivers can improve our understanding and ability to predict ecological responses to multiple processes in heterogeneous environments.

Near-term climate risks and solar radiation modification: a roadmap approach for physical sciences research

Current impacts and escalating risks of climate change require strong and decisive action to reduce greenhouse gas (GHG) emissions. They also highlight the urgency of research to enhance safety for human and natural systems, especially for those most vulnerable. This is reflected in two recent US National Academies of Science, Engineering, and Medicine studies that recommended a national focus on advancing our understanding of how to manage urgent current and future climate risks, and the study of approaches for increasing the reflection of sunlight from the atmosphere to reduce global warming, a process referred to as sunlight reflection modification (SRM). Here, we build on these recommendations by proposing a roadmap approach for the planning, coordination, and delivery of research to support a robust scientific assessment of SRM to reduce near-term climate risks in a defined timeframe. This approach is designed to support the evaluation of SRM as a possible rapid, temporary, additive measure to reduce catastrophic impacts from anthropogenic climate change, not as a substitute for aggressive GHG mitigation. Assessing SRM is proposed to be undertaken in the context of climate hazard risks through 2050, weighing the impacts associated with likely climate change trajectories against scenarios of possible SRM implementations. Provided that research is undertaken openly and that scientific resources are made widely available, the transparency of the process and the evidence generated would contribute to the democratization of information, participation by diverse stakeholders, more informed decision-making, and better opportunities for all people to weigh SRM options against climate change risks.

Exceeding 1.5°C global warming could trigger multiple climate tipping points

Climate tipping points occur when change in a part of the climate system becomes self-perpetuating beyond a warming threshold, leading to substantial Earth system impacts. Synthesizing paleoclimate, observational, and model-based studies, we provide a revised shortlist of global "core" tipping elements and regional "impact" tipping elements and their temperature thresholds. Current global warming of ~1.1°C above preindustrial temperatures already lies within the lower end of some tipping point uncertainty ranges. Several tipping points may be triggered in the Paris Agreement range of 1.5 to <2°C global warming, with many more likely at the 2 to 3°C of warming expected on current policy trajectories. This strengthens the evidence base for urgent action to mitigate climate change and to develop improved tipping point risk assessment, early warning capability, and adaptation strategies.

Destabilisation of the Subpolar North Atlantic prior to the Little Ice Age

The cooling transition into the Little Ice Age was the last notable shift in the climate system prior to anthropogenic global warming. It is hypothesised that sea-ice to ocean feedbacks sustained an initial cooling into the Little Ice Age by weakening the subpolar gyre circulation; a system that has been proposed to exhibit bistability. Empirical evidence for bistability within this transition has however been lacking. Using statistical indicators of resilience in three annually-resolved bivalve proxy records from the North Icelandic shelf, we show that the subpolar North Atlantic climate system destabilised during two episodes prior to the Little Ice Age. This loss of resilience indicates reduced attraction to one stable state, and a system vulnerable to an abrupt transition. The two episodes preceded wider subpolar North Atlantic change, consistent with subpolar gyre destabilisation and the approach of a tipping point, potentially heralding the transition to Little Ice Age conditions.

Bivalves reveal that the subpolar North Atlantic destabilised and shows signs of having crossed a tipping point during the transition into the Little Ice Age.

Climate drives coupled regime shifts across subtropical estuarine ecosystems

Ecological regime shifts are expected to increase this century as climate change propagates cascading effects across ecosystems with coupled elements. Here, we demonstrate that the climate-driven salt marsh-to-mangrove transition does not occur in isolation but is linked to lesser-known oyster reef-to-mangrove regime shifts through the provision of mangrove propagules. Using aerial imagery spanning 82 y, we found that 83% of oyster reefs without any initial mangrove cover fully converted to mangrove islands and that mean (± SD) time to conversion was 29.1 ± 9.6 y. In situ assessments of mangrove islands suggest substantial changes in ecosystem structure during conversion, while radiocarbon dates of underlying reef formation indicate that such transitions are abrupt relative to centuries-old reefs. Rapid transition occurred following release from freezes below the red mangrove (Rhizophora mangle) physiological tolerance limit (-7.3 °C) and after adjacent marsh-to-mangrove conversion. Additional nonclimate-mediated drivers of ecosystem change were also identified, including oyster reef exposure to wind-driven waves. Coupling of regime shifts arises from the growing supply of mangrove propagules from preceding and adjacent marsh-to-mangrove conversion. Climate projections near the mangrove range limit on the Gulf coast of Florida suggest that regime shifts will begin to transform subtropical estuaries by 2070 if propagule supply keeps pace with predicted warming. Although it will become increasingly difficult to maintain extant oyster habitat with tropicalization, restoring oyster reefs in high-exposure settings or active removal of mangrove seedlings could slow the coupled impacts of climate change shown here.

A limit on the evolutionary rescue of an Antarctic bacterium from rising temperatures

Climate change is gradual, but it can also cause brief extreme heat waves that can exceed the upper thermal limit of any one organism. To study the evolutionary potential of upper thermal tolerance, we evolved the cold-adapted Antarctic bacterium Pseudoalteromonas haloplanktis to survive at 30°C, beyond its ancestral thermal limit. This high-temperature adaptation occurred rapidly and in multiple populations. It involved genomic changes that occurred in a highly parallel fashion and mitigated the effects of protein misfolding. However, it also confronted a physiological limit, because populations failed to grow beyond 30°C. Our experiments aimed to facilitate evolutionary rescue by using a small organism with large populations living at temperatures several degrees below their upper thermal limit. Larger organisms with smaller populations and living at temperatures closer to their upper thermal tolerances are even more likely to go extinct during extreme heat waves.

Analysing Historical and Modelling Future Soil Temperature at Kuujjuaq, Quebec (Canada): Implications on Aviation Infrastructure

The impact of climate change on soil temperatures at Kuujjuaq, Quebec in northern Canada is assessed. First, long-term historical soil temperature records (1967–1995) are statistically analyzed to provide a climatological baseline for soils at 5 to 150 cm depths. Next, the nature of the relationship between atmospheric variables and soil temperature are determined using a statistical downscaling model (SDSM) and National Centers for Environmental Prediction (NCEP), a climatological data set. SDSM was found to replicate historic soil temperatures well and used to project soil temperatures for the remainder of the century using climate model output Canadian Second Generation Earth System Model (CanESM2). Three Representative Concentration Pathway scenarios (RCP 2.6, 4.5 and 8.5) were used from the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). This study found that the soil temperature at this location may warm at 0.9 to 1.2 °C per decade at various depths. Annual soil temperatures at all depths are projected to rise to above 0 °C for the 1997–2026 period for all climate scenarios. The melting soil poses a hazard to the airport infrastructure and will require adaptation measures.

Climate change research and action must look beyond 2100

Anthropogenic activity is changing Earth's climate and ecosystems in ways that are potentially dangerous and disruptive to humans. Greenhouse gas concentrations in the atmosphere continue to rise, ensuring that these changes will be felt for centuries beyond 2100, the current benchmark for projection. Estimating the effects of past, current, and potential future emissions to only 2100 is therefore short-sighted. Critical problems for food production and climate-forced human migration are projected to arise well before 2100, raising questions regarding the habitability of some regions of the Earth after the turn of the century. To highlight the need for more distant horizon scanning, we model climate change to 2500 under a suite of emission scenarios and quantify associated projections of crop viability and heat stress. Together, our projections show global climate impacts increase significantly after 2100 without rapid mitigation. As a result, we argue that projections of climate and its effects on human well-being and associated governance and policy must be framed beyond 2100.

Investigating climate tipping points under various emission reduction and carbon capture scenarios with a stochastic climate model

We study the mitigation of climate tipping point transitions using an energy balance model. The evolution of the global mean surface temperature is coupled with the CO 2 concentration through the green-house effect. We model the CO 2 concentration with a stochastic delay differential equation (SDDE), accounting for various carbon emission and capture scenarios. The resulting coupled system of SDDEs exhibits a tipping point phenomena: if CO 2 concentration exceeds a critical threshold (around 478   ppm ), the temperature experiences an abrupt increase of about six degrees Celsius. We show that the CO 2 concentration exhibits a transient growth which may cause a climate tipping point, even if the concentration decays asymptotically. We derive a rigorous upper bound for the CO 2 evolution which quantifies its transient and asymptotic growths, and provides sufficient conditions for evading the climate tipping point. Combining this upper bound with Monte Carlo simulations of the stochastic climate model, we investigate the emission reduction and carbon capture scenarios that would avert the tipping point.

Adaptive Evolution Can Both Prevent Ecosystem Collapse and Delay Ecosystem Recovery

AbstractThere is growing concern about the dire socioecological consequences of abrupt transitions between alternative ecosystem states in response to environmental changes. At the same time, environmental change can trigger evolutionary responses that could stabilize or destabilize ecosystem dynamics. However, we know little about how coupled ecological and evolutionary processes affect the risk of transition between alternative ecosystem states. Using shallow lakes as a model ecosystem, we investigate how trait evolution of a key species affects ecosystem resilience under environmental stress. We find that adaptive evolution of macrophytes can increase ecosystem resilience by shifting the critical threshold, which marks the transition from a clear-water state to a turbid-water state to a higher level of environmental stress. However, following the transition, adaptation to the turbid-water state can delay the ecosystem recovery back to the clear-water state. This implies that restoration could be more effective when implemented early enough after a transition occurs and before organisms adapt to the alternative state. Our findings provide new insights into how to prevent and mitigate the occurrence of regime shifts in ecosystems and highlight the need to understand ecosystem responses to environmental change in the context of coupled ecological and evolutionary processes.

Paleoclimate-conditioning reveals a North Africa land-atmosphere tipping point

While paleoclimate records show that the Earth System is characterized by several different tipping points, their representation within Earth System models (ESMs) remains poorly constrained. This is because historical observations do not encompass variations large enough to provoke such regime changes, and paleoclimate conditions are rarely used to help develop and tune ESMs, which potentially ignores a rich source of information on abrupt climate change. A critical example is the early to mid-Holocene "greening" and subsequent rapid desertification of the Sahara, which most ESMs fail to reproduce, casting doubt on the representation of land-atmosphere coupling and monsoon dynamics. Here, we show that this greening and abrupt termination can be successfully simulated with one ESM after optimizing uncertain model components using both present-day observations and crucially mid-Holocene (6,000 y before present) reconstructions. The optimized model displays abrupt threshold behavior, which shows excellent agreement with long paleoclimate records that were not used in the original optimization. These results suggest that in order to realistically capture climate-system thresholds, ESMs first need to be conditioned with appropriate paleoclimate information.

Evasion of tipping in complex systems through spatial pattern formation

[Figure: see text].

Insects and their pathogens in a changing climate

The complex nature of climate change-mediated multitrophic interaction is an underexplored area, but has the potential to dramatically shift transmission and distribution of many insects and their pathogens, placing some populations closer to the brink of extinction. However, for individual insect-pathogen interactions climate change will have complicated hard-to-anticipate impacts. Thus, both pathogen virulence and insect host immunity are intrinsically linked with generalized stress responses, and in both pathogen and host have extensive trade-offs with nutrition (e.g., host plant quality), growth and reproduction. Potentially alleviating or exasperating these impacts, some pathogens and hosts respond genetically and rapidly to environmental shifts. This review identifies many areas for future research including a particular need to identify how altered global warming interacts with other environmental changes and stressors, and how consistent these impacts are across pathogens and hosts. With that achieved we would be closer to producing an overarching framework to integrate knowledge on all environmental interplay and infectious disease events.

Subpolar North Atlantic western boundary density anomalies and the Meridional Overturning Circulation

Changes in the Atlantic Meridional Overturning Circulation, which have the potential to drive societally-important climate impacts, have traditionally been linked to the strength of deep water formation in the subpolar North Atlantic. Yet there is neither clear observational evidence nor agreement among models about how changes in deep water formation influence overturning. Here, we use data from a trans-basin mooring array (OSNAP-Overturning in the Subpolar North Atlantic Program) to show that winter convection during 2014-2018 in the interior basin had minimal impact on density changes in the deep western boundary currents in the subpolar basins. Contrary to previous modeling studies, we find no discernable relationship between western boundary changes and subpolar overturning variability over the observational time scales. Our results require a reconsideration of the notion of deep western boundary changes representing overturning characteristics, with implications for constraining the source of overturning variability within and downstream of the subpolar region.

Overshooting tipping point thresholds in a changing climate

Palaeorecords suggest that the climate system has tipping points, where small changes in forcing cause substantial and irreversible alteration to Earth system components called tipping elements. As atmospheric greenhouse gas concentrations continue to rise as a result of fossil fuel burning, human activity could also trigger tipping, and the impacts would be difficult to adapt to. Previous studies report low global warming thresholds above pre-industrial conditions for key tipping elements such as ice-sheet melt. If so, high contemporary rates of warming imply that exceeding these thresholds is almost inevitable, which is widely assumed to mean that we are now committed to suffering these tipping events. Here we show that this assumption may be flawed, especially for slow-onset tipping elements (such as the collapse of the Atlantic Meridional Overturning Circulation) in our rapidly changing climate. Recently developed theory indicates that a threshold may be temporarily exceeded without prompting a change of system state, if the overshoot time is short compared to the effective timescale of the tipping element. To demonstrate this, we consider transparently simple models of tipping elements with prescribed thresholds, driven by global warming trajectories that peak before returning to stabilize at a global warming level of 1.5 degrees Celsius above the pre-industrial level. These results highlight the importance of accounting for timescales when assessing risks associated with overshooting tipping point thresholds.

Risk of tipping the overturning circulation due to increasing rates of ice melt

Central elements of the climate system are at risk for crossing critical thresholds (so-called tipping points) due to future greenhouse gas emissions, leading to an abrupt transition to a qualitatively different climate with potentially catastrophic consequences. Tipping points are often associated with bifurcations, where a previously stable system state loses stability when a system parameter is increased above a well-defined critical value. However, in some cases such transitions can occur even before a parameter threshold is crossed, given that the parameter change is fast enough. It is not known whether this is the case in high-dimensional, complex systems like a state-of-the-art climate model or the real climate system. Using a global ocean model subject to freshwater forcing, we show that a collapse of the Atlantic Meridional Overturning Circulation can indeed be induced even by small-amplitude changes in the forcing, if the rate of change is fast enough. Identifying the location of critical thresholds in climate subsystems by slowly changing system parameters has been a core focus in assessing risks of abrupt climate change. This study suggests that such thresholds might not be relevant in practice, if parameter changes are not slow. Furthermore, we show that due to the chaotic dynamics of complex systems there is no well-defined critical rate of parameter change, which severely limits the predictability of the qualitative long-term behavior. The results show that the safe operating space of elements of the Earth system with respect to future emissions might be smaller than previously thought.

Multiple Climate Tipping Points Metrics for Improved Sustainability Assessment of Products and Services

Mounting evidence indicates that climate tipping points can have large, potentially irreversible, impacts on the earth system and human societies. Yet, climate change metrics applied in current sustainability assessment methods generally do not consider these tipping points, with the use of arbitrarily determined time horizons and assumptions that the climate impact of a product or service is independent of emission timing. Here, we propose a new method for calculating climate tipping characterization factors for greenhouse gases (carbon dioxide, methane, and nitrous oxide) at midpoint. It covers 13 projected tipping points, incorporates the effect that the crossing of a given tipping point has on accelerating the crossing of other tipping points, and addresses uncertainties in the temperature thresholds that trigger the tipping points. To demonstrate the added value of the new metric, we apply it to emissions stemming from end-of-life of plastic polymers and compare them with commonly used metrics. This highlights the need to consider climate tipping in sustainability assessment of products and services.

Noise-induced transitions of the Atlantic Meridional Overturning Circulation in CMIP5 models

By studying transition probabilities of the Atlantic Meridional Overturning Circulation (AMOC) in an ensemble of CMIP5 climate models, we revisit one of the stability indicators of the AMOC, i.e. the freshwater transport carried by the AMOC at the southern boundary of the Atlantic basin. A correction to this indicator, based on the transition probabilities, is suggested to measure whether an AMOC state is in a multiple equilibrium regime or not. As a consequence, the AMOC of all CMIP5 models considered is in a multiple equilibrium regime and hence, in principle, a collapsed AMOC state should exist in each of these models. The results further demonstrate the dependence of the Atlantic surface freshwater flux on the AMOC and the impact of extreme events in the AMOC on temperatures in the North Atlantic region.

An extreme cold event leads to community-wide convergence in lower temperature tolerance in a lizard community

Extreme climate events are predicted to increase in frequency and severity due to contemporary climate change. Recent studies have documented the evolutionary impacts of extreme events on single species, but no studies have yet investigated whether such events can drive community-wide patterns of trait shifts. On 22 January 2020, subtropical south Florida experienced an extreme cold episode during which air temperatures dropped below the lower thermal limit of resident lizard populations. In the week immediately after the cold event, we documented decreased lower thermal limits (CTmin) of six co-occurring lizard species that vary widely in ecology, body size and thermal physiology. Although cold tolerance of these species differed significantly before the cold snap, lizards sampled immediately after had converged on the same new, lower limit of thermal tolerance. Here, we demonstrate that extreme climate events can drive substantial and synchronous community-wide trait changes and provide evidence that tropical and subtropical ectotherms-often characterized as unable to withstand rapid changes in climatic conditions-can endure climatic conditions that exceed their physiological limits. Future studies investigating the mechanisms driving these trait shifts will prove valuable in understanding the ability of ectotherm communities to mitigate climate change.

A Warm, Stratified, and Restricted Labrador Sea Across the Middle Eocene and Its Climatic Optimum

Several studies indicate that North Atlantic Deep Water (NADW) formation might have initiated during the globally warm Eocene (56-34 Ma). However, constraints on Eocene surface ocean conditions in source regions presently conducive to deep water formation are sparse. Here we test whether ocean conditions of the middle Eocene Labrador Sea might have allowed for deep water formation by applying (organic) geochemical and palynological techniques, on sediments from Ocean Drilling Program (ODP) Site 647. We reconstruct a long-term sea surface temperature (SST) drop from ~30°C to ~27°C between 41.5 to 38.5 Ma, based on TEX86. Superimposed on this trend, we record ~2°C warming in SST associated with the Middle Eocene Climatic Optimum (MECO; ~40 Ma), which is the northernmost MECO record as yet, and another, likely regional, warming phase at ~41.1 Ma, associated with low-latitude planktic foraminifera and dinoflagellate cyst incursions. Dinoflagellate cyst assemblages together with planktonic foraminiferal stable oxygen isotope ratios overall indicate low surface water salinities and strong stratification. Benthic foraminifer stable carbon and oxygen isotope ratios differ from global deep ocean values by 1-2‰ and 2-4‰, respectively, indicating geographic basin isolation. Our multiproxy reconstructions depict a consistent picture of relatively warm and fresh but also highly variable surface ocean conditions in the middle Eocene Labrador Sea. These conditions were unlikely conducive to deep water formation. This implies either NADW did not yet form during the middle Eocene or it formed in a different source region and subsequently bypassed the southern Labrador Sea.

Allometric constraints and competition enable the simulation of size structure and carbon fluxes in a dynamic vegetation model of tropical forests (LM3PPA-TV)

Tropical forests are a key determinant of the functioning of the Earth system, but remain a major source of uncertainty in carbon cycle models and climate change projections. In this study, we present an updated land model (LM3PPA-TV) to improve the representation of tropical forest structure and dynamics in Earth system models (ESMs). The development and parameterization of LM3PPA-TV drew on extensive datasets on tropical tree traits and long-term field censuses from Barro Colorado Island (BCI), Panama. The model defines a new plant functional type (PFT) based on the characteristics of shade-tolerant, tropical tree species, implements a new growth allocation scheme based on realistic tree allometries, incorporates hydraulic constraints on biomass accumulation, and features a new compartment for tree branches and branch fall dynamics. Simulation experiments reproduced observed diurnal and seasonal patterns in stand-level carbon and water fluxes, as well as mean canopy and understory tree growth rates, tree size distributions, and stand-level biomass on BCI. Simulations at multiple sites captured considerable variation in biomass and size structure across the tropical forest biome, including observed responses to precipitation and temperature. Model experiments suggested a major role of water limitation in controlling geographic variation forest biomass and structure. However, the failure to simulate tropical forests under extreme conditions and the systematic underestimation of forest biomass in Paleotropical locations highlighted the need to incorporate variation in hydraulic traits and multiple PFTs that capture the distinct floristic composition across tropical domains. The continued pressure on tropical forests from global change demands models which are able to simulate alternative successional pathways and their pace to recovery. LM3PPA-TV provides a tool to investigate geographic variation in tropical forests and a benchmark to continue improving the representation of tropical forests dynamics and their carbon storage potential in ESMs.

Abrupt changes in Great Britain vegetation carbon projected under climate change

Past abrupt 'regime shifts' have been observed in a range of ecosystems due to various forcing factors. Large-scale abrupt shifts are projected for some terrestrial ecosystems under climate change, particularly in tropical and high-latitude regions. However, there is very little high-resolution modelling of smaller-scale future projected abrupt shifts in ecosystems, and relatively less focus on the potential for abrupt shifts in temperate terrestrial ecosystems. Here, we show that numerous climate-driven abrupt shifts in vegetation carbon are projected in a high-resolution model of Great Britain's land surface driven by two different climate change scenarios. In each scenario, the effects of climate and CO₂ combined are isolated from the effects of climate change alone. We use a new algorithm to detect and classify abrupt shifts in model time series, assessing the sign and strength of the non-linear responses. The abrupt ecosystem changes projected are non-linear responses to climate change, not simply driven by abrupt shifts in climate. Depending on the scenario, 374-1,144 grid cells of 1.5 km × 1.5 km each, comprising 0.5%-1.5% of Great Britain's land area show abrupt shifts in vegetation carbon. We find that abrupt ecosystem shifts associated with increases (rather than decreases) in vegetation carbon, show the greatest potential for early warning signals (rising autocorrelation and variance beforehand). In one scenario, 89% of abrupt increases in vegetation carbon show increasing autocorrelation and variance beforehand. Across the scenarios, 81% of abrupt increases in vegetation carbon have increasing autocorrelation and 74% increasing variance beforehand, whereas for decreases in vegetation carbon these figures are 56% and 47% respectively. Our results should not be taken as specific spatial or temporal predictions of abrupt ecosystem change. However, they serve to illustrate that numerous abrupt shifts in temperate terrestrial ecosystems could occur in a changing climate, with some early warning signals detectable beforehand.

Flickering of cardiac state before the onset and termination of atrial fibrillation

Complex dynamical systems can shift abruptly from a stable state to an alternative stable state at a tipping point. Before the critical transition, the system either slows down in its recovery rate or flickers between the basins of attraction of the alternative stable states. Whether the heart critically slows down or flickers before it transitions into and out of paroxysmal atrial fibrillation (PAF) is still an open question. To address this issue, we propose a novel definition of cardiac states based on beat-to-beat (RR) interval fluctuations derived from electrocardiogram data. Our results show the cardiac state flickers before PAF onset and termination. Prior to onset, flickering is due to a "tug-of-war" between the sinus node (the natural pacemaker) and atrial ectopic focus/foci (abnormal pacemakers), or the pacing by the latter interspersed among the pacing by the former. It may also be due to an abnormal autonomic modulation of the sinus node. This abnormal modulation may be the sole cause of flickering prior to termination since atrial ectopic beats are absent. Flickering of the cardiac state could potentially be used as part of an early warning or screening system for PAF and guide the development of new methods to prevent or terminate PAF. The method we have developed to define system states and use them to detect flickering can be adapted to study critical transition in other complex systems.

Tipping positive change

Tipping points exist in social, ecological and climate systems and those systems are increasingly causally intertwined in the Anthropocene. Climate change and biosphere degradation have advanced to the point where we are already triggering damaging environmental tipping points, and to avoid worse ones ahead will require finding and triggering positive tipping points towards sustainability in coupled social, ecological and technological systems. To help with that I outline how tipping points can occur in continuous dynamical systems and in networks, the causal interactions that can occur between tipping events across different types and scales of system-including the conditions required to trigger tipping cascades, the potential for early warning signals of tipping points, and how they could inform deliberate tipping of positive change. In particular, the same methods that can provide early warning of damaging environmental tipping points can be used to detect when a socio-technical or socio-ecological system is most sensitive to being deliberately tipped in a desirable direction. I provide some example targets for such deliberate tipping of positive change. This article is part of the theme issue 'Climate change and ecosystems: threats, opportunities and solutions'.

Regime shifts occur disproportionately faster in larger ecosystems

Regime shifts can abruptly affect hydrological, climatic and terrestrial systems, leading to degraded ecosystems and impoverished societies. While the frequency of regime shifts is predicted to increase, the fundamental relationships between the spatial-temporal scales of shifts and their underlying mechanisms are poorly understood. Here we analyse empirical data from terrestrial (n = 4), marine (n = 25) and freshwater (n = 13) environments and show positive sub-linear empirical relationships between the size and shift duration of systems. Each additional unit area of an ecosystem provides an increasingly smaller unit of time taken for that system to collapse, meaning that large systems tend to shift more slowly than small systems but disproportionately faster. We substantiate these findings with five computational models that reveal the importance of system structure in controlling shift duration. The findings imply that shifts in Earth ecosystems occur over 'human' timescales of years and decades, meaning the collapse of large vulnerable ecosystems, such as the Amazon rainforest and Caribbean coral reefs, may take only a few decades once triggered.

Addressing Environmental Change through Emergent Integrated Environmental Observatories: A Case Study in the Czech Republic

A growing body of scientific evidence indicates that we have entered the Anthropocene Epoch. Many assert that society has exceeded sustainable ecological planetary boundaries and that altered biogeophysical processes are no longer reversible to natural rates of ecosystem functioning. To properly and successfully address societal needs for the future, more holistic and complex methods need to be applied at various spatial and temporal scales. The increasingly interconnected nature of human and natural environments—from individuals to large megacities and entire continents and from cells through ecosystems to the biosphere as a whole (e.g., as seen in the carbon cycle)—demand new and often interdisciplinary and international approaches to address emerging global challenges. With that perspective in mind, the Czech Republic’s National Climate Program was established in 1991 with the aim to understand the impact of global environmental change on society. The National Climate Program was updated in 2017 to formulate a new Climate Protection Policy. Here, we outline the multifaceted problems that climate change poses for the Czech Republic, as well as a new scientific infrastructure and approaches directed to better understanding the effects of climate change on our ecosystems, water resources, urban environment, agriculture, human health, and general economy.

Ecological changes with minor effect initiate evolution to delayed regime shifts

Regime shifts have been documented in a variety of natural and social systems. These abrupt transitions produce dramatic shifts in the composition and functioning of socioecological systems. Existing theory on ecosystem resilience has only considered regime shifts to be caused by changes in external conditions beyond a tipping point and therefore lacks an evolutionary perspective. In this study, we show how a change in external conditions has little ecological effect and does not push the system beyond a tipping point. The change therefore does not cause an immediate regime shift but instead triggers an evolutionary process that drives a phenotypic trait beyond a tipping point, thereby resulting (after a substantial delay) in a selection-induced regime shift. Our finding draws attention to the fact that regime shifts observed in the present may result from changes in the distant past, and highlights the need for integrating evolutionary dynamics into the theoretical foundation for ecosystem resilience.

A new statistical downscaling approach for global evaluation of the CMIP5 precipitation outputs: Model development and application

Outputs of the Coupled Model Intercomparison Project Phase 5 (CMIP5) models have been widely used in studies of climate changes related to scenarios at global and regional scales. However, CMIP5 outputs cannot be used directly in analysis of climate changes due to coarse spatial resolution. Here, we proposed a new statistical downscaling method for the downscaling practice of the CMIP5 outputs, i.e. Bias-corrected and station-based Non-linear Regression Downscaling method based on Randomly-Moving Points (BNRD). And up to now, there are only two global downscaled CMIP5 precipitation datasets, i.e. NASA daily downscaled CMIP5 precipitation product and BCSD-based (Bias Correction Spatial Disaggregation) monthly downscaled CMIP5 precipitation product available online, which are both based on BCSD downscaling method. Hence, we evaluated downscaling performance of BNRD by comparing it with the downscaled CMIP5 outputs using the BCSD method in this current study. The results indicate that: (1) during the period for development of the model (1964-2005), the error between downscaled CMIP5 precipitation and GPCC ranges between -50 mm-50 mm at monthly scale. When compared to BCSD-downscaled CMIP5 precipitation, BNRD-downscaled CMIP5 precipitation well reduces errors and avoids underestimation and overestimation of GPCC by BCSD-downscaled CMIP5 precipitation; (2) during period for verification of the downscaling models (2006-2013), the maximum (182 mm), minimum (15 mm) and average (68 mm) RMSEs between BNRD-downscaled CMIP5 precipitation and GPCC are all lower than those between BCSD-downscaled CMIP5 precipitation and GPCC at continental scales. Besides, from the average precipitation viewpoint, BNRD-downscaled CMIP5 precipitation is in higher correlation (around 0.75) with GPCC than BCSD-downscaled CMIP5 precipitation under RCP4.5 and RCP8.5 scenarios at continental scales; (3) BNRD resolved the negative relation to GPCC in the areas near equator, including north part of the South America, southern Africa, northern Australia. In all, BNRD downscaling method developed in this study performs better in describing GPCC changes in both space and time when compared to BCSD and can be used for downscaling practice of CMIP5 and even potentially CMIP6 precipitation outputs over the globe.

Cascading regime shifts within and across scales

Regime shifts are large, abrupt, and persistent critical transitions in the function and structure of ecosystems. Yet, it is unknown how these transitions will interact, whether the occurrence of one will increase the likelihood of another or simply correlate at distant places. We explored two types of cascading effects: Domino effects create one-way dependencies, whereas hidden feedbacks produce two-way interactions. We compare them with the control case of driver sharing, which can induce correlations. Using 30 regime shifts described as networks, we show that 45% of regime shift pairwise combinations present at least one plausible structural interdependence. The likelihood of cascading effects depends on cross-scale interactions but differs for each type. Management of regime shifts should account for potential connections.

The Trajectory Towards a Seasonally Ice-Free Arctic Ocean

PURPOSE OF REVIEW

The observed substantial loss of Arctic sea ice has raised prospects of a seasonally ice-free Arctic Ocean within the foreseeable future. In this review, we summarize our current understanding of the most likely trajectory of the Arctic sea-ice cover towards this state.

RECENT FINDINGS

The future trajectory of the Arctic sea-ice cover can be described through a deterministic component arising primarily from future greenhouse gas emissions, and a chaotic component arising from internal variability. The deterministic component is expected to cause a largely ice-free Arctic Ocean during summer for less than 2 ^∘C global warming relative to pre-industrial levels. To keep chances below 5 % that the Arctic Ocean will largely be ice free in a given year, total future CO₂ emissions must remain below 500 Gt.

SUMMARY

The Arctic Ocean will become ice free during summer before mid-century unless greenhouse gas emissions are rapidly reduced.

Trajectories of the Earth System in the Anthropocene

We explore the risk that self-reinforcing feedbacks could push the Earth System toward a planetary threshold that, if crossed, could prevent stabilization of the climate at intermediate temperature rises and cause continued warming on a "Hothouse Earth" pathway even as human emissions are reduced. Crossing the threshold would lead to a much higher global average temperature than any interglacial in the past 1.2 million years and to sea levels significantly higher than at any time in the Holocene. We examine the evidence that such a threshold might exist and where it might be. If the threshold is crossed, the resulting trajectory would likely cause serious disruptions to ecosystems, society, and economies. Collective human action is required to steer the Earth System away from a potential threshold and stabilize it in a habitable interglacial-like state. Such action entails stewardship of the entire Earth System-biosphere, climate, and societies-and could include decarbonization of the global economy, enhancement of biosphere carbon sinks, behavioral changes, technological innovations, new governance arrangements, and transformed social values.

Choosing the future of Antarctica

We present two narratives on the future of Antarctica and the Southern Ocean, from the perspective of an observer looking back from 2070. In the first scenario, greenhouse gas emissions remained unchecked, the climate continued to warm, and the policy response was ineffective; this had large ramifications in Antarctica and the Southern Ocean, with worldwide impacts. In the second scenario, ambitious action was taken to limit greenhouse gas emissions and to establish policies that reduced anthropogenic pressure on the environment, slowing the rate of change in Antarctica. Choices made in the next decade will determine what trajectory is realized.

Realized niche analysis of phytoplankton communities involving HAB: Phaeocystis spp. as a case study

The link between harmful algal blooms, phytoplankton community dynamics and global environmental change is not well understood. To tackle this challenging question, a new method was used to reveal how phytoplankton communities responded to environmental change with the occurrence of an harmful algae, using the coastal waters of the eastern English Channel as a case study. The great interannual variability in the magnitude and intensity of Phaeocystis spp. blooms, along with diatoms, compared to the ongoing gradual decrease in anthropogenic nutrient concentration and rebalancing of nutrient ratios; suggests that other factors, such as competition for resources, may also play an important role. A realized niche approach was used with the Outlying Mean Index analysis and the dynamics of the species' realized subniches were estimated using the Within Outlying Mean Indexes calculations under low (L) and high (H) contrasting Phaeocystis spp. abundance. The Within Outlying Mean Indexes allows the decomposition of the realized niche into realized subniches, found within the subset of habitat conditions and constrained by a subset of a biotic factor. The two contrasting scenarios were characterized by significantly different subsets of environmental conditions and diatom species (BV-step analysis), and different seasonality in salinity, turbidity, and nutrients. The subset L environmental conditions were potentially favorable for Phaeocystis spp. but it suffered from competitive exclusion by key diatom species such as Skeletonema spp., Thalassiosira gravida, Thalassionema nitzschioides and the Pseudo-nitzchia seriata complex. Accordingly, these diatoms species occupied 81% of Phaeocystis spp.'s existing fundamental subniche. In contrast, the greater number of diatoms, correlated with the community trend, within subset H exerted a weaker biological constraint and favored Phaeocystis spp. realized subniche expansion. In conclusion, the results strongly suggest that both abiotic and biotic interactions should be considered to understand Phaeocystis spp. blooms with greater consideration of the preceeding diatoms. HABs needs must therefore be studied as part of the total phytoplankton community.

Projecting temperature-related years of life lost under different climate change scenarios in one temperate megacity, China

Temperature has been associated with population health, but few studies have projected the future temperature-related years of life lost attributable to climate change. To project future temperature-related disease burden in Tianjin, we selected years of life lost (YLL) as the dependent variable to explore YLL attributable to climate change. A generalized linear model (GLM) and distributed lag non-linear model were combined to assess the non-linear and delayed effects of temperature on the YLL of non-accidental mortality. Then, we calculated the YLL changes attributable to future climate scenarios in 2055 and 2090. The relationships of daily mean temperature with the YLL of non-accident mortality were basically U-shaped. Both the daily mean temperature increase on high-temperature days and its drop on low-temperature days caused an increase of YLL and non-accidental deaths. The temperature-related YLL will worsen if future climate change exceeds 2 °C. In addition, the adverse effects of extreme temperature on YLL occurred more quickly than that of the overall temperature. The impact of low temperature was greater than that of high temperature. Men were vulnerable to high temperature compared with women. This analysis highlights that the government should formulate environmental policies to reach the Paris Agreement goal.

Comparing Climate Sensitivity, Past and Present

Climate sensitivity represents the global mean temperature change caused by changes in the radiative balance of climate; it is studied for both present/future (actuo) and past (paleo) climate variations, with the former based on instrumental records and/or various types of model simulations. Paleo-estimates are often considered informative for assessments of actuo-climate change caused by anthropogenic greenhouse forcing, but this utility remains debated because of concerns about the impacts of uncertainties, assumptions, and incomplete knowledge about controlling mechanisms in the dynamic climate system, with its multiple interacting feedbacks and their potential dependence on the climate background state. This is exacerbated by the need to assess actuo- and paleoclimate sensitivity over different timescales, with different drivers, and with different (data and/or model) limitations. Here, we visualize these impacts with idealized representations that graphically illustrate the nature of time-dependent actuo- and paleoclimate sensitivity estimates, evaluating the strengths, weaknesses, agreements, and differences of the two approaches. We also highlight priorities for future research to improve the use of paleo-estimates in evaluations of current climate change.