Critical slowing down as early warning for the onset of collapse in mutualistic communities

Tipping points are crossed when small changes in external conditions cause abrupt unexpected responses in the current state of a system. In the case of ecological communities under stress, the risk of approaching a tipping point is unknown, but its stakes are high. Here, we test recently developed critical slowing-down indicators as early-warning signals for detecting the proximity to a potential tipping point in structurally complex ecological communities. We use the structure of 79 empirical mutualistic networks to simulate a scenario of gradual environmental change that leads to an abrupt first extinction event followed by a sequence of species losses until the point of complete community collapse. We find that critical slowing-down indicators derived from time series of biomasses measured at the species and community level signal the proximity to the onset of community collapse. In particular, we identify specialist species as likely the best-indicator species for monitoring the proximity of a community to collapse. In addition, trends in slowing-down indicators are strongly correlated to the timing of species extinctions. This correlation offers a promising way for mapping species resilience and ranking species risk to extinction in a given community. Our findings pave the road for combining theory on tipping points with patterns of network structure that might prove useful for the management of a broad class of ecological networks under global environmental change.Systems as complex as the climate (1), financial markets (2), or ecosystems (3) have experienced tipping points in the past and may do so in the future. Tipping points are crossed when small changes in external conditions trigger the sudden collapse of a system to an undesirable state that is usually difficult to reverse. For example, the shutdown of the thermohaline circulation in the North Atlantic (4), or the occasional switches of shallow lakes from clear to turbid waters (5) are examples of sudden transitions that might have been caused by gradual changes in external conditions. It is this “small changes can have big effects” pattern that makes tipping points important to study but notoriously difficult to detect. Nonetheless, recent work has suggested that the possibility of detecting nearby tipping points may not be that distant (6).According to theory, before tipping points, systems tend to recover slowly back to equilibrium upon a random disturbance (7). This phenomenon of “critical slowing down” appears to be generic for a wide class of local bifurcations (8), at which the current equilibrium state of a system loses stability before being replaced by another equilibrium state. Critical slowing down may be captured by two simple statistical signals in the dynamics of complex systems (6): increasing variance and rising correlation. These signals can be used to indicate the proximity of a system to a tipping point and are suggested to serve as indicators of loss of resilience, or, more broadly, as early-warning signals for the impending transition (6). Critical slowing-down indicators (CSD indicators hereafter) have been experimentally shown to detect abrupt transitions between alternative states in yeast cultures (9), plankton chemostats (10), zooplankton populations (11), or even whole lake communities (12). However, these indicators have been mostly studied in systems with single populations or few aggregated components that lack the complexity that characterizes structurally heterogeneous systems of interacting species, such as ecological networks.Although ecological networks have been experiencing an increasing amount of anthropogenic pressures, it is still unclear how strongly they may respond to this stress. Responses might range from local extinctions and species distribution shifts (13) to whole community reorganization and massive biodiversity losses (14). In the best-case scenarios, these responses will be gradual, predictable, or even reversible. However, little is known on whether ecological networks could also respond in abrupt and unexpected ways (15). Theoretical work shows that gradual environmental change in mutualistic communities may have different effects on species tolerance to stress, but the path to extinction appears to be gradual (16). Only recently, it has been suggested that strongly nested mutualistic networks may run a high risk of experiencing a tipping point (17). For these latter cases, the challenge is to detect whether they are approaching a tipping point in advance.Here, we explore whether we can detect tipping points in structurally diverse ecological networks with CSD indicators. We used the structure of 79 mutualistic communities reconstructed from empirical plant–pollinator and plant seed–disperser networks to simulate dynamical scenarios of gradual environmental change that lead to species loss and community-wide collapses. We demonstrate that CSD indicators derived from monitoring biomasses at the species and community level may signal the proximity to the onset of community collapse. We investigate how species structural traits influence the predictive performance of the indicators at the species level. Last, we suggest that species-level indicators may be used to rank species risk to extinction even before the onset of community collapse. Despite the challenge of identifying these patterns in empirical dynamics of observed populations, to our knowledge, our work offers a first theoretical framework for detecting tipping points and mapping species resilience in mutualistic communities that can help to detect potential abrupt transitions in a broad class of ecological networks.     

Tipping elements in the Earth's climate system

The term “tipping point” commonly refers to a critical threshold at which a tiny perturbation can qualitatively alter the state or development of a system. Here we introduce the term “tipping element” to describe large-scale components of the Earth system that may pass a tipping point. We critically evaluate potential policy-relevant tipping elements in the climate system under anthropogenic forcing, drawing on the pertinent literature and a recent international workshop to compile a short list, and we assess where their tipping points lie. An expert elicitation is used to help rank their sensitivity to global warming and the uncertainty about the underlying physical mechanisms. Then we explain how, in principle, early warning systems could be established to detect the proximity of some tipping points.     

The quiet crossing of ocean tipping points

Anthropogenic climate change profoundly alters the ocean’s environmental conditions, which, in turn, impact marine ecosystems. Some of these changes are happening fast and may be difficult to reverse. The identification and monitoring of such changes, which also includes tipping points, is an ongoing and emerging research effort. Prevention of negative impacts requires mitigation efforts based on feasible research-based pathways. Climate-induced tipping points are traditionally associated with singular catastrophic events (relative to natural variations) of dramatic negative impact. High-probability high-impact ocean tipping points due to warming, ocean acidification, and deoxygenation may be more fragmented both regionally and in time but add up to global dimensions. These tipping points in combination with gradual changes need to be addressed as seriously as singular catastrophic events in order to prevent the cumulative and often compounding negative societal and Earth system impacts.     

Reducing abrupt climate change risk using the Montreal Protocol and other regulatory actions to complement cuts in CO2 emissions

Current emissions of anthropogenic greenhouse gases (GHGs) have already committed the planet to an increase in average surface temperature by the end of the century that may be above the critical threshold for tipping elements of the climate system into abrupt change with potentially irreversible and unmanageable consequences. This would mean that the climate system is close to entering if not already within the zone of “dangerous anthropogenic interference” (DAI). Scientific and policy literature refers to the need for “early,” “urgent,” “rapid,” and “fast-action” mitigation to help avoid DAI and abrupt climate changes. We define “fast-action” to include regulatory measures that can begin within 2–3 years, be substantially implemented in 5–10 years, and produce a climate response within decades. We discuss strategies for short-lived non-CO₂ GHGs and particles, where existing agreements can be used to accomplish mitigation objectives. Policy makers can amend the Montreal Protocol to phase down the production and consumption of hydrofluorocarbons (HFCs) with high global warming potential. Other fast-action strategies can reduce emissions of black carbon particles and precursor gases that lead to ozone formation in the lower atmosphere, and increase biosequestration, including through biochar. These and other fast-action strategies may reduce the risk of abrupt climate change in the next few decades by complementing cuts in CO₂ emissions.     

Environmental tipping points significantly affect the cost?benefit assessment of climate policies

Most current cost−benefit analyses of climate change policies suggest an optimal global climate policy that is significantly less stringent than the level required to meet the internationally agreed 2 °C target. This is partly because the sum of estimated economic damage of climate change across various sectors, such as energy use and changes in agricultural production, results in only a small economic loss or even a small economic gain in the gross world product under predicted levels of climate change. However, those cost−benefit analyses rarely take account of environmental tipping points leading to abrupt and irreversible impacts on market and nonmarket goods and services, including those provided by the climate and by ecosystems. Here we show that including environmental tipping point impacts in a stochastic dynamic integrated assessment model profoundly alters cost−benefit assessment of global climate policy. The risk of a tipping point, even if it only has nonmarket impacts, could substantially increase the present optimal carbon tax. For example, a risk of only 5% loss in nonmarket goods that occurs with a 5% annual probability at 4 °C increase of the global surface temperature causes an immediate two-thirds increase in optimal carbon tax. If the tipping point also has a 5% impact on market goods, the optimal carbon tax increases by more than a factor of 3. Hence existing cost−benefit assessments of global climate policy may be significantly underestimating the needs for controlling climate change.Tipping points in the climate system (1) and in ecosystems (2, 3) could be crossed in a changing climate. The resulting impacts are expected to reduce the environmental goods and services provided to humanity by the climate and by ecosystems (4). Some of those impacts will be on goods that have direct market value, such as the food produced from agricultural ecosystems. Other impacts will be on services that do not involve any production processes of market goods but can still directly affect human well-being through, e.g., health effects, changes in physical comfort, sensory satisfaction, or spiritual fulfillment—making them nonmarket impacts (5).Environmental tipping points can occur at a range of spatial scales (6), from global-scale tipping points in the climate system, such as a reorganization of the Atlantic Meridional Overturning Circulation (1, 7), to ecosystem-scale tipping points, such as sudden lake eutrophication (2). Here we consider the idealized case of an instantaneous tipping point that occurs on a sufficient scale to impact the global economy. Such a tipping point could come from a physical tipping element in the climate system, such as the West African or Indian monsoons (1), which in turn impacts humans and ecosystems, or it could come from a more biological tipping element such as a major biome (1). For example, widespread dieback of forests has been observed in Canada (8, 9), both boreal and tropical biomes are thought to exhibit multiple stable states (10–12), and abrupt forest dieback has been forecast in both the Amazon and boreal regions in future (1, 7). There is even speculation that an abrupt and irreversible shift of ecosystems could occur on a planetary scale (3, 4). Whether they themselves tip or they are impacted by tipping in a more physical part of the climate system, ecosystems and the goods and services they provide carry significant market and nonmarket values (5) (as presumably do the goods and services provided by more physical parts of the climate system).Predicting when tipping points will occur is inherently uncertain (1, 2), because they occur in imperfectly understood complex systems, which are subject to stochastic environmental variability (as well as deterministic forcing), meaning that their time of tipping can never be forecast precisely (13). The representation of such risk and uncertainty is recognized as an unresolved issue for the estimation of the social cost of carbon (14–16).Here we explore how the risk of stochastically uncertain environmental tipping points that have nonmarket, or both market and nonmarket, impacts affects the cost−benefit assessment of climate change policies. The majority of attempts to assess the economic implications of the impacts of climate change concentrate on market impacts, whose estimation can draw information from market statistics (approaches and limitations of which are discussed in, e.g., refs. 15 and 17). Most integrated assessment models (IAMs) also include nonmarket impacts, but they tend to discount these future impacts without accounting for increases in their relative price as environmental goods and services become scarcer (18, 19). The damages in IAMs are also often smooth functions of temperature that do not account for abrupt and irreversible impacts from tipping points. Finally, many IAMs are deterministic, failing to consider uncertainty surrounding the impacts of climate change.Each of these three weaknesses has been addressed individually in existing studies. The limited substitutability of ecosystem services has been shown to increase the welfare impact of these nonmarket losses, as discussed by Hoel and Sterner (18) and Sterner and Persson (19). The prospect of irreversible, environmental tipping points has been shown to produce a precautionary optimal management response in many cases (20–22). Stochastic uncertainty surrounding climate change damages has been shown to generally increase the optimal level of mitigation (23, 24). Furthermore, the combination of stochastic uncertainty and abrupt, irreversible patterns of climate change has been shown to increase optimal levels of mitigation (25, 26). Here, we address the three issues simultaneously, analyzing how the stochastic component of climate change risk interacts with the limited substitutability of environmental goods and services, under irreversible tipping.     

From the Cover: Economic impacts of tipping points in the climate system

Climate scientists have long emphasized the importance of climate tipping points like thawing permafrost, ice sheet disintegration, and changes in atmospheric circulation. Yet, save for a few fragmented studies, climate economics has either ignored them or represented them in highly stylized ways. We provide unified estimates of the economic impacts of all eight climate tipping points covered in the economic literature so far using a meta-analytic integrated assessment model (IAM) with a modular structure. The model includes national-level climate damages from rising temperatures and sea levels for 180 countries, calibrated on detailed econometric evidence and simulation modeling. Collectively, climate tipping points increase the social cost of carbon (SCC) by ∼25% in our main specification. The distribution is positively skewed, however. We estimate an ∼10% chance of climate tipping points more than doubling the SCC. Accordingly, climate tipping points increase global economic risk. A spatial analysis shows that they increase economic losses almost everywhere. The tipping points with the largest effects are dissociation of ocean methane hydrates and thawing permafrost. Most of our numbers are probable underestimates, given that some tipping points, tipping point interactions, and impact channels have not been covered in the literature so far; however, our method of structural meta-analysis means that future modeling of climate tipping points can be integrated with relative ease, and we present a reduced-form tipping points damage function that could be incorporated in other IAMs.

Climate tipping points are subject to considerable scientific uncertainty in relation to their size, probability, and how they interact with each other (1–4). Their economic impacts are even more uncertain, and consequently, these are often ignored (5, 6) or given a highly stylized treatment that fails to accurately represent geophysical dynamics and is nearly impossible to calibrate (7–9). As a result, tipping points are only weakly reflected in the policy advice economists give on climate change, typically by way of caveats and contextualization, rather than an integral part of the modeling that gives rise to estimates of the social cost of carbon (SCC) and other economic metrics of interest.The very definition of climate tipping points has attracted significant scholarship (2, 9, 10). We associate them with perhaps the best-known definition of “tipping elements”: “subsystems of the Earth system that are at least subcontinental in scale and can be switched—under certain circumstances—into a qualitatively different state by small perturbations” (2). This is an intentionally broad and flexible definition that admits a variety of geophysical responses, including nonlinear feedbacks and both reversible and irreversible phase changes (9). This flexibility is important for our purposes because economic studies omit or inadequately capture geophysical processes of all these sorts. Adopting a narrower definition (for example, limited to abrupt, discontinuous changes) would lead us to exclude geophysical processes with large economic costs.     

Near-linear response of mean monsoon strength to a broad range of radiative forcings

Theoretical models have been used to argue that seasonal mean monsoons will shift abruptly and discontinuously from wet to dry stable states as their radiative forcings pass a critical threshold, sometimes referred to as a “tipping point.” Further support for a strongly nonlinear response of monsoons to radiative forcings is found in the seasonal onset of the South Asian summer monsoon, which is abrupt compared with the annual cycle of insolation. Here it is shown that the seasonal mean strength of monsoons instead exhibits a nearly linear dependence on a wide range of radiative forcings. First, a previous theory that predicted a discontinuous, threshold response is shown to omit a dominant stabilizing term in the equations of motion; a corrected theory predicts a continuous and nearly linear response of seasonal mean monsoon strength to forcings. A comprehensive global climate model is then used to show that the seasonal mean South Asian monsoon exhibits a near-linear dependence on a wide range of isolated greenhouse gas, aerosol, and surface albedo forcings. This model reproduces the observed abrupt seasonal onset of the South Asian monsoon but produces a near-linear response of the mean monsoon by changing the duration of the summer circulation and the latitude of that circulation’s ascent branch. Thus, neither a physically correct theoretical model nor a comprehensive climate model support the idea that seasonal mean monsoons will undergo abrupt, nonlinear shifts in response to changes in greenhouse gas concentrations, aerosol emissions, or land surface albedo.Monsoons deliver water to billions of people, so catastrophe would likely result if a gradual and small change in a forcing produced a comparatively abrupt and large change in monsoon strength. Previous studies (1, 2) used theoretical models to argue that monsoons will undergo exactly this sort of abrupt transition if anthropogenic or natural forcings exceed a critical threshold, which they referred to as a “tipping point” (3). Changes in land use or atmospheric aerosols sufficient to increase local top-of-atmosphere albedo to 0.5 have been predicted to cause a shift in the Indian summer monsoon from its current wet state to a dry state (1). The idea that anthropogenic climate forcings might produce an abrupt shutdown of some monsoons has become prominent (3, 4), even though some argue that this is unlikely to occur in the next century (5).Paleoclimate records contain abundant evidence for abrupt changes in various measures of monsoon strength (6, 7). However, such records typically measure variations at a particular location and so may not distinguish between a nonlinear response of the entire monsoon and a more gradual, linear shift of a spatial pattern with sharp horizontal gradients. It is also unclear whether mechanisms that govern monsoon changes on orbital to geological time scales are relevant for the response to anthropogenic forcings. However, even if proxy records of past monsoons are ambiguous, the modern seasonal cycle contains evidence for the abrupt response of monsoons to a radiative forcing: South Asian summer monsoon onset occurs more rapidly than can be explained by a linear response to the annual cycle of insolation (8, 9). Although the cause of this nonlinear seasonal evolution is the subject of active research (10, 11), it seems plausible that the same mechanism might produce an abrupt response of the seasonal mean monsoon to an imposed seasonal mean forcing.These results motivate our examination of how monsoon strength scales with a range of forcings. In particular, we use a simple energetic theory and an ensemble of global climate model (GCM) integrations to determine whether the summer mean strength of tropical monsoons will change discontinuously in response to a large range of radiative forcings.     

INAUGURAL ARTICLE by a Recently Elected Academy Member:Beyond the hockey stick: Climate lessons from the Common Era

More than two decades ago, my coauthors, Raymond Bradley and Malcolm Hughes, and I published the now iconic “hockey stick” curve. It was a simple graph, derived from large-scale networks of diverse climate proxy (“multiproxy”) data such as tree rings, ice cores, corals, and lake sediments, that captured the unprecedented nature of the warming taking place today. It became a focal point in the debate over human-caused climate change and what to do about it. Yet, the apparent simplicity of the hockey stick curve betrays the dynamicism and complexity of the climate history of past centuries and how it can inform our understanding of human-caused climate change and its impacts. In this article, I discuss the lessons we can learn from studying paleoclimate records and climate model simulations of the “Common Era,” the period of the past two millennia during which the “signal” of human-caused warming has risen dramatically from the background of natural variability.

Clearly, there is a cautionary tale told by the hockey stick curve in the unprecedented warming that we are causing, but the lessons from the paleoclimate record of the Common Era (CE) go far beyond that. What might we infer, for example, about the role of dynamical mechanisms relevant to climate change impacts today from their past responses to natural drivers? Examples are the El Niño phenomenon, the Asian summer monsoon, and the North Atlantic Ocean “conveyor belt” circulation. Are there potential “tipping point” elements within these climate subsystems? How has sea level changed in past centuries, and what does it tell us about future coastal risk? Are there natural long-term oscillations, evident in the paleoclimate record, that might compete with human-caused climate change today? Can we assess the “sensitivity” of the climate to ongoing human-caused increases in greenhouse gas concentrations from examining how climate has responded to natural factors in the past? Also, can better estimates of past trends inform assessments of how close we are to critical “dangerous” warming thresholds? In this article, I seek to address such questions and offer thoughts about ways forward to more confident answers.     

The future of ice sheets and sea ice: Between reversible retreat and unstoppable loss

We discuss the existence of cryospheric “tipping points” in the Earth''s climate system. Such critical thresholds have been suggested to exist for the disappearance of Arctic sea ice and the retreat of ice sheets: Once these ice masses have shrunk below an anticipated critical extent, the ice–albedo feedback might lead to the irreversible and unstoppable loss of the remaining ice. We here give an overview of our current understanding of such threshold behavior. By using conceptual arguments, we review the recent findings that such a tipping point probably does not exist for the loss of Arctic summer sea ice. Hence, in a cooler climate, sea ice could recover rapidly from the loss it has experienced in recent years. In addition, we discuss why this recent rapid retreat of Arctic summer sea ice might largely be a consequence of a slow shift in ice-thickness distribution, which will lead to strongly increased year-to-year variability of the Arctic summer sea-ice extent. This variability will render seasonal forecasts of the Arctic summer sea-ice extent increasingly difficult. We also discuss why, in contrast to Arctic summer sea ice, a tipping point is more likely to exist for the loss of the Greenland ice sheet and the West Antarctic ice sheet.     

Climatological determinants of woody cover in Africa

Determining the factors that influence the distribution of woody vegetation cover and resolving the sensitivity of woody vegetation cover to shifts in environmental forcing are critical steps necessary to predict continental-scale responses of dryland ecosystems to climate change. We use a 6-year satellite data record of fractional woody vegetation cover and an 11-year daily precipitation record to investigate the climatological controls on woody vegetation cover across the African continent. We find that-as opposed to a relationship with only mean annual rainfall-the upper limit of fractional woody vegetation cover is strongly influenced by both the quantity and intensity of rainfall events. Using a set of statistics derived from the seasonal distribution of rainfall, we show that areas with similar seasonal rainfall totals have higher fractional woody cover if the local rainfall climatology consists of frequent, less intense precipitation events. Based on these observations, we develop a generalized response surface between rainfall climatology and maximum woody vegetation cover across the African continent. The normalized local gradient of this response surface is used as an estimator of ecosystem vegetation sensitivity to climatological variation. A comparison between predicted climate sensitivity patterns and observed shifts in both rainfall and vegetation during 2009 reveals both the importance of rainfall climatology in governing how ecosystems respond to interannual fluctuations in climate and the utility of our framework as a means to forecast continental-scale patterns of vegetation shifts in response to future climate change.     

Dynamics of Political Polarization Special Feature: Polarization and tipping points

Research has documented increasing partisan division and extremist positions that are more pronounced among political elites than among voters. Attention has now begun to focus on how polarization might be attenuated. We use a general model of opinion change to see if the self-reinforcing dynamics of influence and homophily may be characterized by tipping points that make reversibility problematic. The model applies to a legislative body or other small, densely connected organization, but does not assume country-specific institutional arrangements that would obscure the identification of fundamental regularities in the phase transitions. Agents in the model have initially random locations in a multidimensional issue space consisting of membership in one of two equal-sized parties and positions on 10 issues. Agents then update their issue positions by moving closer to nearby neighbors and farther from those with whom they disagree, depending on the agents’ tolerance of disagreement and strength of party identification compared to their ideological commitment to the issues. We conducted computational experiments in which we manipulated agents’ tolerance for disagreement and strength of party identification. Importantly, we also introduced exogenous shocks corresponding to events that create a shared interest against a common threat (e.g., a global pandemic). Phase diagrams of political polarization reveal difficult-to-predict transitions that can be irreversible due to asymmetric hysteresis trajectories. We conclude that future empirical research needs to pay much closer attention to the identification of tipping points and the effectiveness of possible countermeasures.

Democratic societies thrive on disagreement, debate, and intense competition among multiple interest groups (1). Nevertheless, there is growing recognition that political division can become a liability for democratic governance when multiple lines of controversy become aligned with partisan identities (2). Political scientists refer to this crystallization of opinion as “constraint” (3) and point to two principal reasons for concern: partisan division and extremism. First, the alignment of substantively unrelated issues (e.g., capital punishment, reproductive rights, and gun control) attenuates intraparty differences, subdues political cacophony, and rearranges an ideological mosaic into two diametrically opposed political camps (4). Second, issue alignment and factional bifurcation allow differences of opinion to reinforce one another such that moderate voices become muffled and the distribution of opinion becomes increasingly bimodal (5). Analyses of roll-call voting show that political elites have adopted more extreme positions on core political issues in recent decades (6), while polarization among voters has become mainly affective rather than ideological (7). This combination of partisan division and political extremism can eviscerate the “cross-cutting cleavages” on which pluralistic diversity depends, thereby undermining the capacity for compromise required for effective democratic governance.In this paper, we point to a third danger, one that has received too little attention in the growing literature on political and cultural polarization: the existence of a tipping point beyond which the activation of shared interests can no longer bring warring factions together, even in the face of a common threat. Our interest in this problem is motivated by a series of crises that might be expected to activate a broad political identity and unified response: the Great Recession, Russian electoral interference, impending climate catastrophe, a global pandemic, and, most recently, the January 6 attack on the US Congress. It is not surprising that these events prompted a call to arms. What is surprising is the direction in which the arms were pointed.Our goal is not to explain polarization, about which there is an extensive literature and a lively debate. Instead, we focus narrowly on a phase analysis of polarization, a problem that has largely escaped attention in previous research. We use a general model of opinion dynamics to demonstrate the existence of tipping points, at which even an external threat may be insufficient to reverse the self-reinforcing dynamics of political polarization. Polarization reaches a tipping point when the rate of increase suddenly accelerates and when the process displays a phase change characterized by asymmetric hysteresis loops. The existence of a tipping point in a self-reinforcing dynamic is neither inevitable nor especially counterintuitive. However, the existence of multiple tipping points, one when polarization is increasing and another when it is decreasing, cannot be assumed. Moreover, if the threshold on the downward trajectory falls below the threshold going up, the dynamics can be hard to reverse. This study is motivated by the need to call greater attention to that possibility.     

Persistent millennial-scale shifts in moisture regimes in western Canada during the past six millennia

Inferences of past climatic conditions from a sedimentary record from Big Lake, British Columbia, Canada, over the past 5,500 years show strong millennial-scale patterns, which oscillate between periods of wet and drier climatic conditions. Higher frequency decadal- to centennial-scale fluctuations also occur within the dominant millennial-scale patterns. These changes in climatic conditions are based on estimates of changes in lake depth and salinity inferred from diatom assemblages in a well dated sediment core. After periods of relative stability, abrupt shifts in diatom assemblages and inferred climatic conditions occur approximately every 1,220 years. The correspondence of these shifts to millennial-scale variations in records of glacial expansionrecession and ice-rafting events in the Atlantic suggest that abrupt millennial-scale shifts are important to understanding climatic variability in North America during the mid- to late Holocene. Unfortunately, the spatial patterns and mechanisms behind these large and abrupt swings are poorly understood. Similar abrupt and prolonged changes in climatic conditions today could pose major societal challenges for many regions.     

Abrupt climate change and collapse of deep-sea ecosystems

We investigated the deep-sea fossil record of benthic ostracodes during periods of rapid climate and oceanographic change over the past 20,000 years in a core from intermediate depth in the northwestern Atlantic. Results show that deep-sea benthic community “collapses” occur with faunal turnover of up to 50% during major climatically driven oceanographic changes. Species diversity as measured by the Shannon–Wiener index falls from 3 to as low as 1.6 during these events. Major disruptions in the benthic communities commenced with Heinrich Event 1, the Inter-Allerød Cold Period (IACP: 13.1 ka), the Younger Dryas (YD: 12.9–11.5 ka), and several Holocene Bond events when changes in deep-water circulation occurred. The largest collapse is associated with the YD/IACP and is characterized by an abrupt two-step decrease in both the upper North Atlantic Deep Water assemblage and species diversity at 13.1 ka and at 12.2 ka. The ostracode fauna at this site did not fully recover until ≈8 ka, with the establishment of Labrador Sea Water ventilation. Ecologically opportunistic slope species prospered during this community collapse. Other abrupt community collapses during the past 20 ka generally correspond to millennial climate events. These results indicate that deep-sea ecosystems are not immune to the effects of rapid climate changes occurring over centuries or less.     

The control system for the Honda humanoid robot

To avoid tipping over either during walking or on standing up, humans will first push down hard on the ground with a part of the sole of the foot. Then, when the tipping force can no longer be resisted, a change in body position or an extra step (stepping out) may be required to stabilise the posture. Our biped robot's control system attempts to reproduce and execute the same postural control operations carried out by humans. In this article, we present the history of robot development at Honda, fundamental dynamics for robots and the principles of posture control.     

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.

Catastrophic and unexpected shifts in nature and society have been ubiquitous throughout history. In complex, nonlinear systems they can arise when a critical threshold in the boundary conditions is crossed. This is referred to as a tipping point and is of specific concern in the context of anthropogenic climate change. Several elements of the climate system have been identified to be at risk for crossing a critical threshold with increasing greenhouse gas concentrations, including Arctic sea ice, the Amazon rain forest, Boreal permafrost, and the Atlantic Meridional Overturning Circulation (AMOC) (1, 2). Tipping points are most often associated with a bifurcation or attractor crises, i.e., a loss of stability of a stable system state (a so-called attractor). A catastrophic shift occurs as a system parameter is changed beyond the bifurcation point and the system state evolves to another attractor. Consequently, there have been substantial efforts to assess whether elements of the Earth system indeed possess such critical thresholds (3–5) and whether one can determine the proximity of the current state to the threshold (6, 7). Furthermore, the existence of generic precursors or early-warning signals preceding tipping points has been explored (8–10).While these are important issues to address, it is now known that catastrophic transitions to undesired attractors can be induced when the parameter is changed at a rate exceeding a certain critical value, even though the parameter does not cross a critical threshold (bifurcation point) (11–13). This is known as rate-induced tipping and in the context of real-world systems like the climate, such transitions further limit the range of parameters that span the safe operating space. Here, we focus on a potential collapse of the AMOC with increasing freshwater input into the North Atlantic. This is a concern since there is observational evidence for accelerating meltwater runoff from Greenland (14–16), as well as a slowing down of the AMOC (17). As illustrated in Fig. 1A, if the climate system displays rate-induced tipping, the increasing rates of change of freshwater runoff could push it into a regime (gray region) that has been thought safe otherwise. Previous evidence for rate dependency of an AMOC collapse comes from conceptual ocean box models (18, 19) as well as two-dimensional ocean and climate models with varying freshwater (20) or greenhouse gas forcing (21).Open in a separate windowFig. 1.Tipping of the ocean circulation. (A) Observational evidence for accelerating Greenland meltwater runoff (Materials and Methods) in comparison to conceptual boundaries of the safe operating space of the ocean circulation. (B) Maximum value of the meridional stream function, zonally averaged over the Atlantic basin, in a continuous model simulation. The forcing is increased to Fmax=0.31 in small increments within 300 y each (black curve) and subsequently decreased to zero again (orange curve). (C, Inset) Time series of the forcing parameter F in a parameter shift experiment with ramping duration T=160 y. (C, full plot) Corresponding values of the AMOC maximum (time is color coded). The black circles are the values shown in B. (D) Same as C but for T=140 y.Here we show that rate-induced transitions are indeed a concern for the climate system, by demonstrating explicitly the existence of a rate-induced collapse of the AMOC in a three-dimensional model of the global thermohaline circulation with time-dependent freshwater forcing. In addition, by performing large ensemble simulations, we show that there are fundamental difficulties in defining and determining safe rates of parameter changes in the presence of chaotic dynamics, as is the case for the climate system. This makes the boundary separating safe from unsafe climate conditions fuzzy (striped area in Fig. 1A).     

Integrating the invisible fabric of nature into fisheries management

Overfishing and environmental change have triggered many severe and unexpected consequences. As existing communities have collapsed, new ones have become established, fundamentally transforming ecosystems to those that are often less productive for fisheries, more prone to cycles of booms and busts, and thus less manageable. We contend that the failure of fisheries science and management to anticipate these transformations results from a lack of appreciation for the nature, strength, complexity, and outcome of species interactions. Ecologists have come to understand that networks of interacting species exhibit nonlinear dynamics and feedback loops that can produce sudden and unexpected shifts. We argue that fisheries science and management must follow this lead by developing a sharper focus on species interactions and how disrupting these interactions can push ecosystems in which fisheries are embedded past their tipping points.     

El Ni?o/Southern Oscillation response to global warming

The El Niño/Southern Oscillation (ENSO) phenomenon, originating in the Tropical Pacific, is the strongest natural interannual climate signal and has widespread effects on the global climate system and the ecology of the Tropical Pacific. Any strong change in ENSO statistics will therefore have serious climatic and ecological consequences. Most global climate models do simulate ENSO, although large biases exist with respect to its characteristics. The ENSO response to global warming differs strongly from model to model and is thus highly uncertain. Some models simulate an increase in ENSO amplitude, others a decrease, and others virtually no change. Extremely strong changes constituting tipping point behavior are not simulated by any of the models. Nevertheless, some interesting changes in ENSO dynamics can be inferred from observations and model integrations. Although no tipping point behavior is envisaged in the physical climate system, smooth transitions in it may give rise to tipping point behavior in the biological, chemical, and even socioeconomic systems. For example, the simulated weakening of the Pacific zonal sea surface temperature gradient in the Hadley Centre model (with dynamic vegetation included) caused rapid Amazon forest die-back in the mid-twenty-first century, which in turn drove a nonlinear increase in atmospheric CO₂, accelerating global warming.One of the main characteristics of the earth''s climate is its strong natural variability on a wide range of timescales from seasonal to millennial. Climate variability can be generated, on the one hand, internally through interactions within and between the different climate subsystems (atmosphere, ocean, land, sea ice, glaciers, biogeochemistry). The internal nonlinear (chaotic) dynamics of the atmosphere and the oceans, for instance, and ocean–atmosphere interactions generate a large amount of variability on seasonal to decadal timescales. However, the climate system can be externally forced. The annual cycle is a prominent example. On the very long millennial timescales, changes in the orbital parameters are the most important drivers of climate change. They are the pacemakers of the ice age cycles. Anthropogenic climate change is also considered as externally driven in this context.     

Regional drought-induced reduction in the biomass carbon sink of Canada's boreal forests

The boreal forests, identified as a critical "tipping element" of the Earth's climate system, play a critical role in the global carbon budget. Recent findings have suggested that terrestrial carbon sinks in northern high-latitude regions are weakening, but there has been little observational evidence to support the idea of a reduction of carbon sinks in northern terrestrial ecosystems. Here, we estimated changes in the biomass carbon sink of natural stands throughout Canada's boreal forests using data from long-term forest permanent sampling plots. We found that in recent decades, the rate of biomass change decreased significantly in western Canada (Alberta, Saskatchewan, and Manitoba), but there was no significant trend for eastern Canada (Ontario and Quebec). Our results revealed that recent climate change, and especially drought-induced water stress, is the dominant cause of the observed reduction in the biomass carbon sink, suggesting that western Canada's boreal forests may become net carbon sources if the climate change-induced droughts continue to intensify.     

Exploring the likelihood and mechanism of a climate-change-induced dieback of the Amazon rainforest

We examine the evidence for the possibility that 21st-century climate change may cause a large-scale “dieback” or degradation of Amazonian rainforest. We employ a new framework for evaluating the rainfall regime of tropical forests and from this deduce precipitation-based boundaries for current forest viability. We then examine climate simulations by 19 global climate models (GCMs) in this context and find that most tend to underestimate current rainfall. GCMs also vary greatly in their projections of future climate change in Amazonia. We attempt to take into account the differences between GCM-simulated and observed rainfall regimes in the 20th century. Our analysis suggests that dry-season water stress is likely to increase in E. Amazonia over the 21st century, but the region tends toward a climate more appropriate to seasonal forest than to savanna. These seasonal forests may be resilient to seasonal drought but are likely to face intensified water stress caused by higher temperatures and to be vulnerable to fires, which are at present naturally rare in much of Amazonia. The spread of fire ignition associated with advancing deforestation, logging, and fragmentation may act as nucleation points that trigger the transition of these seasonal forests into fire-dominated, low biomass forests. Conversely, deliberate limitation of deforestation and fire may be an effective intervention to maintain Amazonian forest resilience in the face of imposed 21st-century climate change. Such intervention may be enough to navigate E. Amazonia away from a possible “tipping point,” beyond which extensive rainforest would become unsustainable.     

Brief Report: Warming-induced tipping points of Arctic and alpine shrub recruitment

Shrub recruitment, a key component of vegetation dynamics beyond forests, is a highly sensitive indicator of climate and environmental change. Warming-induced tipping points in Arctic and alpine treeless ecosystems are, however, little understood. Here, we compare two long-term recruitment datasets of 2,770 shrubs from coastal East Greenland and from the Tibetan Plateau against atmospheric circulation patterns between 1871 and 2010 Common Era. Increasing rates of shrub recruitment since 1871 reached critical tipping points in the 1930s and 1960s on the Tibetan Plateau and in East Greenland, respectively. A recent decline in shrub recruitment in both datasets was likely related to warmer and drier climates, with a stronger May to July El Niño Southern Oscillation over the Tibetan Plateau and a stronger June to July Atlantic Multidecadal Oscillation over Greenland. Exceeding the thermal optimum of shrub recruitment, the recent warming trend may cause soil moisture deficit. Our findings suggest that changes in atmospheric circulation explain regional climate dynamics and associated response patterns in Arctic and alpine shrub communities, knowledge that should be considered to protect vulnerable high-elevation and high-latitude ecosystems from the cascading effects of anthropogenic warming.