Spatial early warning signals for impending regime shifts: A practical framework for application in real‐world landscapes

Prediction of ecosystem response to global environmental change is a pressing scientific challenge of major societal relevance. Many ecosystems display nonlinear responses to environmental change, and may even undergo practically irreversible ‘regime shifts’ that initiate ecosystem collapse. Recently, early warning signals based on spatiotemporal metrics have been proposed for the identification of impending regime shifts. The rapidly increasing availability of remotely sensed data provides excellent opportunities to apply such model‐based spatial early warning signals in the real world, to assess ecosystem resilience and identify impending regime shifts induced by global change. Such information would allow land‐managers and policy makers to interfere and avoid catastrophic shifts, but also to induce regime shifts that move ecosystems to a desired state. Here, we show that the application of spatial early warning signals in real‐world landscapes presents unique and unexpected challenges, and may result in misleading conclusions when employed without careful consideration of the spatial data and processes at hand. We identify key practical and theoretical issues and provide guidelines for applying spatial early warning signals in heterogeneous, real‐world landscapes based on literature review and examples from real‐world data. Major identified issues include (1) spatial heterogeneity in real‐world landscapes may enhance reversibility of regime shifts and boost landscape‐level resilience to environmental change (2) ecosystem states are often difficult to define, while these definitions have great impact on spatial early warning signals and (3) spatial environmental variability and socio‐economic factors may affect spatial patterns, spatial early warning signals and associated regime shift predictions. We propose a novel framework, shifting from an ecosystem perspective towards a landscape approach. The framework can be used to identify conditions under which resilience assessment with spatial remotely sensed data may be successful, to support well‐informed application of spatial early warning signals, and to improve predictions of ecosystem responses to global environmental change.     

Changing skewness: an early warning signal of regime shifts in ecosystems

Empirical evidence for large-scale abrupt changes in ecosystems such as lakes and vegetation of semi-arid regions is growing. Such changes, called regime shifts, can lead to degradation of ecological services. We study simple ecological models that show a catastrophic transition as a control parameter is varied and propose a novel early warning signal that exploits two ubiquitous features of ecological systems: nonlinearity and large external fluctuations. Either reduced resilience or increased external fluctuations can tip ecosystems to an alternative stable state. It is shown that changes in asymmetry in the distribution of time series data, quantified by changing skewness, is a model-independent and reliable early warning signal for both routes to regime shifts. Furthermore, using model simulations that mimic field measurements and a simple analysis of real data from abrupt climate change in the Sahara, we study the feasibility of skewness calculations using data available from routine monitoring.     

Functional diversity can facilitate the collapse of an undesirable ecosystem state

Biodiversity may increase ecosystem resilience. However, we have limited understanding if this holds true for ecosystems that respond to gradual environmental change with abrupt shifts to an alternative state. We used a mathematical model of anoxic–oxic regime shifts and explored how trait diversity in three groups of bacteria influences resilience. We found that trait diversity did not always increase resilience: greater diversity in two of the groups increased but in one group decreased resilience of their preferred ecosystem state. We also found that simultaneous trait diversity in multiple groups often led to reduced or erased diversity effects. Overall, our results suggest that higher diversity can increase resilience but can also promote collapse when diversity occurs in a functional group that negatively influences the state it occurs in. We propose this mechanism as a potential management approach to facilitate the recovery of a desired ecosystem state.     

Reorganization of a large marine ecosystem due to atmospheric and anthropogenic pressure: a discontinuous regime shift in the Central Baltic Sea

Marine ecosystems such as the Baltic Sea are currently under strong atmospheric and anthropogenic pressure. Besides natural and human-induced changes in climate, major anthropogenic drivers such as overfishing and anthropogenic eutrophication are significantly affecting ecosystem structure and function. Recently, studies demonstrated the existence of alternative stable states in various terrestrial and aquatic ecosystems. These so-called ecosystem regime shifts have been explained mainly as a result of multiple causes, e.g. climatic regime shifts, overexploitation or a combination of both. The occurrence of ecosystem regime shifts has important management implications, as they can cause significant losses of ecological and economic resources. Because of hysteresis in ecosystem responses, restoring regimes considered as favourable may require drastic and expensive management actions. Also the Baltic Sea, the largest brackish water body in the world ocean, and its ecosystems are strongly affected by atmospheric and anthropogenic drivers. Here, we present results of an analysis of the state and development of the Central Baltic Sea ecosystem integrating hydroclimatic, nutrient, phyto- and zooplankton as well as fisheries data. Our analyses of 52 biotic and abiotic variables using multivariate statistics demonstrated a major reorganization of the ecosystem and identified two stable states between 1974 and 2005, separated by a transition period in 1988–1993. We show the change in Baltic ecosystem structure to have the characteristics of a discontinuous regime shift, initiated by climate-induced changes in the abiotic environment and stabilized by fisheries-induced feedback loops in the food web. Our results indicate the importance of maintaining the resilience of an ecosystem to atmospherically induced environmental change by reducing the anthropogenic impact.     

Biodiversity dynamics of freshwater wetland ecosystems affected by secondary salinisation and seasonal hydrology variation: a model-based study

Freshwater wetlands worldwide are under threat from secondary salinisation and climate change. Given that many freshwater wetlands naturally have highly variable hydrology, it is important to understand the combined effects of salinity and water regime on wetland biodiversity. Here a mathematical model has been developed to explore the biodiversity dynamics of freshwater wetland ecosystems affected by secondary salinisation and seasonal hydrology variation. The model shows that seasonal hydrological change can drive the wetland ecosystem into a stable oscillatory state of biodiversity, with the same period as the wetting and drying cycle. The initial condition of a wetland mediates the ecological response of the wetland ecosystem to salinity and seasonal variability. There are two manifestations of stability that occur in relation to wetland biodiversity: monostability and bistability. In model simulations, some wetland ecosystems may respond to the effects of seasonal change quickly, while others may do so more slowly. In ‘slow response’ wetlands, seasonal variability has a weak impact on the ecosystem properties of stability, resilience, sensitivity and the species richness–mean salinity relationship. In contrast, ‘fast response’ wetlands are seasonally controlled heavily. Seasonal variability can play a critical role in determining ecosystem properties. Changes in the strength of seasonality can induce the transition between monostability and bistability. Seasonal variability may also reduce wetland resilience, exacerbating the risk of secondary salinisation. On the other hand, seasonal variability may provide opportunities for the restoration of salinised wetlands by increasing their sensitivity to management actions and facilitating recovery processes. Model simulations show that the response of the stable biodiversity oscillation to changing mean salinity is dependent on seasonality strength (primarily for fast response wetlands) and other wetland conditions. Generally, there are two types of wetland responses to changes in mean salinity: type 1 wetlands exhibit a graded response of species richness (a surrogate for biodiversity), whereas a hysteretic response occurs in type 2 wetlands. Species diversity displays critical behaviour: regime shifts in diversity occur at the thresholds of mean salinity, strength of seasonality or initial species diversity. The predictions are consistent with previously-published field observations in salinised freshwater wetlands. Handling editor: D. Hamilton     

Resilience vs. historical contingency in microbial responses to environmental change

How soil processes such as carbon cycling will respond to future climate change depends on the responses of complex microbial communities, but most ecosystem models assume that microbial functional responses are resilient and can be predicted from simple parameters such as biomass and temperature. Here, we consider how historical contingencies might alter those responses because function depends on prior conditions or biota. Functional resilience can be driven by physiological, community or adaptive shifts; historical contingencies can result from the influence of historical environments or a combination of priority effects and biotic resistance. By modelling microbial population responses to environmental change, we demonstrate that historical environments can constrain soil function with the degree of constraint depending on the magnitude of change in the context of the prior environment. For example microbial assemblages from more constant environments were more sensitive to change leading to poorer functional acclimatisation compared to microbial assemblages from more fluctuating environments. Such historical contingencies can lead to deviations from expected functional responses to climate change as well as local variability in those responses. Our results form a set of interrelated hypotheses regarding soil microbial responses to climate change that warrant future empirical attention.     

Gradual regime shifts in spatially extended ecosystems

Ecosystem regime shifts are regarded as abrupt global transitions from one stable state to an alternative stable state, induced by slow environmental changes or by global disturbances. Spatially extended ecosystems, however, can also respond to local disturbances by the formation of small domains of the alternative state. Such a response can lead to gradual regime shifts involving front propagation and the coalescence of alternative-state domains. When one of the states is spatially patterned, a multitude of intermediate stable states appears, giving rise to step-like gradual shifts with extended pauses at these states. Using a minimal model, we study gradual state transitions and show that they precede abrupt transitions. We propose indicators to probe gradual regime shifts, and suggest that a combination of abrupt-shift indicators and gradual-shift indicators might be needed to unambiguously identify regime shifts. Our results are particularly relevant to desertification in drylands where transitions to bare soil take place from spotted vegetation, and the degradation process appears to involve step-like events of local vegetation mortality caused by repeated droughts.     

Critical slowing down as an indicator of transitions in two-species models

Transitions in ecological systems often occur without apparent warning, and may represent shifts between alternative persistent states. Decreasing ecological resilience (the size of the basin of attraction around a stable state) can signal an impending transition, but this effect is difficult to measure in practice. Recent research has suggested that a decreasing rate of recovery from small perturbations (critical slowing down) is a good indicator of ecological resilience. Here we use analytical techniques to draw general conclusions about the conditions under which critical slowing down provides an early indicator of transitions in two-species predator-prey and competition models. The models exhibit three types of transition: the predator-prey model has a Hopf bifurcation and a transcritical bifurcation, and the competition model has two saddle-node bifurcations (in which case the system exhibits hysteresis) or two transcritical bifurcations, depending on the parameterisation. We find that critical slowing down is an earlier indicator of the Hopf bifurcation in predator-prey models in which prey are regulated by predation rather than by intrinsic density-dependent effects and an earlier indicator of transitions in competition models in which the dynamics of the rare species operate on slower timescales than the dynamics of the common species. These results lead directly to predictions for more complex multi-species systems, which can be tested using simulation models or real ecosystems.     

Marine reserves can enhance ecological resilience

The goals of ecosystem‐based management (EBM) include protecting ecological resilience, the magnitude of a perturbation that a community can withstand and remain in a given state. As a tool to achieve this goal, no‐take marine reserves may enhance resilience by protecting source populations or reduce it by concentrating fishing in harvested areas. Here, we test whether spatial management with marine reserves can increase ecological resilience compared to non‐spatial (conventional) management using a dynamic model of a simplified fish community with structured predation and competition that causes alternative stable states. Relative to non‐spatial management, reserves increase the resilience of the desired (predator‐dominated) equilibrium state in both stochastic and deterministic environments, especially under intensive fishing. As a result, spatial management also increases the feasibility of restoring degraded (competitor‐dominated) systems, particularly if combined with culling of competitors or stock enhancement of adult predators.     

Abrupt shifts in African savanna tree cover along a climatic gradient

Aim To describe patterns of tree cover in savannas over a climatic gradient and a range of spatial scales and test if there are identifiable climate‐related mean structures, if tree cover always increases with water availability and if there is a continuous trend or a stepwise trend in tree cover. Location Central Tropical Africa. Methods We compared a new analysis of satellite tree cover data with botanical, phytogeographical and environmental data. Results Along the climatic transect, six vegetation structures were distinguished according to their average tree cover, which can co‐occur as mosaics. The resulting abrupt shifts in tree cover were not correlated to any shifts in either environmental variables or in tree species distributions. Main conclusions A strong contrast appears between fine‐scale variability in tree cover and coarse‐scale structural states that are stable over several degrees of latitude. While climate parameters and species pools display a continuous evolution along the climatic gradient, these stable structural states have discontinuous transitions, resulting in regions containing mosaics of alternative stable states. Soils appear to have little effect inside the climatic stable state domains but a strong action on the location of the transitions. This indicates that savannas are patch dynamics systems, prone to feedbacks stabilizing their coarse‐scale structure over wide ranges of environmental conditions.     

Capturing the cornerstones of coral reef resilience: linking theory to practice

Coral reefs can undergo unexpected and dramatic changes in community composition, so called phase shifts. This can have profound consequences for ecosystem services upon which human welfare depends. Understanding of this behavior is in many aspects still in its infancy. Resilience has been argued to provide insurance against unforeseen ecosystem responses in the face of environmental change, and has become a prime goal for the management of coral reefs. However, diverse definitions of resilience can be found in the literature, making its meaning ambiguous. Several studies have used the term as a theoretical framework and concern regarding its practical applicability has been raised. Consequently, operationalizing theory to make resilience observable is an important task, particularly for policy makers and managers dealing with pressing environmental problems. Ultimately this requires some type of empirical assessments, something that has proven difficult due to the multidimensional nature of the concept. Biodiversity, spatial heterogeneity, and connectivity have been proposed as cornerstones of resilience as they may provide insurance against ecological uncertainty. The aim of this article is to provide an overview of the divergent uses of the concept and to propose empirical indicators of the cornerstones of coral reef resilience. These indicators include functional group approaches, the ratios of “good” and “bad” colonizers of space, measurements of spatial heterogeneity, and estimates of potential space availability against grazing capacity. The essence of these operational indicators of resilience is to use them as predictive tools to recognize vulnerability before disturbance occurs that may lead to abrupt phase shifts. Moving toward operationalizing resilience theory is imperative to the successful management of coral reefs in an increasingly disturbed and human-dominated environment. Communicating by Ecology Editor Professor Peter Mumby Order of authors 2–3 is alphabetic     

Robustness of early warning signals for catastrophic and non‐catastrophic transitions

Early warning signals (EWS) are statistical indicators that a rapid regime shift may be forthcoming. Their development has given ecologists hope of predicting rapid regime shifts before they occur. Accurate predictions, however, rely on the signals being appropriate to the system in question. Most of the EWS commonly applied in ecology have been studied in the context of one specific type of regime shift (the type brought on by a saddle‐node bifurcation, at which one stable equilibrium point collides with an unstable equilibrium and disappears) under one particular perturbation scheme (temporally uncorrelated noise that perturbs the net population growth rate in a density independent way). Whether and when these EWS can be applied to other ecological situations remains relatively unknown, and certainly underappreciated. We study a range of models with different types of dynamical transitions (including rapid regime shifts) and several perturbation schemes (density‐dependent uncorrelated or temporally‐correlated noise) and test the ability of EWS to warn of an approaching transition. We also test the sensitivity of our results to the amount of available pre‐transition data and various decisions that must be made in the analysis (i.e. the rolling window size and smoothing bandwidth used to compute the EWS). We find that EWS generally work well to signal an impending saddle‐node bifurcation, regardless of the autocorrelation or intensity of the noise. However, EWS do not reliably appear as expected for other types of transition. EWS were often very sensitive to the length of the pre‐transition time series analyzed, and usually less sensitive to other decisions. We conclude that the EWS perform well for saddle‐node bifurcation in a range of noise environments, but different methods should be used to predict other types of regime shifts. As a consequence, knowledge of the mechanism behind a possible regime shift is needed before EWS can be used to predict it.     

Heteroskedasticity as a leading indicator of desertification in spatially explicit data

Regime shifts are abrupt transitions between alternate ecosystem states including desertification in arid regions due to drought or overgrazing. Regime shifts may be preceded by statistical anomalies such as increased autocorrelation, indicating declining resilience and warning of an impending shift. Tests for conditional heteroskedasticity, a type of clustered variance, have proven powerful leading indicators for regime shifts in time series data, but an analogous indicator for spatial data has not been evaluated. A spatial analog for conditional heteroskedasticity might be especially useful in arid environments where spatial interactions are critical in structuring ecosystem pattern and process. We tested the efficacy of a test for spatial heteroskedasticity as a leading indicator of regime shifts with simulated data from spatially extended vegetation models with regular and scale‐free patterning. These models simulate shifts from extensive vegetative cover to bare, desert‐like conditions. The magnitude of spatial heteroskedasticity increased consistently as the modeled systems approached a regime shift from vegetated to desert state. Relative spatial autocorrelation, spatial heteroskedasticity increased earlier and more consistently. We conclude that tests for spatial heteroskedasticity can contribute to the growing toolbox of early warning indicators for regime shifts analyzed with spatially explicit data.     

Global regime shift dynamics of catastrophic sea urchin overgrazing

A pronounced, widespread and persistent regime shift among marine ecosystems is observable on temperate rocky reefs as a result of sea urchin overgrazing. Here, we empirically define regime-shift dynamics for this grazing system which transitions between productive macroalgal beds and impoverished urchin barrens. Catastrophic in nature, urchin overgrazing in a well-studied Australian system demonstrates a discontinuous regime shift, which is of particular management concern as recovery of desirable macroalgal beds requires reducing grazers to well below the initial threshold of overgrazing. Generality of this regime-shift dynamic is explored across 13 rocky reef systems (spanning 11 different regions from both hemispheres) by compiling available survey data (totalling 10 901 quadrats surveyed in situ) plus experimental regime-shift responses (observed during a total of 57 in situ manipulations). The emergent and globally coherent pattern shows urchin grazing to cause a discontinuous ‘catastrophic’ regime shift, with hysteresis effect of approximately one order of magnitude in urchin biomass between critical thresholds of overgrazing and recovery. Different life-history traits appear to create asymmetry in the pace of overgrazing versus recovery. Once shifted, strong feedback mechanisms provide resilience for each alternative state thus defining the catastrophic nature of this regime shift. Importantly, human-derived stressors can act to erode resilience of desirable macroalgal beds while strengthening resilience of urchin barrens, thus exacerbating the risk, spatial extent and irreversibility of an unwanted regime shift for marine ecosystems.     

The effect of climate change on the resilience of ecosystems with adaptive spatial pattern formation

In a rapidly changing world, quantifying ecosystem resilience is an important challenge. Historically, resilience has been defined via models that do not take spatial effects into account. These systems can only adapt via uniform adjustments. In reality, however, the response is not necessarily uniform, and can lead to the formation of (self‐organised) spatial patterns – typically localised vegetation patches. Classical measures of resilience cannot capture the emerging dynamics in spatially self‐organised systems, including transitions between patterned states that have limited impact on ecosystem structure and productivity. We present a framework of interlinked phase portraits that appropriately quantifies the resilience of patterned states, which depends on the number of patches, the distances between them and environmental conditions. We show how classical resilience concepts fail to distinguish between small and large pattern transitions, and find that the variance in interpatch distances provides a suitable indicator for the type of imminent transition. Subsequently, we describe the dependency of ecosystem degradation based on the rate of climatic change: slow change leads to sporadic, large transitions, whereas fast change causes a rapid sequence of smaller transitions. Finally, we discuss how pre‐emptive removal of patches can minimise productivity losses during pattern transitions, constituting a viable conservation strategy.     

Alternative stable equilibria and critical thresholds created by fire regimes and plant responses in a fire‐prone community

Wildfire is a dominant disturbance in many ecosystems, and fire frequency and intensity are being altered as climates change. Through effects on mortality and regeneration, fire affects plant community composition, species richness, and carbon cycling. In some regions, changes to fire regimes could result in critical, non‐reversible transitions from forest to non‐forested states. For example, the Klamath ecoregion (northwest United States) supports extensive conifer forests that are initially replaced by hardwood chaparral following high‐severity fire, but eventually return to conifer forest during the fire‐free periods. Climate change alters both the fire regime and post‐fire recovery dynamics, potentially causing shrubland to persist as a stable (i.e. self‐renewing) vegetation stage, rather than an ephemeral stage. Here, we present a theoretical investigation of how changes in plant traits and fire regimes can alter the stability of communities in forest‐shrub systems such as the Klamath. Our model captures the key characteristics of the system, including life‐stage‐specific responses to disturbance and asymmetrical competitive interactions. We assess vegetation stability via invasion analysis, and conclude that portions of the landscape that are currently forested also can be stable as shrubland. We identify parameter thresholds where community equilibria change from stable to unstable, and show how these thresholds may shift in response to changes in life‐history or environmental parameters. For instance, conifer maturation rates are expected to decrease as aridity increases under climate change, and our model shows that this reduction decreases the fire frequencies at which forests become unstable. Increases in fire activity sufficient to destabilize forest communities are likely to occur in more arid future climates. If widespread, this would result in reduced carbon stocks and a positive feedback to climate change. Changes in stability may be altered by management practices.     

Environmental drivers of the metacommunity structure of insects on the surface of tropical streams of the Amazon

Understanding how species are distributed according to environmental and spatial variation is still one of the main issues in community ecology. We analysed the responses of semiaquatic bugs (Gerromorpha: Hemiptera) to environmental and spatial processes considered drivers of metacommunity structure in Amazonian streams. We tested the hypotheses that environmental variables determine the metacommunity structure and that the spatial structures, both dendritic and overland, are not representative of the metacommunity structure. Environmental variables and semiaquatic bugs were collected from 39 stream sites. Spatial variables were calculated in two configurations – overland and hydrographic distances between streams. We used partial redundancy analysis to test the relative importance of environment and space on the metacommunity structure, considering the two spatial configurations separately. The environmental variables were the metacommunity drivers in tropical streams, mainly structured by the depth, canopy, embeddedness and slope variables. Our results also indicate little or no dispersion limitation, as no spatial patterns were found. Thus, environmental selection determines the semiaquatic bugs' metacommunity structure due to the achievement of optimal habitats through dispersal. We also believe that dispersion cannot be ruled out as a metacommunity driver, since the peculiarities of the group show seasonal changes in dispersion ability, and spatial patterns may occur under different temporal scales.     

Alternative (un)stable states in a stochastic predator–prey model

Stochastic models sometimes behave qualitatively differently from their deterministic analogues. We explore the implications of this in ecosystems that shift suddenly from one state to another. This phenomenon is usually studied through deterministic models with multiple stable equilibria under a single set of conditions, with stability defined through linear stability analysis. However, in stochastic systems, some unstable states can trap stochastic dynamics for long intervals, essentially masquerading as additional stable states. Using a predator–prey model, we demonstrate that this effect is sufficient to make a stochastic system with one stable state exhibit the same characteristics as an analogous system with alternative stable states. Although this result is surprising with respect to how stability is defined by standard analyses, we show that it is well-anticipated by an alternative approach based on the system's “quasi-potential.” Broadly, understanding the risk of sudden state shifts will require a more holistic understanding of stability in stochastic systems.     

Tipping points in tropical tree cover: linking theory to data

It has recently been found that the frequency distribution of remotely sensed tree cover in the tropics has three distinct modes, which seem to correspond to forest, savanna, and treeless states. This pattern has been suggested to imply that these states represent alternative attractors, and that the response of these systems to climate change would be characterized by critical transitions and hysteresis. Here, we show how this inference is contingent upon mechanisms at play. We present a simple dynamical model that can generate three alternative tree cover states (forest, savanna, and a treeless state), based on known mechanisms, and use this model to simulate patterns of tree cover under different scenarios. We use these synthetic data to show that the hysteresis inferred from remotely sensed tree cover patterns will be inflated by spatial heterogeneity of environmental conditions. On the other hand, we show that the hysteresis inferred from satellite data may actually underestimate real hysteresis in response to climate change if there exists a positive feedback between regional tree cover and precipitation. Our results also indicate that such positive feedback between vegetation and climate should cause direct shifts between forest and a treeless state (rather than through an intermediate savanna state) to become more likely. Finally, we show how directionality of historical change in conditions may bias the observed relationship between tree cover and environmental conditions.