Connectivity,regime shifts and the resilience of coral reefs

Connectivity of larvae among metapopulations in open marine systems can be a double-edged sword, allowing for the colonization and replenishment of both desirable and undesirable elements of interacting species-rich assemblages. This article studies the effect of recruitment by coral and macroalgae on the resilience of grazed reef ecosystems. In particular, we focus on how larval connectivity affects regime shifts between alternative assemblages that are dominated either by corals or by macroalgae. Using a model with bistability dynamics, we show that recruitment of coral larvae erodes the resilience of a macroalgae-dominated ecosystem when grazing is high, but has negligible effect when grazing is low. Conversely, recruitment by macroalgae erodes the resilience of a coral-dominated ecosystem when grazing is low, leading to a regime shift to macroalgae. Thus, spillover of coral recruits from highly protected areas will not restore coral cover or prevent flips to macroalgae in the surrounding seascape if grazing levels in these areas are depleted, but may be pivotal for re-building coral populations if grazing is high. Fishing restrictions and the re-introduction of herbivores should therefore be a prime conservation objective for preventing undesirable regime shifts. Connectivity by some components of coral reef assemblages (e.g., macroalgae, pathogens, crown-of-thorns starfish) may be detrimental to sustaining reefs, especially where overfishing and other drivers have eroded their resilience, making them more vulnerable to a regime shift.     

Theoretical basis for predicting climate-induced abrupt shifts in the oceans

Among the responses of marine species and their ecosystems to climate change, abrupt community shifts (ACSs), also called regime shifts, have often been observed. However, despite their effects for ecosystem functioning and both provisioning and regulating services, our understanding of the underlying mechanisms involved remains elusive. This paper proposes a theory showing that some ACSs originate from the interaction between climate-induced environmental changes and the species ecological niche. The theory predicts that a substantial stepwise shift in the thermal regime of a marine ecosystem leads indubitably to an ACS and explains why some species do not change during the phenomenon. It also explicates why the timing of ACSs may differ or why some studies may detect or not detect a shift in the same ecosystem, independently of the statistical method of detection and simply because they focus on different species or taxonomic groups. The present theory offers a way to predict future climate-induced community shifts and their potential associated trophic cascades and amplifications.     

Forecasting the limits of resilience: integrating empirical research with theory

Despite the increasing evidence of drastic and profound changes in many ecosystems, often referred to as regime shifts, we have little ability to understand the processes that provide insurance against such change (resilience). Modelling studies have suggested that increased variance may foreshadow a regime shift, but this requires long-term data and knowledge of the functional links between key processes. Field-based research and ground-truthing is an essential part of the heuristic that marries theoretical and empirical research, but experimental studies of resilience are lagging behind theory, management and policy requirements. Empirically, ecological resilience must be understood in terms of community dynamics and the potential for small shifts in environmental forcing to break the feedbacks that support resilience. Here, we integrate recent theory and empirical data to identify ways we might define and understand potential thresholds in the resilience of nature, and thus the potential for regime shifts, by focusing on the roles of strong and weak interactions, linkages in meta-communities, and positive feedbacks between these and environmental drivers. The challenge to theoretical and field ecologists is to make the shift from hindsight to a more predictive science that is able to assist in the implementation of ecosystem-based management.     

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.     

Contrasting energy pathways at the community level as a consequence of regime shifts

Ecological regime shifts typically result in abrupt changes in ecosystem structure through several trophic levels, which leads to rapid ecosystem reconfiguration between regimes. An interesting aspect of the impact of regime shift is that alternative regimes may induce distinct shifts in energy pathways; these have been less tested than structural changes. This paper addresses this by using stable isotopes to establish the energy pathways in fish communities. We specifically focus on the impact of regime shift on changes of the energy pathways, and how the magnitude and direction of these changes affect the local community. We found that energy pathways significantly varied among the planktivorous, benthivorous, and piscivorous trophic guilds as a result of the alternative regimes. The regime shift from a clear to a turbid state altered the food web towards planktonic energy pathways and truncated food chain length, which is indicative of less ecological efficiency. This was confirmed by the adaptive foraging strategies of prevalent omnivores in the current communities. These structural and functional characteristics of trophic interactions might not facilitate classic trophic cascading effects in such a turbid regime and suppress the system’s response to environmental changes, e.g., nutrient loading, and restoration efforts in turbid to clear water regime shifts.     

Regime Shifts in the Anthropocene: Drivers,Risks, and Resilience

Many ecosystems can experience regime shifts: surprising, large and persistent changes in the function and structure of ecosystems. Assessing whether continued global change will lead to further regime shifts, or has the potential to trigger cascading regime shifts has been a central question in global change policy. Addressing this issue has, however, been hampered by the focus of regime shift research on specific cases and types of regime shifts. To systematically assess the global risk of regime shifts we conducted a comparative analysis of 25 generic types of regime shifts across marine, terrestrial and polar systems; identifying their drivers, and impacts on ecosystem services. Our results show that the drivers of regime shifts are diverse and co-occur strongly, which suggests that continued global change can be expected to synchronously increase the risk of multiple regime shifts. Furthermore, many regime shift drivers are related to climate change and food production, whose links to the continued expansion of human activities makes them difficult to limit. Because many regime shifts can amplify the drivers of other regime shifts, continued global change can also be expected to increase the risk of cascading regime shifts. Nevertheless, the variety of scales at which regime shift drivers operate provides opportunities for reducing the risk of many types of regime shifts by addressing local or regional drivers, even in the absence of rapid reduction of global drivers.     

Compensatory dynamics and the stability of phytoplankton biomass during four decades of eutrophication and oligotrophication

The link between compensatory dynamics and regime shifts is not well understood. We analyse a regime shift in phytoplankton in a large lake with respect to: (1) environmental forcing and (2) the type of dynamics (compensatory or synchronous) between phytoplankton groups. The regime shift in phytoplankton was related to gradual changes in nutrient levels, but unrelated to an almost concurrent shift in climatic conditions. The relationship between total phytoplankton biomass and phosphorus concentrations was sigmoid. Trajectories of phytoplankton biomass and community dynamics suggest that eutrophication effects can successfully be reversed when management efforts decrease nutrient loading to a level sufficiently low to overcome community resilience. The regime shift was associated with a loss of biomass compensation and compensatory dynamics among the phytoplankton groups. This suggests that the type of interactions is important for a better understanding of the existence and shape of nonlinear responses of phytoplankton biomass to environmental change.     

Tracking unstable states: ecosystem dynamics in a changing world

Ecological systems can show complex and sometimes abrupt responses to environmental change, with important implications for their resilience. Theories of alternate stable states have been used to predict regime shifts of ecosystems as equilibrium responses to sufficiently slow environmental change. The actual rate of environmental change is a key factor affecting the response, yet we are still lacking a non-equilibrium theory that explicitly considers the influence of this rate of environmental change. We present a metacommunity model of predator–prey interactions displaying multiple stable states, and we impose an explicit rate of environmental change in habitat quality (carrying capacity) and connectivity (dispersal rate). We study how regime shifts depend on the rate of environmental change and compare the outcome with a stability analysis in the corresponding constant environment. Our results reveal that in a changing environment, the community can track states that are unstable in the constant environment. This tracking can lead to regime shifts, including local extinctions, that are not predicted by alternative stable state theory. In our metacommunity, tracking unstable states also controls the maintenance of spatial heterogeneity and spatial synchrony. Tracking unstable states can also lead to regime shifts that may be reversible or irreversible. Our study extends current regime shift theories to integrate rate-dependent responses to environmental change. It reveals the key role of unstable states for predicting transient dynamics and long-term resilience of ecological systems to climate change.     

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.     

浅水湖泊生态系统稳态转换的阈值判定方法

浅水湖泊生态系统对人类干扰的反应会随着干扰力度的改变或增强而出现突然的变化,即发生稳态转换;对其机理和驱动机制的揭示将有助于对湖泊富营养化的控制及恢复.基于“多稳态”理论的稳态转换研究已广泛开展,但对浅水湖泊生态系统稳态转换的驱动机制结论各异,采用的阈值判定方法相差很大,主要有实验观测、模型模拟和统计分析3种.实验观测多关注少数特定指标,指标筛选过程复杂且工作量大;模型模拟虽能从较为全面的尺度上理解生态系统稳态变化的特征和主要机理过程,但在模型误差和不确定性的处理等问题上尚存在不足;统计分析方法基于对长时间序列数据的统计变化规律分析,用以判断或者预警稳态转换现象的发生,是目前最为常用的方法.目前稳态转换领域的研究大都是对已发生的稳态转换进行机制分析或过程反演,对未来预测与预警的问题仍然亟需加强.     

Early warning signals of demographic regime shifts in invading populations

The Allee effect can cause alternative stable states in population abundance of invasive species. Sudden eruption of invading populations from low to high abundance may be viewed as a regime shift from one alternative state to another. Previous research proposed several types of early warning signals to predict regime shifts in ecological systems such as polluted lakes and semiarid grasslands. This paper explores theoretically the potential of such indicators in predicting demographic regime shifts of invading populations. I analyzed a stochastic differential equation model for the population dynamics of an invasive species subject to Allee effects and propagule pressure. Diffusion approximation to the stochastic model suggests that persistent propagule pressure makes demographic regime shifts inevitable, but Allee effects can lengthen the mean time until regime shifts virtually indefinitely. To compare the potential of indicators, I examined standard deviation, skewness, and estimated return rates of longitudinal population abundance. I found that standard deviation showed a distinct increase as regime shifts became more likely, but skewness and return rates showed no clear trends. This result suggests that standard deviation might be a useful warning signal for forecasting an impending demographic regime shift of invading populations during the period when their abundance is still low.     

Using mean first passage times to quantify equilibrium resilience in perturbed intraguild predation systems

Regime shift inducibility depends on equilibrium resilience, which depends on species interactions. When species interactions include intraguild predation (IGP), integrated pest management may induce regime shifts because enhancing the abundance of intraguild predators simultaneously increases competition with, and predation on, invasive prey. To explore the dynamical consequences of such manipulations, we use a bistable, deterministic IGP model with stochastic removals that perturb invader density from the high-density equilibrium. We quantify the combined effects of IGP and such perturbations in terms of mean first passage times (MFPTs) to target invader densities such as thresholds between regimes. Analytical MFPTs compare favorably with those generated by Monte Carlo numerical solutions of the stochastically perturbed IGP model. MFPTs can therefore usefully quantify equilibrium resilience in terms of perturbation schedules. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Migration Amidst Social-Ecological Regime Shift: The Search for Stability in Garífuna Villages of Northern Honduras

Environmental migration, in its different forms, is an aspiration toward stability domains amidst dynamic system change. This paper assesses critical system relationships that couple human and natural systems and change in due course of a regime shift affecting Garífuna villages in Northern Honduras. The specified resilience of these relationships influences the course that migration takes after a flooding event. In impacted villages, migration is a mechanism for demographic fragmentation, ‘downgrades’ livelihood chains, and reinforces a class divide. Villages systems that experience a shift to uninhabitable and unproductive state spaces become shallow stability domains and consequently, perpetual exporters of migrants over an extended period of time. In the end, migration itself is a cascading aspect of a regime shift that is both ecological and social, forced and chosen.     

A new approach for rapid detection of nearby thresholds in ecosystem time series

Massive changes to ecosystems sometimes cross thresholds from which recovery can be difficult, expensive and slow. These thresholds are usually discovered in post hoc analyses long after the event occurred. Anticipating these changes prior to their occurrence could give managers a chance to intervene. Here we present a novel approach for anticipating ecosystem thresholds that combines resilience indicators with Quickest detection of change points. Unlike existing methods, the Quickest detection method is updated every time a data point arrives, and minimizes the time to detect an approaching threshold given the users’ tolerance for false alarms. The procedure accurately detected an impending regime shift in an experimentally manipulated ecosystem. An ecosystem model was used to determine if the method can detect an approaching threshold soon enough to prevent a regime shift. When the monitored variable was directly involved in the interaction that caused the regime shift, detection was quick enough to avert collapse. When the monitored variable was only indirectly linked to the critical transition, detection came too late. The procedure is useful for assessing changes in resilience as ecosystems approach thresholds. However some thresholds cannot be detected in time to prevent regime shifts, and surprises will be inevitable in ecosystem management.     

Slow recovery from perturbations as a generic indicator of a nearby catastrophic shift

The size of the basin of attraction in ecosystems with alternative stable states is often referred to as "ecological resilience." Ecosystems with a low ecological resilience may easily be tipped into an alternative basin of attraction by a stochastic event. Unfortunately, it is very difficult to measure ecological resilience in practice. Here we show that the rate of recovery from small perturbations (sometimes called "engineering resilience") is a remarkably good indicator of ecological resilience. Such recovery rates decrease as a catastrophic regime shift is approached, a phenomenon known in physics as "critical slowing down." We demonstrate the robust occurrence of critical slowing down in six ecological models and outline a possible experimental approach to quantify differences in recovery rates. In all the models we analyzed, critical slowing down becomes apparent quite far from a threshold point, suggesting that it may indeed be of practical use as an early warning signal. Despite the fact that critical slowing down could also indicate other critical transitions, such as a stable system becoming oscillatory, the robustness of the phenomenon makes it a promising indicator of loss of resilience and the risk of upcoming regime shifts in a system.     

Ecological Network Indicators of Ecosystem Status and Change in the Baltic Sea

Several marine ecosystems under anthropogenic pressure have experienced shifts from one ecological state to another. In the central Baltic Sea, the regime shift of the 1980s has been associated with food-web reorganization and redirection of energy flow pathways. These long-term dynamics from 1974 to 2006 have been simulated here using a food-web model forced by climate and fishing. Ecological network analysis was performed to calculate indices of ecosystem change. The model replicated the regime shift. The analyses of indicators suggested that the system’s resilience was higher prior to 1988 and lower thereafter. The ecosystem topology also changed from a web-like structure to a linearized food-web.     

Coral–macroalgal phase shifts or reef resilience: links with diversity and functional roles of herbivorous fishes on the Great Barrier Reef

Changes from coral to macroalgal dominance following disturbances to corals symbolize the global degradation of coral reefs. The development of effective conservation measures depends on understanding the causes of such phase shifts. The prevailing view that coral–macroalgal phase shifts commonly occur due to insufficient grazing by fishes is based on correlation with overfishing and inferences from models and small-scale experiments rather than on long-term quantitative field studies of fish communities at affected and resilient sites. Consequently, the specific characteristics of herbivorous fish communities that most promote reef resilience under natural conditions are not known, though this information is critical for identifying vulnerable ecosystems. In this study, 11 years of field surveys recorded the development of the most persistent coral–macroalgal phase shift (>7 years) yet observed on Australia’s Great Barrier Reef (GBR). This shift followed extensive coral mortality caused by thermal stress (coral bleaching) and damaging storms. Comparisons with two similar reefs that suffered similar disturbances but recovered relatively rapidly demonstrated that the phase shift occurred despite high abundances of one herbivore functional group (scraping/excavating parrotfishes: Labridae). However, the shift was strongly associated with low fish herbivore diversity and low abundances of algal browsers (predominantly Siganidae) and grazers/detritivores (Acanthuridae), suggesting that one or more of these factors underpin reef resilience and so deserve particular protection. Herbivorous fishes are not harvested on the GBR, and the phase shift was not enhanced by unusually high nutrient levels. This shows that unexploited populations of herbivorous fishes cannot ensure reef resilience even under benign conditions and suggests that reefs could lose resilience under relatively low fishing pressure. Predictions of more severe and widespread coral mortality due to global climate change emphasize the need for more effective identification and protection of ecosystem components that are critical for the prevention of coral reef phase shifts.     

Butyrate Production Pathway Abundances Are Similar in Human and Nonhuman Primate Gut Microbiomes

Over the course of human evolution, shifts in dietary practices such as meat-eating and cooking, have resulted in reduced fiber intake, a trend that has been exaggerated more recently in industrialized populations. Reduced fiber consumption is associated with a loss of gut microbial taxa that degrade fiber, particularly butyrate. Therefore, this dietary shift in humans may have altered the abundance of microbial genes involved in butyrate production. This study uses a gene-targeted alignment approach to quantify the abundance of butyrate production pathway genes from published wild nonhuman primate and human gut metagenomes. Surprisingly, humans have higher diversity and relative abundances of butyrate production pathways compared with all groups of nonhuman primates except cercopithecoids. Industrialized populations of humans also differ only slightly in butyrate pathway abundance from nonindustrialized populations. This apparent resilience of butyrate production pathways to shifts in human diet across both evolutionary and modern populations may signal an evolutionary shift in host–microbe interactions in humans that increased SCFA production. Such a shift could have contributed to meeting the increased energy requirements of humans relative to nonhuman primates.     

Resilience and tipping points of an exploited fish population over six decades

Complex natural systems with eroded resilience, such as populations, ecosystems and socio‐ecological systems, respond to small perturbations with abrupt, discontinuous state shifts, or critical transitions. Theory of critical transitions suggests that such systems exhibit fold bifurcations featuring folded response curves, tipping points and alternate attractors. However, there is little empirical evidence of fold bifurcations occurring in actual complex natural systems impacted by multiple stressors. Moreover, resilience of complex systems to change currently lacks clear operational measures with generic application. Here, we provide empirical evidence for the occurrence of a fold bifurcation in an exploited fish population and introduce a generic measure of ecological resilience based on the observed fold bifurcation attributes. We analyse the multivariate development of Barents Sea cod (Gadus morhua), which is currently the world's largest cod stock, over six decades (1949–2009), and identify a population state shift in 1981. By plotting a multivariate population index against a multivariate stressor index, the shift mechanism was revealed suggesting that the observed population shift was a nonlinear response to the combined effects of overfishing and climate change. Annual resilience values were estimated based on the position of each year in relation to the fitted attractors and assumed tipping points of the fold bifurcation. By interpolating the annual resilience values, a folded stability landscape was fit, which was shaped as predicted by theory. The resilience assessment suggested that the population may be close to another tipping point. This study illustrates how a multivariate analysis, supported by theory of critical transitions and accompanied by a quantitative resilience assessment, can clarify shift mechanisms in data‐rich complex natural systems.     

Nutrient reduction and climate change cause a potential shift from pelagic to benthic pathways in a eutrophic marine ecosystem

The degree to which marine ecosystems may support the pelagic or benthic food chain has been shown to vary across natural and anthropogenic gradients for e.g., in temperature and nutrient availability. Moreover, such external forcing may not only affect the flux of organic matter but could trigger large and abrupt changes, i.e., trophic cascades and ecological regime shifts, which once having occurred may prove potentially irreversible. In this study, we investigate the state and regulatory pathways of the Kattegat; a eutrophied and heavily exploited marine ecosystem, specifically testing for the occurrence of regime shifts and the relative importance of multiple drivers, e.g., climate change, eutrophication and commercial fishing on ecosystem dynamics and trophic pathways. Using multivariate statistics and nonlinear regression on a comprehensive data set, covering abiotic factors and biotic variables across all trophic levels, we here propose a potential regime shift from pelagic to benthic regulatory pathways; a possible first sign of recovery from eutrophication likely triggered by drastic nutrient reductions (involving both nitrogen and phosphorus), in combination with climate‐driven changes in local environmental conditions (e.g., temperature and oxygen concentrations).