Rising variance: a leading indicator of ecological transition

Regime shifts are substantial, long-lasting reorganizations of complex systems, such as ecosystems. Large ecosystem changes such as eutrophication, shifts among vegetation types, degradation of coral reefs and regional climate change often come as surprises because we lack leading indicators for regime shifts. Increases in variability of ecosystems have been suggested to foreshadow ecological regime shifts. However, it may be difficult to discern variability due to impending regime shift from that of exogenous drivers that affect the ecosystem. We addressed this problem using a model of lake eutrophication. Lakes are subject to fluctuations in recycling associated with regime shifts, as well as fluctuating nutrient inputs. Despite the complications of noisy inputs, increasing variability of lake-water phosphorus was discernible prior to the shift to eutrophic conditions. Simulations show that rising standard deviation (SD) could signal impending shifts about a decade in advance. The rising SD was detected by studying variability around predictions of a simple time-series model, and did not depend on detailed knowledge of the actual ecosystem dynamics.     

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.     

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.     

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.     

Leading indicators of phytoplankton transitions caused by resource competition

Many important transitions in phytoplankton composition of lakes and oceans are related to shifts in nutrient supply ratios. Some phytoplankton transitions, such as cyanobacteria blooms in freshwater supplies and red tides in coastal oceans, are important for aquatic resource management. Therefore, it would be useful to have leading indicators which precede phytoplankton shifts and could be readily monitored in the field. We investigated potential indicators using a well-understood model of phytoplankton dynamics parameterized to mimic the transition toward cyanobacteria blooms in freshwater lakes. In stationary distributions, performance of the indicators depends on whether the species are capable of stable coexistence over a certain range of nutrient inputs. In transient simulations, however, indicators show consistent responses regardless of the possibility of stable coexistence. Leading indicators occurring 10 to 40 days prior to species shift include shift of lag-1 autoregression coefficient toward 0, low standard deviation, fluctuating skewness, and high kurtosis. These responses are different from those reported for critical transitions such as fold bifurcations. Thus, the indicators reveal clues to the mechanisms of important ecosystem transitions. In practice, indicators should be measured for multiple ecosystem variables, and interpretation of the indicators should be guided by experiments and mechanistic site-specific models to help resolve potential ambiguities.     

Conditional heteroscedasticity as a leading indicator of ecological regime shifts

Regime shifts are massive, often irreversible, rearrangements of nonlinear ecological processes that occur when systems pass critical transition points. Ecological regime shifts sometimes have severe consequences for human well-being, including eutrophication in lakes, desertification, and species extinctions. Theoretical and laboratory evidence suggests that statistical anomalies may be detectable leading indicators of regime shifts in ecological time series, making it possible to foresee and potentially avert incipient regime shifts. Conditional heteroscedasticity is persistent variance characteristic of time series with clustered volatility. Here, we analyze conditional heteroscedasticity as a potential leading indicator of regime shifts in ecological time series. We evaluate conditional heteroscedasticity by using ecological models with and without four types of critical transition. On approaching transition points, all time series contain significant conditional heteroscedasticity. This signal is detected hundreds of time steps in advance of the regime shift. Time series without regime shifts do not have significant conditional heteroscedasticity. Because probability values are easily associated with tests for conditional heteroscedasticity, detection of false positives in time series without regime shifts is minimized. This property reduces the need for a reference system to compare with the perturbed system.     

Precursors of state transitions in stochastic systems with delay

Ecosystem dynamics may exhibit alternative stable states induced by positive feedbacks between the state of the system and environmental drivers. Bistable systems are prone to abrupt shifts from one state to another in response to even small and gradual changes in external drivers. These transitions are often catastrophic and difficult to predict by analyzing the mean state of the system. Indicators of the imminent occurrence of phase transitions can serve as important tools to warn ecosystem managers about an imminent transition before the bifurcation point is actually reached. Thus, leading indicators of phase transitions can be used either to prepare for or to prevent the occurrence of a shift to the other state. In recent years, theories of leading indicators of ecosystem shift have been developed and applied to a variety of ecological models and geophysical time series. It is unclear, however, how some of these indicators would perform in the case of systems with a delay. Here, we develop a theoretical framework for the investigation of precursors of state shift in the presence of drivers acting with a delay. We discuss how the effectiveness of leading indicators of state shift based on rising variance may be affected by the presence of delays. We apply this framework to an ecological model of desertification in arid grasslands.     

Marine ecosystem regime shifts: challenges and opportunities for ecosystem-based management

Regime shifts have been observed in marine ecosystems around the globe. These phenomena can result in dramatic changes in the provision of ecosystem services to coastal communities. Accounting for regime shifts in management clearly requires integrative, ecosystem-based management (EBM) approaches. EBM has emerged as an accepted paradigm for ocean management worldwide, yet, despite the rapid and intense development of EBM theory, implementation has languished, and many implemented or proposed EBM schemes largely ignore the special characteristics of regime shifts. Here, we first explore key aspects of regime shifts that are of critical importance to EBM, and then suggest how regime shifts can be better incorporated into EBM using the concept of integrated ecosystem assessment (IEA). An IEA uses approaches that determine the likelihood that ecological or socio-economic properties of systems will move beyond or return to acceptable bounds as defined by resource managers and policy makers. We suggest an approach for implementing IEAs for cases of regime shifts where the objectives are either avoiding an undesired state or returning to a desired condition. We discuss the suitability and short-comings of methods summarizing the status of ecosystem components, screening and prioritizing potential risks, and evaluating alternative management strategies. IEAs are evolving as an EBM approach that can address regime shifts; however, advances in statistical, analytical and simulation modelling are needed before IEAs can robustly inform tactical management in systems characterized by regime shifts.     

Early detection of ecosystem regime shifts: a multiple method evaluation for management application

Critical transitions between alternative stable states have been shown to occur across an array of complex systems. While our ability to identify abrupt regime shifts in natural ecosystems has improved, detection of potential early-warning signals previous to such shifts is still very limited. Using real monitoring data of a key ecosystem component, we here apply multiple early-warning indicators in order to assess their ability to forewarn a major ecosystem regime shift in the Central Baltic Sea. We show that some indicators and methods can result in clear early-warning signals, while other methods may have limited utility in ecosystem-based management as they show no or weak potential for early-warning. We therefore propose a multiple method approach for early detection of ecosystem regime shifts in monitoring data that may be useful in informing timely management actions in the face of ecosystem change.     

Marine regime shifts: drivers and impacts on ecosystems services

Marine ecosystems can experience regime shifts, in which they shift from being organized around one set of mutually reinforcing structures and processes to another. Anthropogenic global change has broadly increased a wide variety of processes that can drive regime shifts. To assess the vulnerability of marine ecosystems to such shifts and their potential consequences, we reviewed the scientific literature for 13 types of marine regime shifts and used networks to conduct an analysis of co-occurrence of drivers and ecosystem service impacts. We found that regime shifts are caused by multiple drivers and have multiple consequences that co-occur in a non-random pattern. Drivers related to food production, climate change and coastal development are the most common co-occurring causes of regime shifts, while cultural services, biodiversity and primary production are the most common cluster of ecosystem services affected. These clusters prioritize sets of drivers for management and highlight the need for coordinated actions across multiple drivers and scales to reduce the risk of marine regime shifts. Managerial strategies are likely to fail if they only address well-understood or data-rich variables, and international cooperation and polycentric institutions will be critical to implement and coordinate action across the scales at which different drivers operate. By better understanding these underlying patterns, we hope to inform the development of managerial strategies to reduce the risk of high-impact marine regime shifts, especially for areas of the world where data are not available or monitoring programmes are not in place.     

干旱区生态系统稳态转换及其预警信号——基于景观格局特征的识别方法

在日益加剧的气候变化和土地开垦、放牧等人类活动干扰下,具有多稳态特征的干旱区生态系统可能会经历从相对健康状态到退化状态的稳态转换,导致生态系统的功能下降。早期预警信号的识别是生态系统稳态转换研究的热点,也是管理实践中防止生态系统退化的关键环节。以往预警信号研究聚焦于通用信号如自相关性、方差等统计学指标,然而这些指标对于具有特定机制的干旱区生态系统可能并不适用。基于干旱区景观格局特征所发展起来的空间指标为生态系统稳态转换提供了独特的空间视角,对于理解干旱区生态系统退化过程和机理具有科学意义和实践价值。介绍了干旱区生态系统稳态转换现象及其转换机制;聚焦景观生态学的指标和方法,从空间视角总结基于干旱区景观格局特征的关键预警指标(植被覆盖度、植被斑块形态、植被斑块大小频率分布和水文连通性等),重点剖析这些关键指标的概念、量化方法、识别特征及其实践应用;最后针对指标的优势和局限性对未来的研究方向进行展望,包括发掘潜在景观指标,加强干旱区生态系统变化的多种驱动要素的相互作用机制研究,开展多时空尺度的实证研究,构建生态系统稳态转换预警信号的整体分析框架,以及加强指标阈值的量化研究等方面。     

Spatial variance and spatial skewness: leading indicators of regime shifts in spatial ecological systems

Ecosystems can undergo large-scale changes in their states, known as catastrophic regime shifts, leading to substantial losses to services they provide to humans. These shifts occur rapidly and are difficult to predict. Several early warning signals of such transitions have recently been developed using simple models. These studies typically ignore spatial interactions, and the signal provided by these indicators may be ambiguous. We employ a simple model of collapse of vegetation in one and two spatial dimensions and show, using analytic and numerical studies, that increases in spatial variance and changes in spatial skewness occur as one approaches the threshold of vegetation collapse. We identify a novel feature, an increasing spatial variance in conjunction with a peaking of spatial skewness, as an unambiguous indicator of an impending regime shift. Once a signal has been detected, we show that a quick management action reducing the grazing activity is needed to prevent the collapse of vegetated state. Our results show that the difficulties in obtaining the accurate estimates of indicators arising due to lack of long temporal data can be alleviated when high-resolution spatially extended data are available. These results are shown to hold true independent of various details of model or different spatial dispersal kernels such as Gaussian or heavily fat tailed. This study suggests that spatial data and monitoring multiple indicators of regime shifts can play a key role in making reliable predictions on ecosystem stability and resilience. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

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.     

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.     

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).     

Conditional Heteroskedasticity Forecasts Regime Shift in a Whole-Ecosystem Experiment

Regime shifts in stochastic ecosystem models are often preceded by early warning signals such as increased variance and increased autocorrelation in time series. There is considerable theoretical support for early warning signals, but there is a critical lack of field observations to test the efficacy of early warning signals at spatial and temporal scales relevant for ecosystem management. Conditional heteroskedasticity is persistent periods of high and low variance that may be a powerful leading indicator of regime shift. We evaluated conditional heteroskedasticity as an early warning indicator by applying moving window conditional heteroskedasticity tests to time series of chlorophyll-a and fish catches derived from a whole-lake experiment designed to create a regime shift. There was significant conditional heteroskedasticity at least a year prior to the regime shift in the manipulated lake but there was no significant conditional heteroskedasticity in an adjacent reference lake. Conditional heteroskedasticity was an effective leading indicator of regime shift for the ecosystem manipulation.     

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.     

Regime shifts: catastrophic responses of ecosystems to human impacts

Evidence of abrupt changes in ecosystem states, such as sudden eutrophication in lakes, has been increasingly reported in a variety of aquatic and terrestrial systems. Ecosystems may have more than one state with a self-stabilizing mechanism, so that a shift between states does not occur frequently and is not readily reversible. These big changes are termed regime shifts where often one state is preferred over another. Thus, regime shifts are problematic for ecosystem managers, and the need exists for studies that lead to the identification of thresholds of key variables that trigger regime shifts. Regime shifts are currently difficult to predict and in many cases may be caused by the human pursuit of efficiency in land and water productivity in the last few decades. Here I briefly introduce a theoretical approach to predict the shift between a clear-water state and a turbid state in lakes, the best-studied example of regime shifts. This paper also discusses alternative states in other natural systems besides ecosystems to draw more attention to the research currently being performed on regime shifts. Motomi Genkai-Kato is the recipient of the 10th Denzaburo Miyadi Award.     

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.     

Architecture of collapse: regime shift and recovery in an hierarchically structured marine ecosystem

By the late 20th century, a series of events or ‘natural experiments’, for example the depletion of apex predators, extreme eutrophication and blooms of invasive species, had suggested that the Black Sea could be considered as a large ecosystem ‘laboratory’. The events resulted in regime shifts cascading through all trophic levels, disturbing ecosystem functioning and damaging the water environment. Causal pathways by which the external (hydroclimate, overfishing) and internal (food web interactions) drivers provoke regime shifts are investigated. Statistical data analyses supported by an interpretative framework based on hierarchical ecosystem theory revealed mechanisms of hierarchical incorporation of environmental factors into the ecosystem. Evidence links Atlantic teleconnections to Black Sea hydroclimate, which together with fishing shapes variability in fish stocks. The hydroclimatic signal is conveyed through the food web via changes in productivity at all levels, to planktivorous fish. Fluctuating fish abundance is believed to induce a lagged change in competitor jelly plankton that cascades down to phytoplankton and influences water quality. Deprived of the stabilising role of apex predators, the Black Sea's hierarchical ecosystem organisation is susceptible to both environmental and anthropogenic stresses, and increased fishing makes fish stock collapses highly probable. When declining stocks are confronted with burgeoning fishing effort associated with the inability of fishery managers and decision‐makers to adapt rapidly to changes in fish abundance, there is overfishing and stock collapse. Management procedures are ineffective at handling complex phenomena such as ecosystem regime shifts because of the shortage of suitable explanatory models. The proposed concepts and models reported here relate the hydroclimate, overfishing and invasive species to shifts in ecosystem functioning and water quality, unravelling issues such as the causality of ecosystem interactions and mechanisms and offering potential for finding ways to reverse regime shifts. We advocate a management approach aiming at restoring ecosystem hierarchy that might mitigate the costly consequences of regime shifts.