Resilience indicators: prospects and limitations for early warnings of regime shifts
Ontology highlight
ABSTRACT:
SUBMITTER: Dakos V
PROVIDER: S-EPMC4247400 | biostudies-literature | 2015 Jan
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Regime shift often results in large, abrupt, and persistent changes in the provision of ecosystem services and can therefore have significant impacts on human wellbeing. Understanding regime shifts has profound implications for ecosystem recovery and management. China's coastal ecosystems have experienced substantial deterioration within the past decades, at a scale and speed the world has never seen before. Yet, information about this coastal ecosystem change from a dynamics perspective is quite limited. In this review, I synthesize existing information on coastal ecosystem regime shifts in China and discuss their interactions and cascading effects. The accumulation of regime shifts in China's coastal ecosystems suggests that the desired system resilience has been profoundly eroded, increasing the potential of abrupt shifts to undesirable states at a larger scale, especially given multiple escalating pressures. Policy and management strategies need to incorporate resilience approaches in order to cope with future challenges and avoid major losses in China's coastal ecosystem services.
| S-EPMC4709358 | biostudies-literature
Project description:Complex natural systems, spanning from individuals and populations to ecosystems and social-ecological systems, often exhibit abrupt reorganizations in response to changing stressors, known as regime shifts or critical transitions. Theory suggests that such systems feature folded stability landscapes with fluctuating resilience, fold-bifurcations, and alternate basins of attraction. However, the implementation of such features to elucidate response mechanisms in an empirical context is scarce, due to the lack of generic approaches to quantify resilience dynamics in individual natural systems. Here, we introduce an Integrated Resilience Assessment (IRA) framework: a three-step analytical process to assess resilience and construct stability landscapes of empirical systems. The proposed framework involves a multivariate analysis to estimate holistic system indicator variables, non-additive modelling to estimate alternate attractors, and a quantitative resilience assessment to scale stability landscapes. We implement this framework to investigate the temporal development of the Mediterranean marine communities in response to sea warming during 1985-2013, using fisheries landings data. Our analysis revealed a nonlinear tropicalisation of the Mediterranean Sea, expressed as abrupt shifts to regimes dominated by thermophilic species. The approach exemplified here for the Mediterranean Sea, revealing previously unknown resilience dynamics driven by climate forcing, can elucidate resilience and shifts in other complex systems.
| S-EPMC5651905 | biostudies-other
Project description: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.
| S-EPMC4533971 | biostudies-literature
Project description:Abrupt changes in dynamics of an ecosystem can sometimes be detected using monitoring data. Using nonparametric methods that assume minimal knowledge of the underlying structure, we compute separate estimates of the drift (deterministic) and diffusion (stochastic) components of a general dynamical process, as well as an indicator of the conditional variance. Theory and simulations show that nonparametric conditional variance rises prior to critical transition. Nonparametric diffusion rises also, in cases where the true diffusion function involves a critical transition (sometimes called a noise-induced transition). Thus it is possible to discriminate noise-induced transitions from other kinds of critical transitions by comparing time series for the conditional variance and the diffusion function. Monte Carlo analysis shows that the indicators generally increase prior to the transition, but uncertainties of the indicators become large as the ecosystem approaches the transition point.
| S-EPMC3448650 | biostudies-literature
Project description:The forecasting of sudden, irreversible shifts in natural systems is a challenge of great importance, whose realization could allow pre-emptive action to be taken to avoid or mitigate catastrophic transitions, or to help systems adapt to them. In recent years, there have been many advances in the development of such early warning signals. However, much of the current toolbox is based around the tracking of statistical trends and therefore does not aim to estimate the future time scale of transitions or resilience loss. Metric-based indicators are also difficult to implement when systems have inherent oscillations which can dominate the indicator statistics. To resolve these gaps in the toolbox, we use additional system properties to fit parsimonious models to dynamics in order to predict transitions. Here, we consider nearly-one-dimensional systems-higher dimensional systems whose dynamics can be accurately captured by one-dimensional discrete time maps. We show how the nearly one-dimensional dynamics can be used to produce model-based indicators for critical transitions which produce forecasts of the resilience and the time of transitions in the system. A particularly promising feature of this approach is that it allows us to construct early warning signals even for critical transitions of chaotic systems. We demonstrate this approach on two model systems: of phosphorous recycling in a shallow lake, and of an overcompensatory fish population.
| S-EPMC7536042 | biostudies-literature
Project description:Forecasting transitions between tidal ecosystem states, such as between bare tidal flats and vegetated marshes, is crucial because it may imply the irreversible loss of valuable ecosystem services. In this study, we combine geospatial analyses of three European estuaries with a simple numerical model to demonstrate that the development of micro-topographic patterning on tidal flats is an early indicator of marsh establishment. We first show that the development of micro-topographic patterns precedes vegetation establishment, and that patterns tend to form only on tidal flats with a slope of <0.3 degrees. Numerical modelling then provides an explanation for the formation of micro-topography due to the natural concentration of draining surface water over very gentle slopes. We find this early indicator to be robust across three estuaries where anthropogenic deepening and narrowing has occurred in recent decades, which may suggest its broader applicability to other estuaries with similar morphological management.
| S-EPMC10079839 | biostudies-literature
Project description:Real systems showing regime shifts, such as ecosystems, are often composed of many dynamical elements interacting on a network. Various early warning signals have been proposed for anticipating regime shifts from observed data. However, it is unclear how one should combine early warning signals from different nodes for better performance. Based on theory of stochastic differential equations, we propose a method to optimize the node set from which to construct an early warning signal. The proposed method takes into account that uncertainty as well as the magnitude of the signal affects its predictive performance, that a large magnitude or small uncertainty of the signal in one situation does not imply the signal's high performance, and that combining early warning signals from different nodes is often but not always beneficial. The method performs well particularly when different nodes are subjected to different amounts of dynamical noise and stress.
| S-EPMC10844243 | biostudies-literature
Project description:In complex systems, a critical transition is a shift in a system's dynamical regime from its current state to a strongly contrasting state as external conditions move beyond a tipping point. These transitions are often preceded by characteristic early warning signals such as increased system variability. However, early warning signals in complex, coupled human-environment systems (HESs) remain little studied. Here, we compare critical transitions and their early warning signals in a coupled HES model to an equivalent environment model uncoupled from the human system. We parameterize the HES model, using social and ecological data from old-growth forests in Oregon. We find that the coupled HES exhibits a richer variety of dynamics and regime shifts than the uncoupled environment system. Moreover, the early warning signals in the coupled HES can be ambiguous, heralding either an era of ecosystem conservationism or collapse of both forest ecosystems and conservationism. The presence of human feedback in the coupled HES can also mitigate the early warning signal, making it more difficult to detect the oncoming regime shift. We furthermore show how the coupled HES can be "doomed to criticality": Strategic human interactions cause the system to remain perpetually in the vicinity of a collapse threshold, as humans become complacent when the resource seems protected but respond rapidly when it is under immediate threat. We conclude that the opportunities, benefits, and challenges of modeling regime shifts and early warning signals in coupled HESs merit further research.
| S-EPMC5187665 | biostudies-literature
Project description:Climate change metrics have been used to quantify the exposure of geographic areas to different facets of change and relate these facets to different threats and opportunities for biodiversity at a global scale. In parallel, a suite of indicators have been developed to detect approaching transitions between alternative stable states in ecological systems at a local scale. Here, we explore whether particular geographic areas over the world display evidence for upcoming critical transitions in the temperature regime using five Early Warning Indicators (EWIs) commonly used in the literature. Although all EWIs revealed strong spatial variations regarding the likelihood of approaching transitions we found differences regarding the strength and the distribution of trends across the world, suggesting either that different mechanisms might be at play or that EWIs differ in their ability to detect approaching transitions. Nonetheless, a composite EWI, constructed from individual EWIs, showed congruent trends in several areas and highlighted variations across latitudes, between marine and terrestrial systems and among ecoregions within systems. Although the underlying mechanisms are unclear, our results suggest that some areas over the world might change toward an alternative temperature regime in the future with potential implications for the organisms inhabiting these areas.
| S-EPMC6030089 | biostudies-other
Project description: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.
| S-EPMC3393716 | biostudies-literature