Tipping points are crossed when small changes in external conditions cause abrupt unexpected responses in the current state of a system. In the case of ecological communities under stress, the risk ...of approaching a tipping point is unknown, but its stakes are high. Here, we test recently developed critical slowing-down indicators as early-warning signals for detecting the proximity to a potential tipping point in structurally complex ecological communities. We use the structure of 79 empirical mutualistic networks to simulate a scenario of gradual environmental change that leads to an abrupt first extinction event followed by a sequence of species losses until the point of complete community collapse. We find that critical slowing-down indicators derived from time series of biomasses measured at the species and community level signal the proximity to the onset of community collapse. In particular, we identify specialist species as likely the best-indicator species for monitoring the proximity of a community to collapse. In addition, trends in slowing-down indicators are strongly correlated to the timing of species extinctions. This correlation offers a promising way for mapping species resilience and ranking species risk to extinction in a given community. Our findings pave the road for combining theory on tipping points with patterns of network structure that might prove useful for the management of a broad class of ecological networks under global environmental change.
Significance Little is known on whether structurally diverse ecological networks may respond abruptly to anthropogenic stress and even less on our ability to detect such responses in advance. By simulating mutualistic communities en route to a tipping point, we show how critical slowing-down indicators may be used as early warnings for the collapse of ecological networks. Our findings not only confirm the existence of the generic dynamical signatures of tipping points in ecological networks but also suggest a promising way for identifying most vulnerable components in a broad class of networks at the brink of collapse.
Abstract
The question of what and how to measure ecological resilience has been troubling ecologists since Holling 1973s seminal paper in which he defined resilience as the ability of a system to ...withstand perturbations without shifting to a different state. This definition moved the focus from studying the local stability of a single attractor to which a system always converges, to the idea that a system may converge to different states when perturbed. These two concepts have later on led to the definitions of engineering (local stability) vs ecological (non-local stability) resilience metrics. While engineering resilience is associated to clear metrics, measuring ecological resilience has remained elusive. As a result, the two notions have been studied largely independently from one another and although several attempts have been devoted to mapping them together in some kind of a coherent framework, the extent to which they overlap or complement each other in quantifying the resilience of a system is not yet fully understood. In this perspective, we focus on metrics that quantify resilience following Holling’s definition based on the concept of the stability landscape. We explore the relationships between different engineering and ecological resilience metrics derived from bistable systems and show that, for low dimensional ecological models, the correlation between engineering and ecological resilience can be high. We also review current approaches for measuring resilience from models and data, and we outline challenges which, if answered, could help us make progress toward a more reliable quantification of resilience in practice.
Abstract
Forest ecosystems depend on their capacity to withstand and recover from natural and anthropogenic perturbations (that is, their resilience)
1
. Experimental evidence of sudden increases in ...tree mortality is raising concerns about variation in forest resilience
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, yet little is known about how it is evolving in response to climate change. Here we integrate satellite-based vegetation indices with machine learning to show how forest resilience, quantified in terms of critical slowing down indicators
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, has changed during the period 2000–2020. We show that tropical, arid and temperate forests are experiencing a significant decline in resilience, probably related to increased water limitations and climate variability. By contrast, boreal forests show divergent local patterns with an average increasing trend in resilience, probably benefiting from warming and CO
2
fertilization, which may outweigh the adverse effects of climate change. These patterns emerge consistently in both managed and intact forests, corroborating the existence of common large-scale climate drivers. Reductions in resilience are statistically linked to abrupt declines in forest primary productivity, occurring in response to slow drifting towards a critical resilience threshold. Approximately 23% of intact undisturbed forests, corresponding to 3.32 Pg C of gross primary productivity, have already reached a critical threshold and are experiencing a further degradation in resilience. Together, these signals reveal a widespread decline in the capacity of forests to withstand perturbation that should be accounted for in the design of land-based mitigation and adaptation plans.
Understanding the stability of ecological communities is a matter of increasing importance in the context of global environmental change. Yet it has proved to be a challenging task. Different metrics ...are used to assess the stability of ecological systems, and the choice of one metric over another may result in conflicting conclusions. Although each of the multitude of metrics is useful for answering a specific question about stability, the relationship among metrics is poorly understood. Such lack of understanding prevents scientists from developing a unified concept of stability. Instead, by investigating these relationships we can unveil how many dimensions of stability there are (i.e., in how many independent components stability metrics can be grouped), which should help build a more comprehensive concept of stability. Here we simultaneously measured 27 stability metrics frequently used in ecological studies. Our approach is based on dynamical simulations of multispecies trophic communities under different perturbation scenarios. Mapping the relationships between the metrics revealed that they can be lumped into 3 main groups of relatively independent stability components: early response to pulse, sensitivities to press, and distance to threshold. Selecting metrics from each of these groups allows a more accurate and comprehensive quantification of the overall stability of ecological communities. These results contribute to improving our understanding and assessment of stability in ecological communities.
The concept of ecological stability occupies a prominent place in both fundamental and applied ecological research. We review decades of work on the topic and examine how our understanding has ...progressed. We show that our understanding of stability has remained fragmented and is limited largely to simple or simplified systems. There has been a profusion of metrics proposed to quantify stability, of which only a handful are used commonly. Furthermore, studies typically quantify one to two metrics of stability at a time and in response to a single perturbation, with some of the main environmental pressures of today being the least studied. We argue that we need to build on the existing consensus and strong theoretical foundation of the stability concept to better understand its multidimensionality and the interdependencies between metrics, levels of organisation and types of perturbations. Only by doing so can we make progress in the quantification of stability in theory and in practice, and eventually build a more comprehensive understanding of how ecosystems will respond to ongoing environmental change.
Populations and ecological communities are changing worldwide, and empirical studies exhibit a mixture of either declining or mixed trends. Confusion in global biodiversity trends thus remains, while ...assessing such changes is of major social, political, and scientific importance. Part of this variability may arise from the difficulty to reliably assess global biodiversity trends. Here, we conducted a literature review of studies documenting the temporal dynamics of global biodiversity. We classified the differences among approaches, data, and methodology used by the reviewed papers to reveal common findings and sources of discrepancies. We show that reviews and meta‐analyses, along with the use of global indicators, are more likely to conclude that trends are declining. On the other hand, the longer the data are available, the more nuanced are the trends they generate. Our results also highlight the lack of studies providing information on the impact of synergistic pressures on a global scale, making it even more difficult to understand the driving factors of the observed changes and how to decide conservation plan accordingly. Finally, we stress the importance of taking into account the sources of confusion identified, as well as the complexity of biodiversity changes, in order to implement effective conservation strategies. In particular, biodiversity dynamics are almost systematically assumed to be linear, while non‐linear trends are largely neglected. Clarifying the sources of confusion in global biodiversity trends should strengthen large‐scale biodiversity monitoring and conservation.
Ecological resilience is the ability of a system to persist in the face of perturbations. Although resilience has been a highly influential concept, its interpretation has remained largely ...qualitative. Here we describe an emerging family of methods for quantifying resilience on the basis of observations. A first set of methods is based on the phenomenon of critical slowing down, which implies that recovery upon small perturbations becomes slower as a system approaches a tipping point. Such slowing down can be measured experimentally but may also be indirectly inferred from changes in natural fluctuations and spatial patterns. A second group of methods aims to characterize the resilience of alternative states in probabilistic terms based on large numbers of observations as in long time series or satellite images. These generic approaches to measuring resilience complement the system-specific knowledge needed to infer the effects of environmental change on the resilience of complex systems.
Resilience indicators Dakos, Vasilis; Carpenter, Stephen R.; van Nes, Egbert H. ...
Philosophical transactions - Royal Society. Biological sciences,
01/2015, Letnik:
370, Številka:
1659
Journal Article
Recenzirano
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In the vicinity of tipping points—or more precisely bifurcation points—ecosystems recover slowly from small perturbations. Such slowness may be interpreted as a sign of low resilience in the sense ...that the ecosystem could easily be tipped through a critical transition into a contrasting state. Indicators of this phenomenon of 'critical slowing down (CSD)' include a rise in temporal correlation and variance. Such indicators of CSD can provide an early warning signal of a nearby tipping point. Or, they may offer a possibility to rank reefs, lakes or other ecosystems according to their resilience. The fact that CSD may happen across a wide range of complex ecosystems close to tipping points implies a powerful generality. However, indicators of CSD are not manifested in all cases where regime shifts occur. This is because not all regime shifts are associated with tipping points. Here, we review the exploding literature about this issue to provide guidance on what to expect and what not to expect when it comes to the CSD-based early warning signals for critical transitions.
There is a recognized need to anticipate tipping points, or critical transitions, in social-ecological systems. Studies of mathematical and experimental systems have shown that systems may 'wobble' ...before a critical transition. Such early warning signals may be due to the phenomenon of critical slowing down, which causes a system to recover slowly from small impacts, or to a flickering phenomenon, which causes a system to switch back and forth between alternative states in response to relatively large impacts. Such signals for transitions in social-ecological systems have rarely been observed, not the least because high-resolution time series are normally required. Here we combine empirical data from a lake-catchment system with a mathematical model and show that flickering can be detected from sparse data. We show how rising variance coupled to decreasing autocorrelation and skewness started 10-30 years before the transition to eutrophic lake conditions in both the empirical records and the model output, a finding that is consistent with flickering rather than critical slowing down. Our results suggest that if environmental regimes are sufficiently affected by large external impacts that flickering is induced, then early warning signals of transitions in modern social-ecological systems may be stronger, and hence easier to identify, than previously thought.
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