Multiple Stable States and Catastrophic Shifts in Ecosystems

Ecology ◽  
2019 ◽  
Author(s):  
Sonia Kéfi

The idea that ecosystems may have multiple alternative stable states dates back to the late 1960s–early 1970s, when ecologists realized that this type of behavior could arise in simple mathematical models. A direct consequence is that such ecosystems can suddenly switch (or “tip”) between their alternative stable states rather than gradually responding to changes. In other terms, in these ecosystems, a small environmental perturbation can cause large, discontinuous, and irreversible changes, referred to as catastrophic shifts. This idea has attracted increasing interest in the literature over the years, and has become even more relevant in the current context of global change. Examples of catastrophic shifts in ecosystems include the eutrophication of shallow lakes, the desertification of drylands, and the degradation of coral reefs. Theoretical models have investigated the conditions under which alternative stable states and catastrophic shifts occur. A well-recognized cause of alternative stable states is the presence of strong positive—or self-reinforcing—feedback processes that maintain each of the stable ecosystem states. Understanding the mechanisms underlying the emergence of alternative stable states can help design management as well as restoration strategies for ecosystems. Because catastrophic shifts can have dramatic ecological and economic consequences, approaches have been proposed to detect possible alternative stable states in natural systems, and indicators of approaching ecosystem transitions have been identified (so-called early warning signals of critical slowing down).

2016 ◽  
Author(s):  
Ricard V. Solé ◽  
Raúl Montañez ◽  
Salvador Duran Nebreda ◽  
Daniel Rodriguez-Amor ◽  
Blai Vidiella ◽  
...  

Ecosystems are complex systems, currently experiencing several threats associated with global warming, intensive exploitation, and human-driven habitat degradation. Such threats are pushing ecosystems to the brink of collapse. Because of a general presence of multiple stable states, including states involving population extinction, and due to intrinsic nonlinearities associated with feedback loops, collapse can occur in a catastrophic manner. Such catastrophic shifts have been suggested to pervade many of the future transitions affecting ecosystems at many different scales. Many studies have tried to delineate potential warning signals predicting such ongoing shifts but little is known about how such transitions might be effectively prevented. It has been recently suggested that a potential path to prevent or modify the outcome of these transitions would involve designing synthetic organisms and synthetic ecological interactions that could push these endangered systems out of the critical boundaries. Four classes of such ecological engineering designs orTerraformation motifshave been defined in a qualitative way. Here we develop the simplest mathematical models associated with these motifs, defining the expected stability conditions and domains where the motifs shall properly work.


2020 ◽  
Author(s):  
Edward W. Tekwa ◽  
Martin Krkošek ◽  
Malin L. Pinsky

AbstractMultiple attractors and alternative stable states are defining features of scientific theories in ecology and evolution, implying that abrupt regime shifts can occur and that outcomes can be hard to reverse. Here we describe a statistical inferential framework that uses independent, noisy observations with low temporal resolution to support or refute multiple attractor process models. The key is using initial conditions to choose among a finite number of expected outcomes using a nonstandard finite mixture methodology. We apply the framework to contemporary issues in social-ecological systems, coral ecosystems, and chaotic systems, showing that incorporating history allows us to statistically infer process models with alternative stable states while minimizing false positives. Further, in the presence of disturbances and oscillations, alternative stable states can help rather than hamper inference. The ability to infer models with alternative stable states across natural systems can help accelerate scientific discoveries, change how we manage ecosystems and societies, and place modern theories on firmer empirical ground.


2009 ◽  
Vol 18 (1) ◽  
pp. 159-173 ◽  
Author(s):  
Brian Beckage ◽  
Chris Ellingwood ◽  

Oikos ◽  
2005 ◽  
Vol 110 (2) ◽  
pp. 409-416 ◽  
Author(s):  
Raphael K. Didham ◽  
Corinne H. Watts ◽  
David A. Norton

Author(s):  
Marco Marani ◽  
Andrea D'Alpaos ◽  
Stefano Lanzoni ◽  
Luca Carniello ◽  
Andrea Rinaldo

2013 ◽  
Vol 87 (6) ◽  
Author(s):  
Zhengjia Wang ◽  
Cheng-Chung Chang ◽  
Siang-Jie Hong ◽  
Yu-Jane Sheng ◽  
Heng-Kwong Tsao

2018 ◽  
Vol 116 (2) ◽  
pp. 689-694 ◽  
Author(s):  
Edward W. Tekwa ◽  
Eli P. Fenichel ◽  
Simon A. Levin ◽  
Malin L. Pinsky

Understanding why some renewable resources are overharvested while others are conserved remains an important challenge. Most explanations focus on institutional or ecological differences among resources. Here, we provide theoretical and empirical evidence that conservation and overharvest can be alternative stable states within the same exclusive-resource management system because of path-dependent processes, including slow institutional adaptation. Surprisingly, this theory predicts that the alternative states of strong conservation or overharvest are most likely for resources that were previously thought to be easily conserved under optimal management or even open access. Quantitative analyses of harvest rates from 217 intensely managed fisheries supports the predictions. Fisheries’ harvest rates also showed transient dynamics characteristic of path dependence, as well as convergence to the alternative stable state after unexpected transitions. This statistical evidence for path dependence differs from previous empirical support that was based largely on case studies, experiments, and distributional analyses. Alternative stable states in conservation appear likely outcomes for many cooperatively managed renewable resources, which implies that achieving conservation outcomes hinges on harnessing existing policy tools to navigate transitions.


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