scholarly journals Population dynamics of synthetic Terraformation motifs

2016 ◽  
Author(s):  
Ricard V. Solé ◽  
Raúl Montañez ◽  
Salvador Duran Nebreda ◽  
Daniel Rodriguez-Amor ◽  
Blai Vidiella ◽  
...  
Keyword(s):  
Habitat Degradation ◽  
Ecological Engineering ◽  
Ecological Interactions ◽  
Stable States ◽  
Population Extinction ◽  
Intensive Exploitation ◽  
Engineering Designs ◽  
Synthetic Organisms ◽  
Multiple Stable States ◽  
Catastrophic Shifts

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.

scholarly journals Population dynamics of synthetic terraformation motifs

2018 ◽  
Vol 5 (7) ◽  
pp. 180121 ◽  
Author(s):  
Ricard V. Solé ◽  
Raúl Montañez ◽  
Salva Duran-Nebreda ◽  
Daniel Rodriguez-Amor ◽  
Blai Vidiella ◽  
...  
Keyword(s):  
Habitat Degradation ◽  
Ecological Engineering ◽  
Stable States ◽  
Population Extinction ◽  
Intensive Exploitation ◽  
Engineering Designs ◽  
Synthetic Organisms ◽  
The Stability ◽  
Multiple Stable States ◽  
Transcritical Bifurcations

Ecosystems are complex systems, currently experiencing several threats associated with global warming, intensive exploitation and human-driven habitat degradation. Because of a general presence of multiple stable states, including states involving population extinction, and due to the intrinsic nonlinearities associated with feedback loops, collapse in ecosystems could occur in a catastrophic manner. 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. In this paper, we investigate the dynamics of the simplest mathematical models associated with four classes of ecological engineering designs, named Terraformation motifs (TMs). These TMs put in a nutshell different ecological strategies. In this context, some fundamental types of bifurcations pervade the systems’ dynamics. Mutualistic interactions can enhance persistence of the systems by means of saddle-node bifurcations. The models without cooperative interactions show that ecosystems achieve restoration through transcritical bifurcations. Thus, our analysis of the models allows us to define the stability conditions and parameter domains where these TMs must work.

Multiple Stable States and Catastrophic Shifts in Ecosystems

Ecology ◽  
2019 ◽  
Author(s):  
Sonia Kéfi
Keyword(s):  
Alternative Stable States ◽  
Direct Consequence ◽  
Theoretical Models ◽  
Economic Consequences ◽  
Design Management ◽  
Stable States ◽  
Natural Systems ◽  
Restoration Strategies ◽  
Multiple Stable States ◽  
Catastrophic Shifts

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).

scholarly journals The importance of being coupled: Stable states and catastrophic shifts in tidal biomorphodynamics

2010 ◽  
Vol 115 (F4) ◽  
Author(s):  
Marco Marani ◽  
Andrea D'Alpaos ◽  
Stefano Lanzoni ◽  
Luca Carniello ◽  
Andrea Rinaldo
Keyword(s):  
Stable States ◽  
Catastrophic Shifts

Trapped liquid drop in a microchannel: Multiple stable states

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

scholarly journals Multiple stable states of tree cover in a global land surface model due to a fire-vegetation feedback

2016 ◽  
Vol 43 (12) ◽  
pp. 6324-6331 ◽  
Author(s):  
G. Lasslop ◽  
V. Brovkin ◽  
C. H. Reick ◽  
S. Bathiany ◽  
S. Kloster
Keyword(s):  
Land Surface ◽  
Land Surface Model ◽  
Tree Cover ◽  
Surface Model ◽  
Stable States ◽  
Vegetation Feedback ◽  
Global Land ◽  
Multiple Stable States

scholarly journals How adaptive immunity constrains the composition and fate of large bacterial populations

2018 ◽  
Vol 115 (32) ◽  
pp. E7462-E7468 ◽  
Author(s):  
Madeleine Bonsma-Fisher ◽  
Dominique Soutière ◽  
Sidhartha Goyal
Keyword(s):  
Stochastic Dynamics ◽  
Phage Genome ◽  
Population Level ◽  
Abundance Distribution ◽  
Stable States ◽  
Bacterial Populations ◽  
Multiple Stable States ◽  
Time Invariant ◽  
Microbial Systems ◽  
Rank Abundance

Features of the CRISPR-Cas system, in which bacteria integrate small segments of phage genome (spacers) into their DNA to neutralize future attacks, suggest that its effect is not limited to individual bacteria but may control the fate and structure of whole populations. Emphasizing the population-level impact of the CRISPR-Cas system, recent experiments show that some bacteria regulate CRISPR-associated genes via the quorum sensing (QS) pathway. Here we present a model that shows that from the highly stochastic dynamics of individual spacers under QS control emerges a rank-abundance distribution of spacers that is time invariant, a surprising prediction that we test with dynamic spacer-tracking data from literature. This distribution depends on the state of the competing phage–bacteria population, which due to QS-based regulation may coexist in multiple stable states that vary significantly in their phage-to-bacterium ratio, a widely used ecological measure to characterize microbial systems.

scholarly journals Computing and Stability in Cortical Networks

2004 ◽  
Vol 16 (7) ◽  
pp. 1385-1412 ◽  
Author(s):  
Peter E. Latham ◽  
Sheila Nirenberg
Keyword(s):  
Cortical Neurons ◽  
Unstable State ◽  
Stable States ◽  
Attractor Networks ◽  
Firing Rates ◽  
The Face ◽  
Multiple Stable States ◽  
Background State ◽  
Do So

Cortical neurons are predominantly excitatory and highly interconnected. In spite of this, the cortex is remarkably stable: normal brains do not exhibit the kind of runaway excitation one might expect of such a system. How does the cortex maintain stability in the face of this massive excitatory feedback? More importantly, how does it do so during computations, which necessarily involve elevated firing rates? Here we address these questions in the context of attractor networks—networks that exhibit multiple stable states, or memories. We find that such networks can be stabilized at the relatively low firing rates observed in vivo if two conditions are met: (1) the background state, where all neurons are firing at low rates, is inhibition dominated, and (2) the fraction of neurons involved in a memory is above some threshold, so that there is sufficient coupling between the memory neurons and the background. This allows “dynamical stabilization” of the attractors, meaning feedback from the pool of background neurons stabilizes what would otherwise be an unstable state. We suggest that dynamical stabilization may be a strategy used for a broad range of computations, not just those involving attractors.

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