Large extinctions in an evolutionary model: The role of innovation and keystone species

Jain, Shaili; Krishna, Sandeep

doi:10.1073/pnas.032618499

Cited by 78 publications

(67 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The role of feedback loops in a network structure that evolves under both selection and stochastic forces is also characteristic of several real evolutionary systems. It is significant that in several generalizations of this model introduced earlier ( Jain & Krishna 2002b;Krishna 2004), we find that the lifetime of the evolutionary network increases exponentially with the diversity. This includes models where the network allows self loops, both positive and negative links (that inhibit species production), and links with varying strengths.…”

Section: Discussionmentioning

confidence: 97%

Diversity sustains an evolving network

Mehrotra

Soni

Jain

2008

J. R. Soc. Interface.

Self Cite

View full text Add to dashboard Cite

We study an evolutionary model of a complex system that evolves under catalytic dynamics and Darwinian selection and exhibits spontaneous growth, stasis and then a collapse of its structure. We find that the typical lifetime of the system increases sharply with the diversity of its components or species. We also find that the prime reason for crashes is a naturally occurring internal fragility of the system. This fragility is captured in the network organizational character and is related to a reduced multiplicity of pathways or feedback loops between its components. These results apply to several generalizations of the model as well. This work suggests new parameters for understanding the robustness of evolving molecular networks, ecosystems, societies and markets.

show abstract

Section: Discussionmentioning

confidence: 97%

Diversity sustains an evolving network

Mehrotra

Soni

Jain

2008

J. R. Soc. Interface.

Self Cite

View full text Add to dashboard Cite

show abstract

“…For obtaining a detailed understanding of their architecture it has proved useful to trace the dynamics of the networks structural growth. As recently observed major transitions in a systems dynamics can even be completely governed by preceding transformations in its network structure [15,16].…”

Section: Introductionmentioning

confidence: 99%

“…The complexity of many systems, however, emerges as a consequence of some underlying principle for their evolution, e.g., preferential attachment [11], optimization of transportation and communication pathways [12][13][14] extinction of the least populated species [15,16], or of the mere fact that the network has randomly evolved in time [17]. This, altogether may lead to a highly organized network topology.…”

Section: Introductionmentioning

confidence: 99%

Patterns in randomly evolving networks: Idiotypic networks

Brede

Behn

2003

Phys. Rev. E

View full text Add to dashboard Cite

We present a model for the evolution of networks of occupied sites on undirected regular graphs. At every iteration step in a parallel update I randomly chosen empty sites are occupied and occupied sites having degree outside of a given interval (t l , tu) are set empty. Depending on the influx I and the values of both lower threshold and upper threshold of the degree different kinds of behaviour can be observed. In certain regimes stable long-living patterns appear. We distinguish two types of pattern: static patterns arising on graphs with low connectivity and dynamic patterns found on high connectivity graphs. Increasing I patterns become unstable and transitions between almost stable patterns, interrupted by disordered phases, occur. For still larger I the lifetime of occupied sites becomes very small and network structures are dominated by randomness. We develop methods to analyze nature and dynamics of these network patterns, give a statistical description of defects and fluctuations around them, and elucidate transitions between different patterns. Results and methods presented can be applied to a variety of problems in different fields and a broad class of graphs. Aiming chiefly at the modeling of functional networks of interacting antibodies and B-cells of the immune system (idiotypic networks) we focus on a class of graphs constructed by bit-chains. The biological relevance of the patterns and possible operational modes of idiotypic networks are discussed.

show abstract

“…Invasions can also facilitate the recovery of a socially desirable ecosystem regime (Jain and Krishna, 2002); for example, the invasion of the European green crab (Carcinus maenas) into degraded salt marshes along Cape Cod in New England, USA (Bertness and Cloverdale, 2013). Overfishing of native predator populations resulted in greatly increased densities of native herbivorous marsh crab (Sesarma reticulatum) populations.…”

Section: )mentioning

confidence: 99%

Biological invasions, ecological resilience and adaptive governance

Chaffin

Garmestani

Angeler

et al. 2016

Journal of Environmental Management

View full text Add to dashboard Cite

a b s t r a c tIn a world of increasing interconnections in global trade as well as rapid change in climate and land cover, the accelerating introduction and spread of invasive species is a critical concern due to associated negative social and ecological impacts, both real and perceived. Much of the societal response to invasive species to date has been associated with negative economic consequences of invasions. This response has shaped a war-like approach to addressing invasions, one with an agenda of eradications and intense ecological restoration efforts towards prior or more desirable ecological regimes. This trajectory often ignores the concept of ecological resilience and associated approaches of resilience-based governance. We argue that the relationship between ecological resilience and invasive species has been understudied to the detriment of attempts to govern invasions, and that most management actions fail, primarily because they do not incorporate adaptive, learning-based approaches. Invasive species can decrease resilience by reducing the biodiversity that underpins ecological functions and processes, making ecosystems more prone to regime shifts. However, invasions do not always result in a shift to an alternative regime; invasions can also increase resilience by introducing novelty, replacing lost ecological functions or adding redundancy that strengthens already existing structures and processes in an ecosystem. This paper examines the potential impacts of species invasions on the resilience of ecosystems and suggests that resilience-based approaches can inform policy by linking the governance of biological invasions to the negotiation of tradeoffs between ecosystem services.

show abstract

Large extinctions in an evolutionary model: The role of innovation and keystone species

Cited by 78 publications

References 37 publications

Diversity sustains an evolving network

Diversity sustains an evolving network

Patterns in randomly evolving networks: Idiotypic networks

Biological invasions, ecological resilience and adaptive governance

Contact Info

Product

Resources

About