From asynchronous to synchronous chimeras in ecological multiplex network

We study the emergence of chimera states in coupled ecological systems consisting of prey–predator patches organized in a framework of multiplex network with regular coupling topology. The nodes in each layer of the multiplex network are modeled by a three-component Hastings–Powell model exhibiting chaotic dynamics. The existence of different dynamical states in each layer namely, incoherent, chimera and coherent states is characterized through the strength of incoherence measurement. Our investigation reveals that due to multiplexing the chimera state in one layer completely overlaps with the chimera state in another layer for a suitable range of the intra-layer coupling strengths. The transition scenario from asynchronous to synchronous chimera states is realized through the computation of the inter-layer synchronization error. Besides nonlocal interaction, a similar phenomenon is observed in the nearest-neighbor as well as in all-to-all interaction topology. Furthermore, the presence of distinct collective dynamical states is portrayed in an appropriate range of the various parameter spaces

Aging transition in weighted homogeneous and heterogeneous networks

A network consisting of active and inactive dynamical units experiences aging transition as the number of inactive nodes in the network is increased gradually. In this work, we investigate aging transition by exploring the tenacity of network's global oscillation, implemented by considering a weighted network, while the weights are chosen randomly from a uniform distribution. We examine how the critical transition point from oscillatory to non-oscillatory dynamics changes as the width of the distribution is varied. Exact value of the parameter at which the transition occurs is derived analytically, and interestingly it is found to be dependent on the mean weight of the network. Moreover, we observe a correlation between the results for weighted and unweighted cases. The analysis is performed for both Stuart-Landau limit cycle oscillator network and chaotic Hindmarsh-Rose neuronal network organized in the framework of global (homogeneous) and scale-free (heterogeneous) architectures

Diffusion induced spiral wave chimeras in ecological system

The peculiar phenomenon of chimera state corresponds to the exceptional spatial concurrence of coherent and incoherent dynamical behaviors appearing in networks of coupled oscillatory systems. In the present article, we report the emergence of spiral wave chimera patterns in locally coupled ecological network composed of diffusible prey-predator species. Dynamical transitions from spiral wave states to spiral wave chimera followed by incoherent dynamics with respect to increasing diffusion coefficients are explained. We characterize all these dynamical states while going through the concept of strength of incoherence and computing radius of the spiral wave chimera core. We further validate this occurrence for metapopulation comprising of prey-predator species subject to cross-diffusion

Augmentation of dynamical persistence in networks through asymmetric interaction

There exists several natural instances in which systems may undergo through local degradation of its constituting elements. This may severely affect the overall dynamical activity in unexpected ways. So, it requires to overcome such situations while posing some appropriate mechanisms. In this work we investigate aging networks comprising different groups of dynamical units coupled locally, non-locally or globally. We provide a mechanism that deals with asymmetry in the interaction of active and inactive groups to enhance the dynamical robustness of such aging networks. Apart from numerical experiments, we provide analytical treatment to identify the critical phase transition. Mathematical results are found to perfectly match the outcomes obtained through numerical experiments. Moreover, we provide evidence of the enriched network survivability in more complex topologies considering small-world and scale-free networks. Our proposed method to enhance the dynamical robustness is thus independent of coupling topology and quite efficient in aging networks of coupled oscillators

Cooperation on Interdependent Networks by Means of Migration and Stochastic Imitation

Evolutionary game theory in the realm of network science appeals to a lot of research communities, as it constitutes a popular theoretical framework for studying the evolution of cooperation in social dilemmas. Recent research has shown that cooperation is markedly more resistant in interdependent networks, where traditional network reciprocity can be further enhanced due to various forms of interdependence between different network layers. However, the role of mobility in interdependent networks is yet to gain its well-deserved attention. Here we consider an interdependent network model, where individuals in each layer follow different evolutionary games, and where each player is considered as a mobile agent that can move locally inside its own layer to improve its fitness. Probabilistically, we also consider an imitation possibility from a neighbor on the other layer. We show that, by considering migration and stochastic imitation, further fascinating gateways to cooperation on interdependent networks can be observed. Notably, cooperation can be promoted on both layers, even if cooperation without interdependence would be improbable on one of the layers due to adverse conditions. Our results provide a rationale for engineering better social systems at the interface of networks and human decision making under testing dilemmas

Cooperation on Interdependent Networks by Means of Migration and Stochastic Imitation.

Evolutionary game theory in the realm of network science appeals to a lot of research communities, as it constitutes a popular theoretical framework for studying the evolution of cooperation in social dilemmas. Recent research has shown that cooperation is markedly more resistant in interdependent networks, where traditional network reciprocity can be further enhanced due to various forms of interdependence between different network layers. However, the role of mobility in interdependent networks is yet to gain its well-deserved attention. Here we consider an interdependent network model, where individuals in each layer follow different evolutionary games, and where each player is considered as a mobile agent that can move locally inside its own layer to improve its fitness. Probabilistically, we also consider an imitation possibility from a neighbor on the other layer. We show that, by considering migration and stochastic imitation, further fascinating gateways to cooperation on interdependent networks can be observed. Notably, cooperation can be promoted on both layers, even if cooperation without interdependence would be improbable on one of the layers due to adverse conditions. Our results provide a rationale for engineering better social systems at the interface of networks and human decision making under testing dilemmas

Time delays shape the eco-evolutionary dynamics of cooperation.

We study the intricate interplay between ecological and evolutionary processes through the lens of the prisoners dilemma game. But while previous studies on cooperation amongst selfish individuals often assume instantaneous interactions, we take into consideration delays to investigate how these might affect the causes underlying prosocial behavior. Through analytical calculations and numerical simulations, we demonstrate that delays can lead to oscillations, and by incorporating also the ecological variable of altruistic free space and the evolutionary strategy of punishment, we explore how these factors impact population and community dynamics. Depending on the parameter values and the initial fraction of each strategy, the studied eco-evolutionary model can mimic a cyclic dominance system and even exhibit chaotic behavior, thereby highlighting the importance of complex dynamics for the effective management and conservation of ecological communities. Our research thus contributes to the broader understanding of group decision-making and the emergence of moral behavior in multidimensional social systems