The effect of cooperator recognition on competition among clones in spatially structured microbial communities.

In spatially structured microbial communities, clonal growth of stationary cells passively generates clusters of related individuals. This can lead to stable cooperation without the need for recognition mechanisms. However, recent research suggests that some biofilm-forming microbes may have mechanisms of kin recognition.

Pattern formation in marsh ecosystems modeled through the interaction of marsh vegetation, mussels and sediment.

Spatial self-organization, a common feature of multi-species communities, can provide important insights into ecosystem structure and resilience. As environmental conditions gradually worsen (e.g.

Corrigendum to "Bistability in a differential equation model of oyster reef height and sediment accumulation" [J. Theor. Biol. 289 (2011) 1-11].

There was a mistake in the Matlab code we used to generate time series solutions of our model, Eqs. (16)-(18). The corrected text below replaces one paragraph on p.

Model of pattern formation in marsh ecosystems with nonlocal interactions.

Smooth cordgrass Spartina alterniflora is a grass species commonly found in tidal marshes. It is an ecosystem engineer, capable of modifying the structure of its surrounding environment through various feedbacks. The scale-dependent feedback between marsh grass and sediment volume is particularly of interest.

Enhancement of large fluctuations to extinction in adaptive networks.

During an epidemic, individual nodes in a network may adapt their connections to reduce the chance of infection. A common form of adaption is avoidance rewiring, where a noninfected node breaks a connection to an infected neighbor and forms a new connection to another noninfected node. Here we explore the effects of such adaptivity on stochastic fluctuations in the susceptible-infected-susceptible model, focusing on the largest fluctuations that result in extinction of infection.

A Framework for Inferring Unobserved Multistrain Epidemic Subpopulations Using Synchronization Dynamics.

A new method is proposed to infer unobserved epidemic subpopulations by exploiting the synchronization properties of multistrain epidemic models. A model for dengue fever is driven by simulated data from secondary infective populations. Primary infective populations in the driven system synchronize to the correct values from the driver system.

Epidemics with temporary link deactivation in scale-free networks.

During an epidemic, people may adapt or alter their social contacts to avoid infection. Various adaptation mechanisms have been studied previously. Recently, a new adaptation mechanism was presented in [1], where susceptible nodes temporarily deactivate their links to infected neighbors and reactivate when their neighbors recover.

Effects of community structure on epidemic spread in an adaptive network.

When an epidemic spreads in a population, individuals may adaptively change the structure of their social contact network to reduce risk of infection. Here we study the spread of an epidemic on an adaptive network with community structure. We model two communities with different average degrees.

Epidemics in adaptive social networks with temporary link deactivation.

Disease spread in a society depends on the topology of the network of social contacts. Moreover, individuals may respond to the epidemic by adapting their contacts to reduce the risk of infection, thus changing the network structure and affecting future disease spread. We propose an adaptation mechanism where healthy individuals may choose to temporarily deactivate their contacts with sick individuals, allowing reactivation once both individuals are healthy.

Asymptotically inspired moment-closure approximation for adaptive networks.

Adaptive social networks, in which nodes and network structure coevolve, are often described using a mean-field system of equations for the density of node and link types. These equations constitute an open system due to dependence on higher-order topological structures. We propose a new approach to moment closure based on the analytical description of the system in an asymptotic regime.

Recruitment dynamics in adaptive social networks.

We model recruitment in adaptive social networks in the presence of birth and death processes. Recruitment is characterized by nodes changing their status to that of the recruiting class as a result of contact with recruiting nodes. Only a susceptible subset of nodes can be recruited.

Bistability in a differential equation model of oyster reef height and sediment accumulation.

Native oyster populations in Chesapeake Bay have been the focus of three decades of restoration attempts, which have generally failed to rebuild the populations and oyster reef structure. Recent restoration successes and field experiments indicate that high-relief reefs persist, likely due to elevated reef height which offsets heavy sedimentation and promotes oyster survival, disease resistance and growth, in contrast to low-relief reefs which degrade in just a few years. These findings suggest the existence of alternative stable states in oyster reef populations.

Adaptive Network Dynamics - Modeling and Control of Time-Dependent Social Contacts.

Real networks consisting of social contacts do not possess static connections. That is, social connections may be time dependent due to a variety of individual behavioral decisions based on current network connections. Examples of adaptive networks occur in epidemics, where information about infectious individuals may change the rewiring of healthy people, or in the recruitment of individuals to a cause or fad, where rewiring may optimize recruitment of susceptible individuals.

Converging towards the optimal path to extinction.

Extinction appears ubiquitously in many fields, including chemical reactions, population biology, evolution and epidemiology. Even though extinction as a random process is a rare event, its occurrence is observed in large finite populations. Extinction occurs when fluctuations owing to random transitions act as an effective force that drives one or more components or species to vanish.

Enhanced vaccine control of epidemics in adaptive networks.

We study vaccine control for disease spread on an adaptive network modeling disease avoidance behavior. Control is implemented by adding Poisson-distributed vaccination of susceptibles. We show that vaccine control is much more effective in adaptive networks than in static networks due to feedback interaction between the adaptive network rewiring and the vaccine application.

Asymmetry in the presence of migration stabilizes multistrain disease outbreaks.

We study the effect of migration between coupled populations, or patches, on the stability properties of multistrain disease dynamics. The epidemic model used in this work displays a Hopf bifurcation to oscillations in a single, well-mixed population. It is shown numerically that migration between two non-identical patches stabilizes the endemic steady state, delaying the onset of large amplitude outbreaks and reducing the total number of infections.

Maximal sensitive dependence and the optimal path to epidemic extinction.

Extinction of an epidemic or a species is a rare event that occurs due to a large, rare stochastic fluctuation. Although the extinction process is dynamically unstable, it follows an optimal path that maximizes the probability of extinction. We show that the optimal path is also directly related to the finite-time Lyapunov exponents of the underlying dynamical system in that the optimal path displays maximum sensitivity to initial conditions.

Rewiring for adaptation.

The idea behind adaptive behavioral epidemiology is that groups and individuals respond to the knowledge of a disease threat by changing their habits to avoid interactions with those who are contagious. Network-based models take this adaptive behavior into account by allowing the network to "rewire" its connections.

Epidemics with multistrain interactions: the interplay between cross immunity and antibody-dependent enhancement.

This paper examines the interplay of the effect of cross immunity and antibody-dependent enhancement (ADE) in multistrain diseases. Motivated by dengue fever, we study a model for the spreading of epidemics in a population with multistrain interactions mediated by both partial temporary cross immunity and ADE. Although ADE models have previously been observed to cause chaotic outbreaks, we show analytically that weak cross immunity has a stabilizing effect on the system.

Effect of multiple time delays on intensity fluctuation dynamics in fiber ring lasers.

The effect of time delay on nonlinear oscillators is an important problem in the study of dynamical systems. The dynamics of an erbium-doped fiber ring laser with an extra loop providing time-delayed feedback is studied experimentally by measuring the intensity of the laser. The delay time for the feedback is varied from approximately 0.

Fluctuating epidemics on adaptive networks.

A model for epidemics on an adaptive network is considered. Nodes follow a susceptible-infective-recovered-susceptible pattern. Connections are rewired to break links from noninfected nodes to infected nodes and are reformed to connect to other noninfected nodes, as the nodes that are not infected try to avoid the infection.

Changing dynamical complexity with time delay in coupled fiber laser oscillators.

We investigate the complexity of the dynamics of two mutually coupled systems with internal delays and vary the coupling delay over 4 orders of magnitude. Karhunen-Loève decomposition of spatiotemporal representations of fiber laser intensity data is performed to examine the eigenvalue spectrum and significant orthogonal modes. We compute the Shannon information from the eigenvalue spectra to quantify the dynamical complexity.

Isochronal synchronization of delay-coupled systems.

We consider small network models for mutually delay-coupled systems which typically do not exhibit stable isochronally synchronized solutions. We show analytically and numerically that for certain coupling architectures which involve delayed self-feedback to the nodes, the oscillators become isochronally synchronized. Applications are shown for both incoherent pump-coupled lasers and spatiotemporal coupled fiber ring lasers.

Using dimension reduction to improve outbreak predictability of multistrain diseases.

Multistrain diseases have multiple distinct coexisting serotypes (strains). For some diseases, such as dengue fever, the serotypes interact by antibody-dependent enhancement (ADE), in which infection with a single serotype is asymptomatic, but contact with a second serotype leads to higher viral load and greater infectivity. We present and analyze a dynamic compartmental model for multiple serotypes exhibiting ADE.

Instabilities in multiserotype disease models with antibody-dependent enhancement.

This paper investigates the complex dynamics induced by antibody-dependent enhancement (ADE) in multiserotype disease models. ADE is the increase in viral growth rate in the presence of immunity due to a previous infection of a different serotype. The increased viral growth rate is thought to increase the infectivity of the secondary infectious class.