Abstract. Spatially extended population dynamics models that incorporate demographic noise serve as case studies for the crucial role of fluctuations and correlations in biological systems. Numerical and analytic tools from non-equilibrium statistical physics capture the stochastic kinetics of these complex interacting manyparticle systems beyond rate equation approximations. Including spatial structure and stochastic noise in models for predator-prey competition invalidates the neutral Lotka-Volterra population cycles. Stochastic models yield long-lived erratic oscillations stemming from a resonant amplification mechanism. Spatially extended predator-prey systems display noise-stabilized activity fronts that generate persistent correlations. Fluctuation-induced renormalizations of the oscillation parameters can be analyzed perturbatively via a Doi-Peliti field theory mapping of the master equation; related tools allow detailed characterization of extinction pathways. The critical steadystate and non-equilibrium relaxation dynamics at the predator extinction threshold are governed by the directed percolation universality class. Spatial predation rate variability results in more localized clusters, enhancing both competing species' population densities. Affixing variable interaction rates to individual particles and allowing for trait inheritance subject to mutations induces fast evolutionary dynamics for the rate distributions. Stochastic spatial variants of three-species competition with 'rock-paper-scissors' interactions metaphorically describe cyclic dominance. These models illustrate intimate connections between population dynamics and evolutionary game theory, underscore the role of fluctuations to drive populations toward extinction, and demonstrate how space can support species diversity. Two-dimensional cyclic three-species May-Leonard models are characterized by the emergence of spiraling patterns whose properties are elucidated by a mapping onto a complex GinzburgLandau equation. Multiple-species extensions to general 'food networks' can be classified on the mean-field level, providing both fundamental understanding of ensuing cooperativity and profound insight into the rich spatio-temporal features and coarsening kinetics in the corresponding spatially extended systems. Novel space-time Stochastic population dynamics in spatially extended predator-prey systems 2 patterns emerge as a result of the formation of competing alliances; e.g., coarsening domains that each incorporate rock-paper-scissors competition games.

We study the influence of spatially varying reaction rates on a spatial stochastic two-species Lotka-Volterra lattice model for predator-prey interactions using two-dimensional Monte Carlo simulations. The effects of this quenched randomness on population densities, transient oscillations, spatial correlations, and invasion fronts are investigated. We find that spatial variability in the predation rate results in more localized activity patches, which in turn causes a remarkable increase in the asymptotic population densities of both predators and prey and accelerated front propagation.

Abstract. Intracellular calcium is regulated in part by the release of Ca 2+ ions from the endoplasmic reticulum via inositol-4,5-triphosphate receptor (IP 3 R) channels (among other possibilities such as RyR and L-type calcium channels). The resulting dynamics are highly diverse and lead to local calcium "puffs" as well as global waves propagating through cells, as observed in Xenopus oocytes, neurons, and other cell types. Local fluctuations in the number of calcium ions play a crucial role in the onset of these features. Previous modeling studies of calcium puff dynamics stemming from IP 3 R channels have predominantly focused on stochastic channel models coupled to deterministic diffusion of ions, thereby neglecting local fluctuations of the ion number. Tracking of individual ions is computationally difficult due to the scale separation in the Ca 2+ concentration when channels are in the open or closed states. In this paper, a spatial multiscale model for investigating of the dynamics of puffs is presented. It couples Brownian motion (diffusion) of ions with a stochastic channel gating model. The model is used to analyze calcium puff statistics. Concentration time traces as well as channel state information are studied. We identify the regime in which puffs can be found and develop a mean-field theory to extract the boundary of this regime. Puffs are possible only when the time scale of channel inhibition is sufficiently large. Implications for the understanding of puff generation and termination are discussed.

We employ an elastic line model to investigate the steady-state properties and non-equilibrium relaxation kinetics of magnetic vortex lines in disordered type-II superconductors using Langevin molecular dynamics (LMD). We extract the dependence of the mean vortex line velocity and gyration radius as well as the mean-square displacement in the steady state on the driving current, and measure the vortex density and height autocorrelations in the aging regime. We study samples with either randomly distributed pointlike or columnar attractive pinning centers, which allows us to distinguish the complex relaxation features of interacting flux lines subject to extended vs. uncorrelated disorder. Additionally, we find that our new LMD findings match earlier Monte Carlo (MC) simulation data well, verifying that these two microscopically quite distinct simulation methods lead to macroscopically very similar results for non-equilibrium vortex matter.

We investigate the competing effects and relative importance of intrinsic demographic and environmental variability on the evolutionary dynamics of a stochastic two-species Lotka-Volterra model by means of Monte Carlo simulations on a two-dimensional lattice. Individuals are assigned inheritable predation efficiencies; quenched randomness in the spatially varying reaction rates serves as environmental noise. We find that environmental variability enhances the population densities of both predators and prey while demographic variability leads to essentially neutral optimization.PACS numbers: 87.23. Cc, 87.18.Tt The mathematical modeling of species interactions continues to be a central issue in population ecology [1][2][3][4]. Several simple models have been proposed, investigated, and sometimes realized under laboratory conditions. Yet more realistic and thus biologically more relevant model variants obviously have to include both external spatial disorder in the reaction rates to account for varying environmental conditions and intrinsic demographic heterogeneity stemming from trait variability in individuals. While we addressed the former in a recent study [5], our goal in this letter is to investigate the interplay between quenched spatial rate disorder and additional variability of individuals' reaction rates, as well as intriguing evolutionary co-optimization within interacting populations.We focus on the Lotka-Volterra (LV) predator-prey model owing to its simplicity and because its basic features are well-understood. It was first introduced to study fish populations in the Adriatic sea and chemical oscillations [6,7]. While the original deterministic LV (mean-field) equations yield neutral cycles and hence persistent nonlinear oscillations around a marginal fixed point [1], in stochastic implementations this species coexistence fixed point becomes stable and is approached very slowly through damped oscillations [8][9][10][11][12][13][14]. Spatially extended stochastic versions of the LV model yield striking dynamical patterns and emergent inter-species correlations [15][16][17][18][19][20][21] which may be utilized to quantitatively assess the response to external or internal changes. Population stability can be measured via the extinction time in small systems, where the stochastic kinetics ultimately reaches an absorbing zero-particle state [20,22].In our study of the effects of environmental rate variability in the LV model, we found a remarkable increase of the asymptotic population densities of both species with enhanced quenched spatial disorder, i.e., predation rates that are fixed to different lattice sites [5]. Yet the observed erratic population oscillations and relaxation towards the (quasi-)steady state occur on the time scale of many generations; for real biological systems, one therefore needs to address Darwinian evolutionary adaptation of individuals' traits. Consequently, we introduce fundamentally novel features by endowing individual predator and prey particles with randomly selected...

Assemblies of actin and its regulators underlie the dynamic morphology of all eukaryotic cells. To understand how actin regulatory proteins work together to generate actin-rich structures such as filopodia, we analyzed the localization of diverse actin regulators within filopodia in Drosophila embryos and in a complementary in vitro system of filopodia-like structures (FLSs). We found that the composition of the regulatory protein complex where actin is incorporated (the filopodial tip complex) is remarkably heterogeneous both in vivo and in vitro. Our data reveal that different pairs of proteins correlate with each other and with actin bundle length, suggesting the presence of functional subcomplexes. This is consistent with a theoretical framework where three or more redundant subcomplexes join the tip complex stochastically, with any two being sufficient to drive filopodia formation. We provide an explanation for the observed heterogeneity and suggest that a mechanism based on multiple components allows stereotypical filopodial dynamics to arise from diverse upstream signaling pathways.

Is it possible to recover the position of a source from the steady-state fluxes of Brownian particles to small absorbing windows located on the boundary of a domain? To address this question, we develop a numerical procedure to avoid tracking Brownian trajectories in the entire infinite space. Instead, we generate particles near the absorbing windows, computed from the analytical expression of the exit probability. When the Brownian particles are generated by a steady-state gradient at a single point, we compute asymptotically the fluxes to small absorbing holes distributed on the boundary of half-space and on a disk in two dimensions, which agree with stochastic simulations. We also derive an expression for the splitting probability between small windows using the matched asymptotic method. Finally, when there are more than two small absorbing windows, we show how to reconstruct the position of the source from the diffusion fluxes. The present approach provides a computational first principle for the mechanism of sensing a gradient of diffusing particles, a ubiquitous problem in cell biology.

We study the effects of rapid temperature and magnetic field changes on the non-equilibrium relaxation dynamics of magnetic vortex lines in disordered type-II superconductors by employing an elastic line model and performing Langevin molecular dynamics simulations. In a previously equilibrated system, either the temperature is suddenly changed, or the magnetic field is instantaneously altered which is reflected in adding or removing flux lines to or from the system. The subsequent aging properties are investigated in samples with either randomly distributed point-like or extended columnar defects, which allows to distinguish the complex relaxation features that result from either type of pinning centers. One-time observables such as the radius of gyration and the fraction of pinned line elements are employed to characterize steady-state properties, and two-time correlation functions such as the vortex line height autocorrelations and their mean-square displacement are analyzed to study the non-linear stochastic relaxation dynamics in the aging regime.