1,329 research outputs found
Diffusion-driven instabilities and emerging spatial patterns in patchy landscapes
Spatial variation in population densities across a landscape is a feature of many ecological systems, from
self-organised patterns on mussel beds to spatially restricted insect outbreaks. It occurs as a result of
environmental variation in abiotic factors and/or biotic factors structuring the spatial distribution of
populations. However the ways in which abiotic and biotic factors interact to determine the existence
and nature of spatial patterns in population density remain poorly understood. Here we present a new
approach to studying this question by analysing a predator–prey patch-model in a heterogenous
landscape. We use analytical and numerical methods originally developed for studying nearest-
neighbour (juxtacrine) signalling in epithelia to explore whether and under which conditions patterns
emerge. We find that abiotic and biotic factors interact to promote pattern formation. In fact, we find a
rich and highly complex array of coexisting stable patterns, located within an enormous number of
unstable patterns. Our simulation results indicate that many of the stable patterns have appreciable
basins of attraction, making them significant in applications. We are able to identify mechanisms for
these patterns based on the classical ideas of long-range inhibition and short-range activation, whereby
landscape heterogeneity can modulate the spatial scales at which these processes operate to structure
the populations
Spatiotemporal complexity of a ratio-dependent predator-prey system
In this paper, we investigate the emergence of a ratio-dependent
predator-prey system with Michaelis-Menten-type functional response and
reaction-diffusion. We derive the conditions for Hopf, Turing and Wave
bifurcation on a spatial domain. Furthermore, we present a theoretical analysis
of evolutionary processes that involves organisms distribution and their
interaction of spatially distributed population with local diffusion. The
results of numerical simulations reveal that the typical dynamics of population
density variation is the formation of isolated groups, i.e., stripelike or
spotted or coexistence of both. Our study shows that the spatially extended
model has not only more complex dynamic patterns in the space, but also chaos
and spiral waves. It may help us better understand the dynamics of an aquatic
community in a real marine environment.Comment: 6pages, revtex
Master stability functions reveal diffusion-driven pattern formation in networks
We study diffusion-driven pattern-formation in networks of networks, a class
of multilayer systems, where different layers have the same topology, but
different internal dynamics. Agents are assumed to disperse within a layer by
undergoing random walks, while they can be created or destroyed by reactions
between or within a layer. We show that the stability of homogeneous steady
states can be analyzed with a master stability function approach that reveals a
deep analogy between pattern formation in networks and pattern formation in
continuous space.For illustration we consider a generalized model of ecological
meta-foodwebs. This fairly complex model describes the dispersal of many
different species across a region consisting of a network of individual
habitats while subject to realistic, nonlinear predator-prey interactions. In
this example the method reveals the intricate dependence of the dynamics on the
spatial structure. The ability of the proposed approach to deal with this
fairly complex system highlights it as a promising tool for ecology and other
applications.Comment: 20 pages, 5 figures, to appear in Phys. Rev. E (2018
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