282 research outputs found
Synchronous and Asynchronous Recursive Random Scale-Free Nets
We investigate the differences between scale-free recursive nets constructed
by a synchronous, deterministic updating rule (e.g., Apollonian nets), versus
an asynchronous, random sequential updating rule (e.g., random Apollonian
nets). We show that the dramatic discrepancies observed recently for the degree
exponent in these two cases result from a biased choice of the units to be
updated sequentially in the asynchronous version
Dynamic Critical approach to Self-Organized Criticality
A dynamic scaling Ansatz for the approach to the Self-Organized Critical
(SOC) regime is proposed and tested by means of extensive simulations applied
to the Bak-Sneppen model (BS), which exhibits robust SOC behavior. Considering
the short-time scaling behavior of the density of sites () below the
critical value, it is shown that i) starting the dynamics with configurations
such that one observes an {\it initial increase} of the
density with exponent ; ii) using initial configurations with
, the density decays with exponent . It is
also shown that he temporal autocorrelation decays with exponent . Using these, dynamically determined, critical exponents and suitable
scaling relationships, all known exponents of the BS model can be obtained,
e.g. the dynamical exponent , the mass dimension exponent , and the exponent of all returns of the activity , in excellent agreement with values already accepted and obtained
within the SOC regime.Comment: Rapid Communication Physical Review E in press (4 pages, 5 figures
Clone size distributions in networks of genetic similarity
We build networks of genetic similarity in which the nodes are organisms
sampled from biological populations. The procedure is illustrated by
constructing networks from genetic data of a marine clonal plant. An important
feature in the networks is the presence of clone subgraphs, i.e. sets of
organisms with identical genotype forming clones. As a first step to understand
the dynamics that has shaped these networks, we point up a relationship between
a particular degree distribution and the clone size distribution in the
populations. We construct a dynamical model for the population dynamics,
focussing on the dynamics of the clones, and solve it for the required
distributions. Scale free and exponentially decaying forms are obtained
depending on parameter values, the first type being obtained when clonal growth
is the dominant process. Average distributions are dominated by the power law
behavior presented by the fastest replicating populations.Comment: 17 pages, 4 figures. One figure improved and other minor changes. To
appear in Physica
Irreversible phase transitions induced by an oscillatory input
A novel kind of irreversible phase transitions (IPT's) driven by an
oscillatory input parameter is studied by means of computer simulations. Second
order IPT's showing scale invariance in relevant dynamic critical properties
are found to belong to the universality class of directed percolation. In
contrast, the absence of universality is observed for first order IPT's.Comment: 18 pages (Revtex); 8 figures (.ps); submitted to Europhysics Letters,
December 9th, 199
Network analysis identifies weak and strong links in a metapopulation system
The identification of key populations shaping the structure and connectivity of metapopulation systems is a major challenge in population ecology. The use of molecular markers in the theoretical framework of population genetics has allowed great advances in this field, but the prime question of quantifying the role of each population in the system remains unresolved. Furthermore, the use and interpretation of classical methods are still bounded by the need for a priori information and underlying assumptions that are seldom respected in natural systems. Network theory was applied to map the genetic structure in a metapopulation system by using microsatellite data from populations of a threatened seagrass, Posidonia oceanica, across its whole geographical range. The network approach, free from a priori assumptions and from the usual underlying hypotheses required for the interpretation of classical analyses, allows both the straightforward characterization of hierarchical population structure and the detection of populations acting as hubs critical for relaying gene flow or sustaining the metapopulation system. This development opens perspectives in ecology and evolution in general, particularly in areas such as conservation biology and epidemiology, where targeting specific populations is crucial
Evolutionary and Ecological Trees and Networks
Evolutionary relationships between species are usually represented in
phylogenies, i.e. evolutionary trees, which are a type of networks. The
terminal nodes of these trees represent species, which are made of individuals
and populations among which gene flow occurs. This flow can also be represented
as a network. In this paper we briefly show some properties of these complex
networks of evolutionary and ecological relationships. First, we characterize
large scale evolutionary relationships in the Tree of Life by a degree
distribution. Second, we represent genetic relationships between individuals of
a Mediterranean marine plant, Posidonia oceanica, in terms of a Minimum
Spanning Tree. Finally, relationships among plant shoots inside populations are
represented as networks of genetic similarity.Comment: 6 pages, 5 figures. To appear in Proceedings of the Medyfinol06
Conferenc
Portraits of Complex Networks
We propose a method for characterizing large complex networks by introducing
a new matrix structure, unique for a given network, which encodes structural
information; provides useful visualization, even for very large networks; and
allows for rigorous statistical comparison between networks. Dynamic processes
such as percolation can be visualized using animations. Applications to graph
theory are discussed, as are generalizations to weighted networks, real-world
network similarity testing, and applicability to the graph isomorphism problem.Comment: 6 pages, 9 figure
Results of an aerial survey of the western population of Anser erythropus (Anserini) in autumn migration in Russia 2017
The global population of Anser erythropus has rapidly declined since the middle of the 20th century. The decline in numbers has been accompanied by the fragmentation of the breeding range and is considered as «continuing affecting all populations, giving rise to fears that the species may go extinct». Overhunting, poaching and habitat loss are considered to be the main threats. The official estimate of the dimension of the decline is in the range of 30% to 49% between 1998 and 2008. Monitoring and the prospection of new areas are needed for the future conservation of this species. The eastern part of the Nenetsky Autonomous Okrug, the Baydaratskaya Bay and the Lower Ob (Dvuobye) are important territories for the Western main population of Anser erythropus on a flyway scale. Moving along the coast to the east, Anser erythropus can stay for a long time on the Barents Sea Coast, from where they fly over the Baydaratskaya Bay to the Dvuobye. We made aerial surveys and identified key sites and the main threats for Anser erythropus on this part of the flyway. According to our data, the numbers of the Western main population of Anser erythropus amount to 48 580 ± 2820 individuals after the breeding season, i.e. higher than the previous estimates made in autumn in Northern Kazakhstan. The key sites of Anser erythropus in this part of the flyway were identified
Role of fractal dimension in random walks on scale-free networks
Fractal dimension is central to understanding dynamical processes occurring
on networks; however, the relation between fractal dimension and random walks
on fractal scale-free networks has been rarely addressed, despite the fact that
such networks are ubiquitous in real-life world. In this paper, we study the
trapping problem on two families of networks. The first is deterministic, often
called -flowers; the other is random, which is a combination of
-flower and -flower and thus called hybrid networks. The two
network families display rich behavior as observed in various real systems, as
well as some unique topological properties not shared by other networks. We
derive analytically the average trapping time for random walks on both the
-flowers and the hybrid networks with an immobile trap positioned at an
initial node, i.e., a hub node with the highest degree in the networks. Based
on these analytical formulae, we show how the average trapping time scales with
the network size. Comparing the obtained results, we further uncover that
fractal dimension plays a decisive role in the behavior of average trapping
time on fractal scale-free networks, i.e., the average trapping time decreases
with an increasing fractal dimension.Comment: Definitive version published in European Physical Journal
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