arXiv subjects

A. Castro e Silva

Publications and source records attributed to A. Castro e Silva.

4 recordsLinked to original sources

arXiv2016

Simulations of populations of Sapajus robustus in a fragmented landscape

The study of populations subject to the phenomenon of loss and fragmentation of habitat, transforming continuous areas into small ones, usually surrounded by anthropogenic matrices, has been the focus of many researches within the scope of conservation. The objective of this study was to develop a computer model by introducing modifications to the renowned Penna Model for biological aging, in order to evaluate the behavior of populations subjected to the effects of fragmented environments. As an object of study, it was used biological data of the robust tufted capuchin (Sapajus robustus), an endangered primate species whose geographical distribution within the Atlantic Rain Forest is part of the backdrop of intense habitat fragmentation. The simulations showed the expected behavior based on the three main aspects that affects populations under intense habitat fragmentation: the population density, area and conformation of the fragments and deleterious effects due the low genetic variability in small and isolated populations. The model showed itself suitable to describe changes in viability and population dynamics of the species crested capuchin considering critical levels of survival in a fragmented environment and also, actions in order to preserve the species should be focused not only on increasing available area but also in dispersion dynamics.

q-bio.PE↗

arXiv2010

Mean-Field and Non-Mean-Field Behaviors in Scale-free Networks with Random Boolean Dynamics

We study two types of simplified Boolean dynamics over scale-free networks, both with synchronous update. Assigning only Boolean functions AND and XOR to the nodes with probability $1-p$ and $p$, respectively, we are able to analyze the density of 1's and the Hamming distance on the network by numerical simulations and by a mean-field approximation (annealed approximation). We show that the behavior is quite different if the node always enters in the dynamic as its own input (self-regulation) or not. The same conclusion holds for the Kauffman KN model. Moreover, the simulation results and the mean-field ones (i) agree well when there is no self-regulation, and (ii) disagree for small $p$ when self-regulation is present in the model.

physics.bio-ph↗

arXiv2005

On The Universal Scaling Relations In Food Webs

In the last three decades, researchers have tried to establish universal patterns about the structure of food webs. Recently was proposed that the exponent $η$ characterizing the efficiency of the energy transportation of the food web had a universal value ($η=1.13$). Here we establish a lower bound and an upper one for this exponent in a general spanning tree with the number of trophic species and the trophic levels fixed. When the number of species is large the lower and upper bounds are equal to 1, implying that the result $η=1.13$ is due to finite size effects. We also evaluate analytically and numerically the exponent $η$ for hierarchical and random networks. In all cases the exponent $η$ depends on the number of trophic species $K$ and when $K$ is large we have that $η\to 1$. Moreover, this result holds for any number $M$ of trophic levels. This means that food webs are very efficient resource transportation systems.

cond-mat.stat-mech↗

arXiv2004

A Scale-free Network with Boolean Dynamics as a Function of Connectivity

In this work we analyze scale-free networks with different power law spectra $N(k) \sim k^{-γ}$ under a boolean dynamic, where the boolean rule that each node obeys is a function of its connectivity $k$. This is done by using only two logical functions (AND and XOR) which are controlled by a parameter $q$. Using damage spreading technique we show that the Hamming distance and the number of 1's exhibit power law behavior as a function of $q$. The exponents appearing in the power laws depend on the value of $γ$.

cond-mat.stat-mech↗