Marta Paliaga

Separatrix reconstruction to identify tipping points in an eco-epidemiological model

Many ecological systems exhibit tipping points such that they suddenly shift from one state to another. These shifts can be devastating from an ecological point of view, and additionally have severe implications for the socio-economic system. They can be caused by overcritical perturbations of the state variables such as external shocks, disease emergence, or species removal. It is therefore important to be able to quantify the tipping points. Here we present a study of the tipping points by considering the basins of attraction of the stable equilibrium points. We address the question of finding the tipping points that lie on the separatrix surface, which partitions the space of system trajectories. We present an algorithm that reconstructs the separatrix by using a Moving Least Squares approximant based on radial basis functions. The algorithm is applied to an eco-epidemiological model of pack hunting predators that suffer disease infection. Our analysis reveals that strong hunting cooperation considerably promotes the survival of predators and renders the predators resilient to perturbations.

On basins of attraction for a predator-prey model via meshless approximation

In this work an epidemiological predator-prey model is studied. It analyzes the spread of an infectious disease with frequency-dependent and vertical transmission within the predator population. In particular we consider social predators, i.e. they cooperate in groups to hunt. The result is a three-dimensional system in which the predator population is divided into susceptible and infected individuals. Studying the dynamical system and bifurcation diagrams, a scenario was identified in which the model shows multistability but the domain of attraction of one equilibrium point can be so small that it is almost the point itself. From a biological point of view it is important to analyze this effect in order to understand under which conditions the population goes extinct or survives. Thus we present a study to analyze the basins of attraction of the stable equilibrium points. This paper addresses the question of finding the point lying on the surface which partitions the phase plane. Therefore a meshless app...

Towards an efficient meshfree solver

In this paper we focus on the enhancement in accuracy approximating a function and its derivatives via smoothed particle hydrodynamics. We discuss about improvements in the solution by reformulating the original method by means of the Taylor series expansion and by projecting with the kernel function and its derivatives. The accuracy of a function and its derivatives, up to a fixed order, can be simultaneously improved by assuming them as unknowns of a linear system. The improved formulation has been assessed with gridded and scattered data points distribution and the convergence has been analyzed referring to a case study in a 2D domain.

Correction to: Diseased Social Predators

In the original article, the second author’s family name was misspelled. The correct name is Marta Paliaga.

Highlighting numerical insights of an efficient SPH method

Abstract In this paper we focus on two sources of enhancement in accuracy and computational demanding in approximating a function and its derivatives by means of the Smoothed Particle Hydrodynamics method. The approximating power of the standard method is perceived to be poor and improvements can be gained making use of the Taylor series expansion of the kernel approximation of the function and its derivatives. The modified formulation is appealing providing more accurate results of the function and its derivatives simultaneously without changing the kernel function adopted in the computation. The request for greater accuracy needs kernel function derivatives with order up to the desidered accuracy order in approximating the function or higher for the derivatives. In this paper we discuss on the scheme dealing with the infinitely differentiable Gaussian kernel function. Studies on the accuracy, convergency and computational efforts with various sets of data sites are provided. Moreover, to make large scale problems tractable the improved fast Gaussian transform is considered picking up the computational cost at an acceptable level preserving the accuracy of the computation.

A brief overview on the numerical behavior of an implicit meshless method and an outlook to future challenges

In this paper recent results on a leapfrog ADI meshless formulation are reported and some future challenges are addressed. The method benefits from the elimination of the meshing task from the pre-processing stage in space and it is unconditionally stable in time. Further improvements come from the ease of implementation, which makes computer codes very flexible in contrast to mesh based solver ones. The method requires only nodes at scattered locations and a function and its derivatives are approximated by means of a kernel representation. A perceived obstacle in the implicit formulation is in the second order differentiations which sometimes are eccesively sensitive to the node configurations. Some ideas in approaching the meshless implicit formulation are provided.