Complex Population Dynamics: Nonlinear M: Nonlinear Modeling by Bernd Blasius, Bernd Blasius, Jurgen Kurths, Lewi Stone

By Bernd Blasius, Bernd Blasius, Jurgen Kurths, Lewi Stone

This number of evaluation articles is dedicated to the modeling of ecological, epidemiological and evolutionary structures. Theoretical mathematical types are probably probably the most strong methods to be had for expanding our knowing of the complicated inhabitants dynamics in those ordinary platforms. fascinating new concepts are presently being constructed to satisfy this problem, akin to generalized or structural modeling, adaptive dynamics or multiplicative procedures. lots of those new strategies stem from the sphere of nonlinear dynamics and chaos conception, the place even the best mathematical rule can generate a wealthy number of dynamical behaviors that endure a robust analogy to organic populations.

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Additional resources for Complex Population Dynamics: Nonlinear M: Nonlinear Modeling in Ecology, Epidemiology and Genetics

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Gross et al. matrix models. As in conventional models, generalized model allow to reflect specific features of real world systems in a straightforward way and at the same time they rival the generality and efficiency of random matrix models. We start in Sec. 2 by presenting the main underlying idea of generalized models. The approach is illustrated at the example of a simple predator-prey system in Sec. 3. Thereafter, in Sec. 4, we discuss the treatment of two additional difficulties that typically arise in the construction of more complex models, whereas in Sec.

1,34 For instance the computation of normal form parameters would allow us to distinguish between the supercritical Hopf bifurcation, from which a stable limit cycle emerges and the subcritical Hopf bifurcation in which an unstable limit cycle vanishes. In contrast to the Jacobian, which is essentially a linearization of the processes in the steady state, the normal form parameters contain some information about higher derivatives. In principle these derivatives could be computed from the normalized equations in the same way as the Jacobian.

10). The parameter gx indicates the predator’s sensitivity to prey density, which is an indicator of predation pressure. If prey is scarce the predation rate is in many systems known to increase almost linearly with the prey density and gx ≈ 1. However if prey is abundant, predator saturation sets in and gx approaches 0 July 12, 2007 10:40 28 World Scientific Review Volume - 9in x 6in T. Gross et al. as the predation rate becomes almost independent of the prey density. In a similar way the parameter gy indicates the cooperation between predators.

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