Biomedical subjects

Carlos A Braumann

Publications and source records attributed to Carlos A Braumann.

3 recordsLinked to original sources

PubMed2006

Harvesting in a random environment: Itô or Stratonovich calculus?

We extend to harvesting stochastic differential equation (SDE) models in a random environment our previous work on models without harvesting concerning the resolution of the Itô-Stratonovich controversy. The resolution is obtained for the very general class of models dN/dt=N (r(N)-h(N)+sigmaepsilon(t)), where N=N(t) is the population size at time t, r(N) is the (density-dependent) "mean" per capita growth rate, h(N) is the (density-dependent) harvesting effort, epsilon(t) is a standard white noise (representing environmental random fluctuations), and sigma is a noise intensity parameter. Itô and Stratonovich calculus in the resolution of SDEs apparently give different qualitative and quantitative results, leading to controversy on which calculus is more appropriate and creating an obstacle on the use of this modeling approach. We show that the apparent difference between the two calculi is due to a semantic confusion based on the fallacious assumption that we are working with the same type of mean rates. After clearing the confusion, the two calculi yield exactly the same results and we obtain important common conditions for extinction and for existence of a stationary density. The resolution of the controversy is intertwined with and sheds light on the estimation issues.

Animals↗

PubMed2005

Itô versus Stratonovich calculus in random population growth.

The context is the general stochastic differential equation (SDE) model dN/dt=N(g(N)+sigmaepsilon(t)) for population growth in a randomly fluctuating environment. Here, N=N(t) is the population size at time t, g(N) is the 'average' per capita growth rate (we work with a general almost arbitrary function g), and sigmaepsilon(t) is the effect of environmental fluctuations (sigma>0, epsilon(t) standard white noise). There are two main stochastic calculus used to interpret the SDE, Itô calculus and Stratonovich calculus. They yield different solutions and even qualitatively different predictions (on extinction, for example). So, there is a controversy on which calculus one should use. We will resolve the controversy and show that the real issue is merely semantic. It is due to the informal interpretation of g(x) as being an (unspecified) 'average' per capita growth rate (when population size is x). The implicit assumption usually made in the literature is that the 'average' growth rate is the same for both calculi, when indeed this rate should be defined in terms of the observed process. We prove that, when using Itô calculus, g(N) is indeed the arithmetic average growth rate R(a)(x) and, when using Stratonovich calculus, g(N) is indeed the geometric average growth rate R(g)(x). Writing the solutions of the SDE in terms of a well-defined average, R(a)(x) or R(g)(x), instead of an undefined 'average' g(x), we prove that the two calculi yield exactly the same solution. The apparent difference was due to the semantic confusion of taking the informal term 'average growth rate' as meaning the same average.

Algorithms↗

PubMedDate not supplied

Variable effort harvesting models in random environments: generalization to density-dependent noise intensities.

In a previous paper [Math. Biosci. 156 (1999) 1], we have studied quite general stochastic differential equation models for the growth of populations subjected to harvesting in a random environment. We have obtained conditions for non-extinction and for the existence of stationary distributions (as well as expressions for such distributions) similar to conditions for non-extinction and for the existence of a stable equilibrium in the corresponding deterministic model. The models were quite general, considering density-dependent natural growth functions and harvesting policies of very general form, so that our results would be model independent and provide minimal requirements for the choice of a wise density-dependent harvesting policy. Those models, however, although quite general on all other respects, have a serious limitation. In fact, the ways environmental fluctuations affect the population per capita growth rate are poorly known and those models only considered two possible ways, namely the noise intensity could be constant or proportional to that rate. To overcome this limitation, in this paper we generalize the previous results to density-dependent positive noise intensities of very general form so that they also become independent from the way environmental fluctuations affect population growth rates.

Animals↗