We consider a linear size-structured population model with diffusion in the
size-space. Individuals are recruited into the population at arbitrary sizes.
We equip the model with generalized Wentzell-Robin (or dynamic) boundary
conditions. This approach allows the modelling of populations in which
individuals may have distinguished physiological states. We establish
existence and positivity of solutions by showing that solutions are governed by
a positive quasicontractive semigroup of linear operators on the
biologically relevant state space. These results are obtained by establishing
dissipativity of a suitably perturbed semigroup generator. We also show that
solutions of the model exhibit balanced exponential growth, that is, our model
admits a finite-dimensional global attractor. In case of strictly positive
fertility we are able to establish that solutions in fact exhibit asynchronous
exponential growth.
Citation: József Z. Farkas, Peter Hinow. Physiologically structured populations with diffusion and dynamicboundary conditions[J]. Mathematical Biosciences and Engineering, 2011, 8(2): 503-513. doi: 10.3934/mbe.2011.8.503
Abstract
We consider a linear size-structured population model with diffusion in the
size-space. Individuals are recruited into the population at arbitrary sizes.
We equip the model with generalized Wentzell-Robin (or dynamic) boundary
conditions. This approach allows the modelling of populations in which
individuals may have distinguished physiological states. We establish
existence and positivity of solutions by showing that solutions are governed by
a positive quasicontractive semigroup of linear operators on the
biologically relevant state space. These results are obtained by establishing
dissipativity of a suitably perturbed semigroup generator. We also show that
solutions of the model exhibit balanced exponential growth, that is, our model
admits a finite-dimensional global attractor. In case of strictly positive
fertility we are able to establish that solutions in fact exhibit asynchronous
exponential growth.