Structured population models as abstract delay equations by odl20037

VIEWS: 28 PAGES: 3

									    Structured population models as abstract
                delay equations
                       Mats Gyllenberg
            Department of Mathematics and Statistics
                  00014 University of Helsinki
                           Finland


    Age-structured populations have since the work of McKendrick (1926)
and general physiologicallly structured populations since the 1960s (Tsuchiya
et al. 1966; Fredrickson et al. 1967; Bell & Anderson 1967; Sinko & Streifer
1967) beeen modelled by hyperbolic partial differential equations supple-
mented by a boundary condition describing the birth process. The PDE ap-
proach suffers from certain drawbacks: In more complicated nonlinear models
even proving existence and uniqueness may be a formidable task and apart
from age-structured models no satisfactory qualitative theory including such
basic topics as the principle of linearized (in)stability and Hopf bifurcation
exists.
    In this talk I will show that general nonlinear structured population mod-
els can be formulated in a way which is very similar in spirit to the the work
on age-structured models by Euler (1760). The model takes the form of an
initial value problem
                               x(t) = F (xt ), t > 0                      (DE)
                          x0 (θ) = ϕ(θ),      θ ∈ (−∞, 0],               (IC)
consisting of a delay equation (DE) specifying the rule for extending the
unknown function x from the history given by (IC). Here xt (θ) = x(t + θ).
The unknown function x is a vector
                                          b
                                x=             ,
                                          I


                                      1
where b is the population birth rate vector and I is the environmental con-
dition. If there are only finitely many states at birth, then b is finite di-
mensional. In many applications I is infinite-dimensional. I further show
that the initial value problem (DE) & (IC) can be formulated as an abstract
integral equation
                                            t
                                   −1            ⊙∗
              u(t) = T0 (t)ϕ + j                T0 (t − s)G(u(s))ds .            (AIE),
                                        0

on the space X = L1 (R− ; Y ) of Bochner integrable Y -valued functions. In
(AIE), T0 is the semigroup defined by translation and extension by zero:

                         ϕ(t + θ), −∞ < θ ≤ −t,
       (T0 (t)ϕ) (θ) =                                       ϕ ∈ X,     t ≥ 0.      (1)
                            0,      −t < θ ≤ 0,
  ⊙∗
T0 is also translation and extension by zero but on a bigger space and j is
an embedding of X = L1 (R− ; Y ) into this bigger space.
    In the talk I shall present an abstract framework based on adjoint semi-
groups for extending T0 to the bigger space and for defining G when F
is given. I shall also indicate how one proves the principle of linearized
(in)stability and the Hopf bifurcation theorem for (AIE). I illustrate the ab-
stract results by biologically relevant examples.
    This talk is based on joint work with Odo Diekmann and Philipp Getto
(Diekmann & Gyllenberg, in the press; Diekmann et al., in the press).

References
Bell, G.I., Anderson, E.C. (1967). Cell growth and division I. A mathe-
matical model with applications to cell volume distributions in mammalian
suspension cultures, Biophysical Journal 7 329–351.
Diekmann, O. and Gyllenberg, M. (2006). Abstract delay equations inspired
by population dynamics, in the press.
Diekmann, O., Getto, Ph., and Gyllenberg, M. (2006). Stability and bifur-
cation analysis of Volterra functional equations in the light of suns and stars,
SIAM Journal on Mathematical Analysis, in the press.
                               e e                     e
Euler, L. (1760). Recherches g´n´rales sur la mortalit´ et la multiplication du
genre humain, M´moires de l’Acad´mie Royale des Sciences et Belles Lettres
                  e                 e
XVI 144–164.


                                        2
Fredrickson, A.G., Ramkrishna, D., and Tsuchiya, H.M. (1967). Statistics
and dynamics of procaryotic cell populations, Mathematical Biosciences 1
327–374.
McKendrick, A.G. (1926). Applications of Mathematics to Medical Prob-
lems, Proc. Edinb. Math. Soc. 44 98–130.
Sinko, J.W. and Streifer, W. (1967). A new model for age-size structure of
a population, Ecology 48 910–918.
Tsuchiya, H.M., Fredickson, A.G, and Aris, P. (1966). Dynamics of microbial
cell populations, Advan. Chem. Eng. 6 125–198.




                                    3

								
To top