Finite dimensional state representation of physiologically structured populations

Odo Diekmann, Mats Gyllenberg*, Johan A.J. Metz

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

In a physiologically structured population model (PSPM) individuals are characterised by continuous variables, like age and size, collectively called their i-state. The world in which these individuals live is characterised by another set of variables, collectively called the environmental condition. The model consists of submodels for (i) the dynamics of the i-state, e.g. growth and maturation, (ii) survival, (iii) reproduction, with the relevant rates described as a function of (i-state, environmental condition), (iv) functions of (i-state, environmental condition), like biomass or feeding rate, that integrated over the i-state distribution together produce the output of the population model. When the environmental condition is treated as a given function of time (input), the population model becomes linear in the state. Density dependence and interaction with other populations is captured by feedback via a shared environment, i.e., by letting the environmental condition be influenced by the populations’ outputs. This yields a systematic methodology for formulating community models by coupling nonlinear input–output relations defined by state-linear population models. For some combinations of submodels an (infinite dimensional) PSPM can without loss of relevant information be replaced by a finite dimensional ODE. We then call the model ODE-reducible. The present paper provides (a) a test for checking whether a PSPM is ODE reducible, and (b) a catalogue of all possible ODE-reducible models given certain restrictions, to wit: (i) the i-state dynamics is deterministic, (ii) the i-state space is one-dimensional, (iii) the birth rate can be written as a finite sum of environment-dependent distributions over the birth states weighted by environment independent ‘population outputs’. So under these restrictions our conditions for ODE-reducibility are not only sufficient but in fact necessary. Restriction (iii) has the desirable effect that it guarantees that the population trajectories are after a while fully determined by the solution of the ODE so that the latter gives a complete picture of the dynamics of the population and not just of its outputs.

Original languageEnglish
Pages (from-to)205-273
Number of pages69
JournalJournal of Mathematical Biology
Volume80
Issue number1-2
DOIs
Publication statusPublished - 1 Jan 2020

Funding

Open access funding provided by University of Helsinki including Helsinki University Central Hospital. Parts of the manuscript were written while the first two authors enjoyed the hospitality of the Banach Centre in Warsaw during the Simons semester on Mathematical Biology. We thank Piotr Gwiazda for making this happen. The manuscript was completed while the three of us participated in the research Programme ?Mathematical Biology? at the Institute Mittag-Leffler in the fall semester 2018. We thank the professional and friendly staff for providing such excellent working conditions. J.A.J.M. benefitted from the support from the ?Chair Mod?lisation Math?matique et Biodiversit? of Veolia Environnement-Ecole Polytechnique-Museum National d?Histoire Naturelle-Fondation X?. Finally we thank two referees and Editor Mark Lewis for constructive and very helpful feedback.

Keywords

  • Evolutionary system
  • Input–output system
  • Linear chain trick
  • ODE-reducibility

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