How trait distributions evolve in heterogeneous populations

TL;DR

This paper analyzes how trait distributions evolve over time in heterogeneous populations with fixed individual parameters, revealing constraints on their dynamics and illustrating oscillatory behaviors in complex models.

Contribution

It provides analytical insights into the evolution of trait distributions in non-uniform populations with fixed heterogeneity parameters, including variance dynamics and oscillatory behaviors.

Findings

Initial assumptions restrict possible trait distribution evolutions.

Variance evolution can be explicitly analyzed.

Highly heterogeneous populations can exhibit oscillatory behaviors.

Abstract

We consider the problem of determining the time evolution of a trait distribution in a mathematical model of non-uniform populations with parametric heterogeneity. This means that we consider only heterogeneous populations in which heterogeneity is described by an individual specific parameter that differs in general from individual to individual, but does not change with time for the whole lifespan of this individual. Such a restriction allows obtaining a number of simple and yet important analytical results. In particular we show that initial assumptions on time-dependent behavior of various characteristics, such as the mean, variance, of coefficient of variation, restrict severely possible choices for the exact form of the trait distribution. We illustrate our findings by in-depth analysis of the variance evolution. We also reanalyze a well known mathematical model for gypsy moth population showing that the knowledge of how distributions evolve allows producing oscillatory behaviors for highly heterogeneous populations.