Related Experiment Video
Updated: Jul 19, 2026

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Published on: July 4, 2007
Transient population dynamics in periodic matrix models: methodology and effects of cyclic permutations
Shana K Mertens1, Jonathan M Yearsley, Frank van den Bosch
1Rothamsted Research, Harpenden AL5 2JQ UK. shana.mertens@bbsrc.ac.uk
Abstract:
Many biological populations are subject to periodically changing environments such as years with or without fire, or rotation of crop types. The dynamics and management options for such populations are frequently investigated using periodic matrix models. However the analysis is usually limited to long-term results (asymptotic population growth rate and its sensitivity to perturbations of vital rates). In non-periodic matrix models it has been shown that long-term results may be misleading as populations are rarely in their stable structure. We therefore develop methods to analyze transient dynamics of periodic matrix models. In particular, we show how to calculate the effects of perturbations on population size within and at the end of environmental cycles. Using a model of a weed population subject to a crop rotation, we show that different cyclic permutations produce different patterns of sensitivity of population size and different population sizes. By examining how the starting environment interacts with the initial conditions, we explain how different patterns arise. Such understanding is critical to developing effective management and monitoring strategies for populations subject to periodically recurring environments.
Related Concept Videos
Population Growth
Modeling with Differential Equations
Mechanistic Models: Compartment Models in Individual and Population Analysis
Properties of Laplace Transform-II
Time differentiation involves analyzing the rate of change of a function over time. Mathematically, it is the derivative of a function with respect to time. This concept can be likened to tracking...
Analysis of Population Pharmacokinetic Data
Exponential Equations for Modeling Growth
