Related Experiment Video
Updated: Jul 6, 2026

Methodology for Developing Life Tables for Sessile Insects in the Field Using the Whitefly, Bemisia tabaci, in Cotton As a Model System
Published on: November 1, 2017
Asymptotic distribution of density-dependent stage-grouped population dynamics models
Mélanie Zetlaoui1, Nicolas Picard, Avner Bar-Hen
1Institut National Agronomique Paris-Grignon, OMIP, 16 rue Claude Bernard, 75231 Paris Cedex 5, France.
Abstract:
Matrix models are widely used in biology to predict the temporal evolution of stage-structured populations. One issue related to matrix models that is often disregarded is the sampling variability. As the sample used to estimate the vital rates of the models are of finite size, a sampling error is attached to parameter estimation, which has in turn repercussions on all the predictions of the model. In this study, we address the question of building confidence bounds around the predictions of matrix models due to sampling variability. We focus on a density-dependent Usher model, the maximum likelihood estimator of parameters, and the predicted stationary stage vector. The asymptotic distribution of the stationary stage vector is specified, assuming that the parameters of the model remain in a set of the parameter space where the model admits one unique equilibrium point. Tests for density-dependence are also incidentally provided. The model is applied to a tropical rain forest in French Guiana.
Related Concept Videos
Modeling with Differential Equations
Population Growth
Exponential Equations for Modeling Growth
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Growth Models with Integration: Problem Solving
Life Histories
