Stochastic Differential Equations As Insect Population Models

  • Brian Dennis
Part of the Lecture Notes in Statistics book series (LNS, volume 55)


Stochastic differential equations are a potentially important class of models for describing insect population dynamics. Their advantages include ease of use, relative tractability, ease of understanding, and the potential for approximating many types of stochastic variation affecting insect populations. This paper is an exposition for quantitative ecologists on parameter estimation for one-dimensional stochastic differential equations. Stochastic versions of the exponential growth model and the logistic model are developed in detail as examples. Topics discussed include transition distributions and moments, stationary distributions, maximum likelihood estimates, conditional least squares estimates, maximum quasi-likelihood estimates, jackknifing, multiple stable and unstable equilbria, and deterministic chaos.


Stationary Distribution Stochastic Differential Equation Population Abundance Insect Population Deterministic Chaos 
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Copyright information

© Springer-Verlag Berlin Heidelberg 1989

Authors and Affiliations

  • Brian Dennis
    • 1
  1. 1.College of Forestry, Wildlife and Range SciencesUniversity of IdahoMoscowUSA

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