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A stochastic computer model for simulating population growth
Author(s) -
Sonleitner Frank J.
Publication year - 1977
Publication title -
population ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.819
H-Index - 59
eISSN - 1438-390X
pISSN - 1438-3896
DOI - 10.1007/bf02510937
Subject(s) - fecundity , logistic function , statistical physics , sigmoid function , population , density dependence , birth–death process , statistics , mathematics , logistic regression , monte carlo method , probability density function , biology , population model , exponential function , exponential growth , exponential distribution , demography , physics , computer science , mathematical analysis , machine learning , sociology , artificial neural network
Summary A model is described for investigating the interactions of age‐specific birth and death rates, age distribution and density‐governing factors determining the growth form of single‐species populations. It employs Monte Carlo techniques to simulate the births and deaths of individuals while density‐governing factors are represented by simple algebraic equations relating survival and fecundity to population density. In all respects the model's behavior agrees with the results of more conventional mathematical approaches, including the logistic model and Lotka's Law, which predicts a relationship betwen age‐specific rates, rate of increase and age distribution. Situations involving exponential growth, three different age‐independent density functions affecting survival, three affecting fecundity and their nine combinations were tested. The one function meeting the assumptions of the logistic model produced a logistic growth curve embodying the correct values or r m and K . The others generated sigmoid curves to which arbitrary logistic curves could be fitted with varying success. Because of populational time lags, two of the functions affecting fecundity produced overshoots and damped oscillations during the initial approach to the steady state. The general behavior of age‐dependent density functions is briefly explored and a complex example is described that produces population fluctuations by an egg cannibalism mechanism similar to that found in the flour beetle Tribolium . The model is free of inherent time lags found in other discrete time models yet these may be easily introduced. Because it manipulates separate individuals, the model may be combined readily with the Monte Carlo simulation models of population genetics to study eco‐genetic phenomena.