Identification of the Type of Population Dynamics of the Green Oak Tortrix with a Generalized Discrete Logistic Model

Abstract

Abstract—This paper deals with the identification of the type of population dynamics of the green oak tortrix (Tortrix viridana L.) by the available time series with a generalized discrete logistic model. The results of estimates of model parameters obtained by the ordinary least squares (OLS) method and model parameters obtained by the method of extreme points (MEP) are compared. It is assumed that the model adequately describes the population dynamics if and only if the deviations of the theoretical (model) data from the empirical data meet a number of statistical tests. It is shown that the model using OLS estimates does not provide adequate fitting of time series and the type of population dynamics cannot be identified. Analysis of four variants of MEP estimates shows that the observed regime of the population dynamics is not cyclic (if the length of the cycle is less than 15 000 years); in addition, a rapid decrease in the values of the autocorrelation function, followed by their fluctuation in a narrow range, is observed for all regimes.