The purpose of the study is to construct insect stochastic population dynamic models, which describe causes of insect population stochastic fluctuation by exogenous and endogenous factors. The WGM is constructed according to stochastic theories and by means of statistical methods. There are statistical model, temperature-dependence development model and quantitative population simulation model. These models are built mainly by regressing the density of insect population with environmental factors, accumulating development time distribution and considering both of temperature-dependent development rate and developmental time distribution, respectively. Driving of deterministic insect population models mentioned above by WGM, we get the randomized models for pest management strategy and decision making risk analysis.
Users can use it for risk analysis and decision making in pest management.
To simulate stochastic models with the form of differential equations, we employed Monte Carlo simulation method and scientific visualization techniques, and gave out the results in both text and graphic forms. These are helpful in both theoretical and practical aspects for understanding endogenous mechanism of population dynamics and applying stochastic models in real world. Nonlinear dynamics and chaos in insect populations is a new subject in theoretical ecology. With introducing of nonlinear dynamics and chaos theory, several nonlinear models of single species population, such as discrete time logistic model, Ricker model and Hassell model, were simulated. Their behaviors or model trajectories were represented by means of bifurcation diagram.