Modelling of population dynamics of insects in any ecosystem with several distributions of insect development: A Review: Presentation

Predicting the occurrence of insects with a high accuracy requires the estimation of insect development time and the variation among individuals for each life stage and species under different environmental conditions such as fluctuating temperature, variation of relative humidity, different body sizes and stages of the insects, levels of crowding, and food supply. This review summarized the modeling methods of population dynamics of insects with several distributions of insect development, assumption and prediction accuracy of these developed models, and disadvantages and advantages of these modelling methods. These modeling methods include degree day model, nonlinear model, and distribution delay models. The structure of most common models are cohort, Leslie matrix, simulation, and individual based. The relationships among the modeling assumptions, effects of temperature, and other environmental factors, and structures of the developed models were examined. A new modelling approach such as physiological-biological time scale and chaos theory was suggested.Predicting the occurrence of insects with a high accuracy requires the estimation of insect development time and the variation among individuals for each life stage and species under different environmental conditions such as fluctuating temperature, variation of relative humidity, different body sizes and stages of the insects, levels of crowding, and food supply. This review summarized the modeling methods of population dynamics of insects with several distributions of insect development, assumption and prediction accuracy of these developed models, and disadvantages and advantages of these modelling methods. These modeling methods include degree day model, nonlinear model, and distribution delay models. The structure of most common models are cohort, Leslie matrix, simulation, and individual based. The relationships among the modeling assumptions, effects of temperature, and other environmental factors, and structures of the developed models were examined. A new modelling approach such as physiological-biological time scale and chaos theory was suggested