Simulation modelling of arthropod population dynamics is a useful method for identifying knowledge gaps and generating new hypothesis about the ecology of the target species. In the case of agricultural pests, the consequences of different management tactics can be explored through simulation of population dynamics under different intervention regimes. We developed a computerized system for implementing both population dynamics and tactical simulation models. We assumed that the central process for population abundance and age-structure change is temperature-dependent development through different life stages. Developmental rates are accumulated and distributed based on the extended von Föerster equations. Temperature regimes can be simulated or entered as input data files. Empirical models for diapause induction and interruption based on temperature and photoperiod available for different species can be plugged in the general model. The system allows for simulation of either single or multiple cohorts and generations. It can be tailored according to the number of life stages of the target species, making it generic and flexible. A management simulation module was developed to explore user-defined tactics. Libraries were written containing the particular development rate functions and parameters published in the literature for each one of some species of agricultural interest. Two of them are presented here as examples of various dynamics and management scenarios. With Diatraea saccharalis (Crambidae) we illustrate the dynamics of multiple generations including diapause induction, spring post-diapause emergence and temporal change of arthropod phenology. With Anticarsia gemmatalis (Noctuidae), we analyze the discontinuous dynamics of a pest that immigrates every year in the middle of the summer and crashes in the autumn. We illustrate the management simulation module by exploring optimal timing of insecticide application for the control of D. saccharalis, assessed as the particular spray time that results in the highest reduction of population abundance.
doi: 10.1603/ICE.2016.45806