PARALLEL SIMULATION OF INDIVIDUAL-BASED, PHYSIOLOGICALLY STRUCTURED POPULATION-MODELS

A general scheme for parallel simulation of individual-based, structur ed population models is proposed. Algorithms are developed to simulate such models in a parallel computing environment. The simulation model consists of an individual model and a population model that incorpora tes the individual dynamics. The individual model is a continuous time representation of organism life history for growth with discrete allo cations for reproductive processes. The population model is a continuo us time simulation of a nonlinear partial differential equation of ext ended McKendrick-von Foerster-type. As a prototypical example, we show that a specific individual-based, physiologically structured model fo r Daphnia populations is well suited for parallelization, and signific ant speed-ups can be obtained by using efficient algorithms developed along our general scheme. Because the parallel algorithms are applicab le to generic structured populations which are the foundation for popu lations in a more complex community or food-web model, parallel comput ation appears to be a valuable tool for ecological modeling and simula tion.