SIMULATING THE SEARCHING BEHAVIOR OF MARINE ZOOPLANKTON AND COUNTING PARKING SEQUENCES

Abstract

Marine zooplankton respond to a variety of chemical signals in order to better navigate their environment. Using observations of Gnathia marleyi and Orbicella faveolata as a comparison, we create a series of models to simulate their behavior. We start with I. Ra˜no’s model based on Valentino Braitenberg’s theory of Braitenberg vehicles. We then adapt this model to incorporate reading the gradient of the environment and add an energy reservoir to replicate the resting behavior observed in Gnathia marleyi. We also adapt the model into a stochastic differential equation to replicate the behavior observed in the coral larvae. In addition, we examine a new method for counting parking sequences, as defined by Ehrenborg and Happ, by counting the number of possible preference vectors that result in a given order of parked cars