Overview

Some sources of the information found in this model:

The reason why the ants in the model keep changing the location of their nests:

• Science Direct “Army ants lack a permanent nest; instead, colonies alternate between a stationary stage, during which the queen is enlarged and laying eggs, and a nomadic phase, during which the colony often moves in search of food for their voracious larvae”

Agent Model

Click on the link, which will take you to AgentCubes. If you only want to view the model as is, click ‘Play’. If you wish to play around with the simulation settings and place your own agents, click on ‘Design.’ Click on the Play button to begin the model. Click on the red square to stop the model. Click on the triangle with the bar to observe the model passing one time step. If you are on Design mode, you can click the pencil to place agents into the model, and the eraser tool to erase agents, and the grid tool to place a large amount of agents in a rectangle. Sliding the bar left towards the turtle will slow down the model, while sliding the bar right toward the rabbit will speed up the model. Click on the undo button to reset the model to its original state.

To control some of the simulation properties that make up the model, click on the gear bar on the left and then click on ‘Simulation Properties.’ A table should pop up where you are able to input the different values of the four properties: hunger, death pheromone strength, follower pheromone strength, and ant frequency. Either use the + and - buttons to increment the values or manually input the values yourself to change how the model works when the constants are changed.

You can view the AgentCubes model without any software- it is free and online!

How model operates on bigger scales

This model works best on larger scales and bigger worlds. It makes the model more realistic, for larger ant trails and time to scatter. In smaller scales, the ants and predators don’t have enough space to roam and will encounter each other very quickly. It increases the probability of complete annihilation of a species and doesn’t provide useful information.

Like previously written, small scales breaks the model. In addition, placing too many ant hills next to eachother messes with the diffusion of the pheromones, because the ants themselves don’t have a value of the pheromone.

The model helped further my understanding of the effects of releasing ant pheromones and the predator-prey dynamic between ants and frogs. With just the default parameters of the model, you could observe that the pheromones are vital for ants to communicate and find prey, and if a leader ant is misled the whole trail could be marching in the wrong direction. With changing the simulation properties of the model, specifically, the randomness in this system also will change the outlook of the model every single run through, whether through the direction of the pheromone trail, or the likelihood of an ant mob overcoming a predator. Since all the agents move randomly in the world, the chances of drastic changes to the population are possible, just like in real life, but not likely. This is due to the fact that the ants are directed by a pheromone trail and will follow it.

VenSim Model

To use this model, first download the model. When clicking on the button that reads, “SimtoSim,” you can adjust the parameters shown by the slider bars to see how that affects the model and the graph.

You will need VenSim installed to open this model. Here is a link to the installation page (not a virus). LINK

Due to the model being mostly based on percentages, the model works on different scales, as long as they are proportional. This makes sense, too, because if you start with too many ants or too many spiders in a real life scenario, one population will overcome the other population.

The most common way I tried to break my model was testing unreasonable inputs for my slider bars and seeing how that fantastically would destroy my graph. Just like the delicate balance of life that is nature, populations can spiral out of control due to too much of an increase of one certain species or another. When doing so, my model will break - either with exponential growth of one population or the sudden crashing of populations.

Through the VenSim model, I learned that the dynamic between two populations is fragile and usually results in one population quickly taking over the other - which makes sense in real life scenarios, given army ants swarm through forest populations quickly and ruthlessly.