While working at the UC Davis organization, CodeLab, I had the opportunity to engineer different models for the data science firm, BlockScience. Their Python module, cadCAD, allows for the modeling of various systems represented as state machines.

One of the systems I created with real-world applications modeled ecosystems. The first iteration of this model simply utilized the Lotka-Volterra preadator-prey equations to model population changes between two species. Then, I injected different variables into reproduction rates and interaction factors between species to match the randomness of real-world ecosystems.

Afterward, using the generalized Lotka-Volterra equations, I modified the system to allow for multiple species to interact with each other. A predator to one species may also be prey to another species. At this stage, it becomes possible to fully model population changes among ecosystems.

This model was designed in submission of applications to ecology. Real-world data regarding population sizes, reproduction rates, death rates, of new ecosystems may be collected and input into the model to determine whether the ecosystem is stable. Additionally, the model can be run with the introduction of a new species to determine if a stable ecosystem will remain stable when new populations enter. Species may also be removed from the system to observe reactions by the ecosystem and determine keystone species.