In this project, I examine how life on the seafloor recovers after disturbances, such as bottom trawling, and which factors affect the recovery potential of biological communities. The project produces a modeling tool that can be used to assess environmental impacts in the marine environment by predicting the probability of recovery of the seafloor community in a specific area. The combination of probability calculus and machine learning methods produces new information on the recovery potential of marine ecosystems using historical time-series data and field observations from underwater imaging systems.
