08/04/2026
Where do data scientists go camping? A random forest! 🌲
A “random forest” is a data science method that uses lots of data points to find patterns, making it the perfect camping spot for a data lover!
The data scientist, Bennett McAfee, has an interdisciplinary role at that combines computer science, mathematics, and specific knowledge - like environmental science for us! Data scientists aid in research by creating ecological models of past, current, and future environmental factors, with their changes and interactions. This type of work is essential not just for researchers, but for communities. Predicting what is or can happen will let researchers better understand ecosystems while preparing communities for potential change.
Bennett explains his work focuses on “extracting as much information as possible from real time data.” Much of the work goes into obtaining raw data, cleaning it, examining relationships among different data points, creating equations for those relationships in code, and using those equations to build models.
One of Bennett’s current projects is the Global Lakes Metabolism Respiratory (GLAMR). GLAMR is a centralized, public repository of estimates of ecosystem metabolism and related data for lentic water bodies worldwide. Bennett has been working on this project for about a year, helping to build a massive, reliable, open-source data collection. Another modeling project he has done looks at zooplankton movement in the water column over a day. Bennett is also helping the with angler surveying and our outreach team create a faster way to enter surveys from the organizations we host.
Have questions about these projects? Drop them below so we can ask the expert!