Quantitative tools for ecologists

A minor focus in the MEC Lab is the refinement or development of quantitative tools for ecological use. For example, Dr. Nunez-Mir introduced automated content analysis (ACA) to the broader ecological and evolutionary biology community in an  article published in Methods in Ecology and Evolution, and follow-up blogpost in the journal’s Methods.blog. Automated content analysis (ACA) refers to a suite of text-mining, machine-learning algorithms that use probabilistic models to identify and quantify the concepts and themes discussed in a body of literature. We have used ACA to explore a variety of questions, such as “are sociecological challenges being addressed in forestry research?” and “how have research themes shifted in the past four decades of ecological research?”

Stay tuned to learn more about BattyCoda, a manual and automated annotation tool for bat calls developed with Dr. Angeles Salles from UIC.