FALL 2022: Data Science for Ecologists. Computers are essential in ecological research and modern research is increasingly required to be reproducible, collaborative, and efficient. This means that data and software to conduct analyses must be managed, archived, documented, and accessible. This course will introduce a set of computing skills, equivalent to basic lab skills, necessary for conducting reproducible, collaborative, and efficient computer-based research. Students will learn the basics of literate programming – writing code that a computer can execute and a human reader can understand – and data-science skills, including data management, manipulation, visualization, and analysis, with an emphasis on ecological problems. The course will be taught using R and RStudio but other tools for data management and collaboration (e.g. git and GitHub, OpenRefine) will be introduced. No previous experience with R or any programming language is necessary, we will start from the beginning. If you have questions or trouble registering, please contact the instructor (caz AT tulane).
SPRING 2023: Mathematical Models in Ecology and Evolution. Students are taught to use the R programming language to construct and analyze models including individual based models, evolutionary models. This is a graduate level class but open to advanced undergraduates with instructor’s permission.
Population Ecology (usually taught in fall semester in odd numbered years). A course that covers the principle methods and models of population ecology.
Urban Ecology (usually taught in Spring Semester in even numbered years). Urban Ecology is the study of the ecology of cities and the study of anthropogenic influences on global, regional and local ecology. Students can participate in 20 hours of service learning. Our service learning partners in 2022 were Edible Schoolyard New Orleans and Grow On Urban Farms