Instructors: Walter Jetz, Adam M. Wilson, Giuseppe Amatulli (EEB)
The course will provide an introduction and hands-on exposure to computational and statistical approaches for the analysis of biodiversity data in a geographical, environmental and conservation context. After a general overview of relevant hot topics and questions in conservation and ecology and their associated methodologies and data sources, we will introduce a set of example questions that we then address with a variety of datasets and methods. A particular focus will be the analysis of species distributions and abundances in changing landscapes using remotely sensed environmental information. Beyond broadly available data and methods, students will be able to explore new biodiversity-relevant remote sensing products under development with NASA and prototype tools available through the Yale-based Map of Life project and its partnership with the Google Earth Engine team. By the end of the semester, participants will have gained hands-on experience in spatial analysis and modeling relevant for biodiversity and conservation science and have learnt about key associated concepts and also about potential pitfalls. They will have worked through case studies from forestry, species distribution modeling, biodiversity, and remote sensing data processing. The course is associated with the Yale (YIBS) Program in Spatial Biodiversity Science and Conservation and its activities.
The course is open to advanced undergraduate students and graduate students (postdocs are also welcome) with an interest in advancing their data analysis and modeling skill-set and at least some experience in GIS and statistical analysis in R (or who are willing to acquire it alongside).
The first organizational meeting will take place on Tuesday, January 20, at 2pm in OML 201 (the class will not meet in the first week of the semester). The course will meet weekly for 2-3 hours. Time and day will be determined based on the availability of participants. If you are interested in the course, but unable to attend this meeting, please directly contact email@example.com.