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Quick Guide
Quick Guide
Topic: Freshwater and terrestrial ecology
Data-driven, computer-based project but no coding
Pre-semester work available to help learn software
Introduction to Global Change Ecology
Introduction to Global Change Ecology
The most pressing environmental challenges, such as climate change, biodiversity loss, and ecosystem sustainability, are globally pervasive. Solving these challenges will require new ecological understandings, including those generated from large-scale, collaborative approaches. Furthermore, the complexity of these challenges will require a community of researchers with differing cultural and social backgrounds to create innovative solutions. Therefore, there is a need to train a new generation of researchers that are both 1) highly skilled in working collaboratively on research projects that are quantitative/computational in nature and 2) passionate about working on complex ecological questions. This research area addresses both of those goals.
Students in this research area have the ability to ask a wide range of scientific questions. By leveraging the expertise of the instructional team, students will have support on questions spanning geographic and biological scales (e.g., microbial and plant physiology to community and ecosystem ecology). By leveraging the infrastructure and the existing 10-year dataset of the NutNet research collaborative, students will also be able to put their research in a global and historical context. The NutNet experimental infrastructure will allow students to frame new research questions to match their interests and needs, but examples could include the following: 1) Do herbivores or nutrients have greater impacts on floral production in grassland ecosystems? 2) Does fertilization with nitrogen or phosphorus have different impacts on microbial community dynamics within grassland ecosystems? 3) Do different nutrient types or combinations impact plant susceptibility to fungal or viral infection? In addition to the NutNet data, students also have the option to find and analyze any publicly available data set that relates to their research question.
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