July 16th-20th, 2018
Boston University
As part of the NSF-funded Near-term Ecological Forecasting Initiative this course funds 15 graduate students, post-docs, and early career academic scientists and 5 early career agency scientists interested in learning about ecological forecasting in a variety of contexts. This course is adapted from the newly published Ecological Forecasting book by Dr. Michael Dietze and will highlight iterative forecasting approaches.
Topics include Bayesian statistics (simple models, hierarchical Bayes, state-space models, etc); fusing multiple data sources; forecast uncertainty propagation & assessment; iterative data assimilation; machine learning; decision science; and a range of ecological forecasting applications such as phenology, microbiomes, carbon, infectious disease, and aquatic productivity.
Instructors include Michael Dietze (Boston University), Shannon LaDeau (Cary Institute of Ecosystem Studies), Kathleen Weathers (Cary), Jennifer Bhatnagar (BU), Colin Averill (BU), Barbara Han (Cary), and Melissa Kenney (University of Maryland).
Applications are due February 16th, 2018
Application materials include:
- CV
- Cover letter (experience with R, coding, and statistics; why you want to take this course; what sort of problems are you interested in; and why are you excited to participate)
- Contact information for advisor (may be contacted later to provide a reference)
Application materials and any questions can be emailed to nefi.course@gmail.com.
There are no strict ‘prerequisites’ for the NEFI summer course. The course is largely R based so we will give preference to students that have a basic familiarity with R (basic data manipulation, visualization, and regression). Prior exposure to basic research computing skills (e.g. Software Carpentry) and data management/analysis skills (e.g. Data Carpentry) is helpful but not required. Prior experience with Bayes is likewise not required.
PDF of Summer Course Flyer
Course location
The course is being hosted by Boston University’s Frederick S. Pardee Center for the Study of the Longer-Range Future. Located at 67 Bay State Road Boston, MA 02215, we’ll be in a cozy old brownstone located just a block off of Kenmore Square / Fenway Park and <5 min from the Hotel Buckminster. By subway, take a Green Line B, C, or D train to Kenmore Square.
Course schedule
The day-by-day syllabus builds off of Prof. Dietze’s (MD) existing graduate course on Ecological Forecasting and the book that goes with the course. Additional lectures are provided by Melissa Kenney (MK), Shannon LaDeau (SL), and Barbara Han (BH), with hands-on activities led by the NEFI team.
The course provides a mix of lectures and hands-on applications, including a final end-of-week group project.
Lectures
Decision Structuring and Indicators
Handout: consequence table
Characterizing Uncertainty (Bayes beyond the basics)
Machine Learning
Expert Elicitation
Uncertainty Propagation & Analysis
Decision Trade-offs and Value of Information
Miscellaneous
Postdoc Ad: Margaret Evans