Summer Course 2018

Info for 2019 course can be found here

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

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

Course Schedule_ NEFI 2018


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.


Welcome & Introductions

Why Forecast?

Decision Structuring and Indicators

Handout: consequence table

Characterizing Uncertainty (Bayes beyond the basics)

Hierarchical Bayes

Machine Learning

State Space Models

Expert Elicitation

Uncertainty Propagation & Analysis

Analytical Data Assimilation

Numerical Data Assimilation

Data Fusion

Decision Trade-offs


Project Intros

Participant lightning talks

Example Scripts

Postdoc Ad: Margaret Evans