Early Bird Discount Ends: Introduction to Spatial Analysis in QGIS (ONLINE)

Applications for our 2023-2024 Tropical Forest Landscapes: Conservation, Restoration & Sustainable Use online certificate program are now open!

Celebrating the program’s fifth year, we are pleased to offer this unique opportunity to connect with Yale experts and environmental professionals worldwide.

March 1, 2023 - Early notification deadline (receive your decision by March 24)
April 7, 2023 - Final application deadline

This course—curated by Michigan State University, Forest Carbon and Climate Program— develops foundational knowledge on the relationship between climate regulation, forests, and forest carbon. In five presentations, the course covers: 1) Carbon Cycle and Storage; 2) Humans, the Global Carbon Cycle, and Terrestrial Sinks; 3) Forest Ecosystems and Carbon Storage; 4) Forest Ecosystem Carbon Pools and Fluxes; and 5) Disturbances and their Carbon Impact. Each presentation focuses on key topics and features unique learning outcomes for participants. Course content includes recorded presentations, links to online resources, and recommended reading. 

• • Early bird course fee (ends April 24): $500 professional / $400 student

  • Regular course fee (after April 24): $550 professional / $450 student

  • ESA CEU: included for FREE

  • Recommended prerequisite for Plant Community Assessment (Online)

No instructor support (3 months of access to course materials)

• June 5 - Aug 25 (early bird ends May 1): $400 professional / $300 student

No instructor support (3 months of access to course materials)

• June 5 - Aug 25 (early bird ends May 1, 2023): $400 professional / $300 student

No instructor support (3 months of access to course materials)

• June 5 - Aug 25 (early bird ends May 1): $350 professional / $250 student

DATES: June 5 - August 27, 2023

Generalized linear models are widely used throughout ecology and wildlife management, as they allow us to analyze a wide variety of data, including counts, proportions, and continuous measurements such as length and weight. Being able to fit and interpret these models in R is a basic requirement for modern quantitative ecology. We cover Poisson and binomial models in detail, and extensions of these when the data are overdispersed and/or zero-inflated. We discuss model-checking and residual diagnostics, to see how well our model fits the data, and model comparison using AIC in order to see which terms should be included. Repeated measurements data, in which the response variable is measured at several points in time, are also considered in detail. We explain the distinction between fixed and random effects and show how to fit models that involve random effects. We make extensive use of R throughout the course.

(1) Instructor support. Reach out to your instructor over a 1-month period to get help as you work through prerecorded lectures, problem sets, and your own personal work. You then have access to the course for an additional 2 months. Instructor support includes emailing your instructor, accessing live discussion threads, and scheduling one-on-one appointments (Zoom or phone) about course material, your research, datasets from work, etc. You MUST select this option if you want to take the course for academic credit at your home institution or you would like to work with an instructor on a dataset from school or work.

(2) No instructor support (3 months of access to course materials)

• Early bird course fee (ends May 7): $350 professional / $250 student

• Regular course fee (after May 7): $400 professional / $300 student

Dates: Begins June 5, 2023

This course builds on and extends the scope of the questions, data types, and analytical methods covered in the Introduction to Capture-Mark-Recapture course.  In particular, we will go into depth on spatially-explicit methods, including mark-recapture and mark-resight models, their underlying assumptions, and more advanced applications such as explaining variation in density patterns and developing long-term monitoring programs.

You have two options when enrolling in this course:

(1) Instructor support. Reach out to your instructor over a 1-month period to get help as you work through prerecorded lectures, problem sets, and your own personal work. You then have access to the course for an additional 2 months. Instructor support includes emailing your instructor, accessing live discussion threads, and scheduling one-on-one appointments (Zoom or phone) about course material, your research, datasets from work, etc. You MUST select this option if you want to take the course for academic credit at your home institution or you would like to work with an instructor on a dataset from school or work.

• Early bird course fee (ends May 8): $600 professional / $500 student

• Regular course fee (after May 8): $650 professional / $550 student

(2) No instructor support. Sign up anytime over a 3-month period and learn at your own pace as you work through prerecorded lectures and problem sets. Be aware that at any time during the first month, you may upgrade to receive Instructor support.

• Early bird course fee (ends May 8): $375 professional / $275 student

• Regular course fee (after May 8): $400 professional / $300 student

• Early bird course fee (ends May 8): $550 professional / $450 student

• Regular course fee (after May 8): $600 professional / $500 student

DATES: May 22 - June 18, 2023

• Early bird course fee (ends May 29): $500 professional / $400 student

• Regular course fee (after May 29): $550 professional / $450 student