Introduction to Occupancy Modeling

Species presence/absence is a fundamental concept used in many areas of ecology (e.g., species distributions, habitat modeling, monitoring, and metapopulation studies), however imperfect detection can lead to false absences. Unaccounted for false absences can lead to misleading inferences about patterns and dynamics of species occurrence and the factors that influence them. We will learn methods for accounting for imperfect detection with species detection/non-detection data and also discuss important study design considerations. Exercises are completed using Program PRESENCE and RPresence. You will have 3 months of access to course materials as you work at your own pace. 

Webinar: Design advice for species occurrence studies - Darryl’s 5 top tips.

Learn at your your own pace without instructor support.

Spring: March 2 – May 24, 2026 (Early bird ends February 1)

Summer: Jun 1 – Sept 6, 2026 (Early bird ends May 3)

*Early bird saves $75

This course is for those with no, or little, experience with occupancy modeling, but more experienced users may also benefit from attending. Familiarity with regression, logistic regression, or generalized linear modeling would be advantageous (e.g., R Boot Camp, Ecological Statistics and Modeling, & Generalized Models). Suggested readings for the course:

MacKenzie, D. I., Nichols, J. D., Lachman, G. B., Droege, S., Royle, J. A., & Langtimm, C. A. (2002). Estimating site occupancy rates when detection probabilities are less than one. Ecology, 83(8):2248–2255.

By the end of the course, learners will be able to:

• Explain the conceptual and statistical foundations of occupancy modeling and its role in estimating ecological patterns under imperfect detection.

• Apply single-season occupancy models to analyze ecological data, including incorporation of detection processes, covariates, and unequal sampling effort.

• Evaluate model assumptions, compare competing models, and interpret results using probability-based inference and multi-model approaches.

• Design effective occupancy-based monitoring studies by selecting sampling units, structuring repeat surveys, and allocating sampling effort appropriately.

• Describe and apply multiple-season occupancy models to investigate temporal dynamics such as colonization, extinction, and long-term change.

• Analyze and interpret occupancy data using R-based analytical tools.

• 16 CEUs with The Wildlife Society

• 4 CEUs in Category I(a): Scientific Education and Training with the Ecological Society of America

• Go to our Continuing Education Page for more details