Capture-Mark-Recapture II Online Course

Center for Wildlife Studies
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COURSE DESCRIPTION: 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. As with the Intro course, we will focus on applying hypothetico-deductive reasoning to guide project development, as even ‘simply’ estimating demographic parameters will almost always benefit from thinking in terms of biological hypotheses. Only after defining the questions and scale can we identify the appropriate sampling methods, which should be rooted in animal behavior and ecology, and analytical framework. Throughout the course we will analyze a small number of real-world datasets. This allows a deeper understanding of how the questions, sampling, and analyses function as a whole, instead of using disparate projects that can distract students. To accommodate different strengths and learning styles, we will use both 'canned' (e.g., program MARK) and command-line software (program R) during online lectures and practical exercises. TOPICS: - Asking the right question; identifying objectives; defining your study population; and hypothesis development - Foundations of modeling CMR (i.e., detection, non-detection) data, logistic regression, and point process models - Open and closed population, spatially-explicit capture-recapture and mark-resight models - Modeling state transitions (i.e., multi-state CMR) - Linking animal behavior, population status, and life history to sampling and analyses - Model selection theory, assumptions, and limits - Using simulations to refine study design - Use of auxiliary data and covariates to model observation and state processes - Applications to other frameworks such as integrated population and matrix models FORMAT: This is a 1-credit equivalent academic course (16 contact hrs + additional work) where you learn at your own pace over 3 months. 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. DATES: August 7 - September 1, 2023 (with access to course through Oct 29, 2023) COST: $600 professional / $500 student ESA & TWS CEUs included for FREE!
PREREQUISITES: Introductory statistics; Introduction to CMR or similar training; basic competence in R; and familiarity with logistic regression, population ecology, and animal behavior.
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Jessica Kennelly
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