1. Familiarity with key statistical packages used in analysis of
mark-recapture and other data for fish and wildlife populations
2. Facility with the R programming language
3. Recognition of appropriate statistical tools for specific 
data problems in fish and wildlife population analysis, with 
emphasis on capture-mark-recapture data
4. Ability to apply the R statistical package to data 
manipulation and formatting for capture-mark-recapture analysis
5. Ability to use packages R, RMark, and MARK to appropriately 
analyze capture-mark-recapture data 
6. Ability to correctly interpret program output for performing 
appropriate statistical tests and the valid computation of 
estimates of abundance, survival, and other parameters from 
mark-recapture data
7. Ability to extend basic capture-mark-recapture models to 
more complex situations, including random effects and 
hierarchical structure
8. Ability to appropriately display in tabular and graphical 
form results of analyses for use in presentations, reports, and 
publications

•	Introduction to computing using R
•	Using R to manage data
•	Introduction to Capture-Mark-Recapture models
•	Introduction to programs MARK and RMark
•	Programs MARK and RMark details
•	Age and cohort structure
•	Model fit and multi-model inference 
•	Time and individual covariates; prediction
•	Tag recovery and live-dead models, Known fate models
•	Abundance estimation in closed CMR models
•	Abundance and recruitment estimation in open CMR models
•	Robust design for estimating abundance, survival, 
recruitment, and temporary emigration
•	Multi-state models and intro to simulation
•	Simulation and bootstrapping in R and MARK
•	Bayesian approaches for dealing with random effects and 
hierarchical structure