4. Occupancy estimation

Tuesday

• READING: CHAPTER 7 CONROY AND CARROLL (2009)

• Basics of occupancy estimation and modeling

  • Rationale for occupancy analysis

  • Structure of occupancy data

  • Basic sampling design

  • Essentials of estimation and model comparison (likelihood, AIC, MMI)

• Single-season occupancy estimation

  • Homogeneous detection

  • Detection varying by samples

  • Incorporation of covariates

  • Using R -unmarked to estimate occupancy under the basic design

    • R script

    • Data

• Issues in study design to estimate occupancy 

• Using R to simulate sample sizes needed for single-season occupancy studies

  • • • R script for sample size approximation

      • R script for sample size simulation

• Other approaches for analysis of occupancy data

  • Program PRESENCE

  • Program MARK/ RMark

Thursday 

Reading- Royle-Nichols models and Royle count models

• Modeling site heterogeneity in detection and occupancy

  • Royle-Nichols model, Royle count model

    • Files -- R unmarked script

• Multi-season occupancy: overview 

• Multi-season occupancy in R - unmarked

• Design of multi-season studies- overview

• Using R to simulate sample sizes needed for multi-season occupancy studies 

  • Files --Sample size simulation

Material by Richard Chandler on package unmarked

Assignment