Ducknest data and a simulated line transect data set
Chapter 2 - Making distance sampling work
In this chapter you will learn about the assumptions that underlie distance sampling. As density/abundance metrics produced by distance sampling are estimates, measures of uncertainty (or precision) need to be associated with them. Finally, a few suggestions regarding how a distance sampling analysis might be conducted: beginning, middle and conclusion.
Assessing model performance
Model selection with ducknest dataset
- Exercise description
- Exercise instructions
- the data are in the Distance project used in Chapter 1, if you need to download it again, follow the link below
- Monte Vista Refuge ducknests Distance project zip file
- Narrative solution to ducknest model selection
- Exercise solution
Making distance sampling work (assumptions of the methods)
Measures of precision
Hints regarding performing distance sampling analyses
Analysing simulated line transect data, where true density is known
- Exercise description
- Exercise instructions
- Simulated line transect data Distance project zip file
- Question 2 of exercise: import data into a new project. May wish to view import demonstration video before attempting
- Capercaillie line transect data text file to import
- Capercaillie line transect data text file to import
- Simulated line transect data Distance project zip file
- Narrative solution to simulated line transect data
- Exercise solution