This course consists of 6 chapters or modules, each made up of 2-4 short videos. These are a mix of theory and practice - see the descriptions below.
The 3 videos in this module introduce you
to important concepts behind survey design decisions
Learn about the design-based paradigm of inferring animal abundance, requiring a random sample of the survey region.
Learn how dividing your survey region up into subregions can deliver better design-based inferences.
Learn about an alternative paradigm for inferring abundance, which relies on relating animal density and detectability to covariates.
In the 4 videos in this module we look at how to place camera traps
for a single survey
We cover some of the key concepts behind SCR survey design, including precision and bias, and the importance of sample size.
Concepts from the previous video are put into practice by illustrating a few "hero" (good) and "villain" (bad) designs.
We look at software for creating and testing potential survey designs.
SCR survey design is an evolving field and in this last video of the module we look at some newer, more advanced approaches to survey design.
The 2 videos in this module look at an extra design stage useful when surveying very large regions
SCR models jointly model animal density and detectability. The 2 videos in this model look at detectability
Having covered detectability, the 2 videos in this module look at the other side of an SCR model: a model for animal density
These 2 videos show you the basics of fitting SCR models using the R package secr
We describe some of the basic options for setting up data for analysis with secr.
We learn about using secr to estimate the parameters of the SCR model and draw inferences about animal density and detectability.