We’re looking at detectability this week in Environmental Monitoring & Audit. Here are some relevant links:

1. First, check out Guru and Jose’s video explaining why detectability is important in species distribution models (there’s also some bloopers).

2. Then we have Georgia’s post about setting minimum survey effort requirements to detect a species at a site.

3. Another by Georgia about her trait-based model of detection.

4. And finally, a paper showing that Georgia’s time to detection model can efficiently estimate detectability.

And if you want more about detectability, check out a few posts of mine.

Some statistics to get started

The subject Environmental Monitoring and Audit starts today. We’ll be delving into some statistics, so my introductory chapter on statistical inference for an upcoming book might be useful.

And we’ll be using R, so if you need a quick introduction, check out Liz Martin’s blog.

Edit: And if you want some more information about double sampling (from Angus’ lecture today), please read this blog post.

How many surveys to demonstrate absence?

In the lecture today in Environmental Monitoring and Audit, I mentioned the model examining how much search effort is required to be sufficiently sure of the absence of a species at a site. This was based on a paper by Brendan Wintle et al. (2012).

You can read more about this topic here, with an attempt at an intuitive interpretation of the model, and some links to other examples where the prior probability (base rate) matters.

If you are particularly keen, you can read a copy of the manuscript here.


Wintle, B.A. Walshe, T.V., Parris, K.M., and McCarthy, M.A. (2012). Designing occupancy surveys and interpreting non-detection when observations are imperfect. Diversity and Distributions 18: 417-424.