Speaker
Description
Author information:
Melissa Bather is a statistician from New Zealand, currently living in Vancouver, BC, Canada. She has a Master of Science in Statistics with First Class Honours from the University of Auckland—the birthplace of R! She is currently researching new methods to introduce multi-species models into the field of spatially explicit capture-recapture for the University of Auckland as well as working as a Product Operations Manager in AI.
Primary topic: Spatially explicit capture-recapture modelling with R
Abstract:
How do we know how many animals there are? When I was a child, I thought that ecologists ventured into animal habitats and counted every animal one by one. It turns out there is a much more efficient way to do this using statistics with the help of R.
Spatially explicit capture-recapture (SECR) models estimate animal population densities by modelling where and when animals are detected across an area of interest. They are important tools for conserving, monitoring, and managing animal species. Animals can be detected in many ways, including trapping and tagging, hair snares, camera traps, and even microphones that record animal vocalisations. This allows researchers to study animals from a broad range of sizes—from tiny mice and frogs all the way to grizzly bears and even whales—and in a wide range of different habitats. There are a handful of R packages that allow us to build SECR models quite simply using animal capture histories from numerous detection methods, including secr, ascr, and a newer package acre which is particularly good for acoustic SECR models.
This talk will introduce common animal detection methods, show how detections are recorded as capture histories, and demonstrate how SECR models can easily be implemented and interpreted in R.
Previous conferences:
I previously presented a talk about the same topic at the Cascadia R Conf in Seattle, Washington in 2023, however, this talk will have a stronger focus on R in particular.
External resources:
acre R package: https://github.com/b-steve/acre
secr R package: https://cran.r-project.org/web/packages/secr/secr.pdf
ascr R package: https://github.com/b-steve/ascr
If you used AI tools or services to support the preparation of this submission, please state the name and reason for using each of them.
No AI tools/services were used.
Additional Material or Paper
A brief blog post about my MSc dissertation (including code on GitHub, a PDF, and the presentation I gave): https://statisticsmelissa.netlify.app/posts/2026-02-12_dissertation/ (note that this has a stronger emphasis on acoustic capture-recapture, which is not necessarily the focus of this talk)
| Keywords: Please list up to 5 keywords to help us find the right session for your contribution. | statistical modelling, spatial statistics, ecology |
|---|---|
| Virtual Option | This submission is for onsite presentation primarily, but I would also like it to be considered for pre-recorded virtual presentation if I don't get an onsite slot |
| Video Recording | Video sharing is fine |
| The author(s) agree(s) to take responsibility and be accountable for the contents of the submission and is/are authorized to present it. | Confirm |