Study design for spatial capture-recapture

Chris Sutherland

2020-06-17

Using this book

0.1 Why should you read this book?

Why we did this

0.2 Why should you use oSCR

The main function in oSCR does likelihood analysis of several classes of spatial capture-recapture (SCR) models. THere are also a suite of helper fnctions for formatting and processing data objects. Here are a few of the things that motivated our development of the package:

1. 100% native R code, making it (reasonably) accessible to people who know R and, presumably extensible by ordinary R programmers.
2. Because it’s written in R you can look at the code to figure out exactly what’s going on.
3. It’s quite a bit slower compared to secr but we think it’s quite robust to massive sized problems.
4. The data structure is relatively simple, just as ordinary R lists (for the most part).
5. The models accommodate least-cost path models and models that include telemetry data and resource selection functions
6. oSCR forces you to define the state-space of the point process which we think is important.

0.3 Getting set up

So, using this book of course requires that the oSCR package is loaded:

#remotes::install_github("jaroyle/oSCR") 
library(oSCR)

But you will also need a few others:

library(ggplot2)
library(raster)
library(sf)
library(viridis)

If you have any issues or questions, we have a very responsive, and friendly user group.