Software for spatially explicit capture–recapture

Latest:  secr 4.3.1 and openCR 1.4.4 2020-09-02, secr app 1.3 2020-09-07

Spatially explicit capture–recapture (SECR or SCR) is used to estimate the density of an animal population from capture–recapture data collected using an array of 'detectors'.  

Detectors may be live-capture traps, with animals uniquely marked; they also may be sticky traps or snags that passively sample hair, from which individuals are distinguished by their DNA microsatellites, microphones, or cameras that take photographs from which individuals are recognized by their natural marks. It is also possible to analyse data obtained by searching areas for animals or identifiable cues such as faeces. 

Any SECR model includes a spatial model of the detection process, allowing population density to be estimated without bias from edge effects and incomplete detection.  Maximum likelihood (ML SECR), inverse prediction (IP SECR) and data augmentation in a Bayesian framework are alternative methods for fitting the spatial detection model (Efford 2004, Borchers & Efford 2008, Royle & Young 2008).  See What is SECR? for more.

This site supports three varieties of SECR software :

secr allows a wide range of analyses and has superceded DENSITY. A graphic interface is still convenient for simple analyses and as an introduction. The Shiny application 'secr app' serves this purpose. It can be run directly from GitHub or without any setup on a University of Otago machine. See the step-by-step tutorial.

The package secrdesign offers tools for simulation and study design, and you really should check out secrdesignapp.

The R package openCR offers both nonspatial and spatial open population analyses.

Questions, suggestions and bug reports should be directed to the DENSITY | secr forum at phidot.org or the Google group secr.

Last updated: 7 September 2020

University of Otago DENSITY: software for spatially explicit capture-recapture