Skip to main content
Dryad

Data from: Continuous-time spatially explicit capture-recapture models, with an application to a jaguar camera-trap survey

Foster, Rebecca, University of Belize, Panthera Corporation
Harmsen, Bart, University of Belize, Panthera Corporation
Milazzo, Lorenzo, University of Cambridge
Distiller, Greg, University of Cape Town, https://orcid.org/0000-0001-9033-9320
Borchers, David, University of St Andrews
greg.distiller@uct.ac.za
Published Apr 21, 2014 on Dryad. https://doi.org/10.5061/dryad.mg5kv

Cite this dataset

Foster, Rebecca et al. (2014). Data from: Continuous-time spatially explicit capture-recapture models, with an application to a jaguar camera-trap survey [Dataset]. Dryad. https://doi.org/10.5061/dryad.mg5kv

Abstract

  1. Many capture-recapture surveys of wildlife populations operate in continuous time but detections are typically aggregated into occasions for analysis, even when exact detection times are available. This discards information and introduces subjectivity, in the form of decisions about occasion definition.
  2. We develop a spatio-temporal Poisson process model for spatially explicit capture-recapture (SECR) surveys that operate continuously and record exact detection times. We show that, except in some special cases (including the case in which detection probability does not change within occasion), temporally aggregated data do not provide sufficient statistics for density and related parameters, and that when detection probability is constant over time our continuous-time (CT) model is equivalent to an existing model based on detection frequencies. We use the model to estimate jaguar density from a camera-trap survey and conduct a simulation study to investigate the properties of a CT estimator and discrete-occasion estimators with various levels of temporal aggregation. This includes investigation of the effect on the estimators of spatio-temporal correlation induced by animal movement.
  3. The CT estimator is found to be unbiased and more precise than discrete-occasion estimators based on binary capture data (rather than detection frequencies) when there is no spatio-temporal correlation. It is also found to be only slightly biased when there is correlation induced by animal movement, and to be more robust to inadequate detector spacing, while discrete-occasion estimators with binary data can be sensitive to occasion length, particularly in the presence of inadequate detector spacing.
  4. Our model includes as a special case a discrete-occasion estimator based on detection frequencies, and at the same time lays a foundation for the development of more sophisticated CT models and estimators. It allows modelling within-occasion changes in detectability, readily accommodates variation in detector effort, removes subjectivity associated with user-defined occasions, and fully utilises CT data. We identify a need for developing CT methods that incorporate spatio-temporal dependence in detections and see potential for CT models being combined with telemetry-based animal movement models to provide a richer inference framework.

Usage notes

Camera trap survey (April-July 2011) of jaguars in Belize.

The data are from a camera trap survey of jaguars in Cockscomb Basin Wildlife Sanctuary in Belize (UTM 0348113, 1854515 WGS84). The survey used nineteen paired camera stations and ran for 90 days (April - July 2011). Two Excel worksheets are provided, one contains all the capture information (including the coordinates of each camera station) and the other one has details of trap failures.

Funding

Location

Cockscomb Basin Wildlife Sanctuary
Belize