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A hierarchical model for estimating density in camera-trap studies
Article first published online: 20 NOV 2008
DOI: 10.1111/j.1365-2664.2008.01578.x
© 2008 The Authors. Journal compilation © 2008 British Ecological Society
Additional Information
How to Cite
Royle, J. A., Nichols, J. D., Karanth, K. U. and Gopalaswamy, A. M. (2009), A hierarchical model for estimating density in camera-trap studies. Journal of Applied Ecology, 46: 118–127. doi: 10.1111/j.1365-2664.2008.01578.x
Publication History
- Issue published online: 14 JAN 2009
- Article first published online: 20 NOV 2008
- Received 23 June 2008; accepted 24 September 2008; Handling Editor: Paul Lukacs
Keywords:
- Bayesian analysis;
- camera trapping;
- carnivore surveys;
- density estimation;
- hierarchical model;
- Markov chain Monte Carlo;
- point process;
- spatial capture–recapture;
- tigers;
- trapping grid
Summary
- 1Estimating animal density using capture–recapture data from arrays of detection devices such as camera traps has been problematic due to the movement of individuals and heterogeneity in capture probability among them induced by differential exposure to trapping.
- 2We develop a spatial capture–recapture model for estimating density from camera-trapping data which contains explicit models for the spatial point process governing the distribution of individuals and their exposure to and detection by traps.
- 3We adopt a Bayesian approach to analysis of the hierarchical model using the technique of data augmentation.
- 4The model is applied to photographic capture–recapture data on tigers Panthera tigris in Nagarahole reserve, India. Using this model, we estimate the density of tigers to be 14·3 animals per 100 km2 during 2004.
- 5Synthesis and applications. Our modelling framework largely overcomes several weaknesses in conventional approaches to the estimation of animal density from trap arrays. It effectively deals with key problems such as individual heterogeneity in capture probabilities, movement of traps, presence of potential ‘holes’ in the array and ad hoc estimation of sample area. The formulation, thus, greatly enhances flexibility in the conduct of field surveys as well as in the analysis of data, from studies that may involve physical, photographic or DNA-based ‘captures’ of individual animals.