Present address: ARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland, Australia.
Detection heterogeneity in underwater visual-census data
Article first published online: 11 NOV 2008
© 2008 The Authors Journal compilation © 2008 The Fisheries Society of the British Isles
Journal of Fish Biology
Volume 73, Issue 7, pages 1748–1763, November 2008
How to Cite
MacNeil, M. A., Graham, N. A. J., Conroy, M. J., Fonnesbeck, C. J., Polunin, N. V. C., Rushton, S. P., Chabanet, P. and McClanahan, T. R. (2008), Detection heterogeneity in underwater visual-census data. Journal of Fish Biology, 73: 1748–1763. doi: 10.1111/j.1095-8649.2008.02067.x
¶Present address: Department of Mathematics and Statistics, P. O. Box 56, University of Otago, Dunedin, New Zealand.
- Issue published online: 11 NOV 2008
- Article first published online: 11 NOV 2008
- (Received 6 February 2008, Accepted 12 August 2008)
- marine protected area;
- reef fishes
This study shows how capture–mark–recapture (CMR) models can provide robust estimates of detection heterogeneity (sources of bias) in underwater visual-census data. Detection biases among observers and fish family groups were consistent between fished and unfished reef sites in Kenya, even when the overall level of detection declined between locations. Species characteristics were the greatest source of detection heterogeneity and large, highly mobile species were found to have lower probabilities of detection than smaller, site-attached species. Fish family and functional-group detectability were also found to be lower at fished locations, probably due to differences in local abundance. Because robust CMR models deal explicitly with sampling where not all species are detected, their use is encouraged for studies addressing reef-fish community dynamics.