Detection heterogeneity in underwater visual-census data

M. A. MacNeil, N. A.J. Graham, M. J. Conroy, C. J. Fonnesbeck, N. V.C. Polunin, S. P. Rushton, P. Chabanet, T. R. McClanahan

Research output: Contribution to journalArticlepeer-review

50 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)1748-1763
Number of pages16
JournalJournal of Fish Biology
Volume73
Issue number7
DOIs
Publication statusPublished - Nov 2008
Externally publishedYes

ASJC Scopus Subject Areas

  • Ecology, Evolution, Behavior and Systematics
  • Aquatic Science

Fingerprint

Dive into the research topics of 'Detection heterogeneity in underwater visual-census data'. Together they form a unique fingerprint.

Cite this