Detection heterogeneity in underwater visual‐census data |
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| Authors: | 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 |
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| Institution: | *
School of Marine Science and Technology, University of Newcastle, Newcastle upon Tyne, NE1 7RU, U.K.,
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Cooperative Fish and Wildlife Research Unit, Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA 30606, U.S.A.,
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Fish and Wildlife Research Institute, Florida Fish and Wildlife Conservation Commission, 100 Eighth Avenue SE, St Petersburg, FL 33701, U.S.A.,
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School of Biology and Psychology, University of Newcastle, Newcastle upon Tyne, NE1 7RU, U.K.,
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Institut de Recherche pour le Developpement, Noumea, New Caledonia and
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Marine Programs, Wildlife Conservation Society, 2300 Southern Blvd., Bronx, NY 10460, U.S.A. |
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| 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. |
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| Keywords: | Bayesian marine protected area mark– recapture reef fishes |
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