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Detection heterogeneity in underwater visual‐census data
Author(s) -
MacNeil M. A.,
Graham N. A. J.,
Conroy M. J.,
Fonnesbeck C. J.,
Polunin N. V. C.,
Rushton S. P.,
Chabanet P.,
McClanahan T. R.
Publication year - 2008
Publication title -
journal of fish biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 115
eISSN - 1095-8649
pISSN - 0022-1112
DOI - 10.1111/j.1095-8649.2008.02067.x
Subject(s) - biology , coral reef fish , mark and recapture , reef , fish <actinopterygii> , sampling (signal processing) , abundance (ecology) , census , fishery , underwater , sampling bias , ecology , statistics , sample size determination , geography , computer science , demography , population , mathematics , archaeology , filter (signal processing) , sociology , computer vision
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.