Skip to main content

Detection heterogeneity in underwater visual-census data

Buy Article:

$43.00 plus tax (Refund Policy)

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.
No References
No Citations
No Supplementary Data
No Data/Media
No Metrics

Keywords: Bayesian; marine protected area; markÔÇôrecapture; reef fishes

Document Type: Regular Paper

Affiliations: 1: Cooperative Fish and Wildlife Research Unit, Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA 30606, U.S.A 2: School of Marine Science and Technology, University of Newcastle, Newcastle upon Tyne, NE1 7RU, U.K 3: School of Biology and Psychology, University of Newcastle, Newcastle upon Tyne, NE1 7RU, U.K 4: Institut de Recherche pour le Developpement, Noumea, New Caledonia 5: Marine Programs, Wildlife Conservation Society, 2300 Southern Blvd., Bronx, NY 10460, U.S.A.

Publication date: 2008-11-01

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more