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Article
Probability Sampling of Stony Coral Populations in the Florida Keys
Environmental Monitoring and Assessment
  • Steven G. Smith, University of Miami
  • Dione W. Swanson, University of Miami
  • Mark Chiappone, University of North Carolina - Wilmington
  • Steven Miller, University of North Carolina - Wilmington
  • Jerald Ault, University of Miami
Document Type
Article
Publication Date
12-1-2011
Keywords
  • Coral reefs,
  • Stratified random survey design,
  • Population estimation
Abstract

Principles of probability survey design were applied to guide large-scale sampling of populations of stony corals and associated benthic taxa in the Florida Keys coral reef ecosystem. The survey employed a two-stage stratified random sampling design that partitioned the 251-km2 domain by reef habitat types, geographic regions, and management zones. Estimates of the coefficient of variation (ratio of standard error to the mean) for stony coral population density and abundance ranged from 7% to 12% for four of six principal species. These levels of survey precision are among the highest reported for comparable surveys of marine species. Relatively precise estimates were also obtained for octocoral density, sponge frequency of occurrence, and benthic cover of algae and invertebrates. Probabilistic survey design techniques provided a robust framework for estimating population-level metrics and optimizing sampling efficiency.

Comments

©Springer Science+Business Media B.V. 2011

Additional Comments
Florida Keys National Marine Sanctuary grant #: NA17RJ1226; NOAA Fisheries Coral Reef Conservation Program grant #: NA17RJ1226-SB19; Florida Sea Grant College Program project #: R/C-E-50; National Park Service Cooperative Ecosystems Study Unit contract #: H500000B494-J5120020275; NOAA Biogeography Program grant #: NA17RJ1226-SB99
DOI
10.1007/s10661-011-1912-2
Citation Information
Steven G. Smith, Dione W. Swanson, Mark Chiappone, Steven Miller, et al.. "Probability Sampling of Stony Coral Populations in the Florida Keys" Environmental Monitoring and Assessment Vol. 183 Iss. 1-4 (2011) p. 121 - 138 ISSN: 0167-6369
Available at: http://works.bepress.com/steven-miller/26/