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Biological Status Assessment of Coral Reefs in Southern Puerto Rico: Supporting Coral Reef Protection Under the U.S. Clean Water Act
Authors:William S. Fisher  Deborah N. Vivian  Jed Campbell  Charles Lobue  Rebecca L. Hemmer  Sherry Wilkinson
Affiliation:1. U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Gulf Ecology Division, Gulf Breeze USA;2. Fisher.William@epa.gov;4. U.S. Environmental Protection Agency, Region 2, New York USA
Abstract:Abstract

States and other jurisdictions may protect coral reefs using biological water quality standards outlined by the United States Clean Water Act (CWA). Such protection will require long-term, regional monitoring of the resource using biological indicators and a probability-based sampling design. A 60-station survey targeting nearshore linear coral reef was conducted across southern Puerto Rico in December 2011 to document the status of reef inhabitants using a probabilistic, regional sampling design. The quantity, type and condition of stony corals, fish, gorgonians, and sponges were documented from each station, providing a robust representation of linear reef status and composition across the region. Fish represented 106 unique taxa and stony corals 32 unique taxa. Benthic organisms (stony corals, sponges, and gorgonians) averaged nearly 12 colonies per square meter, more than half of which were gorgonians. Assessment results can be used as a baseline to compare with future regional surveys to quantify change in reef condition over time (trend). Both temporal and spatial changes can be expected after large-scale disturbances like hurricanes Maria and Irma in 2017. The indicators and probabilistic sampling design support the long-term regional monitoring envisioned by the Environmental Protection Agency to implement CWA protections in Puerto Rico and elsewhere.
Keywords:biocriteria  biological criteria  Clean Water Act  coral reef biological status assessments  probability-based regional sampling
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