Benthic Surveys in Vatia, American Samoa: comprehensive assessment of coral demography (adult and juvenile corals) from belt transect surveys from 2020-01-23 to 2020-01-29 (NCEI Accession 0240417)

Jurisdictional managers have expressed concerns that nutrients from the village of Vatia, Tutuila, American Samoa, are having an adverse effect on the adjacent coral reef ecosystem. Excess nutrient loads promote increases in algal growth that can have deleterious effects on corals, such as benthic algae outcompeting and overgrowing corals. Nitrogen and phosphorus can also directly impact corals by lowering fertilization success, and reducing both photosynthesis and calcification rates. Land-based contributions of nutrients come from a variety of sources; in Vatia the most likely sources are poor wastewater management from piggeries and septic systems.

NOAA scientists conducted benthic surveys to establish a baseline against which to compare changes in the algal and coral assemblages in response to land-based sources of pollution, including nutrient fluxes.

The data described here result from benthic coral demographic surveys within belt transects of specified length and width for two life stages (juveniles and adults) in Vatia Bay American Samoa in 2020. The data provide information on adult coral colony counts, morphology, size, partial mortality (old and recent dead), presence and causation of disease and other compromised health conditions, including bleaching. Juvenile colony surveys include morphology and size. Taxonomic identification of adult colonies is to the species level and genus level for juveniles.

In 2020, the survey implemented was a one-stage stratified random sampling (StRS) design to assess the Vatia coral reef community. The survey domain encompassed the majority of the mapped area of reef and hard bottom habitats in the 0–30 m depth range. The stratification scheme included cardinal position (i.e., north and south) and depth (i.e., shallow: >0–6 m and mid-depth: >6–18 m). Sampling effort allocation was determined based on strata area and sites randomly located within strata. The StRS design effectively reduces estimate variance through stratification using environmental covariates and by sampling more sites rather than more transects per site. Therefore, site-to-site comparisons should proceed with caution.