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Identifying coral reef resilience potential in Tutuila, American Samoa based on NOAA coral reef monitoring data from 2010 to 2016 (NCEI Accession 0169632)

Published by NOAA National Centers for Environmental Information | National Oceanic and Atmospheric Administration, Department of Commerce | Catalog Last Checked: May 29, 2026 at 07:20 PM | Dataset Last Updated: December 18, 2020 at 12:00 AM
Declines in the health of coral reef ecosystems lead scientists to search for factors that support reef resilience: the ability of reefs to resist environmental stress and recover when they have been impacted, and to maintain key ecosystem functions throughout. Scientists have identified eleven measurable factors that affect the resilience of coral reefs. Reef resilience factors include characteristics of the coral assemblage, populations of fish that live on the reef, land-based influences, and sea surface temperature variability. NOAA Pacific Islands Fisheries Science Center (PIFSC) Ecosystem Sciences Division (ESD) used these factors to quantitatively assess the resilience potential of reefs around Tutuila and Aunu‘u Islands in American Samoa. Locations of monitoring surveys conducted by ESD from 2010 to 2016 were used to designate study zones. The monitoring surveys provided data to evaluate biological/ecological resilience factors, and external data sources were used to inform physical and environmental factors not directly measured by ESD. Data for each metric was compiled, normalized, and averaged to produce a composite resilience score for each of zone. The primary resilience analysis includes all 11 metrics for 10 study zones around Tutuila and Aunu'u, excluding Taema Bank. The secondary resilience analysis includes the 8 metrics available for 11 study zones around Tutuila and Aunu'u, including Taema Bank. The information provided with this analysis includes the individual datasets for the 11 metrics used in the analysis (data tables), the survey sites and study zones (data tables), and the resilience scores resulting from the analysis (data tables and maps).

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