Spectrally resolved water-leaving radiances (ocean color) and inferred chlorophyll concentration are key to studying phytoplankton dynamics at seasonal and inter-annual scales, for a better understanding of the role of phytoplankton in marine biogeochemistry; the global carbon cycle; and the response of marine ecosystems to climate variability, change, and feedback processes. Ocean color data also have a critical role in operational observation systems monitoring coastal eutrophication, harmful algal blooms, and sediment plumes. The contiguous ocean color record reached 21 years in 2018. However, it is comprised of a number of one-off missions such that creating a consistent time series of ocean color data requires merging of the individual sensors without introducing artifacts. The diffuse attenuation coefficient at 490 nm (Kd490) indicates the turbidity of the water column: i.e., how well visible light in the blue to green region of the spectrum penetrates the water column. The value of Kd490 represents the rate at which light at 490 nm is attenuated with depth. For example, a Kd490 of 0.1 per meter means that light intensity is reduced by one natural log within 10 meters of water. Thus, for a Kd490 of 0.1, one attenuation length is 10 meters. Higher Kd490 values mean shallower attenuation depths and thus higher turbidity, or lower clarity, of ocean water. This layer represents the maximum monthly climatological mean of Kd490 (m-1) from 1998-2018. Data products generated by the Ocean Colour component of the European Space Agency (ESA) Climate Change Initiative (CCI) project. These files are 8-day 4-km composites of merged sensor products: Global Area Coverage (GAC), Local Area Coverage (LAC), MEdium Resolution Imaging Spectrometer (MERIS), Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua, Ocean and Land Colour Instrument (OLCI), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), and Visible Infrared Imaging Radiometer Suite (VIIRS). A quality control mask was applied to remove spurious data associated with shallow water, following Gove et al., 2013. Monthly climatologies were calculated from monthly time series averaging for all same-months (e.g., January). Nearshore map pixels with no data were filled with values from the nearest neighboring valid offshore pixel by using a grid of points and the Near Analysis tool in ArcGIS then converting points to raster. Data source: https://oceanwatch.pifsc.noaa.gov/erddap/griddap/esa-cci-kd-8d-v5-0.graph

Spectrally resolved water-leaving radiances (ocean color) and inferred chlorophyll concentration are key to studying phytoplankton dynamics at seasonal and inter-annual scales, for a better understanding of the role of phytoplankton in marine biogeochemistry; the global carbon cycle; and the response of marine ecosystems to climate variability, change, and feedback processes. Ocean color data also have a critical role in operational observation systems monitoring coastal eutrophication, harmful algal blooms, and sediment plumes. The contiguous ocean color record reached 21 years in 2018. However, it is comprised of a number of one-off missions such that creating a consistent time series of ocean color data requires merging of the individual sensors without introducing artifacts. The diffuse attenuation coefficient at 490 nm (Kd490) indicates the turbidity of the water column: i.e., how well visible light in the blue to green region of the spectrum penetrates the water column. The value of Kd490 represents the rate at which light at 490 nm is attenuated with depth. For example, a Kd490 of 0.1 per meter means that light intensity is reduced by one natural log within 10 meters of water. Thus, for a Kd490 of 0.1, one attenuation length is 10 meters. Higher Kd490 values mean shallower attenuation depths and thus higher turbidity, or lower clarity, of ocean water. This layer represents the annual average number of anomalies of Kd490 (m-1) from 1998-2018, with values presented as fraction of a year. Data products generated by the Ocean Colour component of the European Space Agency (ESA) Climate Change Initiative (CCI) project. These files are 8-day 4-km composites of merged sensor products: Global Area Coverage (GAC), Local Area Coverage (LAC), MEdium Resolution Imaging Spectrometer (MERIS), Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua, Ocean and Land Colour Instrument (OLCI), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), and Visible Infrared Imaging Radiometer Suite (VIIRS). The Kd490 average annual frequency of anomalies was calculated by taking the average number of times that the 8-day time series exceeded the maximum monthly climatological Kd490 value from 1998-2018 for each pixel. A quality control mask was applied to remove spurious data associated with shallow water, following Gove et al., 2013. Nearshore map pixels with no data were filled with values from the nearest neighboring valid offshore pixel by using a grid of points and the Near Analysis tool in ArcGIS then converting points to raster. Data source: https://oceanwatch.pifsc.noaa.gov/erddap/griddap/esa-cci-kd-8d-v5-0.graph

Sea surface temperature (SST) plays an important role in a number of ecological processes and can vary over a wide range of time scales, from daily to decadal changes. SST influences primary production, species migration patterns, and coral health. If temperatures are anomalously warm for extended periods, drastic changes in the surrounding ecosystem can result, including harmful effects such as coral bleaching. This layer represents the mean SST (degrees Celsius) of the weekly time series from 1985-2018. These SST dataset are derived from CoralTemp 5-km gap-free analyzed blended sea surface temperature over the global ocean. CoralTemp is derived from three different but related 5-km daily gap-free SST data sets and provides an internally consistent SST product that stretches from 1985 to present. 1) Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) Sea Surface Temperature Reanalysis (1985-2002). 2) Geo-Polar Blended Night-Only Sea Surface Temperature Reanalysis (2002-2016). 3) Geo-Polar Blended Night-Only Sea Surface Temperature Near Real-Time (2017 to present). The 8-day composites are generated from daily Coral Reef Watch (CRW) files by OceanWatch Central Pacific. The SST long-term mean was calculated by taking the average of all weekly data from 1985-2018 for each pixel. Data source: https://oceanwatch.pifsc.noaa.gov/erddap/griddap/CRW_sst_v1_0_8day.graph

Sea surface temperature (SST) plays an important role in a number of ecological processes and can vary over a wide range of time scales, from daily to decadal changes. SST influences primary production, species migration patterns, and coral health. If temperatures are anomalously warm for extended periods of time, drastic changes in the surrounding ecosystem can result, including harmful effects such as coral bleaching. This layer represents the mean SST (degrees Celsius) of the weekly time series from 2000-2013. Three SST datasets were combined to provide continuous coverage from 1985-2013. The concatenation applies bias adjustment derived from linear regression to the overlap periods of datasets, with the final representation matching the 0.05-degree (~5-km) near real-time SST product. First, a weekly composite, gap-filled SST dataset from the NOAA Pathfinder v5.2 SST 1/24-degree (~4-km), daily dataset (a NOAA Climate Data Record) for each location was produced following Heron et al. (2010) for January 1985 to December 2012. Next, weekly composite SST data from the NOAA/NESDIS/STAR Blended SST 0.1-degree (~11-km), daily dataset was produced for February 2009 to October 2013. Finally, a weekly composite SST dataset from the NOAA/NESDIS/STAR Blended SST 0.05-degree (~5-km), daily dataset was produced for March 2012 to December 2013. The SST long-term mean was calculated by taking the average of all weekly data from 2000-2013 for each pixel.

Chlorophyll-a is a widely used proxy for phytoplankton biomass and an indicator for changes in phytoplankton production. As an essential source of energy in the marine environment, the extent and availability of phytoplankton biomass can be highly influential for fisheries production and dictate trophic structure in marine ecosystems. Changes in phytoplankton biomass are predominantly effected by changes in nutrient availability, through either natural (e.g., turbulent ocean mixing) or anthropogenic (e.g., agricultural runoff) processes. This layer represents the standard deviation of the 8-day time series of chlorophyll-a (mg/m3) from 2002-2013. Monthly and 8-day 4-km (0.0417-degree) spatial resolution data were obtained from the MODIS (Moderate-resolution Imaging Spectroradiometer) Aqua satellite instrument from the NASA OceanColor website (http://oceancolor.gsfc.nasa.gov). The standard deviation was calculated over all 8-day chlorophyll-a data from 2002-2013 for each pixel. A quality control mask was applied to remove spurious data associated with shallow water, following Gove et al., 2013. Nearshore map pixels with no data were filled with values from the nearest neighboring valid offshore pixel by using a grid of points and the Near Analysis tool in ArcGIS then converting points to raster.

To support a long-term NOAA Coral Reef Conservation Program (CRCP) for sustainable management and conservation of coral reef ecosystems, from 2010-02-17 to 2010-03-23, reef fish assessment surveys were conducted, as a part of Rapid Ecological Assessments (REA), during the Pacific Reef Assessment and Monitoring Program (RAMP) Cruise HA1001 in the American Samoa region by the Coral Reef Ecosystem Division (CRED) at the NOAA Pacific Islands Fisheries Science Center (PIFSC). During the cruise, 123 REA sites were surveyed at Tutuila in the American Samoa region. At each REA site, fish biologists entered the water and conducted a fine-scale (~700 m^2) and high degree of taxonomic resolution REA survey to assess and monitor species diversity, size distribution, and abundance of fish in shallow-water hard-bottom (less than 30 m) habitats. Reef fish assessment surveys were focused on cataloging the diversity (species richness), abundance (numeric density) and biomass (fish mass per unit area) of diurnally active reef fish assemblages. The stationary point count (SPC) method was used to quantify reef fish species. Two divers lay out a 30 m transect line, and position themselves at the 7.5 and 22.5 meter marks. The SPC biologist then records estimated size and abundance of all fish within a visually estimated 15-m diameter cylinder centered on the stationary diver (7.5-m radius, total area ~ 177m^2 per cylinder). The diver first spends 5 minutes identifying all fish species in the cylindrical area, then proceeds to count and estimate size (total length) for each in a series of "instantaneous" point counts or sweeps of the cylinder. Fish were identified at the species level, wherever possible. All reef-associated fish, including those in the water column, were surveyed. The survey time for each stationary point count survey was approximately 20 min and generally four stationary point count surveys (two per diver) were conducted at each fish REA site. After completing REA surveys, divers noted the presence, at the survey site, of any unusual fish species not counted during SPC counts, in order to facilitate species lists per location.

Chlorophyll-a is a widely used proxy for phytoplankton biomass and an indicator for changes in phytoplankton production. As an essential source of energy in the marine environment, the extent and availability of phytoplankton biomass can be highly influential for fisheries production and dictate trophic structure in marine ecosystems. Changes in phytoplankton biomass are predominantly effected by changes in nutrient availability, through either natural (e.g., turbulent ocean mixing) or anthropogenic (e.g., agricultural runoff) processes. This layer represents the mean of the 8-day time series of chlorophyll-a (mg/m3) from 2002-2013. Monthly and 8-day 4-km (0.0417-degree) spatial resolution data were obtained from the MODIS (Moderate-resolution Imaging Spectroradiometer) Aqua satellite instrument from the NASA OceanColor website (http://oceancolor.gsfc.nasa.gov). The long-term mean was calculated by taking the average of all 8-day data from 2002-2013 for each pixel. A quality control mask was applied to remove spurious data associated with shallow water, following Gove et al., 2013. Nearshore map pixels with no data were filled with values from the nearest neighboring valid offshore pixel by using a grid of points and the Near Analysis tool in ArcGIS then converting points to raster.

Gridded (5 m cell size) bathymetry of the shelf and slope environments of Tutuila Island, American Samoa, South Pacific. Almost complete bottom coverage was achieved in depths between 2 and 3409 meters (5 m grid includes data to 250 m). The bathymetry dataset includes Simrad EM300, EM3002D, and Reson 8101ER multibeam data collected during Jan. to March of 2004 and during Feb. to March of 2006.

To support a long-term NOAA Coral Reef Conservation Program (CRCP) for sustainable management and conservation of coral reef ecosystems, from 18 February - 19 March 2008, reef fish assessment surveys were conducted, as a part of Rapid Ecological Assessments (REA), during the Pacific Reef Assessment and Monitoring Program (RAMP) Cruise HI0802 in the American Samoa at biennial intervals by the Coral Reef Ecosystem Division (CRED) at the NOAA Pacific Islands Fisheries Science Center (PIFSC). During the cruise, 44 REA sites were surveyed at Tutuila Island in the American Samoa. At the specific REA sites, fish biologists along with coral biologists, algal biologists and marine invertebrate zoologist entered the water and conducted a fine-scale (~300 m2) and high degree of taxonomic resolution REA survey to assess and monitor species composition, abundance, percent cover, size distribution, diversity, and general health of fish, corals, macro-invertebrates, and algae in shallow-water (< 35 m) habitats. Reef fish assessment surveys were focused on cataloging the diversity (species richness), abundance (numeric density [# fish 100 m-2] and biomass density [kg 100 m-2]) of diurnally active reef fish assemblages. Three complementary noninvasive underwater survey methods were used, including belt-transect, stationary point count, and roving-diver surveys. For all methods, fish were identified at the species level, when possible, and assigned to a size bin ranging from 1 to 200 cm based on a visual estimate of total fish length. Belt-transect (BLT) surveys were used to quantify the entire diurnal fish community (all size classes). In belt-transect surveys, two fish biologists swam side-by-side along three consecutively-placed, 25m transect lines. The BLT team swam each transect two times. During the initial swim-out, each fish diver recorded all fish larger than 20 cm observed within a 4-m wide belt perpendicular to their respective side of the transect (200 m2 area per line, 100 m2 per diver). On the return swim, each fish diver recorded all fish less than 20 cm observed within a 2-m wide belt (100 m2 area per line, 50 m2 per diver). The survey of large fish took approximately 5 min to complete while the survey of smaller fish took about 10 min to complete. All reef-associated fish, including those in the water column (including planktivores), were counted. Any coastal pelagic species (e.g., clupeids [sardines], belonids [beakfish], antherinids [silversides]) seen near the surface were not recorded. The stationary point count (SPC) method were used to quantify larger, more mobile reef fish species that can be missed on belt-transect surveys. In stationary point count survey, a fish biologist swam approximately 15 m away from a transect line concurrently being surveyed by the other two BLT fish biologists. The SPC biologist then recorded all fish greater than 25 cm in length that passed within a visually estimated 20-m diameter cylinder centered on the diver's fixed position (10-m radius, total area = 314 m2). The survey time for each stationary point count survey was 5 min and a total of four stationary point count surveys were conducted at each REA site. Roving-diver surveys were followed belt-transect and stationary point count surveys. As diver bottom time permitted, the fish assessment team conducted random swim surveys throughout the REA site area, recording, to the species level or the lowest recognizable taxon, the presence of reef fish not encountered during previous methods.

Environmental Sensitivity Index (ESI) maps are an integral component in oil-spill contingency planning and assessment. They serve as a source of information in the event of an oil spill incident. ESI maps contain three types of information: shoreline habitats (classified according to their sensitivity to oiling), sensitive biological resources, and human-use resources. Most often, this information is plotted on 7.5 minute USGS quadrangles, although in the Alaska ESI maps, USGS topographic maps at scales of 1:63,360 and 1:250,000 are used, and in other ESI maps, NOAA charts have been used as the base map. Collections of these maps, grouped by state or a logical geographic area, are published as ESI atlases. Digital data have been published for most of the U.S. shoreline, including Alaska, Hawaii, and Puerto Rico.