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 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). The long-term mean was calculated by taking the average of all 8-day data 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-chla-8d-v5-0.graph

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.

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 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). The standard deviation was calculated over all 8-day chlorophyll-a data 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-chla-8d-v5-0.graph

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 maximum monthly climatological mean of chlorophyll-a (mg/m3) 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-chla-8d-v5-0.graph

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 annual average of the maximum anomaly 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 chlorophyll-a average annual maximum anomaly was calculated by taking the average of the chlorophyll-a values from the 8-day time series in exceedance of the maximum monthly climatological chlorophyll-a 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. Monthly Climatologies were calculated from monthly time series using only full years over the Ocean Tipping Points (OTP) project time frame of interest (2002-2013). Time series of anomalies were calculated by quantifying the number and magnitude of events from the 8-day time series that exceed the maximum climatological monthly mean. 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.

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.

The variation in the phytoplankton biomass over a decadal time scale, and its relationship with the Antarctic Circumpolar Wave (ACW) and climate change, has been poorly interpreted because of the limited satellite chlorophylla (chl a) data compared with the physical parameters from satellite. We analysed a long-term chl a dataset along the Japanese Antarctic Research Expedition (JARE) cruise tracks since 1965 to investigate inter-annual variation of phytoplankton biomass. In the Southern Ocean, increasing trends of chl a and the spreading of higher chl a area to the north with 3-7 year cycles were found. Although relationships between the decadal change in chl a and climate change such as variation of sea ice extent and the El Nino are still obscure, large variation of primary production in proportion to the chl a is implied. The chl a concentration of sea surface water has been measured routinely on board the icebreakers Fuji and Shirase during almost every cruise of the JARE. The download file contains chlorophyll a data collected from ship tracks on JARE voyages between 1965 and 2002. The field in this dataset are: Date (local time) Year Latitude Longitude Corrected Chlorophyll a See the attached paper for more details. The publications on the data collected during the 1965-1976 and 1988-1993 cruises are listed in Fukuchi [1980] and Suzuki and Fukuchi [1997], respectively. For data on the 1977-1985 and 1994-1997 cruises, see [Kanda and Fukuchi, 1979; Fukuchi and Tamura, 1982; Tanimura, 1981; Watanabe and Nakajima, 1983; Ino and Fukuchi, 1984; Sasaki, 1984; Hamada et al., 1985; Fukuda et al., 1986; Hattori and Fukuchi, 1988; Midorikawa et al., 2000]. Data post 1998-2002 cruises is in Hirawake and Fukuchi [2004]. Data from the 1986-1987 will be published in the JARE data report of digital media, including all cruise data. Auxiliary Material for paper 2004GL021394 Long-term variation of surface phytoplankton chlorophyll a in the Southern Ocean during 1965-2002. Toru Hirawake, Tsuneo Odate and Mitsuo Fukuchi (National Institute of Polar Research, Tokyo) Geophys. Res. Lett., Vol (Num), doi:10.1029/2004GL021394 All of the chl a data have been reported in the publications of the National Institute of Polar Research (NIPR).

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 annual average of the maximum anomaly of chlorophyll-a (mg/m3) 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). The chlorophyll-a average annual maximum anomaly was calculated by taking the average of the chlorophyll-a values from the 8-day time series in exceedance of the maximum monthly climatological chlorophyll-a 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. Time series of anomalies were calculated by quantifying the number and magnitude of events from the 8-day time series that exceed the maximum climatological monthly mean. 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-chla-8d-v5-0.graph

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 annual average number of anomalies of chlorophyll-a (mg/m3) from 2002-2013, with values presented as fraction of a year. 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 chlorophyll-a 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 chlorophyll-a value 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. Monthly climatologies were calculated from monthly time series using only full years over the Ocean Tipping Points (OTP) project time frame of interest (2002-2013). Time series of anomalies were calculated by quantifying the number and magnitude of events from the 8-day time series that exceed the maximum climatological monthly mean. 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.

Coastal habitats are utilized and altered for a suite of human uses. Habitat modification is here defined as the alteration or removal of geomorphic structure as a result of human use. This includes several habitat-modifying features like seawalls, piers, breakwaters, dredged areas, artificial land (i.e., filled wetlands), and offshore structures. This data layer represents the presence of habitat modification in shallow waters of the Main Hawaiian Islands. The Ocean Tipping Points (OTP) project mapped the presence of habitat-modifying features by combining several existing datasets derived primarily from satellite and aerial imagery, including the following datasets: benthic habitat maps (NOAA Center for Coastal Monitoring and Assessment (CCMA), 2007); NOAA Environmental Sensitivity Index (ESI) line data (NOAA Office of Response and Restoration (OR&R), 2001); maintained channels (NOAA, US Army Corps of Engineers (USACE), MarineCadastre.gov); and locations of offshore aquaculture. The layer represents the presence or absence of habitat modification, with a cell size of 500 m. Relevant man-made features were extracted from each individual dataset and saved (features classified as artificial and dredged areas in NOAA benthic habitat maps; coastal segments designated as man-made structures and riprap in NOAA ESI line data; all features from the maintained channels and aquaculture datasets). The resulting polygon datasets were merged together. A field was added to all vector layers with a value of 1 for each feature to represent the presence of habitat modification. Vector data were then converted to 500-m rasters and combined into a mosaic.