At 44,000 miles long, Alaska’s shoreline is more than double the length of the East and West coasts of the United States combined. It provides diverse habitats for marine life, and supports important ecosystem services for Alaska’s communities and economy. The Alaska region is made up of 6 distinct ecosystems: the Gulf of Alaska (GOA), Aleutian Islands (AI), Eastern Bering Sea (EBS), and Chukchi Sea and Beaufort Sea (referred to here as the Alaskan Arctic). These ecosystems support extensive high-value commercial fisheries, indigenous community’s subsistence uses, oil and gas development, and other economic and cultural uses. Each of these high latitude ecosystems is distinct in structure, function and human activity. Indicators are presented for these marine ecosystems as a regional composition, unless otherwise noted.
Over half of the US commercial seafood harvest comes from Alaska, and the Aleutian Islands are a major transit for the Great Circle Route - linking commerce from the U.S. west coast to southern Asia. No other marine system in the U.S. has such extreme weather and climate, vast geographic distances (larger than all other U.S. marine systems combined), and such an extensive coastline.
Understanding the Time series plots
Time series plots show the changes in each indicator as a function of time, over the period 1980-present. Each plot also shows horizontal lines that indicate the median (middle) value of that indicator, as well as the 10th and 90th percentiles, each calculated for the entire period of measurement. Time series plots were only developed for datasets with at least 10 years of data. Two symbols located to the right of each plot describe how recent values of an indicator compare against the overall series. A black circle indicates whether the indicator values over the last five years are on average above the series 90th percentile (plus sign), below the 10th percentile (minus sign), or between those two values (solid circle). Beneath that an arrow reflects the trend of the indicator over the last five years; an increase or decrease greater than one standard deviation is reflected in upward or downward arrows respectively, while a change of less than one standard deviation is recorded by a left-right arrow.
Pacific Decadal Oscillation (PDO)
During the last five years, the PDO indicator has trended downward, shifting from positive phase to negative phase in 2019.
Values correspond to Index scores
Description of time series:
Positive PDO values typically mean cool surface water conditions in the interior of the North Pacific Ocean and warm surface waters along the North American Pacific Coast while negative PDO conditions typically mean warm surface water conditions in the interior to the North Pacific Ocean and cool surface waters along the North American Pacific Coast. During the last five years, the PDO indicator shows a significant downward trend.
Description of gauge:
The unitless two-way gauge depicts whether the average of the last 5 years of data for the climate indicator is above or below the median value of the entire time series. High values in either direction mean extreme variation from the median value of the entire time series.
Description of Pacific Decadal Oscillation (PDO):
The Pacific Decadal Oscillation (PDO) is a long-term pattern of Pacific climate variability. The extreme phases of this climatic condition are classified as warm or cool, based on deviations from average ocean temperature in the northeast and central North Pacific Ocean. When the PDO has a positive value, sea surface temperatures are below average (cool) in the interior North Pacific and warm along the Pacific Coast. When the PDO has a negative value, the climate patterns are reversed, with above average sea surface temperatures in the interior and sea surface temperatures below average along the North American coast. The PDO waxes and wanes; warm and cold phases may persist for decades. Major changes in northeast Pacific marine ecosystems have been correlated with phase changes in the PDO. Warm phases have seen enhanced coastal ocean biological productivity in Alaska and inhibited productivity off the west coast of the United States, while cold PDO phases have seen the opposite, north-south pattern of marine ecosystem productivity. We present data from the Pacific Islands, Alaska, and California Current regions.
Data Background:
Climate indicator data was accessed from the NOAA NCEI (https://www.ncdc.noaa.gov/teleconnections/pdo/data.csv). The data plotted are unitless and based on Sea Surface Temperature anomalies averaged across a given region.
East Pacific - North Pacific Teleconnection Pattern Index (EP-NP)
Values correspond to Index scores
Description of time series:
Positive EP-NP values mean above-average surface temperatures over the eastern North Pacific, and below-average temperatures over the central North Pacific and eastern North America and the opposite for negative EP-NP values. During the last five years, the EP-NP indicator shows no significant trend.
Description of gauge:
The unitless two-way gauge depicts whether the average of the last 5 years of data for the climate indicator is above or below the median value of the entire time series. High values in either direction mean extreme variation from the median value of the entire time series.
Description of East Pacific/ North Pacific Teleconnection Pattern Index:
The East Pacific/ North Pacific Teleconnection Pattern Index is a measure of climate variability. Positive EP-NP values mean above-average surface temperatures over the eastern North Pacific, and below-average temperatures over the central North Pacific and eastern North America and the opposite for negative EP-NP values.
This climate condition impacts people and ecosystems across the globe and each of the indicators presented here. Interactions between the ocean and atmosphere alter weather around the world and can result in severe storms or mild weather, drought, or flooding. Beyond “just” influencing the weather and ocean conditions, these changes can produce secondary results that influence food supplies and prices, forest fires and flooding, and create additional economic and political consequences. The positive phase of the EP-NP pattern is associated with above-average surface temperatures over the eastern North Pacific, and below-average temperatures over the central North Pacific and eastern North America. The main precipitation anomalies associated with this pattern reflect above-average precipitation in the area north of Hawai'i and below-average precipitation over southwestern Canada.
Data Background:
Climate indicator data was accessed from Columbia University (https://iridl.ldeo.columbia.edu/SOURCES/.NOAA/.NCEP/.CPC/.Indices/.NHTI…). The data plotted are unitless anomalies and averaged across a given region.
El Niño-Southern Oscillation (ENSO 3.4)
Values correspond to Index scores
Description of time series:
The Oceanic Niño Index (ONI) is NOAA’s primary index for monitoring the El Niño-Southern Oscillation climate pattern. It is based on Sea Surface Temperature values in a particular part of the central equatorial Pacific, which scientists refer to as the Niño 3.4 region. Positive values of this indicator, greater than +0.5, indicate warm El Niño conditions, while negative values, less than -0.5, indicate cold La Niña conditions. The ONI indicator changed from positive to negative during the summer of 2020, and is now showing La Niña conditions, though it is once again approaching 0 as of summer 2021.
Description of gauge:
The unitless two-way gauge depicts the most recent seasonal value for the ONI showing how far it is above or below the median value of the entire time series. High values in either direction mean extreme variation from the median value of the entire time series.
Description of El Niño-Southern Oscillation (ENSO 3.4):
El Niño and La Niña are opposite phases of the El Niño-Southern Oscillation (ENSO), a cyclical condition occurring across the Equatorial Pacific Ocean with worldwide effects on weather and climate. During an El Niño, surface waters in the central and eastern equatorial Pacific become warmer than average and the trade winds - blowing from east to west - greatly weaken. During a La Niña, surface waters in the central and eastern equatorial Pacific become much cooler, and the trade winds become much stronger. El Niños and La Niñas generally last about 6 months but can extend up to 2 years. The time between events is irregular, but generally varies between 2-7 years. To monitor ENSO conditions, NOAA operates a network of buoys, which measure temperature, currents, and winds in the equatorial Pacific.
This climate pattern impacts people and ecosystems around the world. Interactions between the ocean and atmosphere alter weather globally and can result in severe storms or mild weather, drought or flooding. Beyond “just” influencing the weather and ocean conditions, these changes can produce secondary results that influence food supplies and prices, forest fires and flooding, and create additional economic and political consequences. For example, along the west coast of the U.S., warm El Niño events are known to inhibit the delivery of nutrients from subsurface waters, suppressing local fisheries. El Niño events are typically associated with fewer hurricanes in the Atlantic while La Niña events typically result in greater numbers of Atlantic hurricanes.
Data Background:
ENSO ONI data was accessed from NOAA’s Earth Systems Research Laboratory (https://psl.noaa.gov/data/timeseries/monthly/NINO4/). The data are plotted in degrees Celsius and represent Sea Surface Temperature anomalies averaged across the so-called Niño 3.4 region in the east-central tropical Pacific between 120°-170°W.
Sea Surface Temperature
Eastern Bering Sea
Sea surface temperature is defined as the average temperature of the top few millimeters of the ocean. Sea surface temperature monitoring tells us how the ocean and atmosphere interact, as well as providing fundamental data on the global climate system
Description of time series:
The time series shows the integrated sea surface temperature for Alaska’s Eastern Bering Sea region. During the last five years there has been no notable trend and values have remained within the 10th and 90th percentiles of all observed data in the time series.
Description of gauge:
The gauge value of 92 indicates that the mean sea surface temperature between 2016 and 2020 for the Eastern Bering Sea region was higher than 92% of the temperatures between 1982 and 2017.
Description of Sea Surface Temperature:
Sea surface temperature (SST) is defined as the temperature of the top few millimeters of the ocean. This temperature directly or indirectly impacts the rate of all physical, chemical, and most biological processes occurring in the ocean. SST is globally monitored by sensors on satellites, buoys, ships, ocean reference stations, autonomous underwater vehicles (AUVs) and other technologies.
SST monitoring tells us how the ocean and atmosphere interact, as well as providing fundamental data on the global climate system. This information also aids us in weather prediction, i.e. identifying the onset of El Niño and La Niña cycles - multiyear shifts in atmospheric pressure and wind speeds. These shifts affect ocean circulation, global weather patterns, and marine ecosystems. SST anomalies have been linked to shifting marine resources. With warming temperatures, we observe the poleward movements of fish and other species. Temperature extremes—both ocean heatwaves and cold spells—have been linked to coral bleaching as well as fishery and aquaculture mortality. We present the annual average SST at the large marine ecosystem scale in all regions.
Indicator and source information:
The SST data were accessed from (https://www.ncdc.noaa.gov/oisst). The data are plotted in degrees Celsius.
Data background and limitations:
To compensate for platform differences and sensor biases, satellite and ship observations are referenced to buoys. These data are NOAA 1/4° Daily Optimum Interpolation Sea Surface Temperature (version 2.1). Measurements of SST served through this portal incorporate data obtained from various platforms such as satellites, buoys, Argo floats, and ships.
Sea Surface Temperature
Gulf of Alaska
Sea surface temperature is defined as the average temperature of the top few millimeters of the ocean. Sea surface temperature monitoring tells us how the ocean and atmosphere interact, as well as providing fundamental data on the global climate system
Description of time series:
The time series shows the integrated sea surface temperature for Alaska’s Gulf of Alaska region. During the last five years there has been no notable trend while values have remained within the 10th and 90th percentiles of all observed data in the time series.
Description of gauge:
The gauge value of 90 indicates that the mean sea surface temperature between 2016 and 2020 for the Gulf of Alaska region was higher than 90% of the temperatures between 1982 and 2020.
Description of Sea Surface Temperature:
Sea surface temperature (SST) is defined as the temperature of the top few millimeters of the ocean. This temperature directly or indirectly impacts the rate of all physical, chemical, and most biological processes occurring in the ocean. SST is globally monitored by sensors on satellites, buoys, ships, ocean reference stations, autonomous underwater vehicles (AUVs) and other technologies.
SST monitoring tells us how the ocean and atmosphere interact, as well as providing fundamental data on the global climate system. This information also aids us in weather prediction, i.e. identifying the onset of El Niño and La Niña cycles - multiyear shifts in atmospheric pressure and wind speeds. These shifts affect ocean circulation, global weather patterns, and marine ecosystems. SST anomalies have been linked to shifting marine resources. With warming temperatures, we observe the poleward movements of fish and other species. Temperature extremes—both ocean heatwaves and cold spells—have been linked to coral bleaching as well as fishery and aquaculture mortality. We present the annual average SST at the large marine ecosystem scale in all regions.
Indicator and source information:
The SST data were accessed from (https://www.ncdc.noaa.gov/oisst). The data are plotted in degrees Celsius.
Data background and limitations:
To compensate for platform differences and sensor biases, satellite and ship observations are referenced to buoys. These data are NOAA 1/4° Daily Optimum Interpolation Sea Surface Temperature (version 2.1). Measurements of SST served through this portal incorporate data obtained from various platforms such as satellites, buoys, Argo floats, and ships.
Sea Ice Extent
September
Values correspond to millions of square kilometers of sea ice cover
Description of time series:
This time series shows the sea ice extent for the Alaska-Arctic region from 1979 to 2021. During the last five years, there has been no notable trend and values are within the 10th and 90th percentiles, albeit near the lower end of the time series.
Description of gauge:
The gauge value of 14 indicates that mean sea ice extent between 2017 and 2021 for sea ice in the Alaska-Arctic region was only higher than 14% of the sea ice extent measurements between 1979 and 2021
Description of Sea Ice Extent:
Unlike icebergs, glaciers, ice sheets, and ice shelves, which originate on land, sea ice forms, expands, and melts in the ocean. Sea ice influences global climate by reflecting sunlight back into space. Because this solar energy is not absorbed into the ocean, temperatures nearer the poles remain cool. When sea ice melts, the surface area reflecting sunlight decreases, allowing more solar energy to be absorbed by the ocean, causing temperatures to rise. This creates a positive feedback loop. Warmer water temperatures delay ice growth in the autumn and winter, and the ice melts faster the following spring, exposing dark ocean waters for longer periods the following summer. Sea ice also affects the movement of ocean waters. When sea ice forms, ocean salts are left behind. As the seawater gets saltier, its density increases, and it sinks. Surface water is pulled in to replace the sinking water, which in turn becomes cold and salty and sinks. This initiates deep-ocean currents driving the global ocean conveyor belt.
Sea ice is an important element of the Arctic system. It provides an important habitat for biological activity, e.g. algae grows on the bottom of sea ice, forming the basis of the Arctic food web, and it plays a critical role in the life cycle of many marine mammals - seals and polar bears. Sea ice also serves a critical role in supporting the culture—and even survival—of Indigenous communities. For example, sea ice can be a critical platform for hunting. We present the annual sea ice extent in millions of Kilometers for the Arctic region.
Indicator and source information:
Sea ice affects the movement of ocean waters. When sea ice forms, ocean salts are left behind. As the seawater gets saltier, its density increases, and it sinks. Surface water is pulled in to replace the sinking water, which in turn becomes cold and salty and sinks. This initiates deep-ocean currents driving the global ocean conveyor belt.
The time series shows the Sea Ice extent in September of each year to give a sense of the summertime (i.e., minimum annual) extent through the years of sea ice across the entire Northern Hemisphere, which includes the Arctic Ocean and the Hudson Bay.
Data background and limitations:
Sea ice data was accessed from the NOAA National Climatic Data Center for the northern hemisphere, https://www.ncdc.noaa.gov/snow-and-ice/extent/ ; With the data pulled from here: https://www.ncdc.noaa.gov/snow-and-ice/extent/sea-ice/N/0.csv. The data are plotted in units of million square km.
Sea Level
Gulf of Alaska and Eastern Bering Sea
Sea level varies due to the force of gravity, the Earth’s rotation and irregular features on the ocean floor. Other forces affecting sea levels include temperature, wind, ocean currents, tides, and other similar processes.
Description of time series:
The time series shows the relative sea level, water height as compared to nearby land level, for the Southern Alaska region. During the last five years there has been no notable trend but values were below the 10th percentile of all observed data in the time series.
Description of gauge:
The gauge value of 10 indicates that the sea level between 2016 and 2020 for the Southern Alaska region was only higher than 10% of the sea level between 1980 and 2020.
Description of Sea Level:
Sea level varies due to the force of gravity, the Earth’s rotation and irregular features on the ocean floor. Other forces affecting sea levels include temperature, wind, ocean currents, tides, and other similar processes. With 40 percent of Americans living in densely populated coastal areas, having a clear understanding of sea level trends is critical to societal and economic well being.
Measuring and predicting sea levels, tides and storm surge are important for determining coastal boundaries, ensuring safe shipping, emergency preparedness, and other aspects of the well-being of coastal communities.
Indicator and source information:
NOAA monitors sea levels using tide stations and satellite laser altimeters. Tide stations around the globe tell us what is happening at local levels, while satellite measurements provide us with the average height of the entire ocean. Taken together, data from these sources are fed into models that tell us how our ocean sea levels are changing over time. For this site, data from tide stations around the US were combined to create regionally averaged records of sea-level change since 1980. We present data for all regions.
This indicator includes tide gauges from Ketchikan, Sitka, Juneau, Skagway, Yakutat, Cordova, Valdez, Seward, Seldovia, Nikiski, Anchorage, Kodiak Island, Sand Point, Adak Island, Unalaska, and Port Moller, AK.
Data background and limitations:
Sea level data presented here are measurements of relative sea level, water height as compared to nearby land level, from NOAA tide gauges that have >20 years of hourly data served through NOAA’s Center for Operational Oceanographic Products and Services (CO-OPS) Tides and Currents website. These local measurements are regionally averaged by taking the median value of all the qualifying stations within a region. The measurements are in meters and are relative to the year 2000.
Sea Level
Chukchi and Beaufort Seas
Sea level varies due to the force of gravity, the Earth’s rotation and irregular features on the ocean floor. Other forces affecting sea levels include temperature, wind, ocean currents, tides, and other similar processes.
Description of time series:
The time series shows the relative sea level for this region. During the last five years there has been a positive trend and while values have remained within the 10th and 90th percentiles, albeit near the higher range of time series values.
Description of gauge:
The gauge value of 94 indicates that the mean sea level between 2016 and 2020 for Northern Alaska’s Arctic Sea region was higher than 94% of the sea level between 1980 and 2020.
Description of Sea Level:
Sea level varies due to the force of gravity, the Earth’s rotation and irregular features on the ocean floor. Other forces affecting sea levels include temperature, wind, ocean currents, tides, and other similar processes. With 40 percent of Americans living in densely populated coastal areas, having a clear understanding of sea level trends is critical to societal and economic well being.
Measuring and predicting sea levels, tides and storm surge are important for determining coastal boundaries, ensuring safe shipping, emergency preparedness, and other aspects of the well-being of coastal communities.
Indicator and source information:
NOAA monitors sea levels using tide stations and satellite laser altimeters. Tide stations around the globe tell us what is happening at local levels, while satellite measurements provide us with the average height of the entire ocean. Taken together, data from these sources are fed into models that tell us how our ocean sea levels are changing over time. For this site, data from tide stations around the US were combined to create regionally averaged records of sea-level change since 1980. We present data for all regions.
This indicator includes tide gauges from Nome and Prudhoe Bay.
Data background and limitations:
Sea level data presented here are measurements of relative sea level, water height as compared to nearby land level, from NOAA tide gauges that have >20 years of hourly data served through NOAA’s Center for Operational Oceanographic Products and Services (CO-OPS) Tides and Currents website. These local measurements are regionally averaged by taking the median value of all the qualifying stations within a region. The measurements are in meters and are relative to the year 2000.
Chlorophyll-a
Eastern Bering Sea
Chlorophyll a, a pigment produced by phytoplankton, can be measured to determine the amount of phytoplankton present in water bodies. From a human perspective, high values of chlorophyll a can be good (abundance of nutritious diatoms as food for fish) or bad (Harmful Algal Blooms that may cause respiratory distress for people), based on the associated phytoplankton species.
Description of time series:
This time series shows the average concentration levels of chlorophyll ɑ for Alaska’s Eastern Bering Sea region. During the last five years there has been no significant trend while values have remained within the 10th and 90th percentiles of all observed data in the time series
Description of gauge:
The gauge value of 65 indicates that between 2016 and 2020 the average concentration levels of chlorophyll a in Alaska’s Eastern Bering Sea region were slightly higher than the long term median of all chlorophyll ɑ concentration levels between 1998 and 2020.
Gauge values
0–10: Chlorophyll a was significantly lower than the long term median state.
10–25: Chlorophyll a was considerably lower than the long term median state.
25–50: Chlorophyll a was slightly lower than the long term median state.
50: Chlorophyll a was at the long term median state.
50–75: Chlorophyll a was slightly higher than the long term median state.
75–90: Chlorophyll a was considerably higher than the long term median state.
90–100: Chlorophyll a was significantly higher than the long term median state.
Description of Chlorophyll a:
Phytoplankton are microscopic plants at the base of most marine food webs and produce nearly half of the Earth’s oxygen. One way we estimate the number of phytoplankton in the ocean is by measuring the amount of chlorophyll a in the water. Chlorophyll a is a green pigment (the same pigment that makes tree leaves appear green) that the phytoplankton use to absorb sunlight. The amount (or concentration) of chlorophyll a in surface waters can be calculated by measuring the color of the water ( also referred to as “ocean color”) which can be “seen” by sensors on satellites in space almost like your eyes see the color of the ocean. Environmental and oceanographic factors continuously influence the abundance, species composition, spatial distribution, and productivity of phytoplankton. Tracking the amount of phytoplankton in the ocean conveys the status of the base of the food web, and how much food is available for other animals. Changes in the amount of phytoplankton in the ocean are part of the natural seasonal cycle (similar to seasonal changes of plants on land), but can also indicate an ecosystem’s response to a major external disturbance such as a hurricane or typhoon.
Indicator and source information:
The data for this Chlorophyll a annual indicator were provided by the NOAA Fisheries Coastal and Oceanic Plankton Ecology, Production, and Observations Database (COPEPOD). COPEPOD determined the annual Large Marine Ecosystem (LME) chlorophyll a concentrations using mapped, monthly composites of chlorophyll a concentration as calculated from radiance measurements ("ocean color") made by the SeaWiFS and MODIS-Aqua satellite sensors. These monthly composites were obtained from NASA (https://oceancolor.gsfc.nasa.gov/). Annual means for each LME for each year were calculated from the average of the LME 12 monthly means in that year. The overall “National Annual Mean mean was calculated as the average of all LME annual means. See the Data Background section for more details. Source: https://www.st.nmfs.noaa.gov/copepod/about/about-copepod.html.
To learn more about satellite-based chlorophyll a measurements within NOAA or to supplement the time series data shown here, please visit NOAA CoastWatch for more information and assistance.
Data background and limitations:
Satellite chlorophyll a, 9 km mapped, monthly composited data from SeaWiFS and MODIS-Aqua NASA products were spatially re-binned into 0.5 degree latitude by 0.5 degree longitude boxes (nominally about 50 km2 near the equator) then those ~50 km2 box values were averaged over the area of a given LME, resulting in 12 values per LME, one value for each month. The annual LME chlorophyll a amount reported here is the average of those 12 monthly values. This technique was done for each LME from North America and Hawaii. The overall “National Annual Mean mean was calculated as the average of all the LME annual means. Note that chlorophyll a is often plotted on a logarithmic scale to accentuate proportional changes. In other words, small changes in concentration when amounts are relatively low could mean a very big proportional change in the phytoplankton whereas as the same change in absolute concentration when amount are relatively large is less meaningful.
Chlorophyll a
Gulf of Alaska
Chlorophyll a, a pigment produced by phytoplankton, can be measured to determine the amount of phytoplankton present in water bodies. From a human perspective, high values of chlorophyll a can be good (abundance of nutritious diatoms as food for fish) or bad (Harmful Algal Blooms that may cause respiratory distress for people), based on the associated phytoplankton species.
Description of time series:
This time series shows the average concentration levels of chlorophyll ɑ for Alaska’s Gulf of Alaska region. During the last five years there has been a significant upward trend while values have remained within the 10th and 90th percentiles of all observed data in the time series
Description of gauge:
The gauge value of 57 indicates that between 2016 and 2020 the average concentration levels of chlorophyll a in the Gulf of Alaska region were slightly higher than the long term median of all chlorophyll ɑ concentration levels between 1998 and 2020.
Gauge values
0–10: Chlorophyll a was significantly lower than the long term median state.
10–25: Chlorophyll a was considerably lower than the long term median state.
25–50: Chlorophyll a was slightly lower than the long term median state.
50: Chlorophyll a was at the long term median state.
50–75: Chlorophyll a was slightly higher than the long term median state.
75–90: Chlorophyll a was considerably higher than the long term median state.
90–100: Chlorophyll a was significantly higher than the long term median state.
Description of Chlorophyll a:
Phytoplankton are microscopic plants at the base of most marine food webs and produce nearly half of the Earth’s oxygen. One way we estimate the number of phytoplankton in the ocean is by measuring the amount of chlorophyll a in the water. Chlorophyll a is a green pigment (the same pigment that makes tree leaves appear green) that the phytoplankton use to absorb sunlight. The amount (or concentration) of chlorophyll a in surface waters can be calculated by measuring the color of the water ( also referred to as “ocean color”) which can be “seen” by sensors on satellites in space almost like your eyes see the color of the ocean. Environmental and oceanographic factors continuously influence the abundance, species composition, spatial distribution, and productivity of phytoplankton. Tracking the amount of phytoplankton in the ocean conveys the status of the base of the food web, and how much food is available for other animals. Changes in the amount of phytoplankton in the ocean are part of the natural seasonal cycle (similar to seasonal changes of plants on land), but can also indicate an ecosystem’s response to a major external disturbance such as a hurricane or typhoon.
Indicator and source information:
The data for this Chlorophyll a annual indicator were provided by the NOAA Fisheries Coastal and Oceanic Plankton Ecology, Production, and Observations Database (COPEPOD). COPEPOD determined the annual Large Marine Ecosystem (LME) chlorophyll a concentrations using mapped, monthly composites of chlorophyll a concentration as calculated from radiance measurements ("ocean color") made by the SeaWiFS and MODIS-Aqua satellite sensors. These monthly composites were obtained from NASA (https://oceancolor.gsfc.nasa.gov/). Annual means for each LME for each year were calculated from the average of the LME 12 monthly means in that year. The overall “National Annual Mean mean was calculated as the average of all LME annual means. See the Data Background section for more details. Source: https://www.st.nmfs.noaa.gov/copepod/about/about-copepod.html.
To learn more about satellite-based chlorophyll a measurements within NOAA or to supplement the time series data shown here, please visit NOAA CoastWatch for more information and assistance.
Data background and limitations:
Satellite chlorophyll a, 9 km mapped, monthly composited data from SeaWiFS and MODIS-Aqua NASA products were spatially re-binned into 0.5 degree latitude by 0.5 degree longitude boxes (nominally about 50 km2 near the equator) then those ~50 km2 box values were averaged over the area of a given LME, resulting in 12 values per LME, one value for each month. The annual LME chlorophyll a amount reported here is the average of those 12 monthly values. This technique was done for each LME from North America and Hawaii. The overall “National Annual Mean mean was calculated as the average of all the LME annual means. Note that chlorophyll a is often plotted on a logarithmic scale to accentuate proportional changes. In other words, small changes in concentration when amounts are relatively low could mean a very big proportional change in the phytoplankton whereas as the same change in absolute concentration when amount are relatively large is less meaningful.
Zooplankton
Eastern Bering Sea
Description of time series:
Between 2015 and 2019 the average concentration of zooplankton biomass showed no significant trend.
Description of gauge:
The gauge value of 75 indicates that between 2015 and 2019 the average concentration of zooplankton biomass in Alaskan waters was much higher than the median value of all zooplankton biomass concentration levels between 1995 and 2019.
Gauge values
High values of zooplankton can be good (lots of lipid rich colder water species) or bad (lots of lipid poor warmer water species), depending on the region.
0 - 10: The five-year zooplankton biomass average is very low compared to the median value.
10 - 25: The five-year zooplankton biomass average is much lower than the median value.
25 - 50: The five-year zooplankton biomass average is lower than the median value.
50: The five-year zooplankton biomass average equals the median value.
50 - 75: The five-year zooplankton biomass average is higher than the median value.
75 - 90: The five-year zooplankton biomass average is much higher than the median value.
90 - 100: The five-year zooplankton biomass average is very high compared to the median value.
Description of Zooplankton:
Zooplankton are a diverse group of animals found in oceans, bays, and estuaries. By eating phytoplankton, and each other, zooplankton play a significant role in the transfer of materials and energy up the oceanic food web (e.g., fish, birds, marine mammals, humans.) Like phytoplankton, environmental and oceanographic factors continuously influence the abundance, composition and spatial distribution of zooplankton. These include the abundance and type of phytoplankton present in the water, as well as the water’s temperature, salinity, oxygen, and pH. Zooplankton can rapidly react to changes in their environment. For this reason monitoring the status of zooplankton is essential for detecting changes in, and evaluating the status of ocean ecosystems. We present the annual average total biovolume of zooplankton in the Alaska, California Current, Gulf of Mexico, Hawai'i-Pacific Islands and Northeast regions.
Indicator information
Zooplankton data for each region were obtained from the NOAA Fisheries Coastal & Oceanic Plankton Ecology, Production, & Observations Database, an integrated data set of quality-controlled, globally distributed plankton biomass and abundance data with common biomass units and served in a common electronic format with supporting documentation and access software. Alaska specific data comes from the Ecosystems and Fisheries-Oceanography Coordinated Investigations (EcoFOCI): https://www.ecofoci.noaa.gov/
Data Background and Caveats:
Unlike previous years, all value are now standardized to "ml/m3". For example, EcoMon data units went from "ml/100m3" to just "ml/m3", but that did not affect the shape of the trends as it is a linear multiplicative factor. CalCOFI, however, went from "ml/m2" to "ml/m3", and the trend has changed noticeably. It is now noisier and no clear trend. One converts "ml/m2" to "ml/m3" by dividing by the towing depth (m). That is a non-linear muplicative factor, so it can affect each data point and change the data shape.
HI -Note that Hawai’i is Wet Mass (g/m3) , not DV (ml/m3).
Finally, a log10 value frequency histogram of the raw data values showed that 99.9% of the DV data values were less than 15 ml/m3. To reduce the impact of large outliers (i.e., due to a large jellyfish or an algal mat caught in the net), any DV value greater than 15 was capped at a value of just 15. Again, this would only affect < 0.1% of the data. In some extreme cases, original DV values were over 100+ ... which greatly skewed the means and trends if not removed. This is actually standard practice. CalCOFI offers both a "large" and "small" DV value (with the latter having large values removed), for example, and some programs automatically remove any plankter larger than the 5 cm length from the net sample before measuring the DV.
Zooplankton data for each region were obtained from the NOAA Fisheries Coastal & Oceanic Plankton Ecology, Production, & Observations Database, an integrated data set of quality-controlled, globally distributed plankton biomass and abundance data with common biomass units and served in a common electronic format with supporting documentation and access software. Source: https://www.st.nmfs.noaa.gov/copepod/about/about-copepod.html
Zooplankton
Gulf of Alaska
Description of time series:
Between 2015 and 2019 the average concentration of zooplankton biomass showed no significant trend.
Description of gauge:
The gauge value of 52 indicates that between 2015 and 2019 the average concentration of zooplankton biomass in Alaskan waters was higher than the median value of all zooplankton biomass concentration levels between 1981 and 2019
Gauge values
High values of zooplankton can be good (lots of lipid rich colder water species) or bad (lots of lipid poor warmer water species), depending on the region.
0 - 10: The five-year zooplankton biomass average is very low compared to the median value.
10 - 25: The five-year zooplankton biomass average is much lower than the median value.
25 - 50: The five-year zooplankton biomass average is lower than the median value.
50: The five-year zooplankton biomass average equals the median value.
50 - 75: The five-year zooplankton biomass average is higher than the median value.
75 - 90: The five-year zooplankton biomass average is much higher than the median value.
90 - 100: The five-year zooplankton biomass average is very high compared to the median value.
Description of Zooplankton:
Zooplankton are a diverse group of animals found in oceans, bays, and estuaries. By eating phytoplankton, and each other, zooplankton play a significant role in the transfer of materials and energy up the oceanic food web (e.g., fish, birds, marine mammals, humans.) Like phytoplankton, environmental and oceanographic factors continuously influence the abundance, composition and spatial distribution of zooplankton. These include the abundance and type of phytoplankton present in the water, as well as the water’s temperature, salinity, oxygen, and pH. Zooplankton can rapidly react to changes in their environment. For this reason monitoring the status of zooplankton is essential for detecting changes in, and evaluating the status of ocean ecosystems. We present the annual average total biovolume of zooplankton in the Alaska, California Current, Gulf of Mexico, Hawai'i-Pacific Islands and Northeast regions.
Indicator information
Zooplankton data for each region were obtained from the NOAA Fisheries Coastal & Oceanic Plankton Ecology, Production, & Observations Database, an integrated data set of quality-controlled, globally distributed plankton biomass and abundance data with common biomass units and served in a common electronic format with supporting documentation and access software. Alaska specific data comes from the Ecosystems and Fisheries-Oceanography Coordinated Investigations (EcoFOCI): https://www.ecofoci.noaa.gov/
Data Background and Caveats:
Unlike previous years, all value are now standardized to "ml/m3". For example, EcoMon data units went from "ml/100m3" to just "ml/m3", but that did not affect the shape of the trends as it is a linear multiplicative factor. CalCOFI, however, went from "ml/m2" to "ml/m3", and the trend has changed noticeably. It is now noisier and no clear trend. One converts "ml/m2" to "ml/m3" by dividing by the towing depth (m). That is a non-linear muplicative factor, so it can affect each data point and change the data shape.
HI -Note that Hawai’i is Wet Mass (g/m3) , not DV (ml/m3).
Finally, a log10 value frequency histogram of the raw data values showed that 99.9% of the DV data values were less than 15 ml/m3. To reduce the impact of large outliers (i.e., due to a large jellyfish or an algal mat caught in the net), any DV value greater than 15 was capped at a value of just 15. Again, this would only affect < 0.1% of the data. In some extreme cases, original DV values were over 100+ ... which greatly skewed the means and trends if not removed. This is actually standard practice. CalCOFI offers both a "large" and "small" DV value (with the latter having large values removed), for example, and some programs automatically remove any plankter larger than the 5 cm length from the net sample before measuring the DV.
Zooplankton data for each region were obtained from the NOAA Fisheries Coastal & Oceanic Plankton Ecology, Production, & Observations Database, an integrated data set of quality-controlled, globally distributed plankton biomass and abundance data with common biomass units and served in a common electronic format with supporting documentation and access software. Source: https://www.st.nmfs.noaa.gov/copepod/about/about-copepod.html
Forage Fish
Values correspond to estimated total forage biomass in millions of tons
Time series: Between 2015 and 2019 the biomass of forage fish showed a significant downward trend.
Gauge: Gauge value of 58 indicates that between 2015 and 2019 the biomass of forage fish in Alaska was greater than the median value of all forage fish biomass between 1992 and 2019.
Gauge values
0 - 10: The five-year forage fish small pelagics average is very low compared to the median value.
10 - 25: The five-year forage fish small pelagics average is much lower than the median value.
25 - 50: The five-year forage fish small pelagics average is lower than the median value.
50: The five-year forage fish small pelagics average equals the median value.
50 - 75: The five-year forage fish small pelagics average is higher than the median value.
75 - 90: The five-year forage fish small pelagics average is much higher than the median value.
Description of forage fish:
Forage fish or otherwise known as small pelagics are fish and invertebrates (like squids) that inhabit - the pelagic zone - the open ocean. The number and distribution of pelagic fish vary regionally, depending on multiple physical and ecological factors i.e. the availability of light, nutrients, dissolved oxygen, temperature, salinity, predation, abundance of phytoplankton and zooplankton, etc. Small pelagics are known to exhibit “boom and bust” cycles of abundance in response to these conditions. Examples include anchovies, sardines, shad, menhaden and the fish that feed on them.
Small pelagic species are often important to fisheries and serve as forage for commercially and recreationally important fish, as well as other ecosystem species (e.g. seabirds and marine mammals). They are a critical part of marine food webs and important to monitor because so many other organisms depend on them. We present the annual total biomass of small pelagics/forage fish in the Alaska, California Current, and Northeast regions, as well as selected taxa in the Gulf of Mexico and Southeast regions.
Indicator information:
Forage fish or otherwise known as small pelagics are fish and invertebrates (like squids) that inhabit - the pelagic zone - the open ocean. Small pelagic species are often important to fisheries and serve as forage for commercially and recreationally important fish, as well as other ecosystem species (e.g. seabirds and marine mammals). The number and distribution of pelagic fish vary regionally, depending on multiple physical and ecological factors (i.e., the availability of light, nutrients, dissolved oxygen, temperature, salinity, predation, abundance of phytoplankton and zooplankton, etc.). Small pelagics are known to exhibit “boom and bust” cycles of abundance in response to these conditions. Examples include anchovies, sardines, shad, menhaden and the fish that feed on them.
This indicator from the Gulf of Alaska Integrated Ecosystem Assessment Program’s East Bering Sea (EBS) team includes adult and juvenile pollock, other forage fish such as herring, capelin, eulachon, and sandlance, pelagic rockfish, salmon, and squid.
Data background and caveats:
Units, time series, and species vary by region for this indicator, so no national score is provided. Best practices and caveats vary by region:
Information quality for this indicator ranges from a sophisticated highly quantitative stock assessment for pollock (the biomass dominant in the guild) through relatively high variance EBS shelf survey data for forage fish, to no time series data for salmon and squid.
Seabirds
Eastern Bering Sea Breeding Index
Values indicate estimated seabird abundance using a relative breeding index
Description of time series:
Between 2015 and 2019 the seabird breeding index showed no significant trend.
Description of gauge:
The gauge value of 12 indicates that between 2015 and 2019 the seabird breeding index in Alaska (Eastern Bering Sea) was much lower than the median of all breeding index values between 1996 and 2019.
Overall Scores means the following:
- 0 - 10: The five-year seabirds average is very low compared to the median value.
- 10 - 25: The five-year seabirds average is much lower than the median value.
- 25 - 50: The five-year seabirds average is lower than the median value.
- 50: The five-year seabirds average equals the median value.
- 50 - 75: The five-year seabirds average is higher than the median value.
- 75 - 90: The five-year seabirds average is much higher than the median value.
- 90 - 100: The five-year seabirds average is very high compared to the median value.
Description of seabirds:
Seabirds are a vital part of marine ecosystems and valuable indicators of an ecosystem’s status. Seabirds are attracted to fishing vessels and frequently get hooked or entangled in fishing gear, especially longline fisheries. This is a common threat to seabirds. Depending on the geographic region, fishermen in the United States often interact with albatross, cormorants, gannet, loons, pelicans, puffins, gulls, storm-petrels, shearwaters, terns, and many other species. We track seabirds because of their importance to marine food webs, but also as an indication of efficient fishing practices.
Indicator and Source Information:
This data was compiled by the US Fish and Wildlife Service and the multivariate index is calculated by a NOAA author. The Alaska Maritime National Wildlife Refuge has monitored seabirds at colonies around Alaska in most years since the early- to mid-1970’s. Time series of annual breeding success and phenology (among other parameters) are available from over a dozen species at eight Refuge sites in the Gulf of Alaska, Aleutian Islands, and Bering and Chukchi Seas. Monitored colonies in the eastern Bering Sea include St. Paul and St. George Islands. Here, we focus on cliff-nesting, primarily fish-eating species: black-legged kittiwake (Rissa tridactyla), red-legged kittwake (R. brevirostris), common murre (Uria aalge), thick-billed murre (U. lomvia), and redfaced cormorants (Phalacrocorax urile). Reproductive success is defined as the proportion of nest sites with eggs (or just eggs for murres that do not build nests) that fledged a chick.
Data Background and Caveats:
Data only include the species listed above in the Eastern Bering Sea Sub Region of Alaska. Reproductive activity of central-place foraging seabirds can reflect ecosystem conditions at multiple spatial and temporal scales. For piscivorous species that feed at higher trophic levels, continued reduced reproductive success may indicate that the ecosystem has not yet shifted back from warm conditions and/or there is a lagged response of the prey. Despite environmental changes returning back to more neutral conditions, seabird foraging conditions do not appear to have recovered in the eastern Bering Sea. In contrast, the improvement in attendance and minimal reproductive activity among murres in the Gulf of Alaska during 2017 indicates some improvement in foraging conditions for those species. Data can be directly accessed here: https://apps-afsc.fisheries.noaa.gov/refm/reem/ecoweb/Index.php?ID=9
Overfished Stocks
The x-axis represents years. The y-axis represents the number of fish stocks or fish populations that are deemed by NOAA as overfished. Overfished means the population of fish is too low. Therefore the population can not support a large amount of fishing.
Description of time series:
The series shows the number of fish populations that have qualified as overfished since 2000. Between 2016 and 2020 the number of overfished stocks showed a significant upward trend.
Description of gauge:
Gauge analysis was not appropriate for these data.
Overall Scores mean the following:
High values for overfished stocks are bad, low numbers are good.
- 0 - 10: The five-year overfished stock status average is very low compared to the median value.
- 10 - 25: The five-year overfished stock status average is much lower than the median value.
- 25 - 50: The five-year overfished stock status average is lower than the median value.
- 50: The five-year overfished stock status average equals the median value.
- 50 - 75: The five-year overfished stock status average is higher than the median value.
- 75 - 90: The five-year overfished stock status average is much higher than the median value.
- 90 - 100: The five-year overfished stock status average is very high compared to the median value.
Description of Overfished Stocks:
An overfished stock is a population of fish that is too low. From a technical standpoint, a stock that is overfished is depleted below a minimum level and active rebuilding is required. Stocks that are overfished cannot support a large amount of fishing. A fish stock can be listed as overfished as the result of many factors including overfishing, habitat degradation, pollution, climate change, and disease. The Magnuson-Stevens Act requires the status of overfished stocks be reported annually.
Stock assessments provide information to determine if a stock is overfished or experiencing overfishing (harvest higher than a maximum fishing threshold). This is done by estimating fishing intensity and the abundance of fish stocks and comparing those estimates to management reference points. Stock assessments can provide the science that supports the steps necessary to rebuild overfished stocks to sustainable levels.
It is important to track the status of fish stocks because fish play an important role in marine ecosystems, such as supporting the ecological structure of many marine food webs. Fish also support significant parts of coastal economies including recreational and commercial fisheries, and play an important cultural role in many regions.
This site presents the number of overfished stocks by year in all US Large Marine Ecosystems (LMEs).
Data Source:
Data were obtained from the NOAA Fisheries Fishery Stock Status website. Stocks that met the criteria for overfished status were summed by year for each region.
Threatened/Endangered Marine Mammals
Endangered Species Act threatened or endangered species
Values Correspond to the Number of ESA Threatened or Endangered Species in a given region
Data Interpretation
Gauge and Trend Analyses were not appropriate for marine mammal data.
Data Background and Caveats
NOAA Fisheries goes through required regulatory steps to list, reclassify, or delist a species under the ESA. For more information, see a step-by-step description of the ESA listing process. The listing process requires time and resources; as a result, the timing and number of listed marine species is not necessarily indicative of the actual number of currently endangered or threatened species and the exact timing of when these species became eligible to be listed under the ESA. Many marine species were initially listed when the ESA was passed in 1973; others have taken more time to be listed, and some have been reclassified or delisted since then.
Description of Threatened and Endangered Marine Mammals (ESA):
NOAA Fisheries is responsible for the protection, conservation, and recovery of endangered and threatened marine and anadromous species under the Endangered Species Act (ESA). The ESA aims to conserve these species and the ecosystems they depend on. Under the ESA, a species is considered endangered if it is in danger of extinction throughout all or a significant portion of its range, or threatened if it is likely to become endangered in the foreseeable future throughout all or a significant portion of its range See a species directory of all the threatened and endangered marine species under NOAA Fisheries jurisdiction, including marine mammals.
Under the ESA, a species must be listed if it is threatened or endangered because of any of the following 5 factors:
1) Present or threatened destruction, modification, or curtailment of its habitat or range;
2) Over-utilization of the species for commercial, recreational, scientific, or educational purposes;
3) Disease or predation;
4) Inadequacy of existing regulatory mechanisms; and
5) Other natural or manmade factors affecting its continued existence.
The ESA requires that listing determinations be based solely on the best scientific and commercial information available; economic impacts are not considered in making species listing determinations and are prohibited under the ESA. There are two ways by which a species may come to be listed (or delisted) under the ESA:
- NOAA Fisheries receives a petition from a person or organization requesting that NOAA lists a species as threatened or endangered, reclassify a species, or delist a species.
- NOAA Fisheries voluntarily chooses to examine the status of a species by initiating a status review of a species.
Strategic/Depleted Marine Mammal Stocks
Marine Mammal Protection Act strategic & depleted stocks
Values correspond to the number of MMPA Strategic or Depleted Marine Mammal Species listed each year in each region
Data Interpretation
Gauge and Trend Analyses were not appropriate for marine mammal data.
Data Background and Caveats
NOAA Fisheries prepares marine mammal stock assessment reports to track the status of marine mammal stocks. Some marine mammal stocks are thriving, while others are declining, and we often don’t know all the reasons behind a species or stock’s population trend. Because of this variability, it is difficult to indicate the state of an ecosystem or specific region using stock assessment data for marine mammal species that often range across multiple ecosystems and regions.
Description of Marine Mammal Strategic and Depleted Stocks (MMPA):
A stock is defined by the Marine Mammal Protection Act (MMPA), as a group of marine mammals of the same species or smaller taxa in a common spatial arrangement, that interbreed when mature. See a list of the marine mammal stocks NOAA protects under the MMPA.
A strategic stock is defined by the MMPA as a marine mammal stock—
- For which the level of direct human-caused mortality exceeds the potential biological removal level or PBR (defined by the MMPA as the maximum number of animals, not including natural mortalities, that may be removed from a marine mammal stock while allowing that stock to reach or maintain its optimum sustainable population);
- Which, based on the best available scientific information, is declining and is likely to be listed as a threatened species under the Endangered Species Act (ESA) within the foreseeable future; or
- Which is listed as a threatened or endangered species under the ESA, or is designated as depleted under the MMPA.
A depleted stock is defined by the MMPA as any case in which—
- The Secretary of Commerce, after consultation with the Marine Mammal Commission and the Committee of Scientific Advisors on Marine Mammals established under MMPA title II, determines that a species or population stock is below its optimum sustainable population;
- A State, to which authority for the conservation and management of a species or population stock is transferred under section 109, determines that such species or stock is below its optimum sustainable population; or
- A species or population stock is listed as an endangered species or a threatened species under the ESA.
Marine Species Distribution
Eastern Bering Sea Latitude
Values indicate annual cumulative change in centroid across all species in a region in degrees N
Description of Time Series: Between 2014 and 2018 the average species latitudinal shift showed an increasing trend, indicating a northward shift in distributions.
Description of Gauge: The gauge value of 95 indicates that between 2014 and 2018 the average species latitudinal shift was very high compared to the median average latitudinal shift between 1981 and 2018
Gauge Values
- 0 - 10: The five-year latitudinal shift is very low compared to the median value.
- 10 - 25: The five-year latitudinal shift is much lower than the median value.
- 25 - 50: The five-year latitudinal shift is lower than the median value.
- 50: The five-year latitudinal shift average equals the median value.
- 50 - 75: The five-year latitudinal shift is higher than the median value.
- 75 - 90: The five-year latitudinal shift is much higher than the median value.
- 90 - 100: The five-year latitudinal shift is very high compared to the median value
Description of Marine Species Distribution (Latitude and Depth):
The geographic location where a species is found, known as that species’ “distribution”, is a fundamental piece of information. Some species naturally move from location to location throughout the year, following seasons, food, or other factors. However, as climate change causes ocean waters to warm, populations of many species are moving towards the poles (northward in the northern hemisphere) or deeper towards cooler waters, allowing them to track their preferred temperature. Changes in a species distribution are not always due to individual animals following a preferred temperature, but could also be due to reduced survival of individuals in the warming areas. Understanding where and how fast marine species are moving is important to coastal communities as these changing distributions can affect the species available for fishing, recreation, and cultural practices. Marine species distributions are also good indicators of a warming ocean as they largely follow the species’ preferred temperature, can react quickly to ocean changes, and have been measured for many years, allowing us to see changes over time.
Indicator Source Information:
This data provides important information for fisheries management including which species are caught where and at what depth. The scientists at Ocean Adapt use this data to calculate each species’ centroid as the mean latitude and depth of catch in the survey, weighted by biomass. The centroid for each species is calculated for each year after standardizing the data to ensure that the measure is consistent over time despite changes in survey techniques and total area surveyed.
Data Background and Caveats:
The regional and national marine species distributions shown here represent the average shift in the centroid of species caught in surveys conducted in each region. These species represent a wide range of habitats and species types. As species distributions respond to many environmental and biological factors, combining data from multiple diverse species allows for a more complete picture of the general trends in marine species distribution. In order to more easily track and display changes in these distributions, the first year is standardized to zero. Thus, the indicator represents relative change in distribution from the first survey year.
Marine Species Distribution
Eastern Bering Sea Depth
Values Indicate annual cumulative change in average species centroid depth in meters - for example, a value of -5 indicates a decrease in average depth by 5m.
Description of Time Series: Between 2014 and 2018 the average species water column depth shift showed no significant trend.
Description of Gauge: The gauge value of 59 indicates that between 2014 and 2018 the average species water column depth shift was higher than the median average water column depth shift between 1981 and 2018 with species moving towards the surface.
Gauge Values
- 0 - 10: The five-year water column depth shift is very high compared to the median value with species moving deeper.
- 10 - 25: The five-year water column depth shift is much higher than the median value with species moving deeper.
- 25 - 50: The five-year water column depth shift is higher than the median value with species moving deeper.
- 50: The five-year water column depth shift average equals the median value.
- 50 - 75: The five-year water column depth shift is higher than the median value with species moving towards the surface.
- 75 - 90: The five-year water column depth shift is much higher than the median value with species moving towards the surface.
- 90 - 100: The five-year water column depth shift is very high compared to the median value with species moving towards the surface.
Description of Marine Species Distribution (Latitude and Depth):
The geographic location where a species is found, known as that species’ “distribution”, is a fundamental piece of information. Some species naturally move from location to location throughout the year, following seasons, food, or other factors. However, as climate change causes ocean waters to warm, populations of many species are moving towards the poles (northward in the northern hemisphere) or deeper towards cooler waters, allowing them to track their preferred temperature. Changes in a species distribution are not always due to individual animals following a preferred temperature, but could also be due to reduced survival of individuals in the warming areas. Understanding where and how fast marine species are moving is important to coastal communities as these changing distributions can affect the species available for fishing, recreation, and cultural practices. Marine species distributions are also good indicators of a warming ocean as they largely follow the species’ preferred temperature, can react quickly to ocean changes, and have been measured for many years, allowing us to see changes over time.
Indicator Source Information:
This data provides important information for fisheries management including which species are caught where and at what depth. The scientists at Ocean Adapt use this data to calculate each species’ centroid as the mean latitude and depth of catch in the survey, weighted by biomass. The centroid for each species is calculated for each year after standardizing the data to ensure that the measure is consistent over time despite changes in survey techniques and total area surveyed.
Data Background and Caveats:
The regional and national marine species distributions shown here represent the average centroid of all species caught in every year of the surveys. These species represent a wide range of habitats and species types. As species distributions respond to many environmental and biological factors, combining data from multiple diverse species allows for a more complete picture of the general trends in marine species distribution. In order to more easily track and display changes in these distributions, the first year is standardized to zero. Thus, the indicator represents relative change in distribution from the first survey year.
Marine Species Distribution
Gulf of Alaska Latitude
Values indicate annual cumulative change in centroid across all species in a region in degrees N
Description of Time Series: Between 2013 and 2017 the average species latitudinal shift shows no significant trend.
Description of Gauge: The gauge value of 64 indicates that between 2013 and 2017 the average species latitudinal shift was higher than the median average latitudinal shift between 1984 and 2017.
Gauge Values
- 0 - 10: The five-year latitudinal shift is very low compared to the median value.
- 10 - 25: The five-year latitudinal shift is much lower than the median value.
- 25 - 50: The five-year latitudinal shift is lower than the median value.
- 50: The five-year latitudinal shift average equals the median value.
- 50 - 75: The five-year latitudinal shift is higher than the median value.
- 75 - 90: The five-year latitudinal shift is much higher than the median value.
- 90 - 100: The five-year latitudinal shift is very high compared to the median value
Description of Marine Species Distribution (Latitude and Depth):
The geographic location where a species is found, known as that species’ “distribution”, is a fundamental piece of information. Some species naturally move from location to location throughout the year, following seasons, food, or other factors. However, as climate change causes ocean waters to warm, populations of many species are moving towards the poles (northward in the northern hemisphere) or deeper towards cooler waters, allowing them to track their preferred temperature. Changes in a species distribution are not always due to individual animals following a preferred temperature, but could also be due to reduced survival of individuals in the warming areas. Understanding where and how fast marine species are moving is important to coastal communities as these changing distributions can affect the species available for fishing, recreation, and cultural practices. Marine species distributions are also good indicators of a warming ocean as they largely follow the species’ preferred temperature, can react quickly to ocean changes, and have been measured for many years, allowing us to see changes over time.
Indicator Source Information:
This data provides important information for fisheries management including which species are caught where and at what depth. The scientists at Ocean Adapt use this data to calculate each species’ centroid as the mean latitude and depth of catch in the survey, weighted by biomass. The centroid for each species is calculated for each year after standardizing the data to ensure that the measure is consistent over time despite changes in survey techniques and total area surveyed.
Data Background and Caveats:
The regional and national marine species distributions shown here represent the average shift in the centroid of species caught in surveys conducted in each region. These species represent a wide range of habitats and species types. As species distributions respond to many environmental and biological factors, combining data from multiple diverse species allows for a more complete picture of the general trends in marine species distribution. In order to more easily track and display changes in these distributions, the first year is standardized to zero. Thus, the indicator represents relative change in distribution from the first survey year.
Marine Species Distribution
Gulf of Alaska Depth
Values Indicate annual cumulative change in average species centroid depth in meters - for example, a value of -5 indicates a decrease in average depth by 5m.
Description of Time Series: Between 2013 and 2017 the average species water column depth shift shows no significant trend.
Description of Gauge: The gauge value of 50 indicates that between 2013 and 2017 the average species water column depth shift was the median average water column depth shift between 1984 and 2017.
Gauge Values
- 0 - 10: The five-year water column depth shift is very high compared to the median value with species moving deeper.
- 10 - 25: The five-year water column depth shift is much higher than the median value with species moving deeper.
- 25 - 50: The five-year water column depth shift is higher than the median value with species moving deeper.
- 50: The five-year water column depth shift average equals the median value.
- 50 - 75: The five-year water column depth shift is higher than the median value with species moving towards the surface.
- 75 - 90: The five-year water column depth shift is much higher than the median value with species moving towards the surface.
- 90 - 100: The five-year water column depth shift is very high compared to the median value with species moving towards the surface.
Description of Marine Species Distribution (Latitude and Depth):
The geographic location where a species is found, known as that species’ “distribution”, is a fundamental piece of information. Some species naturally move from location to location throughout the year, following seasons, food, or other factors. However, as climate change causes ocean waters to warm, populations of many species are moving towards the poles (northward in the northern hemisphere) or deeper towards cooler waters, allowing them to track their preferred temperature. Changes in a species distribution are not always due to individual animals following a preferred temperature, but could also be due to reduced survival of individuals in the warming areas. Understanding where and how fast marine species are moving is important to coastal communities as these changing distributions can affect the species available for fishing, recreation, and cultural practices. Marine species distributions are also good indicators of a warming ocean as they largely follow the species’ preferred temperature, can react quickly to ocean changes, and have been measured for many years, allowing us to see changes over time.
Indicator Source Information:
This data provides important information for fisheries management including which species are caught where and at what depth. The scientists at Ocean Adapt use this data to calculate each species’ centroid as the mean latitude and depth of catch in the survey, weighted by biomass. The centroid for each species is calculated for each year after standardizing the data to ensure that the measure is consistent over time despite changes in survey techniques and total area surveyed.
Data Background and Caveats:
The regional and national marine species distributions shown here represent the average centroid of all species caught in every year of the surveys. These species represent a wide range of habitats and species types. As species distributions respond to many environmental and biological factors, combining data from multiple diverse species allows for a more complete picture of the general trends in marine species distribution. In order to more easily track and display changes in these distributions, the first year is standardized to zero. Thus, the indicator represents relative change in distribution from the first survey year.
Coastal Employment
Values correspond to total employment in all industries in a given region
Description of time series:
Alaska’s coastal employment has been relatively steady between 2014 - 2018, with no clear trend and no substantial difference from historical patterns.
Description of gauge:
The gauge value of 85 indicates that coastal employment between 2014 and 2018 for Alaska was higher than 85% of all years between 1990 and 2018.
Extreme Gauge values:
A value of zero on the gauge means that the average coastal employment level over the last 5 years of data was below any annual employment level up until that point, while a value of 100 would indicate the average over that same period was above any annual employment level up until that point.
Description of coastal employment:
The total coastal employment is the number of jobs in coastal communities. Businesses in coastal counties employ tens of millions of people nationally. This includes hundreds of thousands of ocean-dependent businesses that pay over $100 billion in wages annually. Many coastal and ocean amenities attracting visitors are free, generating no direct employment, wages, or gross domestic product. However, these “nonmarket” features are key drivers for many coastal businesses. We present data for all regions.
Data Source:
Coastal employment numbers were downloaded from the U.S. Bureau of Labor Statistics’ quarterly census of employment and wages, filtered to present only coastal county values using the Census Bureau’s list of coastal counties within each state. Of note is that these data fail to include self-employed individuals. Coastal county employment numbers were then summed within each region for reporting purposes.
Commercial Fishery Landings
Values correspond to landings in millions of metric tons
Description of time series:
Between 2015 and 2019, commercial landings from Alaska are substantially above historic levels, although there is no recent trend apparent.
Description of gauge:
The gauge value of 94 indicates that the mean annual commercial landings between 2015 and 2019 for Alaska was higher than 94% of all years between 1950 and 2019
Extreme Gauge values:
A value of zero on the gauge means that the average revenue or landings over the last 5 years of data was below any annual value up until that point, while a value of 100 would indicate the average value over that same period was above any annual value up until that point.
Description of Commercial Fishing (Landings and Revenue):
Commercial landings are the weight of, or revenue from, fish that are caught, brought to shore, processed, and sold for profit. It does not include sport or subsistence (to feed themselves) fishermen or for-hire sector, which earns its revenue from selling recreational fishing trips to saltwater anglers.
Commercial landings make up a major part of coastal economies. U.S. commercial fisheries are among the world’s largest and most sustainable; producing seafood, fish meal, vitamin supplements, and a host of other products for both domestic and international consumers.
The weight (tonnage), and revenue from the sale of commercial landings provides data on the ability of marine ecosystems to continue to supply these important products.
Indicator Source Information:
Landings are reported in pounds of round (live) weight for all species or groups except univalve and bivalve mollusks, such as clams, mussels, oysters and scallops, which are reported as pounds of meats (excludes shell weight). Landings data may sometimes differ from state-reported landings due to our reporting of mollusks in meat weights rather than gallons, shell weight, or bushels. Also, NMFS includes some species such as kelp and oysters that are sometimes reported by state agricultural agencies and may not be included with state fishery agency landings data.
Data Background and Caveats:
All landings summaries will return only non confidential landing statistics. Federal statutes prohibit public disclosure of landings (or other information) that would allow identification of the data contributors and possibly put them at a competitive disadvantage. Most summarized landings are non confidential, but whenever confidential landings occur they have been combined with other landings and usually reported as "Withheld for Confidentiality" Total landings by state include confidential data and will be accurate, but landings reported by individual species may, in some instances, be misleading due to data confidentiality.
Landings data do not indicate the physical location of harvest but the location at which the landings either first crossed the dock or were reported from.
Many fishery products are gutted or otherwise processed while at sea and are landed in a product type other than round (whole) weight. Our data partners have standard conversion factors for the majority of the commonly caught species that convert their landing weights from any product type to whole weight. It is the whole weight that is displayed in our web site landing statistics. Caution should be exercised when using these statistics. An example of a potential problem is when landings statistics are used to monitor fishery quotas. In some situations, specific conversion factors may have been designated in fishery management plans or Federal rule making that differ from those historically used by NOAA Fisheries in reporting landings statistics.
The dollar value of the landings are ex-vessel (as paid to the fisherman at time of first sale) and are reported as nominal (current at the time of reporting) values. Users can use the Consumer Price Index (CPI) or the Producer Price Index (PPI) to convert these nominal landing values into real (deflated) values.
Landings do not include aquaculture products except for clams, mussels and oysters.
Pacific landings summarized by state include an artificial “state” designation of “At-Sea Process, Pac.” This designation was assigned to landings consisting of primarily whiting caught in the EEZ off Washington and Oregon that were processed aboard large vessels while at sea. No Pacific state lists these fish on their trip tickets which are used to report state fishery landing, hence the at-sea processor designation was used to insure that they would be listed as a U.S. landing.
Landing summaries are compiled from data bases that overlap in time and geographic coverage, and come from both within and outside of NOAA Fisheries.
Commercial Fishery Revenue
Values correspond to real revenue is 2020 US Dollars
Description of time series:
Commercial revenue from Alaska between 2015 and 2019 were not different from historical patterns, and there is no trend in values. Given that landings were at historically high levels for that same period, this suggests that the price per pound of fish is substantially lower than historical levels.
Description of gauge:
The gauge value of 67 indicates that the mean annual commercial revenue between 2015 and 2019 for Alaska was higher than 67% of all years between 1950 and 2019
Extreme Gauge values:
A value of zero on the gauge means that the average revenue or landings over the last 5 years of data was below any annual value up until that point, while a value of 100 would indicate the average value over that same period was above any annual value up until that point.
Description of Commercial Fishing (Landings and Revenue):
Commercial landings are the weight of, or revenue from, fish that are caught, brought to shore, processed, and sold for profit. It does not include sport or subsistence (to feed themselves) fishermen or for-hire sector, which earns its revenue from selling recreational fishing trips to saltwater anglers.
Commercial landings make up a major part of coastal economies. U.S. commercial fisheries are among the world’s largest and most sustainable; producing seafood, fish meal, vitamin supplements, and a host of other products for both domestic and international consumers.
The weight (tonnage), and revenue from the sale of commercial landings provides data on the ability of marine ecosystems to continue to supply these important products.
Indicator Source Information:
Landings are reported in pounds of round (live) weight for all species or groups except univalve and bivalve mollusks, such as clams, mussels, oysters and scallops, which are reported as pounds of meats (excludes shell weight). Landings data may sometimes differ from state-reported landings due to our reporting of mollusks in meat weights rather than gallons, shell weight, or bushels. Also, NMFS includes some species such as kelp and oysters that are sometimes reported by state agricultural agencies and may not be included with state fishery agency landings data.
Data Background and Caveats:
All landings summaries will return only non confidential landing statistics. Federal statutes prohibit public disclosure of landings (or other information) that would allow identification of the data contributors and possibly put them at a competitive disadvantage. Most summarized landings are non confidential, but whenever confidential landings occur they have been combined with other landings and usually reported as "Withheld for Confidentiality" Total landings by state include confidential data and will be accurate, but landings reported by individual species may, in some instances, be misleading due to data confidentiality.
Landings data do not indicate the physical location of harvest but the location at which the landings either first crossed the dock or were reported from.
Many fishery products are gutted or otherwise processed while at sea and are landed in a product type other than round (whole) weight. Our data partners have standard conversion factors for the majority of the commonly caught species that convert their landing weights from any product type to whole weight. It is the whole weight that is displayed in our web site landing statistics. Caution should be exercised when using these statistics. An example of a potential problem is when landings statistics are used to monitor fishery quotas. In some situations, specific conversion factors may have been designated in fishery management plans or Federal rule making that differ from those historically used by NOAA Fisheries in reporting landings statistics.
The dollar value of the landings are ex-vessel (as paid to the fisherman at time of first sale) and are reported as nominal (current at the time of reporting) values. Users can use the Consumer Price Index (CPI) or the Producer Price Index (PPI) to convert these nominal landing values into real (deflated) values.
Landings do not include aquaculture products except for clams, mussels and oysters.
Pacific landings summarized by state include an artificial “state” designation of “At-Sea Process, Pac.” This designation was assigned to landings consisting of primarily whiting caught in the EEZ off Washington and Oregon that were processed aboard large vessels while at sea. No Pacific state lists these fish on their trip tickets which are used to report state fishery landing, hence the at-sea processor designation was used to insure that they would be listed as a U.S. landing.
Landing summaries are compiled from data bases that overlap in time and geographic coverage, and come from both within and outside of NOAA Fisheries.
Recreational Fishing Effort
Values correspond to cumulative number of angler trips
Description of time series:
Between 2014 and 2019, recreational fishing effort from Alaska is around historic levels. There is no significant trend apparent.
Description of gauge:
The gauge value of 50 indicates that the recreational fishing effort between 2015 and 2019 for Alaska was the median value for the recreational fishing effort values between 1996 and 2019
Extreme Gauge values:
A value of zero on the gauge means that the average effort or harvest over the last 5 years of data was below any annual value up until that point, while a value of 100 would indicate the average value over that same period was above any annual value up until that point.
Description of Recreational Fishing (Effort and Harvest):
U.S. saltwater recreational fishing is an important source of seafood, jobs, and recreation for millions of anglers and for-hire recreational businesses. Recreational fishing effort is measured as “Angler Trips”, which is the number of recreational fishing trips people go on. Recreational fishing harvest is the number of fish caught and brought to shore on recreational fishing trips.
Recreational effort and harvest help us understand how recreational opportunities and seafood derived from our marine environment is changing over time. Fisheries managers use this data to set annual catch limits and fishing regulations, including season lengths, size, and daily catch limits. We present the total number of fish harvested and angler trips annually for all marine fish in all regions.
Indicator Source Information
Recreational harvest and effort data pulled from National Summary Query. Units of data are in Effort in Angler Trips and Harvest in numbers of fish. The data from these queries is used by state, regional and federal fisheries scientists and managers to maintain healthy and sustainable fish stocks.
Data Background and Caveats:
To properly interpret this information, it is important to consider the following key points:
- When comparing harvest estimates across an extended time series, note differences in sampling coverage through the years. Some estimates may not be comparable over long time series.
- Changes may occur between preliminary and final estimates and year to year, meaning that the data may change when updated. Please review the Limitations and other sections on the Using the Data page from the source for more information.
Recreational Fishing Harvest
Values correspond to harvest in millions of fish
Description of time series:
Between 2015 and 2019, recreational harvest from Alaska are around historic levels. There is a significant downward trend apparent.
Description of gauge:
The gauge value of 62 indicates that the recreational fishing harvest between 2015 and 2019 for Alaska was higher than 62% of the recreational fishing harvest values between 1996 and 2019
Extreme Gauge values:
A value of zero on the gauge means that the average effort or harvest over the last 5 years of data was below any annual value up until that point, while a value of 100 would indicate the average value over that same period was above any annual value up until that point.
Description of Recreational Fishing (Effort and Harvest):
U.S. saltwater recreational fishing is an important source of seafood, jobs, and recreation for millions of anglers and for-hire recreational businesses. Recreational fishing effort is measured as “Angler Trips”, which is the number of recreational fishing trips people go on. Recreational fishing harvest is the number of fish caught and brought to shore on recreational fishing trips.
Recreational effort and harvest help us understand how recreational opportunities and seafood derived from our marine environment is changing over time. Fisheries managers use this data to set annual catch limits and fishing regulations, including season lengths, size, and daily catch limits. We present the total number of fish harvested and angler trips annually for all marine fish in all regions.
Indicator Source Information
Recreational harvest and effort data pulled from National Summary Query. Units of data are in Effort in Angler Trips and Harvest in numbers of fish. The data from these queries is used by state, regional and federal fisheries scientists and managers to maintain healthy and sustainable fish stocks.
Data Background and Caveats:
To properly interpret this information, it is important to consider the following key points:
- When comparing catch estimates across an extended time series, note differences in sampling coverage through the years. Some estimates may not be comparable over long time series.
- Changes may occur between preliminary and final estimates and year to year, meaning that the data may change when updated. Please review the Limitations and other sections on the Using the Data page from the source for more information.
Commercial Fishing Engagement
The x-axis on this time series represents years and the y-axis represents the percent of communities that are moderate to highly engaged in commercial fishing across Alaska. Commercial fishing engagement is measured by the number permits, fish dealers, and vessel landings across Alaska.
Description of time series:
This time series shows the percent of communities moderately or highly engaged in commercial fishing in Alaska from 2009 to 2018. Between 2013 and 2018 (highlighted in green) the percent of communities moderately or highly engaged in commercial fishing showed no significant trend.
Description of gauge:
The gauge value of 70 indicates that the average annual commercial fishing engagement between 2013 and 2018 for Alaska was higher than 70% of all years in the time series.
Extreme Gauge values:
A value of zero on the gauge means that the average percentage of communities engaged in commercial or recreational fishing over the last 5 years of data was below any annual engagement level up until that point, while a value of 100 would indicate the average over that same period was above any engagement level up until that point.
Description of Fishing Engagement:
Recreational and commercial fishing engagement is measured by the presence of fishing activity in coastal communities. The commercial engagement index is measured through permits, fish dealers, and vessel landings. The data for recreational engagement indicators varies by state. A high rank within these indicates more engagement in fisheries. For details on both data sources and indicator development, please see https://www.fisheries.noaa.gov/national/socioeconomics/social-indicators-fishing-communities-0.
NOAA Monitors recreational and commercial fishing engagement to better understand the social and economic impacts of fishing policies and regulations on our nation’s vital fishing communities. This and other social indicators help assess a coastal community’s resilience. NOAA works with state and local partners to monitor these indicators. We present data from the Northeast, Southeast, Gulf of Mexico, California Current, Alaska, and Pacific Island regions.
Data Source:
Commercial fishing engagement data is from the National Marine Fisheries Service’s social indicator data portal:https://www.st.nmfs.noaa.gov/data-and-tools/social-indicators/ The percentage of all communities in each region classified as medium, medium high, or highly engaged is presented for both recreational and commercial fishing.
Recreational Fishing Engagement
The x-axis on this time series represents years and the y-axis represents the percent of communities that are moderately to highly engaged in recreational fishing across Alaska.
Description of time series:
This time series shows the percent of communities moderately to highly engaged in recreational fishing in Alaska from 2009 to 2018. Between 2013 and 2018 (highlighted in green) the percent of communities moderately or highly engaged in recreational fishing showed an upward trend.
Description of gauge:
The gauge value of 40 indicates that the average annual recreational fishing engagement between 2013 and 2018 for Alaska was higher than 40% of all years between 2009 and 2018.
Extreme Gauge values:
A value of zero on the gauge means that the average percentage of communities engaged in commercial or recreational fishing over the last 5 years of data was below any annual engagement level up until that point, while a value of 100 would indicate the average over that same period was above any engagement level up until that point.
Description of Fishing Engagement:
Recreational and commercial fishing engagement is measured by the presence of fishing activity in coastal communities. The commercial engagement index is measured through permits, fish dealers, and vessel landings. The data for recreational engagement indicators varies by state. A high rank within these indicates more engagement in fisheries. For details on both data sources and indicator development, please see https://www.fisheries.noaa.gov/national/socioeconomics/social-indicators-fishing-communities-0.
NOAA Monitors recreational and commercial fishing engagement to better understand the social and economic impacts of fishing policies and regulations on our nation’s vital fishing communities. This and other social indicators help assess a coastal community’s resilience. NOAA works with state and local partners to monitor these indicators. We present data from the Northeast, Southeast, Gulf of Mexico, California Current, Alaska, and Pacific Island regions.
Indicator Source Information
The Alaska recreational engagement index is measured using the number of charter and sportfishing guide businesses, and sportfishing and guide licenses.
Data Source:
Commercial fishing engagement data is from the National Marine Fisheries Service’s social indicator data portal:https://www.st.nmfs.noaa.gov/data-and-tools/social-indicators/ The percentage of all communities in each region classified as medium, medium high, or highly engaged is presented for both recreational and commercial fishing
Billion-Dollar Disasters
Values correspond to the number of events in a given year
Interpretation of Time Series
Billion dollar disasters in Alaska only began to occur after 2000, but the last 5 years of data indicates the number of storms has begun to deviate from historical patterns of events, and there is a recent upward trend in the number of disasters.
Interpretation of Gauge
The gauge value of 82 indicates that the number of billion dollar disasters between 2016 and 202o for Alaska was higher than 82% of all years between 1980 and 2020.
Extreme Gauge values
A value of zero on the gauge means that the average number of disasters over the last 5 years of data was below any annual level up until that point, while a value of 100 would indicate the average over that same period was above any annual number of disasters up until that point.
Description of billion dollar disasters:
In the United States, the number of weather and climate-related disasters exceeding 1 billion dollars has been increasing since 1980. These events have significant impacts to coastal economies and communities. The Billion Dollar Disaster indicator provides information on the frequency and the total estimated costs of major weather and climate events that occur in the United States. This indicator compiles the annual number of weather and climate-related disasters across seven event types. We Present the total annual number of disaster events for all regions.
Indicator Source Information:
Billion dollar disaster event frequency data are taken from NOAA’s National Centers for Environmental Information. The number of disasters within each region were summed for every year of available data. Although the number is the count of unique disaster events within a region, the same disaster can impact multiple regions, meaning a sum across regions will overestimate the unique number of disasters.
Data Background and Caveats:
Events are included if they are estimated to cause more than one billion U.S. dollars in direct losses. The cost estimates of these events are adjusted for inflation using the Consumer Price Index (CPI) and are based on costs documented in several Federal and private-sector databases.
Coastal Population
Values correspond to the total coastal population for a given region
Description of time series:
Alaska’s average coastal population between 2014 – 2018 was substantially above historic levels, although the recent trend is not different from historical trends.
Description of gauge:
The average coastal population in Alaska between 2014 and 2018 was greater than 92% of all population levels between 1970 to 2018, again highlighting the substantial growth in the coastal population of this state.
Extreme Gauge values:
A value of zero on the gauge means that the average coastal population over the last 5 years of data was below any annual population level up until that point, while a value of 100 would indicate the average over that same period was above any annual population level up until that point.
Description of Coastal Population:
While marine ecosystems are important for people all across the country, they are essential for people living in coastal communities. The population density of coastal counties is over six times greater than inland counties. In the U.S. coastal counties make up less than 10 percent of the total land area (not including Alaska), but account for 39 percent of the total population. From 1970 to 2010, the population of these counties increased by almost 40% and are projected to increase by over 10 million people or 8+% into the 2020s.
The population density of an area is an important factor for economic planning, emergency preparedness, understanding environmental impacts, resource demand, and many other reasons. Thus, this indicator is important to track. We present the number of residents within all regions.
Indicator Source Information:
The American Community Survey (ACS) helps local officials, community leaders, and businesses understand the changes taking place in their communities. It is the premier source for detailed population and housing information about our nation. The 2020 ACS Data Update will be publicly available no later than November 30, 2021.
Data Background and Caveats:
The values represented here are coastal county population estimates for states bordering US Large Marine Ecosystems as calculated by the US Census Bureau from the American Community Survey.
Coastal Tourism GDP
Values correspond to percent change in the GDP of the Tourism Sector of Coastal Counties in US States that border a region
Description of Time Series: Between 2014 and 2018 the average change in coastal county tourism GDP showed a decreasing trend.
Description of Gauge: The gauge value of 54 indicates that between 2014 and 2018 the average change in coastal county tourism sector GDP was higher than the median change in coastal county tourism sector GDP between 2006 and 2018.
Extreme Gauge values:
A value of zero on the gauge means that the average coastal tourism GDP over the last 5 years of data was below any annual coastal tourism GDP level up until that point, while a value of 100 would indicate the average over that same period was above any annual coastal tourism GDP value up until that point.
Description of Coastal Tourism:
U.S. coasts are host to a multitude of travel, tourism, and recreation activities. To manage our coasts, plan for development, and assess impacts as a result of coastal hazards including sea level rise, it is important to have baseline economic information. To accomplish this, we need indicators of the economic value of recreation and tourism. We present the annual total change in billions of dollars of goods and services (GDP), employment and annual wages provided from tourism industries in the Gulf of Mexico, Mid-Atlantic, Northeast, Hawaii-Pacific Islands, Southeast, and California Current regions. This data does not include industries located in U.S. territories.
Indicator Source Information
Coastal tourism Gross Domestic Product is the total measure (in billions of 2012 dollars) of goods and services provided from various industries involved in tourism services and products along the coast. Data for Coastal Counties come from the US Census Bureau. This dataset represents US counties and independent cities which have at least one coastal border and select non-coastal counties and independent cities based on proximity to estuaries and other coastal counties. The dataset is built to support coastal and ocean planning and other activities pursuant to the Energy Policy Act, Coastal Zone Management Act, Magnuson-Stevens Fishery Conservation and Management Act, National Environmental Policy Act, Rivers and Harbors Act and the Submerged Lands Act.
Coastal Tourism Employment
Values correspond to percent change in the total Employment of the Tourism Sector of Coastal Counties in US States that border a region
Description of Time Series: Between 2014 and 2018 the average change in coastal county employment showed a decreasing trend.
Description of Gauge: Between 2014 and 2018 the average change in coastal county tourism sector employment was higher than the median change in coastal county tourism sector employment between 2006 and 2018.
Extreme Gauge values:
A value of zero on the gauge means that the average coastal tourism employment over the last 5 years of data was below any annual coastal tourism employment level up until that point, while a value of 100 would indicate the average over that same period was above any annual coastal tourism employment level up until that point.
Description of Coastal Tourism:
U.S. coasts are host to a multitude of travel, tourism, and recreation activities. To manage our coasts, plan for development, and assess impacts as a result of coastal hazards including sea level rise, it is important to have baseline economic information. To accomplish this, we need indicators of the economic value of recreation and tourism. We present the annual total change in billions of dollars of goods and services (GDP), employment and annual wages provided from tourism industries in the Gulf of Mexico, Mid-Atlantic, Northeast, Hawaii-Pacific Islands, Southeast, and California Current regions. This data does not include industries located in U.S. territories.
Indicator Source Information:
Coastal tourism employment is the total measure of jobs in tourism industries along the coast. Data for Coastal Counties come from the US Census Bureau. This dataset represents US counties and independent cities which have at least one coastal border and select non-coastal counties and independent cities based on proximity to estuaries and other coastal counties. The dataset is built to support coastal and ocean planning and other activities pursuant to the Energy Policy Act, Coastal Zone Management Act, Magnuson-Stevens Fishery Conservation and Management Act, National Environmental Policy Act, Rivers and Harbors Act and the Submerged Lands Act.
Coastal Tourism Wages
Values correspond to percent change in the total real wage compensation of the Tourism Sector of Coastal Counties in US States that border a region
Description of Time Series: Between 2014 and 2018 the average change in coastal county real wage compensation showed a decreasing trend.
Description of Gauge: Between 2014 and 2018 the average change in coastal county tourism sector real wage compensation was much higher than the median change in coastal county tourism sector real wage compensation between 2006 and 2018.
Extreme Gauge values:
A value of zero on the gauge means that the average coastal tourism wage compensation over the last 5 years of data was below any annual coastal tourism wage compensation level up until that point, while a value of 100 would indicate the average over that same period was above any annual coastal tourism wage compensation level up until that point.
Description of Coastal Tourism:
U.S. coasts are host to a multitude of travel, tourism, and recreation activities. To manage our coasts, plan for development, and assess impacts as a result of coastal hazards including sea level rise, it is important to have baseline economic information. To accomplish this, we need indicators of the economic value of recreation and tourism. We present the annual total change in billions of dollars of goods and services (GDP), employment and annual wages provided from tourism industries in the Gulf of Mexico, Mid-Atlantic, Northeast, Hawaii-Pacific Islands, Southeast, and California Current regions. This data does not include industries located in U.S. territories.
Indicator Source Information:
Coastal tourism wage is the measure of wages (nominal) paid to employees in tourism industries along the coast. Data for Coastal Counties come from the US Census Bureau. This dataset represents US counties and independent cities which have at least one coastal border and select non-coastal counties and independent cities based on proximity to estuaries and other coastal counties. The dataset is built to support coastal and ocean planning and other activities pursuant to the Energy Policy Act, Coastal Zone Management Act, Magnuson-Stevens Fishery Conservation and Management Act, National Environmental Policy Act, Rivers and Harbors Act and the Submerged Lands Act.
Resources
Arctic Report Card
Tracking recent environmental changes relative to historical records.
Alaska Ecosystem Status Reports
Ecosystem Status Reports are produced annually to compile and summarize information about the status of the Alaska marine ecosystems for the North Pacific Fishery Management Council, the scientific community and the public.
Distributed Biological Observatory
The “Distributed Biological Observatory (DBO)” is envisioned as a change detection array along a latitudinal gradient extending from the northern Bering Sea to the Barrow Arc [map of sites and example of change in sea ice and Chl-a].
International Arctic Systems for Observing the Atmosphere
The mission of the IASOA is to advance and coordinate research objectives from independent pan-Arctic atmospheric observatories.
National Snow and Ice data
The National Snow and Ice Data Center (NSIDC) supports research into our world’s frozen realms: the snow, ice, glaciers, frozen ground, and climate interactions that make up Earth’s cryosphere.
Satellite Observations of Arctic Change
The purpose of this site is to expose NASA satellite data and research on Arctic change, in the form of maps that illustrate the changes taking place in the Arctic over time.
Alaska Ocean Observing System (AOOS) Ocean Data Explorer
This portal contains scientific and management information including real-time sensor feeds, operational oceanographic and atmospheric models, satellite observations and GIS data sets that describe the biological, chemical and physical characteristics of Alaska and its surrounding waters.
AOOS Data Resources
This statewide portal provides access to all of AOOS’ public data, allowing users to visualize and integrate different types of data from many sources.
EcoFOCI
EcoFOCI is a joint research program between the Alaska Fisheries Science Center (NOAA/ NMFS/ AFSC) and the Pacific Marine Environmental Laboratory (NOAA/ OAR/ PMEL). We study the ecosystems of the North Pacific Ocean, Bering Sea and U.S. Arctic to improve understanding of ecosystem dynamics and we apply that understanding to the management of living marine resources. EcoFOCI scientists integrate field, laboratory and modeling studies to determine how varying biological and physical factors influence large marine ecosystems within Alaskan waters.
Arctic Marine Biodiveristy Observation Network
AMBON involves an experienced team of multi-institutional and multi-sector partners already active in a variety of Arctic biodiversity observing programs, and we work with the Alaska Ocean Observing System (AOOS) to coordinate data streams from these different programs into one observation network. This partnership within AMBON will allow us to better coordinate, sustain, and synthesize all efforts, and make data available to a broad audience of users and stakeholders, from local to pan-Arctic to global. Effective data management, integration and dissemination will provide critical information on the status of Arctic ecosystem health and resilience to decision makers and local, regional and global communities.
Sustaining Arctic Observing Networks (SAON)
The purpose of the Sustaining Arctic Observing Networks (SAON) is to support and strengthen the development of multinational engagement for sustained and coordinated pan-Arctic observing and data sharing systems. SAON was initiated by the Arctic Council and the International Arctic Science Committee, and was established by the 2011 Ministerial Meeting in Nuuk.
The SAON inventory builds on a survey circulated in the community at the inception of the activity. This database is continously updated and maintained, and contains projects, activities, networks and programmes related to environmental observation in the circum-polar Arctic.
NOAA Environmental Response Management Application (ERMA): Regional Portals
The Environmental Response Management Application is a web-based Geographic Information System (GIS) tool that assists emergency responders and environmental resource managers in dealing with incidents that may adversely impact the environment.
U.S. Global Change Research Program: Arctic Sea Ice Extent
The U.S. Global Change Research Program (USGCRP) is a federal program mandated by Congress to coordinate federal research and investments in understanding the forces shaping the global environment, both human and natural, and their impacts on society. USGCRP facilitates collaboration and cooperation across its 13 federal member agencies to advance understanding of the changing Earth system and maximize efficiencies in federal global change research.
Marine Biodiversity Observation Network - Arctic Projects
Unprecedented changes are occurring in the Arctic and affect all components of Arctic marine ecosystems, including humans. However, consistent, long-term observations for planning and adaptation are currently lacking in the Arctic Ocean. AMBON is working towards a sustainable approach to biodiversity observing in the Chukchi Sea as one component of the development of a national MBON. Grounded in the concept that sustained biodiversity across ecosystem components is critical for maintaining healthy ecosystem functions, this project is building on lessons learned from the first 5-year AMBON demonstration project.
DBO Data Portal
The Distributed Biological Observatory (DBO) is a multi-agency, ship-based research program studying biological responses to rapid physical changes in the Arctic marine ecosystem.
Arctic Report Card Data Portal
Issued annually since 2006, the Arctic Report Card (https://arctic.noaa.gov/Report-Card) provides clear, reliable, and concise environmental information on the current state of different components of the Arctic environmental system relative to historical records. This portal compiles the publicly available datasets that inform the key findings in the 2020 Vital Signs. In the coming years, it will include the "Frostbites" and "Other Indicators."
Ocean ADAPT
OceanAdapt is a collaboration between Rutgers University, the National Marine Fisheries Service (NMFS), and Fisheries and Oceans Canada (DFO) to provide information about the impacts of changing climate and other factors on the distribution of marine life to the National Climate Assessment, fisheries communities, policymakers, and to others. This website hosts an annually updated database of scientific surveys in the United States and Canada, providing tools for exploring changes in marine fish and invertebrate distributions.
