map of all US marine ecosystem regions

El Niño-Southern Oscillation (ENSO)

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graph of Oceanic Nino Index from 1980-2020

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.

 

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):

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. 

 

Data:

Climate indicator data was accessed from the NOAA Climate Prediction Center (https://origin.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff…). 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.

Multivariate ENSO Index (MEI)

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Graph of Multivariate ENSO Index 1980-2020

Description of time series:

Like the Oceanic Niño Index, positive MEI values indicate warm, El Niño conditions and negative MEI values indicate cold, La Niña conditions. The MEI indicator changed from positive to negative during the summer of 2020, and is now showing La Niña conditions.

 

Description of gauge:

The unitless two-way gauge depicts the most recent seasonal value for the MEI 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 Multivariate El Niño-Southern Oscillation Index:

The Multivariate El Niño-Southern Oscillation Index (MEI) is a more holistic representation of the atmospheric and oceanic conditions that occur during ENSO events and characterizes their intensity. MEI is determined from five variables from the central and eastern equatorial Pacific (Sea-level pressure, surface wind components, sea surface temperature, surface air temperature, and cloudiness) while ENSO is calculated from only two (sea surface temperature and trade wind strength). This index is calculated twelve times per year for each sliding bi-monthly season i.e. Dec-Jan, Jan-Feb, Feb-Mar, etc. We present data from the Pacific Islands, Alaska, and California Current regions.

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.

 

Data:

Climate indicator data was accessed from the NOAA’s Earth Systems Research Laboratory (https://psl.noaa.gov/enso/mei/). The data plotted are unitless anomalies.

Pacific Decadal Oscillation (PDO)

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Pacific Decadal Oscillation plot, 1980-2020

Description of time series:

Positive PDO values typically mean cold, La Niña conditions, and negative PDO values typically mean warm, El Niño conditions. 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.

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.

 

Data:

Climate indicator data was accessed from the NOAA Climate Prediction Center (https://www.cpc.ncep.noaa.gov/data/teledoc/nao.shtmlftp://ftp.cpc.ncep.noaa.gov/wd52dg/data/indices/nao_index.tim). The data plotted are unitless and based on Sea Surface Temperature anomalies averaged across a given region.

East Pacific - North Pacific Index (EP-NP)

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Graph of East Pacific - North Pacific index

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.

 

Data:

Climate indicator data was accessed from the NOAA Climate Prediction Center (https://www.cpc.ncep.noaa.gov/data/teledoc/nao.shtmlftp://ftp.cpc.ncep.noaa.gov/wd52dg/data/indices/nao_index.tim). The data plotted are unitless anomalies and averaged across a given region. 

 

North Atlantic Oscillation (NAO)

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Graph of North Atlantic Oscillation 1980-2020

Description of time series:

Positive NAO values mean significantly warmer winters over the upper Midwest and New England and negative NAO values can mean cold winter outbreaks and heavy snowstorms. During the last five years, the NAO 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 North Atlantic Oscillation (NAO):

The North Atlantic Oscillation (NAO) Index measures the relative strengths and positions of a permanent low-pressure system over Iceland (the Icelandic Low) and a permanent high-pressure system over the Azores (the Azores High). When the index is positive (NAO+) significantly warmer winters can occur over the upper Midwest and New England. On the East Coast of the United States a NAO+ can also cause increased rainfall, and thus warmer, less saline surface water. This prevents nutrient-rich upwelling, which reduces productivity. When the NAO index is negative, the upper central and northeastern portions of the United States can incur winter cold outbreaks and heavy snowstorms. We present data for the Northeast, Southeast, Gulf of Mexico, and Caribbean regions.

 

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.

 

Data:

Climate indicator data was accessed from the NOAA Climate Prediction Center (https://www.cpc.ncep.noaa.gov/data/teledoc/nao.shtmlftp://ftp.cpc.ncep.noaa.gov/wd52dg/data/indices/nao_index.tim). The data plotted are unitless anomalies and averaged across a given region.

Atlantic Meridional Oscillation (AMO)

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Graph of Atlantic Meridional Oscillation 1980-2020

Description of time series:

Positive AMO values indicate the warm phase and negative AMO values indicate the cold phase. During the last five years, the AMO 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 Atlantic Multidecadal Oscillation (AMO):

The Atlantic Multidecadal Oscillation is a series of long-duration changes in the North Atlantic sea surface temperature, with cool and warm phases that may last for 20-40 years. Most of the Atlantic between the equator and Greenland changes in unison. Some areas of the North Pacific also seem to be affected. 

 

This broadscale climate condition affects air temperatures and rainfall over much of the Northern Hemisphere. It is also related to major droughts in the Midwest and the Southwest of the U.S. In the warm phase, these droughts tend to be more frequent and/or severe. Vice-versa for the cold phase. During the warm phases the number of tropical storms that mature into severe hurricanes is much greater than during cool phases. We present data for the Northeast, Southeast, and Gulf of Mexico regions.

 

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.

 

Data:

Climate indicator data was accessed from the NOAA Climate Prediction Center (https://www.cpc.ncep.noaa.gov/data/teledoc/nao.shtmlftp://ftp.cpc.ncep.noaa.gov/wd52dg/data/indices/nao_index.tim). The data plotted are unitless anomalies and averaged across a given region. 

 

 

Sea Surface Temperature

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Graph of sea surface temperature for US waters, 1980-2020

Description of time series:

The time series shows the integrated sea surface temperature across the U.S.  During the last five years there has been a positive trend and values are greater than 90% of all observed data in the time series.

 

Description of gauge:

The gauge value of 92 indicates that the temperature between 2013 and 2017 for the entire US was higher than 92% of the temperatures between 1982 and 2017.

 

Description of Sea Surface Temperature:

Sea Surface Temperature (SST) is defined as the average temperature of the top few millimeters of the ocean. This temperature impacts the rate of all physical, chemical, and most biological processes occurring in the ocean. Sea Surface Temperature is globally monitored by sensors on satellites, buoys, ships, ocean reference stations, AUVs and other technologies. 

Sea Surface Temperature 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. Sea Surface Temperature 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 annual average SST in all regions.

Data:

The sea surface temperature were accessed from (https://www.ncdc.noaa.gov/oisst).  The data are plotted in degrees Celsius.

Sea level

Global coastal sea level from tide gauges

Graph of global sea level 1980-2020

Description of time series:

The time series shows the relative sea level across the U.S. 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 depicts the average of the last 5 years of data for Sea Surface Temperature relative to the median value of the entire time series. High values near 100 mean higher sea level, low values near 0 mean a lower sea level.  The current value indicates that sea level is near the higher end of what has been observed.

 

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, etc. 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, and emergency preparedness, etc. 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.

 

Data:

Source: http://www.cmar.csiro.au/sealevel/sl_data_cmar.html These data are measurements of global tide-gauge data that have been combined statistically to create a picture of global relative sea level (see Church, J. A. and N.J. White (2011), Sea-level rise from the late 19th to the early 21st Century. Surveys in Geophysics, doi:10.1007/s10712-011-9119-1 for methods). Data are in centimeters relative to the year 1880.

Arctic sea ice

Summer maximum sea ice extent

Graph of summer maximum Arctic sea ice extent

Description of time series:

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. 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 17 indicates that the mean sea ice extent between 2014 and 2018 for the Arctic region of the US was only higher than 17% of the sea ice extent measurements between 1980 and 2018.

 

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 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, i.e. 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 Indigenous communities culture and survival. We present the annual sea ice extent in millions of Kilometers for the Arctic region.

 

Data:

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.     

Chlorophyll-a

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Graph of nationwide chlorophyll A, 1980-2020

Description of time series:

Between 2013 and 2017 the national average concentration levels of chlorophyll ɑ showed no significant trend.

 

Description of gauge:

The gauge value of 85 indicates that between 2013 and 2017 the national average concentration levels of chlorophyll a were considerably higher than the median of all chlorophyll ɑ concentration levels between 1998 and 2017. 

 

Description of Chlorophyll a:

At the base of most marine food webs are microscopic plants, called phytoplankton - which also produce nearly half of the Earth’s oxygen. One way we measure the amount of phytoplankton in the ocean is via a pigment that phytoplankton produce - chlorophyll a. Using ocean color sensors on satellites, we can measure the amount of chlorophyll a in surface waters. Environmental and oceanographic factors continuously influence the abundance, composition, spatial distribution, and productivity of phytoplankton. Tracking the amount of phytoplankton in the ocean gives us the status of the base of the food web, and how much food is available for other animals to grow. Changes in the amount of phytoplankton in the ocean are part of the natural seasonal cycle, but can also indicate an ecosystem’s response to a major external disturbance.

 

Overall Scores mean the following:

  • 0 - 10:   “significantly lower” the long term median state
  • 10 - 25:  “considerably lower” the long term median state
  • 25 - 50:  “slightly lower” the long term median state
  • 50:  the long term median state
  • 50 - 75:  “slightly above” the long term median state
  • 75 - 90  “considerably above” the long term median state
  • 90 - 100:  “significantly higher” the long term median state

High values of Chlorophyll a can be good (lots of big nutrious diatoms) or bad (Harmful Algal Blooms), depending on the species present.

 

Data:

Chlorophyll a data were obtained from the NOAA Fisheries Coastal & Oceanic Plankton Ecology, Production, & Observations Database. Measurements of ocean chlorophyll concentration were combined from both the SeaWiFS and MODIS-Aqua "ocean color" datasets and binned at 0.5 x 0.5 degree latitude-longitude boxes, annual averages for each year calculated from the average of all monthly means in that year, and the annual mean was calculated as the average of all annual means.  National numbers are spatially-weighted averages. 

Source: https://www.st.nmfs.noaa.gov/copepod/about/about-copepod.html.

 

Zooplankton

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Graph of nationwide zooplankton biomass, 1980-2020

Description of time series:

Between 2011 and 2015 the national average concentration of zooplankton biomass showed a significant upward trend.

 

Description of gauge:

The gauge value of 79 indicates that between 2011 and 2015 the average concentration of zooplankton biomass in the four US regions with data (Alaska, the California Current, the Gulf of Mexico, and the Northeast) was much higher than the median value of all zooplankton biomass concentration levels from 1986 through 2015.

 

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 and Northeast regions.

 

Overall Scores mean the following:

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.

 

Data:

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. National numbers are spatially-weighted averages. 

Source: https://www.st.nmfs.noaa.gov/copepod/about/about-copepod.html

 

Overfished stocks

Graph of number of overfished stocks, 1980-2020

Description of time series:

Between 2015 and 2019 the number of overfished stocks showed a significant upward trend.

 

 

Description of gauge:

The gauge value of 30 indicates that between 2015 and 2019 the average number of overfished stocks nationwide was lower than the median number of all overfished stocks between 2000 and 2019. 

 

 

Description of Overfished stocks:

Fish play an important role in marine ecosystems, supporting the ecological structure of many marine food webs. Caught by recreational and commercial fisheries, fish support significant parts of coastal economies, and can play an important cultural role in many regions.  To understand the health of fish populations - as well as their abundance and distribution, we regularly assess fish stocks - stock assessments. Assessments let us know if a stock is experiencing overfishing or if it is overfished i.e. how much catch is sustainable while maintaining a healthy stock. And, if a stock becomes depleted, stock assessments can help determine what steps may be taken to rebuild it to sustainable levels. Understanding stock assessments helps measure how well we’re managing and recovering fish stocks over time. We present the number of overfished stocks by year in all regions.

 

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.

 

Data:

Data were obtained (28 Aug 2019) from the NOAA Fisheries Fishery Stock Status website https://www.fisheries.noaa.gov/national/population-assessments/fishery-stock-status-updates. Stocks that met the criteria for overfished status were summed by year for each region.

 

 

Threatened or endangered marine mammals

Endangered Species Act threatened / endangered marine mammals

Graph of numbers of Endangered Species Act threatened marine mammals

Description of time series:

Trend analysis was not appropriate for Endangered Species Act (ESA) threatened or endangered marine mammals data.

 

Description of gauge:

The Gauge value of 50 indicates that between 2014 and 2018 the average number of ESA threatened or endangered species nation-wide is the same as the median number of all ESA threatened or endangered species between 2013 and 2018.

 

Description of Threatened and Endangered Marine mammals:

Some marine mammals face significant threats. The Endangered Species Act (ESA) aims to conserve endangered and threatened 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.  We present the annual number of threatened and endangered marine mammals in all regions except the Caribbean. Data for the Southeast and Gulf of Mexico regions are combined.

 

Overall Scores mean the following:

High values of ESA threatened and endangered species are bad, low numbers are good.

  • 0 - 10: The five-year ESA threatened or endangered marine mammals average is very low compared to the median value.
  • 10 - 25: The five-year ESA threatened or endangered marine mammals is much lower than the median value.
  • 25 - 50: The five-year ESA threatened or endangered marine mammals average is lower than the median value.
  • 50: The five-year ESA threatened or endangered marine mammals average equals the median value.
  • 50 - 75: The five-year ESA threatened or endangered marine mammals average is higher than the median value.
  • 75 - 90: The five-year ESA threatened or endangered marine mammals average is much higher than the median value.
  • 90 - 100: The five-year ESA threatened or endangered marine mammals average is very high compared to the median value.

 

Data:

Summary data tables from the NOAA Fisheries Protected Resources Species Information System were obtained from the database manager 3 April 2020. The number of ESA threatened and endangered species were summed for each region by year.

Strategic depleted marine mammals

Marine Mammal Protection Act

Graph of  numbers of MMPA strategic/depleted marine mammals

Description of time series:

Trend analysis is not appropriate for Marine Mammal Protection Act (MMPA) strategic/depleted species data.

 

Description of gauge:

The gauge value of 50 indicates that between 2013 and 2018 the average number of MMPA strategic/depleted species nation-wide was essentially the same as the median number of all MMPA strategic/depleted species between 2013 and 2018.

 

Description of marine mammals depleted stocks (MMPA):

A strategic stock is defined by the Marine Mammal Protection Act as a marine mammal stock—For which the level of direct human-caused mortality exceeds the potential biological removal level; 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 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. We present the annual number of strategic and depleted marine mammals in all regions except the Caribbean. Data for the Southeast and Gulf of Mexico regions are combined. 

 

Overall Scores mean the following:

 

  • 0 - 10: The five-year MMPA strategic and depleted marine mammals average is very low compared to the median value.
  • 10 - 25: The five-year MMPA strategic and depleted marine mammals average is much lower than the median value.
  • 25 - 50: The five-year MMPA strategic and depleted marine mammals average is lower than the median value.
  • 50: The five-year MMPA strategic and depleted marine mammals average equals the median value.
  • 50 - 75: The five-year MMPA strategic and depleted marine mammals average is higher than the median value.
  • 75 - 90: The five-year MMPA strategic and depleted marine mammals average is much higher than the median value.
  • 90 - 100: The five-year MMPA strategic and depleted marine mammals average is very high compared to the median value.

 

Data:

Data methods Summary data tables from the NOAA Fisheries Protected Resources Species Information System were obtained from the database manager 3 April 2020. The number of MMPA strategic and depleted stock species were summed for each region by year. 

 

Unusual Mortality Events

Significant die-offs in a marine mammal population

Graph of U.S. Unusual Mortality Events 1980-2020

Description of time series:

Trend analysis is not appropriate for Marine Mammal Unusual Mortality Event data.

 

Description of gauge:

The gauge value of 69 indicates that between 2015 and 2019 the average number of marine mammal unusual mortality events nation-wide was higher than the median number of all unusual mortality events between 1991 and 2019.

 

Description of Unusual Mortality events:

Marine mammals are important parts of marine ecosystems. Sometimes we observe significant die-offs in a marine mammal population - also called unusual mortality events (UMEs). A UME is defined as "a stranding that is unexpected; involves a significant die-off of any marine mammal population; and demands immediate response." UMEs are often caused by ecological factors (e.g. changes in ocean conditions or food sources), biotoxins, infectious disease, and human interactions, but in some cases the cause cannot be determined. Some unusual mortality events occur over a period of months and others last for years. Understanding and investigating marine mammal UMEs is crucial because they can be indicators of ocean health, giving insight into larger environmental issues, which may also have implications for human health. We present the number of unusual marine mammal mortality events in a given year in all the Alaska, Pacific Islands, California Current, Gulf of Mexico, Southeast, and Northeast regions.

 

Overall Scores mean the following:

High values for UME are bad, low values are good.

  • 0 - 10: The five-year UME average is very low compared to the median value.
  • 10 - 25: The five-year UME average is much lower than the median value.
  • 25 - 50: The five-year UME average is lower than the median value.
  • 50: The five-year UME average equals the median value.
  • 50 - 75: The five-year UME average is higher than the median value.
  • 75 - 90: The five-year UME average is much higher than the median value.
  • 90 - 100: The five-year UME average is very high compared to the median value.

 

Data:

Unusual mortality event (UME) data for marine mammals were accessed from the NOAA Fisheries Active and Closed Unusual Mortality Events website (https://www.fisheries.noaa.gov/national/marine-life-distress/active-and-closed-unusual-mortality-events). A value of 1 was assigned for each UME (open and closed) reported as occurring for any portion of a given year and the values were summed by year for each region. For UMEs where the date range was not indicated, a value of 1 was applied only for the year the UME was declared.

Coastal population

.

graph of coastal population 1980-2020

Description of time series:

The 2014 – 2018 national average coastal population was substantially above historic levels, although the recent trend is not different from historical trends.  

 

Description of gauge:

The 2014 – 2018 national average coastal population was greater than 94% of all population levels between 1970 to 2018, again highlighting the substantial growth in the coastal population of this region.

 

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.

 

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.

 

Data:

Coastal population data was retrieved from the Census Bureau’s county population totals, filtered to present coastal counties using the Census Bureau’s list of coastal counties within each state. Coastal county populations were then summed within each region for reporting purposes.

Coastal Tourism

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graph of nationwide coastal Gross Domestic Product growth, 1980-2020

Description of time series:

The national growth in the value of coastal tourism varies considerably across time, with no clear trend and the last 5 years of growth not different from historical patterns.  

 

Description of gauge:

The national growth in value of coastal tourism of 0.6% between 2015 and 2016 outperformed all ocean sectors, which decreased 6.7% across that same period, but lagged behind total GDP growth at 1.5%.

 

Description of Coastal Tourism:

Coastal tourism Gross Domestic Product is the total measure (in billions of dollars) of goods and services provided from tourism along the coast. U.S. coasts are host to a multitude of travel, tourism, and recreation activities. These provide social and economic benefits as well as impact the environment. As more and more communities turn to tourism for economic development, it becomes crucial to develop a sustainable tourism industry that is good for communities, the environment, and society more broadly. To accomplish this, we need data on the social and economic impacts of recreation and tourism, and its impacts on natural resources. We present the annual total change (in billions of dollars) of goods and services provided from tourism in the Gulf of Mexico, Mid-Atlantic, Northeast, Pacific Islands, Southeast, and California Current regions.

 

Extreme Gauge values:

A value of zero on the gauge means that the average coastal tourism over the last 5 years of data was below any annual coastal tourism level up until that point, while a value of 100 would indicate the average over that same period was above any annual coastal tourism level up until that point.

 

Data:

Coastal Tourism GDP data was taken from NOAA’s Office of Coastal Management Economics National Ocean Watch custom report building tool, with contextual data taken from the 2019 NOAA Report on the U.S. Ocean and Great Lakes Economy: Regional and State Profiles. Growth was estimated by subtracting the previous year’s Coastal Tourism GDP from the current year’s Coastal Tourism GDP, then dividing by the previous year’s Coastal Tourism GDP to present a percentage. All data was deflated to 2012 constant dollars using the Bureau of Economic Analysis’ chained dollar methodology.

 

Coastal Employment

graph of nationwide coastal county employment 1980-2020

Description of time series:

Across the nation, average coastal employment between 2014 and 2018 was substantially above historical levels, although no trend is apparent over that same period.  

 

Description of gauge:

The gauge value of 89 indicates that coastal employment between 2014 and 2018 for the entire US was higher than 89% of all years between 1990 and 2018.

 

Description of Coastal Employment:

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.

 

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.

Data:

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

(tonnage)

graph of nationwide commercial fishery landings 1980-2020

Description of time series:

Between 2013 and 2017, commercial landings were similar to historic levels nationally, and there is no recent trend apparent.  

 

Description of gauge:

The gauge value of 65 indicates that the mean annual commercial landings between 2013 and 2017 for the entire US was higher than 65% of all years between 1950 and 2017.

 

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. 

 

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.

Data:

Commercial landings and gross revenue were downloaded from the National Marine Fisheries Service’s annual commercial fisheries landings query tool which can be found at https://foss.nmfs.noaa.gov/apexfoss/f?p=215:200::::::. State pounds landed and revenue generated were aggregated to the appropriate region, and all revenue data was deflated to 2017 constant dollars using the Bureau of Labor Statistic’s Consumer Price Index (series CUUR0000SA0).

 

 

Commercial fishery revenue

graph of nationwide commercial fishery revenue 1980-2010

Description of time series:

Between 2013 and 2017, national average annual commercial revenue was not different than historical patterns, and there is no trend in values.  

 

Description of gauge:

The gauge value of 57 indicates that the mean annual commercial revenue between 2013 and 2017 for the entire US was higher than 57% of all years between 1950 and 2017.

 

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. 

 

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.

Data:

Commercial landings and gross revenue were downloaded from the National Marine Fisheries Service’s annual commercial fisheries landings query tool which can be found at https://foss.nmfs.noaa.gov/apexfoss/f?p=215:200::::::. State pounds landed and revenue generated were aggregated to the appropriate region, and all revenue data was deflated to 2017 constant dollars using the Bureau of Labor Statistic’s Consumer Price Index (series CUUR0000SA0).

 

 

Recreational fishing effort

graph of nationwide recreational angler days 1980-2020

Recreational landings are the number of fish caught and brought to shore on recreational fishing trips. U.S. saltwater fisheries are an important source of seafood and recreation for millions of anglers and for-hire recreational businesses, which supports millions of jobs. “Angler Trips” are the number of  trips people fish recreationally and captures the overall activity for this effort. 

Recreational landings and angler trips 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 caught and angler trips annually for all marine fish in all regions.

 

Recreational fishing harvest

graph of nationwide recreational fishing harvest 1980-2020

Recreational landings are the number of fish caught and brought to shore on recreational fishing trips. U.S. saltwater fisheries are an important source of seafood and recreation for millions of anglers and for-hire recreational businesses, which supports millions of jobs. “Angler Trips” are the number of  trips people fish recreationally and captures the overall activity for this effort. 

Recreational landings and angler trips 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 caught and angler trips annually for all marine fish in all regions.

 

Commercial fishing engagement

Nationwide commercial fishing engagement 1980-2019

Description of time series:

There is not enough data to do trend analysis. 

 

Description of gauge:

The gauge value of 25 indicates that the mean annual recreational fishing engagement between 2012 and 2016 for the entire US was higher than 25% of all years between 2009 and 2016.

 

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.

 

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.

 

Data:

Recreational and 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

Nationwide recreational fishing engagement 1980-2019

Description of time series:

There is not enough data to do trend analysis. 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.

 

 Description of gauge:

The gauge value of 38 indicates that the mean annual recreational fishing engagement between 2012 and 2016 for the entire US was higher than 38% of all years between 2009 and 2016.

 

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.

 

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.

 

Data:

Recreational and 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

Billion-dollar weather disasters affecting coastal states

graph of nationwide coastal billion-dollar storm events 1980-2019

Interpretation of time series:

Across the nation, the number of billion dollar disasters is extremely variable over time, fluctuating between zero and ten disasters a year.  The number of disasters over the past 5 years is substantially higher than historical levels of events, although there is no recent trend in the number of events.  

 

Interpretation of gauge:

The gauge value of 92 indicates that the number of billion dollar disasters between 2015 and 2019 for the US was higher than 92% of all years between 1980 and 2019.

 

 

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. 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. We Present the total annual number of disaster events for all regions.

 

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. 

 

 

Source and analysis of data:

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.