Click on the Indicators below for More Information
Northeast Region map

The Northeast region extends from Maine to Virginia encompassing the marine coastlines of 11 states. Within its bounds are the Gulf of Maine, Cape Cod Bay, as well as myriad estuarine systems including Long Island Sound, the New York Bight, the Delaware and Chesapeake Bays. Rocky shorelines, wetlands, beach/dune complexes, barrier island systems with intertidal and freshwater wetland complexes, and low lying sandy coastal plains abound in this region

Significant marine ecosystems in the region include the Gulf of Maine, Mid Atlantic Bight, and Georges Bank which support thousands of marine plant and animal species, including over 180 species of seabirds. This biological richness is supported by seasonal phytoplankton blooms and high annual primary productivity. 

Approximately 70 million people live in the Northeast, making it the most populous region in the U.S. About 82% of these people live in coastal counties which are vulnerable to storm surge, flooding, sea level rise, salt water intrusion, and changes to temperature and precipitation extremes.

The Northeast has significant coastal-dependent industries with three of the top five U.S. ports (value of fish landed) and five of the Nation’s top 20 ports (international cargo volume). Home to a highly productive fishery, this region  supports over a third of the national coastal ocean economy in commercial fishing, with important contributions from tourism, recreation, and shipping.

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.

Graph

North Atlantic Oscillation (NAO)

During the last five years, the NAO indicator shows no significant trend but has remained largely in the negative phase.

graph of the North Atlantic Oscillation index from 1980-2020

Values correspond to Index scores

Description of time series:

Positive NAO values mean significantly warmer winters over much of the eastern U.S. and northern Europe and negative NAO values can mean cold winter outbreaks and heavy snowstorms. During the last five years, the NAO indicator shows no significant trend but has remained largely in the negative phase.

 

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 much of the eastern U.S. This prevents nutrient-rich upwelling, which reduces productivity. When the NAO index is negative, the upper central and eastern portions of the United States can incur winter cold outbreaks and heavy snowstorms. 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 NCEI (https://www.NCEI.noaa.gov/teleconnections/nao). The data plotted are unitless anomalies and averaged across a given region.

Atlantic Multidecadal Oscillation index (AMO)

During the last five years, the AMO has largely been in a positive phase, and continues to trend upward.

graph of the Atlantic Multidecadal Oscillation index from 1980-2020

Values correspond to Index scores

Description of time series:

Positive AMO values indicate the warm phase, during which surface waters in the North Atlantic Ocean are warmer than average, and negative AMO values indicate the cold phase, during which surface waters in the North Atlantic Ocean are cooler than average. During the last five years, the AMO has largely been in a positive phase, and continues to trend upward.

 

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. Despite the association of AMO with multiple weather and climate impacts, recent scientific debate has questioned whether this indicator is a natural climate variation, like the other climate indicators presented here, or a response of the climate system to human-caused climate change. Whether natural or a result of human-caused climate change, AMO is a useful feature for tracking large-scale weather and climate events. 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 Background:

Climate indicator data was accessed from NOAA’s Earth Systems Research Laboratory (https://www.esrl.noaa.gov/psd/data/timeseries/AMO/). The data plotted are unitless anomalies and averaged across a given region

 

Sea Surface Temperature

During the last five years there has been a significant upward trend and values have remained within the 10th and 90th percentiles of all observed data in the time series.

NE SST

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

 

Data Interpretation:

Time series: The time series shows the integrated sea surface temperature for the Northeast US region.  During the last five years there has been a significant upward trend and values have remained within the 10th and 90th percentiles of all observed data in the time series.

 

Indicator and source information:

The SST product used for this analysis is the NOAA Coral Reef Watch CoralTemp v3.1 SST composited monthly (https://coralreefwatch.noaa.gov/product/5km/index_5km_sst.php) accessed from CoastWatch (https://oceanwatch.pifsc.noaa.gov/erddap/griddap/CRW_sst_v3_1_monthly.g…). 

Great Lakes SST data were accessed from (https://coastwatch.glerl.noaa.gov/glsea/glsea.html). 

The data are plotted in degrees Celsius. 

 

Data background and limitations:

The NOAA Coral Reef Watch (CRW) daily global 5km Sea Surface Temperature (SST) product, also known as CoralTemp, shows the nighttime ocean temperature measured at the surface. The CoralTemp SST data product was developed from two, related reanalysis (reprocessed) SST products and a near real-time SST product. Monthly composites were used for this analysis.

Sea Level

During the last five years, there has been no trend and values are greater than 90% of all observed data in the time series.

graph of coastal sea level for Northeast US from 1980-2020

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 no trend and values are greater than 90% of all observed data in the time series.

 

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.

 

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. 

Heatwave Intensity

During the last five years there has been an increasing trend and the five-year average is between the 10th and 90th percentiles of all observed data in the time series.

NE intensity

Values indicate cumulative annual heatwave intensity and duration in a region in degree-days

Description of Time Series: This time series shows the average integrated degree day value for the Northeast region. During the last five years there has been an increasing trend and the five-year average is between the 10th and 90th percentiles of all observed data in the time series.

Indicator Source Information:

The marine heatwave data shown here are calculated by NOAA’s National Centers for Environmental Information using Optimum Interpolation Sea Surface Temperature (OISST) data. The NOAA 1/4° OISST is a long term Climate Data Record that incorporates observations from different platforms (satellites, ships, buoys and Argo floats) into a regular global grid. The dataset is interpolated to fill gaps on the grid and create a spatially complete map of sea surface temperature. Satellite and ship observations are referenced to buoys to compensate for platform differences and sensor biases.

 

Data Background and Caveats:

Heatwave metrics are calculated using OISST, a product that uses some forms of interpolation to fill data gaps. Heatwaves are defined by Hobday et al., 2016 as distinct events where SST anomaly reaches the 90th percentile in a pixel for at least 5 days, separated out by 3 or more days.

Heatwave Area

During the last five years marine heatwave coverage has trended upward and the five-year average is within the 10th and 90th percentiles of all observed data in the time series.

Northeast

Values indicate monthly percent of an LME area affected by heatwave

Description of Time Series: This time series shows the monthly heatwave spatial coverage for the Northeast Region. During the last five years marine heatwave coverage has trended upward and the five-year average is within the 10th and 90th percentiles of all observed data in the time series.

Indicator Source Information:

The marine heatwave data shown here are calculated by NOAA’s National Centers for Environmental Information using Optimum Interpolation Sea Surface Temperature (OISST) data. The NOAA 1/4° OISST is a long term Climate Data Record that incorporates observations from different platforms (satellites, ships, buoys and Argo floats) into a regular global grid. The dataset is interpolated to fill gaps on the grid and create a spatially complete map of sea surface temperature. Satellite and ship observations are referenced to buoys to compensate for platform differences and sensor biases.

 

Data Background and Caveats:

Heatwave metrics are calculated using OISST, a product that uses some forms of interpolation to fill data gaps. Heatwaves are defined by Hobday et al., 2016 as distinct events where SST anomaly reaches the 90th percentile in a pixel for at least 5 days, separated out by 3 or more days

Sea Surface pCO2

Between 2016 and 2021 pCO2 showed no trend and was mostly above the range of historical values to historical values.

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The pCO2 data shown here as an ecosystem indicator of ocean acidification represent regional annual averages of these mapped estimates.

 

Description of Time Series: Between 2016 and 2021 pCO2 showed no trend and was mostly above the range of historical values to historical values. The estimated uncertainty of the pCO2 values used to compute this regional average is ±22 μatm.

 

Description of Sea Surface pCO2:

Carbon dioxide (CO2) released from fossil fuel burning and other human activities (also known as “anthropogenic CO2”) not only accumulates in Earth’s atmosphere, but is also absorbed by seawater at the ocean surface. This process represents a double-edged sword for the planet: CO2, which has negative consequences for climate change, is removed from the atmosphere but it also contributes to the acidification of ocean waters, which can harm sea life like corals and crabs. The partial pressure of CO2 in seawater (pCO2) represents the relative amount of CO2 in the water. It is a critical metric for calculating the exchange of CO2 across the air–sea interface and for tracking the effects of anthropogenic carbon on surface ocean chemistry.

 

Data Source:

Global observations of pCO2 from automated shipboard systems that take in and analyze water while a vessel is moving are aggregated in the Surface Ocean CO2 Atlas (SOCATBakker et al., 2016). These shipboard observations have been combined with data from available observational, model-based, and satellite products (e.g., sea-surface temperature, salinity, and wind speed) to create estimates of surface ocean pCO2 in U.S. Large Marine Ecosystems over multiple decades, using a technique known as machine learning (Sharp et al., in prep.). The pCO2 data shown here as an ecosystem indicator of ocean acidification represent regional annual averages of these mapped estimates. Uncertainty in pCO2 is estimated from a data-based validation of the machine-learning algorithms for each Large Marine Ecosystem, scaled by the data coverage in a given month.

Sea Surface pH

Between 2016 and 2021 pH showed no trend and was largely below the range of historical values.

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The pH data shown here as an ecosystem indicator of ocean acidification represent regional annual averages of these estimates.

 

Description of Time Series: Between 2016 and 2021 pH showed no trend and was largely below the range of historical values.

 

Description of Sea Surface pH:

Man-made (or “anthropogenic”) CO2 that is taken up by the ocean influences the chemistry of seawater, resulting in an increase in hydrogen ion concentration of the surface ocean (i.e. a decrease in surface ocean pH). pH can be viewed as a “master variable” in ocean chemistry, controlling acid-base balance in the sea. It is also a common way to quantify ocean acidification: average surface ocean pH has decreased by more than 0.1 units since the beginning of the industrial revolution (Jiang et al., 2023).

 

Data Source:



Mapped estimates of surface-ocean pCO2 in U.S. Large Marine Ecosystems (LME’s) (Sharp et al., in prep.), based on observations from the SOCAT database, have been paired with another key ocean-carbon variable called total alkalinity (TA), estimated from salinity, temperature, and spatial information using algorithms called ESPERs (Carter et al., 2021), to calculate surface ocean pH across the U.S. LME’s. The pH data shown here as an ecosystem indicator of ocean acidification represent regional annual averages of these estimates. Uncertainty in pH is determined by propagating pCO2 and TA uncertainties through calculations, using reasonable estimates of uncertainty in required chemical constants and ancillary variables.

Sea Surface Ωar

Between 2016 and 2021 Sea Surface Ωar showed no significant trend and was similar to historical values.

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The Ωar data shown here as an ecosystem indicator of ocean acidification represent regional averages of these estimates.

 

Description of Time Series: Between 2016 and 2021 Sea Surface Ωar showed no significant trend and was similar to historical values.

 

Description of Sea Surface Ωar:

Many marine animals and plants build shells or other hard parts from the minerals aragonite and calcite, which are forms of the chemical compound calcium carbonate. The chemical building blocks of these minerals are calcium and carbonate ions, which are common constituents of seawater. However, one effect of ocean acidification is to reduce the carbonate ion concentration in seawater, making it more difficult for these minerals to form. The chemical expression that describes the tendency of these minerals to form at equilibrium is called the saturation state of that mineral: higher values support mineral formation, while lower values inhibit mineral formation, or even promote the dissolution of these minerals. We present here saturation-state estimates for the mineral aragonite (Ωar), which is used by many marine organisms including corals, mollusks, and some zooplankton to create hard parts. At 20°C, saturation state of the mineral calcite is about 50% higher than aragonite (Mucci, 1983)

 

Data Source:



Mapped estimates of surface-ocean pCO2 in U.S. Large Marine Ecosystems (LME’s) (Sharp et al., in prep.), based on observations from the SOCAT database, have been paired with another key ocean-carbon variable called total alkalinity (TA), estimated from salinity, temperature, and spatial information using algorithms called ESPERs (Carter et al., 2021), to calculate surface-ocean Ωar across the U.S. LME’s. The Ωar data shown here as an ecosystem indicator of ocean acidification represent regional averages of these estimates. Uncertainty in Ωar is determined by propagating pCO2 and TA uncertainties through calculations, using reasonable estimates of uncertainty in required chemical constants and ancillary variables.

Chlorophyll-a

During the last five years there has been no significant trend and values are generally within the 10th and 90th percentiles of all observed data in the time series.

graph of chlorophyll A for the Northeast US region from 1980-2020

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.

 

Data Interpretation:

Time series: This time series shows the average concentration levels of chlorophyll a for the  Northeast U.S. region. During the last five years there has been no significant trend and values are generally within the 10th and 90th percentiles of all observed data in the time series.

 

Indicator and source information:

Chlorophyll-a concentration values for this indicator were obtained using data from the European Spatial Agency (ESA) that is a validated, error-characterized, Essential Climate Variable (ECV) and climate data record (CDR) from satellite observations specifically developed for climate studies. The dataset (v56.0) is created by bandshifting the reflectances values from SeaWiFS, MODIS and VIIRS to MERIS wavebands if necessary, and SeaWiFS and MODIS were corrected for inter-sensor bias when compared with MERIS in the 2003-2007 period. VIIRS and OLCI were also corrected to MERIS levels, via a two-stage process comparing against the MODIS-corrected-to-MERIS-levels (2012-2013 for VIIRS and 2016-2019 for OLCI).

 

Source: https://climate.esa.int/en/projects/ocean-colour/key-documents/

https://climate.esa.int/en/projects/ocean-colour/news-and-events/news/ocean-colour-version-50-data-release/

https://docs.pml.space/share/s/fzNSPb4aQaSDvO7xBNOCIw

Annual means for each LME were calculated from the average of the 12 monthly means in that year on a pixel by pixel basis. Then for each year, the median average was taken spatially to yield one value per year per LME.  The overall “National Annual Mean” mean was calculated as the average of all LME annual means. See the Data Background section for more details.  

 

Data background and limitations:

Satellite chlorophyll a data was extracted for each LME from the ESA OC-CCI v6.0 product. These 4 km mapped, monthly composited data were - averaged over each year to produce pixel by pixel annual composites, then the spatial median was calculated  for each LME, resulting in one value per year per LME.   This technique was used for each LME from North America and Hawaii.  The overall “National Annual Mean” was calculated as the average of all the LME annual means. Phytoplankton concentrations are highly variable (spatially and temporally), largely driven by changing oceanographic conditions and seasonal variability.

Zooplankton

Between 2016 and 2021 the average concentration of zooplankton biomass showed a significant downward trend but was similar to historical values.

 graph of billion-dollar storm events for the Northeast US region from 1980-2020

Description of time series:

Between 2016 and 2021 the average concentration of zooplankton biomass showed a significant downward trend but was similar to historical values.

 

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. Gulf of Mexico specific data comes from the Southeast Area Monitoring and Assessment Program (SEAMAP): https://www.gsmfc.org/seamap.php. The SEAMAP data were calculated and provided by David Hanisko.

 

Data Background and Caveats:

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

Between 2017 and 2022 the spring biomass of planktivores in the Northeast was greater than the median value of all spring planktivore biomass between 1978 and 2022.

graph of planktivore biomass for the Northeast region from 1980-2020

Values correspond to forage biomass observed per tow in kg

 

Description of time series:

Between 2018 and 2022 the biomass of spring planktivore forage fish showed a significant trend upward but values remain within the 10th and 90th percentile. 

 

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 is produced by the Northeast Integrated Ecosystem Assessment team and represents Spring Planktivore biomass in kg^tow -1.

 

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.

No Caveats.

Seabirds

The Northeast Count per Mile of Seabirds over the last 5 years was similar to historical values and showed no trend.

graph of seabirds for the Northeast region from 1980-2020

Values indicate estimated seabird abundance based off of the number of seabirds identified by kilometer on Atlantic Marine Assessment Program for Protected Species research cruises

 

Description of the Time Series

The Northeast Count per Mile of Seabirds over the last 5 years was similar to historical values and showed no trend.

 

Indicator and source information:

Seabird count and transect length data for the Northeast are extracted from the Atlantic Marine Assessment Program for Protected Species (AMAPPS) annual reports. Counts for all seabirds observed are summed and divided by the sum of the transect length in nautical miles.

 

Overfished Stocks

The series shows the number of fish populations that have been listed as overfished since 2000. Between 2018 and 2023 the number of overfished stocks shows no trend.

graph of number of overfished stocks in the Northeast US region from 1980-2019

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 cannot support a large amount of fishing.

 

Description of time series:

The series shows the number of fish populations that have been listed as overfished since 2000. Between 2018 and 2023 the number of overfished stocks shows no trend.

 

Description of Overfished stocks:

An overfished stock is a population of fish that is too low. A stock that is experiencing overfishing has an annual rate of catch that is too high. Therefore the population cannot support that level of fishing and is below that level is deemed “overfished.” A fish population can be “overfished” as the result of many factors, including overfishing, as well as habitat degradation, pollution, climate change, and disease. The Magnuson-Stevens Act mandates that overfished stocks and stocks experiencing overfishing be reported annually.   Stock status is determined by NOAA, based on the results of stock assessments. 

 

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.

 

Endangered Species Act Threatened or Endangered Marine Mammals

Gauge and Trend Analyses were not appropriate for marine mammal data.

graph of ESA threatened species numbers for Northeast US region from 1980-2020

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.

 

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.

 

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.

Marine Mammal Protection Act Strategic/Depleted Marine Mammal Stocks

Gauge and Trend Analyses were not appropriate for marine mammal data.

graph of MMPA strategic & depleted stocks for the Northeast region from 1980-2020

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.

 

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. 

 

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.

Marine Species Distribution - Latitude

Between 2017 and 2022 the average species latitudinal shift showed an increasing trend and is above historical averages, indicating a northward shift in distributions.

NE MSD LAT

Values indicate annual cumulative change in centroid across all species in a region in degrees N

 

Description of Time Series: Between 2017 and 2022 the average species latitudinal shift showed an increasing trend and is above historical averages, indicating a northward shift in distributions.

 

Indicator Source Information:

This data was obtained from the Distribution Mapping and Analysis Portal (DisMAP). provides important information for fisheries management including which species are caught where and at what depth. The latitudinal (or depth) centroid is the biomass-weighted center of a population’s distribution. This metric is calculated by the DisMAP portal team using the interpolated biomass distribution surface they generated from the survey catch data, such that the latitudinal (or depth) centroids are the mean latitude (or depth) of the species distribution, where each raster cell latitude (or depth) is weighted by the value of weight-per-unit-effort for that cell. Scientists at NOAA 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. This data provides important information for fisheries management including which species are caught where and at what depth.

 

Data Background and Caveats:

The regional and national marine species distributions shown here represent the average shift in the centroid of a selected core set of species that are caught every year 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 - Depth

Between 2017 and 2022 the average species water column depth shift shows a significant downward trend, indicating the distribution moved deeper.

NE MSD Depth

Values Indicate annual cumulative change in average species centroid depth in meters - for example, a value of -5 indicates the species centroid moving deeper by 5m.

 

Description of Time Series: Between 2017 and 2022 the average species water column depth shift shows a significant downward trend, indicating the distribution moved deeper.

 

Indicator Source Information:

This data was obtained from the Distribution Mapping and Analysis Portal (DisMAP). The latitudinal (or depth) centroid is the biomass-weighted center of a population’s distribution. This metric is calculated by the DisMAP portal team using the interpolated biomass distribution surface they generated from the survey catch data, such that the latitudinal (or depth) centroids are the mean latitude (or depth) of the species distribution, where each raster cell latitude (or depth) is weighted by the value of weight-per-unit-effort for that cell. 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. This data provides important information for fisheries management including which species are caught where and at what depth.

 

Data Background and Caveats:

The regional and national marine species distributions shown here represent the average centroid of a selected core set of species that are caught every year of the surveys in a 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.

Ecosystem Overfishing

Between 2016 and 2021, average annual Ryther Index values from the Northeast were substantially lower than historical patterns, although there is no trend in values.

NE Ryther

Values correspond to Ryther Index values

 

Data Interpretation:

Ecosystem Overfishing Time Series

Between 2016 and 2021, average annual Ryther Index values from the Northeast were substantially lower than historical patterns, although there is no trend in values.

 

Indicator Source Information:

Landings are reported in tons 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 weight 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 used in the compilation of this indicator only include non-confidential data. 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 here 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, which would be minimal given the aggregated nature of how these data were combined.

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, as associated with major regions in the US

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.

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. 

Ecosystem overfishing metrics also have potential thresholds, usually for the Ryther Index of approximately 1; but we do not report Ryther index values here relative to any threshold.  Rather, we report the value of the indices for each region relative to their time series values.  Comparison to some regional reports may slightly differ due to the inclusion or exclusion of specific species, but the same general trends are observed and align.

Coastal Population

The 2017 – 2022 average coastal population in the Northeast was substantially above historic levels, although the recent trend is not different from historical trends.

graph of coastal population for the Northeast US region from 1980-2020

Values correspond to the total coastal population for a given region

 

Time Series

The 2017 – 2022 average coastal population in the Northeast was substantially above historic levels, although the recent trend is not different from historical trends.

 

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. 

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

Between 2015 and 2020 the average change in coastal county tourism GDP showed a significant decreasing trend.

graph of coastal GDP for the Northeast US region from 1980-2020

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 2015 and 2020 the average change in coastal county tourism GDP showed a significant decreasing trend.

 

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

Between 2015 and 2020 the average change in coastal county employment showed a significant decreasing trend.

NE EMp Tour

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 2015 and 2020 the average change in coastal county employment showed a significant decreasing trend.

 

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

Between 2015 and 2020 the average change in coastal county real wage compensation showed a significant decreasing trend.

NE Tour Wage

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 2015 and 2020 the average change in coastal county real wage compensation showed a significant decreasing trend.

 

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.

Coastal Employment

Average coastal employment within the Northeast between 2014 and 2019 was similar to historical levels, and an increasing trend is apparent over that same period.

graph of coastal employment for the Northeast US region from 1980-2020

Values correspond to total employment in all industries in the coastal counties of a given region

 

Time Series

Average coastal employment within the Northeast between 2014 and 2019 was similar to historical levels, and an increasing trend is apparent over that same period.

 

 

Data Source:

Coastal employment numbers were downloaded from the NOAA ENOW Explorer Tool, filtered to present only coastal county values using the Census Bureau’s list of coastal counties within each state. ENOW Explorer streamlines the task of obtaining and comparing economic data, both county and state, for the six sectors dependent on the ocean and Great Lakes: living resources, marine construction, marine transportation, offshore mineral resources, ship and boat building, and tourism and recreation. Data are derived from Economics: National Ocean Watch (ENOW), available on NOAA’s Digital Coast. 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

Between 2017 and 2022, commercial landings from the Northeast were substantially below historic levels, although there is no recent trend apparent.  

graph of commercial fishery landings for the Northeast US region from 1980-2020

Values correspond to landings in millions of metric tons

 

Commercial Landings Time Series

Between 2017 and 2022, commercial landings from the Northeast were substantially below historic levels, although there is no recent trend apparent.  

 

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 Fishing Revenue

Between 2017 and 2022, average annual commercial revenue from the Northeast was higher than  historical patterns, and there is no trend in values.

graph of commercial fishing revenue for the Northeast US region from 1980-2020

Values correspond to real revenue is 2022 US Dollars

 

Commercial Revenue Time Series

Between 2017 and 2022, average annual commercial revenue from the Northeast was higher than  historical patterns, and there is no trend in values.

 

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

Between 2017 and 2022, recreational fishing effort in the Northeast is around historic levels and shows no trend. 

graph of recreational fishing effort for the Northeast US region from 1980-2020

Values correspond to cumulative number of angler trips

 

Description of time series:

Between 2017 and 2022, recreational fishing effort in the Northeast is around historic levels and shows no trend. 

 

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

Between 2017 and 2022, recreational harvest from Northeast are around historic levels. There is no significant trend apparent. 

graph of recreational fishing effort for the Northeast US region from 1980-2020

Values correspond to harvest in millions of fish

 

Description of time series:

Between 2017 and 2022, recreational harvest from Northeast are around historic levels. There is no significant trend apparent. 

 

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

Between 2015 and 2020 the percent of communities moderately or highly engaged in commercial fishing showed a downward trend, with the 2020 level near the series low.

Graph of commercial fishing engagement index in the Northeast US region from 2009-2016

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 Northeast. Commercial fishing engagement is measured by the number permits, fish dealers, and vessel landings across the Northeast. 

 

Description of time series:

This time series shows the percent of communities moderately or highly engaged in commercial fishing in the Northeast from 2009 to 2020. Between 2015 and 2020 the percent of communities moderately or highly engaged in commercial fishing showed a downward trend, with the 2020 level near the series low.

 

Description of Northeast Commercial Fishing Engagement:

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. 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-indicator….

 

NOAA Monitors 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 Hawaiian 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

Between 2015 and 2020 (highlighted in green) the percent of communities moderately or highly engaged in recreational fishing showed no significant trend.

Graph of recreational fishing engagement index in the Northeast US region from 2009-2016

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 the Northeast.

 

Recreational Engagement Time Series

This time series shows the percent of communities moderately to highly engaged in recreational fishing in the Northeast US from 2009 to 2020. Between 2015 and 2020 (highlighted in green) the percent of communities moderately or highly engaged in recreational fishing showed no significant trend.

 

 

Indicator Source Information:

The Northeast recreational engagement indicator is measured using shore, private vessel and for-hire vessel fishing activity estimates.

 

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

Beach Closures

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.

graph of EPA-mandated beach closures for the Gulf of Mexico region from 1980-2020

Beach closures are the number of days when beach water quality is determined to be unsafe.

 

Data Interpretation:

Time series: This time series shows the average number of beach closure days in the Northeast US region from 2000 to 2022. 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.

 

Indicator and source information:

Unsafe water quality may have significant impacts on human health, local economies, and the ecosystem. Beach water quality is determined by the concentration of bacteria in the water (either Enterococcus sp. or Escherichia coli). 

 

The US Environmental Protection Agency (EPA) supports coastal states, counties and tribes in monitoring beach water quality, and notifying the public when beaches must be closed. The information presented is from states, counties, and tribes that submit data to the EPA Beach Program reporting database (BEACON). Data obtained from the EPA BEACON 2.0 website have been provided to EPA by the coastal and Great Lakes states, tribes and territories that receive grants under the BEACH Act. Data were refined to closure, by state or territory, by year.

 

Data background and limitations:

Data compiled by states or territories are combined in regions defined as US Large Marine Ecosystems (LME). Changes in the number of beach closure days may be driven by changes in the number of beaches monitored under the BEACH Act versus by state and local municipalities and not by changes in water and/or air quality. Not all US beach closures are captured in this database, because not all beaches in a state or territory are monitored through the EPA BEACH Act. Data that were not identified to a water body or identified as inland water were not included. Data for beaches monitored by state and local municipalities are not included. 

Data from 2020 may be inflated by the Covid-19 pandemic, as there was no consistent way for states to report pandemic-related closures.

Billion-Dollar Disasters

The number of disasters over the past 5 years is substantially higher than historical levels of events, but there is no trend in the number of events.

graph of billion-dollar storm events for the Northeast US region from 1980-2020

Values correspond to the number of events in a given year

 

Time Series

The number of billion dollar disasters within the Northeast is variable over time.  The number of disasters over the past 5 years is substantially higher than historical levels of events, but there is no trend in the number of events.

 

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.

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.

Resources

Northeast IEA Indicator data

The Northeast Integrated Ecosystem Assessment (IEA) provides a framework that brings social and ecological science and management advice to managers in a manner that is useful under current governance structures while supporting the adoption of Ecosystem-Based Management.

The NOAA Integrated Ecosystem Assessment Logo

Stellwagen Bank National Marine Sanctuary Condition Report

The purpose of a condition report is to use the best available science and most recent data to assess the status and trends of various parts of the sanctuary’s ecosystem.

The National Marine Sanctuary System Logo

Northeast Ocean Data

The Northeast Ocean Data Portal is a centralized, peer-reviewed source of data and interactive maps of the ocean ecosystem and ocean-related human activities in the northeastern United States. 

The Northeast Ocean Data Logo

Integrated Sentinel Monitoring Network (ISMN)

The Integrated Sentinel Monitoring Network for Change in Northeast U.S. Ocean and Coastal Ecosystems (ISMN) initiative is a joint project of NERACOOS and NROC (Northeast Regional Ocean Council), which was established based on a pressing regional need to establish an integrated network to observe and interpret changes in the ecosystem (Runge, et. al 2012). 

The ISMN Logo

Northeastern Regional Association of Coastal Ocean Observing Systems (NERACOOS)

The Northeastern Regional Association of Coastal Ocean Observing Systems (NERACOOS) spans coastal waters from the Canadian Maritime Provinces to the New York Bight. 

The NERACOOS Logo

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.

Mid-Atlantic Ocean Data Portal

The Mid-Atlantic Ocean Data Portal is an online toolkit and resource center that consolidates available data and enables state, federal and local users to visualize and analyze ocean resources and human use information such as fishing grounds, recreational areas, shipping lanes, habitat areas, and energy sites, among others.

The Mid Atlantic Ocean Data Portal Logo

Mid-Atlantic Regional Association Coastal Ocean Observing System (MARACOOS)

MARACOOS is a regional association of partners that collect unique ocean and coastal data that is transformed into information products that support jobs, the economy, safety and well-being for the more than 78 million people living, visiting, and working in the Mid-Atlantic region.

The MARACOOS Logo

Gulf of Maine Marine Biodiversity Observation Network

The Gulf of Maine (GoM) lies at the epicenter of the most rapid warming trend in U.S. coastal waters. The GoM ecosystem supports the most valuable U.S. fishery (lobster) and the most valuable U.S. fishing seaport (New Bedford). Evidence is mounting that recent warming is affecting ecosystem structure and services, for example, closure of the northern shrimp fishery, impacts on Atlantic cod recovery, and recovery of endangered North Atlantic right whales.

The MBON Logo

Gulf of Maine Harmful Algal Bloom Forecast

Annual Alexandrium catenella blooms in the Gulf of Maine produce potent neurotoxins that accumulate in shellfish and cause Paralytic Shellfish Poisoning (PSP) in human consumers. These models have been developed to better predict and monitor these blooms and shellfish toxicity with the goal to minimize impacts to public health and coastal economies.

NOAA logo with National Centers for Coastal and Ocean Science

Choptank River Complex Habitat Focus Area

The Choptank River complex is located on Maryland’s Eastern Shore and includes the Choptank River and its major tributaries. This treasured part of the Chesapeake Bay ecosystem represents critical habitat for spawning striped bass and river herring, as well as historically abundant oyster reefs. Residents of the watershed—including many families who have lived there for multiple generations—have traditionally been employed in agriculture or commercial fishing. Recreational fishing, hunting, and boating attract millions of people each year and contribute significantly to the region’s economy.

Choptank

Penobscot River Habitat Focus Area

The Penobscot River is New England’s second largest river, draining nearly one-third of the State of Maine with a watershed area of 8,570 square miles. The Penobscot River is used as a spawning or nursery area by 11 migratory fish species, including three listed under the Endangered Species Act. The river hosts the largest run of Atlantic salmon left in the United States. Historically, fisheries on the Penobscot River were bountiful, with an estimated 14 to 20 million alewives, 75,000 to 100,000 Atlantic salmon, and 3 to 5 million American shad.

Penobscot

NOAA Digital Coast

The Digital Coast was developed to meet the unique needs of the coastal management community. The website provides not only coastal data, but also the tools, training, and information needed to make these data truly useful. Content comes from many sources, all of which are vetted by NOAA.

Data sets range from economic data to satellite imagery. The site contains visualization tools, predictive tools, and tools that make data easier to find and use. Training courses are available online or can be brought to the user’s location. Information is also organized by focus area or topic.

NOAA North Atlantic Region

NOAA’s North Atlantic Regional Collaboration Team currently focuses on two topical areas: Climate & Watersheds and Coastal & Ocean Uses. This includes NOAA collaboration on habitat restoration, working waterfronts, offshore wind, and aquaculture, as well as climate and ecosystem monitoring and community resilience. Engagement and a functional focus on diversity, equity and inclusion round out our current priorities. 

NOAA Logo

DisMAP

DisMAP provides access to distribution information for more than 800 marine species caught in NOAA Fisheries bottom trawl surveys in five regions in the United States (Northeast, Southeast, Gulf of Mexico, West Coast, and Alaska). In this first version of the portal all species distribution products are derived from NOAA Fisheries regional bottom trawl survey data. They do not take into account alternative sources of fisheries data such as long-line, plankton, video, or fishery-dependent surveys. Because of this, distribution products are not available for the Pacific Islands or Caribbean regions at this time as those regions do not have bottom-trawl surveys; however incorporating these additional data sources is an area of interest for future releases.

DisMAP