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Description: This dataset locates regional ecosystem restoration projects that, when implemented, will improve ocean health in New England (Maine, New Hampshire, Massachusetts, Rhode Island and Connecticut). The dataset was developed and is maintained by the Northeast Regional Planning Body Restoration Subcommittee. It only includes those projects that are not fully funded and therefore represent an opportunity to invest in ocean health. A majority of these projects are eligible for federal funding and are seeking the non-federal cost sharing match. A point has been placed at the approximate location of the restoration project. See process steps for more information on how site locations were mapped for each project. Any parties interested in funding the non-federal portion of a project can contact BillHubbard@CoastalAmericaFoundation.org or the appropriate state subcommittee representative for additional information.

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• Sea Scallops Average Abundance (SMAST)
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Layer: Groundfish and Shellfish EFH Overlay (2)

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Description: This layer is an aggregation of Essential Fish Habitat (EFH) datasets for all 39 species under federal management in the Mid-Atlantic amd Northeas using source data from 2009. EFH is defined as those waters and substrate necessary to fish for spawning, breeding, feeding, or growth to maturity. This layer represents an overlay of EFH polygons for numerous species, including American Plaice, Atlantic Cod, Atlantic Halibut, Atlantic Herring, Atlantic Sea Scallop, Atlantic Wolffish, Barndoor Skate, Black Sea Bass, Bluefish, Butterfish, Clearnose Skate, Haddock, Little Skate, Longfin Inshore Squid, Mackerel, Monkfish, Northern Shortfin Squid, Ocean Pout, Offshore Hake, Pollock, Quahog, Redfish, Red Crab, Red Hake, Rosette Skate, Scup, Silver Hake, Smooth Skate, Spiny Dogfish, Surfclam, Summer Flounder, Tilefish, Thorny Skate, White Hake, Windowpane Flounder, Winter Flounder, Winter Skate, Witch Flounder, and Yellowtail Flounder. This layer was developed for general visualization and informational purposes only and does not necessarily represent the most important habitats. The Nature Conservancy obtained individual EFH layers from NOAA. The data presented here do not represent EFH for individual species but rather the number of overlapping EFH in any given location.

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Layer: Highly Migratory Species EFH Overlay (3)

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Description: This layer shows an aggregation of multiple Essential Fish Habitat (EFH) datasets for Highly Migratory Species along the Atlantic coast and in the Gulf of Mexico. EFH is defined as those waters and substrate necessary to fish for spawning, breeding, feeding, or growth to maturity. This layer represents an overlay of EFH polygons for 42 species, including Albacore Tuna, Angel Shark, Atlantic Sharpnose Shark, Basking Shark, Bigeye Thresher Shark, Bigeye Tuna, Bignose Shark, Blacknose Shark, Blacktip Shark, Bluefin Tuna, Blue Marlin, Blue Shark, Bonnethead Shark, Bull Shark, Caribbean Reef Shark, Common Thresher Shark, Dusky Shark, Finetooth Shark, Great Hammerhead Shark, Lemon Shark, Longbill Spearfish, Longfin Mako Shark, Night Shark, Nurse Shark, Oceanic Whitetip Shark, Porbeagle Roundscale Spearfish, Shark, Sailfish, Sandbar Shark, Sand Tiger Shark, Scalloped Hammerhead Shark, Shortfin Mako Shark, Silky Shark, Skipjack Tuna, Smooth Dogfish, Spinner Shark, Swordfish, Tiger Shark, Whale Shark, White Marlin, White Shark, and Yellowfin Tuna. This layer was developed for general visualization and informational purposes only and does not necessarily represent the most important habitats. Additionally, only certain species were included in this analysis; included species are those under Federal management for which spatial data exists. The data presented here do not represent EFH for individual species but rather the number of overlapping EFH in any given location.

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Layer: Sea Scallops Biomass, meat weight in kg (NEFSC) - Draft (4)

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Layer: Sea Scallops Biomass, meat weight in kg (NEFSC) - Draft (5)

Parent Layer: Sea Scallops Biomass, meat weight in kg (NEFSC) - Draft

Name: Sea Scallops Biomass, meat weight in kg (NEFSC) - Draft

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Description: This layer displays scallop biomass (meat weights in kilograms) from all NOAA Northeast Fisheries Science Center NEFSC scallop dredge surveys from 1966 to 2014. The NEFSC scallop survey program began in 1960 and had a major gear change in 1979. Since 1979 there have been other gear and vessel changes, for which the effects are generally small. In cases where it was deemed appropriate after study, correction factors have been applied to the data. These data are used to help assess the stock of scallops in the North Atlantic. <p> Other data that are collected during NEFSC scallop dredge surveys (but that are not shown here) include scallop shell heights, the number and height of dead scallop shells, any finfish, cephalopods and lobsters caught during the survey, as well as the presence/absence of other bivalve species (e.g., ocean quahogs, razor clams) and invertebrate species (e.g., sand dollars, anemones).

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Layer: usSEABED Data Quality (23)

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Description: This dataset is intended to be a companion layer to the U.S. Geological Survey (USGS) Data Series usSEABED Atlantic Coast Offshore Surficial Sediment extracted data for the entire U.S. Atlantic Coast. The usSEABED Extracted Data for the Entire U.S. Atlantic Coast depicts the point locations of known sediment samplings, inspections and probings from the usSEABED data collection which were integrated using the software system dbSEABED. These point locations were extracted from the database through data mining. The resulting dataset contains information on samples from 58 individual datasets collected by the USGS and other research projects, and includes data processed by the USGS sediment laboratory, in addition to datasets compiled from gray literature or unpublished sources. More information on this dataset can be found in the </SPAN></SPAN><A href="http://pubs.usgs.gov/ds/2005/118/htmldocs/data_cata.htm"><SPAN><SPAN>metadata document</SPAN></SPAN></A><SPAN><SPAN>. </SPAN></SPAN<SPAN><SPAN> <P>The data quality index is informed by a methodology developed and employed by the Massachusetts Division of Marine Fisheries (Ford &amp; Voss 2010) and the Massachusetts Office of Coastal Zone Management (Sampson &amp; Huntley 2015) and which assigns data quality values to variables including the age of the sample, the sampling device, and the analytical technique used.

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Spatial Reference: 102100  (3857)



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Layer: Sediment Stability (24)

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Description: This data product shows sediment stability from the southern Mid-Atlantic to the USA-Canadian border on eastern Georges Bank. Values from 0 to 1 are considered "Stable" sediments and colored in shades of blue. Values above 1 are considered "Unstable" sediments and colored in yellow-to-red gradient. This layer was created with substrate information collected by the University of Massachusetts Dartmouth School of Marine Science and Technology (SMAST) video survey from 1999 through 2012 and shear stress estimates from the Northeast Coastal Ocean Forecast System, which is a part of the Finite-Volume Community Ocean Model. Output cell size is 1-km.

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Copyright Text: University of Massachusetts Dartmouth School of Marine Science and Technology (SMAST), The Nature Conservancy (TNC).

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Layer: Soft Sediments (by grain size) (25)

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Description: This layer classifies soft-sediments based on their grain size. Source data include USGS usSeabed: Atlantic coast offshore surficial sediment data (Data series 118, version 1.0) and the USGS East Coast Sediment Texture Database (2005), Woods Hole Coastal and Marine Science Center. Point-based data were interpolated using krigging tools to create this layer. Resulting values were classified based on grain-size according to the Wentworth (1922) scale. This classification process resulted in the following classes: clay (&lt; 0.002 mmm), silt (0.024 – 0.06), very fine sand (0.06 – 0.125 mm), fine sand (0.125 – 0.25 mm), medium sand (0.25 – 0.5 mm), coarse sand (0.5 – 1.0 mm), very coarse sand (1 – 2 mm), and Gravel/granule (&gt; 2 mm). Finally, point data was interpolated using kriging to create the resulting raster layer. The spatial resolution of this layer is 500 meters.

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Copyright Text: Anderson, M. G., Greene, J., Morse, D., Shumway, D. and Clark, M (2010) Benthic Habitats of the Northwest Atlantic in Greene, J.K., M.G. Anderson, J. Odell, and N. Steinberg, eds. The Northwest Atlantic Marine Ecoregional Assessment: Species, Habitats and Ecosystems. Phase One. The Nature Conservancy, Eastern U.S. Division, Boston, MA.

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Layer: Surface Temperature (C) (26)

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Description: This is a climatological product based on the unstructured Finite Volume Coastal Ocean Model (FVCOM), developed by the Marine Ecosystem Dynamics Modeling Laboratory at the University of Massachusetts-Dartmouth and the Woods Hole Oceanographic Institute. <p>A climatology is a long term average of a given environmental variable over a certain time range. This layer shows the annual average surface temperature from 1978 to 2013, which comprises 36 years for which FVCOM hindcast data are available.

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Copyright Text: University of Massachusetts-Dartmouth School for Marine Science and Technology (SMAST), Woods Hole Oceanographic Institution (WHOI), RPS Applied Science Associates (RPS ASA)

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Layer: Bottom Temperature (C) (27)

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Description: This is a climatological toloical product based on the unstructured Finite Volume Coastal Ocean Model (FVCOM), developed by the Marine Ecosystem Dynamics Modeling Laboratory at the University of Massachusetts-Dartmouth and the Woods Hole Oceanographic Institute. <p>A climatology is a long term average of a given environmental variable over a certain time range. This layer shows the annual average bottom temperature from 1978 to 2013, which comprises 36 years for which FVCOM hindcast data are available.

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Copyright Text: University of Massachusetts-Dartmouth School for Marine Science and Technology (SMAST), Woods Hole Oceanographic Institution (WHOI), RPS Applied Science Associates (RPS ASA)

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Layer: Stratification (σT/m) (28)

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Description: This is a climatological product based on the unstructured Finite Volume Coastal Ocean Model (FVCOM), developed by the Marine Ecosystem Dynamics Modeling Laboratory at the University of Massachusetts-Dartmouth and the Woods Hole Oceanographic Institute. <p>A climatology is a long term average of a given environmental variable over a certain time range. This layer shows the annual average stratification from 1978 to 2013, which comprises 36 years for which FVCOM hindcast data are available. Mean and standard deviation of density at surface minus the density at 20 meters (or bottom, whichever is shallower), divided by the difference in depth between the two observations.

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Copyright Text: University of Massachusetts-Dartmouth School for Marine Science and Technology (SMAST), Woods Hole Oceanographic Institution (WHOI), RPS Applied Science Associates (RPS ASA)

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Layer: Biological Habitat (29)

Sub Layers:
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• Historical Eelgrass Extent
• Shellfish Habitat
• Coastal Wetlands
• Primary Production
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• Chlorophyll-a Spring (median)
• Chlorophyll-a Summer (median)
• Chlorophyll-a Fall (median)
• Calanus finmarchicus, Spring
• Calanus finmarchicus, Fall
• Euphausiids, Fall
• Euphausiids, Spring
• Gammarid amphipods, Fall
• Gammarid amphipods, Spring
• Mysid shrimp, Fall
• Mysid shrimp, Spring
• Moon Snail Average Abundance
• Hermit Crab Average Abundance
• Seastar Average Abundance
• Bryozoans or Hydrozoans Average percent of samples
• Sand Dollars Average percent of samples
• Sponges Average percent of samples
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Layer: Eelgrass Meadows (30)

Parent Layer: Biological Habitat

Name: Eelgrass Meadows

Display Field: state

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Description: Eelgrass (Zostera marina) meadows are critical wetlands components of shallow coastal ecosystems throughout the region. Eelgrass meadows provide food and cover for a great variety of commercially and recreationally important fauna and their prey. Eelgrass and other seagrasses are often referred to as "Submerged Aquatic Vegetation" or SAV. This distinguishes them from algae, which are not classified as "plants" by biologists (rather they are often placed in the kingdom protista), and distinguishes them from the "emergent" saltwater plants found in salt marshes. In addition to the term SAV, some coastal managers use the term SRV or submerged rooted vegetation. The Eelgrass Meadows layer was created from several separate datasets for the states of Maine, New Hampshire, Massachusetts, Rhode Island, Connecticut, and New York. Where possible, polygon datasets depicting the most recent eelgrass surveys were used. Attributes with common themes for each dataset were integrated in order to better represent eelgrass density and year sampled. The data user is encouraged to read this and the metadata of each individual state’s data carefully, as geometry, attribute details, and timeliness are not necessarily consistent among datasets used to develop this layer. Details of each state’s data source are described in the data processing section of the metadata. Note that the eelgrass distribution data is presence-only. Because surveys of eelgrass do not encompass all coastal waters, absence of eelgrass in a particular place on the map does not necessarily mean that eelgrass does not live at that location.

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Copyright Text: This data was compiled by the Northeast Ocean Data Portal using datasets from the Maine Departments of Marine Resources and Environmental Protection, University of New Hampshire, New Hampshire Department of Environmental Services, Piscataqua Region Estuary Partnership, NH GRANIT (New Hampshire Geographically Referenced Analysis and Information Transfer System), Massachusetts Department of Environmental Protection, Massachusetts Division of Marine Fisheries, MassGIS, Rhode Island Eelgrass Task Force, RIGIS, Connecticut Department of Energy and Environmental Protection, Peconic Estuary Partnership, and New York Natural Heritage Program, New York State Department of Environmental Conservation

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Layer: Historical Eelgrass Extent (79)

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Description: The purpose of mapping historical eelgrass extent is to create a reference layer depicting areas where eelgrass was present in the past and/or could be present again in the future throughout coastal New England waters. The historical eelgrass extent layer was created from several separate datasets for the states of Maine, New Hampshire, Massachusetts, Rhode Island, Connecticut, and New York. Datasets that were included in the historical layer were derived from quantitative surveys such as aerial photography and/or field verification. The range of historical data available varied greatly by state. The data user is encouraged to read this and the metadata of each individual state’s data carefully, as geometry, attribute details, and timeliness are not necessarily consistent among datasets used to develop this layer. All of the datasets used to develop the historical eelgrass extent layer are available separately for download at <a href="https://www.northeastoceandata.org/eelgrass/" target="_blank">https://www.northeastoceandata.org/eelgrass/</a>. <br/> <ul> <li><b>Maine:</b> 1997, 2001-2010, 2013, 2018</li> <li><b>New Hampshire:</b> 1981, 1986-2017, 2019</li> <li><b>Massachusetts:</b> 1995, 2001, 2006-2007, 2010-2013, 2015-2017, 2019</li> <li><b>Rhode Island:</b> 1988, 1996, 2000, 2006, 2009, 2012, 2016</li> <li><b>Connecticut:</b> 1974-1996, 2002, 2006, 2009, 2012, 2017</li> <li><b>New York:</b> 1930, 2000, 2003-2014</li></ul>

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Copyright Text: This data was compiled by the Northeast Ocean Data Portal using historical datasets from the Maine Departments of Marine Resources and Environmental Protection, University of New Hampshire, New Hampshire Department of Environmental Services, Piscataqua Region Estuary Partnership, NH GRANIT (New Hampshire Geographically Referenced Analysis and Information Transfer System), Massachusetts Department of Environmental Protection, Massachusetts Division of Marine Fisheries, MassGIS, Rhode Island Eelgrass Task Force, RIGIS, Connecticut Department of Energy and Environmental Protection, Peconic Estuary Partnership, and New York Natural Heritage Program, New York State Department of Environmental Conservation

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Layer: Birds (52)

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Layer: Bird Nest Sites (53)

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Description: This map layer shows nest sites of coastal bird species in Connecticut, Massachusetts, New Hampshire, New York and Rhode Island. Multiple records may be available at the same feature location. The data were created from NOAA's Environmental Sensitivity Index, which was developed to characterize shorelines based on their sensitivity to spilled oil in order to understand the potential risk to these species. These data are currently not available for download.

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Description: This layer shows the movement patterns of 3 black-capped petrels during their non-breeding season from the first tracking study of this species. The black-capped petrel (Pterodroma hasitata) is an endangered seabird with fewer than 2000 breeding pairs restricted to a few breeding sites in Haiti and the Dominican Republic. To date, use areas at sea have been determined entirely from vessel-based surveys and opportunistic sightings and, as such, spatial and temporal gaps in our understanding of the species’ marine range are likely. For example, compare these tracks with the modeled distribution (MDAT) data products under Birds > Individual Species. This study used satellite tags to document individual movement patterns of black-capped petrels. <br/> <br/> During chick rearing, petrels primarily used marine habitats in the southern Caribbean Sea. During the post-breeding period, each bird dispersed north and used waters west of the Gulf Stream offshore of the mid- and southern Atlantic coasts of the USA as well as Gulf Stream waters and deeper pelagic waters east of the Gulf Stream. Petrels used waters located within 14 different exclusive economic zones, suggesting that international collaboration will benefit the development of management strategies for this species. <br/> <br/> The tracks on the map represent the following time periods: <br/> <ul> <li>Bird 175 (blue): 11 July to 30 August 2014</li> <li>Bird 176 (purple): 28 June to 25 August 2014</li> <li>Bird 177 (yellow): 13 May to 4 November 2014</li></ul>

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Copyright Text: Jodice et al. 2015, Endangered Species Research Vol. 29; 23-33

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Description: These layers represent data from 271 satellite tags deployed on large juvenile and adult loggerheads in the northwest Atlantic by 6 tagging programs between 2004 and 2016. Mixed effect models were used to map spatial variation in the relative density of tagged loggerheads over the course of the year. To do this, daily weighted location estimates were binned by month and aggregated over a 40 km resolution version of the Atlantic Marine Assessment Program for Protected Species (AMAPPS) spatial grid. The data products focus on the area with the highest track densities (i.e., between 25.0° and 41.5° N, 81.5° and 65.0° W), even though some individuals ventured further north or into the Gulf of Mexico. The high density areas shown in these data products are based on over 10 years of satellite tagging data, and represent the relative distribution of tagged loggerheads that may be expected on average in a given month.

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Copyright Text: NOAA Northeast Fisheries Science Center; Winton et al. 2018. Estimating the distribution and relative density of satellite-tagged loggerhead sea turtles using geostatistical mixed effect models. Marine Ecology Progress Series 586: 217-232

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Layer: Intrinsic Seabed Habitat Vulnerability to Fishing - Bottom trawl, median fishing effort (72)

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Description: The Intrinsic Seabed Habitat Vulnerability to Fishing layers show the vulnerability of the seabed to each gear type. These datasets constitute a secondary set of outputs from the Northeast Fishing Effects Model (Fishing Effects). The model combines seafloor data (sediment type, energy regime) with parameters related to the interactions between fishing gear and seafloor habitats to generate habitat disturbance estimates in space and time. A higher habitat disturbance percentage suggests that the seafloor in that location is more vulnerable to that fishing gear. Mobile bottom contact gears generate higher benthic habitat disturbance values than fixed bottom contact gears. The intrinsic vulnerability products allow the Council to predict which areas would be vulnerable to impact, even in the absence of existing fishing pressure. <br/> <br/> Data inputs include a benthic sediment/energy map (in Data Explorer category Habitat > Physical) and fishing effort as swept area. Energy classification is based on depth or benthic boundary shear stress data. Data inputs and outputs to Fishing Effects are gridded at a 5 km by 5 km resolution. The model outputs extend only to the shelf break/upper continental slope because this is the limit of fishing activity with bottom-tending gears in the northeast region. The intrinsic habitat vulnerability products apply a spatially and temporally constant level of fishing disturbance for six types of bottom-tending fishing gears: trawl, scallop dredge, hydraulic clam dredge, longline, gillnet, and trap, across all grid cells of the model, at each monthly timestep from 1996-2017. The level of fishing disturbance evaluated for these model runs reflects the median swept area ratio over the entire time series and across all grid cells. Swept area ratio is simply the total swept area within each grid, relative to the grid size. For this model, which has a 25 km2 grid resolution, a swept area of 25 km2 would lead to a swept area ratio of 1, and a swept area of 12.5 km2 would lead to a swept area ratio of 0.5, etc. Values used are described in NEFMC (2019) and vary by gear type; the model report also shows results for the 95th percentile of swept area ratio. <br/> <br/> The maps in the Portal show the estimated percent seabed habitat disturbance for each of these six gear types by grid cell for the final month of the time series (December 2017), This type of product is of value to managers because fishing effort is influenced by numerous factors which are subject to change, including spatial closures that prohibit certain types of gear in specific locations. Every cell in the domain has a modeled value. Larger percentages indicate that a greater percentage of the seafloor is estimated to be impacted at these median levels of fishing disturbance, while smaller percentages indicate a lower impact. All gear types use the same color scale to allow for comparison among gears. While there are modeled differences below a 3% level, those differences are not thought to be especially meaningful in a management context, and are therefore not shown. <br/> <br/> Additional information about the model can be found on the <a href="https://www.nefmc.org/library/fishing-effects-model" target="_blank">New England Fishery Management Council's Fishing Effects</a> page.

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Copyright Text: New England Fishery Management Council, 2020. For questions contact Michelle Bachman, mbachman@nefmc.org

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Layer: Intrinsic Seabed Habitat Vulnerability to Fishing - Scallop Dredge, median fishing effort (73)

Name: Intrinsic Seabed Habitat Vulnerability to Fishing - Scallop Dredge, median fishing effort

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Description: The Intrinsic Seabed Habitat Vulnerability to Fishing layers show the vulnerability of the seabed to each gear type. These datasets constitute a secondary set of outputs from the Northeast Fishing Effects Model (Fishing Effects). The model combines seafloor data (sediment type, energy regime) with parameters related to the interactions between fishing gear and seafloor habitats to generate habitat disturbance estimates in space and time. A higher habitat disturbance percentage suggests that the seafloor in that location is more vulnerable to that fishing gear. Mobile bottom contact gears generate higher benthic habitat disturbance values than fixed bottom contact gears. The intrinsic vulnerability products allow the Council to predict which areas would be vulnerable to impact, even in the absence of existing fishing pressure. <br/> <br/> Data inputs include a benthic sediment/energy map (in Data Explorer category Habitat > Physical) and fishing effort as swept area. Energy classification is based on depth or benthic boundary shear stress data. Data inputs and outputs to Fishing Effects are gridded at a 5 km by 5 km resolution. The model outputs extend only to the shelf break/upper continental slope because this is the limit of fishing activity with bottom-tending gears in the northeast region. The intrinsic habitat vulnerability products apply a spatially and temporally constant level of fishing disturbance for six types of bottom-tending fishing gears: trawl, scallop dredge, hydraulic clam dredge, longline, gillnet, and trap, across all grid cells of the model, at each monthly timestep from 1996-2017. The level of fishing disturbance evaluated for these model runs reflects the median swept area ratio over the entire time series and across all grid cells. Swept area ratio is simply the total swept area within each grid, relative to the grid size. For this model, which has a 25 km2 grid resolution, a swept area of 25 km2 would lead to a swept area ratio of 1, and a swept area of 12.5 km2 would lead to a swept area ratio of 0.5, etc. Values used are described in NEFMC (2019) and vary by gear type; the model report also shows results for the 95th percentile of swept area ratio. <br/> <br/> The maps in the Portal show the estimated percent seabed habitat disturbance for each of these six gear types by grid cell for the final month of the time series (December 2017), This type of product is of value to managers because fishing effort is influenced by numerous factors which are subject to change, including spatial closures that prohibit certain types of gear in specific locations. Every cell in the domain has a modeled value. Larger percentages indicate that a greater percentage of the seafloor is estimated to be impacted at these median levels of fishing disturbance, while smaller percentages indicate a lower impact. All gear types use the same color scale to allow for comparison among gears. While there are modeled differences below a 3% level, those differences are not thought to be especially meaningful in a management context, and are therefore not shown. <br/> <br/> Additional information about the model can be found on the <a href="https://www.nefmc.org/library/fishing-effects-model" target="_blank">New England Fishery Management Council's Fishing Effects</a> page.

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Copyright Text: New England Fishery Management Council, 2020. For questions contact Michelle Bachman, mbachman@nefmc.org

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Layer: Intrinsic Seabed Habitat Vulnerability to Fishing - Hydraulic Clam dredge, median fishing effort (74)

Name: Intrinsic Seabed Habitat Vulnerability to Fishing - Hydraulic Clam dredge, median fishing effort

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Description: The Intrinsic Seabed Habitat Vulnerability to Fishing layers show the vulnerability of the seabed to each gear type. These datasets constitute a secondary set of outputs from the Northeast Fishing Effects Model (Fishing Effects). The model combines seafloor data (sediment type, energy regime) with parameters related to the interactions between fishing gear and seafloor habitats to generate habitat disturbance estimates in space and time. A higher habitat disturbance percentage suggests that the seafloor in that location is more vulnerable to that fishing gear. Mobile bottom contact gears generate higher benthic habitat disturbance values than fixed bottom contact gears. The intrinsic vulnerability products allow the Council to predict which areas would be vulnerable to impact, even in the absence of existing fishing pressure. <br/> <br/> Data inputs include a benthic sediment/energy map (in Data Explorer category Habitat > Physical) and fishing effort as swept area. Energy classification is based on depth or benthic boundary shear stress data. Data inputs and outputs to Fishing Effects are gridded at a 5 km by 5 km resolution. The model outputs extend only to the shelf break/upper continental slope because this is the limit of fishing activity with bottom-tending gears in the northeast region. The intrinsic habitat vulnerability products apply a spatially and temporally constant level of fishing disturbance for six types of bottom-tending fishing gears: trawl, scallop dredge, hydraulic clam dredge, longline, gillnet, and trap, across all grid cells of the model, at each monthly timestep from 1996-2017. The level of fishing disturbance evaluated for these model runs reflects the median swept area ratio over the entire time series and across all grid cells. Swept area ratio is simply the total swept area within each grid, relative to the grid size. For this model, which has a 25 km2 grid resolution, a swept area of 25 km2 would lead to a swept area ratio of 1, and a swept area of 12.5 km2 would lead to a swept area ratio of 0.5, etc. Values used are described in NEFMC (2019) and vary by gear type; the model report also shows results for the 95th percentile of swept area ratio. <br/> <br/> The maps in the Portal show the estimated percent seabed habitat disturbance for each of these six gear types by grid cell for the final month of the time series (December 2017), This type of product is of value to managers because fishing effort is influenced by numerous factors which are subject to change, including spatial closures that prohibit certain types of gear in specific locations. Every cell in the domain has a modeled value. Larger percentages indicate that a greater percentage of the seafloor is estimated to be impacted at these median levels of fishing disturbance, while smaller percentages indicate a lower impact. All gear types use the same color scale to allow for comparison among gears. While there are modeled differences below a 3% level, those differences are not thought to be especially meaningful in a management context, and are therefore not shown. <br/> <br/> Additional information about the model can be found on the <a href="https://www.nefmc.org/library/fishing-effects-model" target="_blank">New England Fishery Management Council's Fishing Effects</a> page.

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Copyright Text: New England Fishery Management Council, 2020. For questions contact Michelle Bachman, mbachman@nefmc.org

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Layer: Intrinsic Seabed Habitat Vulnerability to Fishing - Gillnet, median fishing effort (75)

Name: Intrinsic Seabed Habitat Vulnerability to Fishing - Gillnet, median fishing effort

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Description: The Intrinsic Seabed Habitat Vulnerability to Fishing layers show the vulnerability of the seabed to each gear type. These datasets constitute a secondary set of outputs from the Northeast Fishing Effects Model (Fishing Effects). The model combines seafloor data (sediment type, energy regime) with parameters related to the interactions between fishing gear and seafloor habitats to generate habitat disturbance estimates in space and time. A higher habitat disturbance percentage suggests that the seafloor in that location is more vulnerable to that fishing gear. Mobile bottom contact gears generate higher benthic habitat disturbance values than fixed bottom contact gears. The intrinsic vulnerability products allow the Council to predict which areas would be vulnerable to impact, even in the absence of existing fishing pressure. <br/> <br/> Data inputs include a benthic sediment/energy map (in Data Explorer category Habitat > Physical) and fishing effort as swept area. Energy classification is based on depth or benthic boundary shear stress data. Data inputs and outputs to Fishing Effects are gridded at a 5 km by 5 km resolution. The model outputs extend only to the shelf break/upper continental slope because this is the limit of fishing activity with bottom-tending gears in the northeast region. The intrinsic habitat vulnerability products apply a spatially and temporally constant level of fishing disturbance for six types of bottom-tending fishing gears: trawl, scallop dredge, hydraulic clam dredge, longline, gillnet, and trap, across all grid cells of the model, at each monthly timestep from 1996-2017. The level of fishing disturbance evaluated for these model runs reflects the median swept area ratio over the entire time series and across all grid cells. Swept area ratio is simply the total swept area within each grid, relative to the grid size. For this model, which has a 25 km2 grid resolution, a swept area of 25 km2 would lead to a swept area ratio of 1, and a swept area of 12.5 km2 would lead to a swept area ratio of 0.5, etc. Values used are described in NEFMC (2019) and vary by gear type; the model report also shows results for the 95th percentile of swept area ratio. <br/> <br/> The maps in the Portal show the estimated percent seabed habitat disturbance for each of these six gear types by grid cell for the final month of the time series (December 2017), This type of product is of value to managers because fishing effort is influenced by numerous factors which are subject to change, including spatial closures that prohibit certain types of gear in specific locations. Every cell in the domain has a modeled value. Larger percentages indicate that a greater percentage of the seafloor is estimated to be impacted at these median levels of fishing disturbance, while smaller percentages indicate a lower impact. All gear types use the same color scale to allow for comparison among gears. While there are modeled differences below a 3% level, those differences are not thought to be especially meaningful in a management context, and are therefore not shown. <br/> <br/> Additional information about the model can be found on the <a href="https://www.nefmc.org/library/fishing-effects-model" target="_blank">New England Fishery Management Council's Fishing Effects</a> page.

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Copyright Text: New England Fishery Management Council, 2020. For questions contact Michelle Bachman, mbachman@nefmc.org

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Layer: Intrinsic Seabed Habitat Vulnerability to Fishing - Longline, median fishing effort (76)

Name: Intrinsic Seabed Habitat Vulnerability to Fishing - Longline, median fishing effort

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Description: The Intrinsic Seabed Habitat Vulnerability to Fishing layers show the vulnerability of the seabed to each gear type. These datasets constitute a secondary set of outputs from the Northeast Fishing Effects Model (Fishing Effects). The model combines seafloor data (sediment type, energy regime) with parameters related to the interactions between fishing gear and seafloor habitats to generate habitat disturbance estimates in space and time. A higher habitat disturbance percentage suggests that the seafloor in that location is more vulnerable to that fishing gear. Mobile bottom contact gears generate higher benthic habitat disturbance values than fixed bottom contact gears. The intrinsic vulnerability products allow the Council to predict which areas would be vulnerable to impact, even in the absence of existing fishing pressure. <br/> <br/> Data inputs include a benthic sediment/energy map (in Data Explorer category Habitat > Physical) and fishing effort as swept area. Energy classification is based on depth or benthic boundary shear stress data. Data inputs and outputs to Fishing Effects are gridded at a 5 km by 5 km resolution. The model outputs extend only to the shelf break/upper continental slope because this is the limit of fishing activity with bottom-tending gears in the northeast region. The intrinsic habitat vulnerability products apply a spatially and temporally constant level of fishing disturbance for six types of bottom-tending fishing gears: trawl, scallop dredge, hydraulic clam dredge, longline, gillnet, and trap, across all grid cells of the model, at each monthly timestep from 1996-2017. The level of fishing disturbance evaluated for these model runs reflects the median swept area ratio over the entire time series and across all grid cells. Swept area ratio is simply the total swept area within each grid, relative to the grid size. For this model, which has a 25 km2 grid resolution, a swept area of 25 km2 would lead to a swept area ratio of 1, and a swept area of 12.5 km2 would lead to a swept area ratio of 0.5, etc. Values used are described in NEFMC (2019) and vary by gear type; the model report also shows results for the 95th percentile of swept area ratio. <br/> <br/> The maps in the Portal show the estimated percent seabed habitat disturbance for each of these six gear types by grid cell for the final month of the time series (December 2017), This type of product is of value to managers because fishing effort is influenced by numerous factors which are subject to change, including spatial closures that prohibit certain types of gear in specific locations. Every cell in the domain has a modeled value. Larger percentages indicate that a greater percentage of the seafloor is estimated to be impacted at these median levels of fishing disturbance, while smaller percentages indicate a lower impact. All gear types use the same color scale to allow for comparison among gears. While there are modeled differences below a 3% level, those differences are not thought to be especially meaningful in a management context, and are therefore not shown. <br/> <br/> Additional information about the model can be found on the <a href="https://www.nefmc.org/library/fishing-effects-model" target="_blank">New England Fishery Management Council's Fishing Effects</a> page.

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Copyright Text: New England Fishery Management Council, 2020. For questions contact Michelle Bachman, mbachman@nefmc.org

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Layer: Intrinsic Seabed Habitat Vulnerability to Fishing - Trap, median fishing effort (77)

Name: Intrinsic Seabed Habitat Vulnerability to Fishing - Trap, median fishing effort

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Description: The Intrinsic Seabed Habitat Vulnerability to Fishing layers show the vulnerability of the seabed to each gear type. These datasets constitute a secondary set of outputs from the Northeast Fishing Effects Model (Fishing Effects). The model combines seafloor data (sediment type, energy regime) with parameters related to the interactions between fishing gear and seafloor habitats to generate habitat disturbance estimates in space and time. A higher habitat disturbance percentage suggests that the seafloor in that location is more vulnerable to that fishing gear. Mobile bottom contact gears generate higher benthic habitat disturbance values than fixed bottom contact gears. The intrinsic vulnerability products allow the Council to predict which areas would be vulnerable to impact, even in the absence of existing fishing pressure. <br/> <br/> Data inputs include a benthic sediment/energy map (in Data Explorer category Habitat > Physical) and fishing effort as swept area. Energy classification is based on depth or benthic boundary shear stress data. Data inputs and outputs to Fishing Effects are gridded at a 5 km by 5 km resolution. The model outputs extend only to the shelf break/upper continental slope because this is the limit of fishing activity with bottom-tending gears in the northeast region. The intrinsic habitat vulnerability products apply a spatially and temporally constant level of fishing disturbance for six types of bottom-tending fishing gears: trawl, scallop dredge, hydraulic clam dredge, longline, gillnet, and trap, across all grid cells of the model, at each monthly timestep from 1996-2017. The level of fishing disturbance evaluated for these model runs reflects the median swept area ratio over the entire time series and across all grid cells. Swept area ratio is simply the total swept area within each grid, relative to the grid size. For this model, which has a 25 km2 grid resolution, a swept area of 25 km2 would lead to a swept area ratio of 1, and a swept area of 12.5 km2 would lead to a swept area ratio of 0.5, etc. Values used are described in NEFMC (2019) and vary by gear type; the model report also shows results for the 95th percentile of swept area ratio. <br/> <br/> The maps in the Portal show the estimated percent seabed habitat disturbance for each of these six gear types by grid cell for the final month of the time series (December 2017), This type of product is of value to managers because fishing effort is influenced by numerous factors which are subject to change, including spatial closures that prohibit certain types of gear in specific locations. Every cell in the domain has a modeled value. Larger percentages indicate that a greater percentage of the seafloor is estimated to be impacted at these median levels of fishing disturbance, while smaller percentages indicate a lower impact. All gear types use the same color scale to allow for comparison among gears. While there are modeled differences below a 3% level, those differences are not thought to be especially meaningful in a management context, and are therefore not shown. <br/> <br/> Additional information about the model can be found on the <a href="https://www.nefmc.org/library/fishing-effects-model" target="_blank">New England Fishery Management Council's Fishing Effects</a> page.

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Copyright Text: New England Fishery Management Council, 2020. For questions contact Michelle Bachman, mbachman@nefmc.org

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Layer: Tidal Marsh Vegetation Classification (91)

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Description: This data product was developed in collaboration with the U.S. Environmental Protection Agency, Region 1 (EPA R1). As part of an 18-month project, EPA R1 convened multiple meetings of an expert work group to both update regional (ME to NY) coastal vegetation datasets on the Northeast Ocean Data Portal (eelgrass meadows and tidal marsh) and to determine appropriate methods for mapping blue carbon stocks in these habitats. <br/><br/> The EPA R1 work group sought tidal marsh data that were mapped consistently across the region of interest (ME to NY). The work group decided to use multiple datasets to address the needs of this effort. A dataset developed by the <a href="https://www.tidalmarshbirds.org" target="_blank">Saltmarsh Habitat and Avian Research Program (SHARP)</a>, contains a regional classification produced using a combination of Digital Elevation Model and National Agriculture Imagery Program (NAIP) multispectral imagery, and provides a contiguous classification of tidal marsh cover types from coastal Maine to Virginia. However, these data had gaps in the region of interest around New Bedford Harbor, MA, due to lack of available or interpretable NAIP imagery in that area. To fill this gap, the work group recommended extracting marsh habitat information from the <a href="https://www.sciencebase.gov/catalog/item/60f992fcd34e3ccd82fe3fbf" target="_blank">Conceptual Marsh Units of Massachusetts salt marshes</a> dataset from USGS (“CMUs”). Massachusetts CMUs are polygons created from the 2005 Massachusetts salt marsh dataset that were delineated to smaller, conceptual marsh units by the geoprocessing of surface elevation data. Each layer associated with these datasets are maintained separately in the Portal but visualized together. The data user is encouraged to refer to the metadata of this composite and of each individual source layer carefully, as the methods to produce vegetation classes, feature geometry, attribute details, and timeliness are not necessarily consistent among datasets.

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Layer: Tidal Marsh Vegetation Classification (DEM) (78)

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Description: This dataset represents salt marsh communities in the Northeast Atlantic coast. The classification was produced using a combination of Digital Elevation Model (DEM) and National Agriculture Imagery Program (NAIP) multispectral imagery. This dataset combined with "Tidal Marsh Vegetation Classification, no DEM, 3m, Northeast U.S." provides a contiguous classification of tidal marsh cover types from coastal Maine to Virginia. The eight distinct cover/community types identified are: <br/> <ul> <li><b>High marsh:</b> Area flooded during spring tides related to the lunar cycle and dominated by Spartina patens, Distichlis spicata, Juncus gerardii, and short form Spartina alterniflora. Other species include Juncus roemerianus, Scirpus pungens, Scirpus robustus, Limonium nashii, Aster tenuifolius, and Triglochin maritima.</li> <li><b>Low marsh:</b>Area flooded regularly by daily tides and dominated by tall form Spartina alterniflora.</li> <li><b>Salt pools/pannes:</b>Depressed, bare areas with sparse vegetation cover and extremely high soil salinities. Generally, pools retain water between high tides while pannes do not.</li> <li><b>Terrestrial border:</b>Area infrequently flooded by storm and spring tides and can include areas of marsh with fresh/brackish water due to a high water table and/or runoff from impervious surfaces. Typical plant species include Typha angustifolia, Iva frutescens, Baccharis halimifolia, Solidago sempervirens, Scirpus robustus, and Spartina pectinata.</li> <li><b>Phragmites australis:</b>A species of considerable management interest due to the invasive nature of an introduced form, especially in marshes with freshwater input, upland development, and/or increased nutrients.</li> <li><b>Mudflat:</b>Exposed muddy areas free of vegetation.</li> <li><b>Open water (bordering cover type):</b>Channels and bays leading to open ocean.</li> <li><b>Upland (bordering cover type):</b>All non-marsh terrestrial cover.</li></ul> <br/> Detailed zone descriptions, accuracy estimates for each cover type, and data limitation details are provided at <a href="https://nalcc.databasin.org/documents/documents/53ff96d6c2814d43aa92dc4948aa7d64/." target="_blank">https://nalcc.databasin.org/documents/documents/53ff96d6c2814d43aa92dc4948aa7d64/</a>. For more information about the development of the data please contact Mo Correll at <A HREF="mailto:Maureen.correll@maine.edu">Maureen.correll@maine.edu</A>. <br/> <br/> Data are hosted on an external server.

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Copyright Text: SHARP 2017. “Marsh Habitat Zonation Map”. Saltmarsh Habitat and Avian Research Program. Ver: 26 Oct 2017. https://www.tidalmarshbirds.org.

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Layer: MA CMU (90)

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Layer: Proposed Passive Acoustic Network (80)

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Layer: Proposed PAM Stations (20km) (81)

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Description: This data layer shows the components of a proposed Passive Acoustic Monitoring (PAM) design for regional long-term monitoring in North and Mid-Atlantic offshore lease areas and wind energy areas. <br/> <br/> In June 2021, the Bureau of Ocean Energy Management (BOEM) convened a workshop titled "Improving monitoring, data consistency, archiving, and access for improved regional integration of renewable energy projects and science: Passive acoustic monitoring and marine mammals." Attendees reviewed a nested grid monitoring design for placing PAM detector broadly across whale habitat off the US east coast continental shelf and in areas of proposed wind energy development. The design is based on achieving 100% acoustic coverage of North Atlantic right whales by using 20 x 20 km grid cells spacing throughout offshore wind energy lease areas and larger 40 x 40 km grid cells aimed at connecting the offshore wind energy areas, with suggested PAM stations centered in each respective grid cell. The latter would achieve acoustic coverage of around 50% of the area monitored, balancing the costs and logistics of collecting regional data with the ability to detect species presence across contiguous areas of interest within and between offshore wind areas. More detailed regional PAM monitoring designs can be seen for the five main current wind energy areas of interest. Baseline monitoring over the larger region is essential in order to be able to understand changes in species presence at a relevant scale for these highly migratory baleen whale species. The area grids will be updated as new wind energy areas are leased. <br/> <br/> To view when and where specific whale, dolphin, and other cetacean species have been previously acoustically detected in the North Atlantic Ocean based PAM deployed between 2004-2020, visit the <a href="https://apps-nefsc.fisheries.noaa.gov/pacm/#/" target="_blank">Passive Acoustic Cetacean Map</a>.

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Description: This data layer shows the components of a proposed Passive Acoustic Monitoring (PAM) design for regional long-term monitoring in North and Mid-Atlantic offshore lease areas and wind energy areas. <br/> <br/> In June 2021, the Bureau of Ocean Energy Management (BOEM) convened a workshop titled "Improving monitoring, data consistency, archiving, and access for improved regional integration of renewable energy projects and science: Passive acoustic monitoring and marine mammals." Attendees reviewed a nested grid monitoring design for placing PAM detector broadly across whale habitat off the US east coast continental shelf and in areas of proposed wind energy development. The design is based on achieving 100% acoustic coverage of North Atlantic right whales by using 20 x 20 km grid cells spacing throughout offshore wind energy lease areas and larger 40 x 40 km grid cells aimed at connecting the offshore wind energy areas, with suggested PAM stations centered in each respective grid cell. The latter would achieve acoustic coverage of around 50% of the area monitored, balancing the costs and logistics of collecting regional data with the ability to detect species presence across contiguous areas of interest within and between offshore wind areas. More detailed regional PAM monitoring designs can be seen for the five main current wind energy areas of interest. Baseline monitoring over the larger region is essential in order to be able to understand changes in species presence at a relevant scale for these highly migratory baleen whale species. The area grids will be updated as new wind energy areas are leased. <br/> <br/> To view when and where specific whale, dolphin, and other cetacean species have been previously acoustically detected in the North Atlantic Ocean based PAM deployed between 2004-2020, visit the <a href="https://apps-nefsc.fisheries.noaa.gov/pacm/#/" target="_blank">Passive Acoustic Cetacean Map</a>.

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Layer: Proposed PAM Stations (40km) (83)

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Description: This data layer shows the components of a proposed Passive Acoustic Monitoring (PAM) design for regional long-term monitoring in North and Mid-Atlantic offshore lease areas and wind energy areas. <br/> <br/> In June 2021, the Bureau of Ocean Energy Management (BOEM) convened a workshop titled "Improving monitoring, data consistency, archiving, and access for improved regional integration of renewable energy projects and science: Passive acoustic monitoring and marine mammals." Attendees reviewed a nested grid monitoring design for placing PAM detector broadly across whale habitat off the US east coast continental shelf and in areas of proposed wind energy development. The design is based on achieving 100% acoustic coverage of North Atlantic right whales by using 20 x 20 km grid cells spacing throughout offshore wind energy lease areas and larger 40 x 40 km grid cells aimed at connecting the offshore wind energy areas, with suggested PAM stations centered in each respective grid cell. The latter would achieve acoustic coverage of around 50% of the area monitored, balancing the costs and logistics of collecting regional data with the ability to detect species presence across contiguous areas of interest within and between offshore wind areas. More detailed regional PAM monitoring designs can be seen for the five main current wind energy areas of interest. Baseline monitoring over the larger region is essential in order to be able to understand changes in species presence at a relevant scale for these highly migratory baleen whale species. The area grids will be updated as new wind energy areas are leased. <br/> <br/> To view when and where specific whale, dolphin, and other cetacean species have been previously acoustically detected in the North Atlantic Ocean based PAM deployed between 2004-2020, visit the <a href="https://apps-nefsc.fisheries.noaa.gov/pacm/#/" target="_blank">Passive Acoustic Cetacean Map</a>.

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Description: This data layer shows the components of a proposed Passive Acoustic Monitoring (PAM) design for regional long-term monitoring in North and Mid-Atlantic offshore lease areas and wind energy areas. <br/> <br/> In June 2021, the Bureau of Ocean Energy Management (BOEM) convened a workshop titled "Improving monitoring, data consistency, archiving, and access for improved regional integration of renewable energy projects and science: Passive acoustic monitoring and marine mammals." Attendees reviewed a nested grid monitoring design for placing PAM detector broadly across whale habitat off the US east coast continental shelf and in areas of proposed wind energy development. The design is based on achieving 100% acoustic coverage of North Atlantic right whales by using 20 x 20 km grid cells spacing throughout offshore wind energy lease areas and larger 40 x 40 km grid cells aimed at connecting the offshore wind energy areas, with suggested PAM stations centered in each respective grid cell. The latter would achieve acoustic coverage of around 50% of the area monitored, balancing the costs and logistics of collecting regional data with the ability to detect species presence across contiguous areas of interest within and between offshore wind areas. More detailed regional PAM monitoring designs can be seen for the five main current wind energy areas of interest. Baseline monitoring over the larger region is essential in order to be able to understand changes in species presence at a relevant scale for these highly migratory baleen whale species. The area grids will be updated as new wind energy areas are leased. <br/> <br/> To view when and where specific whale, dolphin, and other cetacean species have been previously acoustically detected in the North Atlantic Ocean based PAM deployed between 2004-2020, visit the <a href="https://apps-nefsc.fisheries.noaa.gov/pacm/#/" target="_blank">Passive Acoustic Cetacean Map</a>.

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Layer: Current PAM deployments (85)

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Description: This layer shows locations within the Proposed Passive Acoustic Monitoring (PAM) Network where PAM devices are currently located. A PAM device may be deployed anywhere within the highlighted grid cell. When 20km grid cells overlap a 40km grid cell and the larger 40km grid cell is highlighted, it can be assumed that the device is not deployed in any of the overlapping 20km grid cells. Click on each highlighted grid cell to obtain available information about the entity responsible for the deployment, length of deployment, and contact information. There may be PAM devices deployed outside of these grid cells that are not depicted on this map. More detail on active recording locations within each grid cell and the broader region can be viewed on the <a href="https://apps-nefsc.fisheries.noaa.gov/pacm/#/" target="_blank">NEFSC Passive Acoustic Cetacean Map</a>.<br/><br/>This layer currently includes deployments managed by:<br/><ul style=“list-style-type:circle”><li>NOAA Northeast Fisheries Science Center</li> <li>University of New Hampshire</li> <li>Maine Department of Marine Resources</li> <li>Robots4Whales/WHOI</li> </ul><br/> <br/>For more information about active deployments, contact Sofie Van Parijs (<A HREF="mailto:sofie.vanparijs@noaa.gov">sofie.vanparijs@noaa.gov</A>) at the NOAA NEFSC Passive Acoustics Research Program.

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Layer: PAM detections of NARW since 2010 (86)

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Description: This layer shows locations within the Proposed Passive Acoustic Monitoring (PAM) Network where North Atlantic right whales (NARW) were detected at least one day within each grid cell since 2010. There have also been detections of NARW outside of these grid cells over this time that are not depicted on this map. These data are meant to inform locations where new PAM devices could be placed to detect NARW in the future. For detail on recording locations within each grid cell, lengths of deployment, and number of detections over time (including for cetacean species other than NARW), visit the <a href="https://apps-nefsc.fisheries.noaa.gov/pacm/#/" target="_blank">NEFSC Passive Acoustic Cetacean Map</a>.

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Layer: New England Aquarium Megafauna Aerial Survey Transects 2011-2021 (87)

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Description: This layer represents transects from New England Aquarium aerial surveys conducted from 2011-2021. These surveys focused on all marine megafauna visible from a plane (excluding birds) and were comprised of ten north-south transects evenly spaced at approximately six nautical miles (nm). Eight survey options are available: each option shifts all 10 transects 0.75 nm east or west, but maintains the six nm spacing between transects. One of these options was selected at random before each survey. The surveys have been funded by the Massachusetts Clean Energy Center (MassCEC), the Bureau of Ocean Energy Management (BOEM), and most recently by offshore wind development companies. In some years, surveys were coordinated with partners that conducted boat-based oceanographic sampling to assess the physical and biological characteristics of the study area. <br/> <br/> The surveys show that many species of marine megafauna use the study area in high numbers. The most recent surveys show an increased presence of right whales in all seasons and a decrease in the presence of other large whales, such as humpbacks. There also appears to be a shift in presence of all large whales towards the eastern side of the survey area. Continued surveys are needed to determine the consistency of these patterns. Continuing this 10-year time series of consistent aerial survey data also represents a unique opportunity to detect potential short-term effects of turbine construction on US marine species and develop solutions for mitigating these effects. <br/> <br/> View the most recent survey report: <a href="https://files-cdn.masscec.com/uploads/attachments/BOEM%202021-054%20NEAq%20MACEC%20BOEM%20Large%20Pelagics%20Campaign%206A%20Final.pdf" target="_blank">Megafauna Aerial Surveys in the Wind Energy Areas of Massachusetts and Rhode Island with Emphasis on Large Whales: Summary Report Campaign 6a, March 2020 - October 2020</a>.

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Copyright Text: New England Aquarium, Jessica Redfern jredfern@neaq.org

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Layer: Glacial Moraines (88)

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Description: Areas of Particular Concern have been designated in state waters through the <a href="https://rules.sos.ri.gov/regulations/part/650-20-05-11" target="_blank">RI Ocean Special Area Management Plan</a> (Ocean SAMP) process with the goal of protecting areas that have high conservation value, cultural and historic value, or human use value from offshore development. These areas may be limited in their use by a particular regulatory agency (e.g., shipping lanes), or have inherent risk associated with them (e.g., unexploded ordnance locations), or have inherent natural value or value assigned by human interest (e.g., glacial moraines, historic shipwreck sites). <br/> <br/> Glacial moraines are important habitat areas for a diversity of fish and other marine plants and animals because of their relative structural permanence and structural complexity. Glacial moraines create a unique bottom topography that allows for habitat diversity and complexity, which allows for species diversity in these areas and creates environments that exhibit some of the highest biodiversity within the entire Ocean SAMP area. The RI CRMC also recognizes that because glacial moraines contain valuable habitats for fish and other marine life, they are also important to commercial and recreational fishermen. Accordingly, the RI CRMC designated glacial moraines as identified in the Ocean SAMP as Areas of Particular Concern.

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Copyright Text: Rhode Island Coastal Resources Management Council (RI CRMC)

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Layer: Sea Scallops 2016-2018 Potential Reproductive Output (89)

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Description: This layer shows the results of a drop camera survey to estimate the number and size of Atlantic sea scallops (Placopecten magellanicus) over 70,000 km^2 of the continental shelf, an area that nearly covers the entire range of this species. The survey was conducted from May to October in 2017, with additional areas surveyed in 2016 and 2018. In total, 22,592 quadrat samples were collected at 5648 stations. The productivity of sampled areas was ranked by the presence or absence of scallops observed in each quadrat image: 0 scallops for low productivity, 1–2 scallops for medium productivity, and 3 or more scallops for high productivity. This sampling represents a snapshot in time; over the 20-year time-series of the US resource, areas that at one time did not have scallops could potentially support high densities at a later date if a recruitment event were to occur. From these surveys, researchers estimated that there were 34 billion individual scallops (95% confidence limits: 22–46 billion) within the species’ range.

Definition Expression: N/A

Copyright Text: Stokesbury and Bethoney, 2020; Frontiers in Ecology and Environment 18(9):513–519, doi:10.1002/fee.2244

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