Benthic habitat maps were developed for the Otis Pike and Sunken Forest study areas following the top-down mapping approach, for which habitat map units are geologically defined based on the presumption that geologic environments or features contain distinct biological assemblages. The resulting habitats are classified according to the CMECS framework and are referred to as “biotopes.” The term “biotope” is specific in that it integrates biotic-abiotic characteristics to offer more ecologically meaningful information. In this study, biotopes reflect the relationship between macrofaunal communities and geological features of their associated environments within the defined map units. The resulting biotopes are considered preliminary because the relationships identified have not been repeatedly demonstrated over time, as this study represents the first of its kind within FIIS.

Sediment Grain Size and CMECS Classification Data used to construct benthic habitat maps for FIIS. The ground-truth surveys involved the collection of surficial grab samples of the seafloor, sediment profile imagery (SPI), and underwater video. The three instruments were deployed together, allowing for co-located datasets. Combined, these datasets help provide a thorough understanding of the study areas, as they capture sediment and biological community characteristics at various spatial scales and resolutions.

Sediment Grain Size and CMECS Classification Data used to construct benthic habitat maps for FIIS. The ground-truth surveys involved the collection of surficial grab samples of the seafloor, sediment profile imagery (SPI), and underwater video. The three instruments were deployed together, allowing for co-located datasets. Combined, these datasets help provide a thorough understanding of the study areas, as they capture sediment and biological community characteristics at various spatial scales and resolutions.

Sediment Profile Image (SPI) Analysis and Coastal/Marine Ecological Classification Standard (CMECS) Classification Data used to construct benthic habitat maps for FIIS. Sediment profile imagery (SPI) provides an in-situ perspective of the seafloor and associated characteristics. Specifically, the camera takes a profile photograph of the sediment-water interface, which offers information about the biological and environmental attributes of the surface of the seafloor, the substrate just below the seafloor, and the overlying water column. SPI imagery has been used as the basis for or to complement ecological studies for several decades (for further reading, refer to Germano et al., 2011; Solan et al., 2003; Germano et al., 1989). For this study, SPI images were collected to corroborate and complement the acoustic and grab sample data. Images were taken at each grab sample site and also along a series of planned transects designed to cross boundaries identified in the sidescan mosaics. All deployments of the camera were done in triplicate, resulting in six images per site (one deployment of the camera captures two images ten seconds apart). The images were processed and analyzed in Adobe Photoshop CS3. Color and contrast adjustments were applied to enhance the images for detection of features. Geological and biological features were identified and described through expert interpretation of the images, including relative grain size, bedforms, biogenic features, and presence of seagrass and organisms (identified to lowest taxonomic level). Furthermore, consistent settings were applied when taking penetration and apparent redox potential discontinuity (aRPD) measurements. The aRPD value indicates the depth at which the sediment transitions from being oxidized to reduced (Gerwing et al., 2017).

Habitat classification map based on surveys completed along the 58‐km long Assateague barrier island stretching from the Ocean City inlet in Maryland, down past Chincoteague Island in northern Virginia. The data was collected June 20th-25th, 2014 and May 12th - 21th, 2015. Full coverage side-scan sonar and partial coverage bathymetry data were collected using an EdgeTech 6205 Multiphase Echosounder. In total, 73 square kilometers were mapped at primarily at 100m line spacing and 80 m swath range per channel (to allow overlap between lines).

Habitat classification map based on surveys completed along the 58‐km long Assateague barrier island stretching from the Ocean City inlet in Maryland, down past Chincoteague Island in northern Virginia. The data was collected June 20th-25th, 2014 and May 12th - 21th, 2015. Full coverage side-scan sonar and partial coverage bathymetry data were collected using an EdgeTech 6205 Multiphase Echosounder. In total, 73 square kilometers were mapped at primarily at 100m line spacing and 80 m swath range per channel (to allow overlap between lines).

Supervised classification utilized training texels of 30 x 30 to 90 x 90 pixels cut from GeoTiff orthotiles centered on the coordinates of the grab sample stations. Each texel was assigned to a cluster training set based on that sample’s classification in the original (latent) cluster analysis calculated on similarity of sediment characteristics. However, none of the potential 2470 combinations of backscatter signal characters and their treatments were able to discriminate significantly among these 5 classes, meaning that variation among samples of at least 2 classes overlapped considerably. Recombination into 4 classes (combining Classes 3 and 4) yielded significant discrimination. Mapping of the results showed that one of these classes was likely to be legitimate when applied to the bayside, but additionally was duplicated as an artifact of edge between orthotiles on the oceanside because of fading at the swath margins. This means that backscatter was characteristic of the larger habitat distinctions shown in the latent dendrogram with confidence, and of lesser branches with less confidence. Therefore, the entire oceanside was characterized as one habitat, and classification of the bayside was attempted again in isolation. Recombination into 3 classes (“mud”, “sand”, “gravelly sand”) was able to resolve 3 classes significantly (score = 0.33548) using input factors Contrast, Gray Mean, and Directionality with 30 x 30 pixel (15 x 15 m) texels. Despite good separation in the training texels, with some slight overlap at the 5% confidence ellipsoid for mud and gravel, most areas known to be muddy were classified as being gravelly sand in the resulting classification map. This is likely a function of reflective shell hash in acoustically dark mud having similar contrast to reflective gravel with acoustically dark shadows created by high relief. A test of natural separation (Davies-Bouldin Index) indicated four modes using these characters, so the same factors were used in an unsupervised classification allowing four latent classes. The four latent classes mapped very similar to the previous supervised classification but broke up the latent analog to the “gravelly sand” class. Class error was low at 0.1110. The newly resolved class was clearly mud with shell, based on video ground truthing. This class was combined with the mud class in compiling the final habitat classification map.

Benthic habitat maps were developed for the CACO study areas following the top-down mapping approach, for which habitat map units are geologically defined based on the presumption that geologic environments or features contain distinct biological assemblages. The resulting habitats are classified according to the CMECS framework and are referred to as “biotopes.” The term “biotope” is specific in that it integrates biotic-abiotic characteristics to offer more ecologically meaningful information. In this study, biotopes reflect the relationship between macrofaunal communities and geological features of their associated environments within the defined map units. The resulting biotopes are considered preliminary because the relationships identified have not been repeatedly demonstrated over time.

Benthic habitat maps were developed for the CACO study areas following the top-down mapping approach, for which habitat map units are geologically defined based on the presumption that geologic environments or features contain distinct biological assemblages. The resulting habitats are classified according to the CMECS framework and are referred to as “biotopes.” The term “biotope” is specific in that it integrates biotic-abiotic characteristics to offer more ecologically meaningful information. In this study, biotopes reflect the relationship between macrofaunal communities and geological features of their associated environments within the defined map units. The resulting biotopes are considered preliminary because the relationships identified have not been repeatedly demonstrated over time.

Sediment Profile Images (SPI) used to construct benthic habitat maps for FIIS. Sediment profile imagery (SPI) provides an in-situ perspective of the seafloor and associated characteristics. Specifically, the camera takes a profile photograph of the sediment-water interface, which offers information about the biological and environmental attributes of the surface of the seafloor, the substrate just below the seafloor, and the overlying water column. SPI imagery has been used as the basis for or to complement ecological studies for several decades (for further reading, refer to Germano et al., 2011; Solan et al., 2003; Germano et al., 1989). For this study, SPI images were collected to corroborate and complement the acoustic and grab sample data. Images were taken at each grab sample site and also along a series of planned transects designed to cross boundaries identified in the sidescan mosaics. All deployments of the camera were done in triplicate, resulting in six images per site (one deployment of the camera captures two images ten seconds apart). The images were processed and analyzed in Adobe Photoshop CS3. Color and contrast adjustments were applied to enhance the images for detection of features. Geological and biological features were identified and described through expert interpretation of the images, including relative grain size, bedforms, biogenic features, and presence of seagrass and organisms (identified to lowest taxonomic level). Furthermore, consistent settings were applied when taking penetration and apparent redox potential discontinuity (aRPD) measurements. The aRPD value indicates the depth at which the sediment transitions from being oxidized to reduced (Gerwing et al., 2017).