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Data used for the creation of the potential marine benthic habitat interpretation consists of multibeam bathymetry, acoustic backscatter, sediment samples, camera-sled imagery, and existing geologic and seafloor interpretive maps. All data were compiled and displayed for interpretation using ESRI ArcGIS software, ArcMap v.10.0. The process consists of editing a shapefile within ArcMap, beginning with the construction of polygons to delineate benthic features. A benthic feature is an area with common characteristics which can be characterized as a single potential habitat type. The boundaries and extents of these features were determined from the bathymetric data. In general, interpretations were made at scales between 1:2,000 and 1:5,000. The USGS kindly provided the Center for Habitat Studies with a geodatabase consisting of feature datasets delineating geologic features and attributes for offshore San Gregorio. Some of the delineated polygons were preserved as part of the potential marine benthic habitat characterization. However, the Greene and others (2007) code was used in attributing the dataset and additional polygons were added using the methods outlined below. High-resolution multibeam sonar data in the form of bathymetric depth grids (seafloor digital elevation models, referred to as the "bathymetry") were the primary data used in the interpretation of potential habitat types. Shaded-relief imagery ("hillshade") allows for visualization of the terrain and interpretation of submarine landforms. On the basis of these hillshades, areas of rock were identified by their often sharply defined edges and high relative relief; these may be contiguous outcrops, isolated parts of outcrop protruding through sediment cover (pinnacles), or isolated boulders. Although these types of features can be confidently characterized as exposed rock, it is not uncommon to find areas within or around the rocky feature that appear to be covered by a thin veneer of sediment. These areas are identified as "mixed" induration, containing both rock and sediment. Broad areas of the seafloor lacking sharp and angular characteristics are considered to be sediment. Sedimentary features may contain erosional or depositional characteristics recognizable in the bathymetry, such as dynamic bedforms (dunes or sand waves). General morphologic features such as scours, mounds, and depressions were also identified using the hillshade imagery. The combination of acoustic backscatter data and "ground truthed" sediment samples were used to delineate seafloor sediment types within areas identified as "soft (s)" induration. Initially, ground truth data, in the form of grab sample descriptions and average grain size measurements, were categorized into four grain-size categories: mud (m), muddy sand (s/m), sand (s), and sandy gravel (s/g). Backscatter data was then classified into four intensity categories (low, med, high, very high) that are assumed to correspond to relative grain sizes. The aim was to develop an intensity classification of the seafloor that correlated with the data collected from the sediment samples. Thus, the combination of remotely observed data (acoustic backscatter) and directly observed data (sediment grab samples) translates to higher confidence in our ability to interpret broad areas of the seafloor. Nonetheless, we caution against using our sediment type interpretations as anything more than "best-guess" because of the following issues: characterization of contiguous sediment bodies is a difficult procedure because even small areas can exhibit a wide spectrum of backscatter-intensity values that lack distinct boundaries; backscatter intensity can be affected by depth, vegetation, water column conditions, and seafloor relief; and directly observed sediment data, in the form of sediment samples, represents a very small area relative to remotely observed data, requiring broad areas of interpolation. Please refer to Greene and others (2007) for more information regarding the Benthic Marine Potential Habitat Classification Scheme and the codes used to represent various seafloor features. References Cited: Greene, H.G., Bizzarro, J.J., O'Connell, V.M., and Brylinsky, C.K., 2007, Construction of digital potential marine benthic habitat maps using a coded classification scheme and its application, in Todd, B.J., and Greene, H.G., eds., Mapping the seafloor for habitat characterization: Geological Association of Canada Special Paper 47, p. 141-155. Greene, H.G., Yoklavich, M.M., Starr, R.M., O'Connell, V.M., Wakefield, W.W., Sullivan, D.E., McRea, J.E., Jr., and Cailliet, G.M., 1999, A classification scheme for deep seafloor habitats: Oceanologica Acta, v. 22, no. 6, p. 663-678.
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