Remote sensing studies based on satellite and aerial imagery have improved our understanding of the morphology and distribution of several shallow reefs along the Red Sea Arabian coast and of the benthic assemblages associated to them (Bruckner et al., 2011; Bruckner et al., 2012; Rowlands et al., 2016). However, data concerning the deeper benthic assemblages' composition and spatial distribution in the central Red Sea are still missing. Using high-resolution acoustic technology and an underwater remotely operated vehicle (ROV), we aim to map, describe, and classify the reefs found in Thuwal's coastal area, filling the information gap by producing the first benthic habitat map of this area and making progress towards the evaluation of shallow and upper mesophotic benthic resources in the Saudi Arabian Red Sea. High-resolution acoustic data was collected using a multibeam echosounder system, which generated a bathymetric model. Based on this, the seafloor features were classified into 12 morphotypes following a visual assessment. Based on the morphotypes classification, 28 sites were visually selected for ground-truthing data acquisition and characterization of the substrate and benthic assemblages using a remotely operated vehicle equipped with an ultra-short baseline (USBL) positioning system. With the information obtained from the bathymetry data and the ROV video transects, a Top-Down approach in which we analyzed, categorized, and classified the data was used to create Thuwal's reefs benthic habitat map in which 23 different benthic habitat types were identified. This research uncovered previously poorly studied reef morphologies in the Red Sea and their associated benthic assemblages. Moreover, this work will help improve the understanding of the spatial distribution of benthic communities located on Thuwal's reefs, giving a baseline with the potential to provide fundamental information that can be used for mapping, management, conservation, and future research at other Red Sea reef sites in Saudi Arabia.

Using a towed underwater video camera system, benthic habitats were classified along transects in a popular offshore fishing area on the West Florida Shelf (WFS) known as “The Elbow.” Additionally, high resolution multibeam bathymetry and co-registered backscatter data were collected for the entire study area. Using these data, full coverage geologic and biotic habitat maps were developed using both unsupervised and supervised statistical classification methodologies. The unsupervised methodology used was k-means clustering, and the supervised methodology used a random forest algorithm. The two methods produced broadly similar results; however, the supervised methodology outperformed the unsupervised methodology. The results of the supervised classification demonstrated “substantial agreement” (κ>0.6) between observations and predictions for both geologic and biotic habitat, while the results of the unsupervised classification demonstrated “moderate agreement” (κ>0.4) between observations and predictions for both geologic and biotic habitat. Comparisons were made with the previously existing map for this area created by Florida Fish and Wildlife Conservation Commission’s Fish and Wildlife Research Institute (FWC-FWRI). Some features are distinguishable in both maps, but the FWC-FWRI map shows a greater extent of low relief hard bottom features than was predicted in our habitat maps. The areas predicted as low relief hard-bottom by FWC-FWRI often coincide with areas of higher uncertainty in the supervised map of geologic habitat from this study, but even when compared with ground-truth points from the towed video rather than predictions, the low relief hard bottom in FWC-FWRI’s map still corresponds to what was identified as sand in the video 73% of the time. The higher uncertainty might be a result of the presence of mixed habitats, differing morphology of hard-bottom, or the presence of sand intermixed with gravel or debris. More ground-truth samples should be taken in these areas to increase the confidence of these classifications and resolve discrepancies between the two maps. Data from the towed video system were also used to assess differences in fish communities among habitat types and to calculate habitat-specific densities for each taxa. Fish communities were found to significantly differ between soft and hard bottom habitats as well as among the hard-bottom habitats with different vertical relief (flat hard-bottom vs more steeply sloping areas). Additionally, significant differences were found between the fish communities in habitats with attached fauna such as sponges and gorgonians, and areas without attached fauna; however, attached fauna require rock to attach to and the rock habitats rarely lacked attached fauna, so this difference may just reflect the difference between fish communities in sand and rock habitats without the consideration of vertical relief. Moreover, the species driving the differences in the fish communities were identified. Fish were more likely to be present and assemblages were more species rich in more complex habitats (rockier, higher relief, presence of attached fauna). Habitat specific densities were calculated for each species, and general trends are discussed. Lastly the habitat-specific densities were extrapolated to the total area of habitat type (sand vs rock) as predicted by the supervised geologic habitat map. There is predicted to be approximately 111,000 fish (95% CI [67015, 169405]) within the study area based on this method, with ~47,000 (~43%) predicted to be within the sand habitat and ~64,000 (~57%) in the rock habitat. This demonstrates the potential of offshore rocky reefs as “critical habitats” for demersal fish in the offshore environment as rock accounts for just 4% of the study area but is expected to contain over half of the total abundance. The value of sand habitats is also shown, as due to their large area they are able to contribute substantially to the total number of fish despite sustaining comparatively low densities.

Anthropogenic changes to the landscape, storm events and sea level rise are contributing to the erosion of beaches leading to an increase of the sediment load in near shore marine environments. Palm Beach, Florida is host to unique near shore hardbottom habitats. These areas are distinct from the vast expanses of surrounding sediments and play and important role of habitat and shelter for many different species. In this study, remotely sensed images from 2000-2015 were used to look at the movement of sediment and how it contributes to exposure rates of near shore hardbottom habitats in Palm Beach, Florida and how these factors affect the benthic community. GIS was used to determine areas of hardbottom with high exposure (exposed in >60% of aerial images), medium exposure (40-60%), and low exposure ( I strived to determine if one can detect a successional relationship of benthic communities in a dynamic environment with annual mapping. I also examined if areas with higher exposure rates have more complex successive communities than those with lower exposure rates, and what implications this has on near shore benthic communities. In situ surveys conducted at 117 sites determined the community structure (corals, octocorals, macroalgae, and hydroids). This study confirmed that periodic mapping was successful in identifying hardbottom burial and exposure, which fluctuate both spatially and temporally. This periodic mapping along with manual delineation did identify hardbottom burials and exposures that fluctuate between years and relate to benthic community differences. The near shore hardbottom coral reef communities aligned with the observed exposure categories with the greater coral species richness and octocoral morphologies found at sites classified as highly exposed. Statistical analyses showed differences in communities shallower and deeper than three meters’ depth. Increasing the frequency of imagery captures and in situ observation would further increase our comprehension of the metrics of hardbottom exposures in reference to community structure.

The aim of this study was to develop and examine the use of backscatter data collected with multibeam sonar (MBS) systems for benthic habitat mapping. Backscatter data were collected from six sites around the Australian coastal zone using the Reson SeaBat 8125 MBS system operating at 455 kHz. Benthic habitats surveyed in this study included: seagrass meadows, rhodolith beds, coral reef, rock, gravel, sand, muddy sand, and mixtures of those habitats. Methods for processing MBS backscatter data were developed for the Coastal Water Habitat Mapping (CWHM) project by a team from the Centre for Marine Science and Technology (CMST). The CMST algorithm calculates the seafloor backscatter strength derived from the peak and integral (or average) intensity of backscattered signals for each beam. The seafloor backscatter strength estimated from the mean value of the integral backscatter intensity was shown in this study to provide an accurate measurement of the actual backscatter strength of the seafloor and its angular dependence. However, the seafloor backscatter strength derived from the peak intensity was found to be overestimated when the sonar insonification area is significantly smaller than the footprint of receive beams, which occurs primarily at oblique angles. The angular dependence of the mean backscatter strength showed distinct differences between hard rough substrates (such as rock and coral reef), seagrass, coarse sediments and fine sediments. The highest backscatter strength was observed not only for the hard and rough substrate, but also for marine vegetation, such as rhodolith and seagrass. The main difference in acoustic backscatter from the different habitats was the mean level, or angle-average backscatter strength. However, additional information can also be obtained from the slope of the angular dependence of backscatter strength. / It was shown that the distribution of the backscatter. The shape parameter was shown to relate to the ratio of the insonification area (which can be interpreted as an elementary scattering cell) to the footprint size rather than to the angular dependence of backscatter strength. When this ratio is less than 5, the gamma shape parameter is very similar for different habitats and is nearly linearly proportional to the ratio. Above a ratio of 5, the gamma shape parameter is not significantly dependent on the ratio and there is a noticeable difference in this parameter between different seafloor types. A new approach to producing images of backscatter properties, introduced and referred to as the angle cube method, was developed. The angle cube method uses spatial interpolation to construct a three-dimensional array of backscatter data that is a function of X-Y coordinates and the incidence angle. This allows the spatial visualisation of backscatter properties to be free from artefacts of the angular dependence and provides satisfactory estimates of the backscatter characteristics. / Using the angle-average backscatter strength and slope of the angular dependence, derived by the angle cube method, in addition to seafloor terrain parameters, habitat probability and classification maps were produced to show distributions of sand, marine vegetation (e.g. seagrass and rhodolith) and hard substrate (e.g. coral and bedrock) for five different survey areas. Ultimately, this study demonstrated that the combination of high-resolution bathymetry and backscatter strength data, as collected by MBS, is an efficient and cost-effective tool for benthic habitat mapping in costal zones.