Abstract:Small remotely operated vehicles (ROVs), sometimes described as low-cost (<$150,000) ROVs, have become valuable tools in the study of marine organisms and their habitats. The versatility and relative simplicity of these vehicles is enabling scientists and fishery managers to develop a better understanding of the marine ecosystem that has not been possible using conventional survey methodologies. The ability to work at depths beyond the reach of scuba divers and in complex habitats inaccessible to trawl surveys… Show more
“…If, for example, only one constituent was present, such as cobbles, then the coding would be C/C indicating that both the primary and secondary sediment grain size are of the same clast size. Below are the sediment grain size combinations that are used to characterize the coarse-grain substrate types: smB/C/P ¼small boulder/cobble/pebble C/smB/P ¼cobble/small boulder/pebble C/P/smB ¼cobble/pebble/small boulder P/C/smB ¼pebble/cobble/small boulder C/C ¼cobble/cobble (a single clast size) C/P¼cobble/pebble P/C ¼pebble/cobble lgB¼ large size boulder mB¼ medium size boulder smB¼ small size boulder These grain size combinations are consistent with that used to describe marine benthic habitat characteristics by Lynch et al (2004), Anderson and Yoklavich (2007), and Pacunski et al (2008). Below are the sediment grain size combinations that are used to characterize the fine-grain substrate types: C/P/gr ¼cobble/pebble/gravel P/C/gr ¼pebble/cobble/gravel P/gr/C ¼pebble/gravel/cobble gr/C/P ¼gravel/cobble/pebble gr/P/C ¼gravel/pebble/cobble gr/gr ¼gravel/gravel (single grain size) s/s ¼sand/sand (single grain size) …”
“…If, for example, only one constituent was present, such as cobbles, then the coding would be C/C indicating that both the primary and secondary sediment grain size are of the same clast size. Below are the sediment grain size combinations that are used to characterize the coarse-grain substrate types: smB/C/P ¼small boulder/cobble/pebble C/smB/P ¼cobble/small boulder/pebble C/P/smB ¼cobble/pebble/small boulder P/C/smB ¼pebble/cobble/small boulder C/C ¼cobble/cobble (a single clast size) C/P¼cobble/pebble P/C ¼pebble/cobble lgB¼ large size boulder mB¼ medium size boulder smB¼ small size boulder These grain size combinations are consistent with that used to describe marine benthic habitat characteristics by Lynch et al (2004), Anderson and Yoklavich (2007), and Pacunski et al (2008). Below are the sediment grain size combinations that are used to characterize the fine-grain substrate types: C/P/gr ¼cobble/pebble/gravel P/C/gr ¼pebble/cobble/gravel P/gr/C ¼pebble/gravel/cobble gr/C/P ¼gravel/cobble/pebble gr/P/C ¼gravel/pebble/cobble gr/gr ¼gravel/gravel (single grain size) s/s ¼sand/sand (single grain size) …”
“…The focal survey area (San Juan Channel) was selected based on the availability of high-resolution bathymetric habitat maps for this region (G. Greene unpubl.). Detailed maps were used to randomly select sites that covered a broad spatial area and represented all available habitat types seen in prior ROV and dredge surveys (Pacunski et al 2008). …”
Section: Methodsmentioning
confidence: 99%
“…Acquisition of ROV video in field-Surveys from 4-to 131-m depth were conducted between 30 September and 20 October 2004 using a Deep Ocean Engineering Phantom HD2+2 ROV (Pacunski et al 2008). The ROV was equipped with six thrusters and a Sony EVI-330 highresolution color zoom camera with tilt capability.…”
Section: Methodsmentioning
confidence: 99%
“…In this arrangement, the ROV was free to explore the substratum within a fixed radius (determined by the amount of tether) of the clump weight, and the vessel followed the ROV from above as it swam the transect. See Pacunski et al (2008) for further technical details on ROV equipment and survey protocol.…”
We used a remotely operated vehicle to investigate landscape-scale patterns of subtidal drift material and invertebrates within a 60-km 2 marine basin in Washington State. Specifically, we quantified the distribution and abundance of drift macrophytes (seaweed and seagrass) and four macroinvertebrate species across depth and habitat type to depths of 170 m. Drift macrophytes were present on 97% of all video segments deeper than 30 m, with large drift piles particularly associated with low-angle habitats at depths exceeding 70 m. Two commercially harvested species (Strongylocentrotus franciscanus and Pandalus platyceros) that feed directly on drift material appear to be distributed in space (depth and substrate type) so as to maximize access to drift macrophyte food resources, according to their respective feeding modes. Basin shape and depth drive the landscape-scale distribution of drift material and indirectly the consumers that feed on it. The export of large amounts of detritus derived from nearshore macrophyte production into deep-water habitats likely fuels extensive secondary production in these aphotic zones.Nearshore macrophyte production contributes a substantial amount of carbon to high-latitude marine ecosystems. Much of this production is exported as macroscopic detritus (i.e., drift) to adjacent deeper, aphotic habitats (Mann 1988;Okey 2003). Despite the absence of endogenous carbon sources, these deep subtidal environments (DSE) often support considerable secondary productivity (Vetter 1995;Vetter and Dayton 1999;Britton-Simmons et al. 2009) and are a key source of commercial fisheries worldwide (Food and Agriculture Organization 2007). However, subtidal population and process-focused studies are typically constrained to depths accessible by divers and to relatively small spatial scales. In the present study, we examined the landscape-scale distribution and abundance of drift macrophytes and select invertebrates within the San Juan Archipelago (SJA), a 60-km 2 marine basin, in Washington State.Subtidal drift macrophytes in our system are produced by a diverse assemblage of nearshore seaweeds and seagrasses that diminish in abundance below 18 m and become rare by 23-m depth (Britton-Simmons et al. 2009) due to light limitation. Most subtidal drift biomass is contributed by kelps (order Laminariales) with substantial contributions also made by orders Fucales and Desmarestiales. Seagrasses (mostly Zostera marina) are present in the drift but contribute relatively little to biomass (BrittonSimmons et al. 2009). Drift material is an excellent food resource since it tends to have elevated levels of nitrogen (Mann 1988) and diminished levels of defensive chemicals (Duggins and Eckman 1997). This resource could be important for driving marine secondary productivity in DSE, but we know little about its distribution among depths and habitat types within DSE. Moreover, we need key information about where this material is distributed relative to the taxa that could be using it (Suchanek et al. 1985;Ve...
“…In [6] a laser light is used to inspect internal structure of a pipeline. In [7] was showed the real use in shallow water of a pair of laser to estimate the width, but the method does not consider the camera calibration in the process of distance estimation, and the angle information is not provided. The use of stereo vision is also possible to estimate the distance to some target [8], [9], but it fails in normal underwater condition due to the difficulty in obtaining the disparity map.…”
Nowadays, the ocean plays a fundamental role in the global economy, mainly due to oil extraction industry. It makes this environment be populated with human-made structures that needs to be inspected and maintained. In this context, this paper details a system for real-time detecting an underwater flat target using computer vision algorithms and a dual laser emitter. This enable an underwater vehicle to track the target, as well as control distance between the target to be inspected and the vehicle. The system could be used to assist a human operator during inspection tasks. This work is concluded with a series of tests and analyses aiming to the system validation.
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