Using a Multibeam Echosounder to Monitor an Artificial Reef

Abstract

ABSTRACT:Artificial reefs (ARs) have become popular technological interventions in shallow water environments characterized by soft seabed for a wide number of purposes, from fisheries/environmental protection and enhancement to research and tourism. AR deployment has the potential for causing significant hydrographical and biological changes in the receiving environments and, in turn, ARs are strongly affected by the surrounding area in terms of spatial arrangement and structural integrity as well as colonization by benthic communities and finfish. In this context, ARs require a systematic monitoring program that a multibeam echosounder (MBES) can provide better than other sampling methods such as visual dives and ROV inspections that are not quantitative and often influenced by water visibility and diver experience/skills. In this paper, some subsequent MBES surveys of the Senigallia scientifically-planned AR (Northern Adriatic Sea) are presented and state-of-the art data processing and visualization techniques are used to draw post-reef deployment comparisons and quantify the evolution of the reef in terms of spatial arrangement and bulk volume. These multibeam surveys play a leading part in a general multi-year program, started simultaneously with the AR design and deployment and aimed to map how the reef structure quantitatively changes over time, as well as it affects the sea-bottom morphology and the fishery resource. All the data, surveyed over years making use of different sampling methods such as visual and instrumental echosounding observations and catch rate surveys, gain a mechanistic and predictive understanding of how the Senigallia AR functions ecologically and physically across spatial and temporal scales during its design life.

Artificial structure selection by economically important reef fishes at North Carolina artificial reefs

“…However, it is important to note that artificial structures can change over time and the current structure condition may not be completely representative of the condition of the structure when it was deployed. For example, lower relief structures such as reef balls and concrete pipes can be buried in sand and higher profile structures such as vessels could collapse or break down, changing the physical characteristics of the structure such as area, perimeter, or relief (Tassetti et al, 2015). We did not examine these quantitative metrics in this study, but they should be considered in future work.…”

Characterizing the three‐dimensional distribution of schooling reef fish with a portable multibeam echosounder

“…The bathymetry surface was then offset by 1 m to provide a small buffer for manually rendered structures and seafloor detection anomalies (Ona and Mitson 1996) and was subsequently imported back into Echoview (Step M6) so that seafloor and surface data could be masked out (Step M7). It is important to note that due to the high level of accuracy required for this bathymetry surface, it should ideally be generated from this concurrent MBES data, rather than relying on archival data, as the interaction of currents and benthic organisms with artificial reef structures can gradually alter seafloor morphology (Tassetti et al 2015) and reef structures may shift and deteriorate over time (Sala et al 2007).…”

Artificial Reef Detection Method for Multibeam Sonar Imagery Based on Convolutional Neural Networks

“…With the development of modern sonar technology, detectors that are based on acoustic methods have become the most effective and efficient technical means for seabed detection. The multibeam sonar detector, which is an advanced acoustic detector, has become an important technical means for the monitoring of artificial reefs on the seabed [14][15][16]. Artificial reef detection in multibeam sonar images usually relies on visual interpretation, which has the disadvantages of a large workload and high labor costs.…”