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Assessing marine fish community size spectra with hydroacoustics is challenging, as communities are diverse, schooling and swim-bladder-less fishes are common, and fish orientation is variable. We developed an approach to examine these challenges and applied it to data from 51 optic–acoustic surveys of fishes at petroleum platforms throughout the US Gulf of Mexico. When in situ target strength (TS; dB re 1 m2) distributions were used to calculate the density (and subsequently abundance) of schooling fishes, fish lengths and size spectra slopes were significantly smaller than in simulated communities and fish community censuses at platforms (i.e., reference datasets). However, acoustic slopes were comparable to reference slopes when simulated TS values (based on species composition) were used to calculate schooling fish abundance. These findings held regardless of whether specific or general models were used to convert TS to length. Fish orientation was not a useful predictor of TS or slope, but may explain why in situ TS measurements from small groups of fishes around schools were unsuitable for abundance calculations. By examining the challenges associated with assessing size spectra with acoustics, this study aids progress towards using acoustic size spectra metrics for ecological inferences. [ABSTRACT FROM AUTHOR]

Ocean fronts can cause the accumulation of nutrients and affect the propagation of underwater sound, so high-precision ocean front detection is of great significance to the marine fishery and national defense fields. However, the existing ocean front detection methods either have low detection accuracy or regard it as a binary classification problem to only detect where the ocean front occurs and cannot identify and distinguish various categories of ocean fronts with different behavior characteristics in different times and regions. In order to solve the above problems, we propose a semantic segmentation network called location and seasonality enhanced network (LSENet) for multiclass ocean fronts detection at pixel level. In this network, we first design a channel supervision unit (CSU) structure, which integrates the seasonal characteristics of the ocean front itself and the contextual information to improve the detection accuracy. We also introduce a location attention (LA) mechanism to adaptively assign attention weights to the fronts according to their frequently occurred sea area, which can further improve the accuracy of multiclass ocean front detection. Compared with other semantic segmentation methods and current representative ocean front detection method at Offshore China and Gulf of Mexico, the experimental results demonstrate convincingly that our method is more effective. The source code and datasets are released and publicly available via https://github.com/lliusha1155/LSENET. [ABSTRACT FROM AUTHOR]

Autonomous platforms and vehicles are a growing component of the ocean research fleet, producing data sets crucial to our understanding of oceanographic and fishery ecosystem processes. One emerging tool for making these measurements is underwater gliders that autonomously sample the water column for weeks to months at a time. Although originally designed to measure temperature and salinity, underwater gliders can now support a myriad of sensors. For the demonstration project described within, three complementary acoustic technologies were integrated into an underwater glider for mapping fish on the continental shelf: an acoustic telemetry receiver, a passive acoustic monitoring recorder, and a fisheries echosounder. The demonstration project was designed to evaluate the effectiveness of each sensing technology. Sixty-one fish were implanted with acoustic tags near the Gulfstream Natural Gas pipeline in the eastern Gulf of Mexico in advance of planned underwater glider missions. The glider was deployed four times over 12 months, with all three acoustic technologies to traverse the pipeline and surrounding habitat. Glider detections were compared to detections of fish at moored acoustic tag telemetry receivers and passive acoustic recorders co-located at the tagged fish locations. All three technologies identified fish along the targeted hard-bottom pipeline habitat, as well as previously uncharted areas of hard-bottom reef. The results of this study demonstrate the utility of gliders integrated with acoustic sensors as a potential tool to identify areas that merit deeper investigation to assess fish stocks. [ABSTRACT FROM AUTHOR]

Sound scattering layers (SSLs) are important components of oceanic ecosystems with ubiquitous distribution throughout the world's oceans. This vertical movement is an important mechanism for exchanging organic matter from the surface to the deep ocean, as many of the organisms comprising SSLs serve as prey resources for linking the lower trophic levels to larger predators. Variations in abundance and taxonomic composition of mesopelagic organisms were quantified using repeated discrete net sampling and acoustics over a 30-h survey, performed during 26–27 June 2011 at single site (27°28’51”N and 88°27’54”W) in the northern Gulf of Mexico. We acoustically classified the mesopelagic SSL into four broad taxonomic categories, crustacean and small non-swimbladdered fish (CSNSBF), large non-swimbladdered fish (LNSBF), swimbladdered fish (SBF) and unclassified and we quantified the abundance of mesopelagic organisms over three discrete depth intervals; epipelagic (0–200 m); upper mesopelagic (200–600 m) and lower mesopelagic (600–1000 m). Irrespective of the acoustic categories at dusk part of the acoustic energy redistributed from the mesopelagic into the upper epipelagic (shallower than 100 m) remaining however below the thermocline depth. At night higher variability in species composition was observed between 100 and 200 m suggested that a redistribution of organisms may also occur within the upper portion of the water column. Along the upper mesopelagic backscatter spectra from CSNSBF migrated between 400 and 460 m while spectra from the other categories moved to shallower depths (300 and 350 m), resulting in habitat separation from CSNSBF. Relatively small vertical changes in both acoustic backscatter and center of mass metrics of the deep mesopelagic were observed for CNSBF and LNSBF suggesting that these animals may be tightly connected to deeper (below 1000 m) mesopelagic habitats, and do not routinely migrate into the epipelagic. [ABSTRACT FROM AUTHOR]

Remotely operated vehicles (ROVs) provide a non-extractive approach to characterizing fish communities in complex habitats. Despite the demonstrated effectiveness of ROVs in studying reef fishes over natural hard-bottom and small artificial reefs, there has been little application of this technology to larger artificial structures (10s of m tall and wide). We explored the utility of ROVs in rapidly characterizing an assemblage of fishes associated with an artificial reef complex in the western Gulf of Mexico (26.9–28.2° N; 95.5–97.0° W) dominated by partially removed and toppled oil and gas platforms. This study reports on an efficient method to sample these structures, where we integrated depth-interval transect (DIT) and continuous roving transect (CRT) protocols to document fish distribution and community structure on 14 artificial reef sites. Consistent with previous hydroacoustic studies, south Texas artificial reefs exhibited a vertically heterogeneous distribution of fishes that varied with structure orientation. These reefs were dominated by economically important lutjanids and carangids, both of which presented sampling challenges due to their patchy distribution around these vast structures. The non-uniform distribution and mobility of these dominant taxa highlight the utility of adopting roving approaches to assess fish communities on these complex structures. We conclude our study with a discussion of important logistical challenges associated with micro-ROV surveys in deepwater habitats, and potential complementary approaches to assist documentation of demersal fishes inhabiting a persistently turbid bottom layer. [ABSTRACT FROM AUTHOR]

In the Gulf of Mexico (GOM), fish biomass estimates are necessary for the evaluation of habitat use and function following the mandate for ecosystem-based fisheries management in the recently reauthorized Sustainable Fisheries Act of 2007. Acoustic surveys have emerged as a potential tool to estimate fish biomass in shallow-water estuaries, however, the transformation of acoustic data into an index of fish biomass is not straightforward. In this article, we examine the consequences of equation selection for target strength (TS) to fish length relationships on potential error generation in hydroacoustic fish biomass estimates. We applied structural equation models (SEMs) to evaluate how our choice of an acoustic TS–fish length equation affected our biomass estimates, and how error occurred and propagated during this process. To demonstrate the magnitude of the error when applied to field data, we used SEMs on normally distributed simulated data to better understand the sources of error involved with converting acoustic data to fish biomass. As such, we describe where, and to what magnitude, error propagates when estimating fish biomass. Estimates of fish lengths were affected by measurement errors of TS, and from inexact relationships between fish length and TS. Differences in parameter estimates resulted in significant differences in fish biomass estimates and led to the conclusion that in the absence of known TS–fish length relationships, Love’s (J Acoust Soc Am 46:746–752, ) lateral-aspect equation may be an acceptable substitute for an ecosystem-specific TS–fish length relationship. Based upon SEMs applied to simulated data, perhaps the most important, yet most variable, component is the mean volume backscattering strength, which significantly inflated biomass errors in approximately 10% of the cases. [ABSTRACT FROM AUTHOR]

Whistle characteristics were quantitatively compared between both geographically separated and neighboring populations of Atlantic spotted dolphins ( Stenella frontalis), bottlenose dolphins ( Tursiops truncatus), and pilot whales ( Globicephala spp.) in U.S. waters to evaluate if intraspecific acoustic differences exist between groups. We compared nine whistle characteristics between continental shelf and offshore Atlantic spotted dolphins in the western North Atlantic and between northern Gulf of Mexico and western North Atlantic bottlenose dolphins and pilot whales using discriminant analysis. Offshore Atlantic spotted dolphin whistles were significantly different (Hotelling's T2, P= 0.0003) from continental shelf whistles in high frequency, bandwidth, duration, number of steps, and number of inflection points. Atlantic bottlenose dolphin whistles were significantly different (Hotelling's T2, P < 0.0001) from those in the Gulf of Mexico in duration, number of steps, and number of inflection points. There was no significant difference between pilot whale whistles in the two basins. The whistle differences indicate acoustic divergence between groups in different areas that may arise from geographic isolation or habitat separation between neighboring but genetically distinct populations of dolphins. This study supports the premise that acoustic differences can be a tool to evaluate the ecological separation between marine mammal groups in field studies. [ABSTRACT FROM AUTHOR]

A recently introduced theoretical model of wave propagation in an unconsolidated, sandy marine sediment is discussed in this article. Essentially, the model consists of four analytical expressions, which specify four wave properties of the sediment, namely the speed and attenuation of the compressional and the shear wave. These expressions contain just three unknown constants, which must be evaluated from data. A technique is described in which these constants are determined from measured values of the compressional wave speed, the shear wave speed, and the shear wave attenuation. This technique is applied to preliminary data from O.N.R.s SAX'99 recent experiment on a sandy sediment in the Gulf of Mexico. From the fully specified equations, the fourth wave property, the attenuation of the compressional wave, is computed and found to lie within 0.5 dB/m of the measured value. Based on this limited evidence, it appears that the wave properties of an unconsolidated sediment are highly correlated and predictable. According to the theory, the causal connections between the wave properties originate in the sliding of one micro-asperity against another on the surfaces of contact between contiguous grains in the medium. [ABSTRACT FROM AUTHOR]

Passive acoustic monitoring (PAM), particularly autonomous platforms, offers many advantages in monitoring phonating deep-diving marine mammals in oceanic environment. Relevant data can be obtained day and night continuously over long durations and in any weather conditions. It provides a cost-efficient solution with greater detection ranges when compared to traditional large research vessel and aerial visual surveys requiring keeping expert observers on station for long periods of time and relying on good visibility and calm seas. Therefore, PAM is becoming a preferred tool to assess population dynamics trends and health of deep-water marine mammal stocks. However the large volumes of collected data require robust automatic detection and classification algorithms to identify marine mammals in recordings. As for beaked whales, one of the challenging automatic processing goals is the identification of different species to advance our understanding of their role in the marine ecosystem. At present, traditional detection and classification methods employ searches for acoustic events above a user-defined signal-to-noise ratio threshold in the frequency band of interest and further rely on an experienced operator's manual inspection for species classification and removal of false positives. Current passive monitoring data collection systems yield large volumes of acoustic data, therefore a manual classification approach becomes very time-consuming and impractical. This paper focuses on developing a multi-stage automatic classifier for beaked whale species. The proposed method utilizes unsupervised machine clustering of signal attributes extracted from potential detection events flagged by an energy-band detector. The proposed algorithm was benchmarked against a manually annotated workshop dataset and applied to acoustic data collected in the northern Gulf of Mexico. The algorithm classifies beaked whale species in automatic mode with minimal operator involvement only at the validation stage. When compared with the manually annotated classification dataset, the proposed method achieved a recall rate of 82.8% for Cuvier's and 77.9% for Gervais' species in automatic mode. New insights on habitat use by different species of beaked whales in the Gulf of Mexico were gained when using the species-specific classifier. The high spatial resolution acoustic monitoring results showed that the habitat preferences of two dominating beaked whale species in the Gulf of Mexico support the habitat division (ecological niche) hypothesis. • Signal-based unsupervised clustering to detect beaked whale species in acoustic data. • Automatic detector performance is fully competitive with expert annotations. • Observations of habitat division between beaked whale species in the Gulf of Mexico. • Insights into unknown beaked whale calls observed in the Gulf of Mexico. [ABSTRACT FROM AUTHOR]

The articles presents several research studies related to acoustics or sound. It states that scientists at the U.S. Naval Research Laboratory have investigated the acoustic characteristics of the deep seafloor in the Gulf of Mexico. It says that researchers from the University of Auckland have found out that noise-induced hearing loss in rats can be recovered via a new drug. Marine scientists say that North American right whales increase their calls' volume as environmental noise rises.