Active Acoustic Data Research Articles

Influence of ocean dynamics on Cuvier’s beaked whale (Ziphius cavirostris): Presence and their prey

Cuvier’s beaked whales (Ziphius cavirostris; Zc) dive below 1000 m to forage predominantly on deep-sea squids. The impact of oceanographic conditions on Zc prey and the effects of anthropogenic sounds on Zc foraging remain unclear. Zc prey distribution is patchy and potentially influenced by mesoscale oceanographic features interacting with local bathymetry. Favorable environmental conditions lead to aggregations of lower trophic level species that attract squid, and potentially increase Zc presence. We collected simultaneous active and passive acoustic data in Tanner Basin, a southern California submarine canyon, intermittently between 2017 and 2022. Passive acoustic data revealed Zc were present throughout all years, with lower presence during late summer and fall. Subsurface Zc 3D track reconstructions indicated a preference for one side of the canyon, where Zc foraged within a layer of potential prey, detected from active acoustic data. Prey concentrations, quantified as volume backscatter strength below ∼1150 m depth, exhibited an increase following the passage of mesoscale features, which were measured using Finite-size Lyapunov Exponents (FSLE). These prey increases drove immediate increases in Zc presence. Understanding potential physical drivers of Zc predator-prey dynamics is a critical first step for assessing natural variability and potential impacts of sonar use on Zc foraging behavior.

Variability in acoustic backscatter and fish school abundance at a shallow water CCS site

Carbon capture and storage (CCS) is one approach used to reduce carbon dioxide (CO2) emissions to the atmosphere. Subsea CO2 storage sites must have low risk of leakage and have minimal impact on the marine environment. Single beam echosounders (SBES) are a good technology for detecting CO2 leakage in the water column for application in a marine Measurement, Monitoring and Verification (MM&V) framework. Characterisation of active acoustic data is needed to determine whether levels of water column backscatter enable CO2 gas leaks to be detected, and to understand acoustic false positives caused by naturally occurring acoustic signals (e.g., fish schools). We used acoustic data collected by SBES fitted to two mobile and two fixed sensor platforms over four years to characterise the site of the proposed CarbonNet CCS Project subsurface CO2 storage reservoir. We observed diel and seasonal variability in water column backscatter and fish school abundance. Water column backscatter was highest at night and in Austral summer and autumn periods but was at a level that would allow small CO2 gas leaks to be detected. Fish abundance was highest during the day and in Austral summer and autumn. To reduce the likelihood of acoustic false positives, surveys designed to detect CO2 gas leaks using active acoustic technologies could prioritise data collection at night and during the months where fish school abundance is lowest. Understanding these sources of natural variability can guide survey strategies and response actions.

Antarctic krill (Euphausia superba) distributions, aggregation structures, and predator interactions in Bransfield Strait

The Antarctic krill, Euphausia superba, is a major component of the Southern Ocean’s ecosystem. Limited high-resolution data on the relative importance of oceanographic processes on the behavioral responses of krill at traditional predator foraging grounds constitutes a major obstacle in the understanding of krill-environment coupling and ecosystem-based management of this resource. Aggregation structures of krill and predator interactions were investigated using active acoustic data collected by WBAT echosounders deployed on moorings in two hydrographically different sites in Bransfield Strait. Near Nelson Island, water flows from the northwest to southeast while Deception Island is influenced by stronger net current velocities from the southwest to northeast. Krill aggregations were identified and then classified in three clusters using a swarm-identification algorithm and hierarchical clustering using aggregation morphological characteristics: acoustic density, mean depth, center of mass, inertia, equivalent area, aggregation index, and proportion occupied. A total of 693 and 736 aggregations were detected at the mooring sites close to Nelson and Deception Islands. The three aggregation categories ranged from high to low densities, evenness, and dispersion and were distributed throughout the water column. Krill aggregation density distribution and mean thickness are influenced by krill mean depth, current velocities and direction. The majority of observed predator dive profiles occurred over the aggregation type with highest krill densities at both Nelson and Deception Islands, and within the first 25 m of the water column. The heterogeneity of krill aggregations potentially impacts predator foraging strategies and predator–krill interactions in the hydrodynamically active Bransfield Strait.

Underwater Acoustic Signal Detection Using Calibrated Hidden Markov Model with Multiple Measurements.

It is important to find signals of interest (SOIs) when operating sonar systems. A threshold-based method is generally used for SOI detection. However, it induces a high false alarm rate at a low signal-to-noise ratio. On the other side, machine-learning-based detection is performed to obtain more reliable detection results using abundant training data, costing intensive time and labor. We propose a method with favorable detection performance by using a hidden Markov model (HMM) for sequential acoustic data, which requires no separate training data. Since the detection results from HMM are significantly affected by the random initial parameters of HMM, the genetic algorithm (GA) is adopted to reduce the sensitivity of the initial parameters. The tuned initial parameters from GA are used as a start point for the subsequent Baum–Welch algorithm updating the HMM parameters. Furthermore, multiple measurements from arrays are exploited both in determining the proper initial parameters with GA and updating the parameters with the Baum–Welch algorithm. In contrast to the standard random selection of the initial point with single measurement, a stable initial point setting by the GA ensures improved SOI detections with the Baum–Welch algorithm using the multiple measurements, which are demonstrated in passive and active acoustic data. Particularly, the proposed method shows the most confidential detection in finding weak elastic surface waves from target, compared to existing methods such as conventional HMM.

Representative range of acoustic point source measurements in the Chukchi Sea

The use of stationary, active acoustics provides an effective approach to characterize and monitor temporal variability in the abundance and behavior of pelagic organisms, especially in seasonally ice-covered waters of high latitude marine ecosystems. However, point measurements from stationary echosounders are limited in their spatial coverage. A quantification of the spatial area represented by point measurements (i.e., representative range) is required to ensure effective biological characterization and monitoring. Here, concurrent mobile and stationary active acoustic data collected during summers of 2015 and 2017 are used to assess the representative range of fish and zooplankton density measurements from the Chukchi Ecosystem Observatory located at Hanna Shoal, Northeast Chukchi Sea. Six methods used to calculate representative ranges of backscatter means and variances resulted in representative ranges between approximately 0.3 and 86 km, depending on the year and calculation method. Such relatively large representative ranges reflect the tight bio-physical associations and large characteristic environmental length scales of the NE Chukchi Sea. Between years, up to 10-fold variations in representative ranges were attributed to interannual changes in water mass characteristics and associated species assemblages. Differences of 1–2 orders of magnitude in our calculated ranges among methods are attributed to differences in the rationale and associated assumptions of each approach. The choice of method and resulting representative range depends on monitoring goals: detection of change, mapping of spatial distributions, characterization of spatial variance, or interpolation of temporal variability over space. Our comparison of stationary acoustic to mobile surveys extends the understanding of spatiotemporal variability of marine organism distributions in the NE Chukchi Sea and informs cost-effective design of observing systems to monitor and predict impacts of environmental change.

Seamount effects on micronekton at a subtropical central Pacific seamount

Seamounts are globally ubiquitous features with potential for increased biodiversity and biomass, including those of economically important fish. Although their ecological and economical importance is well known, the mechanisms for supporting seamount-associated communities are not well understood. In this study, the effects of an intermediate depth seamount (Cross Seamount) on the micronekton communities, forage for economically important bigeye tuna, are investigated. Relative biomass and composition estimates were calculated from multi-frequency active acoustic data from surveys over 3 years. Mean micronekton biomass was significantly higher than in the ambient environment and its composition differed over the flanks and plateau of Cross Seamount. The effects of the seamount extended ∼3.5 km away from the plateau's edge, possibly further below 400 m depth at the flanks. Micronekton occupied the water column from the surface to the 400 m deep plateau with dense aggregations immediately over the bottom at night. During the day, these micronekton migrated both horizontally and downward, occupying depths of 500–700 m, preferably along the upstream flank of the seamount. Descending micronekton from near-surface waters appeared to be temporarily blocked by the topography before swimming below the plateau at the flanks. Mechanisms supporting the increase in micronekton biomass are uncertain, although hydrographic data support topographic trapping of zooplankton and the existence of transient or semi-permanent Taylor caps.

Intraseasonal variation in southeast Pacific blue whale acoustic presence, zooplankton backscatter, and oceanographic variables on a feeding ground in Northern Chilean Patagonia

Seasonal variation in the acoustic presence of blue whale calls has been widely reported for feeding grounds worldwide, however variation over the submonthly scale (several days to <1 month) has been examined to a much lesser extent. This study combines passive acoustic, hydroacoustic, and in situ oceanographic observations collected at a mooring in the Corcovado Gulf, Northern Chilean Patagonia, from January 2016-February 2017, to examine the temporal variation in blue whale acoustic occurrence and prey backscatter over seasonal and submonthly scales. Time series data for a) Southeast Pacific blue whale song calls and D-calls, b) zooplankton backscatter, c) tidal amplitude, and d) meridional and zonal wind stress were examined visually for seasonal trends. To examine submonthly timescales over the summer feeding season (January-June), wavelet transforms and wavelet coherence were applied; generalized linear models (GLM) were also applied. There was a 3-month lag between the seasonal onsets of high zooplankton backscatter (October) and blue whale acoustic presence (January), and an almost immediate drop in blue whale acoustic presence with the seasonal decrease of backscatter (June). This may be due to the use of memory by animals when timing their arrival on the feeding ground, but the timing of their departure may be related to detection of low prey availability. Over the summer feeding season, blue whale acoustic presence was strongly associated with zooplankton backscatter (GLM coefficient p ≪ 0.0001). Song calls followed a seasonal cycle, but D-calls appeared to respond to short term variations in environmental conditions over submonthly scales. Results suggest that spring tides may increase prey aggregation and/or transport into the Corcovado Gulf, leading to increased blue whale acoustic presence over 15-day or 30-day cycles; and short-lived events of increased wind stress with periodicities of 2–8 days and 16–30 days, may also contribute to the aggregation of prey. We discuss the strengths and limitations of coupling passive and active acoustic data to examine drivers of blue whale distribution.

Seamount effects on the diel vertical migration and spatial structure of micronekton

We examined the diel vertical migration (DVM) behavior and vertical spatial structure of sound-scattering layers (SLs) at two seamounts (Condor and Gigante) in the Azores and in surrounding open-waters. Active acoustic data were recorded day and night during nine cruises conducted in spring, summer and autumn between 2009 and 2011. SLs were permanent features with two main layers, shallow scattering layers (SSLs) and deep scattering layers (DSLs). Over seamount plateaus, SSLs aggregated close to the seafloor during the day and in slightly shallower waters at night. Backscatter intensity on plateaus varied little between day and night and was consistently higher than in SSLs above slopes or in open-waters. DSLs found over slopes and open-waters migrated towards the surface at dusk and returned to their daylight depths at dawn but an intense DSL persisted overnight in deep open-waters. Variograms showed that SSLs and DSLs were not uniformly distributed but amount of spatial heterogeneity varied between seamount plateaus, slopes and open-waters, and day-night periods. Taken together, these findings suggest that (1) Condor and Gigante Seamounts host a resident micronekton community, (2) there is an influx of vertically migrating organisms over the plateaus at night, and (3) seamount topography affects the DVM behavior of the DSL. Physical processes, such as Taylor cap effect, along with topographic blockage and lateral advection of migrating organisms, may play a role in transporting micronekton from open-waters to seamount plateaus. These findings are critical to understanding the ecology of seamount communities and the function of seamount habitats in oceanic ecosystems.

Relationship between cetacean presence, their prey, and oceanographic conditions at an offshore pelagic environment

Large mobile predators take advantage of offshore pelagic environments that tend to be surveyed at a low temporal scale. We present results from a one-year observation of passive and active acoustics, as well as oceanographic measures, taken at a moored location 150 nmi offshore southern California in 4000 m deep pelagic waters. The passive acoustic data shows presence of delphinids and baleen, sperm, and beaked whales throughout the recording period with species-specific seasonal occurrence. Variability in small pelagics, krill, and diel vertical migrators is evident from the active acoustic data. Multiple upwelling events and associated changes in dissolved oxygen at 500 m water depth, as well as in surface waters, were also recorded over the year. We will present results on the relationships among oceanographic variability, presence of pelagic species, and top predator presence. This study will provide valuable information on ecosystem processes in meso- and epipelagic waters on a relatively small spatial scale but very fine temporal scale.

Bio-Inspired Human Action Recognition With a Micro-Doppler Sonar System

This paper explores computational methods to address the problem of doing inference from data in multiple modalities, where there exists a large amount of low dimensional data complementary to a much smaller set of high dimensional data. In this instance the low dimensional time-series data are active acoustics from a bio-inspired micro-Doppler sonar sensor system that include no or very limited spatial information, and the high dimensional data are RGB-depth data from a 3-D point cloud sensor. The task is human action recognition from the active acoustic data. To accomplish this, statistical models, trained simultaneously on both the micro-Doppler modulations induced by human actions and symbolic representations of skeletal poses, derived from the 3-D point cloud data, are developed. This simultaneous training enables the model to learn relations between the rich temporal structure of the micro-Doppler modulations and the high-dimensional pose sequences of human action. During runtime, the model relies purely on the active acoustic sonar data to infer the human action. Our approach is applicable to other sensing modalities, such as the millimeter wave electromagnetic radar devices.

Comparison between trawl volume and composition and acoustic backscatter

Active acoustics is an important tool to quantitatively assess the densities of pelagic organisms. While it is an important tool, it is hard to determine the organism composition recorded acoustically especially in oligotrophic waters where mixed organism assemblages are common. One such mixed stock in the Hawaii Islands is the Deep Scattering Layers (DSL). These layers are made up of micronekton (small squid, fish, and crustaceans) which may be an important component linking primary producers with higher trophic levels. Trawling can identify the composition in these layers but this tool can be costly and unable to sample as much area as active acoustics. Many organisms in the DSL diurnally migrate to the surface between 0 and 200 m to feed. We surveyed these organisms using active acoustics and trawling collected in June 2013 and March 2014 on the R/V Oscar Elton Sette. We compared the composition of organisms, volume by functional group, and total volume in the trawl with the acoustic backscatter to determine the relationship between trawl and active acoustic data. We determined that the acoustic densities changed as a function of the trawl composition and volume potentially allowing for the ability to exclusively use acoustics in the future.

The R package EchoviewR for automated processing of active acoustic data using Echoview

Acoustic data is time consuming to process due to the large data size and the requirement to often undertake some data processing steps manually. Manual processing may introduce subjective, irreproducible decisions into the data processing work flow, reducing consistency in processing between surveys. We introduce the R package EchoviewR as an interface between R and Echoview, a commercially available acoustic processing software package. EchoviewR allows for automation of Echoview using scripting which can drastically reduce the manual work required when processing acoustic surveys. This package plays an important role in reducing subjectivity in acoustic data processing by allowing exactly the same process to be applied automatically to multiple surveys and documenting where subjective decisions have been made. Using data from a survey of Antarctic krill, we provide two examples of using EchoviewR: krill estimation and swarm detection.

Overcoming energy spreading loss (ESL) for characterization of broadband frequency dispersion

A shallow water, high-frequency active acoustic data set is being examined for the existence of a broadband frequency dispersion phenomena (BDP). Two scenarios, an up-slope source-to-receiver propagation path and a shallow-to-shallow path are studied in detail using a time domain finite element parabolic equation model and measured environmental parameters. It was expected that the analysis of the shot data from the AEAS exercise off the Pacific West Coast would result in confirmation that echoes or reflection events from bottom reflectors would be distinguishable from echoes of water column reflectors. This expected result could be detected only for the up-slope propagation path where energy spreading loss (ESL) was relatively low. The shallow-to-shallow propagation paths were dominated by ESL and it was determined that the ESL must be modeled accurately before the BDP can be analyzed and utilized for very shallow water propagation paths. ESL is modeled for the two propagation scenarios and the impact of ESL on active high-frequency operations in very shallow water is discussed. Signal processing solutions to ESL degradation are also presented. [This work was funded by the Office of Naval Research.]