Search

Shoreward intrusions of anomalously salty water along the continental shelf of the Middle Atlantic Bight are often observed in spring and summer. Exchange of heat, nutrients, and carbon across the salinity-intrusion front has a significant impact on the marine ecosystem and fisheries. In this article, we developed a method of using an autonomous underwater vehicle (AUV) to detect a salinity-intrusion front and track the front's movement. Autonomous front detection is based on the different vertical structures of salinity in the two distinct water types: the vertical difference of salinity is large in the intruding saltier water because of the salinity “tongue” at mid-depth, but is small in the nearshore fresher water due to absence of the salinity anomaly. Every time the AUV crosses and detects the front, the vehicle makes a turn at an oblique angle to cross the front, thus zigzagging through the front to map the frontal zone. The AUV's zigzags sweep back and forth to track the front as it moves over time. From June 25 to 30, 2021, a Tethys-class long-range AUV mapped and tracked a salinity-intrusion front on the southern New England shelf. The frontal tracking revealed the salinity intrusion's 3-D structure and temporal evolution with unprecedented detail. [ABSTRACT FROM AUTHOR]

Phytoplankton (microscopic algae) play an important role in marine ecology. Resulting from a combination of physical, chemical, and biological processes, the distribution of phytoplankton is patchy, particularly in coastal marine ecosystems. Patches of high chlorophyll represent areas where enhanced primary productivity and biogeochemical cycling can occur. The scientific goal is to place observations within these biological hotspots to enable more extensive characterization of the environment and plankton populations. Aerial or satellite remote sensing can detect optical signal originating from phytoplankton within a limited depth range only near the ocean surface, and application of remote sensing is limited by atmospheric clarity. To observe the development of patchy phytoplankton communities in situ, we need the ability to locate and track individual patches. In this article, we present a method for an autonomous underwater vehicle (AUV) to autonomously find and climb on a positive horizontal gradient of chlorophyll to locate and track a phytoplankton patch. In two experiments in 2021, a Tethys-class long-range AUV autonomously located and tracked phytoplankton patches in southern Monterey Bay, CA, USA. The experiments demonstrated effectiveness of the method and pointed to the need for increased onboard adaptiveness in autonomous patch finding and tracking. [ABSTRACT FROM AUTHOR]

Many pelagic animals, such as krill, lanternfish, and cephalopods, migrate to deep water at dawn to avoid visual predators during daylight hours and move up toward the sea surface at dusk to search for food. This behavior is termed “diel vertical migration.” Migrating animals graze on phytoplankton or zooplankton and in turn serve as food for higher trophic levels, hence providing a key mechanism for carbon export via this migration. These animals are often observed as sound-scattering layers by echosounders, but the animals causing the acoustic scattering are difficult to identify using acoustics alone. In a spring 2019 experiment in Monterey Bay, we deployed autonomous underwater and surface vehicles over a seabed-mounted upward-looking echosounder to collect environmental DNA (eDNA) with the goal of identifying the vertically migrating animals. The echosounder was installed at 890-m depth on the Monterey Accelerated Research System (MARS) seabed cabled ocean observatory, providing real-time data of acoustic backscatter from the full water column. One long-range autonomous underwater vehicle (LRAUV) carrying a Third-Generation Environmental Sample Processor (3G-ESP) acquired water samples from a sequence of layers from near surface down to ~ 290 m as directed by the distribution of animals observed by the echosounder. During the sampling of each layer, the LRAUV ran on a tight circular yo-yo trajectory directly above the echosounder, remaining in its beam by acoustically tracking a station-keeping Wave Glider on the sea surface marking the echosounder's latitude and longitude. The persistent and simultaneous acoustic observation and eDNA acquisition enables identification of animals at precise locations to better understand their vertical migration behaviors. We present the methods and the system performance in the experiment. [ABSTRACT FROM AUTHOR]

Phytoplankton communities residing in the open ocean, the largest habitat on Earth, play a key role in global primary production. Through their influence on nutrient supply to the euphotic zone, open-ocean eddies impact the magnitude of primary production and its spatial and temporal distributions. It is important to gain a deeper understanding of the microbial ecology of marine ecosystems under the influence of eddy physics with the aid of advanced technologies. In March and April 2018, we deployed autonomous underwater and surface vehicles in a cyclonic eddy in the North Pacific Subtropical Gyre to investigate the variability of the microbial community in the deep chlorophyll maximum (DCM) layer. One long-range autonomous underwater vehicle (LRAUV) carrying a third-generation Environmental Sample Processor (3G-ESP) autonomously tracked and sampled the DCM layer for four days without surfacing. The sampling LRAUV's vertical position in the DCM layer was maintained by locking onto the isotherm corresponding to the chlorophyll peak. The vehicle ran on tight circles while drifting with the eddy current. This mode of operation enabled a quasi-Lagrangian time series focused on sampling the temporal variation of the DCM population. A companion LRAUV surveyed a cylindrical volume around the sampling LRAUV to monitor spatial and temporal variation in contextual water column properties. The simultaneous sampling and mapping enabled observation of DCM microbial community in its natural frame of reference. [ABSTRACT FROM AUTHOR]

Studies of marine physical, chemical, and microbiological processes benefit from observing in a Lagrangian frame of reference. Some of these processes are related to specific density or temperature ranges. We have developed a method for a Tethys-class long-range autonomous underwater vehicle (LRAUV) (which has a propeller and a buoyancy engine) to track a targeted isothermal layer (within a narrow temperature range) in a stratified water column when operating in buoyancy-controlled drift mode. In this mode, the vehicle shuts off its propeller and autonomously detects the isotherm and stays with it by actively controlling the vehicle's buoyancy. The LRAUV starts on an initial descent to search for the target temperature. Once the temperature falls in the target center bracket, the vehicle records the corresponding depth and adjusts buoyancy to hold that depth. As long as the temperature stays within a tolerance range, the vehicle continues to hold that depth. If the temperature falls out of the tolerance range, the vehicle will increase or decrease buoyancy to reacquire the target temperature and track it. In a June 2015 experiment in Monterey Bay, CA, USA, an LRAUV ran the presented algorithm to successfully track a target isotherm for 13 h. Over the isotherm tracking duration, the LRAUV mostly remained in the 0.5 $^\circ $ C (peak-to-peak) tolerance range as designed, even though the water column's stratification kept changing. This work paves the way to coupling an LRAUV's complimentary modes of flight and drift—searching for an oceanographic feature in flight mode, and then switching to drift mode to track the feature in a Lagrangian frame of reference. [ABSTRACT FROM AUTHOR]