Search for: All records

Optical fiber is increasingly used for both communication and distributed sensing of temperature and strain in environmental studies. In this work, we demonstrate the viability of unreinforced fiber tethers (bare fiber) for Raman-based distributed temperature sensing in deep ocean and deep ice environments. High-pressure testing of single-mode and multimode optical fiber showed little to no changes in light attenuation over pressures from atmospheric to 600 bars. Most importantly, the differential attenuation between Stokes and anti-Stokes frequencies, critical for the evaluation of distributed temperature sensing, was shown to be insignificantly affected by fluid pressures over the range of pressures tested for single-mode fiber, and only very slightly affected in multimode fiber. For multimode fiber deployments to ocean depths as great as 6000 m, the effect of pressure-dependent differential attenuation was shown to impact the estimated temperatures by only 0.15 °K. These new results indicate that bare fiber tethers, in addition to use for communication, can be used for distributed temperature or strain in fibers subjected to large depth (pressure) in varying environments such as deep oceans, glaciers and potentially the icy moons of Saturn and Jupiter. 

We report the performance of a low-power one-way travel-time inverted ultra-short baseline (OWTTIUSBL) system designed specifically for use on long endurance autonomous underwater vehicles (AUVs), as deployed during trials in late 2020. The system consists of a WHOI Micromodem-2 as the acoustic processing core coupled with a MEMS attitude and heading reference system (AHRS) and bespoke four-channel array. At low tilts our system provides standalone position fixes to better than ±5° azimuth at slant ranges in excess of 1500 m. The system consumes 1.1 W when active and is capable of entering a low-power 10 mW sleep mode sufficient to maintain its time base. These specifications are based on data collected with the device lowered from a vessel and excited by a mobile source on the vessel’s small boat. We further present preliminary results from the device as installed on a Seaglider that show the potential for improved low-power navigation insensitive to temporal or depth-dependent variations in current profile. 

Abstract. Metaproteomics is an increasingly popular methodology that provides information regarding the metabolic functions of specific microbial taxa and has potential for contributing to ocean ecology and biogeochemical studies. A blinded multi-laboratory intercomparison was conducted to assess comparability and reproducibility of taxonomic and functional results and their sensitivity to methodological variables. Euphotic zone samples from the Bermuda Atlantic Time-Series Study in the North Atlantic Ocean collected by in situ pumps and the AUV Clio were distributed with a paired metagenome, and one-dimensional liquid chromatographic data dependent acquisition mass spectrometry analyses was stipulated. Analysis of mass spectra from seven laboratories through a common informatic pipeline identified a shared set of 1056 proteins from 1395 shared peptides constituents. Quantitative analyses showed good reproducibility: pairwise regressions of spectral counts between laboratories yielded R2 values ranging from 0.43 to 0.83, and a Sørensen similarity analysis of the top 1,000 proteins revealed 70–80 % similarity between laboratory groups. Taxonomic and functional assignments showed good coherence between technical replicates and different laboratories. An informatic intercomparison study, involving 10 laboratories using 8 software packages successfully identified thousands of peptides within the complex metaproteomic datasets, demonstrating the utility of these software tools for ocean metaproteomic research. Future efforts could examine reproducibility in deeper metaproteomes, examine accuracy in targeted absolute quantitation analyses, and develop standards for data output formats to improve data interoperability. Together, these results demonstrate the reproducibility of metaproteomic analyses and their suitability for microbial oceanography research including integration into global scale ocean surveys and ocean biogeochemical models. 

Abstract. Metaproteomics is an increasingly popular methodology that provides information regarding the metabolic functions of specific microbial taxa and has potential for contributing to ocean ecology and biogeochemical studies. A blinded multi-laboratory intercomparison was conducted to assess comparability and reproducibility of taxonomic and functional results and their sensitivity to methodological variables. Euphotic zone samples from the Bermuda Atlantic Time-series Study (BATS) in the North Atlantic Ocean collected by in situ pumps and the autonomous underwater vehicle (AUV) Clio were distributed with a paired metagenome, and one-dimensional (1D) liquid chromatographic data-dependent acquisition mass spectrometry analysis was stipulated. Analysis of mass spectra from seven laboratories through a common bioinformatic pipeline identified a shared set of 1056 proteins from 1395 shared peptide constituents. Quantitative analyses showed good reproducibility: pairwise regressions of spectral counts between laboratories yielded R2 values averaged 0.62±0.11, and a Sørensen similarity analysis of the top 1000 proteins revealed 70 %–80 % similarity between laboratory groups. Taxonomic and functional assignments showed good coherence between technical replicates and different laboratories. A bioinformatic intercomparison study, involving 10 laboratories using eight software packages, successfully identified thousands of peptides within the complex metaproteomic datasets, demonstrating the utility of these software tools for ocean metaproteomic research. Lessons learned and potential improvements in methods were described. Future efforts could examine reproducibility in deeper metaproteomes, examine accuracy in targeted absolute quantitation analyses, and develop standards for data output formats to improve data interoperability. Together, these results demonstrate the reproducibility of metaproteomic analyses and their suitability for microbial oceanography research, including integration into global-scale ocean surveys and ocean biogeochemical models. 

This paper reviews the scientific motivation and challenges, development, and use of underwater robotic vehicles designed for use in ice-covered waters, with special attention paid to the navigation systems employed for under-ice deployments. Scientific needs for routine access under fixed and moving ice by underwater robotic vehicles are reviewed in the contexts of geology and geophysics, biology, sea ice and climate, ice shelves, and seafloor mapping. The challenges of under-ice vehicle design and navigation are summarized. The paper reviews all known under-ice robotic vehicles and their associated navigation systems, categorizing them by vehicle type (tethered, untethered, hybrid, and glider) and by the type of ice they were designed for (fixed glacial or sea ice and moving sea ice). 

Vast and diverse microbial communities exist within the ocean. To better understand the global influence of these microorganisms on Earth’s climate, we developed a robot capable of sampling dissolved and particulate seawater biochemistry across ocean basins while still capturing the fine-scale biogeochemical processes therein. Carbon and other nutrients are acquired and released by marine microorganisms as they build and break down organic matter. The scale of the ocean makes these processes globally relevant and, at the same time, challenging to fully characterize. Microbial community composition and ocean biochemistry vary across multiple physical scales up to that of the ocean basins. Other autonomous underwater vehicles are optimized for moving continuously and, primarily, horizontally through the ocean. In contrast,Clio, the robot that we describe, is designed to efficiently and precisely move vertically through the ocean, drift laterally in a Lagrangian manner to better observe water masses, and integrate with research vessel operations to map large horizontal scales to a depth of 6000 meters. We present results that show howClioconducts high-resolution sensor surveys and sample return missions, including a mapping of 1144 kilometers of the Sargasso Sea to a depth of 1000 meters. We further show how the samples obtain filtered biomass from seawater that enable genomic and proteomic measurements not possible through in situ sensing. These results demonstrate a robotic oceanography approach for global-scale surveys of ocean biochemistry.