Research ArticleMARINE ROBOTICS

A system of coordinated autonomous robots for Lagrangian studies of microbes in the oceanic deep chlorophyll maximum

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Science Robotics  13 Jan 2021:
Vol. 6, Issue 50, eabb9138
DOI: 10.1126/scirobotics.abb9138
  • Fig. 1 Water column properties at Station ALOHA and at the experiment site in the eddy.

    (A) Averaged profiles of potential density anomaly (σθ; potential density − 1000 kg/m3), chloropigment (chlorophylls + phaeopigments) concentration, the sum of nitrate and nitrite concentrations, and photosynthetically active radiation (PAR) for March and April at Station ALOHA (22°45′N, 158°W), north of the Hawaiian Islands (see the Supplementary Materials). The center of the DCM is labeled. (B) Two 100-km transects (gold solid lines) across a cyclonic eddy north of the Hawaiian Islands (14 to 16 March 2018) by LRAUVs Aku and Opah, overlaid on an SLA map for 14 March. Arrows represent geostrophic velocities (0 to 0.89 m/s). Station ALOHA is marked by the circle. (C) Perspective views of chlorophyll and temperature measured by the two LRAUVs as they ran on sawtooth trajectories on the respective 100-km transects to acquire 274 profiles from near the surface to 250-m depth starting from the eddy’s edge and progressing into the eddy interior. The transects were completed in 38 hours (Aku) and 35 hours (Opah).

  • Fig. 2 The system of coordinated autonomous robots.

    (A) Illustration of the coordinated, fully autonomous operation of LRAUVs Aku and Opah, and Wave Glider Mola. (B) Tracks of Aku, Opah, and Mola from 31 March 10:03 to 10:40 UTC (from triangle to square). Aku was in the process of collecting one sample within the DCM, while Opah spiraled downward using Aku as the centroid navigational target. The color of the subsurface lines depicts the fluorescence-derived concentration of chlorophyll. Mola, on the sea surface (black line), tracked Aku and is seen dithering above for a short time as Aku’s drift slowed and then accelerated.

  • Fig. 3 Trajectories, tracking, and environmental conditions of the Lagrangian drifts.

    (A) Tracks of Aku (gold) and the drogued drifter (green) on legs 1 (left) and 2 (right) overlaid on SLA and geostrophic velocity maps averaged for each drift period. Current speed ranges represented by the arrows are 0.01 to 0.45 m/s and 0.01 to 0.49 m/s, respectively. Tracks represent the longest contiguous DCM sampling segment in each leg, both beginning at the eastern side of the eddy. Circles show locations of the DCM samples acquired by the shipboard CTD rosette, during (white) and preceding or following (gray) the Aku drift period shown. (B) Distance between Aku and Opah. (C and D) Aku’s time-depth trajectory (black line) overlaid on water column temperature and chlorophyll measured by Opah. In (D), ESP sample collection periods are marked red. Time is UTC. On 19 March, water column data were limited because the profiling depth of Opah was temporarily reduced (to 50 m in the first half of the day; to 150 m in the second half) in the process of reestablishing acoustic tracking of Aku.

  • Fig. 4 Autonomous temperature-based depth control.

    (A) Depth of Aku during the Lagrangian drift in leg 2, colored by ΔTemperature (actual minus target). (B) Statistical summary of Aku depth rate in relation to ΔTemperature; boxes show the interquartile range (IQR; 25th to 75th percentiles) and median. Time is UTC.

  • Fig. 5 Microphotographs of organisms in a water sample from the DCM.

    Images were taken by an Imaging FlowCytobot. Representative phytoplankton species are noted in text for diatoms (Chaetoceros, Thalassionema, and Pseudo-nitzschia) and coccolithophores (Ophiaster and Calciopappus).

  • Fig. 6 Sample RNA quality assessment.

    RQN data are from 0.22- to 5-μm size fraction samples acquired by ESP and CTD rosette sampling platforms. (A and B) Time series from DCM samples during sampling legs 1 and 2. (C) Nonparametric box plots of DCM samples grouped by sampling leg and sampling platform. (D) Nonparametric box plots grouped by depth and sampling platform. In (C) and (D), the thick line corresponds to the median; the box spans the IQR; vertical lines extend at most 1.5 × IQR from the first and third quartiles; and data points beyond this range are individually plotted (circles).

  • Fig. 7 Sample RNA quantification.

    Total RNA data are from 0.22- to 5-μm size fraction samples acquired by ESP and CTD rosette sampling platforms. (A and B) Time series from DCM samples during sampling legs 1 and 2. (C) Nonparametric box plots of DCM samples grouped by sampling leg and sampling platform. (D) Nonparametric box plots grouped by depth and sampling platform. In (C) and (D), the thick line corresponds to the median; the box spans the IQR; vertical lines extend at most 1.5 × IQR from the first and third quartiles; and data points beyond this range are individually plotted (circles).

  • Fig. 8 The robotic sampling vehicle.

    (A) LRAUV Aku deployed in March and April 2018 during the SCOPE Eddy Experiment. (B) The 3G-ESP installed in Aku’s fore-mid section. (C) One ESP sample collection cartridge. (D) Particulate material on the filter in one ESP cartridge after Aku’s recovery. Photo credits: Elisha Wood-Charlson (A, B, and D) and Todd Walsh (C).

Supplementary Materials

  • robotics.sciencemag.org/cgi/content/full/6/50/eabb9138/DC1

    Section S1. Method for computing average profiles of physical, chemical, and bio-optical conditions at Station ALOHA.

    Section S2. Method for computing statistical summaries from profiles of chloropigment and particulate beam attenuation coefficient from shipboard CTD rosette measurements.

    Section S3. Methods for ship-based current velocity measurement and comparison with drift velocities.

    Section S4. Methods for shipboard sampling for RNA analysis.

    Section S5. Methods for RNA extraction from shipboard and ESP samples.

    Section S6. Methods for shipboard sampling for conventional and imaging flow cytometry and statistical analysis.

    Section S7. Methods for sea-surface PAR measurement and statistical analysis.

    Fig. S1. Ship-based characterization of the DCM.

    Fig. S2. Lagrangian drift velocities.

    Fig. S3. Vertical variation of horizontal current speed.

    Fig. S4. Water-column biomass characterization.

    Fig. S5. Localization of the DCM followed by Lagrangian drift within the DCM.

    References (75, 76)

  • Supplementary Materials

    This PDF file includes:

    • Section S1. Method for computing average profiles of physical, chemical, and bio-optical conditions at Station ALOHA.
    • Section S2. Method for computing statistical summaries from profiles of chloropigment and particulate beam attenuation coefficient from shipboard CTD rosette measurements.
    • Section S3. Methods for ship-based current velocity measurement and comparison with drift velocities.
    • Section S4. Methods for shipboard sampling for RNA analysis.
    • Section S5. Methods for RNA extraction from shipboard and ESP samples.
    • Section S6. Methods for shipboard sampling for conventional and imaging flow cytometry and statistical analysis.
    • Section S7. Methods for sea-surface PAR measurement and statistical analysis.
    • Fig. S1. Ship-based characterization of the DCM.
    • Fig. S2. Lagrangian drift velocities.
    • Fig. S3. Vertical variation of horizontal current speed.
    • Fig. S4. Water-column biomass characterization.
    • Fig. S5. Localization of the DCM followed by Lagrangian drift within the DCM.
    • References (75, 76)

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