| Contributors | Affiliation | Role |
|---|---|---|
| Breier, John | University of Texas Rio Grande Valley | Co-Principal Investigator |
| Mickle, Audrey | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Samples were collected in two different ways with two different instruments and these methods are identified in the data file. One method collected whole water samples as vertical profiles with a trace metal grade water rosette. The other method collected water samples with AUV Sentry equipped with a SUPR in situ sample collection system.
Samples collected with CTD water rosette were collected as whole water and filtered through 0.2 um Sterivex PES filters on deck and frozen until analysis.
Samples collected with AUV Sentry/SUPR sampler were filtered in situ through 0.2 um SUPR PES filters and the filtrate was subsampled for nutrient aliquots in a shipboard laboratory and frozen until analysis. These samples were collected in horizontal surveys as the AUV flew a gridded survey through plume depths. The AUV samples were collected while the AUV was in motion and since they were also filtering for particulate material for separate analyses, the associated water samples are an integrated mixture of waters from segments of the survey line and not point samples.
The coverage for either modes of collection are variable as we were targeting hydrothermal plume anomalies. All nutrient samples were analyzed for dissolved silicate, orthophosphate, nitrate, nitrite, and ammonium in seawater by standard methods for oceanographic nutrient samples at the UC San Diego Oceanographic Data Facility (Becker et al. 2019).
For nutrient data, this is the primary data returned from the UC San Diego ODF facility, no other processing was done on this nutrient data.
| Parameter | Description | Units |
| CRUISE_ID | Cruise ID | unitless |
| CRUISE_NAME | Cruise Name | unitless |
| SENTRY_SUPR_DIVE | Sentry Dive ID | unitless |
| DATE | Date of collection, UTC | unitless |
| START_EVENT | Time sample collection started, UTC | unitless |
| ISO_DateTime_UTC_START_EVENT | Datetime sample collection started in ISO format, UTC | unitless |
| END_EVENT | Time sample collection ended, UTC | unitless |
| ISO_DateTime_UTC_END_EVENT | Datetime sample collection ended in ISO format, UTC | unitless |
| START_EVENT_LAT | Latitude sample collection started | decimal degrees |
| START_EVENT_LON | Longitude sample collection started | decimal degrees |
| END_EVENT_LAT | Latitude sample collection ended | decimal degrees |
| END_EVENT_LON | Longitude sample collection ended | decimal degrees |
| STNNBR | Station Number | unitless |
| FEATURE | Feature being sampled | unitless |
| FEATURE_COMMENTS | Comments on feature being sampled | unitless |
| SAMPLE_METHOD | Sampling method used (Trace Metal Rosette or AUV SENTRY+SUPR Sampler) | unitless |
| EVENT | Event | unitless |
| SUPR_PORT | SUPR port | unitless |
| SUPR_BOTTLE | SUPR bottle number | unitless |
| SUPR_FILTERED_VOLUME | Volume filtered by SUPR | liters |
| CTD_CAST | CTD cast number | unitless |
| CTD_ROSETTE_POSITION | Bottle position on CTD rosette | unitless |
| CTD_NISKIN_BOTTLE | CTD bottle number | unitless |
| CRUISE_SAMPNO | Sample number | unitless |
| LOCATION_FLAG | Flag with quality note relating to location | unitless |
| DEPTH | Depth | meters (m) |
| CTD_ROSETTE_ACTUAL_DEPTH | CTD rosette actual depth | meters (m) |
| BOTTOM_DEPTH | Depth to bottom from sampling depth | meters (m) |
| SILICATE_CONC | Concentration of silicate | µmol/L |
| PHOSPHATE_CONC | Concentration of phosphate | µmol/L |
| NITRATE_CONC | Concentration of nitrate | µmol/L |
| NITRITE_CONC | Concentration of nitrite | µmol/L |
| AMMONIUM_CONC | Concetration of ammonium | µmol/L |
| NUTRIENT_LAB_TEMP | Temperature of nutrient lab | Celsius |
| NUTRIENT_FLAG | Flag with quality note relating to nutrient levels | unitless |
| KNOWN_CTD_BOTTLE_ISSUE | Flag with quality note relating to CTD bottle issues | unitless |
| KNOWN_SUPR_PORT_ISSUE | Flag with quality note relating to SUPR port issues | unitless |
| Dataset-specific Instrument Name | AUV Sentry/SUPR sampler |
| Generic Instrument Name | AUV Sentry |
| Dataset-specific Description | Samples collected with AUV Sentry/SUPR sampler were filtered in situ through 0.2 SUPR PES filters and the filtrate was subsampled for nutrient aliquots in a shipboard laboratory and frozen until analysis. SUPR sampling system deployed on AUV Sentry (Breier et al. 2014; Breier et al. 2020). |
| Generic Instrument Description | The autonomous underwater vehicle (AUV) Sentry is a fully autonomous underwater vehicle capable of exploring the ocean down to 6,000 meters (19,685 feet) depth. Sentry builds on the success of its predecessor the ABE, with improved speed, range, and maneuverability.
Sentry's hydrodynamic shape also allows faster ascents and descents. Sentry carries a superior science sensor suite and an increased science payload enabling it to be used for both mid-water and near-seabed oceanographic investigations. Sentry produces bathymetric, sidescan, subbottom, and magnetic maps of the seafloor and is capable of taking digital bottom photographs in a variety of deep-sea terrains such as mid-ocean ridges, deep-sea vents, and cold seeps at ocean margins. Sentry is uniquely able to operate in extreme terrain, including volcano caldera and scarps. Sentry's navigation system uses a doppler velocity log and inertial navigation system, aided by acoustic navigation systems (USBL or LBL). The USBL system also provides acoustic communications, which can be used to obtain the vehicle state and sensor status as well as to retask the vehicle while on the bottom. In addition its standard sensors, Sentry has carried a variety of science-supplied sensors, including the Nakamura redox potential probe, ACFR 3-D imaging system, and the Tethys in-situ mass spectrometer.
Sentry can be used to locate and quantify hydrothermal fluxes. Sentry is also capable of a much wider range of oceanographic applications due to its superior sensing suite, increased speed and endurance, improved navigation, and acoustic communications. Sentry can be used as a stand alone vehicle or in tandem with Alvin or an ROV to increase the efficiency of deep-submergence investigations.
More information is available from the operator site at URL: http://www.whoi.edu/main/sentry |
| Dataset-specific Instrument Name | CTD water rosette |
| Generic Instrument Name | CTD Sea-Bird SBE 911plus |
| Dataset-specific Description | Samples collected with CTD water rosette were collected as whole water and filtered through 0.2 Sterivex PES filters on deck and frozen until analysis. |
| Generic Instrument Description | The Sea-Bird SBE 911 plus is a type of CTD instrument package for continuous measurement of conductivity, temperature and pressure. The SBE 911 plus includes the SBE 9plus Underwater Unit and the SBE 11plus Deck Unit (for real-time readout using conductive wire) for deployment from a vessel. The combination of the SBE 9 plus and SBE 11 plus is called a SBE 911 plus. The SBE 9 plus uses Sea-Bird's standard modular temperature and conductivity sensors (SBE 3 plus and SBE 4). The SBE 9 plus CTD can be configured with up to eight auxiliary sensors to measure other parameters including dissolved oxygen, pH, turbidity, fluorescence, light (PAR), light transmission, etc.). more information from Sea-Bird Electronics |
| Dataset-specific Instrument Name | |
| Generic Instrument Name | Seal Analytical AutoAnalyser 3HR |
| Dataset-specific Description | These samples were analyzed at the UC San Diego Oceanographic Data Facility using standard methods for dissolved nutrients (silicate, orthophosphate, nitrate, nitrite, and ammonium) in seawater. |
| Generic Instrument Description | A fully automated Segmented Flow Analysis (SFA) system, ideal for water and seawater analysis. It comprises a modular system which integrates an autosampler, peristaltic pump, chemistry manifold and detector. The sample and reagents are pumped continuously through the chemistry manifold, and air bubbles are introduced at regular intervals forming reaction segments which are mixed using glass coils. The AA3 uses segmented flow analysis principles to reduce inter-sample dispersion, and can analyse up to 100 samples per hour using stable LED light sources. |
| Website | |
| Platform | R/V Atlantis |
| Start Date | 2007-01-10 |
| End Date | 2007-02-05 |
NSF Award Abstract:
Like volcanoes on land, the mid-ocean ridges that cross the ocean floor are not continuously erupting; however, the magmatic heat present just beneath the surface can continue to drive hot springs, just like the ones found within the crater of the "super volcano" at Yellowstone. In our recent work, we have shown that the chemicals released into the oceans from seafloor hot-springs can be dispersed all across the oceans. Now our interest has focused in on one element in particular, iron. This is one of the most abundant elements in every planetary body in the Universe yet it is vanishingly rare in Earth's oceans today. Set against that, it is essential to just about every form of life on Earth from the simplest and most ancient strains of microbes to the most complex animals including humans. In Earth's oceans, the lack of this "essential micro-nutrient" has been found to limit how much life can flourish near both the south and north poles in the Pacific Ocean in the sunlit surface ocean even though the supply of sunlight and other major nutrients (phosphorous, nitrogen) should be more than adequate. Our newest research suggests that iron released from hydrothermal plumes (where the concentrations coming from vents are more than 1 million times higher than normal ocean water) could play a major role. Despite undergoing massive dilution as hydrothermal solutions leave the vents and traverse thousands of kilometers through the oceans, we believe that at least some of the iron released from deep sea hot springs can survive this journey and make a significant impact on how much live exists in Earth's polar oceans and how much CO2 it draws down from the atmosphere. To investigate that idea, this project will study the fate of iron released from a hydrothermal vent over a length scale that hasn't been studied before - from the first 1km through the ocean out to 100km away from the vent-site. This will fill a gap in our knowledge between what happens right at a vent-site (as studied by research submarines) and what happens to ocean chemistry all across Earth's entire ocean basins (as studied by a huge international research project called GEOTRACES). Our work will use a 3D computational model to predict where the plume of material from a vent in the Northeast Pacific Ocean should escape to after it is erupted from some vents at a volcanic system called the Juan de Fuca Ridge. We will then use an advanced autonomous free-swimming robot to search out in the predicted plume area, first to test the accuracy of our predicted model and, second, to collect samples from the hydrothermal plume from where it first forms to as far out as we can follow it. The samples we collect will include both filtered seawater and the particulate material (whether mineralogical or microbiological) that we can extract from the filters. Together, this will allow us to track the fate of the iron and other key physical and geochemical tracers down-plume away from the vents, to work out where it ends up (in the water and in the sediments) and also how fast those processes happen. The work we do will also help plan how to conduct similar robotics-based exploration on future space missions beyond Earth where it has been hypothesized that seafloor events also exist (e.g. Saturn's moon Enceladus) and where, if we are really lucky, we may find that life is hosted based on the energy from seafloor volcanoes, just as happens here on Earth. We have a resident artist embedded in our program who has already begun experimenting with the use of air-flow and sound in her sculptures to help communicate the complex nature of these plumes. She will join our cruise, and work with our team post-cruise to design and hopefully build a sculpture that that could potentially result in a large and long-term outdoor installation.
The international GEOTRACES program has revealed that iron (Fe) is released ubiquitously from submarine ridges to the deep ocean. Results from US GEOTRACES section GP16 showed that both dissolved and particulate (colloidal) Fe may persist so far as to be able to influence primary productivity in High-Nutrient/Low-Chlorophyll (HNLC) regions of the Southern Ocean. As a complement to these sectional studies, we propose a detailed process study to elucidate the mechanisms by which hydrothermally sourced Fe can persist across the oceans at the scale that GEOTRACES has revealed. Specifically, while the "persistent" Fe in a hydrothermal plume appears to behave quasi-conservatively from 100km to 4000km across the SE Pacific Ocean, it is also known that the majority of the Fe present at the Southern EPR on that US GEOTRACES GP16 cruise did not persist over the 100km separation between that station and the next deep ocean station beyond the ridge crest. To fill that gap, this project will conduct a coupled modelling and field study to investigate the fate of hydrothermally sourced Fe at ranges of 0-1, 1-10 and 10-100km down-plume away from a well established vent-source. To begin, we will use the detailed micro-bathymetry and the long-term current meter data available from the Main Endeavour Segment of the Juan de Fuca Ridge to implement a recently developed 3D theoretical plume dispersion model that can predict both the detailed 3D dispersion trajectory and the rate of flow within the hydrothermal plume away from two long-studied and well characterized Main Endeavour Field (MEF) vents. At sea, we will use that predictive model to guide Sentry autonomous underwater vehicle (AUV) surveys that will follow the plume "down-wind" and "across-plume" to compile a 3D survey using in-situ sensors [optical, redox, conductivity, temperature, depth (CTD)] that will allow us to (1) confirm (and better constrain) the predictive model, and to (2) map out the shape and trajectory of the plume to provide context for discrete water column samples that we will collect - both from the AUV and from a trace metal clean CTD-rosette. Sampling from the AUV will use the latest generation of SUPR samplers designed for the CLIO trace-metal-clean water sampler. This will suffice for samples of dissolved, colloidal and particulate trace metals and collection of filtered material for grain-by-grain mineralogical and biogeochemical analyses. That sampling program will be backed up by larger volume sampling down-plume using a CTD-rosette to augment our AUV-based program with helium isotope analyses (to track extents of physical plume dilution at increasing distances downwind and across plume) and for complementary ligand and organic compound analyses to investigate the role that organic complexation might play in protecting reduced species of Fe [and manganese (Mn), too] against oxidative precipitation and removal from the oceanic water column. Post cruise, our combination of biogeochemical measurements and improved 3D physical modelling will not only be able to provide new insights into the processes that control the fluxes of Fe and Mn to the oceans from hydrothermal venting but also the length scales over which those processes take effect. Finally, because our 3D theoretical model includes velocities, we also anticipate being able to deduce the rates at which these processes occur.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
| Funding Source | Award |
|---|---|
| NSF Division of Ocean Sciences (NSF OCE) |