| Contributors | Affiliation | Role |
|---|---|---|
| Levin, Lisa A. | University of California-San Diego Scripps (UCSD-SIO) | Principal Investigator |
| Lee, Kendra | University of California-San Diego Scripps (UCSD-SIO) | Student |
| McGurrin, Jonathan | University of California-San Diego Scripps (UCSD-SIO) | Student |
| Pereira, Olívia Soares | University of California-San Diego Scripps (UCSD-SIO) | Student |
| Mickle, Audrey | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Samples were collected with HOV Alvin using the manipulator. Samples were placed into individual compartments in a biobox on the Alvin basket. Before preserving, samples were kept cold and animals were handpicked to sample tissue for stable isotope analyses (see related datasets for isotopic data, Pereira et al. 2025). The remaining sample was sieved through 0.3 mm mesh, separating the sample in two fractions (a fine fraction with the meiofauna, and a coarser one with the macrofauna), both preserved in 95% Ethanol.
In the laboratory, rock samples were washed in distilled water through a 0.3 mm sieve and sorted under the microscope. Animals in rock samples were primarily identified to major taxa, counted, and preserved in 95% ethanol.
- Opened "Alaska BCO Entry.xlsx" in Excel
- Identified the fields on the "Final" sheet with decimals that were not showing in the preview. Used the format of "#.##############################" for columns "Latitude", "Longitude", and "Surface_Area". Applied format of "yyyy-mm-dd" to "Date_Recovered"
- Exported file as "Alaska BCO Entry_final.csv"
- Imported "Alaska BCO Entry_final.csv" into the BCO-DMO system
- Replaced all spaces with underscores and removed periods and parenthesis from parameters
- Adjusted taxa names in parameter names to accepted versions, upon request from submitter
- Exported file as "984553_v1_carbonate_macrofauna_sanak_seep.csv"
Scientific names in the data were checked using World Register of Marine Species (WoRMS) Taxon Match. All scientific names in the data are valid and accepted names as of 2025-09-19. A report of these matches is attached as a supplemental file.
| File |
|---|
984553_v1_carbonate_macrofauna_sanak_seep.csv (Comma Separated Values (.csv), 6.03 KB) MD5:60ba1000f6c352b288334da0f0cf8dfd Primary data file for dataset ID 984553, version 1 |
| File |
|---|
taxonomy_carbonate_macrofauna_sanak_seep.csv (Comma Separated Values (.csv), 3.14 KB) MD5:ab044ee11e1fad90e5a8d350537d503c Column "ScientificName" list of taxa referenced in primary dataset column, listed along with "LSID", "AphiaID_accepted", "ScientificName_accepted" results given by the WoRMs taxa matching tool |
| Parameter | Description | Units |
| Alvin_Dive | Number of the Alvin dive from which the sample was collected | unitless |
| Date_Recovered | Date sample was collected | unitless |
| Site | Site name | unitless |
| Substrate_Type | Substrate of sample | unitless |
| Latitude | Latitude of sampling location, positive is North | decimal degrees |
| Longitude | Longitude of sampling location, negative is West | decimal degrees |
| Depth | Depth from which the sample was collected | meters |
| Sample_Number | Sample number | unitless |
| Surface_Area | Surface area | cm^2 |
| Sample_ID | Alvin dive and sample number | unitless |
| Ampharetidae_sp_1 | Number of individuals identified as Ampharetidae sp 1 | unitless |
| Chrysopetalidae_sp_1 | Number of individuals identified as Chrysopetalidae sp 1 | unitless |
| Cirratulidae_sp_1 | Number of individuals identified as Cirratulidae sp 1 | unitless |
| Cirratulidae_sp_2 | Number of individuals identified as Cirratulidae sp 2 | unitless |
| Dorvilleidae_sp_1 | Number of individuals identified as Dorvilleidae sp 1 | unitless |
| Dorvilleidae_sp_2 | Number of individuals identified as Dorvilleidae sp 2 | unitless |
| Dorvilleidae_sp_3 | Number of individuals identified as Dorvilleidae sp 3 | unitless |
| Dorvilleidae_sp_4 | Number of individuals identified as Dorvilleidae sp 4 | unitless |
| Dorvilleidae_sp_5 | Number of individuals identified as Dorvilleidae sp 5 | unitless |
| Dorvilleidae_sp_6 | Number of individuals identified as Dorvilleidae sp 6 | unitless |
| Exogoninae_sp_1 | Number of individuals identified as Exogoninae sp 1 | unitless |
| Exogoninae_sp_2 | Number of individuals identified as Exogoninae sp 2 | unitless |
| Exogoninae_sp_3 | Number of individuals identified as Exogoninae sp 3 | unitless |
| Hesionidae_sp_1 | Number of individuals identified as Hesionidae sp 1 | unitless |
| Hesionidae_sp_2 | Number of individuals identified as Hesionidae sp 2 | unitless |
| Hesionidae_sp_3 | Number of individuals identified as Hesionidae sp 3 | unitless |
| Hesionidae_sp_4 | Number of individuals identified as Hesionidae sp 4 | unitless |
| Lacydoniidae_sp_1 | Number of individuals identified as Lacydoniidae sp 1 | unitless |
| Lacydoniidae_sp_2 | Number of individuals identified as Lacydoniidae sp 2 | unitless |
| Lumbrineridae_sp_1 | Number of individuals identified as Lumbrineridae sp 1 | unitless |
| Lumbrineridae_sp_2 | Number of individuals identified as Lumbrineridae sp 2 | unitless |
| Maldanidae_sp_1 | Number of individuals identified as Maldanidae sp 1 | unitless |
| Maldanidae_sp_2 | Number of individuals identified as Maldanidae sp 2 | unitless |
| Myzostomida_sp_1 | Number of individuals identified as Myzostomida sp 1 | unitless |
| Nereididae_sp_1 | Number of individuals identified as Nereididae sp 1 | unitless |
| Nereididae_sp_2 | Number of individuals identified as Nereididae sp 2 | unitless |
| Nereididae_sp_3_juv | Number of individuals identified as Nereididae sp 3 juv | unitless |
| Oenonidae_sp_1 | Number of individuals identified as Oenonidae sp 1 | unitless |
| Ophryotrocha_sp_1 | Number of individuals identified as Ophryotrocha sp 1 | unitless |
| Ophryotrocha_sp_2 | Number of individuals identified as Ophryotrocha sp 2 | unitless |
| Ophryotrocha_sp_3_uncertain | Number of individuals identified as Ophryotrocha sp 3 uncertain | unitless |
| Paraonidae_sp_1 | Number of individuals identified as Paraonidae sp 1 | unitless |
| Paraonidae_sp_2 | Number of individuals identified as Paraonidae sp 2 | unitless |
| Phyllodocidae_sp_1 | Number of individuals identified as Phyllodocidae sp 1 | unitless |
| Phyllodocidae_sp_2 | Number of individuals identified as Phyllodocidae sp 2 | unitless |
| Phyllodocidae_sp_3 | Number of individuals identified as Phyllodocidae sp 3 | unitless |
| Phyllodocidae_sp_4 | Number of individuals identified as Phyllodocidae sp 4 | unitless |
| Pilargidae_sp_1 | Number of individuals identified as Pilargidae sp 1 | unitless |
| Polynoidae_sp_1 | Number of individuals identified as Polynoidae sp 1 | unitless |
| Polynoidae_sp_2 | Number of individuals identified as Polynoidae sp 2 | unitless |
| Polynoidae_sp_3 | Number of individuals identified as Polynoidae sp 3 | unitless |
| Polynoidae_sp_4 | Number of individuals identified as Polynoidae sp 4 | unitless |
| Polynoidae_sp_5 | Number of individuals identified as Polynoidae sp 5 | unitless |
| Sipuncula_sp_1 | Number of individuals identified as Sipuncula sp 1 | unitless |
| Sphaerodoridae_sp_1 | Number of individuals identified as Sphaerodoridae sp 1 | unitless |
| Terebellidae_sp_1 | Number of individuals identified as Terebellidae sp 1 | unitless |
| Tanaidacea_sp_1 | Number of individuals identified as Tanaidacea sp 1 | unitless |
| Ammotheidae_sp_1 | Number of individuals identified as Ammotheidae sp 1 | unitless |
| Caprellidae_sp_1 | Number of individuals identified as Caprellidae sp 1 | unitless |
| Desmosomatidae_sp_1 | Number of individuals identified as Desmosomatidae sp 1 | unitless |
| Halacaridae_sp_1 | Number of individuals identified as Halacaridae sp 1 | unitless |
| Halacaridae_sp_2 | Number of individuals identified as Halacaridae sp 2 | unitless |
| Haploniscidae_sp_1 | Number of individuals identified as Haploniscidae sp 1 | unitless |
| Munnidae_sp_1 | Number of individuals identified as Munnidae sp 1 | unitless |
| Munnidae_sp_2 | Number of individuals identified as Munnidae sp 2 | unitless |
| Munnopsidae_sp_1 | Number of individuals identified as Munnopsidae sp 1 | unitless |
| Tanaidacea_sp_2 | Number of individuals identified as Tanaidacea sp 2 | unitless |
| Unciolidae_sp_1 | Number of individuals identified as Unciolidae sp 1 | unitless |
| Holothuroidea_sp_1 | Number of individuals identified as Holothuroidea sp 1 | unitless |
| Ophiuridae_sp_1 | Number of individuals identified as Ophiuridae sp 1 | unitless |
| Aplacophora_sp_1 | Number of individuals identified as Aplacophora sp 1 | unitless |
| Bathyacmaea_sp_1 | Number of individuals identified as Bathyacmaea sp 1 | unitless |
| Hyalogyrina_sp_1 | Number of individuals identified as Hyalogyrina sp 1 | unitless |
| Lepetodrilus_sp_1 | Number of individuals identified as Lepetodrilus sp 1 | unitless |
| Neolepetopsis_sp_1 | Number of individuals identified as Neolepetopsis sp 1 | unitless |
| Neptunea_sp_1 | Number of individuals identified as Neptunea sp 1 | unitless |
| Paralepetopsis_sp_1 | Number of individuals identified as Paralepetopsis sp 1 | unitless |
| Provanna_sp_1 | Number of individuals identified as Provanna sp 1 | unitless |
| Pyropelta_sp_1 | Number of individuals identified as Pyropelta sp 1 | unitless |
| Pyropelta_sp_2 | Number of individuals identified as Pyropelta sp 2 | unitless |
| Vesicomyidae_sp_1 | Number of individuals identified as Vesicomyidae sp 1 | unitless |
| Metridioidea_sp_1 | Number of individuals identified as Metridioidea sp 1 | unitless |
| Nemertea_sp_1 | Number of individuals identified as Nemertea sp 1 | unitless |
| Hymedesmia_sp_1 | Number of individuals identified as Hymedesmia sp 1 | unitless |
| Unknown_Egg_sp_1 | Number of individuals identified as Unknown Egg sp 1 | unitless |
| Total_Annelida | Number of individuals identified Annelida | unitless |
| Total_Arthropoda | Number of individuals identified Arthropoda | unitless |
| Total_Echinodermata | Number of individuals identified Echinodermata | unitless |
| Total_Mollusca | Number of individuals identified Mollusca | unitless |
| Total_Cnidaria | Number of individuals identified Cnidaria | unitless |
| Total_Nemertea | Number of individuals identified Nemertea | unitless |
| Total_Porifera | Number of individuals identified Porifera | unitless |
| Total_Other | Number of individuals identified as Other | unitless |
| Dataset-specific Instrument Name | HOV Alvin |
| Generic Instrument Name | HOV Alvin |
| Dataset-specific Description | Puschore, rocks, biotubes, and slurp samples were collected with HOV Alvin using the manipulator. |
| Generic Instrument Description | Human Occupied Vehicle (HOV) Alvin is part of the National Deep Submergence Facility (NDSF). Alvin enables in-situ data collection and observation by two scientists to depths reaching 6,500 meters, during dives lasting up to ten hours.
Commissioned in 1964 as one of the world’s first deep-ocean submersibles, Alvin has remained state-of-the-art as a result of numerous overhauls and upgrades made over its lifetime. The most recent upgrades, begun in 2011 and completed in 2021, saw the installation of a new, larger personnel sphere with a more ergonomic interior; improved visibility and overlapping fields of view; longer bottoms times; new lighting and high-definition imaging systems; improved sensors, data acquisition and download speed. It also doubled the science basket payload, and improved the command-and-control system allowing greater speed, range and maneuverability.
With seven reversible thrusters, it can hover in the water, maneuver over rugged topography, or rest on the sea floor. It can collect data throughout the water column, produce a variety of maps and perform photographic surveys. Alvin also has two robotic arms that can manipulate instruments, obtain samples, and its basket can be reconfigured daily based on the needs of the upcoming dive.
Alvin's depth rating of 6,500m gives researchers in-person access to 99% of the ocean floor. Alvin is a proven and reliable platform capable of diving for up to 30 days in a row before requiring a single scheduled maintenance day. Recent collaborations with autonomous vehicles such as Sentry have proven extremely beneficial, allowing PIs to visit promising sites to collect samples and data in person within hours of their being discovered, and UNOLs driven technological advances have improved the ability for scientific outreach and collaboration via telepresence
Alvin is named for Allyn Vine, a WHOI engineer and geophysicist who helped pioneer deep submergence research and technology.
(from https://www.whoi.edu/what-we-do/explore/underwater-vehicles/hov-alvin/, accessed 2022-09-09) |
| Dataset-specific Instrument Name | Wild Heerbrugg Stereomicroscope M5A |
| Generic Instrument Name | Microscope - Optical |
| Dataset-specific Description | Animals in rock samples were primarily identified to major taxa, counted, and preserved in 95% ethanol. |
| Generic Instrument Description | Instruments that generate enlarged images of samples using the phenomena of reflection and absorption of visible light. Includes conventional and inverted instruments. Also called a "light microscope". |
| Website | |
| Platform | R/V Atlantis |
| Start Date | 2024-05-16 |
| End Date | 2024-06-07 |
| Description | See more information from R2R: https://www.rvdata.us/search/cruise/AT50-24 |
NSF Award Abstract:
This research examines the role of deep-sea organisms in determining the fate and footprint of methane, a potent greenhouse gas, on Pacific continental margins. The investigators are evaluating the deep ocean methanosphere defined by the microbial communities that consume methane and the animals that directly feed on or form symbioses with methane-consuming microbes. They are also investigating animal communities that gain energy indirectly from methane, as well as those that take advantage of carbonate rocks, the physical manifestation of methane consumption in seafloor sediments. The study of methane seeps in the deep waters of both Alaska (4400-5500 meters) and Southern California (450-1040 meters) is enabling comparisons of the methanosphere under different food-limitation and oxygen regimes. By applying diverse chemical, isotopic, microscopy, and genetic-based analyses to seep microbes and fauna, this study is advancing understanding of the contribution of methane to deep-sea biodiversity and ecosystem function, information that can inform management and conservation actions in US waters. In addition to training for graduate and undergraduate students at their home institutions, the investigators are collaborating with the Alaska Native Science and Engineering Program (ANSEP). They are recruiting Alaskan undergraduates to participate in the research, contributing to ANSEP's online resources that promote interaction between scientists and middle and high school students, and participating in ANSEP's annual residential Career Exploration in Marine Science programs to engage middle school students in learning about deep-sea ecosystems and the variety of career pathways available in marine related fields.
Microbial production and consumption of methane is dynamic and widespread along continental margins, and some animals within deep-sea methane seeps rely on the oxidation and sequestration of methane for nutrition. At the same time, understanding of methane-dependent processes and symbioses in the deep-sea environment is still rudimentary. The goals of this study are to 1) examine the diversity of animals involved in methane-based symbioses and heterotrophic consumption of methane-oxidizing microbes and how these symbioses extend the periphery of seeps, contributing to non-seep, continental slope food webs; and 2) determine whether carbonates on the seep periphery sustain active methanotrophic microbial assemblages, providing a localized food source or chemical fuel for thiotrophic symbioses, via anaerobic oxidation of methane, or free-living, sulfide-oxidizing bacteria consumed by animals. The investigators are addressing these goals by surveying, sampling, and characterizing microbes, water, sediments, carbonates and animals at a deep seep site on the Aleutian Margin and a shallow site off Southern California. Shipboard experiments and laboratory analyses are using molecular, isotopic, geochemical, and radiotracer tools to understand transfer of methane-sourced carbon from aerobic methanotrophs under multiple oxygen levels, pressures, and photosynthetic food inputs. This approach offers a wide lens by which to examine the methane seep footprint, allow reinterpretation of past observations, and identify new scientific areas for future study. Improved characterization of the deep continental margin methanosphere informs climate science, biodiversity conservation, and resource management.
| Funding Source | Award |
|---|---|
| NSF Division of Ocean Sciences (NSF OCE) |