19:I[42426,["/_next/static/immutable/chunks/1xctgzqre-wsy.js","/_next/static/immutable/chunks/06_-wz6pdtp2b.js","/_next/static/immutable/chunks/30e52g49hg40p.js","/_next/static/immutable/chunks/02yq6tul2z-oh.js","/_next/static/immutable/chunks/10bx_ec2vj7n_.js","/_next/static/immutable/chunks/33bfn03fo8xnt.js","/_next/static/immutable/chunks/0tfjf78scu61b.js","/_next/static/immutable/chunks/31xnvej4n1bi9.js"],"default"] 1a:Tde0,

An oceanographic survey was performed onboard the RV Sally Ride from Puntarenas, Costa Rica to San Diego, USA. Forty-nine CTD-rosette stations and 8 MOCNESS tows (Multiple Opening-Closing Net and Environmental Sensing System; Wiebe et al. 1985) were conducted along the cruise track (see Figure 1 of Gutiérrez-Bravo, et al. 2024). The CTD-rosette system used for water sampling and water column profiling included a SeaBird SBE9+ CTD and calibrated Seapoint-Fluorescence and SBE 43-DO sensors. A MOCNESS system was used for zooplankton and fish sampling and was equipped with 10 nets of 1 square meter (m^2) mouth opening and 333 micrometer (µm) mesh size, a SeaBird SBE9+ CTD, a SeaBird SBE 43 DO sensor, and flow meter and angle sensors.

The vertical sampling strategy followed five specific oxypleths (referred to as sampling levels) using horizontal tows. The deep level followed the 10 micromoles per kilogram (µmol/kg) oxypleth below the anoxic core (~900 meters (m) depth). The anoxic level followed the center of the anoxic core, with DO <1 µmol/kg and depth of ~450 m. The suboxic and hypoxic levels followed the 10 and 100 µmol/kg oxypleths above the anoxic core, with varying depths. The oxic level followed the >200 µmol/kg oxypleth near the surface (~20 m). Abrupt vertical oxygen gradients and the lagged depth control of the MOCNESS tow caused DO values to be less than half or more than double the desired DO values in seven out of 40 nets (M1-Oxic, M1-Hypoxic, M6-Hypoxic, M3-Suboxic, M6-Suboxic, M7-Suboxic and M8-Anoxic). These nets were considered outliers and were removed from the inter-level comparison statistics.

The zooplankton samples were preserved in ethanol 95%. Fish larvae were separated and identified to the most specific taxonomic level possible. The larval stages (preflexion, flexion, postflexion, and transformation) were defined according to Moser (1996). Juveniles and adults were separated, counted, and identified to the most specific taxonomic level possible. A more comprehensive description of the sample processing is described in Gutiérrez Bravo et al. (2024). The habitat type of each taxon was consulted in specialized literature (Moser 1996; Aceves-Medina et al. 2003; Froese and Pauly 2010).

The stable isotope ratios of carbon (13C/12C) and nitrogen (15N/14N) were measured on 39 samples of zooplankton (sample M5-Suboxic presented issues), 44 samples of fish larvae, and 8 samples of fish adults. For zooplankton, a wide-mouth 1.5 milliliter (mL) pipette was used to separate an aliquot from each of the 40 zooplankton samples. This approach was used to assess the integrated isotopic signature of the whole zooplankton community, and does not resolve species-specific differences. For fish, on the other hand, individuals of the same species, same development stage, and same net, were separated using a stereoscope and tweezer to obtain a critical weight of >2 milligrams (mg). Adjacent development stages were pooled if the sample weight was lower than 2mg.

The samples were rinsed to remove ethanol with deionized water, and then dried at 60 degrees Celsius (°C) for 24 hours. The dried samples were then ground to a fine powder using a mortar and pestle. The samples were loaded into tin cups and weighed to ~2mg using an analytical balance. Carbon and nitrogen isotope ratios were measured at the Boston University Stable Isotope Laboratory using a GV Instruments IsoPrime isotope ratio mass spectrometer coupled with an elemental analyzer.

1b:T46b,This dataset includes carbon and nitrogen isotope data from zooplankton and fish larvae collected on the SR2114 expedition onboard the RV Sally Ride from December 2021 to January 2022. Samples were collected using a MOCNESS (Multiple Opening-Closing Net and Environmental Sensing) system. The vertical sampling strategy followed five specific oxypleths (referred to as sampling levels) using horizontal tows. The zooplankton samples were preserved in ethanol 95%. The stable isotope ratios of carbon (13C/12C) and nitrogen (15N/14N) were measured on 39 samples of zooplankton, 44 samples of fish larvae, and 8 samples of fish adults. Carbon and nitrogen isotope ratios were measured at the Boston University Stable Isotope Laboratory using a GV Instruments IsoPrime isotope ratio mass spectrometer coupled with an elemental analyzer. The results were compared to international standards (Pee Dee Belemnite for 13C and atmospheric nitrogen for 15N) and presented as delta notation. This methodology was followed to gather information on the trophic structure of the ecosystem and its ontogenic changes during early fish development.1c:T1239,NSF Award Abstract: Several regions of the deep ocean naturally contain almost no oxygen. Because of this lack of oxygen, microbes living in these regions live in ways that differ from those in oxygenated waters consuming nitrate ions instead of oxygen for respiration. Use of nitrate for microbial respiration results in the production of nitrogen gas which is called denitrification. The resulting removal of nitrate has consequences for the whole ocean as nitrogen is an important nutrient controlling plant growth; however, whereas plants can use nitrogen in the form of nitrate, they cannot, with a few exceptions, use nitrogen gas. There remains a number of uncertainties regarding how much denitrification occurs in the ocean, what controls it, and how it varies in time and space. Traditional studies of ocean denitrification have been limited by the time ships can be at sea and the relatively small proportion of the ocean they can observe. Our project plans to remedy this problem by using vehicles called floats that can operate autonomously in the ocean for three years or more as they drift with currents over hundreds of kilometers. We will outfit ten floats with sensors to measure oxygen and nitrogen gas which will be placed throughout the oxygen-depleted region of the Pacific Ocean to the west of Mexico. This is the largest such region in the ocean from which we have two years of results from a prototype float which validated our approach. This study may well transform our understanding of ocean denitrification and ultimately benefit society as a whole through greater confidence in predictions of the ocean's nitrogen cycle and capacity to fix carbon dioxide under current and future conditions. Application and further development of float systems using commercially available technology will directly benefit successor studies, and more broadly showcase the use of water-following platforms to tackle difficult oceanographic problems. Advances from this study are expected to carry over to other disciplines including ocean biogeochemical modeling. Outreach activities, support for an early career scientist, and student training are included in the project. For the outreach activities, the investigators plan to tie into well-established after-school programs serving underrepresented populations in Massachusetts and established opportunities for public presentations using float related display materials at the University of Washington. Oxygen deficient zones (ODZs), despite constituting a small fraction of total oceanic volume, play important roles in regulating global ocean carbon and nitrogen cycles including hosting 30 to 50% of the global loss of fixed nitrogen. Unfortunately, current uncertainty in ODZ nitrogen loss derives from substantial temporal and spatial variability in rates that remain under-sampled by ship-based measurements. While local regulation of nitrogen loss by oxygen and organic matter availability are well accepted, temporal/spatial variability in the nitrogen flux is likely a result of the influence of physical forcings such as remote ventilation, seasonal variability, and mesoscale eddies. Understanding how the impact of physical forcings on nitrogen loss as mediated through oxygen and organic flux will be required to fully understand the causes and consequences of any future ODZ expansion. To improve our understanding of ODZ nitrogen loss, we will carry out a multiyear, autonomous float-based observational program to address outstanding questions regarding bioavailable nitrogen loss in ODZs. As the largest ODZ and region of our pilot deployments, our operation area will be the Eastern Tropical N. Pacific (ETNP) where our study will determine over a multi-year period, in-situ nM-level oxygen and biogenic nitrogen on float profiles spanning geographic gradients in oxygen and surface productivity. For the first time, our study will also determine in situ nitrogen loss rates from changes in nitrogen concentration during 1 to 2 week Lagrangian float drifts along a constant density surface. A pilot 2 yr float deployment in the ETNP documents our ability to do so. Critically, our float-based approach more closely matches the frequency and distribution of observations to the expected variability in biogenic nitrogen production as compared to prior work and will dramatically increase the data density for this region by acquiring >500 profiles/drifts for nitrogen and >1000 profiles for nM oxygen. 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.6:["$","$L19",null,{"dataset":{"_id":"936689","description":"","problem":"Abrupt vertical oxygen gradients and the lagged depth control of the MOCNESS tow caused DO values to be less than half or more than double the desired DO values in seven out of 40 nets (M1-Oxic, M1-Hypoxic, M6-Hypoxic, M3-Suboxic, M6-Suboxic, M7-Suboxic and M8-Anoxic). ","acquisition":"$1a","processing":"

The results were compared to international standards (Pee Dee Belemnite for 13C and atmospheric nitrogen for 15N) and presented as delta notation. MOCNESS data were analyzed using SBE Data processing.

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Usually used for samples including organic material.","type_acronym":""},{"_id":"936697","name":"flow meter","description":"","type_id":"650","type_name":"Flow Meter","type_desc":"General term for a sensor that quantifies the rate at which fluids (e.g. water or air) pass through sensor packages, instruments, or sampling devices. 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More information from the manufacturer: https://www.seabird.com/products/sbe-43-dissolved-oxygen-sensor","type_acronym":"SBE-43 DO"}],"parameters":[{"_id":"936761","name":"MOCNESS","format":"","frictionlessType":"integer","description":"

Sequential MOCNESS number under the sampling strategy

","units":{"_id":"","name":"unitless"},"type":{"_id":"903","name":"number","description":"

number of organisms counted/observed, a generic term, specific to the data set in which it appears

"}},{"_id":"936762","name":"Level","format":"","frictionlessType":"integer","description":"

Sampling level identifier. 1=Oxic ---> 5=Deep.

","units":{"_id":"","name":"unitless"},"type":{"_id":"1741","name":"sample_descrip","description":"

text description or other traits of the sample collected

"}},{"_id":"936763","name":"Level_Outlier","format":"","frictionlessType":"integer","description":"

Sampling level identifier denoting outliers. 1=Oxic ---> 5=Deep. 0 = Outlier. Abrupt vertical oxygen gradients and the lagged depth control of the MOCNESS tow caused DO values to be less than half or more than double the desired DO values in seven out of 40 nets (M1-Oxic, M1-Hypoxic, M6-Hypoxic, M3-Suboxic, M6-Suboxic, M7-Suboxic and M8-Anoxic). These are the outliers, marked as 0.

","units":{"_id":"","name":"unitless"},"type":{"_id":"1741","name":"sample_descrip","description":"

text description or other traits of the sample collected

"}},{"_id":"936764","name":"LevelName","format":"","frictionlessType":"string","description":"

Name of the MOCNESS sampling level

","units":{"_id":"","name":"unitless"},"type":{"_id":"1741","name":"sample_descrip","description":"

text description or other traits of the sample collected

"}},{"_id":"936765","name":"Date","format":"%Y-%m-%d","frictionlessType":"date","description":"

Date of sampling

","units":{"_id":"","name":"unitless"},"type":{"_id":"1070","name":"date","description":"

date; generally reported in GMT as YYYYMMDD (year; month; day); also as MMDD (month; day); EqPac dates are local Hawaii time. ISO_Date format is YYYY-MM-DD (http://www.iso.org/iso/home/standards/iso8601.htm)

"}},{"_id":"936766","name":"Latitude","format":"","frictionlessType":"number","description":"

Latitude of sampling

","units":{"_id":"","name":"decimal degrees North"},"type":{"_id":"730","name":"latitude","description":"

latitude, in decimal degrees, North is positive, negative denotes South; Reported in some datasets as degrees, minutes

"}},{"_id":"936767","name":"Longitude","format":"","frictionlessType":"number","description":"

Longitude of sampling

","units":{"_id":"","name":"decimal degrees East"},"type":{"_id":"731","name":"longitude","description":"

longitude, in decimal degrees, East is positive, negative denotes West; Reported in some datasets as degrees, minutes

"}},{"_id":"936768","name":"Depth","format":"","frictionlessType":"number","description":"

Distance from surface ocean in meters

","units":{"_id":"","name":"meters (m)"},"type":{"_id":"808","name":"depth","description":"

Observation/sample depth below the sea surface. Units often reported as: meters, feet.

\nWhen used in a JGOFS/GLOBEC dataset the depth is a best estimate; usually but not always calculated from pressure; calculated either from CTD pressure using Fofonoff and Millard (1982; UNESCO Tech Paper #44) algorithm adjusted for 1980 equation of state for seawater (EOS80) or simply equivalent to nominal depth as recorded during sampling if CTD pressure was unavailable.

"}},{"_id":"936769","name":"Sal_SA","format":"","frictionlessType":"number","description":"

Absolute salinity

","units":{"_id":"","name":"PSU"},"type":{"_id":"955","name":"sal","description":"

Salinity: The amount (mass or quantity of matter) of salt per amount (volume or mass) of a body of water.

"}},{"_id":"936770","name":"Temperature","format":"","frictionlessType":"number","description":"

Temperature, conservative TEOS 10

","units":{"_id":"","name":"degrees Celsius"},"type":{"_id":"733","name":"temperature","description":"

water temperature at measurement depth

"}},{"_id":"936771","name":"Oxygen","format":"","frictionlessType":"number","description":"

Dissolved oxygen

","units":{"_id":"","name":"micromoles per kilogram (umol/kg)"},"type":{"_id":"910","name":"dissolved Oxygen","description":"

dissolved oxygen concentration

"}},{"_id":"936772","name":"Species","format":"","frictionlessType":"string","description":"

Identified species name

","units":{"_id":"","name":"unitless"},"type":{"_id":"976","name":"species","description":"

a taxonomic binomial that consists of a genus name followed by the species name of an organism

"}},{"_id":"936773","name":"Hab","format":"","frictionlessType":"string","description":"

Habitat according to Moser 1996 and FishBase 2024

","units":{"_id":"","name":"unitless"},"type":{"_id":"1740","name":"site_descrip","description":"

Description or characteristics of a sampling site

"}},{"_id":"936774","name":"Stage","format":"","frictionlessType":"string","description":"

Fish larvae development stage according to Moser 1996

","units":{"_id":"","name":"unitless"},"type":{"_id":"985","name":"stage","description":"

Organism life history stage, reported as a code or text.

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Sequential development stage number (1=flexion, 5=adult). X indicates zooplankton (stage does not apply). Stage 1 is preflexion. 2 is flexion. 3 is postflexion. 4 is transformation. 5 is juveniles/adult.

","units":{"_id":"","name":"unitless"},"type":{"_id":"985","name":"stage","description":"

Organism life history stage, reported as a code or text.

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Weight

","units":{"_id":"","name":"milligrams (mg)"},"type":{"_id":"1678","name":"weight","description":"

Weight of a sample or object; see dataset for units of measurement. Weight is a physical quality inhering in a bearer that has mass near a gravitational body. (Mass and weight are not equivalent.)

"}},{"_id":"936777","name":"pcnt_C","format":"","frictionlessType":"number","description":"

Percentage of carbon by elemental analyzer

","units":{"_id":"","name":"unitless"},"type":{"_id":"707571","name":"C","description":"

Elemental carbon (C)

"}},{"_id":"936778","name":"d13C","format":"","frictionlessType":"number","description":"

delta C-13

","units":{"_id":"","name":"per mil"},"type":{"_id":"671305","name":"d13C","description":"

Delta 13C (d13C) is the ratio of stable isotopes 13C:12C, reported in parts per thousand (per mil, ‰).

"}},{"_id":"936779","name":"pcnt_N","format":"","frictionlessType":"number","description":"

Percentage of nitrogen by elemental analyzer

","units":{"_id":"","name":"unitless"},"type":{"_id":"707573","name":"N","description":"

Nitrogen (N)

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delta N-15

","units":{"_id":"","name":"per mil"},"type":{"_id":"711970","name":"d15N","description":"

delta 15N (d15N) is a measure of the ratio of stable isotopes 15N:14N. It is commonly reported in parts per thousand (per mil, 0/00).

"}},{"_id":"936781","name":"C_N_ratio","format":"","frictionlessType":"number","description":"

Carbon to nitrogen ratio

","units":{"_id":"","name":"unitless"},"type":{"_id":"1186","name":"C_to_N","description":"

Carbon to Nitrogen ratio (C:N)

"}}],"related_publications":[{"id":"936703","citation":"Aceves-Medina, G., Jiménez-Rosenberg, S. P. A., Hinojosa-Medina, A., Funes-Rodríguez, R., Saldierna, R. J., Lluch-Belda, D., Smith, P. E., & Watson, W. (2003). Fish larvae from the Gulf of California. Scientia Marina, 67(1), 1–11. https://doi.org/10.3989/scimar.2003.67n11\r\n","relation_type":["Methods"],"relation_desc":""},{"id":"936702","citation":"Froese, R. & Pauly, Daniel. (2001). Fishbase 99: A global information system on fishes. 25. ","relation_type":["Methods"],"relation_desc":""},{"id":"936701","citation":"Gutierrez-Bravo, et al. (2024). Midwater anoxia disrupts the trophic structure of zooplankton and fish in an oxygen deficient zone. Limnology & Oceanography (submitted)","relation_type":["Results"],"relation_desc":""},{"id":"931395","citation":"Gutiérrez‐Bravo, J. G., Sánchez‐Velasco, L., Jiménez‐Rosenberg, S. P. A., Altabet, M. A., Méndez‐Mendez, S., & Cambronero‐Solano, S. (2024). Anoxic waters constrain the vertical distribution of fish developmental stages in an oxygen minimum zone. Limnology and Oceanography. Portico. https://doi.org/10.1002/lno.12594\r\n","relation_type":["Results"],"relation_desc":""},{"id":"931399","citation":"Moser, H. G. (Ed.). (1996). The early stages of fishes in the California Current region. US Department of the Interior, Minerals Management Service, Pacific OCS Region.","relation_type":["Methods"],"relation_desc":""},{"id":"743463","citation":"Wiebe, P. H., Morton, A. W., Bradley, A. M., Backus, R. H., Craddock, J. E., Barber, V., … Flierl, G. R. (1985). New development in the MOCNESS, an apparatus for sampling zooplankton and micronekton. Marine Biology, 87(3), 313–323. doi:10.1007/bf00397811\r\n","relation_type":["Methods"],"relation_desc":""}],"related_datasets":[],"services":[{"grouping":"","items":[{"name":"View Data","description":"An in-browser view of the primary tabular data file","url":"https://www.bco-dmo.org/dataset/936689/data/view","contentType":"text/html","actionType":"view"}]},{"grouping":"ERDDAP","items":[{"name":"SUBSET DATA","description":"","url":"https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_936689_v1.html","contentType":"text/html","actionType":"tool"},{"name":"VIEW TABLE","description":"","url":"https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_936689_v1.htmlTable","contentType":"text/html","actionType":"view"},{"name":"CSV","description":"","url":"https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_936689_v1.csv","contentType":"text/csv","actionType":"download"},{"name":"TSV","description":"","url":"https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_936689_v1.tsv","contentType":"text/tsv","actionType":"download"},{"name":"GeoJSON","description":"","url":"https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_936689_v1.geoJson","contentType":"application/geo+json","actionType":"download"},{"name":"MATLAB","description":"","url":"https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_936689_v1.mat","contentType":"text/x-matlab","actionType":"download"},{"name":"netCDF","description":"","url":"https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_936689_v1.nc","contentType":"application/x-netcdf","actionType":"download"}]},{"grouping":"Metadata","items":[{"name":"HTML","description":"A simple HTML page of the dataset metadata","url":"https://www.bco-dmo.org/dataset/936689/description","contentType":"text/html","actionType":"view"},{"name":"PDF","description":"A PDF of the HTML dataset metadata","url":"https://www.bco-dmo.org/dataset/936689/Dataset_description.pdf","contentType":"application/pdf","actionType":"download"},{"name":"ISO 19115-2 (NOAA Profile)","description":"","url":"https://www.bco-dmo.org/dataset/936689/iso","contentType":"application/xml","actionType":"download"}]}],"programs":[],"projects":[{"_id":"925430","name":"Collaborative Research: Multiyear autonomous measurement of N-loss in the ETNP ODZ","acronym":"N-loss in the ETNP ODZ","description":"$1c"}],"archives":[{"id_value":"10.26008/1912/bco-dmo.936689.1","url":"https://doi.org/10.26008/1912/bco-dmo.936689.1","date_assigned":"2025-11-03","version_date":"2024-09-06","archiver":"Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)","archiver_id":"272"}],"license":{"name":"Creative Commons Attribution 4.0","id":"CC-BY-4.0","uri":"https://creativecommons.org/licenses/by/4.0/","spdxUri":"https://spdx.org/licenses/CC-BY-4.0"},"metrics":{"views":{"count":188},"downloads":{"count":129}}}}]