Dataset abstract: This dataset includes available published non-cyanobacterial diazotroph (NCD) qPCR/ddPCR data available prior to August 2021. This dataset was compiled by Mary R Gradoville (UCSC) and Kendra Turk-Kubo (UCSC). If the abundance of an NCD was reported in the original source as undetected, it is included as a 0 in this dataset; detected but not quantified values were given the nominal value of 1 nifH copy/L. Most reported abundances were determined using quantitative PCR, but several source studies used digital droplet PCR (ddPCR). All information about sample collection and processing (including the primer/probe set used) are provided in the source studies listed (source_data). All sampling times listed are in local time. When sampling times were not available, 00:00:00 was used. Data was extrapolated, when possible, using Web Plot digitizer (https://automeris.io/WebPlotDigitizer/). See the results publication Kirk-Turbo et al. (2022; doi:10.1093/femsre/fuac046) for analysis and discussion of these data. Study abstract: The global biogeography of pelagic, non-cyanobacterial diazotrophs (NCDs) is not well constrained. These are potentially important microorganisms in well-lit surface oceans, because if active, they may supply bioavailable nitrogen to the base of the pelagic food web through the process of biological nitrogen fixation. This dataset is a formal meta analysis of all reported measurements of non-cyanobacterial diazotroph abundances in the global ocean, based quantitative PCR (or digital droplet PCR) targeting taxa-specific nifH genes. NifH genes are used to enumerate NCDs, as they are a good genetic proxy for nitrogen fixation capability, and have congruence with other taxonomic markers, like the 16S rRNA gene. In order to create this dataset, we collected all accounts of NCD abundances from previously reported sources, resulting in a database that draws from 59 published studies detailing the abundance of 55 NCD targets, yielding a total of 7385 water column observations. This database shows that while NCD taxa have been quantified from many ocean regions, there has been a strong North Pacific sampling bias. 

Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Processing Description
  • Problem Description
• Related Publications
• Related Datasets
• Parameters
• Project Information
• Funding

This is a formal meta analysis of all available NDC qPCR datasets published between 2000 and 2019. Seawater DNA and RNA samples were collected using two main field approaches, via Niskin bottles attached to rosettes with CTDs, are using the ship's underway seawater systems). Samples were collected by numerous different research groups. DNA and RNA samples were generally filtered through 0.2 µm filers, using a variety of materials, and in some cases, size fractionated samples were collected (e.g. 3 µm and 0.2 µm filters in series). DNA and RNA samples were typically extracted using on column purification-based kits, and in the case where nifH transcription was quantified cDNA (derived from RNA) was typically generated using Superscript reverse transcriptase kits.  Purified DNA/RNA/cDNA were typically stored at -80oC prior to analysis. Quantitative PCR assays (55 total), were developed by multiple different groups, and his database only includes data generated using qPCR using Taqman(R) chemistry.

This dataset was compiled/formatted for CMAP by Mary R Gradoville and Kendra Turk-Kubo from the Zehr Research Group at the University of California Santa Cruz. 

Data sources:  Individual dataset sources are listed in the "source_data" column for each observation (from 59 published studies).  Column "source_doi" is the DOI for the reference provided in "source_data."  Additional details about the specific data used are provided in the "source_location_of_data" column (e.g., specific tables, figures, whether data provided by the authors, or databases).   

Cruise description: This dataset is a compilation of multiple cruises, collectively carried out by numerous research groups, not all funded by NSF. The original citations are provided in the metadata for the dataset. 

All data would be retrieved off the qPCR instrument as a simple matrix of sample number and relative fluorescence units, including standards (with known quantities of the target gene). Additional software products are not needed. 

For this dataset, data was extrapolated, when possible, using Web Plot digitizer (https://automeris.io/WebPlotDigitizer/). 

* Sheet "data" of submitted file "NCDReview_qPCR_database_06092025.xlsx" was exported from excel to capture the formatted values as displayed in excel. The exported csv file was imported into the BCO-DMO data system for this dataset. Table will appear as Data File: 982905_v1_ncd-qpcr-database.csv (along with other download format options).

Additional metadata included in excel sheet "variable metadata" was attached to this dataset as supplemental file 982905_v1_additional_variable_metadata.csv

Additional metadata include in excel sheet "dataset metadata" were added to fields on this BCO-DMO dataset page.

Added DOIs for each source_data reference publication.
* A unique list of each unique reference included in the column "source_data" was made and each provided reference text was matched to a DOI using Crossref's SimpleQuery Tool. And additional column was added to the dataset table "source_doi." The reference text was cleaned for any special characters that didn't display properly in UTF-8 (e.g. "Bostr√ɬ∂m et al. (2007)" -> "Boström et al. (2007)")

The following character replacements were made:

√¢¬Ä¬ê → -
√¢¬Ä¬ì → –
√Ǭ† → make a space (instead of deleting this char)
√ɬ° → á
√ɬ± → ñ
√ɬ© → é
√ɬ≠ → í
√ɬ∂ → ö
√ɬº → ü
√ɬ≥ → ñ
√ɬü → ß

Additional databases included in "source_location_of_data" doi:10.1594/PANGAEA.818214,doi:10.1594/PANGAEA.833791 were added to the section "Related Datasets" on this page.

Missing Data Identifiers:
* In the BCO-DMO data system missing data identifiers are displayed according to the format of data you access. For example, in csv files it will be blank (null) values. In Matlab .mat files it will be NaN values. When viewing data online at BCO-DMO, the missing value will be shown as blank (null) values.

Note: Column "time" in this dataset includes the local date and time, which varies by the location of the data from the source publication. When sampling times were not available, 00:00:00 was used.

Coverage: Scripps Institution of Oceanography, Tropical and Subtropical Pacific, Chukchi and Beaufort Sea

NSF Award Abstract:
Nitrogen (N) is an important element in the ocean that limits the growth of the microscopic marine plants, phytoplankton. Estimates suggest N inputs and losses may not be balanced in the modern ocean, and thus an underestimation of N inputs may explain this imbalance. The conversion of gaseous N2 to biologically available N (N2 fixation) is the largest source of new N to the ocean. It is possible that the "missing" N can be explained by identifying new sources of N2 fixation. N2 fixation relies on a group of microorganisms, termed "diazotrophs", that utilize N2 for growth, unlike other marine microorganisms. Diazotrophs fall into two groups, cyanobacterial diazotrophs, which are able to derive energy through photosynthesis, and non-cyanobacterial diazotrophs (NCDs), which require a non-light-based energy source. Next to nothing is known about the ecology and biology of NCDs, except that they are ubiquitous in the ocean and contain the nitrogen fixing gene, but no direct measurements of their N2 fixation activity exist. Recent molecular advances for studying organisms at the single cell level now makes the measurement of N2 fixation by NCDs possible. This study is focused on determining whether marine NCDs are actually fixing N2 in the environment and understanding how their N2 fixation is modulated. Determining if NCD activity is an important missing N source in the global oceans has the potential to fill a critical gap in our understanding of the marine N cycle. This project supports early career STEM researchers including a graduate student and a postdoctoral scientist, as well as undergraduate students through several programs including UCSC's California Alliance for Minority Participation (CAMP).

Nitrogen fixation, the microbial process of converting N2 into biologically available ammonia, is an important source of N in the oceans. Historically, research has focused on the most conspicuous diazotrophs, such as Trichodesmium, but the discovery of unicellular cyanobacterial and non-cyanobacterial diazotrophs (NCDs) in the open ocean revealed a broader diversity than previously thought. Much of what is known about NCDs is restricted to presence, abundance estimates and transcriptional activity from gene surveys. NCDs are globally distributed throughout coastal and oligotrophic environments, however, it is not known whether NCDs supply N to support primary productivity. Measurements of marine NCDs are needed to determine if NCDs are actively fixing N2. This study is focused on measuring single cell NCD N2 fixation rates from a variety of taxa living in well-lit, oxygen-rich coastal and oligotrophic surface waters in the North Pacific and Arctic Oceans. The investigators are using a cultivation-independent technique called geneFISH to microscopically visualize and localize NCDs and measuring the incorporation of 15N2 into single cells using nanoscale secondary ion mass spectrometry. Beyond measuring in situ NCD N2 fixation rates, experiments are being conducted to determine environmental controls on single cell NCD N2 fixation (light, temperature, dissolved organic matter, dissolved inorganic N, and iron). Obtaining single cell NCD N2 fixation rates from a range of taxa, under different experimental conditions and in coastal and oligotrophic environments will provide information to link their presence to N2 fixation activity, determine the quantitative significance of NCDs in the marine environment, and set the stage for their inclusion in biogeochemical models.

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.