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Title Sum-
Institution Dataset ID
   set  data   graph     files  public Diel, daily, and spatial variation of coral reef seawater microbial communities from US
Virgin Islands, 2017
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The Dataset's Variables and Attributes

Row Type Variable Name Attribute Name Data Type Value
attribute NC_GLOBAL access_formats String .htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson
attribute NC_GLOBAL acquisition_description String Sample collection:
Five Porites astreoides colonies and a sand patch were selected and marked
with flagging tape by divers on Ram Head reef (18\u00ba18\u201907.3\u201d N,
64\u00ba42\u201914.5\u201d W; 8 m depth in sand) in St. John, U. S. Virgin
Islands. Colonies of various sizes (3 \u2013 16 inches in diameter) from a
range of heights above the seafloor (1 \u2013 27 cm) were selected and these
colonies were labeled A through E. Additionally, colonies were evenly
distributed across the reef in order to minimize location effects (range of
3.6 to 14 meters between each colony). All colonies were located directly next
to sand patches based on colony size constraints and the space needed for
deployment of the custom made Coral Ecosphere Sampling Devices (CESD). Six
CESD made out of aluminum strut material were deployed adjacent to each
sampling location with sand screws. The last CESD was placed in a wide sand
patch with no corals or benthic organisms located in its vicinity and this
sampling location was used as a \u2018no-coral\u2019 control. Divers
positioned the CESD so that a 60 ml syringe with an attached filter holder
could be placed 5 cm away from the middle of the colony. Light and temperature
loggers (8K HOBO/PAR loggers; Onset, Wareham, MA) were zip-tied to the end of
each CESD and programmed to collect temperature and relative light intensity
measurements every 5 minutes over the course of the three-day study. An hour
after CESD deployment, scuba divers collected the first set of samples (Day 1,
3:00 pm). Filter holders were pre-loaded with 0.22 \u00b5m pore size
Supor\u00ae filters (Pall Corporation, Ann Arbor, MI, USA) and were contained
within sterile Whirl-pack\u00ae bags prior to sampling.\u00a0 Divers also
descended with acid-washed polyethylene nutrient bottles (30 ml volume) to
collect seawater samples for unfiltered inorganic nutrient analysis and flow
cytometry. At depth, seawater samples (60 ml) collected for amplicon-based
microbial community analysis were conducted at 2 different stationary
locations relative to the CESD device (with the exception of collections
completed at the sand-patch location). Reef-depth samples were collected first
at the top of the CESD (2 m from the colony) in order to minimize stirring
close to the coral ecosphere sampling area. To collect the sample, a diver
attached a piece of acid-cleaned Masterflex silicone tubing to connect the end
of the filter holder to the mouth of the syringe and then used reverse
filtration to pull seawater through the filter. The filter-holder was then
placed in an individual Whirl-pack\u00ae bag and sealed. After collection of
microbial biomass with the syringe, a nutrient sample was collected. After
collection of the reef-depth sample, a diver attached the filter holder to the
syringe, slowly descended closer to the coral colony, but behind the CESD to
maintain sufficient distance from the sampling area and then placed the
syringe into the syringe holder located on the horizontal arm of the CESD. As
before, the diver first collected the coral ecosphere sample (5 cm from the
colony) onto the filter followed by a nutrient sample in the same location.
Replicate samples collected for DNA analysis were collected from both seawater
environments surrounding each colony on the first dive, but were not collected
on the following dives due to time constraints. Surface seawater samples (< 1
m) were collected using 60 mL syringes at each time point from the dive boat.

This sampling scheme was repeated at approximately 3 am and 3 pm for the next
three days, totaling up to 6 sampling time points. Divers sampled each colony
and collected samples in the same order (reef-depth followed by coral
ecosphere) during all time points. After collection, samples were placed in a
cooler equipped with blue-ice packs for the transit from the reef to the lab
and then samples were processed immediately. Over the course of sampling, 85
seawater samples were collected.

After the last time point, coral tissue was collected from each colony (close
to the area where the coral ecosphere seawater was sampled) using a hammer and
chisel and the CESD were removed. Sand was also collected in the location
where the sand control CESD device was deployed.

Sample processing:
In the laboratory, sterile syringes were used to remove residual seawater
trapped within filter holders and then filters were placed into cryovials,
flash-frozen in a dry shipper charged with liquid nitrogen, and then
transferred into a\u00a0 -20 C freezer.

Seawater collected for flow cytometric analysis was subsampled from unfiltered
nutrient samples and preserved with paraformaldehyde (Electron Microscopy
Sciences, Allentown, PA) to a final concentration of 1% (by volume). Nutrient,
DNA, and flow cytometry samples were shipped frozen back to Woods Hole
Oceanographic Institution and ultimately stored at -80 C prior to analysis.
The coral tissue and sand samples were stored in a second dry shipper and
ultimately at -80 C until they were processed.\u00a0

Macronutrient analysis and flow cytometry:
Frozen and unfiltered nutrient samples were analyzed with a continuous
segmented flow-system using previously described methods (as in Apprill and
Rappe 2011). The concentrations of NO2- + NO3-, NO2-, PO43-, NH4+, and
silicate were measured in all of the samples. Nitrate concentrations were
obtained by subtracting the nitrite concentration from the nitrite + nitrate
measurements for each sample.

Samples collected for flow cytometry were analyzed using colinear analysis
(laser excitation wavelength of 488 nm, UV) on an Altra flow cytometer
(Beckman Coulter, Pasadena, CA.). Unstained subsamples were used to enumerate
the abundances of picocyanobacteria (Prochlorococcus, Synechococcus) and
picoeukaryotes. Stained (Hoechst stain, 1 \u00b5g ml-1 final concentration)
subsamples were analyzed to estimate the abundance of unpigmented cells (an
estimate of heterotrophic bacterial abundance) (Marie et al. 1997). FlowJo (v.
6.4.7) software was used to estimate the abundance of each cell type. The
abundance of total cells was calculated by adding the cell counts obtained for
each of the respective picoplankton classes together for each sample.

DNA extraction, amplification, pooling, and sequencing:
DNA was extracted from filters using a sucrose-lysis extraction method and
Qiagen spin-columns (Santoro et al. 2010) Control extractions were also
completed with unused filters (control filters without biomass) in order to
account for contamination from the filters or extraction reagents. Lastly,
diluted DNA from a synthetic staggered mock community (BEI Resources,
Manassas, VA, USA) was used to account for amplification and sequencing errors
in downstream microbial community analysis. Coral tissue was removed from the
skeleton using air-brushing with autoclaved 1% phosphate-buffered-saline (PBS)
solution (Apprill et al. 2016; Weber et al. 2017). The coral tissue slurry was
pelleted using a centrifuge and the PBS supernatant was discarded. DNA was
extracted from each pellet (300 mg of tissue) using a modified version of the
DNeasy DNA extraction kit protocol (Qiagen, Germantown, MD). The lysis buffer
in the kit was added to each tube followed by approximately 300 mg of garnet
beads (from a MOBIO DNA extraction kit) and 300 mg of Lysing B matrix beads
(MP Biomedicals, Solon, OH). The tubes were subjected to a bead-beating step
for 15 minutes so that the beads could break up the coral tissue (Weber et al.
2017). After bead-beating, 20 \u00b5l of proteinase-k was added to each tube
and the samples were incubated with gentle agitation for 10 minutes at 56
\u00b0C. After these modifications, the DNeasy protocol (Qiagen) was followed
to complete extractions.

Extracts were amplified with barcoded primers targeting the V4 hypervariable
region of the bacterial and archaeal small subunit ribosomal RNA gene (Kozich
et al. 2013). The forward primer: 5\u2019 TATGGTAATTGTGTGYCAGCMGCCGCGGTAA
3\u2019 (Parada et al. 2016) and reverse primer: 3\u2019
AGTCAGTCAGCCGGACTACNVGGGTWTCTAAT 5\u2019 (Apprill et al. 2015) were used,
along with the barcodes, to amplify and tag each sample prior to pooling. We
used forward and reverse primers with degeneracies in order to eliminate
amplification biases against Crenarchaeota/ Thaumarchaeota (Parada et al.
2016)\u00a0 and SAR 11 (Apprill et al. 2015). Triplicate Polymerase Chain
Reactions (25 l volume) were run with 2 l of DNA template from each sample
using the same barcodes in order to minimize the formation of chimeras during
amplification. The reaction conditions included: a 2-minute hot start at 95
\u00b0C followed by 36 cycles of 95 \u00b0C for 20 seconds, 55 \u00b0C for 15
seconds, and 72 \u00b0C for 5 minutes. The final extension step was 72 \u00b0C
for 10 minutes. Triplicate barcoded amplicons were pooled and screened using
gel electrophoresis to assess the quality and the relative concentration of
amplicons. Amplicons were purified using the MinElute Gel Extraction Kit
(Qiagen) and pooled to form the sequencing library. The library was sequenced
(paired-end 2x250 bp) at the Georgia Genomics and Bioinformatics Core with a
Miseq (Illumina, San Diego, CA) sequencer and raw sequence reads are available
at the NCBI Sequence Read Archive under BioProject # PRJNA550343.

Microbial community analyses:
Raw sequences were quality-filtered and grouped into amplicon sequence
variants (ASVs) using DADA2 (Callahan et al. 2016). Reads were filtered,
trimmed, dereplicated and error rates were calculated using the program\u2019s
parametric error model. The DADA2 algorithm was used to infer the number of
different ASVs (8357 distinct ASVs), paired reads were merged, an ASV table
was constructed, and chimeras were removed (1% of all ASVs). Taxonomy was
assigned to each ASV using the Silva v.132 reference database (Quast et al.
2013). Mock communities were used to assess the performance of the program as
well as sequencing error rates. DADA2 inferred 15, 17, and 17 strains within
the mock community (compared to the 20 expected stains present at different
concentrations within the staggered community) and 13, 14, and 14 of the
strains were exact matches to the expected sequences from the mock community
reference file. Sequence recovery is slightly lower than expected, but is
comparable to normal performance of DADA2 on this staggered mock community
(Callahan et al. 2016).

The R packages Phyloseq (McMurdie and Holmes 2013), Vegan (Oksanen et al.
2017), DESeq2 (Love et al. 2014), and ggplot2 (Wickham 2016) were used for
downstream analysis of the microbial community. Sequences were not subsampled,
but samples with less than 1000 reads (2 samples) were removed. In addition,
ASVs identifying as chloroplasts were removed.\u00a0 Sequences representing
ASVs that identified as \u201cNA\u201d at the Phylum level were checked using
the SINA aligner and classifier (v.1.2.11) (Pruesse et al. 2012) and then
removed if not identified as bacteria or archaea at 70% similarity. The
average number of reads across all seawater samples used in microbial
community analyses was 58,398 (\u00b1 32,184 standard deviation) with a range
of 11,502 \u2013 206,689 reads. The average number of reads in coral tissue
samples was 38,096 (\u00b123,854) with a range of 11,538 \u2013 59,437 reads.
DNA extraction control communities were initially inspected and then removed
because they fell out as outliers compared to the highly similar seawater
microbial communities. Taxonomic bar plots, metrics of alpha diversity
(observed richness of ASVs), and boxplots of alpha diversity were made and
calculated using Phyloseq. Alpha diversity was also calculated for samples
after Prochlorococcus and Synechococcus ASVs were removed in order to
understand how much their dynamics influenced observed richness. Constrained
analysis of principal coordinates (CAP) based on Bray \u2013 Curtis
dissimilarity was completed (using \u2018capscale\u2019 in Vegan) and variance
partitioning was used to identify which of the measured environmental
parameters significantly (p<0.01) contributed to shifts in the microbial
community composition over time. Permutational Multivariate Analysis of
Variance using distance matrices (PERMANOVA/Adonis) tests identified
categorical factors that significantly (p<0.05) contributed to a similarity
between the microbial communities. DESeq2 was used to identify differentially
abundant ASVs between day and night as well as reef-associated (reef-depth and
coral ecosphere) compared to surface microbial communities (using the
\u201clocal\u201d fitType parameter to estimate gene dispersion). Lastly, the
Rhythmicity Analysis Incorporating Non-parametric methods (RAIN)\u00a0 R
package was used to identify ASVs that experienced rhythmic change in relative
abundance over a period of 24 hours (Thaben and Westermark 2014). This
analysis was completed separately for reef-depth and coral ecosphere seawater
and the input ASV matrix was center log-ratio transformed and detrended
following previous methods (Hu et al. 2018). Only ASVs with significant
p-values (p<0.05) after adaptive Benjamini-Hochberg correction were reported
to control for false recovery rates (Benjamini and Hochberg 2000).

Statistical analyses:
A Principal Coordinates Analysis (PCA) was completed to summarize changes in
picoplankton abundances, inorganic nutrient concentrations, and relative light
and temperature information collected from the HOBO loggers and reduce the
dimensionality of this data. Separate PCAs were also generated using samples
collected during either day or night to observe trends specific to these
times. Kruskal-Wallis rank sums tests were used to test for significant
differences (p<0.05) in alpha diversity between the different sample
groupings. Pairwise post-hoc Dunn\u2019s tests with Bonferonni corrections
were used to identify which groups were significantly different from each
other. These tests were also used to test for significant differences in
picoplankton cell abundance overtime, between day and night samples, and
between coral ecosphere and reef-depth samples.
attribute NC_GLOBAL awards_0_award_nid String 746195
attribute NC_GLOBAL awards_0_award_number String OCE-1736288
attribute NC_GLOBAL awards_0_data_url String http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1736288 (external link)
attribute NC_GLOBAL awards_0_funder_name String NSF Division of Ocean Sciences
attribute NC_GLOBAL awards_0_funding_acronym String NSF OCE
attribute NC_GLOBAL awards_0_funding_source_nid String 355
attribute NC_GLOBAL awards_0_program_manager String Daniel Thornhill
attribute NC_GLOBAL awards_0_program_manager_nid String 722161
attribute NC_GLOBAL cdm_data_type String Other
attribute NC_GLOBAL comment String Diel, daily, and spatial variation of coral reef seawater microbial communities, US Virgin Islands, 2017
PI: A. Apprill (WHOI)
version date: 2019-08-12
attribute NC_GLOBAL Conventions String COARDS, CF-1.6, ACDD-1.3
attribute NC_GLOBAL creator_email String info at bco-dmo.org
attribute NC_GLOBAL creator_name String BCO-DMO
attribute NC_GLOBAL creator_type String institution
attribute NC_GLOBAL creator_url String https://www.bco-dmo.org/ (external link)
attribute NC_GLOBAL data_source String extract_data_as_tsv version 2.3 19 Dec 2019
attribute NC_GLOBAL date_created String 2019-08-14T13:23:09Z
attribute NC_GLOBAL date_modified String 2019-08-19T12:17:28Z
attribute NC_GLOBAL defaultDataQuery String &amp;time&lt;now
attribute NC_GLOBAL doi String 10.1575/1912/bco-dmo.775229.1
attribute NC_GLOBAL Easternmost_Easting double -64.70403
attribute NC_GLOBAL geospatial_lat_max double 41.5265
attribute NC_GLOBAL geospatial_lat_min double 18.30204
attribute NC_GLOBAL geospatial_lat_units String degrees_north
attribute NC_GLOBAL geospatial_lon_max double -64.70403
attribute NC_GLOBAL geospatial_lon_min double -70.6731
attribute NC_GLOBAL geospatial_lon_units String degrees_east
attribute NC_GLOBAL infoUrl String https://www.bco-dmo.org/dataset/775229 (external link)
attribute NC_GLOBAL institution String BCO-DMO
attribute NC_GLOBAL instruments_0_acronym String Nutrient Autoanalyzer
attribute NC_GLOBAL instruments_0_dataset_instrument_description String Used to analyze nutrient samples.
attribute NC_GLOBAL instruments_0_dataset_instrument_nid String 775252
attribute NC_GLOBAL instruments_0_description String Nutrient Autoanalyzer is a generic term used when specific type, make and model were not specified. In general, a Nutrient Autoanalyzer is an automated flow-thru system for doing nutrient analysis (nitrate, ammonium, orthophosphate, and silicate) on seawater samples.
attribute NC_GLOBAL instruments_0_instrument_external_identifier String https://vocab.nerc.ac.uk/collection/L05/current/LAB04/ (external link)
attribute NC_GLOBAL instruments_0_instrument_name String Nutrient Autoanalyzer
attribute NC_GLOBAL instruments_0_instrument_nid String 558
attribute NC_GLOBAL instruments_0_supplied_name String A continuous segmented flow-system
attribute NC_GLOBAL instruments_1_acronym String Automated Sequencer
attribute NC_GLOBAL instruments_1_dataset_instrument_description String Used to obtain genetic data.
attribute NC_GLOBAL instruments_1_dataset_instrument_nid String 775254
attribute NC_GLOBAL instruments_1_description String General term for a laboratory instrument used for deciphering the order of bases in a strand of DNA. Sanger sequencers detect fluorescence from different dyes that are used to identify the A, C, G, and T extension reactions. Contemporary or Pyrosequencer methods are based on detecting the activity of DNA polymerase (a DNA synthesizing enzyme) with another chemoluminescent enzyme. Essentially, the method allows sequencing of a single strand of DNA by synthesizing the complementary strand along it, one base pair at a time, and detecting which base was actually added at each step.
attribute NC_GLOBAL instruments_1_instrument_name String Automated DNA Sequencer
attribute NC_GLOBAL instruments_1_instrument_nid String 649
attribute NC_GLOBAL instruments_1_supplied_name String Miseq (Illumina, San Diego, CA) sequencer
attribute NC_GLOBAL instruments_2_acronym String Flow Cytometer
attribute NC_GLOBAL instruments_2_dataset_instrument_description String Used for measuring cell concentrations. Samples collected for flow cytometry were analyzed using colinear analysis (laser excitation wavelength of 488 nm, UV) on an Altra flow cytometer (Beckman Coulter, Pasadena, CA.).
attribute NC_GLOBAL instruments_2_dataset_instrument_nid String 775253
attribute NC_GLOBAL instruments_2_description String Flow cytometers (FC or FCM) are automated instruments that quantitate properties of single cells, one cell at a time. They can measure cell size, cell granularity, the amounts of cell components such as total DNA, newly synthesized DNA, gene expression as the amount messenger RNA for a particular gene, amounts of specific surface receptors, amounts of intracellular proteins, or transient signalling events in living cells.
(from: http://www.bio.umass.edu/micro/immunology/facs542/facswhat.htm)
attribute NC_GLOBAL instruments_2_instrument_external_identifier String https://vocab.nerc.ac.uk/collection/L05/current/LAB37/ (external link)
attribute NC_GLOBAL instruments_2_instrument_name String Flow Cytometer
attribute NC_GLOBAL instruments_2_instrument_nid String 660
attribute NC_GLOBAL instruments_3_dataset_instrument_description String Measured temperature and relative light level.
attribute NC_GLOBAL instruments_3_dataset_instrument_nid String 775251
attribute NC_GLOBAL instruments_3_description String Records temperature data over a period of time.
attribute NC_GLOBAL instruments_3_instrument_name String Temperature Logger
attribute NC_GLOBAL instruments_3_instrument_nid String 639396
attribute NC_GLOBAL instruments_3_supplied_name String Light temperature loggers (8K HOBO/PAR loggers; Onset, Wareham, MA)
attribute NC_GLOBAL keywords String accession, ammonia, ammonium, Ammonium_uM, bco, bco-dmo, bio, biological, cells, chemical, chemistry, collection, Collection_Date, Collection_location, Collection_time, colony, concentration, coral, Coral_Colony_or_sand, data, dataset, date, depth, Depth_Feet, dmo, earth, Earth Science > Oceans > Ocean Chemistry > Ammonia, Earth Science > Oceans > Ocean Chemistry > Nitrate, Earth Science > Oceans > Ocean Chemistry > Phosphate, Earth Science > Oceans > Ocean Chemistry > Silicate, erddap, latitude, levels, light, longitude, management, mass, mass_concentration_of_phosphate_in_sea_water, mass_concentration_of_silicate_in_sea_water, mole, mole_concentration_of_ammonium_in_sea_water, mole_concentration_of_nitrate_in_sea_water, mole_concentration_of_nitrite_in_sea_water, n02, ncbi, NCBI_BioProject_accession_number, NCBI_BioSample_accession_number, nh4, nitrate, Nitrate_uM, nitrite, Nitrite_uM, no3, number, ocean, oceanography, oceans, office, phosphate, Phosphate_uM, picoeukaryotes, Picoeukaryotes_cells_mL, po4, preliminary, prochlorococcus, Prochlorococcus_cells_mL, project, relative, Relative_light_levels, sample, Sample_ID, Sample_type, sand, science, sea, seawater, silicate, Silicate_uM, synechococcus, Synechococcus_cells_mL, temperature, Temperature_F, time, type, unpigmented, Unpigmented_cells_cells_mL, water
attribute NC_GLOBAL keywords_vocabulary String GCMD Science Keywords
attribute NC_GLOBAL license String https://www.bco-dmo.org/dataset/775229/license (external link)
attribute NC_GLOBAL metadata_source String https://www.bco-dmo.org/api/dataset/775229 (external link)
attribute NC_GLOBAL Northernmost_Northing double 41.5265
attribute NC_GLOBAL param_mapping String {'775229': {'Depth_Feet': 'master - depth', 'lat': 'master - latitude', 'lon': 'master - longitude'}}
attribute NC_GLOBAL parameter_source String https://www.bco-dmo.org/mapserver/dataset/775229/parameters (external link)
attribute NC_GLOBAL people_0_affiliation String Woods Hole Oceanographic Institution
attribute NC_GLOBAL people_0_affiliation_acronym String WHOI
attribute NC_GLOBAL people_0_person_name String Amy Apprill
attribute NC_GLOBAL people_0_person_nid String 553489
attribute NC_GLOBAL people_0_role String Principal Investigator
attribute NC_GLOBAL people_0_role_type String originator
attribute NC_GLOBAL people_1_affiliation String Woods Hole Oceanographic Institution
attribute NC_GLOBAL people_1_affiliation_acronym String WHOI
attribute NC_GLOBAL people_1_person_name String Laura Weber
attribute NC_GLOBAL people_1_person_nid String 662109
attribute NC_GLOBAL people_1_role String Contact
attribute NC_GLOBAL people_1_role_type String related
attribute NC_GLOBAL people_2_affiliation String Woods Hole Oceanographic Institution
attribute NC_GLOBAL people_2_affiliation_acronym String WHOI BCO-DMO
attribute NC_GLOBAL people_2_person_name String Nancy Copley
attribute NC_GLOBAL people_2_person_nid String 50396
attribute NC_GLOBAL people_2_role String BCO-DMO Data Manager
attribute NC_GLOBAL people_2_role_type String related
attribute NC_GLOBAL project String Coral Exometabolomes
attribute NC_GLOBAL projects_0_acronym String Coral Exometabolomes
attribute NC_GLOBAL projects_0_description String NSF abstract:
Coral reefs are some of the most diverse and productive ecosystems in the ocean. Globally, reefs have declined in stony (reef-building) coral abundance due to environmental variations, and in the Caribbean this decline has coincided with an increase in octocoral (soft coral) abundance. This phase shift occurring on Caribbean reefs may be impacting the interactions between the sea floor and water column and particularly between corals and picoplankton. Picoplankton are the microorganisms in the water column that utilize organic matter released from corals to support their growth. These coral-picoplankton interactions are relatively unstudied, but could have major implications for reef ecology and coral health. This project will take place in the U.S. territory of the Virgin Islands (USVI) and will produce the first detailed knowledge about the chemical diversity and composition of organic matter released from diverse stony coral and octocoral species. This project will advance our understanding of coral reef microbial ecology by allowing us to understand how different coral metabolites impact picoplankton growth and dynamics over time. The results from this project will be made publically accessible in a freely available online magazine, and USVI minority middle and high school students will be exposed to a lesson about chemical-biological interactions on coral reefs through established summer camps. This project will also contribute to the training of USVI minority undergraduates as well as a graduate student.
Coral exometabolomes, which are the sum of metabolic products of the coral together with its microbiome, are thought to structure picoplankton communities in a species-specific manner. However, a detailed understanding of coral exometabolomes, and their influences on reef picoplankton, has not yet been obtained. This project will utilize controlled aquaria-based experiments with stony corals and octocorals, foundational species of Caribbean reef ecosystems, to examine how the exometabolomes of diverse coral species differentially influence the reef picoplankton community. Specifically, this project will capitalize on recent developments in mass spectrometry-based metabolomics to define the signature exometabolomes of ecologically important and diverse stony corals and octocorals. Secondly, this project will determine how the exometabolomes of these corals vary with factors linked to coral taxonomy as well as the coral-associated microbiome (Symbiodinium algae, bacteria and archaea). With this new understanding of coral exometabolomes, the project will then apply a stable isotope probe labeling approach to the coral exometabolome and will examine if and how (through changes in growth and activity) the seawater picoplankton community incorporates coral exometabolomes from different coral species over time. This project will advance our ability to evaluate the role that coral exometabolomes play in contributing to benthic-picoplankton interactions on changing Caribbean reefs.
attribute NC_GLOBAL projects_0_end_date String 2020-09
attribute NC_GLOBAL projects_0_geolocation String U.S. Virgin Islands
attribute NC_GLOBAL projects_0_name String Signature exometabolomes of Caribbean corals and influences on reef picoplankton
attribute NC_GLOBAL projects_0_project_nid String 746196
attribute NC_GLOBAL projects_0_start_date String 2017-10
attribute NC_GLOBAL publisher_name String Biological and Chemical Oceanographic Data Management Office (BCO-DMO)
attribute NC_GLOBAL publisher_type String institution
attribute NC_GLOBAL sourceUrl String (local files)
attribute NC_GLOBAL Southernmost_Northing double 18.30204
attribute NC_GLOBAL standard_name_vocabulary String CF Standard Name Table v55
attribute NC_GLOBAL subsetVariables String NCBI_BioProject_accession_number
attribute NC_GLOBAL summary String Bacterial and archaeal diversity and composition, microbial cell abundances, inorganic nutrient concentrations, and physicochemical conditions were determined and measured in coral reef seawater over a three-day, diel time series on one reef in St. John, U.S. Virgin Islands.
attribute NC_GLOBAL title String Diel, daily, and spatial variation of coral reef seawater microbial communities from US Virgin Islands, 2017
attribute NC_GLOBAL version String 1
attribute NC_GLOBAL Westernmost_Easting double -70.6731
attribute NC_GLOBAL xml_source String osprey2erddap.update_xml() v1.3
variable Sample_ID   String  
attribute Sample_ID bcodmo_name String sample
attribute Sample_ID description String sample identifier
attribute Sample_ID long_name String Sample ID
attribute Sample_ID nerc_identifier String https://vocab.nerc.ac.uk/collection/P02/current/ACYC/ (external link)
attribute Sample_ID units String unitless
variable NCBI_BioProject_accession_number   String  
attribute NCBI_BioProject_accession_number bcodmo_name String accession number
attribute NCBI_BioProject_accession_number description String NCBI BioProject accession number
attribute NCBI_BioProject_accession_number long_name String NCBI Bio Project Accession Number
attribute NCBI_BioProject_accession_number units String unitless
variable NCBI_BioSample_accession_number   String  
attribute NCBI_BioSample_accession_number bcodmo_name String accession number
attribute NCBI_BioSample_accession_number description String NCBI BioSample accession number
attribute NCBI_BioSample_accession_number long_name String NCBI Bio Sample Accession Number
attribute NCBI_BioSample_accession_number units String unitless
variable Sample_type   String  
attribute Sample_type bcodmo_name String sample_type
attribute Sample_type description String Sample type
attribute Sample_type long_name String Sample Type
attribute Sample_type units String unitless
variable Coral_Colony_or_sand   String  
attribute Coral_Colony_or_sand bcodmo_name String sample
attribute Coral_Colony_or_sand description String Coral Colony or sand identifier
attribute Coral_Colony_or_sand long_name String Coral Colony Or Sand
attribute Coral_Colony_or_sand nerc_identifier String https://vocab.nerc.ac.uk/collection/P02/current/ACYC/ (external link)
attribute Coral_Colony_or_sand units String unitless
variable Collection_time   String  
attribute Collection_time bcodmo_name String time
attribute Collection_time description String Collection time (day or night) and day relative to the start of the study
attribute Collection_time long_name String Collection Time
attribute Collection_time nerc_identifier String https://vocab.nerc.ac.uk/collection/P01/current/AHMSAA01/ (external link)
attribute Collection_time units String unitless
variable Collection_Date   String  
attribute Collection_Date bcodmo_name String date
attribute Collection_Date description String Collection Date; fomatted as Mon-yyyy
attribute Collection_Date long_name String Collection Date
attribute Collection_Date nerc_identifier String https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/ (external link)
attribute Collection_Date units String unitless
variable Collection_location   String  
attribute Collection_location bcodmo_name String site
attribute Collection_location description String Collection location
attribute Collection_location long_name String Collection Location
attribute Collection_location units String unitless
variable latitude   double  
attribute latitude _CoordinateAxisType String Lat
attribute latitude _FillValue double NaN
attribute latitude actual_range double 18.30204, 41.5265
attribute latitude axis String Y
attribute latitude bcodmo_name String latitude
attribute latitude colorBarMaximum double 90.0
attribute latitude colorBarMinimum double -90.0
attribute latitude description String latitude; north is positive
attribute latitude ioos_category String Location
attribute latitude long_name String Latitude
attribute latitude nerc_identifier String https://vocab.nerc.ac.uk/collection/P09/current/LATX/ (external link)
attribute latitude standard_name String latitude
attribute latitude units String degrees_north
variable longitude   double  
attribute longitude _CoordinateAxisType String Lon
attribute longitude _FillValue double NaN
attribute longitude actual_range double -70.6731, -64.70403
attribute longitude axis String X
attribute longitude bcodmo_name String longitude
attribute longitude colorBarMaximum double 180.0
attribute longitude colorBarMinimum double -180.0
attribute longitude description String longitude; east is postive
attribute longitude ioos_category String Location
attribute longitude long_name String Longitude
attribute longitude nerc_identifier String https://vocab.nerc.ac.uk/collection/P09/current/LONX/ (external link)
attribute longitude standard_name String longitude
attribute longitude units String degrees_east
variable Prochlorococcus_cells_mL   int  
attribute Prochlorococcus_cells_mL _FillValue int 2147483647
attribute Prochlorococcus_cells_mL actual_range int 11250, 47419
attribute Prochlorococcus_cells_mL bcodmo_name String cell_concentration
attribute Prochlorococcus_cells_mL description String concentration of Prochlorococcus
attribute Prochlorococcus_cells_mL long_name String Prochlorococcus Cells M L
attribute Prochlorococcus_cells_mL units String cell/milliliter
variable Synechococcus_cells_mL   int  
attribute Synechococcus_cells_mL _FillValue int 2147483647
attribute Synechococcus_cells_mL actual_range int 27721, 79875
attribute Synechococcus_cells_mL bcodmo_name String cell_concentration
attribute Synechococcus_cells_mL description String concentration of Synechococcus
attribute Synechococcus_cells_mL long_name String Synechococcus Cells M L
attribute Synechococcus_cells_mL units String cell/milliliter
variable Picoeukaryotes_cells_mL   short  
attribute Picoeukaryotes_cells_mL _FillValue short 32767
attribute Picoeukaryotes_cells_mL actual_range short 440, 4331
attribute Picoeukaryotes_cells_mL bcodmo_name String cell_concentration
attribute Picoeukaryotes_cells_mL description String concentration of Picoeukaryotes
attribute Picoeukaryotes_cells_mL long_name String Picoeukaryotes Cells M L
attribute Picoeukaryotes_cells_mL units String cell/milliliter
variable Unpigmented_cells_cells_mL   int  
attribute Unpigmented_cells_cells_mL _FillValue int 2147483647
attribute Unpigmented_cells_cells_mL actual_range int 397448, 802850
attribute Unpigmented_cells_cells_mL bcodmo_name String cell_concentration
attribute Unpigmented_cells_cells_mL description String concentration of unpigmented cells
attribute Unpigmented_cells_cells_mL long_name String Unpigmented Cells Cells M L
attribute Unpigmented_cells_cells_mL units String cell/milliliter
variable Phosphate_uM   float  
attribute Phosphate_uM _FillValue float NaN
attribute Phosphate_uM actual_range float 0.13, 1.465
attribute Phosphate_uM bcodmo_name String PO4
attribute Phosphate_uM description String concentration of Phosphate_uM
attribute Phosphate_uM long_name String Mass Concentration Of Phosphate In Sea Water
attribute Phosphate_uM units String micromoles
variable Silicate_uM   float  
attribute Silicate_uM _FillValue float NaN
attribute Silicate_uM actual_range float 0.3, 13.7
attribute Silicate_uM bcodmo_name String SiOH_4
attribute Silicate_uM description String concentration of Silicate_uM
attribute Silicate_uM long_name String Mass Concentration Of Silicate In Sea Water
attribute Silicate_uM units String micromoles
variable Nitrate_uM   float  
attribute Nitrate_uM _FillValue float NaN
attribute Nitrate_uM actual_range float -0.001, 0.4004
attribute Nitrate_uM bcodmo_name String NO3
attribute Nitrate_uM colorBarMaximum double 50.0
attribute Nitrate_uM colorBarMinimum double 0.0
attribute Nitrate_uM description String concentration of Nitrate_uM
attribute Nitrate_uM long_name String Mole Concentration Of Nitrate In Sea Water
attribute Nitrate_uM nerc_identifier String https://vocab.nerc.ac.uk/collection/P01/current/NTRAIGGS/ (external link)
attribute Nitrate_uM units String micromoles
variable Nitrite_uM   float  
attribute Nitrite_uM _FillValue float NaN
attribute Nitrite_uM actual_range float -0.02, 0.08
attribute Nitrite_uM bcodmo_name String NO2
attribute Nitrite_uM colorBarMaximum double 1.0
attribute Nitrite_uM colorBarMinimum double 0.0
attribute Nitrite_uM description String concentration of Nitrite_uM
attribute Nitrite_uM long_name String Mole Concentration Of Nitrite In Sea Water
attribute Nitrite_uM nerc_identifier String https://vocab.nerc.ac.uk/collection/P01/current/NTRIAAZX/ (external link)
attribute Nitrite_uM units String micromoles
variable Ammonium_uM   float  
attribute Ammonium_uM _FillValue float NaN
attribute Ammonium_uM actual_range float 0.13, 2.23
attribute Ammonium_uM bcodmo_name String Ammonium
attribute Ammonium_uM colorBarMaximum double 5.0
attribute Ammonium_uM colorBarMinimum double 0.0
attribute Ammonium_uM description String concentration of Ammonium_uM
attribute Ammonium_uM long_name String Mole Concentration Of Ammonium In Sea Water
attribute Ammonium_uM nerc_identifier String https://vocab.nerc.ac.uk/collection/P01/current/AMONAAZX/ (external link)
attribute Ammonium_uM units String micromoles
variable Temperature_F   float  
attribute Temperature_F _FillValue float NaN
attribute Temperature_F actual_range float 85.014, 86.641
attribute Temperature_F bcodmo_name String temperature
attribute Temperature_F description String Temperature
attribute Temperature_F long_name String Temperature F
attribute Temperature_F nerc_identifier String https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/ (external link)
attribute Temperature_F units String degrees Fahrenheit
variable Depth_Feet   double  
attribute Depth_Feet _FillValue double NaN
attribute Depth_Feet actual_range double 23.0, 28.0
attribute Depth_Feet bcodmo_name String depth
attribute Depth_Feet colorBarMaximum double 8000.0
attribute Depth_Feet colorBarMinimum double -8000.0
attribute Depth_Feet colorBarPalette String TopographyDepth
attribute Depth_Feet description String Depth
attribute Depth_Feet long_name String Depth
attribute Depth_Feet nerc_identifier String https://vocab.nerc.ac.uk/collection/P09/current/DEPH/ (external link)
attribute Depth_Feet standard_name String depth
attribute Depth_Feet units String feet
variable Relative_light_levels   short  
attribute Relative_light_levels _FillValue short 32767
attribute Relative_light_levels actual_range short 0, 864
attribute Relative_light_levels bcodmo_name String unknown
attribute Relative_light_levels description String Relative_light_levels
attribute Relative_light_levels long_name String Relative Light Levels
attribute Relative_light_levels units String lumens/foot^2

The information in the table above is also available in other file formats (.csv, .htmlTable, .itx, .json, .jsonlCSV1, .jsonlCSV, .jsonlKVP, .mat, .nc, .nccsv, .tsv, .xhtml) via a RESTful web service.

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