ERDDAP > info > bcodmo_dataset_775229

Grid DAP Data	Sub- set	Table DAP Data	Make A Graph	W M S	Source Data Files	Acces- sible	Title	Sum- mary	ISO, Metadata	Back- ground Info	RSS	E mail	Institution	Dataset ID
	set	data	graph		files	public	Diel, daily, and spatial variation of coral reef seawater microbial communities from US Virgin Islands, 2017		I   M	background			BCO-DMO	bcodmo_dataset_775229

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
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/
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
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/
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/
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
attribute	NC_GLOBAL	metadata_source	String	https://www.bco-dmo.org/api/dataset/775229
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
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/
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/
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/
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/
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/
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/
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/
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/
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/
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/
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/
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.