ERDDAP > info > bcodmo_dataset_734674

Grid DAP Data	Sub- set	Table DAP Data	Make A Graph	W M S	Source Data Files	Acces- sible	Title	Sum- mary	FGDC, ISO, Metadata	Back- ground Info	RSS	E mail	Institution	Dataset ID
		data	graph		files	public	[MBRS Symbiodinium OTU] - OTU molecular abundances for coral Symbiodinium, Belize Mesoamerican Barrier Reef System (MBRS), 2014-2015 (Investigating the influence of thermal history on coral growth response to recent and predicted end-of-century ocean warming across a cascade of ecological scales)		I   M	background			BCO-DMO	bcodmo_dataset_734674

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
attribute	NC_GLOBAL	acquisition_description	String	From Baumann et al (2017): DNA Extraction Coral holobiont (coral, algae, and microbiome) DNA was isolated from each sample following a modified phenol-chloroform [86,87,88] method described in detail by Davies et al. [87]. Briefly, DNA was isolated by immersing the tissue in digest buffer (100 mM NaCL, 10 mM Tris-Cl pH 8.0, 25 mM EDTA pH 9.0, 0.5% SDS, 0.1 mg ml-1 Proteinase K, and 1 \u00b5g ml-1 RNaseA) for 1 h at 42 \u00b0C followed by a standard phenol-chloroform extraction. Extracted DNA was confirmed on an agarose gel and quantified using a Nanodrop 2000 Spectrophotometer (Thermo Scientific). PCR Amplification and Metabarcoding The ITS-2 region (350 bp) was targeted and amplified in each sample using custom primers that incorporated Symbiodinium specific ITS-2-dino-forward and its2rev2-reverse regions [65, 73, 89]. Each primer was constructed with a universal linker, which allowed for the downstream incorporation of Illumina specific adapters and barcodes during the second PCR as well as four degenerative bases whose function was to increase the complexity of library composition. The forward primer was 5'-GTCTCGTCGGCTCGG + AGATGTGTATAAGAGACAG+ NNNN + CCTCCGCTTACTTATATGCTT-3', where the underlined bases are the 5'-universal linker, italicized bases indicate spacer sequences, Ns denote degenerative bases, and the bold bases are the ITS-2-dino. The reverse primer was 5'-TCGTCGGCAGCGTCA + AGATGTGTATAAGAGACAG + NNNN + GTGAATTGCAGAACTCGTG-3'. Each 20 \u00b5L PCR reaction contained 5-100 ng DNA template, 12.4 \u00b5L Milli-Q H2O, 0.2 \u00b5M dNTPs, 1 \u00b5M forward and 1 \u00b5M reverse primers, 1\u00d7 Extaq buffer, and 0.5 U (units) Extaqpolymerase (Takara Biotechnology). PCR cycles were run for all samples using the following PCR profile: 95 \u00b0C for 5 min, 95 \u00b0C for 40 s, 59 \u00b0C for 2 min, 72 \u00b0C for 1 min per cycle and a final elongation step of 72 \u00b0C for 7 min. The optimal number of PCR cycles for each sample was determined from visualization of a faint band on a 2% agarose gel (usually between 22 and 28 cycles) as per Quigley et al. [65]. PCR products were cleaned using GeneJET PCR purification kits (Fermentas Life Sciences), and then a second PCR reaction was performed to incorporate custom barcode-primer sequences [65] modified for Illumina Miseq as in Klepac et al. [90]. Custom barcode primer sequences included 5'-Illumina adaptor + 6 bp barcode sequence + one of two universal linkers-3' (e.g., 5'-CAAGCAGAAGACGGCATACGAGAT + GTATAG + GTCTCGTGGGCTCGG-3', or 5'-AATGATACGGCGACCACCGAGATCTACAC + AGTCAA + TCGTCGGCAGCGTC-3'). Following barcoding, PCR samples were visualized on a 2% agarose gel and pooled based on band intensity (to ensure equal contributions of each sample in the pool). The resulting pool was run on a 1% SYBR Green (Invitrogen) stained gel for 60 min at 90 V and 120 mA. The target band was excised, soaked in 30 \u00b5L of Milli-Q water overnight at 4 \u00b0C, and the supernatant was submitted for sequencing to the University of North Carolina at Chapel Hill High Throughput Sequencing Facility across two lanes of Illumina MiSeq (one 2 \u00d7 250, one 2 \u00d7 300). The two lanes produced similar mapping efficiencies (73 and 73%, respectively; Table S3). Bioinformatic Pipeline The bioinformatic pipeline used here builds upon previous work by Quigley et al. [65] and Green et al. [73]. Raw sequences were renamed to retain sample information, and then all forward (R1) and reverse (R2) sequences were concatenated into two files, which were processed using CD-HIT-OTU [91]. CD- HIT-OTU clusters concatenated reads into identical groups at 100% similarity for identification of operational taxonomic units (OTUs). Each sample was then mapped back to the resulting reference OTUs, and an abundance count for each sample across all OTUs was produced. A BLASTn search of each reference OTU was then run against the GenBank (NCBI) nucleotide reference collection using the representative sequence from each OTU to identify which Symbiodinium lineage was represented by each OTU (Table S2). The phylogeny of representative sequences of each distinct Symbiodinium OTU was constructed using the PhyML tool [92, 93] within Geneious version 10.0.5 ([http://geneious.com](\\"http://geneious.com\\")) [94]. PhyML was run using the GTR+I model (chosen based on delta AIC values produced from jModelTest [92, 95]) to determine the maximum likelihood tree. The TreeDyn tool in Phylogeny.fr was used to view the tree (Fig. 2) [96, 97, 98]. The reference sequences included in the phylogeny were accessed from GenBank (Table S6). These data are reported in: Baumann, J.H., Davies, S.W., Aichelman, H.E. and Castillo, K. D. (2017) Coral Symbiodinium Community Composition Across the Belize Mesoamerican Barrier Reef System is Influenced by Host Species and Thermal Variability. Microb Ecol. [https://doi.org/10.1007/s00248-017-1096-6](\\"https://doi.org/10.1007/s00248-017-1096-6\\"). Methodology References: 65\. Quigley KM, Davies SW, Kenkel CD, Willis BL, Matz MV, Bay LK (2014) Deep- sequencing method for quantifying background abundances of Symbiodinium types: exploring the rare Symbiodinium biosphere in reef-building corals. PLoS One 9:e94297 73\. Green EA, Davies SW, Matz MV, Medina M (2014) Quantifying cryptic Symbiodinium diversity within Orbicella faveolata and Orbicella franksi at the Flower Garden Banks, Gulf of Mexico. PeerJ 2:e386 86\. Aronson RB, Precht WF, Toscano MA, Koltes KH (2002) The 1998 bleaching event and its aftermath on a coral reef in Belize. Marine Biology xxx 87\. Davies SW, Rahman M, Meyer E, Green EA, Buschiazzo E, Medina M, Matz MV (2013) Novel polymorphic microsatellite markers for population genetics of the endangered Caribbean star coral, Montastraea faveolata. Mar Biodivers 43:167-172 88\. Chomczynski P, Sacchi N (2006) The single-step method of RNA isolation by acid guanidinium thiocyanate-phenol-chloroform extraction: twenty-something years on. Nat Protoc 1:581-585 89\. Stat M, Loh WKH, Hoegh-Guldberg O, Carter DA (2009) Stability of coral- endosymbiont associations during and after a thermal stress event in the southern Great Barrier Reef. Coral Reefs 28:709-713 90\. Klepac CN, Beal J, Kenkel CD, Sproles A, Polinski JM, Williams MA, Matz MV, Voss JD (2015) Seasonal stability of coral-Symbiodinium associations in the subtropical coral habitat of St. Lucie Reef, Florida. Mar Ecol Prog Ser 532:137-151 91\. Li W, Fu L, Niu B, Wu S, Wooley J (2012) Ultrafast clustering algorithms for metagenomic sequence analysis. Briefings in bioinformatics: bbs035 92\. Guindon S, Gascuel O (2003) A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst Biol 52:696-704 93\. Guindon S, Dufayard J-F, Lefort V, Anisimova M, Hordijk W, Gascuel O (2010) New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst Biol 59:307-321 94\. Kearse M, Moir R, Wilson A, Stones-Havas S, Cheung M, Sturrock S, Buxton S, Cooper A, Markowitz S, Duran C (2012) Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28:1647-1649 95\. Darriba D, Taboada GL, Doallo R, Posada D (2012) jModelTest 2: more models, new heuristics and parallel computing. Nat Methods 9:772-772 96\. Dereeper A, Guignon V, Blanc G, Audic S, Buffet S, Chevenet F, Dufayard J-F, Guindon S, Lefort V, Lescot M (2008) Phylogeny.fr: robust phylogenetic analysis for the non-specialist. Nucleic Acids Res. 36:W465-W469 97\. Dereeper A, Audic S, Claverie J-M, Blanc G (2010) BLAST-EXPLORER helps you building datasets for phylogenetic analysis. BMC Evol. Biol. 10:8 98\. Chevenet F, Brun C, Ba\u00f1uls A-L, Jacq B, Christen R (2006) TreeDyn: towards dynamic graphics and annotations for analyses of trees. BMC bioinformatics 7:439
attribute	NC_GLOBAL	awards_0_award_nid	String	635862
attribute	NC_GLOBAL	awards_0_award_number	String	OCE-1459522
attribute	NC_GLOBAL	awards_0_data_url	String	http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1459522
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	Michael E. Sieracki
attribute	NC_GLOBAL	awards_0_program_manager_nid	String	50446
attribute	NC_GLOBAL	cdm_data_type	String	Other
attribute	NC_GLOBAL	comment	String	OTU molecular data for coral Symbiodinium abundances Belize Mesoamerican Barrier Reef System (MBRS), 2014-2015 PI's: K. Castillo, J. Baumann version: 2018-04-16 Published in Baumann et al, Microb Ecol (2017). https://doi.org/10.1007/s00248-017-1096-6
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	2018-04-30T17:16:00Z
attribute	NC_GLOBAL	date_modified	String	2019-12-11T13:30:36Z
attribute	NC_GLOBAL	defaultDataQuery	String	&time<now
attribute	NC_GLOBAL	doi	String	10.1575/1912/bco-dmo.734674.1
attribute	NC_GLOBAL	infoUrl	String	https://www.bco-dmo.org/dataset/734674
attribute	NC_GLOBAL	institution	String	BCO-DMO
attribute	NC_GLOBAL	instruments_0_acronym	String	Automated Sequencer
attribute	NC_GLOBAL	instruments_0_dataset_instrument_nid	String	734685
attribute	NC_GLOBAL	instruments_0_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_0_instrument_name	String	Automated DNA Sequencer
attribute	NC_GLOBAL	instruments_0_instrument_nid	String	649
attribute	NC_GLOBAL	instruments_0_supplied_name	String	Illumina Mi-seq
attribute	NC_GLOBAL	instruments_1_acronym	String	Spectrophotometer
attribute	NC_GLOBAL	instruments_1_dataset_instrument_description	String	Used to confirm presence of extracted DNA on agarose gel.
attribute	NC_GLOBAL	instruments_1_dataset_instrument_nid	String	734687
attribute	NC_GLOBAL	instruments_1_description	String	An instrument used to measure the relative absorption of electromagnetic radiation of different wavelengths in the near infra-red, visible and ultraviolet wavebands by samples.
attribute	NC_GLOBAL	instruments_1_instrument_external_identifier	String	https://vocab.nerc.ac.uk/collection/L05/current/LAB20/
attribute	NC_GLOBAL	instruments_1_instrument_name	String	Spectrophotometer
attribute	NC_GLOBAL	instruments_1_instrument_nid	String	707
attribute	NC_GLOBAL	instruments_1_supplied_name	String	Nanodrop 2000 Spectrophotometer (Thermo Scientific)
attribute	NC_GLOBAL	instruments_2_acronym	String	Thermal Cycler
attribute	NC_GLOBAL	instruments_2_dataset_instrument_nid	String	734684
attribute	NC_GLOBAL	instruments_2_description	String	General term for a laboratory apparatus commonly used for performing polymerase chain reaction (PCR). The device has a thermal block with holes where tubes with the PCR reaction mixtures can be inserted. The cycler then raises and lowers the temperature of the block in discrete, pre-programmed steps. (adapted from http://serc.carleton.edu/microbelife/research_methods/genomics/pcr.html)
attribute	NC_GLOBAL	instruments_2_instrument_name	String	PCR Thermal Cycler
attribute	NC_GLOBAL	instruments_2_instrument_nid	String	471582
attribute	NC_GLOBAL	keywords	String	a4a, B1_I, B1_II, B_BG, bco, bco-dmo, biological, C1_I, C1_II, C1_III, chemical, code, d1a, data, dataset, diversity, dmo, erddap, iii, illumina, illumina_run, lat_location, latitude, management, oceanography, office, otu, otu_diversity, preliminary, run, sample, site, species, species_code, thermal, thermal_type, type
attribute	NC_GLOBAL	license	String	https://www.bco-dmo.org/dataset/734674/license
attribute	NC_GLOBAL	metadata_source	String	https://www.bco-dmo.org/api/dataset/734674
attribute	NC_GLOBAL	param_mapping	String	{'734674': {}}
attribute	NC_GLOBAL	parameter_source	String	https://www.bco-dmo.org/mapserver/dataset/734674/parameters
attribute	NC_GLOBAL	people_0_affiliation	String	University of North Carolina at Chapel Hill
attribute	NC_GLOBAL	people_0_affiliation_acronym	String	UNC-Chapel Hill
attribute	NC_GLOBAL	people_0_person_name	String	Karl D. Castillo
attribute	NC_GLOBAL	people_0_person_nid	String	51711
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	University of North Carolina at Chapel Hill
attribute	NC_GLOBAL	people_1_affiliation_acronym	String	UNC-Chapel Hill
attribute	NC_GLOBAL	people_1_person_name	String	Justin Baumann
attribute	NC_GLOBAL	people_1_person_nid	String	733684
attribute	NC_GLOBAL	people_1_role	String	Student
attribute	NC_GLOBAL	people_1_role_type	String	related
attribute	NC_GLOBAL	people_2_affiliation	String	University of North Carolina at Chapel Hill
attribute	NC_GLOBAL	people_2_affiliation_acronym	String	UNC-Chapel Hill
attribute	NC_GLOBAL	people_2_person_name	String	Justin Baumann
attribute	NC_GLOBAL	people_2_person_nid	String	733684
attribute	NC_GLOBAL	people_2_role	String	Contact
attribute	NC_GLOBAL	people_2_role_type	String	related
attribute	NC_GLOBAL	people_3_affiliation	String	Woods Hole Oceanographic Institution
attribute	NC_GLOBAL	people_3_affiliation_acronym	String	WHOI BCO-DMO
attribute	NC_GLOBAL	people_3_person_name	String	Nancy Copley
attribute	NC_GLOBAL	people_3_person_nid	String	50396
attribute	NC_GLOBAL	people_3_role	String	BCO-DMO Data Manager
attribute	NC_GLOBAL	people_3_role_type	String	related
attribute	NC_GLOBAL	project	String	Thermal History and Coral Growth
attribute	NC_GLOBAL	projects_0_acronym	String	Thermal History and Coral Growth
attribute	NC_GLOBAL	projects_0_description	String	Description from NSF award abstract: Rising global ocean surface temperatures have reduced coral growth rates, thereby negatively impacting the health of coral reef ecosystems worldwide. Recent studies on tropical reef building corals reveal that corals' growth in response to ocean warming may be influenced by their previous seawater temperature exposure - their thermal history. Although these recent findings highlight significant variability in coral growth in response to climate change, uncertainty remains as to the spatial scale at which corals' thermal history influences how they have responded to ocean warming and how they will likely respond to predicted future increases in ocean temperature. This study investigates the influence of thermal history on coral growth in response to recent and predicted seawater temperatures increases across four ecologically relevant spatial scales ranging from reef ecosystems, to reef communities, to reef populations, to an individual coral colony. By understanding how corals have responded in the past across a range of ecological scales, the Principal Investigator will be able to improve the ability to predict their susceptibility and resilience, which could then be applied to coral reef conservation in the face of climate change. This research project will broaden the participation of undergraduates from underrepresented groups and educate public radio listeners using minority voices and narratives. The scientist will leverage current and new partnerships to recruit and train minority undergraduates, thus allowing them to engage high school students near field sites in Florida, Belize, and Panama. Through peer advising, undergraduates will document this research on a digital news site for dissemination to the public. The voice of the undergraduates and scientist will ground the production of a public radio feature exploring the topic of acclimatization and resilience - a capacity for stress tolerance within coral reef ecosystems. This project will provide a postdoctoral researcher and several graduate students with opportunities for field and laboratory research training, teaching and mentoring, and professional development. The results will allow policy makers from Florida, the Mesoamerican Barrier Reef System countries, and several Central American countries to benefit from Caribbean-scale inferences that incorporate corals' physiological abilities, thereby improving coral reef management for the region. Coral reefs are at significant risk due to a variety of local and global scale anthropogenic stressors. Although various stressors contribute to the observed decline in coral reef health, recent studies highlight rising seawater temperatures due to increasing atmospheric carbon dioxide concentration as one of the most significant stressors influencing coral growth rates. However, there is increasing recognition of problems of scale since a coral's growth response to an environmental stressor may be conditional on the scale of description. This research will investigate the following research questions: (1) How has seawater temperature on reef ecosystems (Florida Keys Reef Tract, USA; Belize Barrier Reef System, Belize; and Bocas Del Toro Reef Complex, Panama), reef communities (inshore and offshore reefs), reef populations (individual reefs), and near reef colonies (individual colonies), varied in the past? (2) How has seawater temperature influenced rates of coral growth and how does the seawater temperature-coral growth relationship vary across these four ecological spatial scales? (3) Does the seawater temperature-coral growth relationship forecast rates of coral growth under predicted end-of-century ocean warming at the four ecological spatial scales? Long term sea surface temperature records and small-scale high-resolution in situ seawater temperature measurements will be compared with growth chronologies for the reef building corals Siderastrea siderea and Orbicella faveolata, two keystone species ubiquitously distributed throughout the Caribbean Sea. Nutrients and irradiance will be quantified via satellite-derived observations, in situ measurements, and established colorimetric protocols. Field and laboratory experiments will be combined to examine seawater temperature-coral growth relationships under recent and predicted end-of-century ocean warming at four ecologically relevant spatial scales. The findings of this study will help us bridge the temperature-coral growth response gap across ecologically relevant spatial scales and thus improve our understanding of how corals have responded to recent warming. This will lead to more meaningful predictions about future coral growth response to climate change.
attribute	NC_GLOBAL	projects_0_end_date	String	2018-02
attribute	NC_GLOBAL	projects_0_geolocation	String	Western Caribbean
attribute	NC_GLOBAL	projects_0_name	String	Investigating the influence of thermal history on coral growth response to recent and predicted end-of-century ocean warming across a cascade of ecological scales
attribute	NC_GLOBAL	projects_0_project_nid	String	635863
attribute	NC_GLOBAL	projects_0_project_website	String	http://www.unc.edu/~kdcastil/research.html
attribute	NC_GLOBAL	projects_0_start_date	String	2015-03
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	standard_name_vocabulary	String	CF Standard Name Table v55
attribute	NC_GLOBAL	summary	String	This dataset contains relative abundance (counts?) of operational taxonomic units (OTUs) from Sumbiodinium samples collected from three coral species (S. siderea, S. radians, and P. strigosa) at nine sites across four latitudes along the Belize MBRS in 2014 and 2015. These sites were previously characterized into three thermally distinct regimes (lowTP, modTP, highTP) and exhibited variations in coral species diversity and richness.
attribute	NC_GLOBAL	title	String	[MBRS Symbiodinium OTU] - OTU molecular abundances for coral Symbiodinium, Belize Mesoamerican Barrier Reef System (MBRS), 2014-2015 (Investigating the influence of thermal history on coral growth response to recent and predicted end-of-century ocean warming across a cascade of ecological scales)
attribute	NC_GLOBAL	version	String	1
attribute	NC_GLOBAL	xml_source	String	osprey2erddap.update_xml() v1.3
variable	species		String
attribute	species	bcodmo_name	String	species
attribute	species	description	String	taxonomic species name
attribute	species	long_name	String	Species
attribute	species	units	String	unitless
variable	species_code		String
attribute	species_code	bcodmo_name	String	taxon_code
attribute	species_code	description	String	species code
attribute	species_code	long_name	String	Species Code
attribute	species_code	units	String	unitless
variable	Sample		String
attribute	Sample	bcodmo_name	String	sample
attribute	Sample	description	String	coral sample identifier
attribute	Sample	long_name	String	Sample
attribute	Sample	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P02/current/ACYC/
attribute	Sample	units	String	unitless
variable	site		String
attribute	site	bcodmo_name	String	site
attribute	site	description	String	site identifier: nearby city and the thermally distinct regime code: 1=low; 2=moderate; 3=high
attribute	site	long_name	String	Site
attribute	site	units	String	unitless
variable	thermal_type		String
attribute	thermal_type	bcodmo_name	String	treatment
attribute	thermal_type	description	String	thermal regime code: 1=lowTP; 2=modTP; 3=highTP. These 3 categories are based on low; moderate; and high temperature parameters (see Baumann et al 2016 for details)
attribute	thermal_type	long_name	String	Thermal Type
attribute	thermal_type	units	String	unitless
variable	lat_location		String
attribute	lat_location	bcodmo_name	String	region
attribute	lat_location	description	String	site location and code number
attribute	lat_location	long_name	String	Latitude
attribute	lat_location	standard_name	String	latitude
attribute	lat_location	units	String	unitless
variable	illumina_run		byte
attribute	illumina_run	_FillValue	byte	127
attribute	illumina_run	actual_range	byte	1, 2
attribute	illumina_run	bcodmo_name	String	replicate
attribute	illumina_run	description	String	Illumina run number
attribute	illumina_run	long_name	String	Illumina Run
attribute	illumina_run	units	String	unitless
variable	otu_diversity		byte
attribute	otu_diversity	_FillValue	byte	127
attribute	otu_diversity	actual_range	byte	2, 8
attribute	otu_diversity	bcodmo_name	String	count
attribute	otu_diversity	description	String	total number of operational taxonomic units (OTU) in sample
attribute	otu_diversity	long_name	String	Otu Diversity
attribute	otu_diversity	units	String	OTU's
variable	C1_I		int
attribute	C1_I	_FillValue	int	2147483647
attribute	C1_I	actual_range	int	1, 170259
attribute	C1_I	bcodmo_name	String	relative_abund
attribute	C1_I	description	String	relative abundance of OTU C1.I
attribute	C1_I	long_name	String	C1 I
attribute	C1_I	units	String	unitless
variable	B1_I		int
attribute	B1_I	_FillValue	int	2147483647
attribute	B1_I	actual_range	int	0, 123302
attribute	B1_I	bcodmo_name	String	relative_abund
attribute	B1_I	description	String	relative abundance of OTU B1.I
attribute	B1_I	long_name	String	B1 I
attribute	B1_I	units	String	unitless
variable	C1_II		int
attribute	C1_II	_FillValue	int	2147483647
attribute	C1_II	actual_range	int	0, 107514
attribute	C1_II	bcodmo_name	String	relative_abund
attribute	C1_II	description	String	relative abundance of OTU C1.II
attribute	C1_II	long_name	String	C1 II
attribute	C1_II	units	String	unitless
variable	C1_III		short
attribute	C1_III	_FillValue	short	32767
attribute	C1_III	actual_range	short	0, 29764
attribute	C1_III	bcodmo_name	String	relative_abund
attribute	C1_III	description	String	relative abundance of OTU C1.III
attribute	C1_III	long_name	String	C1 III
attribute	C1_III	units	String	unitless
variable	D1a		int
attribute	D1a	_FillValue	int	2147483647
attribute	D1a	actual_range	int	0, 37100
attribute	D1a	bcodmo_name	String	relative_abund
attribute	D1a	description	String	relative abundance of OTU D1a
attribute	D1a	long_name	String	D1a
attribute	D1a	units	String	unitless
variable	B1_II		short
attribute	B1_II	_FillValue	short	32767
attribute	B1_II	actual_range	short	0, 12000
attribute	B1_II	bcodmo_name	String	relative_abund
attribute	B1_II	description	String	relative abundance of OTU B1.II
attribute	B1_II	long_name	String	B1 II
attribute	B1_II	units	String	unitless
variable	G3		short
attribute	G3	_FillValue	short	32767
attribute	G3	actual_range	short	0, 7517
attribute	G3	bcodmo_name	String	relative_abund
attribute	G3	description	String	relative abundance of OTU G3
attribute	G3	long_name	String	G3
attribute	G3	units	String	unitless
variable	A4a		short
attribute	A4a	_FillValue	short	32767
attribute	A4a	actual_range	short	0, 3692
attribute	A4a	bcodmo_name	String	relative_abund
attribute	A4a	description	String	relative abundance of OTU A4a
attribute	A4a	long_name	String	A4a
attribute	A4a	units	String	unitless
variable	B_BG		short
attribute	B_BG	_FillValue	short	32767
attribute	B_BG	actual_range	short	0, 2758
attribute	B_BG	bcodmo_name	String	relative_abund
attribute	B_BG	description	String	relative abundance of OTU B.BG
attribute	B_BG	long_name	String	B BG
attribute	B_BG	units	String	unitless
variable	C3		short
attribute	C3	_FillValue	short	32767
attribute	C3	actual_range	short	0, 1143
attribute	C3	bcodmo_name	String	relative_abund
attribute	C3	description	String	relative abundance of OTU C3
attribute	C3	long_name	String	C3
attribute	C3	units	String	unitless

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.