http://lod.bco-dmo.org/id/dataset/876787
eng; USA
utf8
dataset
Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2022-07-08
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Microbial Symbionts, Carbon, and Nutrient Cycling in Caribbean Coral Reef Sponges from Conch Reef, Key Largo (Florida, USA) and Carrie Bow Cay (Belize) in June and July 2016
2022-07-11
publication
2022-07-11
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2022-08-17
publication
https://doi.org/10.26008/1912/bco-dmo.876787.1
Christopher Finelli
University of North Carolina - Wilmington
principalInvestigator
Patrick M. Erwin
University of North Carolina - Wilmington
principalInvestigator
Steven McMurray
University of North Carolina - Wilmington
principalInvestigator
Joseph Pawlik
University of North Carolina - Wilmington
principalInvestigator
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
publisher
Cite this dataset as: Finelli, C., Pawlik, J., Erwin, P. M., McMurray, S. (2022) Microbial Symbionts, Carbon, and Nutrient Cycling in Caribbean Coral Reef Sponges from Conch Reef, Key Largo (Florida, USA) and Carrie Bow Cay (Belize) in June and July 2016. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2022-07-11 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.876787.1 [access date]
Sponge Symbiont Carbon and Nutrient Cycling Dataset Description: Methods and Sampling: <p><strong>Sample Collection:</strong><br />
Ambient seawater and sponge tissue were collected from two geographically distant locations (~1203 kilometers apart): Conch Reef, Florida (24° 56.9'&nbsp;N, 80° 27.2′ W), and Carrie Bow Cay, Belize (16° 48.14'&nbsp;N, 88° 4.79′ W). Ten of the most common Caribbean coral reef sponges were sampled in Key Largo, Florida (Conch Reef), and eight of these species were sampled in Belize (Carrie Bow Cay) from depths of 13 to 23 meters in June and July 2016, respectively (see Supplemental File named "Microbial communities in sponge species" (Table_1_Finelli_Dataset.pdf)). Only apparently healthy sponge individuals (i.e., no evidence of disease, tissue damage, algal colonization, or epibionts) with a single osculum were sampled (except in the case of <em>Agelas tubulata</em> which had multiple oscula) (McMurray et al. 2018). All sponge tissue samples were collected in separate bags, preserved in 100% ethanol, and stored at -20°C until processing. Seawater samples (1 liter) were collected at each sampling site and day of sponge tissue sample collection, concentrated onto 0.2 micrometer (μm) filters, preserved in 100% ethanol, and stored at -20°C until processing.</p>
<p><strong>Sponge barcoding</strong><br />
All ten sponge species represent common Caribbean coral reef species and were identified morphologically following Zea et al. (2014). To confirm identifications made in the field, PCR amplification of the partial mitochondrial cytochrome c oxidase subunit I (COI) gene was amplified using the forward primer LCO1490 and reverse primer HCO2198 for species barcoding (Folmer et al. 1994). PCR amplification reactions contained 0.5 μl of each primer 10 μM, 12.5 μl (0.5 units) of MyTaq™ Red Mix DNA polymerase (Bioline), 1 μl&nbsp;of DNA template, and PCR water for a total reaction volume of 25 μl. The thermocycler conditions included an initial denaturation step (95 °C, 1 minute) followed by 35 cycles of denaturation (95 °C, 15 s), annealing (45 °C, 15 s), and extension (72 °C, 10 s), with a final extension step (72 °C, 1 min) and 6 °C hold. The COI amplicons were used in a sequencing PCR with BigDye version 3.1 (Applied Biosystems) and a thermocycler program consisting of an initial denaturation step (96 °C, 1min), 25 cycles of annealing (50 °C, 5 s), extension (60 °C, 4 min), and denaturation (96 °C, 10 s), followed by a final annealing (50 °C, 5 s), extension (60 °C, 4 min), and 10 °C hold. Amplicons were cleaned using BigDye® XTerminator™ Purification Kit (Thermo Fischer), following the manufacturer’s protocol, and sequenced on an AB 3500 Gene Analyzer (Applied Biosystems) at the UNCW Center for Marine Science. Forward and reverse sequences were aligned in Geneious version 8.1.9 (Kearse et al. 2012) to create consensus sequences and compared to the GenBank database using the nucleotide Basic Local Alignment Search Tool (BLASTn). Sequence data were deposited in GenBank under the accession numbers MH297440 to MH297461.</p>
<p><strong>Sample metadata</strong><br />
For each sponge tissue sample that was collected, metadata on sponge pumping rates, sponge volumes, and carbon fluxes were collected on in situ colonies (prior to tissue sampling) and processed as reported previously (McMurray et al. 2018). Briefly, sponge pumping rates were measured using an acoustic Doppler velocimeter (SonTek) (McMurray et al. 2014) and sponge tissue volume was estimated using measurements of the dimensions of each sponge (McMurray et al. 2018). Paired incurrent (ambient) and excurrent seawater samples (1.5 L) were collected via syringe and subsequently filtered (Whatman GF/F). POC on filters was quantified using a CE Elantech NC2100 elemental analyzer, and DOC in the filtrate of each sample was quantified using a Shimadzu TOC 5050 analyzer (McMurray et al. 2016). In Belize, an additional 40 mL of the filtrate from each incurrent and excurrent seawater sample was collected and stored frozen until quantification of NOx, NH4, and PO4 using a Bran + Luebbe AutoAnalyzer III following standard protocols (EPA 1997). The specific filtration rate (SFR, μmol C, or nutrient/s/L sponge) for each carbon and nutrient species (i.e., POC, DOC, NOx, NH4, and PO4) was calculated as: SFR ((Cin−Cex) x Q)/Vsponge where Cin and Cex are the incurrent and excurrent concentrations of each carbon pool or nutrient type (C/mL), Vsponge is the sponge tissue volume (L), and Q is the pumping rate for each sponge (mL/s); thus, positive values indicate net consumption and negative values indicate net production of a particular carbon pool or nutrient type.<br />
<br />
<strong>DNA extraction and sequence processing</strong><br />
Ethanol-preserved tissue samples were dissected into 2 mm³ cubes that included interior and exterior sponge tissue and were extracted using the DNeasy® Blood &amp; Tissue Kit (Qiagen) following the manufacturer protocols. Partial (V4) 16S rRNA gene sequences were amplified using the 515f forward primer and 806r reverse primer (Caporaso et al. 2011) and sequenced on an Illumina MiSeq platform at Molecular Research LP (Shallowater, TX). Illumina sequence reads were processed in mothur v1.38.0 (Schloss et al. 2009) using a modified version of the bioinformatics pipeline described in Weigel and Erwin (2016). Briefly, raw sequences (n = 13.9 million) were demultiplexed, quality-filtered, aligned, classified, and clustered into operational taxonomic units (OTUs) at 97% sequence identity (nOTU = 25,712). Sequence libraries for each sample were subsampled to the lowest read count (n = 15,825), and all data analyses were based on the subsampled dataset. Sequence data were deposited in the Sequence Read Archive (SRA) for microbial data (16S ribosomal RNA gene sequences, Illumina MiSeq platform) of the National Center for Biotechnology under Accession number SRP142647 (<a href="https://www.ncbi.nlm.nih.gov/sra/SRP142647" target="_blank">https://www.ncbi.nlm.nih.gov/sra/SRP142647</a>).</p>
<p>GenBank Database for sponge data (Mitochondrial cytochrome oxidase subunit I genes, Sanger platform). Accession numbers MH297440 to MH297461. <a href="https://www.ncbi.nlm.nih.gov/nuccore/?term=Microbial+Symbionts%2C+Carbon+and+Nutrient+Cycling+in+Caribbean+Coral+Reef+Sponges" target="_blank">https://www.ncbi.nlm.nih.gov/nuccore/?term=Microbial+Symbionts%2C+Carbon+and+Nutrient+Cycling+in+Caribbean+Coral+Reef+Sponges</a></p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1558580 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1558580
completed
Christopher Finelli
University of North Carolina - Wilmington
910-962-3487
Department of Biology and Marine Biology 601 S. College Rd
Wilmington
NC
28403
USA
finellic@uncw.edu
pointOfContact
Patrick M. Erwin
University of North Carolina - Wilmington
910-962-2326
Department of Biology and Marine Biology 5600 Marvin K Moss Ln
Wilmington
NC
28409
USA
erwinp@uncw.edu
pointOfContact
Steven McMurray
University of North Carolina - Wilmington
(567) 623-4874
Old Woman Creek National Estuarine Research Reserve 2514 Cleveland Road East
Huron
OH
44839
USA
steven.mcmurray@dnr.ohio.gov
pointOfContact
Joseph Pawlik
University of North Carolina - Wilmington
910-962-2378
Center for Marine Science 5600 Marvin Moss Lane
Wilmington
NC
28409-5928
USA
pawlikj@uncw.edu
pointOfContact
asNeeded
Dataset Version: 1
Unknown
SRAStudy
Submission
ProjectID
Sample
BioSample
BioProject
Experiment
sample_name
organism
host
isolation_source
collection_date
Latitude
Longitude
geo_loc_name
Platform
Model
LibraryStrategy
LibrarySelection
LibrarySource
LibraryLayout
SonTek acoustic doppler velocimeter
Illumina MiSeq platform
CE Elantech NC2100 Elemental Analyzer
AB 3500 Applied Biosystems Gene Analyzer
Shimadzu TOC 5050 analyzer
theme
None, User defined
NCBI SRA study accession (SRP)
No BCO-DMO term
project
sample identification
NCBI BioSample accession
NCBI BioProject accession
NCBI SRA experiment accession (SRX)
taxon
sample description
date
latitude
longitude
region
instrument
featureType
BCO-DMO Standard Parameters
Acoustic Doppler Velocimeter
Automated DNA Sequencer
Bran Luebbe AA3 AutoAnalyzer
Elemental Analyzer
Gene Analyzer
Shimadzu TOC-L Analyzer
instrument
BCO-DMO Standard Instruments
otherRestrictions
otherRestrictions
Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use.
Testing the sponge-loop hypothesis for Caribbean coral reefs
https://osprey.bco-dmo.org/project/676143
Testing the sponge-loop hypothesis for Caribbean coral reefs
<p><em>NSF Abstract:</em><br />
Sponges are bottom-dwelling animals that dominate Caribbean reefs now that reef-building corals have been declining for decades. Sponges feed by filtering huge volumes of seawater, providing a mechanism for recycling organic material back to the reef. A new theory has been proposed called the "sponge-loop hypothesis" that is potentially the most important new concept in marine ecology in many years, because it seeks to explain Darwin's Paradox: how do highly productive and diverse coral reefs grow in desert-like tropical seas? The sponge loop hypothesis proposes that sponges on coral reefs absorb the large quantities of dissolved organic carbon (molecules such as carbohydrates) that are released by seaweeds and corals and return it to the reef as particles in the form of living and dead cells, or other cellular debris. This project will use a rigorous set of techniques to test the sponge-loop hypothesis in the field on ten of the largest and most common sponges on Caribbean reefs. For each species, the contributions of particles and dissolved organic carbon to sponge nutrition will be measured, as well as the production of cellular particles in the seawater flowing out of the sponge. For selected sponge species, the concentration of dissolved organic carbon entering the sponge will be experimentally enhanced to determine the capacity of the sponge to absorb this potential food source, and to gauge its effect on the production of cellular particles. This project will provide STEM education and training for postdoctoral, graduate and undergraduate students and public outreach in the form of easily accessible educational videos. Further, this project is important for understanding the carbon cycle on coral reefs where the effects of climate change and ocean acidification may be tipping the competitive balance toward non-reef-building organisms, such as sponges.</p>
<p>The cycling of carbon from the water-column to the benthos is central to marine ecosystem function; for coral reefs, this process begins with photosynthesis by seaweeds and coral symbionts, which then exude a substantial portion of fixed carbon as dissolved organic carbon (DOC) that may be lost to currents and tides. But if sponges, with their enormous water filtering capacity, can return DOC from the water column to the reef, it would represent a major unrecognized source of carbon cycling. The "sponge-loop hypothesis" has the potential to transform our understanding of carbon cycling on coral reefs. Building on preliminary data from studies of the giant barrel sponge, this project will investigate each of the three components of the sponge-loop hypothesis for ten common barrel, vase and tube-forming species that span a range of associations with microbial symbionts, from high microbial abundance (HMA) to low microbial abundance (LMA) in the sponge tissue. Specifically, the experimental approach will include InEx techniques (comparative sampling of seawater immediately before and after passage through the sponge), velocimetry, and flow cytometry to determine whether each species consumes DOC and produces particulate organic carbon (POC) in the form of cellular detritus. Then, for species that consume DOC, the same techniques will be used in manipulative experiments that augment the amount of DOC from three categories (labile, semi-labile and refractory) to determine the types of DOC consumed by sponges. In addition to testing the sponge-loop hypothesis, this project will use molecular techniques to investigate the differences among HMA and LMA sponge species, targeting the microbial symbionts that may be responsible for DOC uptake.</p>
Sponge_Loop
largerWorkCitation
project
eng; USA
oceans
-88.07979
-80.453
16.8025
24.948
2016-06-01
2016-07-19
Conch Reef, Key Largo, Florida, USA; Carrie Bow Cay, Belize
0
BCO-DMO catalogue of parameters from Microbial Symbionts, Carbon, and Nutrient Cycling in Caribbean Coral Reef Sponges from Conch Reef, Key Largo (Florida, USA) and Carrie Bow Cay (Belize) in June and July 2016
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
http://lod.bco-dmo.org/id/dataset-parameter/876820.rdf
Name: SRAStudy
Units: unitless
Description: <p>NCBI SRA Study number</p>
http://lod.bco-dmo.org/id/dataset-parameter/876821.rdf
Name: Submission
Units: unitless
Description: <p>submission number</p>
http://lod.bco-dmo.org/id/dataset-parameter/876822.rdf
Name: ProjectID
Units: unitless
Description: <p>project identification number</p>
http://lod.bco-dmo.org/id/dataset-parameter/876823.rdf
Name: Sample
Units: unitless
Description: <p>unique identifier for each sample</p>
http://lod.bco-dmo.org/id/dataset-parameter/876824.rdf
Name: BioSample
Units: unitless
Description: <p>NCBI BioSample number</p>
http://lod.bco-dmo.org/id/dataset-parameter/876825.rdf
Name: BioProject
Units: unitless
Description: <p>NCBI BioProject number</p>
http://lod.bco-dmo.org/id/dataset-parameter/876826.rdf
Name: Experiment
Units: unitless
Description: <p>experiment number</p>
http://lod.bco-dmo.org/id/dataset-parameter/876827.rdf
Name: sample_name
Units: unitless
Description: <p>unique sample identifier</p>
http://lod.bco-dmo.org/id/dataset-parameter/876828.rdf
Name: organism
Units: unitless
Description: <p>organism</p>
http://lod.bco-dmo.org/id/dataset-parameter/876829.rdf
Name: host
Units: unitless
Description: <p>host sponge species or seawater</p>
http://lod.bco-dmo.org/id/dataset-parameter/876830.rdf
Name: isolation_source
Units: unitless
Description: <p>source of isolation</p>
http://lod.bco-dmo.org/id/dataset-parameter/876831.rdf
Name: collection_date
Units: unitless
Description: <p>date of sample collection in format YYYY-MM-DD</p>
http://lod.bco-dmo.org/id/dataset-parameter/876832.rdf
Name: Latitude
Units: decimal degrees
Description: <p>latitude North of sample location</p>
http://lod.bco-dmo.org/id/dataset-parameter/876833.rdf
Name: Longitude
Units: decimal degrees
Description: <p>longitude East of sample location</p>
http://lod.bco-dmo.org/id/dataset-parameter/876834.rdf
Name: geo_loc_name
Units: unitless
Description: <p>location of samples collected</p>
http://lod.bco-dmo.org/id/dataset-parameter/876835.rdf
Name: Platform
Units: unitless
Description: <p>platform used</p>
http://lod.bco-dmo.org/id/dataset-parameter/876836.rdf
Name: Model
Units: unitless
Description: <p>model of platform used</p>
http://lod.bco-dmo.org/id/dataset-parameter/876837.rdf
Name: LibraryStrategy
Units: unitless
Description: <p>library strategy used</p>
http://lod.bco-dmo.org/id/dataset-parameter/876838.rdf
Name: LibrarySelection
Units: unitless
Description: <p>library selection used</p>
http://lod.bco-dmo.org/id/dataset-parameter/876839.rdf
Name: LibrarySource
Units: unitless
Description: <p>source of library used</p>
http://lod.bco-dmo.org/id/dataset-parameter/876840.rdf
Name: LibraryLayout
Units: unitless
Description: <p>layout of library used</p>
GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
22708
https://darchive.mblwhoilibrary.org/bitstream/1912/29229/1/dataset-876787_sponge-symbiont-carbon-and-nutrient-cycling__v1.tsv
download
https://doi.org/10.26008/1912/bco-dmo.876787.1
download
onLine
dataset
<p><strong>Sample Collection:</strong><br />
Ambient seawater and sponge tissue were collected from two geographically distant locations (~1203 kilometers apart): Conch Reef, Florida (24° 56.9'&nbsp;N, 80° 27.2′ W), and Carrie Bow Cay, Belize (16° 48.14'&nbsp;N, 88° 4.79′ W). Ten of the most common Caribbean coral reef sponges were sampled in Key Largo, Florida (Conch Reef), and eight of these species were sampled in Belize (Carrie Bow Cay) from depths of 13 to 23 meters in June and July 2016, respectively (see Supplemental File named "Microbial communities in sponge species" (Table_1_Finelli_Dataset.pdf)). Only apparently healthy sponge individuals (i.e., no evidence of disease, tissue damage, algal colonization, or epibionts) with a single osculum were sampled (except in the case of <em>Agelas tubulata</em> which had multiple oscula) (McMurray et al. 2018). All sponge tissue samples were collected in separate bags, preserved in 100% ethanol, and stored at -20°C until processing. Seawater samples (1 liter) were collected at each sampling site and day of sponge tissue sample collection, concentrated onto 0.2 micrometer (μm) filters, preserved in 100% ethanol, and stored at -20°C until processing.</p>
<p><strong>Sponge barcoding</strong><br />
All ten sponge species represent common Caribbean coral reef species and were identified morphologically following Zea et al. (2014). To confirm identifications made in the field, PCR amplification of the partial mitochondrial cytochrome c oxidase subunit I (COI) gene was amplified using the forward primer LCO1490 and reverse primer HCO2198 for species barcoding (Folmer et al. 1994). PCR amplification reactions contained 0.5 μl of each primer 10 μM, 12.5 μl (0.5 units) of MyTaq™ Red Mix DNA polymerase (Bioline), 1 μl&nbsp;of DNA template, and PCR water for a total reaction volume of 25 μl. The thermocycler conditions included an initial denaturation step (95 °C, 1 minute) followed by 35 cycles of denaturation (95 °C, 15 s), annealing (45 °C, 15 s), and extension (72 °C, 10 s), with a final extension step (72 °C, 1 min) and 6 °C hold. The COI amplicons were used in a sequencing PCR with BigDye version 3.1 (Applied Biosystems) and a thermocycler program consisting of an initial denaturation step (96 °C, 1min), 25 cycles of annealing (50 °C, 5 s), extension (60 °C, 4 min), and denaturation (96 °C, 10 s), followed by a final annealing (50 °C, 5 s), extension (60 °C, 4 min), and 10 °C hold. Amplicons were cleaned using BigDye® XTerminator™ Purification Kit (Thermo Fischer), following the manufacturer’s protocol, and sequenced on an AB 3500 Gene Analyzer (Applied Biosystems) at the UNCW Center for Marine Science. Forward and reverse sequences were aligned in Geneious version 8.1.9 (Kearse et al. 2012) to create consensus sequences and compared to the GenBank database using the nucleotide Basic Local Alignment Search Tool (BLASTn). Sequence data were deposited in GenBank under the accession numbers MH297440 to MH297461.</p>
<p><strong>Sample metadata</strong><br />
For each sponge tissue sample that was collected, metadata on sponge pumping rates, sponge volumes, and carbon fluxes were collected on in situ colonies (prior to tissue sampling) and processed as reported previously (McMurray et al. 2018). Briefly, sponge pumping rates were measured using an acoustic Doppler velocimeter (SonTek) (McMurray et al. 2014) and sponge tissue volume was estimated using measurements of the dimensions of each sponge (McMurray et al. 2018). Paired incurrent (ambient) and excurrent seawater samples (1.5 L) were collected via syringe and subsequently filtered (Whatman GF/F). POC on filters was quantified using a CE Elantech NC2100 elemental analyzer, and DOC in the filtrate of each sample was quantified using a Shimadzu TOC 5050 analyzer (McMurray et al. 2016). In Belize, an additional 40 mL of the filtrate from each incurrent and excurrent seawater sample was collected and stored frozen until quantification of NOx, NH4, and PO4 using a Bran + Luebbe AutoAnalyzer III following standard protocols (EPA 1997). The specific filtration rate (SFR, μmol C, or nutrient/s/L sponge) for each carbon and nutrient species (i.e., POC, DOC, NOx, NH4, and PO4) was calculated as: SFR ((Cin−Cex) x Q)/Vsponge where Cin and Cex are the incurrent and excurrent concentrations of each carbon pool or nutrient type (C/mL), Vsponge is the sponge tissue volume (L), and Q is the pumping rate for each sponge (mL/s); thus, positive values indicate net consumption and negative values indicate net production of a particular carbon pool or nutrient type.<br />
<br />
<strong>DNA extraction and sequence processing</strong><br />
Ethanol-preserved tissue samples were dissected into 2 mm³ cubes that included interior and exterior sponge tissue and were extracted using the DNeasy® Blood &amp; Tissue Kit (Qiagen) following the manufacturer protocols. Partial (V4) 16S rRNA gene sequences were amplified using the 515f forward primer and 806r reverse primer (Caporaso et al. 2011) and sequenced on an Illumina MiSeq platform at Molecular Research LP (Shallowater, TX). Illumina sequence reads were processed in mothur v1.38.0 (Schloss et al. 2009) using a modified version of the bioinformatics pipeline described in Weigel and Erwin (2016). Briefly, raw sequences (n = 13.9 million) were demultiplexed, quality-filtered, aligned, classified, and clustered into operational taxonomic units (OTUs) at 97% sequence identity (nOTU = 25,712). Sequence libraries for each sample were subsampled to the lowest read count (n = 15,825), and all data analyses were based on the subsampled dataset. Sequence data were deposited in the Sequence Read Archive (SRA) for microbial data (16S ribosomal RNA gene sequences, Illumina MiSeq platform) of the National Center for Biotechnology under Accession number SRP142647 (<a href="https://www.ncbi.nlm.nih.gov/sra/SRP142647" target="_blank">https://www.ncbi.nlm.nih.gov/sra/SRP142647</a>).</p>
<p>GenBank Database for sponge data (Mitochondrial cytochrome oxidase subunit I genes, Sanger platform). Accession numbers MH297440 to MH297461. <a href="https://www.ncbi.nlm.nih.gov/nuccore/?term=Microbial+Symbionts%2C+Carbon+and+Nutrient+Cycling+in+Caribbean+Coral+Reef+Sponges" target="_blank">https://www.ncbi.nlm.nih.gov/nuccore/?term=Microbial+Symbionts%2C+Carbon+and+Nutrient+Cycling+in+Caribbean+Coral+Reef+Sponges</a></p>
Specified by the Principal Investigator(s)
<p><strong>Data analysis</strong><br />
<strong>Microbial community diversity</strong><br />
Diversity statistics (Shannon-Weaver, OTU richness, Simpson) were calculated in mothur using OTU relative abundance data. Two-way nested analyses of variance (ANOVA) were used to test for significant differences in diversity indices for two factors: "source" (sponge species or seawater) and “location” (Key Largo or Belize) nested within source in JMP (version 12.0), followed by Tukey’s honest significant difference (HSD) tests to assess multiple post hoc comparisons of means.<br />
<br />
<strong>Microbial community structure</strong><br />
Bray-Curtis similarity matrices were constructed using square root transformed OTU relative abundance data to give more even representation of rare and abundant taxa in community comparisons using Primer-e (version 6.1.11) and visualized in a cluster dendrogram and a two-dimensional non-metric multidimensional scaling (nMDS) plot. A permutational multivariate analysis of variance (PERMANOVA, version 1.0.1) was conducted to test for significant differences in microbial community structure across two factors: “source” and “location” nested within source, with significance determined by Monte Carlo asymptotic P values.<br />
<br />
<strong>OTU-level analyses</strong><br />
Similarity percentage (SIMPER) analysis was used to identify individual OTUs driving the overall dissimilarity between microbial communities within each sponge species, using OTU relative abundance matrices and a cumulative dissimilarity cutoff percentage of 0.70. Significant differences in OTU relative abundances were assessed using Metastats (White et al. 2009) in mothur with 1000 permutations. OTUs of interest were then taxonomically identified and compared to OTUs identified in nutrient correlations (see below).</p>
<p><strong>Correlations between microbial community diversity and carbon/nutrient flux</strong><br />
Spearman rank-order correlations were conducted in SigmaPlot (version 11) to assess relationships between microbial diversity indices (Shannon-Weaver, OTU richness, Simpson) and carbon/nutrient flux data (DOC, POC, NOx, NH4, and PO4). Correlations between microbial community structure and carbon/nutrient flux Distance-based linear models (DistLM) were conducted in Primer-e to assess correlations between microbial community (Bray-Curtis) similarity and carbon/nutrient flux data (DOC, POC, NOx, NH4, and PO4) and visualized with distance-based redundancy analysis (dbRDA) plots. Specifically, carbon and nutrient flux measurements estimated from specific filtration rates (SFR, μmol C, or nutrient/s/L sponge) were tested as marginal predictor variables for microbial community similarity within and among sponge species. Analyses were repeated using Bray-Curtis similarity matrices constructed from untransformed (raw) data, showing identical significance patterns and thus minimal impact of data transformation on statistical results. Analyses were also repeated using carbon and nutrient uptake (Cin–Cex) instead of specific filtration rates, showing similar statistical patterns when considering a metric not influenced by pumping rates. Inter-specific comparisons were conducted at three levels: all sponge species, within each sponge category (HMA, LMA), and between each pairwise species comparison. Pearson correlations were run in JMP to compare nutrient flux data (POC and NH4) in the form of SFR and OTU abundance counts for the first 1000 OTUs within each sponge species.<br />
<br />
<strong>Functional gene PCR screening</strong><br />
To test for the presence of signature functional genes involved in nitrogen cycling processes (nitrification: ammonia monooxygenase, amoA/amoB; nitrogen fixation: nitrogenase, nifH; and denitrification: nitrite reductase, nirS), the following primer pairs and cited procedures were used: Arch-amoAF and Arch-amoAR (Francis et al. 2005), AmoBMF and AmoBMR (Calvo et al. 2004), nif1/2 and nif3/4 (Mohamed et al. 2008), nirS1F and nirS6R (Yang et al. 2012). For all sponge species, at least two replicates were tested for the presence of each functional gene, except for Aplysina archeri (only one sample available). If positive, all remaining replicates of that species were tested at both sites. If negative, the PCR was repeated twice for verification.</p>
<p><strong>BCO-DMO Processing: </strong><br />
- Converted dates to format YYYY-MM-DD;<br />
- Adjusted field/parameter names to comply with BCO-DMO naming conventions;<br />
- Added a conventional header with dataset name, PI names, version date;<br />
- Split lat/lon into separate columns and converted longitude from West to East to comply with BCO-DMO standards.</p>
Specified by the Principal Investigator(s)
asNeeded
7.x-1.1
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
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SonTek acoustic doppler velocimeter
SonTek acoustic doppler velocimeter
PI Supplied Instrument Name: SonTek acoustic doppler velocimeter Instrument Name: Acoustic Doppler Velocimeter Instrument Short Name:ADV Instrument Description: ADV is the acronym for acoustic doppler velocimeter. The ADV is a remote-sensing, three-dimensional velocity sensor. Its operation is based on the Doppler shift effect. The sensor can be deployed either as a moored instrument or attached to a still structure near the seabed.
Reference:
G. Voulgaris and J. H. Trowbridge, 1998. Evaluation of the Acoustic Doppler Velocimeter (ADV) for Turbulence Measurements. J. Atmos. Oceanic Technol., 15, 272–289. doi: http://dx.doi.org/10.1175/1520-0426(1998)0152.0.CO;2 Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/384/
Illumina MiSeq platform
Illumina MiSeq platform
PI Supplied Instrument Name: Illumina MiSeq platform Instrument Name: Automated DNA Sequencer Instrument Short Name:Automated Sequencer Instrument Description: A DNA sequencer is an instrument that determines the order of deoxynucleotides in deoxyribonucleic acid sequences.
PI Supplied Instrument Name: Instrument Name: Bran Luebbe AA3 AutoAnalyzer Instrument Short Name:Bran Luebbe AA3 AutoAnalyzer Instrument Description: Bran Luebbe AA3 AutoAnalyzer
See the description from the manufacturer. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/LAB04/
CE Elantech NC2100 Elemental Analyzer
CE Elantech NC2100 Elemental Analyzer
PI Supplied Instrument Name: CE Elantech NC2100 Elemental Analyzer Instrument Name: Elemental Analyzer Instrument Short Name: Instrument Description: Instruments that quantify carbon, nitrogen and sometimes other elements by combusting the sample at very high temperature and assaying the resulting gaseous oxides. Usually used for samples including organic material. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/LAB01/
AB 3500 Applied Biosystems Gene Analyzer
AB 3500 Applied Biosystems Gene Analyzer
PI Supplied Instrument Name: AB 3500 Applied Biosystems Gene Analyzer Instrument Name: Gene Analyzer Instrument Short Name: Instrument Description: An automated analyzer designed for a wide range of sequencing and fragment analysis applications with the ability to perform comparative sequencing, linkage analysis, STR analysis, SNP detection, discovery and validation, mutation detection, and many other applications.
Shimadzu TOC 5050 analyzer
Shimadzu TOC 5050 analyzer
PI Supplied Instrument Name: Shimadzu TOC 5050 analyzer Instrument Name: Shimadzu TOC-L Analyzer Instrument Short Name:Shimadzu TOC-L Instrument Description: A Shimadzu TOC-L Analyzer measures DOC by high temperature combustion method.
Developed by Shimadzu, the 680 degree C combustion catalytic oxidation method is now used worldwide. One of its most important features is the capacity to efficiently oxidize hard-to-decompose organic compounds, including insoluble and macromolecular organic compounds. The 680 degree C combustion catalytic oxidation method has been adopted for the TOC-L series.
http://www.shimadzu.com/an/toc/lab/toc-l2.html Community Standard Description: http://onto.nerc.ac.uk/CAST/124.html