http://lod.bco-dmo.org/id/dataset/535507
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
2014-10-17
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Putative taxonomic information for ARISA bins as generated from clone libraries, 2014 (Bacterial, Archaeal, and Protistan Biodiversity project, Marine Viral Dynamics project)
2014-11-03
publication
2014-11-03
revision
BCO-DMO Linked Data URI
2014-11-03
creation
http://lod.bco-dmo.org/id/dataset/535507
Jed A. Fuhrman
University of Southern California
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: Fuhrman, J. A. (2014) Putative taxonomic information for ARISA bins as generated from clone libraries, 2014 (Bacterial, Archaeal, and Protistan Biodiversity project, Marine Viral Dynamics project). Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 2014-11-05) Version Date 2014-11-03 [if applicable, indicate subset used]. http://lod.bco-dmo.org/id/dataset/535507 [access date]
Putative taxonomic information for ARISA bins as generated from clone libraries, Dataset Description: <p>This dataset contains&nbsp;putative taxonomic information for the ARISA bins, as generated from clone libraries. The protocol for assigning these IDs is described in Cram et al. (in press).</p>
<p>This file also contains statistics (eg. mean, standard deviation, etc.) of every variable measured.</p>
<p><strong>Related Dataset:</strong><br />
<a href="http://www.bco-dmo.org/dataset/537137" target="_blank">SPOT environmental data</a><br />
<a href="http://www.bco-dmo.org/dataset/535915" target="_blank">ARISA Relative Abundances</a><br />
<a href="http://www.bco-dmo.org/dataset/536264" target="_blank">SPOT cruises</a></p> Methods and Sampling: <p>Detailed information on the <a href="http://dmoserv3.whoi.edu/data_docs/Bact_Arch_Prot_Biodiversity/Cram_Suppl_Methods.pdf" target="_blank">Methodology</a> (pdf), including:<br />
&nbsp;&nbsp; &nbsp;Satellite measurements<br />
&nbsp;&nbsp; &nbsp;Assigning Taxonomic Identities to ARISA peaks<br />
&nbsp;&nbsp; &nbsp;Environmental parameter variability<br />
&nbsp;&nbsp; &nbsp;Seasonal variability of microbial community structure<br />
&nbsp;&nbsp; &nbsp;Mantel test approach<br />
&nbsp;&nbsp; &nbsp;Interannual variability of microbial community structure<br />
&nbsp;&nbsp; &nbsp;Alpha diversity:&nbsp;<br />
&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Variability between depths<br />
&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Relation to season<br />
&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Relation to community similarity between depths<br />
&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Relation to community change<br />
&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Environmental parameters and community structure: Mantel tests<br />
&nbsp;&nbsp; &nbsp;Temporal dynamics of microbial taxa over time<br />
&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Transformations<br />
&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Taxonomic Groups<br />
&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;OTUs</p>
<p><strong>Relavent References:</strong></p>
<p>Beman JM, Steele JA, Fuhrman JA. (2011). Co-occurrence patterns for abundant marine archaeal and bacterial lineages in the deep chlorophyll maximum of coastal California. ISME J 5: 1077-1085.</p>
<p>Cram JA, Chow C-ET, Sachdeva R, et al. (2014) Seasonal and interannual variability of the marine bacterioplankton community throughout the water column over ten years. The ISME Journal. doi: 10.1038/ismej.2014.153.</p>
<p>Frouin R, Franz BA, Werdell PJ (2003) The SeaWiFS PAR product. Algorithm updates for the fourth SeaWiFS data reprocessing 46-50.</p>
<p>Fuhrman J, Azam F (1982) Thymidine incorporation as a measure of heterotrophic bacterioplankton production in marine surface waters - evaluation and field results. marine biology 66:109-120.</p>
<p>Kirchman D, K’nees E, Hodson R (1985) Leucine incorporation and its potential as a measure of protein synthesis by bacteria in natural aquatic systems. Appl Environ Microbiol 49:599-607.</p>
<p>Morel A, Gentili B (2009) A simple band ratio technique to quantify the colored dissolved and detrital organic material from ocean color remotely sensed data. Remote Sensing of Environment 113:998-1011. doi: 10.1016/j.rse.2009.01.008</p>
<p>Noble RT, Fuhrman JA. (1998). Use of SYBR Green I for rapid epifluorescence counts of marine viruses and bacteria. Aquat. Microb. Ecol 14: 113-118.</p>
<p>Parsons TR (1984) A manual of chemical and biological methods for seawater analysis, 1st ed. Pergamon Press, Oxford [Oxfordshire]; New York</p>
<p>Patel A, Noble RT, Steele JA, Schwalbach MS, Hewson I, Fuhrman JA. (2007). Virus and prokaryote enumeration from planktonic aquatic environments by<br />
epifluorescence microscopy with SYBR Green I. Nat Protoc 2: 269-276.</p>
<p>Stramski D, Reynolds RA, Babin M, et al. (2008) Relationships between the surface concentration of particulate organic carbon and optical properties in the eastern South Pacific and eastern Atlantic Oceans. Biogeosciences 5:171-201.</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1136818 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1136818
Funding provided by NSF Division of Molecular and Cellular Biosciences (NSF MCB) Award Number: MCB-0703159 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=0703159
completed
Jed A. Fuhrman
University of Southern California
213-740-5757
Dept. Biological Sciences, Dornsife College of Letters, Arts, and Sciences 3616 Trousdale Parkway
Los Angeles
CA
90089-0371
USA
fuhrman@usc.edu
pointOfContact
asNeeded
Dataset Version: 2014-11-05
Unknown
nodeIDs
nodeType
nodeDepths
mean
sd
median
mad
count1000
countALL
LB
UB
Project
Location
DepthCat
Clone1Hits
Clone2Hits
OtherHits
Clone1ID
Clone2ID
Accession
SecAccession
Domain
Phylum
Class
Order
Family
Genus
Species
SilvaTag
RDP_Clade
Ecotype
SecDomain
SecPhylum
SecClass
SecOrder
SecFamily
SecGenus
SecSpecies
SecSilvaTag
SecRDP_Clade
SecEcotype
Letter6
amean
asd
amedian
amad
acount1000
acountall
theme
None, User defined
No BCO-DMO term
mean
project
region
Depth_Loc
accession number
phylum
taxonomic class
order
family
genus
species scientific name (binomial)
featureType
BCO-DMO Standard Parameters
lab_Fuhrman_2014
service
Deployment Activity
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.
Dimensions of Biodiversity
http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=503446
Dimensions of Biodiversity
(adapted from the NSF Synopsis of Program)
Dimensions of Biodiversity is a program solicitation from the NSF Directorate for Biological Sciences. FY 2010 was year one of the program. [MORE from NSF]
The NSF Dimensions of Biodiversity program seeks to characterize biodiversity on Earth by using integrative, innovative approaches to fill rapidly the most substantial gaps in our understanding. The program will take a broad view of biodiversity, and in its initial phase will focus on the integration of genetic, taxonomic, and functional dimensions of biodiversity. Project investigators are encouraged to integrate these three dimensions to understand the interactions and feedbacks among them. While this focus complements several core NSF programs, it differs by requiring that multiple dimensions of biodiversity be addressed simultaneously, to understand the roles of biodiversity in critical ecological and evolutionary processes.
Dimensions of Biodiversity
largerWorkCitation
program
Pattern and Process in Marine Bacterial, Archaeal, and Protistan Biodiversity, and Effects of Human Impacts
http://dornsife.usc.edu/labs/usc-microbial-observatory/
Pattern and Process in Marine Bacterial, Archaeal, and Protistan Biodiversity, and Effects of Human Impacts
<p><em>Description from NSF award abstract:</em><br />
Bacteria, Archaea, and Protists dominate global elemental cycling and are immensely diverse genetically, taxonomically, and functionally. Yet the extent of marine microbial diversity, its patterns, and relationships among genetic, taxonomic, and functional diversity are very poorly characterized, even though the ocean covers 70% of the planet's surface. Among the least well known variables is the effect of human impacts on native marine microbial systems, although it is recognized that impacted systems are more prone to events like harmful algal blooms. Knowledge of these relationships and impacts are necessary to anticipate the responses of biota to global changes and feedback mechanisms that may alter the extents, rates, and even pathways of such changes. This project will expand upon an existing NSF-funded 10+-year monthly ocean time series (Microbial Observatory) that has focused on a single site midway between Los Angeles and Santa Catalina Island, to also include quarterly sampling adjacent to the impacted LA Harbor region to the barely-impacted Catalina coast. USC already runs facilities in LA Harbor and Catalina, with daily boats between (no cost). Measurements include (1) Genetic diversity: high throughput DNA sequences of "housekeeping" and functional genes. (2) Taxonomic diversity: high throughput tag sequences of small subunit ribosomal RNA genes, flow cytometry, automated image analysis (3) Functional Diversity: (a) Functional measurements (carbon fixation and respiration rates, microbial growth and grazing rates, cell size, morphology, and biomass variations), (b) distribution and expression of particular target functional genes involved with processes central to the cycles of carbon, nitrogen, and sulfur, (c) exploratory metatranscriptomics to explore functionalities that were not anticipated. (4) Integrating these: Multivariate statistical and network approaches including newly developed techniques (e.g. Bayesian networks to examine cause-effect relationships), and high speed computational approaches to assess the relationships among the genetic, taxonomic, and functional aspects of biodiversity observed. The PIs will also examine the collected data for signatures and specific effects (on organism identity and functions) associated with human impacted harbor site vs. the relatively pristine one.</p>
<p>The PIs will use network and time series analysis, along with other statistical tools to integrate "classical" microbial and oceanographic rate process measurements, flow cytometric and microscopic characterizations of communities, along with targeted as well as untargeted metagenomics and metatranscriptomics to relate genetic and taxonomic diversity with specific functions (at organismal, food web, and system levels). For example, they should be able to determine how different variants of particular taxa (e.g. at resolution levels ranging from what might be considered near the subspecies to genus levels) would differ in their association with particular measured functions, functional genes, or particular other taxa - or they might see how particular clusters of related organisms behave similarly or differently in their associations. This project offers an unprecedented and potentially transformative opportunity to combine and integrate measurements of genetic, taxonomic, and functional diversity along with direct measurements of system function in a well studied marine system that includes a gradient from one of the world's busiest harbors to a largely pristine ocean habitat. Far beyond just describing the distributions of organisms and functions (itself a necessary first step), they will specifically link spatial and temporal variations in a variety of functions with variations in genetic and taxonomic community composition.</p>
Bacterial, Archaeal, and Protistan Biodiversity
largerWorkCitation
project
Marine viral dynamics and incorporation into microbial association networks
http://dornsife.usc.edu/labs/fuhrmanlab/research/
Marine viral dynamics and incorporation into microbial association networks
<p><em>Description from NSF award abstract:</em><br />
Marine microbes are tremendously abundant and are major players and driving forces in global biogeochemical cycles of carbon, nitrogen, phosphorus, and iron. We learned over the past two decades that viruses are pervasive elements in marine systems, with significant ecological, biogeochemical, genetic, and evolutionary effects on cellular marine organisms, but we have remarkably little information about the dynamics of marine viral community structure and how it relates to the community structure of their hosts (largely bacteria and phytoplankton). Such information is critical for developing proper conceptual and practical models of the roles of viruses and how these change over time and space. The goals of this project are:<br />
(1) primarily, to characterize a significant subset of the natural virus community and its dynamics, along with bacterial host communities, as they change over daily to monthly time scales at the USC well-studied marine Microbial Observatory site (midway between Los Angeles and Santa Catalina Island), testing hypotheses regarding repeating patterns, host range effects, and taxa-time relationships, and<br />
(2) secondarily, to incorporate these viruses into microbial association networks by statistically connecting particular types of viruses to specific potential hosts.</p>
<p>Approaches for this study include:<br />
(a) nested daily, weekly, and monthly collection of bacteria and viruses for nucleic acid samples,<br />
(b) amplification of conserved genes, as proxy phylogenetic markers, from a few moderately-well-characterized broad viral groups previously readily found in seawater (i.e. the T4-like myoviruses, T7-like podoviruses), as well as bacterial rRNA genes,<br />
(c) extensive sequencing, after screening by community fingerprinting, from the mixed amplified products,<br />
(d) binning of the sequences or fingerprint fragments into operational taxonomic units (OTUs) at different levels of resolution,<br />
(e) evaluation of the results with statistical approaches to examine temporal patterns, relationships (including time-lagged ones) with other viral OTUs, bacteria, protists (monthly only), and environmental parameters,<br />
(f) incorporating the viral OTUs mathematically into microbial association networks.</p>
<p>Data on environmental parameters, bacteria, and protists are already being collected monthly for an existing Microbial Observatory, so the viral work is complementary to this project, providing a major value-added component. Similarly, this project will add selected daily and weekly microbial data to the Microbial Observatory. Data from the literature and from the PI's preliminary results show they have the technology and capability to meet the first goal, and to our knowledge this would be the first such data set of its scope and kind. The investigators have already published in 2006 that the bacterial communities at the 5m depth of this site show a predictable repeating annual cycle in bacterial community composition, so the expectation of a predictable repeating viral community is not unreasonable. They also have some preliminary data showing some repeated viral occurrences. The second goal requires that there are indeed significant statistical relationships between the viruses and other measured parameters, which the PI anticipates to be the case, but of course cannot predict; if they cannot be demonstrated, this result itself would be informative and would constrain the possible modes of microbial/viral interactions.</p>
Marine Viral Dynamics
largerWorkCitation
project
eng; USA
biota
oceans
2014-11-03
From projects that focused on the following 2 locations: 1. San Pedro Ocean Time Series; approx. 33N, 118W 2. Southern California between Los Angeles and Santa Catalina Island; Approx. 33.5N, 118.5 W
0
BCO-DMO catalogue of parameters from Putative taxonomic information for ARISA bins as generated from clone libraries, 2014 (Bacterial, Archaeal, and Protistan Biodiversity project, Marine Viral Dynamics 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
http://lod.bco-dmo.org/id/dataset-parameter/537427.rdf
Name: nodeIDs
Units: unitless
Description: <p>Full name of variable; if arisa fragment the format is depth_ARISA_ITS-length; if environmental variable depth_variable-name</p>
http://lod.bco-dmo.org/id/dataset-parameter/537428.rdf
Name: nodeType
Units: unitless
Description: <p>ARISA=arisa fragment bin; Env= other measurement</p>
http://lod.bco-dmo.org/id/dataset-parameter/537429.rdf
Name: nodeDepths
Units: meters
Description: <p>depth to which the measurment corresponds</p>
http://lod.bco-dmo.org/id/dataset-parameter/537430.rdf
Name: mean
Units: various
Description: <p>mean value of parameter at a given depth - ARISA node or environmental parameter as described in nodeIDs</p>
http://lod.bco-dmo.org/id/dataset-parameter/537431.rdf
Name: sd
Units: various
Description: <p>standard deviation of parameter - ARISA node or environmental parameter as described in nodeIDs</p>
http://lod.bco-dmo.org/id/dataset-parameter/537432.rdf
Name: median
Units: various
Description: <p>median value of parameter - ARISA node or environmental parameter as described in nodeIDs</p>
http://lod.bco-dmo.org/id/dataset-parameter/537433.rdf
Name: mad
Units: various
Description: <p>median adjusted deviation - ARISA node or environmental parameter as described in nodeIDs</p>
http://lod.bco-dmo.org/id/dataset-parameter/537434.rdf
Name: count1000
Units: unitless
Description: <p>count1000 is the number of occurrences in the data set in which the organism shows up with greater than 0.1% relative abundance.</p>
http://lod.bco-dmo.org/id/dataset-parameter/537435.rdf
Name: countALL
Units: unitless
Description: <p>the number of occurrences in the data set in which the organism shows up with greater than 0.01% relative abundance</p>
http://lod.bco-dmo.org/id/dataset-parameter/537436.rdf
Name: LB
Units: unitless
Description: <p>lower bound of ARISA fragment bin</p>
http://lod.bco-dmo.org/id/dataset-parameter/537437.rdf
Name: UB
Units: unitless
Description: <p>upper bound of ARISA fragment bin</p>
http://lod.bco-dmo.org/id/dataset-parameter/537438.rdf
Name: Project
Units: unitless
Description: <p>Identity of project from which clone (used to identify the bin) was isolated</p>
http://lod.bco-dmo.org/id/dataset-parameter/537439.rdf
Name: Location
Units: unitless
Description: <p>Location from which the clone (used to identify the bin) was isolated</p>
http://lod.bco-dmo.org/id/dataset-parameter/537440.rdf
Name: DepthCat
Units: unitless
Description: <p>Category of depth from which that clone was isolated: surf <10m deep; >=500m; nd = unknown</p>
http://lod.bco-dmo.org/id/dataset-parameter/537441.rdf
Name: Clone1Hits
Units: unitless
Description: <p>Number of occurrences in library of most frequently found clone of this ARISA fragment size</p>
http://lod.bco-dmo.org/id/dataset-parameter/537442.rdf
Name: Clone2Hits
Units: unitless
Description: <p>Number of occurrences in library of second most frequently found clone of this ARISA fragment size</p>
http://lod.bco-dmo.org/id/dataset-parameter/537443.rdf
Name: OtherHits
Units: unitless
Description: <p>Number of occurences in library of other clones of this ARISA fragment size</p>
http://lod.bco-dmo.org/id/dataset-parameter/537444.rdf
Name: Clone1ID
Units: unitless
Description: <p>Internal ID number for Clone 1</p>
http://lod.bco-dmo.org/id/dataset-parameter/537445.rdf
Name: Clone2ID
Units: unitless
Description: <p>Internal ID number for Clone 2</p>
http://lod.bco-dmo.org/id/dataset-parameter/537446.rdf
Name: Accession
Units: unitless
Description: <p>NCBI accession number of clone1</p>
http://lod.bco-dmo.org/id/dataset-parameter/537447.rdf
Name: SecAccession
Units: unitless
Description: <p>NCBI accession of clone2</p>
http://lod.bco-dmo.org/id/dataset-parameter/537448.rdf
Name: Domain
Units: unitless
Description: <p>Clone 1 Greengenes Domain ID</p>
http://lod.bco-dmo.org/id/dataset-parameter/537449.rdf
Name: Phylum
Units: unitless
Description: <p>Clone 1 Greengenes Phylum</p>
http://lod.bco-dmo.org/id/dataset-parameter/537450.rdf
Name: Class
Units: unitless
Description: <p>Clone 1 Greengenes Class</p>
http://lod.bco-dmo.org/id/dataset-parameter/537451.rdf
Name: Order
Units: unitless
Description: <p>Clone 1 Greengenes Order</p>
http://lod.bco-dmo.org/id/dataset-parameter/537452.rdf
Name: Family
Units: unitless
Description: <p>Clone 1 Greengenes Family</p>
http://lod.bco-dmo.org/id/dataset-parameter/537453.rdf
Name: Genus
Units: unitless
Description: <p>Clone 1 Greengenes Genus</p>
http://lod.bco-dmo.org/id/dataset-parameter/537454.rdf
Name: Species
Units: unitless
Description: <p>Clone 1 Greengenes Species</p>
http://lod.bco-dmo.org/id/dataset-parameter/537455.rdf
Name: SilvaTag
Units: unitless
Description: <p>Clone 1 Silva Taxonomy finest level identifier</p>
http://lod.bco-dmo.org/id/dataset-parameter/537456.rdf
Name: RDP_Clade
Units: unitless
Description: <p>Clone 1 RDP Taxonomy clade level identifier</p>
http://lod.bco-dmo.org/id/dataset-parameter/537457.rdf
Name: Ecotype
Units: unitless
Description: <p>Ecotype as assigned by Chow et al 2013</p>
http://lod.bco-dmo.org/id/dataset-parameter/537458.rdf
Name: SecDomain
Units: unitless
Description: <p>Clone 2 Greengenes Domain ID</p>
http://lod.bco-dmo.org/id/dataset-parameter/537459.rdf
Name: SecPhylum
Units: unitless
Description: <p>Clone 2 Greengenes Phylum</p>
http://lod.bco-dmo.org/id/dataset-parameter/537460.rdf
Name: SecClass
Units: unitless
Description: <p>Clone 2 Greengenes Class</p>
http://lod.bco-dmo.org/id/dataset-parameter/537461.rdf
Name: SecOrder
Units: unitless
Description: <p>Clone 2 Greengenes Order</p>
http://lod.bco-dmo.org/id/dataset-parameter/537462.rdf
Name: SecFamily
Units: unitless
Description: <p>Clone 2 Greengenes Family</p>
http://lod.bco-dmo.org/id/dataset-parameter/537463.rdf
Name: SecGenus
Units: unitless
Description: <p>Clone 2 Greengenes Genus</p>
http://lod.bco-dmo.org/id/dataset-parameter/537464.rdf
Name: SecSpecies
Units: unitless
Description: <p>Clone 2 Greengenes Species</p>
http://lod.bco-dmo.org/id/dataset-parameter/537465.rdf
Name: SecSilvaTag
Units: unitless
Description: <p>Clone 2 Silva Taxonomy finest level identifier</p>
http://lod.bco-dmo.org/id/dataset-parameter/537466.rdf
Name: SecRDP_Clade
Units: unitless
Description: <p>Clone 2 RDP Taxonomy clade level identifier</p>
http://lod.bco-dmo.org/id/dataset-parameter/537467.rdf
Name: SecEcotype
Units: unitless
Description: <p>Clone 2 Ecotype as assigned by Chow et al 2013</p>
http://lod.bco-dmo.org/id/dataset-parameter/537468.rdf
Name: Letter6
Units: unitless
Description: <p>6 letters or fewer long identifier plus ARISA fragment size</p>
http://lod.bco-dmo.org/id/dataset-parameter/537469.rdf
Name: amean
Units: various
Description: <p>mean value of ARISA fragment</p>
http://lod.bco-dmo.org/id/dataset-parameter/537470.rdf
Name: asd
Units: various
Description: <p>standard deviation of ARISA fragment</p>
http://lod.bco-dmo.org/id/dataset-parameter/537471.rdf
Name: amedian
Units: various
Description: <p>median value of ARISA fragment</p>
http://lod.bco-dmo.org/id/dataset-parameter/537472.rdf
Name: amad
Units: various
Description: <p>median adjusted deviation of ARISA fragment</p>
http://lod.bco-dmo.org/id/dataset-parameter/537473.rdf
Name: acount1000
Units: unitless
Description: <p>the number of times the ARISA fragment is seen with greater than 0.1% relative abundance</p>
http://lod.bco-dmo.org/id/dataset-parameter/537474.rdf
Name: acountall
Units: unitless
Description: <p>the number of times the ARISA fragment is seen with greater than 0.01% relative abundance</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
480082
https://datadocs.bco-dmo.org/file/wnnxNoLTVnYLD6/bins_taxonomy.csv
bins_taxonomy.csv
Primary data file for dataset ID 535507
download
https://osprey.bco-dmo.org/dataset/535507/data/download
download
onLine
dataset
<p>Detailed information on the <a href="http://dmoserv3.whoi.edu/data_docs/Bact_Arch_Prot_Biodiversity/Cram_Suppl_Methods.pdf" target="_blank">Methodology</a> (pdf), including:<br />
&nbsp;&nbsp; &nbsp;Satellite measurements<br />
&nbsp;&nbsp; &nbsp;Assigning Taxonomic Identities to ARISA peaks<br />
&nbsp;&nbsp; &nbsp;Environmental parameter variability<br />
&nbsp;&nbsp; &nbsp;Seasonal variability of microbial community structure<br />
&nbsp;&nbsp; &nbsp;Mantel test approach<br />
&nbsp;&nbsp; &nbsp;Interannual variability of microbial community structure<br />
&nbsp;&nbsp; &nbsp;Alpha diversity:&nbsp;<br />
&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Variability between depths<br />
&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Relation to season<br />
&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Relation to community similarity between depths<br />
&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Relation to community change<br />
&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Environmental parameters and community structure: Mantel tests<br />
&nbsp;&nbsp; &nbsp;Temporal dynamics of microbial taxa over time<br />
&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Transformations<br />
&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Taxonomic Groups<br />
&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;OTUs</p>
<p><strong>Relavent References:</strong></p>
<p>Beman JM, Steele JA, Fuhrman JA. (2011). Co-occurrence patterns for abundant marine archaeal and bacterial lineages in the deep chlorophyll maximum of coastal California. ISME J 5: 1077-1085.</p>
<p>Cram JA, Chow C-ET, Sachdeva R, et al. (2014) Seasonal and interannual variability of the marine bacterioplankton community throughout the water column over ten years. The ISME Journal. doi: 10.1038/ismej.2014.153.</p>
<p>Frouin R, Franz BA, Werdell PJ (2003) The SeaWiFS PAR product. Algorithm updates for the fourth SeaWiFS data reprocessing 46-50.</p>
<p>Fuhrman J, Azam F (1982) Thymidine incorporation as a measure of heterotrophic bacterioplankton production in marine surface waters - evaluation and field results. marine biology 66:109-120.</p>
<p>Kirchman D, K’nees E, Hodson R (1985) Leucine incorporation and its potential as a measure of protein synthesis by bacteria in natural aquatic systems. Appl Environ Microbiol 49:599-607.</p>
<p>Morel A, Gentili B (2009) A simple band ratio technique to quantify the colored dissolved and detrital organic material from ocean color remotely sensed data. Remote Sensing of Environment 113:998-1011. doi: 10.1016/j.rse.2009.01.008</p>
<p>Noble RT, Fuhrman JA. (1998). Use of SYBR Green I for rapid epifluorescence counts of marine viruses and bacteria. Aquat. Microb. Ecol 14: 113-118.</p>
<p>Parsons TR (1984) A manual of chemical and biological methods for seawater analysis, 1st ed. Pergamon Press, Oxford [Oxfordshire]; New York</p>
<p>Patel A, Noble RT, Steele JA, Schwalbach MS, Hewson I, Fuhrman JA. (2007). Virus and prokaryote enumeration from planktonic aquatic environments by<br />
epifluorescence microscopy with SYBR Green I. Nat Protoc 2: 269-276.</p>
<p>Stramski D, Reynolds RA, Babin M, et al. (2008) Relationships between the surface concentration of particulate organic carbon and optical properties in the eastern South Pacific and eastern Atlantic Oceans. Biogeosciences 5:171-201.</p>
Specified by the Principal Investigator(s)
<p><strong>BCO-DMO Processing:</strong></p>
<p>- added conventional header with dataset name, PI name, version date<br />
- moved columns amoA through bcsim89 before the ARISA_# columns<br />
- transformed ARISA_#.# columns to rows with new column of arisa_frag for the arisa name and rel_abund for the values<br />
- replaced NA with nd<br />
- reformated date&nbsp;from m/d/yyyy to yyyy-mm-dd</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.
pointOfContact
Deployment: lab_Fuhrman_2014
lab_Fuhrman_2014
USC
laboratory
lab_Fuhrman_2014
Jed A. Fuhrman
University of Southern California
USC
laboratory