http://lod.bco-dmo.org/id/dataset/537137
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
2014-11-03
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Environmental measurements from ARISA samples, San Pedro Channel, 5 depths , 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/537137
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) Environmental measurements from ARISA samples, San Pedro Channel, 5 depths , 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/537137 [access date]
Environmental measurements from ARISA samples, San Pedro Channel, 5 depths Dataset Description: <p>All measurements were taken from August 2000 – January 2011 at five depths from the San Pedro Channel 5m, the Deep Chlorophyll Maximum (DCM or CMAX), 150m, 500m, 890m.<span style="font-size:12.7272720336914px">&nbsp;Additional data will be added periodically.</span></p>
<p><strong>Related Dataset:</strong><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/535507" target="_blank">ARISA Bin Taxonomy</a><br />
<a href="http://www.bco-dmo.org/dataset/536264" target="_blank">SPOT cruises</a></p> Methods and Sampling: <p>Water samples were collected on monthly trips to the SPOT station in the San Pedro Basin.</p>
<p>Cruise logs are available at:&nbsp;<a href="http://dornsife.usc.edu/spot/document-access/" target="_blank">http://dornsife.usc.edu/spot/document-access/</a></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
onGoing
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
year
cruise_id2
cruise_id
lat
lon
month
date_local
DayI
days_shift
days_elapsed
day_length
day_length_change_per_month
MEI
PRCP
PrecipCat
AirTempMax
AirTempMin
Sverdrup_trans
Upwelling
vert_vol_Eckman
WindGust
DomWavePd
WaveHeight
AvgWavePd
SSHD_Sat
AvgWind
Chl_A_Sat
ChlA_Sat8
Prim_Prod
Prim_Prod8
CDOM
depth
depth_n
depth_mixlayr
Cmax_Depth
temp
temp_CTD
sal
sal_CTD
cond
sigma_theta
PAR
NO2
NO3_NO2
PO4
Pstar_P_N
POC
SiO3
O2Wink
OxygenCS
OxygenCTD
OxygenCurrent
OxygenSaturation
OxygenTemperature
O2Combined
CTD Sea-Bird
Dissolved Oxygen Sensor
theme
None, User defined
year
Cruise identfier
latitude
longitude
month of year
date
day of month
days
length_day
No BCO-DMO term
precip_level
precip_type
air temperature
wind_speed
wave_height
chlorophyll a
production
colored or chromophoric dissolved organic matter
depth
depth nominal
mixed layer depth
water temperature at measurement depth
salinity
salinity from CTD
conductivity
sigma-theta potential density
PAR
Nitrite
nitrate plus nitrite
reactive phosphorus (PO4)
particulate organic Carbon (POC)
Silicate, Si(OH)4, silicic acid
dissolved Oxygen
O2 saturation
featureType
BCO-DMO Standard Parameters
CTD Sea-Bird
Oxygen Sensor
instrument
BCO-DMO Standard Instruments
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
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 Environmental measurements from ARISA samples, San Pedro Channel, 5 depths , 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/537233.rdf
Name: year
Units: YYYY
Description: <p>year of sampling</p>
http://lod.bco-dmo.org/id/dataset-parameter/537234.rdf
Name: cruise_id2
Units: unitless
Description: <p>cruise identification</p>
http://lod.bco-dmo.org/id/dataset-parameter/537235.rdf
Name: cruise_id
Units: unitless
Description: <p>secondary deployment identification: same for all lab work (lab_Fuhrman_2014)</p>
http://lod.bco-dmo.org/id/dataset-parameter/537236.rdf
Name: lat
Units: decimal degrees
Description: <p>latitude; north is positive</p>
http://lod.bco-dmo.org/id/dataset-parameter/537237.rdf
Name: lon
Units: decimal degrees
Description: <p>longitude; east is positive</p>
http://lod.bco-dmo.org/id/dataset-parameter/537238.rdf
Name: month
Units: MM
Description: <p>month of sampling</p>
http://lod.bco-dmo.org/id/dataset-parameter/537239.rdf
Name: date_local
Units: YYYY-MM-DD
Description: <p>sampling date</p>
http://lod.bco-dmo.org/id/dataset-parameter/537240.rdf
Name: DayI
Units: unitless
Description: <p>Day of the month (Imputed with 15 if day not recorded)</p>
http://lod.bco-dmo.org/id/dataset-parameter/537241.rdf
Name: days_shift
Units: days
Description: <p>Number of days since last sample</p>
http://lod.bco-dmo.org/id/dataset-parameter/537242.rdf
Name: days_elapsed
Units: unitless
Description: <p>Date - 08August2000</p>
http://lod.bco-dmo.org/id/dataset-parameter/537243.rdf
Name: day_length
Units: hours
Description: <p>geosphere package in R; daylength(date; 33.55)</p>
http://lod.bco-dmo.org/id/dataset-parameter/537244.rdf
Name: day_length_change_per_month
Units: hours
Description: <p>geosphere package in R; daylength(date; 33.55)</p>
http://lod.bco-dmo.org/id/dataset-parameter/537245.rdf
Name: MEI
Units: Standard Departure
Description: <p>Multivariate ENSO Index</p>
http://lod.bco-dmo.org/id/dataset-parameter/537246.rdf
Name: PRCP
Units: 1/10 mm
Description: <p>Precipitation</p>
http://lod.bco-dmo.org/id/dataset-parameter/537247.rdf
Name: PrecipCat
Units: unitless
Description: <p>Precipitation category</p>
http://lod.bco-dmo.org/id/dataset-parameter/537248.rdf
Name: AirTempMax
Units: 1/10 degrees Celsius
Description: <p>Maximum air temperature</p>
http://lod.bco-dmo.org/id/dataset-parameter/537249.rdf
Name: AirTempMin
Units: 1/10 degrees Celsius
Description: <p>Minimum air temperature</p>
http://lod.bco-dmo.org/id/dataset-parameter/537250.rdf
Name: Sverdrup_trans
Units: ?
Description: <p>Sverdrup transport</p>
http://lod.bco-dmo.org/id/dataset-parameter/537251.rdf
Name: Upwelling
Units: m^3/s/100mCoast
Description: <p>Bakun Upwelling Index</p>
http://lod.bco-dmo.org/id/dataset-parameter/537252.rdf
Name: vert_vol_Eckman
Units: ?
Description: <p>Vertical velocity into the Eckman layer</p>
http://lod.bco-dmo.org/id/dataset-parameter/537253.rdf
Name: WindGust
Units: 1/10 m/s
Description: <p>Maximum 2 minute Wind Gust Speed</p>
http://lod.bco-dmo.org/id/dataset-parameter/537254.rdf
Name: DomWavePd
Units: s
Description: <p>Dominant wave period</p>
http://lod.bco-dmo.org/id/dataset-parameter/537255.rdf
Name: WaveHeight
Units: meters
Description: <p>Wave height</p>
http://lod.bco-dmo.org/id/dataset-parameter/537256.rdf
Name: AvgWavePd
Units: s
Description: <p>Average wave period</p>
http://lod.bco-dmo.org/id/dataset-parameter/537257.rdf
Name: SSHD_Sat
Units: meters
Description: <p>Sea Surface Height Deviation - Aviso: 0.25 degrees; global; science quality; monthly average</p>
http://lod.bco-dmo.org/id/dataset-parameter/537258.rdf
Name: AvgWind
Units: 1/10 m/s
Description: <p>Average wind speed</p>
http://lod.bco-dmo.org/id/dataset-parameter/537259.rdf
Name: Chl_A_Sat
Units: mg/m^3
Description: <p>Chlorophyll-a satellite monthly average</p>
http://lod.bco-dmo.org/id/dataset-parameter/537260.rdf
Name: ChlA_Sat8
Units: mg/m^3
Description: <p>Chlorophyll-a satellite 8 day average</p>
http://lod.bco-dmo.org/id/dataset-parameter/537261.rdf
Name: Prim_Prod
Units: mg_C/m^2/day
Description: <p>Primary productivity satellite monthly average</p>
http://lod.bco-dmo.org/id/dataset-parameter/537262.rdf
Name: Prim_Prod8
Units: mg_C/m^2/day
Description: <p>Primary productivity satellite 8 day average</p>
http://lod.bco-dmo.org/id/dataset-parameter/537263.rdf
Name: CDOM
Units: %
Description: <p>Colored dissolved organic matter index</p>
http://lod.bco-dmo.org/id/dataset-parameter/537264.rdf
Name: depth
Units: meters
Description: <p>Actual depth</p>
http://lod.bco-dmo.org/id/dataset-parameter/537265.rdf
Name: depth_n
Units: meters
Description: <p>sample depth; CMAX = depth of chlorophyl maximum</p>
http://lod.bco-dmo.org/id/dataset-parameter/537266.rdf
Name: depth_mixlayr
Units: meters
Description: <p>Mixed layer depth</p>
http://lod.bco-dmo.org/id/dataset-parameter/537267.rdf
Name: Cmax_Depth
Units: meters
Description: <p>Chlorophyll maximum depth</p>
http://lod.bco-dmo.org/id/dataset-parameter/537268.rdf
Name: temp
Units: degrees Celsius
Description: <p>Temperature</p>
http://lod.bco-dmo.org/id/dataset-parameter/537269.rdf
Name: temp_CTD
Units: degrees Celsius
Description: <p>CTD temperature</p>
http://lod.bco-dmo.org/id/dataset-parameter/537270.rdf
Name: sal
Units: psu
Description: <p>Salinity</p>
http://lod.bco-dmo.org/id/dataset-parameter/537271.rdf
Name: sal_CTD
Units: PSU
Description: <p>CTD salinity</p>
http://lod.bco-dmo.org/id/dataset-parameter/537272.rdf
Name: cond
Units: S/m
Description: <p>CTD conductivity</p>
http://lod.bco-dmo.org/id/dataset-parameter/537273.rdf
Name: sigma_theta
Units: kg/m^3
Description: <p>Sigma theta</p>
http://lod.bco-dmo.org/id/dataset-parameter/537274.rdf
Name: PAR
Units: Einstein*m^-2*day-1
Description: <p>Photosynthetically active radiation</p>
http://lod.bco-dmo.org/id/dataset-parameter/537275.rdf
Name: NO2
Units: uM
Description: <p>Nitrite concentration</p>
http://lod.bco-dmo.org/id/dataset-parameter/537276.rdf
Name: NO3_NO2
Units: uM
Description: <p>Nitrate + Nitrite concentration</p>
http://lod.bco-dmo.org/id/dataset-parameter/537277.rdf
Name: PO4
Units: uM
Description: <p>Phosphate concentration</p>
http://lod.bco-dmo.org/id/dataset-parameter/537278.rdf
Name: Pstar_P_N
Units: uM
Description: <p>[Phosphate]- [Nitrate + Nitrite]/16</p>
http://lod.bco-dmo.org/id/dataset-parameter/537279.rdf
Name: POC
Units: mg*m^-3
Description: <p>Particulate organic carbon</p>
http://lod.bco-dmo.org/id/dataset-parameter/537280.rdf
Name: SiO3
Units: uM
Description: <p>Silicate concentration</p>
http://lod.bco-dmo.org/id/dataset-parameter/537281.rdf
Name: O2Wink
Units: ml/L
Description: <p>Winkler Oxygen</p>
http://lod.bco-dmo.org/id/dataset-parameter/537282.rdf
Name: OxygenCS
Units: uM
Description: <p>Oxygen concentration</p>
http://lod.bco-dmo.org/id/dataset-parameter/537283.rdf
Name: OxygenCTD
Units: ml/l
Description: <p>CTD Oxygen concentration</p>
http://lod.bco-dmo.org/id/dataset-parameter/537284.rdf
Name: OxygenCurrent
Units: uA
Description: <p>CTD Oxygen current</p>
http://lod.bco-dmo.org/id/dataset-parameter/537285.rdf
Name: OxygenSaturation
Units: ml/l
Description: <p>CTD maximum Oxygen saturation potential</p>
http://lod.bco-dmo.org/id/dataset-parameter/537286.rdf
Name: OxygenTemperature
Units: degrees Celsius
Description: <p>CTD Oxygen temperature</p>
http://lod.bco-dmo.org/id/dataset-parameter/537287.rdf
Name: O2Combined
Units: ml/l
Description: <p>Winkler data measurment if available; if not - estimated from CTD measument and linear model comparing CTD to winkler measuments</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
152804
https://datadocs.bco-dmo.org/file/p99nD4MupxkXo1/arisa_latlon_sort_vess_phys.csv
arisa_latlon_sort_vess_phys.csv
Primary data file for dataset ID 537137
download
https://osprey.bco-dmo.org/dataset/537137/data/download
download
onLine
dataset
<p>Water samples were collected on monthly trips to the SPOT station in the San Pedro Basin.</p>
<p>Cruise logs are available at:&nbsp;<a href="http://dornsife.usc.edu/spot/document-access/" target="_blank">http://dornsife.usc.edu/spot/document-access/</a></p>
Specified by the Principal Investigator(s)
<p>Detailed information on the <strong><a href="http://dmoserv3.whoi.edu/data_docs/Bact_Arch_Prot_Biodiversity/Cram_Suppl_Methods.pdf" target="_blank">methodology</a></strong> (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>Relevent 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>
<p><strong>BCO-DMO Processing:</strong></p>
<p>- added conventional header with dataset name, PI name, version date<br />
- renamed parameters to BCO-DMO standard or more descriptive terms<br />
- split data into physical and biological datasets to reduce overall size of each dataset<br />
- replaced NA with nd<br />
- reformated data from m/d/yyyy to yyyy-mm-dd<br />
- changed year from 1 or 2 digits to 4 digits<br />
- added lat, lon, cruise_id, cruise_id2<br />
-&nbsp;<span style="font-size:12.7272720336914px">missing</span><span style="font-size:12.7272720336914px">&nbsp;</span><span style="font-size:13px">depth data added from </span><a href="http://dornsife.usc.edu/spot/document-access/" style="font-size: 13px; line-height: 1.6;" target="_blank">CTD logs</a><span style="font-size:13px"> where&nbsp;available</span></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
CTD Sea-Bird
CTD Sea-Bird
PI Supplied Instrument Name: CTD Sea-Bird Instrument Name: CTD Sea-Bird Instrument Short Name:CTD Sea-Bird Instrument Description: A Conductivity, Temperature, Depth (CTD) sensor package from SeaBird Electronics. This instrument designation is used when specific make and model are not known or when a more specific term is not available in the BCO-DMO vocabulary. Refer to the dataset-specific metadata for more information about the specific CTD used. More information from: http://www.seabird.com/ Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/130/
Dissolved Oxygen Sensor
Dissolved Oxygen Sensor
PI Supplied Instrument Name: Dissolved Oxygen Sensor PI Supplied Instrument Description:Sea-bird, model 13 Instrument Name: Oxygen Sensor Instrument Short Name:Dissolved Oxygen Sensor Instrument Description: An electronic device that measures the proportion of oxygen (O2) in the gas or liquid being analyzed
Deployment: lab_Fuhrman_2014
lab_Fuhrman_2014
USC
laboratory
lab_Fuhrman_2014
Jed A. Fuhrman
University of Southern California
USC
laboratory