Accessing BCO-DMO data
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| Dataset Title: | [Palau lakes: tissue archive] - Marine lakes of Palau barcoded specimens from transect survey with both lab identification number (M0D#) and original tube number (Do Parallel Patterns Arise from Parallel Processes?) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_768180) |
| Information: | Summary
| License
| ISO 19115
| Metadata
| Background
| Files
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Attributes {
s {
M0D {
String bcodmo_name "sample";
String description "Unique lab number assigned to curate specimens and sequences.";
String long_name "M0 D";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
String units "unitless";
}
Tube_Number {
String bcodmo_name "sample";
String description "The tube number assigned in the field and comprised of the location code; transect/site number; the collector's initials; the target depth in meters; and the cell (i.e. A; B; C; or D).";
String long_name "Tube Number";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
String units "unitless";
}
Field_assigned_phylum {
String bcodmo_name "phylum";
String description "The phylum of the specimen or high level categorization assigned in the field.";
String long_name "Field Assigned Phylum";
String units "unitless";
}
Instant_Field_ID {
String bcodmo_name "sample_descrip";
String description "Identification assigned in the field; In some cases a single tube can contain multiple species but assigned phylum will only reflect one for specimens that were not separated (i.e. multiple taxa in a single logged tube)";
String long_name "Instant Field ID";
String units "unitless";
}
lake_code {
String bcodmo_name "site";
String description "3-letter code for sampled lake name";
String long_name "Lake Code";
String units "unitless";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
String acquisition_description
"Sample collection:
Each lake was sampled using the point intercept transect method at no less
than 10 randomly chosen sites around its perimeter (unless the small size of a
lake precluded this number of non-overlapping sites).\\u00a0 At each site,
three parallel transects approximately were run 5 m apart from the intertidal
(0 m) to the deepest depth accessible to SCUBA divers (i.e. the bottom of the
lake, or bottom of the epilimnion, or the divers\\u2019 maximum certified
depth).\\u00a0 In lakes 8m or deeper, a line (\\u2018the horizontal\\u2019) was
placed, at eight evenly spaced target depths (1\\u20134 m depth intervals,
depending on lake), orthogonal to each of the transect lines so that small
(2.0 cm diameter) cells fell over four points A\\u2013D each at 15 cm
increments to the right of the transect line at the same depth.\\u00a0 At each
depth, from deepest to shallowest, the actual depth was measured in feet with
a dive computer, the \\u2018horizontal\\u2019 was photographed from ~0.5 m
distance, the substrate type was recorded, and then each cell photographed in
close-up.\\u00a0 A tissue sample of the \\u2018primary\\u2019 organism within
each cell, i.e. the organism at the center of the cell, or if no organism in
the centre then the first organisms at the periphery going clockwise from
noon, or if only sediment visible, the organism within the sediment directly
under the Cell was then biopsied for DNA analyses and placed in a container
labeled with site, depth, and cell code A\\u2013D.\\u00a0 Because the benthos
may be three dimensional a \\u2018primary\\u2019 organism might also have many
\\u2018secondary\\u2019 epibionts and/or epiphytes attached.\\u00a0 Any organisms
in the photographs but not sampled were classified as
\\u2018tertiary\\u2019.\\u00a0 After all four cells were sampled at a depth, the
diver ascended to the next shallowest depth on his/her transect and repeated
the procedure.\\u00a0 Thus, at each randomly chosen site, we surveyed a total
of 96 points from the deepest to shallowest depths of the lake habitable by
macro-invertebrates and macrophytes, with two categories of exception. (1) If
a lake was <8 m deep, the number of depths sampled was equivalent to the
maximum depth in meters. (2) Lakes with gently sloping sides could lead to
adjacent target depths being >10 m apart leading to undersampling of
horizontal patchiness; in which case the transect distance between adjacent
target depths was estimated and divided in half or in thirds so that no two
samples were more than 10 transect meters apart.\\u00a0 At the surface, at the
end of each dive, samples were transferred to individual tubes of 95% ethanol
labeled with a field number composed of lake, site, collector, depth, and cell
IDs.\\u00a0 Each evening, new samples were stored in a freezer, dive profiles
were downloaded, and fieldnotes were transcribed to a standardized electronic
data sheet.
Error-checking biodiversity transect files
Each evening, or as soon thereafter as possible, divers compared specimens to
standardize field-identifications and all tissue samples were reconciled to
the electronic data sheet for each lake using tube labels, original field
notes, photographs of specimens in the field, and visual inspection of tube
contents.\\u00a0 If necessary, primary and secondary specimens were placed in
individually labelled tubes of ethanol.\\u00a0 In cases of discrepancy between
electronic notes and original field notes, we edited the electronic data sheet
to be consistent with original notes and corroborated this by double-checking
the original photographs and inspecting tube contents.\\u00a0 Significant
changes\\u2014i.e. samples that could not be reconciled after accounting for
tube transpositions, mislabeling, or mis-identification in the field\\u2014were
logged in a separate file highlighting the specific change and
justification.\\u00a0 If a specimen was unable to be reconciled with notes it
was discarded (this was necessary for only one specimen).\\u00a0 Subsequently,
every tissue sample was assigned an unique identifying number (M0D#) for
curation; during this process, every tenth sample was double-checked for
agreement between the original field number and new M0D#.";
String awards_0_award_nid "55103";
String awards_0_award_number "OCE-1241255";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1241255";
String awards_0_funder_name "NSF Division of Ocean Sciences";
String awards_0_funding_acronym "NSF OCE";
String awards_0_funding_source_nid "355";
String awards_0_program_manager "David L. Garrison";
String awards_0_program_manager_nid "50534";
String cdm_data_type "Other";
String comment
"PaPaPro Tissue Archive
Transect survey barcoded specimens with both lab identification number (M0D#) and original tube number.
M. Dawson (UC-Merced)
version date: 2019-05-13";
String Conventions "COARDS, CF-1.6, ACDD-1.3";
String creator_email "info@bco-dmo.org";
String creator_name "BCO-DMO";
String creator_type "institution";
String creator_url "https://www.bco-dmo.org/";
String data_source "extract_data_as_tsv version 2.3 19 Dec 2019";
String date_created "2019-05-16T19:27:54Z";
String date_modified "2019-07-08T13:00:52Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.768180.1";
String history
"2024-11-23T17:28:44Z (local files)
2024-11-23T17:28:44Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_768180.html";
String infoUrl "https://www.bco-dmo.org/dataset/768180";
String institution "BCO-DMO";
String keywords "assigned, bco, bco-dmo, biological, chemical, code, data, dataset, dmo, erddap, field, Field_assigned_phylum, instant, Instant_Field_ID, lake, lake_code, M0D, management, number, oceanography, office, phylum, preliminary, tube, Tube_Number";
String license "https://www.bco-dmo.org/dataset/768180/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/768180";
String param_mapping "{'768180': {}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/768180/parameters";
String people_0_affiliation "University of California-Merced";
String people_0_affiliation_acronym "UC Merced";
String people_0_person_name "Michael N Dawson";
String people_0_person_nid "51577";
String people_0_role "Principal Investigator";
String people_0_role_type "originator";
String people_1_affiliation "Woods Hole Oceanographic Institution";
String people_1_affiliation_acronym "WHOI BCO-DMO";
String people_1_person_name "Nancy Copley";
String people_1_person_nid "50396";
String people_1_role "BCO-DMO Data Manager";
String people_1_role_type "related";
String project "PaPaPro";
String projects_0_acronym "PaPaPro";
String projects_0_description
"This project will survey the taxonomic, genetic, and functional diversity of the organisms found in marine lakes, and investigate the processes that cause gains and losses in this biodiversity. Marine lakes formed as melting ice sheets raised sea level after the last glacial maximum and flooded hundreds of inland valleys around the world. Inoculated with marine life from the surrounding sea and then isolated to varying degrees for the next 6,000 to 15,000 years, these marine lakes provide multiple, independent examples of how environments and interactions between species can drive extinction and speciation. Researchers will survey the microbes, algae, invertebrates, and fishes present in 40 marine lakes in Palau and Papua, and study how diversity has changed over time by retrieving the remains of organisms preserved in sediments on the lake bottoms. The project will test whether the number of species, the diversity of functional roles played by organisms, and the genetic diversity within species increase and decrease in parallel; whether certain species can greatly curtail diversity by changing the environment; whether the size of a lake determines its biodiversity; and whether the processes that control diversity in marine organisms are similar to those that operate on land.
Because biodiversity underlies the ecosystem services on which society depends, society has a great interest in understanding the processes that generate and retain biodiversity in nature. This project will also help conserve areas of economic importance. Marine lakes in the study region are important for tourism, and researchers will work closely with governmental and non-governmental conservation and education groups and with diving and tourism businesses to raise awareness of the value and threats to marine lakes in Indonesia and Palau.";
String projects_0_end_date "2017-12";
String projects_0_geolocation "Western Pacific; Palau; Indonesia (West Papua)";
String projects_0_name "Do Parallel Patterns Arise from Parallel Processes?";
String projects_0_project_nid "2238";
String projects_0_project_website "http://marinelakes.ucmerced.edu/";
String projects_0_start_date "2013-01";
String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
String publisher_type "institution";
String sourceUrl "(local files)";
String standard_name_vocabulary "CF Standard Name Table v55";
String summary "Marine lakes of Palau barcoded specimens from transect survey with both lab identification number (M0D#) and original tube number. The purpose of this dataset is (1) to link unique identification numbers used in different circumstances and files, specifically tube ID used in the field and the M0D# identifier for the lab\\u2019s permanent collection, and (2) to summarize the tissue samples collected during biodiversity surveys under this project.";
String title "[Palau lakes: tissue archive] - Marine lakes of Palau barcoded specimens from transect survey with both lab identification number (M0D#) and original tube number (Do Parallel Patterns Arise from Parallel Processes?)";
String version "1";
String xml_source "osprey2erddap.update_xml() v1.3";
}
}
Data Access Protocol (DAP) and its
selection constraints.
The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.
Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names,
followed by a collection of
constraints (e.g., variable<value),
each preceded by '&' (which is interpreted as "AND").
For details, see the tabledap Documentation.