Accessing BCO-DMO data
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BCO-DMO ERDDAP
Accessing BCO-DMO data |
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| Dataset Title: | [Capture efficiency of scyphomedusae] - Raw capture efficiency data of scyphomedusae from video analysis collected in Woods Hole, MA beginning in 2015. (RUI: Collaborative Research: What's their impact?: Quantification of medusan feeding mechanics as a tool for predicting medusan predation) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_683750) |
| Information: | Summary
| License
| ISO 19115
| Metadata
| Background
| Data Access Form
| Files
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![[The graph you specified. Please be patient.]](https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_683750.png?individual,encounter_effeciency&.draw=markers&.marker=5%7C5&.color=0x000000&.colorBar=%7C%7C%7C%7C%7C&.bgColor=0xffccccff)
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Attributes {
s {
Cnidaria_species {
String bcodmo_name "species";
String description "Species of Cnidaria analyzed on video";
String long_name "Cnidaria Species";
String units "unitless";
}
food_type {
String bcodmo_name "unknown";
String description "Type of prey that was observed";
String long_name "Food Type";
String units "unitless";
}
individual {
Byte _FillValue 127;
String _Unsigned "false";
Byte actual_range 1, 10;
String bcodmo_name "individual";
String description "Individual ID number";
String long_name "Individual";
String units "unitless";
}
video_id {
String bcodmo_name "file_name";
String description "Video ID number";
String long_name "Video Id";
String units "unitless";
}
time2 {
String bcodmo_name "time_begin";
String description "Time interaction occurs in video; HH:MM:SS";
String long_name "Time";
String units "unitless";
}
evaded {
String bcodmo_name "count";
String description "Encounters that show the prey item evaded contact through the feeding current produced by the medusae; Each X represents a tally mark and should be counted as a single occurance of this behavior.";
String long_name "Evaded";
String units "count";
}
ingested {
String bcodmo_name "count";
String description "Encounters that resulted in being injested by the medusae (moved to the gastric pouches); Each X represents a tally mark and should be counted as a single occurance of this behavior.";
String long_name "Ingested";
String units "count";
}
tentacle_capture {
String bcodmo_name "count";
String description "Encounters that resulted in the capture of individuals on the tentacles; Each X represents a tally mark and should be counted as a single occurance of this behavior.";
String long_name "Tentacle Capture";
String units "count";
}
oralArm_capture {
String bcodmo_name "count";
String description "Encounters that resulted in the capture of individuals on the oral arms; Each X represents a tally mark and should be counted as a single occurance of this behavior.";
String long_name "Oral Arm Capture";
String units "count";
}
capture_evade {
String bcodmo_name "count";
String description "Encounters that resulted in an initial capture of the individual prey items escaping by breaking contact with the medusae; Each X represents a tally mark and should be counted as a single occurance of this behavior.";
String long_name "Capture Evade";
String units "count";
}
encounter_effeciency {
Float64 _FillValue NaN;
Float64 actual_range 17.47572816, 76.0;
String bcodmo_name "unknown";
String description "All individuals that have some sort of interaction with the medusae weither through direct contact or through the feeding current.";
String long_name "Encounter Effeciency";
String units "unitless";
}
capture_effeciency {
Float64 _FillValue NaN;
Float64 actual_range 16.50485437, 74.0;
String bcodmo_name "unknown";
String description "Prey individuals making contact with the medusae within the tentacles and the oral arms and being captured by the medusae.";
String long_name "Capture Effeciency";
String units "unitless";
}
notes {
String bcodmo_name "comment";
String description "Observation notes";
String long_name "Notes";
String units "unitless";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
String acquisition_description
"Medusae were video recorded with different prey assemblages. Video was
analyzed by identifying encounters (defined as prey entering encounter zone
occupied by tentacles) and recording the outcome of each encounter.";
String awards_0_award_nid "654089";
String awards_0_award_number "OCE-1536688";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1536688";
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 "Michael E. Sieracki";
String awards_0_program_manager_nid "50446";
String cdm_data_type "Other";
String comment
"Medusae Predator-Prey Interactions
S. Colin
Version 1 March 2017";
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 "2017-03-03T23:14:17Z";
String date_modified "2019-04-04T15:25:56Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.683750.1";
String history
"2024-11-08T05:43:55Z (local files)
2024-11-08T05:43:55Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_683750.das";
String infoUrl "https://www.bco-dmo.org/dataset/683750";
String institution "BCO-DMO";
String instruments_0_acronym "camera";
String instruments_0_dataset_instrument_description "Medusae were recorded on video and this was analyzed to produce the data";
String instruments_0_dataset_instrument_nid "683757";
String instruments_0_description "All types of photographic equipment including stills, video, film and digital systems.";
String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/311/";
String instruments_0_instrument_name "Camera";
String instruments_0_instrument_nid "520";
String instruments_0_supplied_name "Camera";
String keywords "arm, bco, bco-dmo, biological, capture, capture_effeciency, capture_evade, chemical, cnidaria, Cnidaria_species, data, dataset, dmo, effeciency, encounter, encounter_effeciency, erddap, evade, evaded, food, food_type, individual, ingested, management, notes, oceanography, office, oral, oralArm_capture, preliminary, species, tentacle, tentacle_capture, time, time2, type, video, video_id";
String license "https://www.bco-dmo.org/dataset/683750/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/683750";
String param_mapping "{'683750': {}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/683750/parameters";
String people_0_affiliation "Roger Williams University";
String people_0_affiliation_acronym "RWU";
String people_0_person_name "Dr Sean Colin";
String people_0_person_nid "51362";
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 "Hannah Ake";
String people_1_person_nid "650173";
String people_1_role "BCO-DMO Data Manager";
String people_1_role_type "related";
String project "Medusan Feeding Mechanics";
String projects_0_acronym "Medusan Feeding Mechanics";
String projects_0_description
"In many areas around the world jellyfish population abundances are increasing and, at times, result in destructive blooms. Their rapid growth and high feeding rates make them important predators in marine ecosystems and their effects on ecosystems and human activities have increasingly raised concerns. Unfortunately, scientists do not currently understand the factors that determine which types of prey jellyfish eat and how much prey they eat. This presents a knowledge gap of increasing importance as jellyfish undergo inexplicable population fluctuations and invade new environments. In this project the investigators will develop a robust understanding of the factors that determine who and how much jellyfish consume based on their morphology, behavior and size. This fundamental understanding of their feeding process will enable researchers to use simple jellyfish characteristics to predict the ecological impact of different types of jellyfish. This project will include the studying of a greatly understudied group, rhizostome jellyfish, which represents many of the recorded bloom events and geographic expansions. Further, these techniques are sufficiently robust to have broader use in the study of physical-biological interactions for other jellyfish species and other pelagic organisms. The principal investigators participating in this collaboration are from primarily undergraduate institutions. Student participation in the project will involve several undergraduates during each year of the award. Through summer research at the Marine Biology Laboratory, undergraduate students will become exposed to a wide range of research and become immersed in a post-graduate environment that can strongly influence their perception of the scientific profession. The trophic impacts of scyphomedusae are subjects of broad international interest and results of our research will be exchanged with a wide range of colleagues, contributing to international scientific dialogue. In addition, we will use our contacts with media (e.g. PBS Shape of Life series, Fantastic Jellies exhibit at the New England Aquarium) involved in scientific education of the general public to communicate our new findings.
The goal of this project is to quantify the variables that control the post-encounter capture process in order to be able to predict the prey selection patterns and clearance rate potential of different rowing medusae based upon their morphological characteristics and size. To achieve this goal, the PIs will use laboratory and in situ videography and optics techniques to quantify the outcome of individual interactions with prey in the lab and in the field. Step-by-step quantification of the post-encounter capture process will enable them to quantify capture efficiencies of different prey types and determine which stages of the process were most influential in determining the outcome of the encounter. The investigators will use these quantitative observations to relate medusan morphology and nematocyst properties to capture efficiencies. This will allow them to predict prey selection patterns. These predictions will be combined with flow-based encounter models to predict clearance rate potential and prey selection of different medusan species under different prey conditions. Finally, the investigators will validate our predictions using laboratory bottle incubation studies to quantify prey selection and clearance rates of medusae fed different prey assemblages. When achieved, this study will provide marine ecologists with the critical \"missing links\" to be able to model and predict the ecological impact of medusae populations in a variety of environments.";
String projects_0_end_date "2018-07";
String projects_0_geolocation "Woods Hole, MA";
String projects_0_name "RUI: Collaborative Research: What's their impact?: Quantification of medusan feeding mechanics as a tool for predicting medusan predation";
String projects_0_project_nid "654090";
String projects_0_start_date "2015-08";
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 "Raw capture efficiency data of scyphomedusae from video analysis collected in Woods Hole, MA beginning in 2015.";
String title "[Capture efficiency of scyphomedusae] - Raw capture efficiency data of scyphomedusae from video analysis collected in Woods Hole, MA beginning in 2015. (RUI: Collaborative Research: What's their impact?: Quantification of medusan feeding mechanics as a tool for predicting medusan predation)";
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.