BCO-DMO ERDDAP
Accessing BCO-DMO data 		log in    
Brought to you by BCO-DMO    
 
 
Row Type Variable Name Attribute Name Data Type Value
attribute NC_GLOBAL access_formats String .htmlTable,.csv,.json,.mat,.nc,.tsv
attribute NC_GLOBAL acquisition_description String The following methodology applies to this dataset in addition to other\ndatasets published in Edmunds et al. (2019).\n \nMethodology:  \n This study was completed on the coral reefs of St. John, which have been the\nsubjects of time-series analyses for 32 years. The measurements described\nherein originated from a schedule of instrument deployments initiated in 2014\nto quantify variation in underwater physical environmental conditions, and\nultimately, to facilitate testing for their role in driving changes in benthic\ncommunity structure. As part of this schedule, rainfall was recorded\nthroughout the year, and a light meter was placed in Great Lameshur Bay in\nAugust 2017, with the objective of leaving it immersed for 6\\u201312 months.\nThree weeks later, the first of two Category 5 hurricanes impacted the island,\nwith the second arriving 14 days later. The discovery in July 2018 that this\nmeter had survived the storms, and had remained upright and functional,\ncreated the opportunity to describe underwater light during, and immediately\nafter, two major storms.\n \nRainfall was recorded on the north shore of St. John at Windswept Beach\n(18\\u00b0 21\\u00b4 20.95N, 64\\u00b0 45\\u00b4 57.53W), where a 20.3 cm,\nStandard Rain Gauge (NOAA, National Weather Service) was mounted on a roof,\n1.5 m above the ground. This rain gauge was ~ 6.7 km from the underwater light\nsensor, and was emptied and read on a daily basis.\n \nUnderwater light was recorded with a light meter (Compact LW, JFE Advantech\nCo., Ltd, Japan) fitted with a cosine-corrected sensor recording\nphotosynthetically active radiation (PAR, 400-700 nm wavelength) as\nphotosynthetic photon flux density (PPFD). The meter was equipped with a\nmechanical wiper that cleaned the sensor before every measurement, and it was\nmounted with the sensor at 19.1-m depth on the eastern side of Great Lameshur\nBay (18\\u00b0 18\\u00b4 37.04N, 64\\u00b0 43\\u00b4 23.17W. The instrument was\noperated in burst mode during which 10 measurements were recorded every 180\nminutes, with 30 seconds separating measurements within a burst. This sampling\nregime ensured that the battery would support a deployment of one year. The\nCompact LW meter is designed for oceanographic applications to 200-m depth, is\nfitted with a photodiode sensor, and has an accuracy of \\u00b1 4% (over\n0\\u20132,000 \\u00b5mol photons m-2 s-1) and resolution of 0.1 \\u00b5mol\nphotons m-2 s-1. The sensors are calibrated by the manufacturer, with the\ncalibration stable for at least 1 year. When the meter was deployed in August\n2017, it had been used underwater for ~ 16 mo in previous deployments, and\ninitial records of PPFD were similar to those previously recorded at the same\ndepth and time of year in St. John, which suggested that the calibration had\nnot appreciably drifted.\n \nPPFD also was measured on the surface, using two cosine-corrected sensors\n(S-LIA-M003, Onset Computer Corporation) mounted ~ 4 m above sea level on the\nroof of the lab, ~ 0.875 km from the underwater sensor. The surface sensors\nwere attached to weather stations (Micro Station Data Logger H21-002, Onset\nComputer Corporation) that recorded light every 5 minutes. The two sensors\nwere calibrated by the manufacturers, and were operated in a paired mode to\ndetect spurious records and sensor drift, and to guard against equipment\nmalfunction.
attribute NC_GLOBAL awards_0_award_nid String 722162
attribute NC_GLOBAL awards_0_award_number String OCE-1801335
attribute NC_GLOBAL awards_0_data_url String http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1801335 (external link)
attribute NC_GLOBAL awards_0_funder_name String NSF Division of Ocean Sciences
attribute NC_GLOBAL awards_0_funding_acronym String NSF OCE
attribute NC_GLOBAL awards_0_funding_source_nid String 355
attribute NC_GLOBAL awards_0_program_manager String Daniel Thornhill
attribute NC_GLOBAL awards_0_program_manager_nid String 722161
attribute NC_GLOBAL cdm_data_type String Other
attribute NC_GLOBAL comment String Edmunds et al. MarBio 2019a: Light and rainfall data \n  PI: Peter J. Edmunds \n  Data Version 1: 2020-02-14
attribute NC_GLOBAL Conventions String COARDS, CF-1.6, ACDD-1.3
attribute NC_GLOBAL creator_email String info at bco-dmo.org
attribute NC_GLOBAL creator_name String BCO-DMO
attribute NC_GLOBAL creator_type String institution
attribute NC_GLOBAL creator_url String https://www.bco-dmo.org/ (external link)
attribute NC_GLOBAL data_source String extract_data_as_tsv version 2.3  19 Dec 2019
attribute NC_GLOBAL dataset_current_state String Final and no updates
attribute NC_GLOBAL date_created String 2020-02-13T21:26:07Z
attribute NC_GLOBAL date_modified String 2020-05-28T15:17:31Z
attribute NC_GLOBAL defaultDataQuery String &time<now
attribute NC_GLOBAL doi String 10.1575/1912/bco-dmo.793461.1
attribute NC_GLOBAL infoUrl String https://www.bco-dmo.org/dataset/793461 (external link)
attribute NC_GLOBAL institution String BCO-DMO
attribute NC_GLOBAL instruments_0_acronym String AWS
attribute NC_GLOBAL instruments_0_dataset_instrument_description String A Standard Rain Gauge (NOAA, National Weather Service) was mounted on a roof 1.5 m above the ground.
attribute NC_GLOBAL instruments_0_dataset_instrument_nid String 793559
attribute NC_GLOBAL instruments_0_description String Land-based AWS systems are designed to record meteorological information.
attribute NC_GLOBAL instruments_0_instrument_external_identifier String https://vocab.nerc.ac.uk/collection/L05/current/102/ (external link)
attribute NC_GLOBAL instruments_0_instrument_name String Automated Weather Station
attribute NC_GLOBAL instruments_0_instrument_nid String 407
attribute NC_GLOBAL instruments_0_supplied_name String Standard Rain Gauge
attribute NC_GLOBAL instruments_1_acronym String Light Meter
attribute NC_GLOBAL instruments_1_dataset_instrument_description String Underwater light was recorded with a light meter (Compact LW, JFE Advantech Co., Ltd, Japan) fitted with a cosine-corrected sensor recording photosynthetically active radiation (PAR, 400-700 nm wavelength) as photosynthetic photon flux density (PPFD).
attribute NC_GLOBAL instruments_1_dataset_instrument_nid String 793558
attribute NC_GLOBAL instruments_1_description String Light meters are instruments that measure light intensity. Common units of measure for light intensity are umol/m2/s or uE/m2/s (micromoles per meter squared per second or microEinsteins per meter squared per second). (example: LI-COR 250A)
attribute NC_GLOBAL instruments_1_instrument_name String Light Meter
attribute NC_GLOBAL instruments_1_instrument_nid String 703
attribute NC_GLOBAL instruments_1_supplied_name String Compact LW
attribute NC_GLOBAL instruments_2_acronym String Light Meter
attribute NC_GLOBAL instruments_2_dataset_instrument_description String PPFD was measured on the surface, using two cosine-corrected sensors (S-LIA-M003, Onset Computer Corporation)
attribute NC_GLOBAL instruments_2_dataset_instrument_nid String 793560
attribute NC_GLOBAL instruments_2_description String Light meters are instruments that measure light intensity. Common units of measure for light intensity are umol/m2/s or uE/m2/s (micromoles per meter squared per second or microEinsteins per meter squared per second). (example: LI-COR 250A)
attribute NC_GLOBAL instruments_2_instrument_name String Light Meter
attribute NC_GLOBAL instruments_2_instrument_nid String 703
attribute NC_GLOBAL instruments_2_supplied_name String S-LIA-M003, Onset Computer Corporation
attribute NC_GLOBAL keywords String 1300hrs, bco, bco-dmo, biological, chemical, daily, data, dataset, date, day, dmo, erddap, integrated, intensity, management, max, oceanography, office, precipitation, preliminary, rain, rainfall, surface, Surface_Daily_Integrated, time, underwater, Underwater_1300hrs_Max_Intensity, Underwater_24H_integrated
attribute NC_GLOBAL license String https://www.bco-dmo.org/dataset/793461/license (external link)
attribute NC_GLOBAL metadata_source String https://www.bco-dmo.org/api/dataset/793461 (external link)
attribute NC_GLOBAL param_mapping String {'793461': {}}
attribute NC_GLOBAL parameter_source String https://www.bco-dmo.org/mapserver/dataset/793461/parameters (external link)
attribute NC_GLOBAL people_0_affiliation String California State University Northridge
attribute NC_GLOBAL people_0_affiliation_acronym String CSU-Northridge
attribute NC_GLOBAL people_0_person_name String Peter J. Edmunds
attribute NC_GLOBAL people_0_person_nid String 51536
attribute NC_GLOBAL people_0_role String Principal Investigator
attribute NC_GLOBAL people_0_role_type String originator
attribute NC_GLOBAL people_1_affiliation String California State University Northridge
attribute NC_GLOBAL people_1_affiliation_acronym String CSU-Northridge
attribute NC_GLOBAL people_1_person_name String Dr Georgios Tsounis
attribute NC_GLOBAL people_1_person_nid String 565353
attribute NC_GLOBAL people_1_role String Co-Principal Investigator
attribute NC_GLOBAL people_1_role_type String originator
attribute NC_GLOBAL people_2_affiliation String Laboratoire d'Écogéochimie des Environnements Benthiques
attribute NC_GLOBAL people_2_affiliation_acronym String LECOB
attribute NC_GLOBAL people_2_person_name String Dr Lorenzo Bramanti
attribute NC_GLOBAL people_2_person_nid String 562094
attribute NC_GLOBAL people_2_role String Contact
attribute NC_GLOBAL people_2_role_type String related
attribute NC_GLOBAL people_3_affiliation String Woods Hole Oceanographic Institution
attribute NC_GLOBAL people_3_affiliation_acronym String WHOI BCO-DMO
attribute NC_GLOBAL people_3_person_name String Amber D. York
attribute NC_GLOBAL people_3_person_nid String 643627
attribute NC_GLOBAL people_3_role String BCO-DMO Data Manager
attribute NC_GLOBAL people_3_role_type String related
attribute NC_GLOBAL project String Hurricane Irma and St. John Reefs
attribute NC_GLOBAL projects_0_acronym String Hurricane Irma and St. John Reefs
attribute NC_GLOBAL projects_0_description String Coral reefs have long been recognized for their diversity, and unique functional roles, but these features have been undermined by decades of disturbances that cast doubt on their ability to survive. Against this backdrop, 2017 brought two hurricanes of unprecedented magnitude to the Caribbean, both of which damaged coral reefs that already were degraded compared to those of a few decades ago. While the impacts of these storms on some of the few coral reefs protected within the US National Park and National Monument systems is particularly unfortunate, it also creates unique opportunities to understand the impacts on coral reefs that have been studied in detail for decades. This project builds on these opportunities by leveraging 31 years of coral reef monitoring research, much of which has been supported by NSF, to describe the impacts of Hurricanes Irma and Maria on coral reefs in St. John, US Virgin Islands. That the analyses will reveal severe destruction is a forgone conclusion, but what remains unknown is how present-day reefs will respond to severe versions of a well-known disturbance (hurricanes), and how these effects will impact their long-term survival. Post-storm surveys and new analyses will be used to determine whether ongoing declines in coral abundance have influenced the way coral reefs respond to storms, notably to enhance post-storm mortality, and reduce the capacity to recover from such event. To achieve these outcomes, a team of researchers from California State University, Northridge, will use a cruise on the R/V Walton Smith to survey the reefs of St. John using photography and in-water counts to generate data that will be analyzed throughout 2018. The benefits of this research will extend beyond scientific discoveries to include leveraged support for other scientists participating in the cruise, evaluation of the status of natural resources in the VI National Park, the delivery of relief supplies from Miami to St. John, and the creation of unique research and training opportunities for graduate students who will participate in all phases of the project.\nCoral reefs have undergone dramatic changes in community structure since they were first described in the 1950's, and the current onslaught of threats from rising temperature, declining seawater pH, storms, and numerous other events has cast doubt on their persistence in the Athropocene. With such profound changes underway, time-series analyses of community structure are on the cutting edge of contemporary studies of coral reefs. In the Caribbean, the impact of two category 5 hurricanes underscores why time-series are important, as they are the only means to describe the impact of such events, and critically, create the context for testing hypotheses regarding impacts and consequences of disturbances. This project addresses the impacts of Hurricanes Irma and Maria on the coral reefs of St. John, US Virgin Islands, which have been studied since the 1950's, and for the last 31 years largely with NSF LTREB support. This support provides descriptions of the population dynamics of the important coral, Orbicella annularis, and the coral community dynamics in adjacent habitats. Any study of the effects of these storms will demonstrate that large waves kill corals, but here intellectual merit is acquired through testing of general hypotheses: (1) storm impacts on O. annularis will be colony-density dependent, (2) delayed coral mortality will be accentuated compared to previous storms, (3) the resilience of coral communities to physical disturbances has declined since 1989, and (4) evolutionary rescue will mediate reef recovery for select corals through large initial population sizes, density-dependent population growth, and recruitment. These hypotheses will be tested using a 14 day cruise on the R/V Walton Smith to collect critical time-sensitive data, followed by a year of analysis of new and legacy photographic data.
attribute NC_GLOBAL projects_0_end_date String 2018-10
attribute NC_GLOBAL projects_0_geolocation String St. John, US Virgin Islands
attribute NC_GLOBAL projects_0_name String RAPID: Hurricane Irma: Effects of repeated severe storms on shallow Caribbean reefs and their changing ecological resilience
attribute NC_GLOBAL projects_0_project_nid String 722163
attribute NC_GLOBAL projects_0_project_website String http://coralreefs.csun.edu (external link)
attribute NC_GLOBAL projects_0_start_date String 2017-11
attribute NC_GLOBAL publisher_name String Biological and Chemical Oceanographic Data Management Office (BCO-DMO)
attribute NC_GLOBAL publisher_type String institution
attribute NC_GLOBAL sourceUrl String (local files)
attribute NC_GLOBAL standard_name_vocabulary String CF Standard Name Table v55
attribute NC_GLOBAL summary String Light and rainfall data from surveys conducted at Windswept Beach and Great Lameshur Bay, St. John, US Virgin Islands in 2016 and 2017. These data were used in Edmunds et al. (2019) in Figure 1.
attribute NC_GLOBAL title String [Edmunds et al. MarBio 2019a: Light and rainfall data] - Light and rainfall data from surveys conducted in St. John, US Virgin Islands in 2016 and 2017 (RAPID: Hurricane Irma: Effects of repeated severe storms on shallow Caribbean reefs and their changing ecological resilience)
attribute NC_GLOBAL version String 1
attribute NC_GLOBAL xml_source String osprey2erddap.update_xml() v1.5
variable Date String
attribute Date bcodmo_name String date_local
attribute Date description String Local date (AST,UTC-4) in ISO format yyyy-mm-dd. Dates in 2016 and 2017.
attribute Date long_name String Date
attribute Date source_name String Date
attribute Date time_precision String 1970-01-01
attribute Date units String unitless
variable Rainfall float
attribute Rainfall _FillValue float NaN
attribute Rainfall actual_range float 0.0, 10.82
attribute Rainfall bcodmo_name String precip_level
attribute Rainfall description String Daily rainfall recorded in each year. Displayed in Edmunds et al. (2019a) Fig. 1 Panel A
attribute Rainfall long_name String Rainfall
attribute Rainfall units String centimeters (cm)
variable Surface_Daily_Integrated float
attribute Surface_Daily_Integrated _FillValue float NaN
attribute Surface_Daily_Integrated actual_range float 1.7, 60.5
attribute Surface_Daily_Integrated bcodmo_name String PAR
attribute Surface_Daily_Integrated description String Surface PAR integrated over each day. Displayed in Edmunds et al. (2019a) Fig. 1 Panel B
attribute Surface_Daily_Integrated long_name String Surface Daily Integrated
attribute Surface_Daily_Integrated units String moles per square meter per second (mol quanta/m2/s)
variable Underwater_1300hrs_Max_Intensity short
attribute Underwater_1300hrs_Max_Intensity _FillValue short 32767
attribute Underwater_1300hrs_Max_Intensity actual_range short 0, 512
attribute Underwater_1300hrs_Max_Intensity bcodmo_name String PAR
attribute Underwater_1300hrs_Max_Intensity description String Underwater maximum PAR recorded on each day at 19.1 m depth recorded at 13:00 daily. Displayed in Edmunds et al. (2019a) Fig. 1 Panel C
attribute Underwater_1300hrs_Max_Intensity long_name String Underwater 1300hrs Max Intensity
attribute Underwater_1300hrs_Max_Intensity units String micromoles per square meter per second (µmol quanta/m2/s)
variable Underwater_24H_integrated float
attribute Underwater_24H_integrated _FillValue float NaN
attribute Underwater_24H_integrated actual_range float 0.0, 10.9
attribute Underwater_24H_integrated bcodmo_name String PAR
attribute Underwater_24H_integrated description String Daily PAR integrated at depth
attribute Underwater_24H_integrated long_name String Underwater 24 H Integrated
attribute Underwater_24H_integrated units String moles per square meter per second (mol quanta/m2/s)

 
ERDDAP, Version 2.22
Disclaimers | Privacy Policy | Contact