ERDDAP > info > bcodmo_dataset_793581

Grid DAP Data	Sub- set	Table DAP Data	Make A Graph	W M S	Source Data Files	Acces- sible	Title	Sum- mary	FGDC, ISO, Metadata	Back- ground Info	RSS	E mail	Institution	Dataset ID
		data	graph		files	public	[Edmunds et al. MarBio 2019a: Data in support of energy budget calculations] - Light data from surveys in St. John, US Virgin Islands in 2017 used to calculate photosynthetic input to coral energy budget as in Edwards et al. (2019) (RAPID: Hurricane Irma: Effects of repeated severe storms on shallow Caribbean reefs and their changing ecological resilience)		I   M	background			BCO-DMO	bcodmo_dataset_793581

The Dataset's Variables and Attributes

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 datasets published in Edmunds et al. (2019). Methodology: This study was completed on the coral reefs of St. John, which have been the subjects of time-series analyses for 32 years. The measurements described herein originated from a schedule of instrument deployments initiated in 2014 to quantify variation in underwater physical environmental conditions, and ultimately, to facilitate testing for their role in driving changes in benthic community structure. As part of this schedule, rainfall was recorded throughout the year, and a light meter was placed in Great Lameshur Bay in August 2017, with the objective of leaving it immersed for 6\u201312 months. Three weeks later, the first of two Category 5 hurricanes impacted the island, with the second arriving 14 days later. The discovery in July 2018 that this meter had survived the storms, and had remained upright and functional, created the opportunity to describe underwater light during, and immediately after, two major storms. Rainfall was recorded on the north shore of St. John at Windswept Beach (18\u00b0 21\u00b4 20.95N, 64\u00b0 45\u00b4 57.53W), where a 20.3 cm, Standard Rain Gauge (NOAA, National Weather Service) was mounted on a roof, 1.5 m above the ground. This rain gauge was ~ 6.7 km from the underwater light sensor, and was emptied and read on a daily basis. 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). The meter was equipped with a mechanical wiper that cleaned the sensor before every measurement, and it was mounted with the sensor at 19.1-m depth on the eastern side of Great Lameshur Bay (18\u00b0 18\u00b4 37.04N, 64\u00b0 43\u00b4 23.17W. The instrument was operated in burst mode during which 10 measurements were recorded every 180 minutes, with 30 seconds separating measurements within a burst. This sampling regime ensured that the battery would support a deployment of one year. The Compact LW meter is designed for oceanographic applications to 200-m depth, is fitted with a photodiode sensor, and has an accuracy of \u00b1 4% (over 0\u20132,000 \u00b5mol photons m-2 s-1) and resolution of 0.1 \u00b5mol photons m-2 s-1. The sensors are calibrated by the manufacturer, with the calibration stable for at least 1 year. When the meter was deployed in August 2017, it had been used underwater for ~ 16 mo in previous deployments, and initial records of PPFD were similar to those previously recorded at the same depth and time of year in St. John, which suggested that the calibration had not appreciably drifted. PPFD also was measured on the surface, using two cosine-corrected sensors (S-LIA-M003, Onset Computer Corporation) mounted ~ 4 m above sea level on the roof of the lab, ~ 0.875 km from the underwater sensor. The surface sensors were attached to weather stations (Micro Station Data Logger H21-002, Onset Computer Corporation) that recorded light every 5 minutes. The two sensors were calibrated by the manufacturers, and were operated in a paired mode to detect spurious records and sensor drift, and to guard against equipment malfunction.
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
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: Energy Budget PI: Peter J. Edmunds Data Version 1: 2020-02-17
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/
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	2020-02-17T17:32:41Z
attribute	NC_GLOBAL	date_modified	String	2020-02-18T18:00:53Z
attribute	NC_GLOBAL	defaultDataQuery	String	&time<now
attribute	NC_GLOBAL	doi	String	10.1575/1912/bco-dmo.793581.1
attribute	NC_GLOBAL	infoUrl	String	https://www.bco-dmo.org/dataset/793581
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	793589
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/
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	793588
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	793590
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	bco, bco-dmo, biological, chemical, data, dataset, day, dmo, erddap, light, management, oceanography, office, preliminary, surface, Surface_Light, time, underwater, Underwater_Light_at_10_m, Underwater_Light_at_19_m
attribute	NC_GLOBAL	license	String	https://www.bco-dmo.org/dataset/793581/license
attribute	NC_GLOBAL	metadata_source	String	https://www.bco-dmo.org/api/dataset/793581
attribute	NC_GLOBAL	param_mapping	String	{'793581': {}}
attribute	NC_GLOBAL	parameter_source	String	https://www.bco-dmo.org/mapserver/dataset/793581/parameters
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. Coral 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
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 data from surveys in Great Lameshur Bay, St. John, US Virgin Islands in 2017 used to calculate photosynthetic input to coral energy budget as in Edwards et al. (2019). These data were used in Edmunds et al. (2019).
attribute	NC_GLOBAL	title	String	[Edmunds et al. MarBio 2019a: Data in support of energy budget calculations] - Light data from surveys in St. John, US Virgin Islands in 2017 used to calculate photosynthetic input to coral energy budget as in Edwards et al. (2019) (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	Day		String
attribute	Day	bcodmo_name	String	date
attribute	Day	description	String	Local date (UTC-4) in format ISO format yyyy-mm-dd
attribute	Day	long_name	String	Day
attribute	Day	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/
attribute	Day	source_name	String	Day
attribute	Day	time_precision	String	1970-01-01
attribute	Day	units	String	unitless
variable	Surface_Light		float
attribute	Surface_Light	_FillValue	float	NaN
attribute	Surface_Light	actual_range	float	33.7, 2516.2
attribute	Surface_Light	bcodmo_name	String	PAR
attribute	Surface_Light	description	String	Surface PAR
attribute	Surface_Light	long_name	String	Surface Light
attribute	Surface_Light	units	String	micromoles per square meter per second (µmol quanta/m2/s)
variable	Kd		float
attribute	Kd	_FillValue	float	NaN
attribute	Kd	actual_range	float	0.066, 0.426
attribute	Kd	bcodmo_name	String	unknown
attribute	Kd	description	String	Diffuse attenuation coefficient for downwelling irradiance (Kd). See methodology for calculation
attribute	Kd	long_name	String	KD
attribute	Kd	units	String	unitless
variable	Underwater_Light_at_19_m		float
attribute	Underwater_Light_at_19_m	_FillValue	float	NaN
attribute	Underwater_Light_at_19_m	actual_range	float	0.2, 511.7
attribute	Underwater_Light_at_19_m	bcodmo_name	String	PAR
attribute	Underwater_Light_at_19_m	description	String	Underwater light at 19.1m depth
attribute	Underwater_Light_at_19_m	long_name	String	Underwater Light At 19 M
attribute	Underwater_Light_at_19_m	units	String	micromoles per square meter per second (µmol quanta/m2/s)
variable	Underwater_Light_at_10_m		float
attribute	Underwater_Light_at_10_m	_FillValue	float	NaN
attribute	Underwater_Light_at_10_m	actual_range	float	2.3, 1034.2
attribute	Underwater_Light_at_10_m	bcodmo_name	String	PAR
attribute	Underwater_Light_at_10_m	description	String	Underwater light at 10m depth
attribute	Underwater_Light_at_10_m	long_name	String	Underwater Light At 10 M
attribute	Underwater_Light_at_10_m	units	String	micromoles per square meter per second (µmol quanta/m2/s)

The information in the table above is also available in other file formats (.csv, .htmlTable, .itx, .json, .jsonlCSV1, .jsonlCSV, .jsonlKVP, .mat, .nc, .nccsv, .tsv, .xhtml) via a RESTful web service.