{"@context":{"content":"http:\/\/purl.org\/rss\/1.0\/modules\/content\/","dc":"http:\/\/purl.org\/dc\/terms\/","foaf":"http:\/\/xmlns.com\/foaf\/0.1\/","og":"http:\/\/ogp.me\/ns#","rdfs":"http:\/\/www.w3.org\/2000\/01\/rdf-schema#","sioc":"http:\/\/rdfs.org\/sioc\/ns#","sioct":"http:\/\/rdfs.org\/sioc\/types#","skos":"http:\/\/www.w3.org\/2004\/02\/skos\/core#","xsd":"http:\/\/www.w3.org\/2001\/XMLSchema#","owl":"http:\/\/www.w3.org\/2002\/07\/owl#","rdf":"http:\/\/www.w3.org\/1999\/02\/22-rdf-syntax-ns#","rss":"http:\/\/purl.org\/rss\/1.0\/","site":"https:\/\/www.bco-dmo.org\/ns#","odo":"http:\/\/ocean-data.org\/schema\/","emo":"http:\/\/ocean-data.org\/schema\/entity-matching#","bibo":"http:\/\/purl.org\/ontology\/bibo\/","crypto":"http:\/\/id.loc.gov\/vocabulary\/preservation\/cryptographicHashFunctions\/","bcodmo":"http:\/\/lod.bco-dmo.org\/id\/","tw":"http:\/\/tw.rpi.edu\/schema\/","dcat":"http:\/\/www.w3.org\/ns\/dcat#","time":"http:\/\/www.w3.org\/2006\/time#","geo":"http:\/\/www.w3.org\/2003\/01\/geo\/wgs84_pos#","geosparql":"http:\/\/www.opengis.net\/ont\/geosparql#","sf":"http:\/\/www.opengis.net\/ont\/sf#","void":"http:\/\/rdfs.org\/ns\/void#","sd":"http:\/\/www.w3.org\/ns\/sparql-service-description#","dctype":"http:\/\/purl.org\/dc\/dcmitype\/","prov":"http:\/\/www.w3.org\/ns\/prov#","schema":"http:\/\/schema.org\/","geolink":"http:\/\/schema.geolink.org\/1.0\/base\/main#","spdx":"http:\/\/spdx.org\/rdf\/terms#","bcodmo_vocab":"http:\/\/schema.bco-dmo.org\/"},"@id":"http:\/\/lod.bco-dmo.org\/id\/dataset\/793581#graph","@graph":[{"http:\/\/lod.bco-dmo.org\/id\/dataset\/793581":{"@id":"http:\/\/lod.bco-dmo.org\/id\/dataset\/793581","@type":["http:\/\/ocean-data.org\/schema\/DeploymentDatasetCollection","http:\/\/www.w3.org\/ns\/dcat#Dataset","http:\/\/ocean-data.org\/schema\/Dataset"],"http:\/\/ocean-data.org\/schema\/hasAcquisitionDescription":[{"@value":"
The following methodology applies to this dataset in addition to other datasets published in Edmunds et al. (2019).<\/p>\n
Methodology:
\nThis 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.<\/p>\n
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. <\/p>\n
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.<\/p>\n
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.<\/p><\/div>","@type":"rdf:HTML"}],"http:\/\/purl.org\/dc\/terms\/description":[{"@value":"
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).<\/p>\n
Related Datasets: All were used in Edmunds et al. (2019) Data were truncated to extend from 17 August to 30 November, which covered the impact of the two storms and represented the greatest period over which the in situ records of light were unaffected by fouling of the sensor. To provide context to the results from 2017, and evaluate the relative impact of the storms on underwater PPFD, comparisons were made to light recorded in 2016 over the same period of the year. Records of surface PPFD were integrated over each 5 minute measurement interval, and summed by day to calculate daily integrated PPFD (mol photons m-2 d-1). Underwater PPFD was averaged by burst, which occurred every 3 hours, and the values at ~13:00 hrs provided the maximum daily irradiance on most days. Average burst values of PPFD were integrated over each 180 minute burst interval within each day to estimate daily in situ, integrated PPFD (mol photons m-2 d-1). To compare these values with records obtained in 2016 at the same location, but at a higher frequency (with burst sampling every 60 minutes, the earlier records were sub-sampled to create a burst interval of 180 minutes, and thereafter, were processed the same way as the results from 2017. Daily underwater integrated PPFD values in 2017 were cumulatively summed by day after Hurricane Irma (6 September), and expressed as a percentage of PPFD recorded over the same periods in 2016 to calculate the cumulative depression of in situ light in 2017. <\/p>\n Estimates of the transmission of surface PAR to 19.1-m depth were constrained to measurements around noon, when the high angle of the sun ensured that most of the surface light passed through the air-water interface. When sun altitudes are > 46\u00b0, and wind speeds are < 5 m s-1, virtually all (~ 96%) surface light is transmitted across the air-water interface. The transmission of surface light to 19.1-m depth was calculated by day using the mean transmission recorded at 10:00 hrs and 13:00 hrs. PPFD measured at 19.1-m depth and on the surface at 13:00 hrs were also used to calculate the diffuse attenuation coefficient for PAR (Kd-PAR) using the equation representing the Beer-Lambert Law:<\/p>\n E_d (Z)= E_d (O^- ) e^(-K_d \u00d7 Z)<\/p>\n where Ed(Z) is the downwelling PPFD at Z m depth, Ed(O-) is downwelling PPFD just below the surface of the seawater, and Kd is the diffuse attenuation coefficient for downwelling irradiance; Ed(O-) was approximated from concurrent records of surface PPFD without correction for transmission across the air-water interface. This method of calculating Kd is prone to greater variance than the regression approach using downwelling PPFD quickly measured at multiple depths, but it allows a time-series of Kd to be obtained using a single instrument.<\/p>\n BCO-DMO Data Manager Processing Notes:
\n\u200bEdmunds et al. MarBio 2019a: Light and rainfall data https:\/\/www.bco-dmo.org\/dataset\/793461<\/a>
\nEdmunds et al. MarBio 2019a: Transmission data https:\/\/www.bco-dmo.org\/dataset\/793561<\/a>
\nEdmunds et al. MarBio 2019a: Kd data https:\/\/www.bco-dmo.org\/dataset\/793571<\/a><\/p><\/div>","@type":"rdf:HTML"}],"http:\/\/www.w3.org\/2000\/01\/rdf-schema#label":[{"@value":"Edmunds et al. MarBio 2019a: Data in support of energy budget calculations","@type":"xsd:string"}],"http:\/\/ocean-data.org\/schema\/hasProcessingDescription":[{"@value":"
\n* Original data submitted as the second of two data tables in Excel sheet "Energy Budget" extracted to csv. See Data Files for the originally submitted Excel file.
\n* added a conventional header with dataset name, PI name, version date
\n* modified parameter names to conform with BCO-DMO naming conventions (spaces, +, and - changed to underscores). Units in parentheses removed and added to Parameter Description metadata section.
\n* Date format changed to ISO 8601 format YYYY-mm-dd.<\/p><\/div>","@type":"rdf:HTML"}],"http:\/\/purl.org\/dc\/terms\/identifier":[{"@value":"793581","@type":"xsd:int"}],"http:\/\/purl.org\/dc\/terms\/title":[{"@value":"Edmunds et al. 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