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Row Type | Variable Name | Attribute Name | Data Type | Value |
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attribute | NC_GLOBAL | access_formats | String | .htmlTable,.csv,.json,.mat,.nc,.tsv |
attribute | NC_GLOBAL | acquisition_description | String | Light was measured as the radiant energy between 400 and 700 nm wavelength\n(i.e., PAR, \\u03bcmol quanta m-2 s-1) as Photosynthetic Photon Flux Density\n(PPFD). In situ light was measured using two logging meters fitted with a\ncosine-corrected PAR sensor and wiper (Compact LW, JFE Advantech Co., Ltd,\nJapan), that were deployed at ~ 19.1-m depth (height of the sensor) in Great\nLameshur Bay (18\\u00b0 18 \\u0301 37.04N, 63\\u00b0 43 \\u0301 23.17W).\n \nThese instruments recorded downwelling PAR, and were deployed six times from\n2014and 2017, from August to March and from March to August. The meters were\noperated in burst mode, during which they would wake up, clean the sensor with\na wiper, and record a burst of multiple records before returning to sleep. The\nCompact LW meter is designed for oceanographic applications to 200 m depths,\nis fitted with a photodiode sensor, and has a stated accuracy of \\u00b1 4%\n(over 0\\u20132000 \\u03bcmol photons m2 s-1) and resolution of 0.1 \\u03bcmol\nphotons m2 s-1. Both meters were purchased new for this study, and were\ndeployed individually and sequentially between field samplings with\ncomparisons between consecutive deployments used to screen for calibration\ndrift. One sensor was used for a combined duration of 16 months during, and\nthe other sensor was used for 4 months, returned to the manufacturer for\nservicing (May 2016), and then used again for 3 months. In between\ndeployments, sensors were inspected for abrasions that would affect\ncalibration, and were carefully cleaned with vinegar.\n \nDifferent configurations of the meter were employed to prolong battery life.\nIn the first and second deployments (starting 21 August 2014 and 19 March\n2015, respectively), a burst of 10 measurements was recorded at 0.033 Hz\n(i.e., every 30 s) every 1.5 h; the instrument failed during the third\ndeployment (starting August 2015); in the fourth and fifth deployments\n(starting 16 March 2016 and 29 July 2016, respectively) a burst of 10\nmeasurements was recorded at 0.033 Hz every 1.0 h; and in the sixth\ndeployment(starting 23 February 2017) a burst of 30 measurements was recorded\nat 0.100 Hz (i.e.,every 10 s) every 2.0 h. The timing of bursts was not\nstandardized to local time and, therefore, the number and timing of bursts\nbracketing noon (which were used to calculate transmission, described below)\ndiffered among deployments. The sampling frequency within each burst was\nsufficient to alleviate the bias resulting from wave-induced light flecking\n(Zheng et al. 2002). As a result of varying power demands of each sampling\nconfiguration, the meter did not always record for the full duration of each\ndeployment.\\u00a0\n \nSurface light was recorded with two cosine-corrected PAR sensor (S-LIA-M003,\nOnsetComputer Corporation) attached to loggers (Micro Station Data Logger\nH21-002, OnsetComputer Corporation) recording at 0.0033 Hz (i.e., every 5\nminutes). The sensors were calibrated by the manufacturers, and were mounted ~\n4-m above sea level adjacent to Great Lameshur Bay (18\\u00b0 19 \\u0301 6.61N,\n64\\u00b0 43 \\u0301 27.73W), and ~ 0.875 km from the sensor recording in situ\nlight. The paired surface sensors were used to ensure data integrity should\none sensor fail, and the paired deployments provided a means to detect\nerroneous records due to sensor drift or failure. The surface sensors were\ndownloaded, reprogrammed, and cleaned in July of each year, and have been\ndeployed for 11 y(from 2007). Here, surface light data for 2014-2017 are\npresented to provide temporal concordance with the submerged sensor.\n \nRainfall was measured using a 20.3 cm, Standard Rain Gauge (NOAA,\nNationalWeather Service) that was deployed on the north shore of St. John\n(18\\u00b0 21 \\u0301 20.95N, 64\\u00b045 \\u0301 57.53W). The gauge was used to\nmanually record daily rainfall that was averaged by month for each sampling\nyear. |
attribute | NC_GLOBAL | awards_0_award_nid | String | 562085 |
attribute | NC_GLOBAL | awards_0_award_number | String | OCE-1332915 |
attribute | NC_GLOBAL | awards_0_data_url | String | http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1332915 |
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 | David L. Garrison |
attribute | NC_GLOBAL | awards_0_program_manager_nid | String | 50534 |
attribute | NC_GLOBAL | awards_1_award_nid | String | 562593 |
attribute | NC_GLOBAL | awards_1_award_number | String | DEB-1350146 |
attribute | NC_GLOBAL | awards_1_data_url | String | http://www.nsf.gov/awardsearch/showAward?AWD_ID=1350146 |
attribute | NC_GLOBAL | awards_1_funder_name | String | NSF Division of Environmental Biology |
attribute | NC_GLOBAL | awards_1_funding_acronym | String | NSF DEB |
attribute | NC_GLOBAL | awards_1_funding_source_nid | String | 550432 |
attribute | NC_GLOBAL | awards_1_program_manager | String | Betsy Von Holle |
attribute | NC_GLOBAL | awards_1_program_manager_nid | String | 701685 |
attribute | NC_GLOBAL | cdm_data_type | String | Other |
attribute | NC_GLOBAL | comment | String | Rainfall and Light \n P. Edmunds, PI \n Data associated with Fig. 1 of: \n Edmunds, Coral Reefs (2018) Long-term variation in light intensity on a coral reef. \n Version 13 July 2018 |
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 | date_created | String | 2018-07-09T21:09:31Z |
attribute | NC_GLOBAL | date_modified | String | 2018-08-21T20:41:31Z |
attribute | NC_GLOBAL | defaultDataQuery | String | &time<now |
attribute | NC_GLOBAL | doi | String | 10.1575/1912/bco-dmo.744498 |
attribute | NC_GLOBAL | infoUrl | String | https://www.bco-dmo.org/dataset/739601 |
attribute | NC_GLOBAL | institution | String | BCO-DMO |
attribute | NC_GLOBAL | instruments_0_acronym | String | LI-COR Biospherical PAR |
attribute | NC_GLOBAL | instruments_0_dataset_instrument_description | String | Used to determine PAR |
attribute | NC_GLOBAL | instruments_0_dataset_instrument_nid | String | 742234 |
attribute | NC_GLOBAL | instruments_0_description | String | The LI-COR Biospherical PAR Sensor is used to measure Photosynthetically Available Radiation (PAR) in the water column. This instrument designation is used when specific make and model are not known. |
attribute | NC_GLOBAL | instruments_0_instrument_external_identifier | String | https://vocab.nerc.ac.uk/collection/L22/current/TOOL0074/ |
attribute | NC_GLOBAL | instruments_0_instrument_name | String | LI-COR Biospherical PAR Sensor |
attribute | NC_GLOBAL | instruments_0_instrument_nid | String | 480 |
attribute | NC_GLOBAL | instruments_0_supplied_name | String | PAR Sensor |
attribute | NC_GLOBAL | keywords | String | bco, bco-dmo, biological, chemical, data, dataset, dmo, erddap, light, management, mean, month, oceanography, office, precipitation, preliminary, rain, rainfall, surface, SurfaceLight_Mean, SurfaceLight_SE, year |
attribute | NC_GLOBAL | license | String | https://www.bco-dmo.org/dataset/739601/license |
attribute | NC_GLOBAL | metadata_source | String | https://www.bco-dmo.org/api/dataset/739601 |
attribute | NC_GLOBAL | param_mapping | String | {'739601': {}} |
attribute | NC_GLOBAL | parameter_source | String | https://www.bco-dmo.org/mapserver/dataset/739601/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 | Woods Hole Oceanographic Institution |
attribute | NC_GLOBAL | people_1_affiliation_acronym | String | WHOI BCO-DMO |
attribute | NC_GLOBAL | people_1_person_name | String | Hannah Ake |
attribute | NC_GLOBAL | people_1_person_nid | String | 650173 |
attribute | NC_GLOBAL | people_1_role | String | BCO-DMO Data Manager |
attribute | NC_GLOBAL | people_1_role_type | String | related |
attribute | NC_GLOBAL | project | String | VI Octocorals,RUI-LTREB |
attribute | NC_GLOBAL | projects_0_acronym | String | VI Octocorals |
attribute | NC_GLOBAL | projects_0_description | String | The recent past has not been good for coral reefs, and journals have been filled with examples of declining coral cover, crashing fish populations, rising cover of macroalgae, and a future potentially filled with slime. However, reefs are more than the corals and fishes for which they are known best, and their biodiversity is affected strongly by other groups of organisms. The non-coral fauna of reefs is being neglected in the rush to evaluate the loss of corals and fishes, and this project will add on to an on-going long term ecological study by studying soft corals. This project will be focused on the ecology of soft corals on reefs in St. John, USVI to understand the Past, Present and the Future community structure of soft corals in a changing world. For the Past, the principal investigators will complete a retrospective analysis of octocoral abundance in St. John between 1992 and the present, as well as Caribbean-wide since the 1960's. For the Present, they will: (i) evaluate spatio-temporal changes between soft corals and corals, (ii) test for the role of competition with macroalgae and between soft corals and corals as processes driving the rising abundance of soft corals, and (iii) explore the role of soft corals as \"animal forests\" in modifying physical conditions beneath their canopy, thereby modulating recruitment dynamics. For the Future the project will conduct demographic analyses on key soft corals to evaluate annual variation in population processes and project populations into a future impacted by global climate change.\nThis project was funded to provide and independent \"overlay\" to the ongoing LTREB award (DEB-1350146, co-funded by OCE, PI Edmunds) focused on the long-term dynamics of coral reefs in St. John.\nNote: This project is closely associated with the project \"RAPID: Resilience of Caribbean octocorals following Hurricanes Irma and Maria\". See: https://www.bco-dmo.org/project/749653.\nThe following publications and data resulted from this project:\n2017 Tsounis, G., and P. J. Edmunds. Three decades of coral reef community dynamics in St. John, USVI: a contrast of scleractinians and octocorals. Ecosphere 8(1):e01646. DOI: 10.1002/ecs2.1646Rainfall and temperature dataCoral and macroalgae abundance and distributionDescriptions of hurricanes affecting St. John\n2016 Gambrel, B. and Lasker, H.R. Marine Ecology Progress Series 546: 85–95, DOI: 10.3354/meps11670Colony to colony interactionsEunicea flexuosa interactionsGorgonia ventalina asymmetryNearest neighbor surveys\n2015 Lenz EA, Bramanti L, Lasker HR, Edmunds PJ. Long-term variation of octocoral populations in St. John, US Virgin Islands. Coral Reefs DOI 10.1007/s00338-015-1315-xoctocoral survey - densitiesoctocoral counts - photoquadrats vs. insitu surveyoctocoral literature reviewDownload complete data for this publication (Excel file)\n2015 Privitera-Johnson, K., et al., Density-associated recruitment in octocoral communities in St. John, US Virgin Islands, J.Exp. Mar. Biol. Ecol. DOI: 10.1016/j.jembe.2015.08.006octocoral density dependenceDownload complete data for this publication (Excel file)\nOther datasets related to this project:octocoral transects - adult colony height |
attribute | NC_GLOBAL | projects_0_end_date | String | 2016-08 |
attribute | NC_GLOBAL | projects_0_geolocation | String | St. John, US Virgin Islands: 18.3185, 64.7242 |
attribute | NC_GLOBAL | projects_0_name | String | Ecology and functional biology of octocoral communities |
attribute | NC_GLOBAL | projects_0_project_nid | String | 562086 |
attribute | NC_GLOBAL | projects_0_project_website | String | http://coralreefs.csun.edu/ |
attribute | NC_GLOBAL | projects_0_start_date | String | 2013-09 |
attribute | NC_GLOBAL | projects_1_acronym | String | RUI-LTREB |
attribute | NC_GLOBAL | projects_1_description | String | Describing how ecosystems like coral reefs are changing is at the forefront of efforts to evaluate the biological consequences of global climate change and ocean acidification. Coral reefs have become the poster child of these efforts. Amid concern that they could become ecologically extinct within a century, describing what has been lost, what is left, and what is at risk, is of paramount importance. This project exploits an unrivalled legacy of information beginning in 1987 to evaluate the form in which reefs will persist, and the extent to which they will be able to resist further onslaughts of environmental challenges. This long-term project continues a 27-year study of Caribbean coral reefs. The diverse data collected will allow the investigators to determine the roles of local and global disturbances in reef degradation. The data will also reveal the structure and function of reefs in a future with more human disturbances, when corals may no longer dominate tropical reefs.\nThe broad societal impacts of this project include advancing understanding of an ecosystem that has long been held emblematic of the beauty, diversity, and delicacy of the biological world. Proposed research will expose new generations of undergraduate and graduate students to natural history and the quantitative assessment of the ways in which our planet is changing. This training will lead to a more profound understanding of contemporary ecology at the same time that it promotes excellence in STEM careers and supports technology infrastructure in the United States. Partnerships will be established between universities and high schools to bring university faculty and students in contact with k-12 educators and their students, allow teachers to carry out research in inspiring coral reef locations, and motivate children to pursue STEM careers. Open access to decades of legacy data will stimulate further research and teaching. |
attribute | NC_GLOBAL | projects_1_end_date | String | 2019-04 |
attribute | NC_GLOBAL | projects_1_geolocation | String | USVI |
attribute | NC_GLOBAL | projects_1_name | String | RUI-LTREB Renewal: Three decades of coral reef community dynamics in St. John, USVI: 2014-2019 |
attribute | NC_GLOBAL | projects_1_project_nid | String | 734983 |
attribute | NC_GLOBAL | projects_1_project_website | String | http://coralreefs.csun.edu/ |
attribute | NC_GLOBAL | projects_1_start_date | String | 2014-05 |
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 | Data supporting publication through measurements of rainfall on St. John and surface light adjacent to Lameshur Bay. These data describe rainfall on the north shore of St. John as measured by R. Boulon using a manual rain gauge. |
attribute | NC_GLOBAL | title | String | [Rainfall and surface light intensity] - Measurements of rainfall and surface light intensity (PAR) in St. John, US Virgin Islands from 2014-2017. (Collaborative research: Ecology and functional biology of octocoral communities) |
attribute | NC_GLOBAL | version | String | 1 |
attribute | NC_GLOBAL | xml_source | String | osprey2erddap.update_xml() v1.3 |
variable | Year | short | ||
attribute | Year | _FillValue | short | 32767 |
attribute | Year | actual_range | short | 2014, 2017 |
attribute | Year | bcodmo_name | String | year |
attribute | Year | description | String | Year of sampling |
attribute | Year | long_name | String | Year |
attribute | Year | nerc_identifier | String | https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/ |
attribute | Year | units | String | unitless |
variable | Month | String | ||
attribute | Month | bcodmo_name | String | unknown |
attribute | Month | description | String | Month of sampling |
attribute | Month | long_name | String | Month |
attribute | Month | units | String | unitless |
variable | Rainfall | float | ||
attribute | Rainfall | _FillValue | float | NaN |
attribute | Rainfall | actual_range | float | 0.3556, 35.2552 |
attribute | Rainfall | bcodmo_name | String | precip_level |
attribute | Rainfall | description | String | Rainfall per month |
attribute | Rainfall | long_name | String | Rainfall |
attribute | Rainfall | units | String | centimeters per month |
variable | SurfaceLight_Mean | float | ||
attribute | SurfaceLight_Mean | _FillValue | float | NaN |
attribute | SurfaceLight_Mean | actual_range | float | 34.08, 56.26 |
attribute | SurfaceLight_Mean | bcodmo_name | String | PAR_photons |
attribute | SurfaceLight_Mean | description | String | Surface light mean |
attribute | SurfaceLight_Mean | long_name | String | Surface Light Mean |
attribute | SurfaceLight_Mean | units | String | umol photons per square meter per day |
variable | SurfaceLight_SE | float | ||
attribute | SurfaceLight_SE | _FillValue | float | NaN |
attribute | SurfaceLight_SE | actual_range | float | 0.59, 2.56 |
attribute | SurfaceLight_SE | bcodmo_name | String | PAR_photons |
attribute | SurfaceLight_SE | description | String | Surface light mean standard error |
attribute | SurfaceLight_SE | long_name | String | Surface Light SE |
attribute | SurfaceLight_SE | units | String | umol photons per square meter per day |