Timeline / Data.gov — Climate Datasets
changed Source changed
A new raw object was archived. Both versions are preserved. 2866 line(s) added, 2081 line(s) removed.
Evidence
| Source | Data.gov — Climate Datasets |
|---|---|
| Agency | Data.gov |
| URL | https://api.gsa.gov/technology/datagov/v4/search?q=climate&sort=last_harvested_date&per_page=100&api_key=${DATAGOV_API_KEY} |
| Observed by | Civic Memory, directly, on 2026-10-03T00:19:08+00:00 |
| Content type | application/json |
| Current object |
d23ac58ff7e04700af1581c1bd631aa18229bf32e6cbcf9302e6cde5ba915a1e
download raw
metadata
|
| Previous object |
e358c454e13f1666cb05f5d0f0de79b3613dd1fcaab0b29b81f6b955fdfb88b0
download raw
metadata
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What changed derived
This diff is not evidence. It was produced by
civic-memory.diff_engine 1.1.0 at
2026-10-03T00:19:08+00:00 by normalizing the two archived objects above. The
objects are authoritative; this reading of them can be regenerated or deleted
without loss. 2866 line(s) added, 2081 line(s) removed.
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"https://data.nist.gov/od/ds/ark:/88434/mds2-3055/mCP%20SIMCA%20Model/NIST_mCP_SIMCAModel.mat", + "mediaType": "application/x-matlab-data" + }, + { + "downloadURL": "https://data.nist.gov/od/ds/ark:/88434/mds2-3055/mCP%20SIMCA%20Model/NIST_mCP_SIMCAModel.mat.sha256", + "mediaType": "text/plain" + } + ], + "identifier": "ark:/88434/mds2-3055", + "issued": "2024-04-02", + "keyword": [ + "SIMCA", + "m-cresol purple", + "pH indicator", + "seawater pH", + "spectrophotometric pH" + ], + "landingPage": "https://data.nist.gov/od/id/mds2-3055", + "language": [ + "en" + ], + "license": "https://www.nist.gov/open/license", + "modified": "2023-07-13 00:00:00", + "programCode": [ + "006:045" + ], + "publisher": { + "@type": "org:Organization", + "name": "National Institute of Standards and Technology" + }, + "references": [ + "https://doi.org/10.1016/j.marchem.2024.104362" + ], + "theme": [ + "Chemistry:Analytical chemistry", + "Environment:Marine science" + ], + "title": "UV-visible absorbance spectra of purified and unpurified m-cresol purple samples in sodium hydroxide and sodium chloride solutions at pH 12" + }, + "description": "M-cresol purple is the most widely used pH indicator dye for seawater pH measurements. Impurities in the indicator are known to absorb strongly at one of the wavelengths used in spectrophotometric pH determination and lead to large biases in the pH measurements. This repository contains data and Matlab scripts to facilitate the implementation of a DD-SIMCA model for detecting residual impurities in purified m-cresol purple (mCP) relevant to climate quality seawater pH measurements. The model was trained on measurements of UV-visible absorbance spectra of purified mCP and tested on independent datasets consisting of purified and unpurified mCP samples. The repository contains demo scripts that will demonstrate the training and optimization of the DD-SIMCA model and reproduce the figures in the associated publication. A function is provided for users to classify new mCP samples with the model.\n\nThe datasets consist of measurements of the UV-visible absorbance spectra (350 nm to 750 nm) of purified and unpurified m-cresol purple samples in sodium hydroxide and sodium chloride solutions at pH\n12 and an ionic strength of 0.7 mol/kg soln. The UV-visible absorbance measurements were collected on an Agilent Cary 100 spectrophotometer at NIST. A second dataset is included consisting of \nsimilar measurements of various purified m-cresol purple samples collected on an Agilent 8453 spectrophotometer at MBARI. This dataset was used to test the performance of the SIMCA model on samples measured on a different spectrophotometer. The SIMCA model and results are published in the manuscript \"Detection of impurities in m-cresol purple with SIMCA for the quality control of spectrophotometric pH measurements in seawater.\"", + "distribution_titles": [], + "harvest_record": "https://catalog.data.gov/harvest_record/21dd9172-001d-4abb-96e0-1d2ea0fa88a1", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/21dd9172-001d-4abb-96e0-1d2ea0fa88a1/raw", + "has_download": true, + "has_spatial": false, + "identifier": "ark:/88434/mds2-3055", + "keyword": [ + "SIMCA", + "m-cresol purple", + "pH indicator", + "seawater pH", + "spectrophotometric pH" + ], + "last_harvested_date": "2026-10-02T19:53:21.664493", + "organization": { + "aliases": [ + "dept", + "doc" + ], + "code_repo_exempt": false, + "code_repo_url": null, + "description": null, + "id": "16980d1c-5e8f-4188-b962-42446f2d3f63", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/commerce.png", + "name": "Department of Commerce", + "organization_type": "Federal Government", + "slug": "commerce" + }, + "parent_identifier": null, + "popularity": 0, + "publisher": "National Institute of Standards and Technology", + "slug": "uv-visible-absorbance-spectra-of-purified-and-unpurified-m-cresol-purple-samples-in-sod-12-aa07f", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Chemistry:Analytical chemistry", + "Environment:Marine science" + ], + "title": "UV-visible absorbance spectra of purified and unpurified m-cresol purple samples in sodium hydroxide and sodium chloride solutions at pH 12", + "type": "dataset" + }, + { + "_score": 10.418863, + "_sort": [ + 1790970781691, + 10.418863, + 0, + "a90682d4-8e79-4a04-a87c-03fc83666753" + ], + "access_level": "public", + "dcat": { + "@type": "dcat:Dataset", + "accessLevel": "public", + "bureauCode": [ + "006:55" + ], + "contactPoint": { + "fn": "Aaron Rowane", + "hasEmail": "mailto:aaron.rowane@nist.gov" + }, + "description": "Speed of Sound Measurements of Binary Mixtures of Difluoromethane (R-32) with 2,3,3,3-Tetrafluoropropene (R-1234yf) or trans-1,3,3,3-Tetrafluoropropene (R-1234ze(E)) Refrigerants", + "distribution": [ + { + "description": "Unaveraged speed of sound data for R-32/1234yf and R-32/1234ze(E). Each state point contains up to four speed of sound values derived from triplicated, back-to-back, speed of sound measurements. Included are the REFPROP fluid names, composition, temperature, pressure, and speed of sound. Additionally included are the standard deviations and uncertainties in temperature, pressure, and speed of sound measurements.", + "downloadURL": "https://data.nist.gov/od/ds/mds2-2804/R32_R1234yf_R1234ze%28E%29_SOSData.csv", + "format": "The data are in .csv format for easy export into data analysis tools. Opening data in excel allow for the data to be viewed in human readable format.", + "mediaType": "text/csv", + "title": "Unaveraged speed of sound data for R-32/1234yf and R-32/1234ze(E) binary mixtures" + } + ], + "identifier": "ark:/88434/mds2-2804", + "issued": "2022-10-03", + "keyword": [ + "Advanced Materials", + "Energy", + "Environment and Climate", + "Physical Infrastructure", + "Safety", + "Security and Forensics" + ], + "language": [ + "en" + ], + "license": "https://www.nist.gov/open/license", + "modified": "2021-11-28 00:00:00", + "programCode": [ + "006:045" + ], + "publisher": { + "@type": "org:Organization", + "name": "National Institute of Standards and Technology" + }, + "theme": [ + "Chemistry:Chemical thermodynamics and chemical properties" + ], + "title": "Speed of Sound Measurements of Binary Mixtures of Difluoromethane (R-32) with 2,3,3,3-Tetrafluoropropene (R-1234yf) or trans-1,3,3,3-Tetrafluoropropene (R-1234ze(E)) Refrigerants" + }, + "description": "Speed of Sound Measurements of Binary Mixtures of Difluoromethane (R-32) with 2,3,3,3-Tetrafluoropropene (R-1234yf) or trans-1,3,3,3-Tetrafluoropropene (R-1234ze(E)) Refrigerants", + "distribution_titles": [ + "Unaveraged speed of sound data for R-32/1234yf and R-32/1234ze(E) binary mixtures" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/2bc69ab3-1326-4abd-aa13-6c5ab88c5961", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/2bc69ab3-1326-4abd-aa13-6c5ab88c5961/raw", + "has_download": true, + "has_spatial": false, + "identifier": "ark:/88434/mds2-2804", + "keyword": [ + "Advanced Materials", + "Energy", + "Environment and Climate", + "Physical Infrastructure", + "Safety", + "Security and Forensics" + ], + "last_harvested_date": "2026-10-02T19:53:01.691525", + "organization": { + "aliases": [ + "dept", + "doc" + ], + "code_repo_exempt": false, + "code_repo_url": null, + "description": null, + "id": "16980d1c-5e8f-4188-b962-42446f2d3f63", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/commerce.png", + "name": "Department of Commerce", + "organization_type": "Federal Government", + "slug": "commerce" + }, + "parent_identifier": null, + "popularity": 0, + "publisher": "National Institute of Standards and Technology", + "slug": "speed-of-sound-measurements-of-binary-mixtures-of-difluoromethane-r-32-with-2333-tetrafluo-f4efe", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Chemistry:Chemical thermodynamics and chemical properties" + ], + "title": "Speed of Sound Measurements of Binary Mixtures of Difluoromethane (R-32) with 2,3,3,3-Tetrafluoropropene (R-1234yf) or trans-1,3,3,3-Tetrafluoropropene (R-1234ze(E)) Refrigerants", + "type": "dataset" + }, + { + "_score": 10.453738, + "_sort": [ + 1790970781542, + 10.453738, + 0, + "faa594b6-b93d-4d2f-94f1-8cb05fa430ba" + ], + "access_level": "public", + "dcat": { + "@type": "dcat:Dataset", + "accessLevel": "public", + "accrualPeriodicity": "irregular", + "bureauCode": [ + "006:55" + ], + "contactPoint": { + "fn": "Aaron Rowane", + "hasEmail": "mailto:aaron.rowane@nist.gov" + }, + "description": "Workflow: The data that falls into this category are gathered from a measurement program and are published in the archival literature.", + "distribution": [ + { + "description": "A readme describing the thermal conductivity data supplied on this page", + "downloadURL": "https://data.nist.gov/od/ds/mds2-2803/2803_README.txt", + "mediaType": "text/plain", + "title": "Readme for thermal conductivity data of R-1234yf/134a, R-1234yf/1234ze(E), and R-134a/1234ze(E) mixtures" + }, + { + "description": "Data included are the components in the binary mixture and their composition listed with the measured temperature, pressure, and thermal conductivity values. Additionally included in the data set are densities calculated to determine the thermal conductivity.", + "downloadURL": "https://data.nist.gov/od/ds/mds2-2803/AllTCXData.csv", + "format": ".csv file which is a machine readable format. Opening the file in excel provides a human readable format.", + "mediaType": "text/csv", + "title": "Thermal conductivity data for R-1234yf/134a, R-1234yf/1234ze(E), and R-134a/1234ze(E) mixture" + }, + { + "description": "Thermal conductivity data for binary mixtures of R-134a, R-1234yf, and R-1234ze(E)", + "downloadURL": "https://data.nist.gov/od/ds/mds2-2803/SupplementalFiles.zip", + "mediaType": "application/x-zip-compressed", + "title": "Thermal Conductivity of Binary Mixtures of 1,1,1,2-Tetrafluoroethane(R-134a), 2,3,3,3-Tetrafluoropropene (R-1234yf), and trans-1,3,3,3-Tetrafluoropropene (R-1234ze(E)) Refrigerants" + } + ], + "identifier": "ark:/88434/mds2-2803", + "issued": "2022-10-03", + "keyword": [ + "Advanced Materials", + "Energy", + "Environment and Climate", + "Physical Infrastructure", + "Safety", + "Security and Forensics" + ], + "landingPage": "https://data.nist.gov/od/id/mds2-2803", + "language": [ + "en" + ], + "license": "https://www.nist.gov/open/license", + "modified": "2022-07-28 00:00:00", + "programCode": [ + "006:045" + ], + "publisher": { + "@type": "org:Organization", + "name": "National Institute of Standards and Technology" + }, + "references": [ + "https://doi.org/10.1021/acs.iecr.2c01924" + ], + "theme": [ + "Chemistry:Chemical thermodynamics and chemical properties" + ], + "title": "Thermal Conductivity of Binary Mixtures of 1,1,1,2-Tetrafluoroethane(R-134a), 2,3,3,3-Tetrafluoropropene (R-1234yf), and trans-1,3,3,3-Tetrafluoropropene (R-1234ze(E)) Refrigerants" + }, + "description": "Workflow: The data that falls into this category are gathered from a measurement program and are published in the archival literature.", + "distribution_titles": [ + "Readme for thermal conductivity data of R-1234yf/134a, R-1234yf/1234ze(E), and R-134a/1234ze(E) mixtures", + "Thermal conductivity data for R-1234yf/134a, R-1234yf/1234ze(E), and R-134a/1234ze(E) mixture", + "Thermal Conductivity of Binary Mixtures of 1,1,1,2-Tetrafluoroethane(R-134a), 2,3,3,3-Tetrafluoropropene (R-1234yf), and trans-1,3,3,3-Tetrafluoropropene (R-1234ze(E)) Refrigerants" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/4beb3357-1da1-45ef-b1d7-cfee836c99a3", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/4beb3357-1da1-45ef-b1d7-cfee836c99a3/raw", + "has_download": true, + "has_spatial": false, + "identifier": "ark:/88434/mds2-2803", + "keyword": [ + "Advanced Materials", + "Energy", + "Environment and Climate", + "Physical Infrastructure", + "Safety", + "Security and Forensics" + ], + "last_harvested_date": "2026-10-02T19:53:01.542324", + "organization": { + "aliases": [ + "dept", + "doc" + ], + "code_repo_exempt": false, + "code_repo_url": null, + "description": null, + "id": "16980d1c-5e8f-4188-b962-42446f2d3f63", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/commerce.png", + "name": "Department of Commerce", + "organization_type": "Federal Government", + "slug": "commerce" + }, + "parent_identifier": null, + "popularity": 0, + "publisher": "National Institute of Standards and Technology", + "slug": "thermal-conductivity-of-binary-mixtures-of-1112-tetrafluoroethaner-134a-2333-tetrafluoropr-aeb81", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Chemistry:Chemical thermodynamics and chemical properties" + ], + "title": "Thermal Conductivity of Binary Mixtures of 1,1,1,2-Tetrafluoroethane(R-134a), 2,3,3,3-Tetrafluoropropene (R-1234yf), and trans-1,3,3,3-Tetrafluoropropene (R-1234ze(E)) Refrigerants", + "type": "dataset" + }, + { + "_score": 8.451689, + "_sort": [ + 1790970752211, + 8.451689, + 0, + "7a70facc-94a5-4465-b4d8-155fb411a2b7" + ], + "access_level": "public", + "dcat": { + "@type": "dcat:Dataset", + "accessLevel": "public", + "accrualPeriodicity": "irregular", + "bureauCode": [ + "006:55" + ], + "contactPoint": { + "fn": "Jared Ragland", + "hasEmail": "mailto:jared.ragland@nist.gov" + }, + "describedBy": "https://data.nist.gov/od/ds/mds2-2431/reported_fields.csv", + "description": "Here we provide curated analytical chemistry data for eggs collected from 1999 to 2010 on a subset of species and analytes that were measured regularly and reasonably systematically. Included in this publication are 487 samples analyzed for 174 ubiquitous environmental contaminants such as (poly)brominated diphenyl ethers (BDEs), mercury, organochlorine pesticides (OCPs), and polychlorinated biphenyls (PCBs). Data were collated to form a dataset useful in chemometric and related analyses of the marine ecosystem in the north Pacific Ocean.", + "distribution": [ + { + "accessURL": "https://doi.org/10.18434/mds2-2431", + "title": "DOI Access for Data Supporting \"Seabird Tissue Archival and Monitoring Project (STAMP) Data from 1999-2010\"" + }, + { + "description": "A list of the column names present in files \"stamp_chemistry.csv\" and \"stamp_samples.csv\" with human meaningful definitions.", + "downloadURL": "https://data.nist.gov/od/ds/mds2-2431/reported_fields.csv", + "format": "comma-separated-value", + "mediaType": "application/vnd.ms-excel", + "title": "Data Dictionary" + }, + { + "description": "Analytical chemistry values for this data set including aliquot ID, analyte name, detection limit, measured value, detection status, units, analyte category, and a statistical value. 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Conversely, removing crop residue can generate an additional income stream for agricultural producers, while broadening the spectrum of uses from harvestable commodities. Understanding potential tradeoffs of crop residue removal across a range of agroecosystems over the long-term is essential to adequately guide management decisions. A study was conducted to quantify crop and soil responses to continuous spring wheat treatments with and without straw removal, each managed under minimum and no-tillage. Treatments were replicated three times and deployed over a 24-yr period. Soil coverage by crop residue was measured annually using two 25 point transects spaced equally along a 7.6 m cable. Spring wheat aboveground biomass was measured prior to combine harvest using 0.33 m2 frames. Biomass samples were threshed to separate grain from straw. Soil samples were collected in 2018 with a hydraulic probe to a 152.4 cm depth in increments of 0-7.6, 7.6-15.2, 15.2-30.5, 30.5-61.0, 61.0-91.4, 91.4-121.9, and 121.9-152.4 cm. Separate samples for aggregate stability analysis were collected with a trowel from the 0-7.6 cm depth. Soil samples were evaluated for soil bulk density, water-stable aggregates (WSA), electrical conductivity, soil pH, nitrate-nitrogen, available phosphorus, sulfate-sulfur, exchangeable cations (Ca, Mg, K, Na), micronutrients (B, Cu, Fe, Mn, Zn), total soil nitrogen, total carbon, inorganic carbon, and particulate organic matter (POM) carbon and nitrogen. Particulate organic matter (POM) was estimated from material retained on a 0.053 mm sieve analyzed for carbon and nitrogen content by dry combustion. Analyses for POM and WSA were conducted for the 0-7.6 cm depth only. Data may be used to better understand crop and soil property responses to residue management and tillage practices under rainfed conditions within a semiarid continental climate. Applicable USDA soil types include Temvik, Wilton, Grassna, Linton, Mandan, and Williams.</p><p dir=\"ltr\">The SQM Data Dictionary describes element/value names, data type, etc. for each spreadsheet tab, and the Metadata files describe attributes and units for their respective data files.</p><p><br></p><p dir=\"ltr\"><br></p>", - "distribution": [ - { - "@type": "dcat:Distribution", - "downloadURL": "https://ndownloader.figshare.com/files/66673745", - "format": "xlsx", - "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", - "title": "SQM_Data Dictionary.xlsx" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://ndownloader.figshare.com/files/66673748", - "format": "xlsx", - "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", - "title": "SQM_AllDepthsSoil_2018.xlsx" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://ndownloader.figshare.com/files/66673751", - "format": "xlsx", - "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", - "title": "SQM_Crop_Aboveground Biomass.xlsx" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://ndownloader.figshare.com/files/66673754", - "format": "xlsx", - "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", - "title": "SQM_Soil Cover.xlsx" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://ndownloader.figshare.com/files/66673757", - "format": "xlsx", - "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", - "title": "SQM_WSA&POM.xlsx" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://ndownloader.figshare.com/files/66673760", - "format": "csv", - "mediaType": "text/csv", - "title": "SQM_AllDepthsSoil_2018_Data.csv" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://ndownloader.figshare.com/files/66673763", - "format": "csv", - "mediaType": "text/csv", - "title": "SQM_AllDepthsSoil_2018_Metadata.csv" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://ndownloader.figshare.com/files/66673766", - "format": "csv", - "mediaType": "text/csv", - "title": "SQM_Crop_Aboveground Biomass_Data.csv" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://ndownloader.figshare.com/files/66673769", - "format": "csv", - "mediaType": "text/csv", - "title": "SQM_Crop_Aboveground Biomass_Metadata.csv" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://ndownloader.figshare.com/files/66673772", - "format": "csv", - "mediaType": "text/csv", - "title": "SQM_Soil Cover_Data.csv" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://ndownloader.figshare.com/files/66673775", - "format": "csv", - "mediaType": "text/csv", - "title": "SQM_Soil Cover_Metadata.csv" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://ndownloader.figshare.com/files/66673778", - "format": "csv", - "mediaType": "text/csv", - "title": "SQM_WSA&POM_Data.csv" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://ndownloader.figshare.com/files/66673781", - "format": "csv", - "mediaType": "text/csv", - "title": "SQM_WSA&POM_Metadata.csv" - } - ], - "identifier": "10.15482/USDA.ADC/32911835.v1", - "keyword": [ - "No-tillage", - "Residue management", - "Semiarid cropping systems", - "Soil cover", - "Spring wheat" - ], - "license": "https://creativecommons.org/publicdomain/zero/1.0/", - "modified": "2026-08-11", - "programCode": [ - "005:040" - ], - "publisher": { - "@type": "org:Organization", - "name": "Agricultural Research Service" - }, - "spatial": "{\"type\": \"Point\", \"coordinates\": [-100.95, 46.77099999999999]}", - "temporal": "1994-04-01/2018-04-01", - "title": "Data from: Crop and Soil Responses to 24 years of Wheat Residue Removal and Tillage" - }, - "description": "<p dir=\"ltr\">Retaining crop residue on the soil surface is important in semiarid cropping systems, where dry conditions and variable weather can render the soil susceptible to degradation and moisture loss. Conversely, removing crop residue can generate an additional income stream for agricultural producers, while broadening the spectrum of uses from harvestable commodities. Understanding potential tradeoffs of crop residue removal across a range of agroecosystems over the long-term is essential to adequately guide management decisions. A study was conducted to quantify crop and soil responses to continuous spring wheat treatments with and without straw removal, each managed under minimum and no-tillage. Treatments were replicated three times and deployed over a 24-yr period. Soil coverage by crop residue was measured annually using two 25 point transects spaced equally along a 7.6 m cable. Spring wheat aboveground biomass was measured prior to combine harvest using 0.33 m2 frames. Biomass samples were threshed to separate grain from straw. Soil samples were collected in 2018 with a hydraulic probe to a 152.4 cm depth in increments of 0-7.6, 7.6-15.2, 15.2-30.5, 30.5-61.0, 61.0-91.4, 91.4-121.9, and 121.9-152.4 cm. Separate samples for aggregate stability analysis were collected with a trowel from the 0-7.6 cm depth. Soil samples were evaluated for soil bulk density, water-stable aggregates (WSA), electrical conductivity, soil pH, nitrate-nitrogen, available phosphorus, sulfate-sulfur, exchangeable cations (Ca, Mg, K, Na), micronutrients (B, Cu, Fe, Mn, Zn), total soil nitrogen, total carbon, inorganic carbon, and particulate organic matter (POM) carbon and nitrogen. Particulate organic matter (POM) was estimated from material retained on a 0.053 mm sieve analyzed for carbon and nitrogen content by dry combustion. Analyses for POM and WSA were conducted for the 0-7.6 cm depth only. Data may be used to better understand crop and soil property responses to residue management and tillage practices under rainfed conditions within a semiarid continental climate. Applicable USDA soil types include Temvik, Wilton, Grassna, Linton, Mandan, and Williams.</p><p dir=\"ltr\">The SQM Data Dictionary describes element/value names, data type, etc. for each spreadsheet tab, and the Metadata files describe attributes and units for their respective data files.</p><p><br></p><p dir=\"ltr\"><br></p>", - "distribution_titles": [ - "SQM_Data Dictionary.xlsx", - "SQM_AllDepthsSoil_2018.xlsx", - "SQM_Crop_Aboveground Biomass.xlsx", - "SQM_Soil Cover.xlsx", - "SQM_WSA&POM.xlsx", - "SQM_AllDepthsSoil_2018_Data.csv", - "SQM_AllDepthsSoil_2018_Metadata.csv", - "SQM_Crop_Aboveground Biomass_Data.csv", - "SQM_Crop_Aboveground Biomass_Metadata.csv", - "SQM_Soil Cover_Data.csv", - "SQM_Soil Cover_Metadata.csv", - "SQM_WSA&POM_Data.csv", - "SQM_WSA&POM_Metadata.csv" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/84fcca8f-454c-4458-8141-4a9f51de279c", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/84fcca8f-454c-4458-8141-4a9f51de279c/raw", - "has_download": true, - "has_spatial": true, - "identifier": "10.15482/USDA.ADC/32911835.v1", - "keyword": [ - "No-tillage", - "Residue management", - "Semiarid cropping systems", - "Soil cover", - "Spring wheat" - ], - "last_harvested_date": "2026-09-30T21:31:35.703428", - "organization": { - "aliases": [ - "dept" - ], - "code_repo_exempt": false, - "code_repo_url": null, - "description": null, - "id": "352b4532-793d-4075-a03f-05b778a3c43a", - "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/usda.png", - "name": "Department of Agriculture", - "organization_type": "Federal Government", - "slug": "usda" - }, - "parent_identifier": null, - "popularity": 4, - "publisher": "Agricultural Research Service", - "slug": "data-from-crop-and-soil-responses-to-24-years-of-wheat-residue-removal-and-tillage", - "spatial_centroid": { - "lat": 46.77099999999999, - "lon": -100.95 - }, - "spatial_shape": { - "coordinates": [ - -100.95, - 46.77099999999999 - ], - "type": "Point" - }, - "theme": [], - "title": "Data from: Crop and Soil Responses to 24 years of Wheat Residue Removal and Tillage", - "type": "dataset" - }, - { - "_score": 4.5621758, - "_sort": [ - 1790803845020, - 4.5621758, - 3, - "64eb3d36-297a-42e0-8ada-993f0f668373" - ], - "access_level": "public", - "dcat": { - "@type": "dcat:Dataset", - "accessLevel": "public", - "bureauCode": [ - "005:18" - ], - "contactPoint": { - "fn": "Roeder, Karl, A.", - "hasEmail": "mailto:karl.roeder@usda.gov" - }, - "description": "<p dir=\"ltr\">Three .csv files. Two years of data collected on critical thermal maxima and minima (CTmax and CTmin) from 14 colonies in Oklahoma from 2017-2018. Additional data files represent thermal traits from 10 colonies in a short term (10 days) acclimation experiment and projections using environmental data for potential activity differences.</p><p dir=\"ltr\"><b><u>Abstract from paper:</u></b></p><p dir=\"ltr\">How do individuals tolerate both the hot and the cold climate of our planet? One possibility is that organisms have plastic traits like thermal tolerance that allow them to function in highly variable environments. In this study, we tested whether phenotypic plasticity of temperature tolerance (i.e. acclimatization in the field and acclimation in the lab) occurs in the red harvester ant, <i>Pogonomyrmex barbatus</i>, at two temporal scales. We first measured the upper and lower critical thermal limits (CT<sub>max</sub> and CT<sub>min</sub>) of ants monthly for two years while concurrently measuring environmental conditions. Both CT<sub>max</sub> and CT<sub>min</sub> co-varied with temperature in a predictable way; values increased in a positive, linear manner. We then experimentally tested whether CT<sub>max</sub> and CT<sub>min</sub> could shift within a shorter time period by exposing subcolonies of ants to cool (10°C), moderate (20°C), and hot (30°C) temperatures for 10 days. CT<sub>max</sub> increased only slightly at the hottest temperature treatment (+1.2°C), however CT<sub>min</sub> increased considerably under both moderate (+2.6°C) and hot treatments (+3.8°C). Combined, our results suggest that thermal tolerance of ants may be more plastic than originally hypothesized, potentially aiding an already thermophilic clade.</p><p dir=\"ltr\"><b><u>Methods from paper:</u></b></p><p dir=\"ltr\"><i>Study site and environmental temperature</i></p><p dir=\"ltr\">We sampled ant workers monthly during their annual active period in 2017 and 2018 (i.e. March-November) from 14 colonies in a 30-ha grazed prairie in the central Great Plains of Oklahoma (34.5478º N, -98.2311º W, 330 m elevation). Over two years, ground temperature was recorded every 10 minutes using HOBO U23 Pro v2 External Temperature Data loggers at three equidistant locations within the sampling area. Temperature values were then averaged per month.</p><p><br></p><p dir=\"ltr\"><i>Thermal tolerance across months</i></p><p dir=\"ltr\">During each sampling event (n = 18), we collected ~20 workers directly outside the nest of each colony and used 5 workers to measure critical thermal maximum (CT<sub>max</sub>) and 5 workers to measure critical thermal minimum (CT<sub>min</sub>). We did so using a heating/cooling assay to determine the temperature at which individuals lost muscle control. Thermal assays were conducted by placing individual ants into 1.5ml microcentrifuge tubes and plugging the tops with cotton to remove a potential thermal refuge in the cap. For CT<sub>max</sub>, tubes were placed randomly into a Thermal-Lok 2-position dry heat bath that was prewarmed to 36ºC. Every 10 minutes, individuals were checked to see if they had reached their critical thermal limit by rotating the tube to check for a righting response. The temperature was then increased by 2ºC, with the process repeated until all individuals had reached their critical thermal maximum. CT<sub>min</sub> was assayed in a similar manner, but we used a EchoThermTM IC20 chilling/heating dry bath that was precooled to 20ºC, following the methods above except with temperature lowered 2°C every 10 minutes. Additional ants from each colony were kept at ambient conditions as a control during each thermal assay, all of which survived. During each trial, we also confirmed the interior temperature of one unused vial using a thermocouple attached to an Extech MN35 Digital Mini MultiMeter. CT<sub>max</sub> and CT<sub>min</sub> values were averaged per colony for each month.</p><p><br></p><p dir=\"ltr\"><i>Thermal tolerance within a month</i></p><p dir=\"ltr\">In April of 2019, we collected ~200 workers from each of 10 separate colonies to assess if critical thermal limits could change within a single cohort of ants over a short period of time. We split each group of 200 workers into three sub-colonies containing 50 workers and placed these newly created sub-colonies into three environmental chambers set at 10ºC, 20ºC, and 30ºC with a 12:12 L:D cycle and 85% RH. The selected temperatures span the approximate range of average monthly temperatures at our study site during which ants were active. Each sub-colony was provided with water and 20% sucrose solution ad libitum in cotton plugged vials and a small petri dish with Plaster of Paris that was moistened every other day. Critical thermal limits (CT<sub>max</sub> and CT<sub>min</sub>) were assayed using five individuals from each colony immediately prior to the start of the experiment and for five individuals from each sub-colony after 10 days in the environmental chambers. CT<sub>max</sub> and CT<sub>min</sub> values were averaged per colony for each temperature treatment.</p>", - "distribution": [ - { - "@type": "dcat:Distribution", - "downloadURL": "https://ndownloader.figshare.com/files/52668251", - "format": "csv", - "mediaType": "text/csv", - "title": "File 2 Across Months Pogo Thermal.csv" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://ndownloader.figshare.com/files/52668254", - "format": "csv", - "mediaType": "text/csv", - "title": "File 3 Within Month Pogo Thermal.csv" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://ndownloader.figshare.com/files/52668257", - "format": "csv", - "mediaType": "text/csv", - "title": "File 1 METADATA Pogo Thermal.csv" - } - ], - "identifier": "10.15482/USDA.ADC/28459058.v1", - "keyword": [ - "Critical thermal limits", - "Pogonomyrmex barbatus", - "temperature", - "traits" - ], - "license": "https://www.usa.gov/publicdomain/label/1.0/", - "modified": "2026-08-25", - "programCode": [ - "005:040" - ], - "publisher": { - "@type": "org:Organization", - "name": "Agricultural Research Service" - }, - "temporal": "2017-03-01/2018-11-30", - "title": "Data from: Temporal plasticity of thermal tolerance in ants" - }, - "description": "<p dir=\"ltr\">Three .csv files. Two years of data collected on critical thermal maxima and minima (CTmax and CTmin) from 14 colonies in Oklahoma from 2017-2018. Additional data files represent thermal traits from 10 colonies in a short term (10 days) acclimation experiment and projections using environmental data for potential activity differences.</p><p dir=\"ltr\"><b><u>Abstract from paper:</u></b></p><p dir=\"ltr\">How do individuals tolerate both the hot and the cold climate of our planet? One possibility is that organisms have plastic traits like thermal tolerance that allow them to function in highly variable environments. In this study, we tested whether phenotypic plasticity of temperature tolerance (i.e. acclimatization in the field and acclimation in the lab) occurs in the red harvester ant, <i>Pogonomyrmex barbatus</i>, at two temporal scales. We first measured the upper and lower critical thermal limits (CT<sub>max</sub> and CT<sub>min</sub>) of ants monthly for two years while concurrently measuring environmental conditions. Both CT<sub>max</sub> and CT<sub>min</sub> co-varied with temperature in a predictable way; values increased in a positive, linear manner. We then experimentally tested whether CT<sub>max</sub> and CT<sub>min</sub> could shift within a shorter time period by exposing subcolonies of ants to cool (10°C), moderate (20°C), and hot (30°C) temperatures for 10 days. CT<sub>max</sub> increased only slightly at the hottest temperature treatment (+1.2°C), however CT<sub>min</sub> increased considerably under both moderate (+2.6°C) and hot treatments (+3.8°C). Combined, our results suggest that thermal tolerance of ants may be more plastic than originally hypothesized, potentially aiding an already thermophilic clade.</p><p dir=\"ltr\"><b><u>Methods from paper:</u></b></p><p dir=\"ltr\"><i>Study site and environmental temperature</i></p><p dir=\"ltr\">We sampled ant workers monthly during their annual active period in 2017 and 2018 (i.e. March-November) from 14 colonies in a 30-ha grazed prairie in the central Great Plains of Oklahoma (34.5478º N, -98.2311º W, 330 m elevation). Over two years, ground temperature was recorded every 10 minutes using HOBO U23 Pro v2 External Temperature Data loggers at three equidistant locations within the sampling area. Temperature values were then averaged per month.</p><p><br></p><p dir=\"ltr\"><i>Thermal tolerance across months</i></p><p dir=\"ltr\">During each sampling event (n = 18), we collected ~20 workers directly outside the nest of each colony and used 5 workers to measure critical thermal maximum (CT<sub>max</sub>) and 5 workers to measure critical thermal minimum (CT<sub>min</sub>). We did so using a heating/cooling assay to determine the temperature at which individuals lost muscle control. Thermal assays were conducted by placing individual ants into 1.5ml microcentrifuge tubes and plugging the tops with cotton to remove a potential thermal refuge in the cap. For CT<sub>max</sub>, tubes were placed randomly into a Thermal-Lok 2-position dry heat bath that was prewarmed to 36ºC. Every 10 minutes, individuals were checked to see if they had reached their critical thermal limit by rotating the tube to check for a righting response. The temperature was then increased by 2ºC, with the process repeated until all individuals had reached their critical thermal maximum. CT<sub>min</sub> was assayed in a similar manner, but we used a EchoThermTM IC20 chilling/heating dry bath that was precooled to 20ºC, following the methods above except with temperature lowered 2°C every 10 minutes. Additional ants from each colony were kept at ambient conditions as a control during each thermal assay, all of which survived. During each trial, we also confirmed the interior temperature of one unused vial using a thermocouple attached to an Extech MN35 Digital Mini MultiMeter. CT<sub>max</sub> and CT<sub>min</sub> values were averaged per colony for each month.</p><p><br></p><p dir=\"ltr\"><i>Thermal tolerance within a month</i></p><p dir=\"ltr\">In April of 2019, we collected ~200 workers from each of 10 separate colonies to assess if critical thermal limits could change within a single cohort of ants over a short period of time. We split each group of 200 workers into three sub-colonies containing 50 workers and placed these newly created sub-colonies into three environmental chambers set at 10ºC, 20ºC, and 30ºC with a 12:12 L:D cycle and 85% RH. The selected temperatures span the approximate range of average monthly temperatures at our study site during which ants were active. Each sub-colony was provided with water and 20% sucrose solution ad libitum in cotton plugged vials and a small petri dish with Plaster of Paris that was moistened every other day. Critical thermal limits (CT<sub>max</sub> and CT<sub>min</sub>) were assayed using five individuals from each colony immediately prior to the start of the experiment and for five individuals from each sub-colony after 10 days in the environmental chambers. CT<sub>max</sub> and CT<sub>min</sub> values were averaged per colony for each temperature treatment.</p>", - "distribution_titles": [ - "File 2 Across Months Pogo Thermal.csv", - "File 3 Within Month Pogo Thermal.csv", - "File 1 METADATA Pogo Thermal.csv" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/baca902d-dd40-4535-bead-faa5a68dce8f", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/baca902d-dd40-4535-bead-faa5a68dce8f/raw", - "has_download": true, - "has_spatial": false, - "identifier": "10.15482/USDA.ADC/28459058.v1", - "keyword": [ - "Critical thermal limits", - "Pogonomyrmex barbatus", - "temperature", - "traits" - ], - "last_harvested_date": "2026-09-30T21:30:45.020435", - "organization": { - "aliases": [ - "dept" - ], - "code_repo_exempt": false, - "code_repo_url": null, - "description": null, - "id": "352b4532-793d-4075-a03f-05b778a3c43a", - "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/usda.png", - "name": "Department of Agriculture", - "organization_type": "Federal Government", - "slug": "usda" - }, - "parent_identifier": null, - "popularity": 3, - "publisher": "Agricultural Research Service", - "slug": "data-from-temporal-plasticity-of-thermal-tolerance-in-ants", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [], - "title": "Data from: Temporal plasticity of thermal tolerance in ants", - "type": "dataset" - }, - { - "_score": 15.252234, - "_sort": [ - 1790803842515, - 15.252234, - 1, - "a592d3cf-ad2e-4a98-a2bf-e2f7fdd71671" - ], - "access_level": "public", - "dcat": { - "@type": "dcat:Dataset", - "accessLevel": "public", - "bureauCode": [ - "005:18" - ], - "contactPoint": { - "fn": "Bandaru, Varaprasad", - "hasEmail": "mailto:prasad.bandaru@usda.gov" - }, - "description": "<p dir=\"ltr\">The Environmental Policy Integrated Climate (EPIC) model is a comprehensive, field-scale agroecosystem model widely used for both diagnostic and prognostic analyses in agriculture. However, its application at regional scales is limited due to its original design to simulate a limited number of fields. Custom Python or R scripts have attempted to scale EPIC, but they are often inefficient, non-standardized, and not publicly available. To address these issues, a comprehensive Python package, named as GeoEPIC, that streamlines spatial EPIC implementation. GeoEPIC automates input generation from spatial datasets, model calibration, simulation execution, and output post-processing.</p>", - "distribution": [ - { - "@type": "dcat:Distribution", - "downloadURL": "https://smarsgroup.github.io/geo_epic_win/reference/api/core/", - "mediaType": "text/html", - "title": "https://smarsgroup.github.io/geo_epic_win/reference/api/core/" - } - ], - "identifier": "10779/USDA.ADC.31151371.v1", - "keyword": [ - "EPIC crop model", - "Python", - "Spatial Modeling Approach" - ], - "license": "https://opensource.org/license/BSD-3-Clause", - "modified": "2026-08-25", - "programCode": [ - "005:040" - ], - "publisher": { - "@type": "org:Organization", - "name": "Agricultural Research Service" - }, - "temporal": "2024-06-01/2025-11-30", - "title": "GeoEPIC Python Package" - }, - "description": "<p dir=\"ltr\">The Environmental Policy Integrated Climate (EPIC) model is a comprehensive, field-scale agroecosystem model widely used for both diagnostic and prognostic analyses in agriculture. However, its application at regional scales is limited due to its original design to simulate a limited number of fields. Custom Python or R scripts have attempted to scale EPIC, but they are often inefficient, non-standardized, and not publicly available. To address these issues, a comprehensive Python package, named as GeoEPIC, that streamlines spatial EPIC implementation. GeoEPIC automates input generation from spatial datasets, model calibration, simulation execution, and output post-processing.</p>", - "distribution_titles": [ - "https://smarsgroup.github.io/geo_epic_win/reference/api/core/" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/8efe138f-32f1-43cf-ad94-fc669543fae2", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/8efe138f-32f1-43cf-ad94-fc669543fae2/raw", - "has_download": true, - "has_spatial": false, - "identifier": "10779/USDA.ADC.31151371.v1", - "keyword": [ - "EPIC crop model", - "Python", - "Spatial Modeling Approach" - ], - "last_harvested_date": "2026-09-30T21:30:42.515787", - "organization": { - "aliases": [ - "dept" - ], - "code_repo_exempt": false, - "code_repo_url": null, - "description": null, - "id": "352b4532-793d-4075-a03f-05b778a3c43a", - "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/usda.png", - "name": "Department of Agriculture", - "organization_type": "Federal Government", - "slug": "usda" - }, - "parent_identifier": null, - "popularity": 1, - "publisher": "Agricultural Research Service", - "slug": "geoepic-python-package", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [], - "title": "GeoEPIC Python Package", - "type": "dataset" - }, - { - "_score": 8.308588, - "_sort": [ - 1790794424534, - 8.308588, - 4, - "374f22e6-71ff-41c8-ad59-226d7c041e6e" - ], - "access_level": "public", - "dcat": { - "@type": "dcat:Dataset", - "accessLevel": "public", - "contactPoint": { - "@type": "vcard:Contact", - "fn": "OpenData", - "hasEmail": "mailto:no-reply@data.sf.gov" - }, - "description": "<strong>A. SUMMARY</strong>\nThe Municipal Natural Gas Equipment Inventory serves to catalog natural gas-fueled equipment used in municipally owned buildings. \nThis inventory, implemented by the SF Environment Department, aims to establish an understanding of the scope of work needed to electrify municipal buildings and inform an effective and collaborative planning process.\nThis effort was identified as an action in Section BO-2.4 of the <u><a href=\"https://www.sfenvironment.org/files/events/2021_climate_action_plan.pdf\">2021 Climate Action Plan</a></u> and is included in the <u><a href=\"https://codelibrary.amlegal.com/codes/san_francisco/latest/sf_environment/0-0-0-577\">Environment Code Chapter 7</a></u> (Municipal Green Building Requirements). \n\n<strong>B. HOW THE DATASET IS CREATED</strong>\nThe list of buildings required to report data for the Municipal Natural Gas Equipment Inventory was compiled by cross-referencing the City’s <u><a href=\"https://data.sfgov.org/City-Infrastructure/City-Facilities/nc68-ngbr/about_datax\">Facility Systems of Record</a></u> and the <u><a href=\"https://sfpuc.org/about-us/reports/municipal-buildings-energy-benchmarking\">2020 municipal benchmarking report</a></u> to identify all city-owned buildings with non-zero carbon emissions. Numerous municipal buildings are exempt from these reporting requirements, including facilities of the Port of San Francisco and buildings with a primary purpose of providing collection, storage, treatment, delivery, distribution, and/or transmission of water, wastewater, and/or power utilities. \nEach department received an inventory template, provided by the Environment Department, to submit high level building data and detailed information on each piece of natural gas equipment in use in these buildings. Departments were asked to self-report the required building and equipment data over the course of a 6-month data collection period in 2023 and are asked to keep this inventory up to date in the following years as equipment is replaced. \n\n<strong>C. 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"EARTH SCIENCE SERVICES > ENVIRONMENTAL ADVISORIES > MARINE ADVISORIES > MARINE WEATHER/FORECAST", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > ALABAMA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > ALASKA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > CALIFORNIA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > CONNECTICUT", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > DELAWARE", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > DISTRICT OF COLUMBIA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > FLORIDA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > GEORGIA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > GREAT LAKES", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > HAWAII", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > ILLINOIS", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > LOUISIANA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > MAINE", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > MARYLAND", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > MASSACHUSETTS", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > MICHIGAN", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > MINNESOTA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > MISSISSIPPI", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > NEW JERSEY", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > NEW YORK", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > NORTH CAROLINA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > OHIO", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > OREGON", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > PENNSYLVANIA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > RHODE ISLAND", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > SOUTH CAROLINA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > TEXAS", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > VIRGINIA", - 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Since the 1990s, NOAA's Center for Operational Oceanographic Products and Services (CO-OPS) has been collecting various meteorological data along the U.S. coastline, around the Great Lakes and connecting channels, as well as in various U.S. territories. Stations are configured for a variety of observation periods, depending upon the location. Some of these sensors are located with water level stations, while others are independent, dedicated meteorological stations. These data are used to support a variety of purposes including but not limited to safe and efficient marine navigation and coastal hazards monitoring. 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"CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > ALABAMA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > ALASKA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > CALIFORNIA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > CONNECTICUT", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > DELAWARE", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > DISTRICT OF COLUMBIA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > FLORIDA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > GEORGIA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > GREAT LAKES", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > HAWAII", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > ILLINOIS", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > LOUISIANA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > MAINE", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > MARYLAND", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > MASSACHUSETTS", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > MICHIGAN", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > MINNESOTA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > MISSISSIPPI", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > NEW JERSEY", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > NEW YORK", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > NORTH CAROLINA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > OHIO", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > OREGON", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > PENNSYLVANIA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > RHODE ISLAND", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > SOUTH CAROLINA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > TEXAS", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > VIRGINIA", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > WASHINGTON", - "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > WISCONSIN", - 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"type": "dataset" - }, - { - "_score": 2.201933, - "_sort": [ - 1790722008932, - 2.201933, - 0, - "6190e5f3-b470-4186-972c-5fb43ca6325c" - ], - "access_level": "non-public", - "dcat": { - "@type": "dcat:Dataset", - "accessLevel": "non-public", - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Gajdzik, Laura", - "hasEmail": "mailto:laura.gajdzik@noaa.gov" - }, - "describedByType": "application/octet-stream", - "description": "This metadata record describes multiple datasets including traits (reef fish and coral) as well as disturbance exposure (heat and tropical cyclone) of coral reef ecosystems in Guam and the CNMI in 2011 and 2022. Trait values were inferred from online databases, scientific papers, and gaps were filled in by experts. Environmental disturbance data were generated by scientists of the Ecosystem Sciences Division (ESD) of the Pacific Islands Fisheries Science Center (PIFSC). For disturbance exposure, site-level heat stress and cyclone exposure data was generated for 2011 and 2022. These data were derived from NOAA Coral Reef Watch CoralTemp v3.1 daily SST (1985–present) and IBTrACS v4 (1950–2022). Both trait and disturbance exposure datasets described in this metadata record were used with the already archived Mariana Archipelago RAMP (MARAMP) and the National Coral Reef Monitoring Program (NCRMP) data, to generate functional trait-based diversity indices, providing another aspect of reef resilience.\n\nThis project was funded by CRCP Project #36143 titled \"Estimating functional diversity and redundancy of reef communities to inform resilience-based management in the Marianas\". \nLink to publication will be provided once published.", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://accession.nodc.noaa.gov/#", - "describedByType": "application/octet-stream", - "description": "Fish trait values compiled from literature (reports, publication, etc) and online databases. Traits include: taxon name, mobility, schooling, activity, position, and diet.", - "mediaType": "text/html", - "title": "ESD_FISHTRAIT_MARIAN" - }, - { - "@type": "dcat:Distribution", - "accessURL": "https://forum.earthdata.nasa.gov/app.php/tag/GCMD%2BKeywords", - "describedByType": "application/octet-stream", - "description": "Global Change Master Directory (GCMD). 2026. GCMD Keywords, Version 24. Greenbelt, MD: Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA). URL (GCMD Keyword Forum Page): https://forum.earthdata.nasa.gov/app.php/tag/GCMD+Keywords", - "mediaType": "text/html", - "title": "GCMD Keyword Forum Page" - }, - { - "@type": "dcat:Distribution", - "accessURL": "https://www.fisheries.noaa.gov/inport/item/79227", - "describedByType": "application/octet-stream", - "description": "View the complete metadata record on InPort for more information about this dataset.", - "mediaType": "text/html", - "title": "Full Metadata Record" - } - ], - "identifier": "https://data.noaa.gov/waf/NOAA/nmfs/pifsc/iso/xml/79227.xml", - "issued": "2026-01-01T00:00:00.000+00:00", - "keyword": [ - "DOC/NOAA/NMFS/PIFSC/ESD > Ecosystem Sciences Division, Pacific Islands Fisheries Science Center, National Marine Fisheries Service, NOAA, U.S. Department of Commerce", - "EARTH SCIENCE > AGRICULTURE > ANIMAL SCIENCE > ANIMAL ECOLOGY AND BEHAVIOR", - "EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC PRESSURE > ANTICYCLONES/CYCLONES", - "EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > MARINE ECOSYSTEMS > BENTHIC", - "EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > MARINE ECOSYSTEMS > REEF > CORAL REEF", - "EARTH SCIENCE > CLIMATE INDICATORS > ATMOSPHERIC/OCEAN INDICATORS > SEA SURFACE TEMPERATURE INDICES", - "36143", - "Estimating functional diversity and redundancy of reef communities to inform resilience-based management in the Marianas", - "Numeric Data Sets > Biology", - "Numeric Data Sets > Oceanography", - "EARTH SCIENCE > Biosphere > Aquatic Habitat > Reef Habitat", - "EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment", - "EARTH SCIENCE > Oceans > Coastal Processes > Coral Reefs", - "EARTH SCIENCE > Oceans > Marine Biology > Coral", - "EARTH SCIENCE > Oceans > Marine Biology > Coral Communities", - "EARTH SCIENCE > Oceans > Marine Biology > Fish", - "EARTH SCIENCE > Oceans > Ocean Temperature > Sea Surface Temperature", - "CORAL REEF", - "CORAL SPECIES", - "FISH - CORAL REEF", - "FISH SPECIES", - "HABITAT - BENTHIC", - "Tropical Cyclones", - "WATER TEMPERATURE", - "derived products", - "laboratory analysis", - "CORAL REEF STUDIES", - "Coral Reef Conservation Program", - "National Coral Reef Monitoring Program", - "Pacific Reef and Assessment Monitoring Program", - "US DOC; NOAA; NMFS; Pacific Islands Fisheries Science Center; Ecosystem Sciences Division", - "COUNTRY/TERRITORY > Northern Mariana Islands > Rota > Rota Island ( Luta ) (14N145E0007)", - "COUNTRY/TERRITORY > Northern Mariana Islands > Saipan > Saipan Island (15N145E0002)", - "COUNTRY/TERRITORY > Northern Mariana Islands > Tinian > Tinian Island (14N145E0005)", - "COUNTRY/TERRITORY > United States of America > Guam > Guam (13N144E0000)", - "OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Guam > Guam (13N144E0000)", - "OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Rota Island > Rota Island ( Luta ) (14N145E0007)", - "OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Saipan Island > Saipan Island (15N145E0002)", - "OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Tinian Island Reefs > Tinian Island (14N145E0005)", - "OCEAN > PACIFIC OCEAN > WESTERN PACIFIC OCEAN > MICRONESIA > GUAM", - "NW Pacific (limit-180)", - "CNMI", - "CRED", - "CREP", - "Commonwealth of the Northern Mariana Islands", - "Coral Reef Ecosystem Division", - "Coral Reef Ecosystem Program", - "ESD", - "Ecosystem Sciences Division", - "Guam", - "Mariana Archipelago", - "Mariana Islands", - "Marianas", - "PIFSC", - "Pacific Islands Fisheries Science Center", - "DOC/NOAA/NMFS/PIFSC > Pacific Islands Fisheries Science Center, National Marine Fisheries Service, NOAA, U.S. Department of Commerce", - "PIFSC Publication" - ], - "landingPage": "https://www.fisheries.noaa.gov/inport/item/79227", - "language": [], - "license": "https://creativecommons.org/publicdomain/zero/1.0/", - "modified": "2026-01-01T00:00:00.000+00:00", - "publisher": { - "@type": "org:Organization", - "name": "Pacific Islands Fisheries Science Center" - }, - "rights": "otherRestrictions, unclassified", - "spatial": "145.85,13.2,144.6,15.35", - "temporal": "2011-04-06T00:00:00+00:00/2022-06-01T00:00:00+00:00", - "theme": [ - "geospatial" - ], - "title": "Reef Fish and Coral Traits, as well as Disturbance Exposure (Heat and Cyclone) of Coral Reefs in Guam and the CNMI in 2011 and 2022" - }, - "description": "This metadata record describes multiple datasets including traits (reef fish and coral) as well as disturbance exposure (heat and tropical cyclone) of coral reef ecosystems in Guam and the CNMI in 2011 and 2022. Trait values were inferred from online databases, scientific papers, and gaps were filled in by experts. Environmental disturbance data were generated by scientists of the Ecosystem Sciences Division (ESD) of the Pacific Islands Fisheries Science Center (PIFSC). For disturbance exposure, site-level heat stress and cyclone exposure data was generated for 2011 and 2022. These data were derived from NOAA Coral Reef Watch CoralTemp v3.1 daily SST (1985–present) and IBTrACS v4 (1950–2022). Both trait and disturbance exposure datasets described in this metadata record were used with the already archived Mariana Archipelago RAMP (MARAMP) and the National Coral Reef Monitoring Program (NCRMP) data, to generate functional trait-based diversity indices, providing another aspect of reef resilience.\n\nThis project was funded by CRCP Project #36143 titled \"Estimating functional diversity and redundancy of reef communities to inform resilience-based management in the Marianas\". \nLink to publication will be provided once published.", - "distribution_titles": [ - "ESD_FISHTRAIT_MARIAN", - "GCMD Keyword Forum Page", - "Full Metadata Record" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/bbcaa7b7-67e6-4a1a-a7b6-64fb207440d0", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/bbcaa7b7-67e6-4a1a-a7b6-64fb207440d0/raw", - "harvest_record_transformed": "https://catalog.data.gov/harvest_record/bbcaa7b7-67e6-4a1a-a7b6-64fb207440d0/transformed", - "has_download": false, - "has_spatial": true, - "identifier": "https://data.noaa.gov/waf/NOAA/nmfs/pifsc/iso/xml/79227.xml", - "keyword": [ - "DOC/NOAA/NMFS/PIFSC/ESD > Ecosystem Sciences Division, Pacific Islands Fisheries Science Center, National Marine Fisheries Service, NOAA, U.S. Department of Commerce", - "EARTH SCIENCE > AGRICULTURE > ANIMAL SCIENCE > ANIMAL ECOLOGY AND BEHAVIOR", - "EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC PRESSURE > ANTICYCLONES/CYCLONES", - "EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > MARINE ECOSYSTEMS > BENTHIC", - "EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > MARINE ECOSYSTEMS > REEF > CORAL REEF", - "EARTH SCIENCE > CLIMATE INDICATORS > ATMOSPHERIC/OCEAN INDICATORS > SEA SURFACE TEMPERATURE INDICES", - "36143", - "Estimating functional diversity and redundancy of reef communities to inform resilience-based management in the Marianas", - "Numeric Data Sets > Biology", - "Numeric Data Sets > Oceanography", - "EARTH SCIENCE > Biosphere > Aquatic Habitat > Reef Habitat", - "EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment", - "EARTH SCIENCE > Oceans > Coastal Processes > Coral Reefs", - "EARTH SCIENCE > Oceans > Marine Biology > Coral", - "EARTH SCIENCE > Oceans > Marine Biology > Coral Communities", - "EARTH SCIENCE > Oceans > Marine Biology > Fish", - "EARTH SCIENCE > Oceans > Ocean Temperature > Sea Surface Temperature", - "CORAL REEF", - "CORAL SPECIES", - "FISH - CORAL REEF", - "FISH SPECIES", - "HABITAT - BENTHIC", - "Tropical Cyclones", - "WATER TEMPERATURE", - "derived products", - "laboratory analysis", - "CORAL REEF STUDIES", - "Coral Reef Conservation Program", - "National Coral Reef Monitoring Program", - "Pacific Reef and Assessment Monitoring Program", - "US DOC; NOAA; NMFS; Pacific Islands Fisheries Science Center; Ecosystem Sciences Division", - "COUNTRY/TERRITORY > Northern Mariana Islands > Rota > Rota Island ( Luta ) (14N145E0007)", - "COUNTRY/TERRITORY > Northern Mariana Islands > Saipan > Saipan Island (15N145E0002)", - "COUNTRY/TERRITORY > Northern Mariana Islands > Tinian > Tinian Island (14N145E0005)", - "COUNTRY/TERRITORY > United States of America > Guam > Guam (13N144E0000)", - "OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Guam > Guam (13N144E0000)", - "OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Rota Island > Rota Island ( Luta ) (14N145E0007)", - "OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Saipan Island > Saipan Island (15N145E0002)", - "OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Tinian Island Reefs > Tinian Island (14N145E0005)", - "OCEAN > PACIFIC OCEAN > WESTERN PACIFIC OCEAN > MICRONESIA > GUAM", - "NW Pacific (limit-180)", - "CNMI", - "CRED", - "CREP", - "Commonwealth of the Northern Mariana Islands", - "Coral Reef Ecosystem Division", - "Coral Reef Ecosystem Program", - "ESD", - "Ecosystem Sciences Division", - "Guam", - "Mariana Archipelago", - "Mariana Islands", - "Marianas", - "PIFSC", - "Pacific Islands Fisheries Science Center", - "DOC/NOAA/NMFS/PIFSC > Pacific Islands Fisheries Science Center, National Marine Fisheries Service, NOAA, U.S. Department of Commerce", - "PIFSC Publication" - ], - "last_harvested_date": "2026-09-29T22:46:48.932365", - "organization": { - "aliases": [ - "" - ], - "code_repo_exempt": false, - "code_repo_url": null, - "description": null, - "id": "5f4f1195-e770-4a2a-8f75-195cd98860ce", - "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png", - "name": "National Oceanic and Atmospheric Administration, Department of Commerce", - "organization_type": "Federal Government", - "slug": "noaa" - }, - "parent_identifier": null, - "popularity": 0, - "publisher": "Pacific Islands Fisheries Science Center", - "slug": "reef-fish-and-coral-traits-as-well-as-disturbance-exposure-heat-and-cyclone-of-coral--2022", - "spatial_centroid": { - "lat": 14.059999999999999, - "lon": 145.35 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - 145.85, - 13.2 - ], - [ - 145.85, - 15.35 - ], - [ - 144.6, - 15.35 - ], - [ - 144.6, - 13.2 - ], - [ - 145.85, - 13.2 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Reef Fish and Coral Traits, as well as Disturbance Exposure (Heat and Cyclone) of Coral Reefs in Guam and the CNMI in 2011 and 2022", - "type": "dataset" - }, - { - "_score": 9.36532, - "_sort": [ - 1790722007003, - 9.36532, - 0, - "568dfc80-0faf-4183-998b-bf8dc8f7b763" - ], - "access_level": "non-public", - "dcat": { - "@type": "dcat:Dataset", - "accessLevel": "non-public", - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Barkley, Hannah C", - "hasEmail": "mailto:hannah.barkley@noaa.gov" - }, - "describedByType": "application/octet-stream", - "description": "The calcification rate data described here are derived from Calcification Accretion Units (CAUs) that were deployed and retrieved at long-term climate monitoring sites during NOAA Pacific Islands Fisheries Science Center (PIFSC), Ecosystem Sciences Division (ESD) led National Coral Reef Monitoring Program (NCRMP) missions across the Pacific Remote Island Regions in 2014, 2015, 2017, 2018, and 2023 as well as pre-NCRMP missions in 2010, 2011, and 2012. CAUs are PVC settlement plates that facilitate the recruitment and colonization of crustose coralline algae, hard corals, and other reef calcifiers. Laboratory experiments show that CCA and coral calcification rates are strongly correlated with seawater chemistry, and shifts in carbonate chemistry conditions due to ocean acidification could lead to reduced calcification and accretion rates and ecological phase shifts in coral reef communities.\n\nCoral reef calcium carbonate accretion rates can be estimated by measuring the change in weight of the CAUs between deployment and retrieval. Monitoring net accretion over successive deployments allows for the detection of changes in reef calcification rates over time. Five units were deployed on the seafloor at each CAU site for 3 years in 2015 and 5 years in 2018. The number of processed CAUs for a site may be less than the number deployed, either because the units were lost or damaged at sea and therefore not recovered, or in rare instances, due to errors during laboratory processing.\n\nThis study provides information about spatial and temporal patterns of reef carbonate calcification and accretion rates and serves as a basis for detecting changes associated with changing seawater chemistry due to ocean acidification. These data can also be used in comparative analyses across natural gradients, thereby assisting efforts to determine whether key reef-building taxa can acclimatize to changing oceanographic environments. These data will have immediate, direct impacts on predictions of reef resilience in a higher carbon dioxide (CO2) world and on the design of reef management strategies.", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://accession.nodc.noaa.gov/0137093", - "describedByType": "application/octet-stream", - "description": "CAU unit recoveries collected across the Pacific Remote Island Areas (Baker, Howland, Jarvis, Johnston, Kingman, Palmyra) by the PIFSC Ecosystem Sciences Division during pre-NCRMP mission in 2012 (HA1201). These CAU units were deployed during pre-NCRMP missions in 2010 (HA1001). Data include calcification rates per CAU unit.", - "mediaType": "text/html", - "title": "ESD_NCRMP_CAU_2012_PRIAs.csv" - }, - { - "@type": "dcat:Distribution", - "accessURL": "https://accession.nodc.noaa.gov/0175166", - "describedByType": "application/octet-stream", - "description": "CAU unit recoveries collected across the Pacific Remote Island Areas (Wake) by the PIFSC Ecosystem Sciences Division during MARAMP 2017 (HA1701). These CAU units were deployed during MARAMP 2014 (HA1401). Data include calcification rates per CAU unit.", - "mediaType": "text/html", - "title": "ESD_NCRMP_CAU_2017_PRIAs.csv" - }, - { - "@type": "dcat:Distribution", - "accessURL": "https://accession.nodc.noaa.gov/0231439", - "describedByType": "application/octet-stream", - "description": "CAU unit recoveries collected across the Pacific Remote Island Areas (Baker, Howland, and Jarvis Islands, Kingman Reef, and Palmyra atolls) by the PIFSC Ecosystem Sciences Division during ASRAMP 2018 (HA1801). These CAU units were deployed during ASRAMP 2015 (HA1501), with the exception of one CAU unit from Jarvis Island that was deployed during pre-NCRMP mission in 2012 (HA1201). Data include calcification rates per CAU unit.", - "mediaType": "text/html", - "title": "ESD_NCRMP_CAU_2018_PRIAs.csv" - }, - { - "@type": "dcat:Distribution", - "accessURL": "https://accession.nodc.noaa.gov/0159156", - "describedByType": "application/octet-stream", - "description": "CAU unit recoveries collected across the Pacific Remote Island Areas (Baker, Howland, Jarvis, Johnston, Kingman, Palmyra) by the PIFSC Ecosystem Sciences Division during ASRAMP 2015 (HA1501). These CAU units were deployed during pre-NCRMP mission in 2012 (HA1201). 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Data include calcification rates per CAU unit.", - "mediaType": "text/html", - "title": "ESD_NCRMP_CAU_2014_PRIAs.csv" - }, - { - "@type": "dcat:Distribution", - "accessURL": "https://accession.nodc.noaa.gov/0318706", - "describedByType": "application/octet-stream", - "description": "Quality control report generated for recovered CAU data from sites across the Pacific Remote Island Areas (Baker, Howland) by the PIFSC Ecosystem Sciences Division during ASRAMP 2023 (RA2301).", - "mediaType": "text/html", - "title": "ESD_NCRMP_CAU_2023_PRIAs_QC.pdf" - }, - { - "@type": "dcat:Distribution", - "accessURL": "https://forum.earthdata.nasa.gov/app.php/tag/GCMD%2BKeywords", - "describedByType": "application/octet-stream", - "description": "Global Change Master Directory (GCMD). 2026. GCMD Keywords, Version 24. Greenbelt, MD: Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA). URL (GCMD Keyword Forum Page): https://forum.earthdata.nasa.gov/app.php/tag/GCMD+Keywords", - "mediaType": "text/html", - "title": "GCMD Keyword Forum Page" - }, - { - "@type": "dcat:Distribution", - "accessURL": "https://www.fisheries.noaa.gov/inport/item/36069", - "describedByType": "application/octet-stream", - "description": "View the complete metadata record on InPort for more information about this dataset.", - "mediaType": "text/html", - "title": "Full Metadata Record" - } - ], - "identifier": "https://data.noaa.gov/waf/NOAA/nmfs/pifsc/iso/xml/36069.xml", - "issued": "2016-01-01T00:00:00.000+00:00", - "keyword": [ - "DOC/NOAA/NMFS/PIFSC/ESD > Ecosystem Sciences Division, Pacific Islands Fisheries Science Center, National Marine Fisheries Service, NOAA, U.S. Department of Commerce", - "EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > MARINE ECOSYSTEMS > BENTHIC", - "EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > MARINE ECOSYSTEMS > REEF > CORAL REEF", - "OCEAN > PACIFIC OCEAN > CENTRAL PACIFIC OCEAN > BAKER ISLAND", - "OCEAN > PACIFIC OCEAN > CENTRAL PACIFIC OCEAN > HOWLAND ISLAND", - "OCEAN > PACIFIC OCEAN > CENTRAL PACIFIC OCEAN > JARVIS ISLAND", - "OCEAN > PACIFIC OCEAN > CENTRAL PACIFIC OCEAN > JOHNSTON ATOLL", - "OCEAN > PACIFIC OCEAN > CENTRAL PACIFIC OCEAN > KINGMAN REEF", - "OCEAN > PACIFIC OCEAN > CENTRAL PACIFIC OCEAN > PALMYRA ATOLL", - "1221", - "409", - "587", - "743", - "C204 Pacific Reef Assessment and Monitoring Program (Pacific RAMP): Biennial monitoring for the US Pacific Islands and Atolls", - "National Coral Reef Monitoring Program", - "Ocean Acidification - Quantification of Calcification and Accretion Rates of Corals and Crustose Coralline Algae across the Pacific Ocean", - "Pacific Reef Assessment and Monitoring Program: Monitoring coral reef ecosystems of the US Pacific Islands and Atolls", - "Numeric Data Sets > Calcification Rate", - "EARTH SCIENCE > Biosphere > Aquatic Habitat > Reef Habitat", - "EARTH SCIENCE > Biosphere > Vegetation > Algae > Algal Cover", - "EARTH SCIENCE > Biosphere > Vegetation > Algae > Algal Growth > Calcification Rate", - "EARTH SCIENCE > Biosphere > Vegetation > Algae > Calcareous Macroalgae", - "EARTH SCIENCE > Biosphere > Vegetation > Algae > Crustose Coralline Algae", - "EARTH SCIENCE > Biosphere > Vegetation > Algae > Encrusting Macroalgae", - "EARTH SCIENCE > Biosphere > Vegetation > Algae > Fleshy Macroalgae", - "EARTH SCIENCE > Biosphere > Vegetation > Algae > Reef Monitoring and Assessment", - "EARTH SCIENCE > Biosphere > Vegetation > Algae > Reef Monitoring and Assessment > Calcification Accretion Unit (CAU)", - "EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment", - "EARTH SCIENCE > Oceans > Coastal Processes > Coral Reefs", - "EARTH SCIENCE > Oceans > Ocean Chemistry > Calcification", - "EARTH SCIENCE > Oceans > Ocean Chemistry > Carbonate Chemistry", - "EARTH SCIENCE > Oceans > Ocean Chemistry > Ocean Acidification", - "CALCIFICATION", - "in situ", - "laboratory analyses", - "CORAL REEF STUDIES", - "Coral Reef Conservation Program", - "National Coral Reef Monitoring Program", - "Pacific Reef and Assessment Monitoring Program", - "US DOC; NOAA; Office of Oceanic and Atmospheric Research; Ocean Acidification Program", - "US DOC; NOAA; NMFS; Pacific Islands Fisheries Science Center; Ecosystem Sciences Division", - "COUNTRY/TERRITORY > United States of America > USA Minor Outlying Islands > Baker Island (00N176W0001)", - "COUNTRY/TERRITORY > United States of America > USA Minor Outlying Islands > Howland Island (00S176W0001)", - "COUNTRY/TERRITORY > United States of America > USA Minor Outlying Islands > Jarvis Island (00S160W0001)", - "COUNTRY/TERRITORY > United States of America > USA Minor Outlying Islands > Johnston Atoll (16N169W0001)", - "COUNTRY/TERRITORY > United States of America > USA Minor Outlying Islands > Kingman Reef (06N162W0001)", - "COUNTRY/TERRITORY > United States of America > USA Minor Outlying Islands > Palmyra Atoll (05N162W0001)", - "COUNTRY/TERRITORY > United States of America > USA Minor Outlying Islands > Wake Atoll (19N167E0001)", - "OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Baker Island > Baker Island (00N176W0001)", - "OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Howland Island > Howland Island (00S176W0001)", - "OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Johnston Atoll > Johnston Atoll (16N169W0001)", - "OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Line Islands > Jarvis Island (00S160W0001)", - "OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Line Islands > Kingman Reef (06N162W0001)", - "OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Line Islands > Palmyra Atoll (05N162W0001)", - "OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Wake Atoll > Wake Atoll (19N167E0001)", - "Central Pacific Ocean", - "Equatorial Pacific Ocean", - "Pacific Remote Islands Marine National Monument", - "HI'IALAKAI", - "RAINIER", - "ASRAMP", - "American Samoa Reef Assessment and Monitoring Program", - "CRED", - "CREP", - "Calcification Plate", - "Coral Reef Ecosystem Division", - "Coral Reef Ecosystem Program", - "ESD", - "Ecosystem Sciences Division", - "NCRMP", - "Ocean Acidification", - "PIFSC", - "Pacific Islands Fisheries Science Center", - "RAMP", - "Reef Assessment and Monitoring Program", - "Settlement Plate", - "calcification accretion unit", - "triennial", - "PRIA", - "PRIMNM", - "Pacific Remote Island Areas", - "Calcification Accretion Unit (CAU)", - "DOC/NOAA/NMFS/PIFSC > Pacific Islands Fisheries Science Center, National Marine Fisheries Service, NOAA, U.S. Department of Commerce", - "Pacific Remote Island Areas" - ], - "landingPage": "https://www.fisheries.noaa.gov/inport/item/36069", - "language": [], - "license": "https://creativecommons.org/publicdomain/zero/1.0/", - "modified": "2026-01-01T00:00:00.000+00:00", - "publisher": { - "@type": "org:Organization", - "name": "Pacific Islands Fisheries Science Center" - }, - "rights": "otherRestrictions, unclassified", - "spatial": "-159.9788,-0.38235459,-176.6239,16.7633668", - "temporal": "2012-03-02T00:00:00+00:00/2015-04-27T00:00:00+00:00", - "theme": [ - "geospatial" - ], - "title": "National Coral Reef Monitoring Program: Calcification Rates of Crustose Coralline Algae Derived from Calcification Accretion Units (CAUs) Deployed across the Pacific Remote Island Areas from 2010 to 2023" - }, - "description": "The calcification rate data described here are derived from Calcification Accretion Units (CAUs) that were deployed and retrieved at long-term climate monitoring sites during NOAA Pacific Islands Fisheries Science Center (PIFSC), Ecosystem Sciences Division (ESD) led National Coral Reef Monitoring Program (NCRMP) missions across the Pacific Remote Island Regions in 2014, 2015, 2017, 2018, and 2023 as well as pre-NCRMP missions in 2010, 2011, and 2012. CAUs are PVC settlement plates that facilitate the recruitment and colonization of crustose coralline algae, hard corals, and other reef calcifiers. Laboratory experiments show that CCA and coral calcification rates are strongly correlated with seawater chemistry, and shifts in carbonate chemistry conditions due to ocean acidification could lead to reduced calcification and accretion rates and ecological phase shifts in coral reef communities.\n\nCoral reef calcium carbonate accretion rates can be estimated by measuring the change in weight of the CAUs between deployment and retrieval. Monitoring net accretion over successive deployments allows for the detection of changes in reef calcification rates over time. Five units were deployed on the seafloor at each CAU site for 3 years in 2015 and 5 years in 2018. The number of processed CAUs for a site may be less than the number deployed, either because the units were lost or damaged at sea and therefore not recovered, or in rare instances, due to errors during laboratory processing.\n\nThis study provides information about spatial and temporal patterns of reef carbonate calcification and accretion rates and serves as a basis for detecting changes associated with changing seawater chemistry due to ocean acidification. These data can also be used in comparative analyses across natural gradients, thereby assisting efforts to determine whether key reef-building taxa can acclimatize to changing oceanographic environments. 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The BEPS is a minimum threshold of energy performance that will be no lower than the local median?ENERGY STAR?score by property type (or equivalent metric). The standards were created to drive energy performance in existing buildings to help meet the energy and climate goals of the?Sustainable DC?plan — to reduce greenhouse gas emissions and energy consumption by 50% by 2032. DOEE established the first set of Standards on January 1, 2021. Standards will then be set every 6 years, creating BEPS Periods (BEPS Period 1, BEPS Period 2, etc.). The 2021 Building Energy Performance Standards and a Guide to the 2021 BEPS are available for viewing on DOEE’s website.</span></p><p><span>To improve transparency and help building owners understand how their building performs relative to the BEPS, DOEE is publishing this BEPS Disclosure that compares a building’s benchmarking data with the BEPS and provides an estimate of the building’s distance from the standard and estimated performance requirement.</span></p><p><span>Please note that this dataset is based on information currently available to DOEE using calendar year 2019 benchmarking data provided by the building owner. Some buildings are still being evaluated and therefore have been designated as “Under Review” in this dataset. Building owners that believe their 2019 calendar year data is incorrect should contact the Benchmarking Help Center (info.benchmark@dc.gov). Additionally, build + "harvest_record": "https://catalog.data.gov/harvest_record/73e60f2d-38