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EPA conducted a probabilistic survey at 64 stations from linear reef habitat along the southern coastline of Puerto Rico to characterize the regional condition of coral reef inhabitants. The probabilistic design was the first step toward establishing a long-term monitoring program for biological water quality standards (such as biocriteria) in Puerto Rico using these indicators. The target population was limited to coral reef and hardbottom substrate within 1.5 km o f shore and between 2-12 m depth. Divers dropped a buoy at the appropriate station coordinates and assessed the reef resources at the best available habitat within a 20 m radius of the buoy. If suitable habitat was not found, the next location on the predetermined site list was chosen. This dataset is associated with the following publication: Fisher, W., D. Vivian, J. Campbell, C. Lobue, R. Hemmer, S. Wilkinson, P. Harris, D. Santavy, M. Parsons, P. Bradley, A. Humphrey, L. Oliver, and L. Harwell. Biological Status Assessment of Coral Reefs in Southern Puerto Rico: Supporting Coral Reef Protection Under the U.S. Clean Water Act.. Coastal Management. Taylor and Francis, Philadelphia, PA, USA, 47(5): 429-452, (2019).

After over two years of public reporting, the State Profile Report will no longer be produced and distributed after February 2023. The final release was on February 23, 2023. We want to thank everyone who contributed to the design, production, and review of this report and we hope that it provided insight into the data trends throughout the COVID-19 pandemic. Data about COVID-19 will continue to be updated at CDC’s COVID Data Tracker.

The State Profile Report (SPR) is generated by the Data Strategy and Execution Workgroup in the Joint Coordination Cell, in collaboration with the White House. It is managed by an interagency team with representatives from multiple agencies and offices (including the United States Department of Health and Human Services (HHS), the Centers for Disease Control and Prevention, the HHS Assistant Secretary for Preparedness and Response, and the Indian Health Service). The SPR provides easily interpretable information on key indicators for each state, down to the county level.

It is a weekly snapshot in time that:

• Focuses on recent outcomes in the last seven days and changes relative to the month prior
• Provides additional contextual information at the county level for each state, and includes national level information
• Supports rapid visual interpretation of results with color thresholds

The Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) comprehensively analyzes possible pathways for Puerto Rico to achieve its renewable energy goals while incorporating stakeholder perspectives and advancing energy resilience for all Puerto Ricans. PR100 is a wide-ranging and in-depth examination of Puerto Rico's energy system investment options. The findings are the culmination of two years of stakeholder engagement, scenario modeling, and impact analysis. The PR100 report and Implementation Roadmap contain a range of results and actions that reflect Puerto Rico's priorities around energy justice, resilience, and reliability. Led by the U.S. Department of Energy's Grid Deployment Office with funding from the Federal Emergency Management Agency, the PR100 study leveraged and integrated dozens of best-in-class models and in-depth analyses from researchers across six national laboratories: National Renewable Energy Laboratory (which led the study), along with Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory, and Sandia National Laboratories (which conducted the study). For more information, please see the "PR100 Project Website" resource below.

These data were automated to provide an accurate high-resolution historical shoreline of Eastern Puerto Rico, PR suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies which were based on an office interpretation of imagery and/or field survey. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://www.fisheries.noaa.gov/inport/item/39808

To support high spatial- and temporal-resolution land surface modeling, this dataset provides 3-hourly time step historic weather forcing at 1-km spatial resolution for Puerto Rico and surrounding islands. The latest Daymet V4 data provides gridded historic daily weather observation at 1-km spatial resolution from 1950 to present. Using sub-daily temporal information from two meteorological reanalysis datasets (GSWP3 and NARR), Daymet was further temporally downscaled to 3-hourly time steps and provided in the format required for land surface model simulations. The process of temporal downscaling preserves the relative magnitude in each sub-daily time step from GSWP3 and NARR while maintaining the total and average values from Daymet at each day. These result in two blended datasets: 1950-2014 Daymet-GSWP3 and 1979-2019 Daymet-NARR. Available variables include surface air temperature, precipitation, specific humidity, shortwave and longwave radiation, wind speed, and pressure. These data can be used as a high-resolution meteorological forcing dataset to support high-resolution land surface modeling where accurate meteorological forcing datasets built from historic observations and/or reanalysis datasets are desirable.

Data provided in this collection were gathered around Puerto Rico as part of NCCOS-led missions in collaboration with partners at U.S. Fish and Wildlife Service, University of Puerto Rico Department of Marine Sciences, HJR Reefscaping, and University of the Virgin Islands.

In 2014 the Belt Transect method was used to conduct fish surveys in Puerto Rico as part of the ongoing National Coral Reef Monitoring Program (NCRMP). The Belt Transect method collects and reports information on fish species composition, density, size, abundance and derived metrics (e.g., species richness, diversity). Surveys were concurrent with and along the same transect as the Line Point-Intercept (LPI) benthic survey. Starting in 2016 fish data were collected using the stationary point count method. This method collects and reports information on fish species composition, density, size structure, abundance and derived metrics (e.g., species richness, diversity).

This summary describes the programs and services VA provided in Puerto Rico in fiscal year 2015.

The FY2017 State Summaries provide an overview of benefits, services, demographics and population of Veterans analyzed by state.

The National Renewable Energy Laboratory's (NREL) PV Rooftop Database for Puerto Rico (PVRDB-PR) is a lidar-derived, geospatially-resolved dataset of suitable roof surfaces and their PV technical potential for virtually all buildings in Puerto Rico. The dataset can be downloaded at the AWS S3 explorer page. The GitHub documentation page provides a description of the dataset with methods and assumptions. The Puerto Rico Solar-For-All dataset provides Census Tract level estimates of residential low-to-moderate income (LMI) PV rooftop technical potential as well as solar electric bill savings potential for LMI communities at the municipality level.

The FY2016 State Summaries provide an overview of benefits, services, demographics and population of Veterans analyzed by state.

This is a summary of the programs and services provided by VA in Puerto Rico in fiscal year 2014.

These data provide an accurate high-resolution shoreline compiled from imagery of East Coast of Puerto Rico, Pta Iglesia to Pta Toro, PR . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://inport.nmfs.noaa.gov/inport/item/39808

This data release presents the post-processed Global Navigation Satellite System (GNSS) ground-survey data acquired during the installation of a camera system at Tres Palmas, Rincón, Puerto Rico (PR). The data contains topographic survey data collected during the installation of the camera. Data were collected on foot, by a person equipped with a GNSS antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ). The GNSS measurements were made using Post-Processed Kinematic (PPK) corrections referenced to a temporary base station located approximately 250 meters from the study area.

The base Land Cover data layer for the Commonwealth of Puerto Rico was produced by the International Institute of Tropical Forestry(IITF) and crosswalked to NLCD classes, with additional crop type modeling conducted by the National Oceanic and Atmospheric Administration (NOAA). This original base data layer is available at http://fsgeodata.fs.fed.us/rastergateway/ An additional link for the publication associated with this work is http://tropicalforestry.net/Members/ehelmer/caribbean-vegetation-and-land-cover The full reference for this work is Kennaway, T., and E. H. Helmer. 2007. The forest types and ages cleared for land development in Puerto Rico. GIScience and Remote Sensing 44:356-382. NLCD data layers are made through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Adm ...

The U.S. Geological Survey (USGS), in cooperation with the Puerto Rico Environmental Quality Board, has compiled a series of geospatial datasets for Puerto Rico to be implemented into the USGS StreamStats application (https://streamstats.usgs.gov/ss/). These geospatial datasets, along with basin characteristics datasets for Puerto Rico published as a separate USGS data release (https://doi.org/10.5066/P9HK9SSQ), were used to delineate watersheds and develop the peak-flow and low-flow regression equations used by StreamStats. The geospatial dataset described herein are the digital elevation model rasters from NED, at a 10-m resolution, elevations in centimeters. Data are partitioned into four TIFF files, one for each of the four 8-digit Hydrologic Unit Code (HUC) areas for Puerto Rico: 21010002, 21010003, 21010004, and 21010005.

Registro de Hospitales y Otras Facilidades de Salud de Puerto RicoLista de hospitales en Puerto Rico que están acreditados por la Secretaría Auxiliar para Reglamentación y Acreditación de Facilidades de Salud (SARAFS) del Departamento de Salud de Puerto Rico. Data: data.pr.gov

Underserved communities, especially those in coastal areas in Puerto Rico, face significant threats from natural hazards such as hurricanes and rising sea levels. Limited funding hinders the investment in costly mitigation measures, increasing exposure to natural disasters. Providing coastal resources and data products through effective communication mechanisms is fundamental to improving the well-being of these underserved coastal communities. The overall objectives of the pilot effort to engage and connect with underrepresented coastal communities in Puerto Rico were the following: (1) compile a comprehensive database of the projects and resources relevant to natural hazards in Puerto Rico; (2) foster connections with Puerto Rican interested parties to better understand their priorities regarding coastal hazards and provide them with pertinent U.S. Geological Survey (USGS) resources; and (3) identify knowledge gaps to guide future USGS projects in Puerto Rico. To address these objectives, the research team held a virtual internal meeting amongst USGS colleagues (organized with a professional facilitator) to identify and gather information on existing USGS data, knowledge, and tools available for natural hazards and resources in Puerto Rico. The goals of the meeting were to: (1) exchange knowledge among colleagues, (2) broaden the network of participants, (3) foster potential collaborative relationships with researchers engaged in USGS hazards projects in Puerto Rico, and (4) document all the research taking place in Puerto Rico related to natural hazards and resources. The result was a database of USGS natural hazards projects being conducted or recently completed in Puerto Rico. For further information about this data, refer to the associated journal article (Torres-García and others, 2024).

The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000 scale and exists at that scale for the whole country. High resolution NHD adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Like the 1:100,000-scale NHD, high resolution NHD contains reach codes for networked features and isolated lakes, flow direction, names, stream level, and centerline representations for areal water bodies. Reaches are also defined to represent waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria set out by the Federal Geographic Data Committee.

Physical factors, such as the slope of the land, the texture of the soil, and the precipitation regime influence erosion in an area. Parts of Puerto Rico are very steep and erosion-prone. In addition, the nature of the soil and intense rainfall events promote severe erosion in these areas. Erosion can be extreme in exposed areas (cleared for a road or residential construction, or where soil is exposed due to cropping patterns or agricultural cycle.)