Comprehensive dataset of 286 Islands in Virginia, United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

This dataset is a compilation of completed, in progress, and planned restoration projects identified in the study area by the Deepwater Horizon (DWH) Project Tracker as of March 2022. The goal of compiling projects and information was to identify target resources and impacts of these projects in the study area. Projects were screened for action types, completion year, and resources intended to benefit from restoration in barrier island and shoreline systems. In addition, system components of structure and function were identified. The potential for geomorphological impacts was categorized among different types of projects.

Comprehensive dataset of 343 Islands in Turkey as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Anchialine pools are brackish water systems fed by subsurface groundwater (freshwater) and tides (sea water), with no surface connection to the ocean. Although anchialine pools occur around the world, these habitats tend to be small, isolated, and threatened by human development and introduced nonnative species. These pools provide habitat for rare invertebrate species including shrimp, snails, and odonates.The Pacific Island Network (PACN) is monitoring these unique ecosystems to determine status and trends over time. This will provide managers with information to determine how to best protect these unique habitats and the species they support. This dataset contains pilot data collected during the development of the anchialine pool monitoring protocol. Park anchialine pool monitoring data collected by the resource management staff at Kaloko Honokahau National Historical Park are also included in the database. Each sampling event in the database is associated with a project. Those labeled as I&M Pilot Data are data associated with the I&M Monitoring Protocol. This dataset also includes water quality data imported from the PACN water quality monitoring protocol, the project is I&M Water Quality Monitoring Data. Information on the PACN water quality monitoring protocol can be found at https://irma.nps.gov/App/Reference/Profile/2166407. This data went through a vigorous data certification process, including verification and validation of the data. All others are data collected by park staff or outside researchers. The data verification and validation of this data is unknown.

SPACK is a spatio-temporal database dedicated to whaling, sealing and fishing history. It aims to gather miscellaneous and scattered sources about whaling, sealing and fishing voyages that visited Saint-Paul, Amsterdam, Crozet and Kerguelen Islands between 1780’s and 1930’s.

SPACK has been defined and populated during a PhD thesis in history. The main purpose is to assess the attendance of whaling, sealing and fishing ships around the French Southern Islands from the late 18th century. The goal is also to shed light on the issues arising from the first public policies for managing natural resources once French sovereignty was affirmed in the late 19th.

The data collected in SPACK are stored in the object-relational database, PostgreSQL, plus its spatial extension PostGIS. This repository can be used to create a new instance of the SPACK database. It contains 7 SQL files that represent the main tables of the SPACK model.

- attested_presence_areas: this table shows the dates on which the vessel is present in the area.

- code_areas: this table indicates the codes used to identify each covered area.

- code_sealing_gangs: this table shows the code used to indicate when a gang of hunters has been dropped off or relieved on shore by the ship.

- natural_resources: this table provides the codes used to classify vessel activity by 'area'.

- shipment_origin: this table lists the codes for the main shipowner's geographical origin.

- stop_over_voyages: this table describes the date of arrival and departure by 'area'. It also indicates the degree of interpolation of the data, month or day.

- voyages_areas: this table contains a list of vessels involved in whaling, fishing and sealing activities that crossed Saint-Paul, Amsterdam, Crozet or/and Kerguelen islands. It provides information such as vessel name, rig type, tonnage, port, shipment origin, natural resource exploited, agent, dates of presence, primary and secondary sources.

The main entity of this database is a ship attached to a voyage and a geographical area. This entity is described by a set of properties: ship’s and master’s names, geographical origin, shipowner, port, arrival and departure dates. Those data are featured in the voyages_areas table. The database also provides other helpful information, such as the dates of attendance on the island, the type of natural resource exploited and the sources used to identify a voyage.

The SPACK database takes profit from the Whaling History Database (https://whalinghistory.org/). It does not contain any data imported from WHDB, but it is still possible to link the two sources. Indeed, the voyages_areas table stores the identifier used by the WHDB to describe each voyage.

The WHDB provides the vessel's location in lat/lon for several voyages. Those locations have been processed to populate the voyages_areas table and check when a voyage crossed a study area: Saint-Paul, Amsterdam, Crozet or Kerguelen Islands. However, no spatial information is saved in the SQL files. You can contact the authors if you want more information about the spatial analysis techniques used.

Comprehensive dataset of 205 Islands in Poland as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

To study how the phylogenetic composition of native island floras influences naturalized alien species richness, we assembled a dataset of 249 global islands from the global inventory of floras and traits (GIFT, Weigelt et al., 2020) and the Global Naturalized Alien Flora database (GloNAF, van Kleunen et al. 2019). The dataset contains naturalized and native species number, island area (km²) geological information from these sources. Additionally, we calculated three phylogenetic community metrics (Faith's PD, MPD and MNTD) using a global seed plant phylogeny (Smith and Brown, 2018) with different source pools, unstandardized Faith's PD with global island species pool, global island and mainland species pool and without missing species added to the phylogeny (pd, pd.matched), standardized measures with global island species pool and missing species added into the phylogeny (pd.ses, mpd.ses, mntd.ses), standardized measures with global island and mainland species pool and missing species...

The dataset includes data on all fur seals tagged at Macquarie Island since 1986. The dataset includes information on the sex and species of individuals, information on their reproductive histories, resight data and tagging history.

The file is the database kept by the Falkland Islands Public Work department with information on owners, addresses and type of transactions (lease, sale, mortgage, crown grant etc) occurred to land owned by the Falkland Island Government.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Other Collections. The data include parameters of others with a geographic location of Eastern Pacific Ocean. The time period coverage is from 47797 to 171 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

Abstract

Estache and Goicoechea present an infrastructure database that was assembled from multiple sources. Its main purposes are: (i) to provide a snapshot of the sector as of the end of 2004; and (ii) to facilitate quantitative analytical research on infrastructure sectors. The related working paper includes definitions, source information and the data available for 37 performance indicators that proxy access, affordability and quality of service (most recent data as of June 2005). Additionally, the database includes a snapshot of 15 reform indicators across infrastructure sectors.

This is a first attempt, since the effort made in the World Development Report 1994, at generating a database on infrastructure sectors and it needs to be recognized as such. This database is not a state of the art output—this is being worked on by sector experts on a different time table. The effort has however generated a significant amount of new information. The database already provides enough information to launch a much more quantitative debate on the state of infrastructure. But much more is needed and by circulating this information at this stage, we hope to be able to generate feedback and fill the major knowledge gaps and inconsistencies we have identified.

Geographic coverage

The database covers the following countries: - Afghanistan - Albania - Algeria - American Samoa - Andorra - Angola - Antigua and Barbuda - Argentina - Armenia - Aruba - Australia - Austria - Azerbaijan - Bahamas, The - Bahrain - Bangladesh - Barbados - Belarus - Belgium - Belize - Benin - Bermuda - Bhutan - Bolivia - Bosnia and Herzegovina - Botswana - Brazil - Brunei - Bulgaria - Burkina Faso - Burundi - Cambodia - Cameroon - Canada - Cape Verde - Cayman Islands - Central African Republic - Chad - Channel Islands - Chile - China - Colombia - Comoros - Congo, Dem. Rep. - Congo, Rep. - Costa Rica - Cote d'Ivoire - Croatia - Cuba - Cyprus - Czech Republic - Denmark - Djibouti - Dominica - Dominican Republic - Ecuador - Egypt, Arab Rep. - El Salvador - Equatorial Guinea - Eritrea - Estonia - Ethiopia - Faeroe Islands - Fiji - Finland - France - French Polynesia - Gabon - Gambia, The - Georgia - Germany - Ghana - Greece - Greenland - Grenada - Guam - Guatemala - Guinea - Guinea-Bissau - Guyana - Haiti - Honduras - Hong Kong, China - Hungary - Iceland - India - Indonesia - Iran, Islamic Rep. - Iraq - Ireland - Isle of Man - Israel - Italy - Jamaica - Japan - Jordan - Kazakhstan - Kenya - Kiribati - Korea, Dem. Rep. - Korea, Rep. - Kuwait - Kyrgyz Republic - Lao PDR - Latvia - Lebanon - Lesotho - Liberia - Libya - Liechtenstein - Lithuania - Luxembourg - Macao, China - Macedonia, FYR - Madagascar - Malawi - Malaysia - Maldives - Mali - Malta - Marshall Islands - Mauritania - Mauritius - Mayotte - Mexico - Micronesia, Fed. Sts. - Moldova - Monaco - Mongolia - Morocco - Mozambique - Myanmar - Namibia - Nepal - Netherlands - Netherlands Antilles - New Caledonia - New Zealand - Nicaragua - Niger - Nigeria - Northern Mariana Islands - Norway - Oman - Pakistan - Palau - Panama - Papua New Guinea - Paraguay - Peru - Philippines - Poland - Portugal - Puerto Rico - Qatar - Romania - Russian Federation - Rwanda - Samoa - San Marino - Sao Tome and Principe - Saudi Arabia - Senegal - Seychelles - Sierra Leone - Singapore - Slovak Republic - Slovenia - Solomon Islands - Somalia - South Africa - Spain - Sri Lanka - St. Kitts and Nevis - St. Lucia - St. Vincent and the Grenadines - Sudan - Suriname - Swaziland - Sweden - Switzerland - Syrian Arab Republic - Tajikistan - Tanzania - Thailand - Togo - Tonga - Trinidad and Tobago - Tunisia - Turkey - Turkmenistan - Uganda - Ukraine - United Arab Emirates - United Kingdom - United States - Uruguay - Uzbekistan - Vanuatu - Venezuela, RB - Vietnam - Virgin Islands (U.S.) - West Bank and Gaza - Yemen, Rep. - Yugoslavia, FR (Serbia/Montenegro) - Zambia - Zimbabwe

Kind of data

Aggregate data [agg]

Mode of data collection

Face-to-face [f2f]

Response rate

Sector Performance Indicators

Energy The energy sector is relatively well covered by the database, at least in terms of providing a relatively recent snapshot for the main policy areas. The best covered area is access where data are available for 2000 for about 61% of the 207 countries included in the database. The technical quality indicator is available for 60% of the countries, and at least one of the perceived quality indicators is available for 40% of the countries. Price information is available for about 41% of the countries, distinguishing between residential and non residential.

Water & Sanitation Because the sector is part of the Millennium Development Goals (MDGs), it enjoys a lot of effort on data generation in terms of the access rates. The WHO is the main engine behind this effort in collaboration with the multilateral and bilateral aid agencies. The coverage is actually quite high -some national, urban and rural information is available for 75 to 85% of the countries- but there are significant concerns among the research community about the fact that access rates have been measured without much consideration to the quality of access level. The data on technical quality are only available for 27% of the countries. There are data on perceived quality for roughly 39% of the countries but it cannot be used to qualify the information provided by the raw access rates (i.e. access 3 hours a day is not equivalent to access 24 hours a day).

Information and Communication Technology The ICT sector is probably the best covered among the infrastructure sub-sectors to a large extent thanks to the fact that the International Telecommunications Union (ITU) has taken on the responsibility to collect the data. ITU covers a wide spectrum of activity under the communications heading and its coverage ranges from 85 to 99% for all national access indicators. The information on prices needed to make assessments of affordability is also quite extensive since it covers roughly 85 to 95% of the 207 countries. With respect to quality, the coverage of technical indicators is over 88% while the information on perceived quality is only available for roughly 40% of the countries.

Transport The transport sector is possibly the least well covered in terms of the service orientation of infrastructure indicators. Regarding access, network density is the closest approximation to access to the service and is covered at a rate close to 90% for roads but only at a rate of 50% for rail. The relevant data on prices only cover about 30% of the sample for railways. Some type of technical quality information is available for 86% of the countries. Quality perception is only available for about 40% of the countries.

Institutional Reform Indicators

Electricity The data on electricity policy reform were collected from the following sources: ABS Electricity Deregulation Report (2004), AEI-Brookings telecommunications and electricity regulation database (2003), Bacon (1999), Estache and Gassner (2004), Estache, Trujillo, and Tovar de la Fe (2004), Global Regulatory Network Program (2004), Henisz et al. (2003), International Porwer Finance Review (2003-04), International Power and Utilities Finance Review (2004-05), Kikukawa (2004), Wallsten et al. (2004), World Bank Caribbean Infrastructure Assessment (2004), World Bank Global Energy Sector Reform in Developing Countries (1999), World Bank staff, and country regulators. The coverage for the three types of institutional indicators is quite good for the electricity sector. For regulatory institutions and private participation in generation and distribution, the coverage is about 80% of the 207 counties. It is somewhat lower on the market structure with only 58%.

Water & Sanitation The data on water policy reform were collected from the following sources: ABS Water and Waste Utilities of the World (2004), Asian Developing Bank (2000), Bayliss (2002), Benoit (2004), Budds and McGranahan (2003), Hall, Bayliss, and Lobina (2002), Hall and Lobina (2002), Hall, Lobina, and De La Mote (2002), Halpern (2002), Lobina (2001), World Bank Caribbean Infrastructure Assessment (2004), World Bank Sector Note on Water Supply and Sanitation for Infrastructure in EAP (2004), and World Bank staff. The coverage for institutional reforms in W&S is not as exhaustive as for the other utilities. Information on the regulatory institutions responsible for large utilities is available for about 67% of the countries. Ownership data are available for about 70% of the countries. There is no information on the market structure good enough to be reported here at this stage. In most countries small scale operators are important private actors but there is no systematic record of their existence. Most of the information available on their role and importance is only anecdotal.

Information and Communication Technology The report Trends in Telecommunications Reform from ITU (revised by World Bank staff) is the main source of information for this sector. The information on institutional reforms in the sector is however not as exhaustive as it is for its sector performance indicators. While the coverage on the regulatory institutions is 100%, it varies between 76 and 90% of the countries for more of the other indicators. Quite surprisingly also, in contrast to what is available for other sectors, it proved difficult to obtain data on the timing of reforms and of the creation of the regulatory agencies.

Transport Information on transport institutions and reforms is not systematically generated by any agency. Even though more data are needed to have a more comprenhensive picture of the transport sector, it was possible to collect data on railways policy reform from Janes World Railways (2003-04) and complement it with

Comprehensive dataset of 424 Islands in China as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

The Roads database includes an inventory of road assets (roadways, blocks, intersections, sidewalks, curbs) with a spatial representation and various attached information. Aggregate pavement-type road assets represent carriageways located in the public domain and which are part of the local or arterial road network. Aggregate pavements are represented by polygons that are aggregated by type of use. Among the information associated with a roadway-type object is the date of construction, the date of resurfacing, the date of survey, the date of survey, the materials of the pavement, the type of foundation, the presence of bicycle lane, use, etc. island-type road assets represent malls located in the public domain and which are juxtaposed to the local or arterial road network. The islands are represented by polygons that are differentiated by their configuration. Among the information associated with an island-type object is the date of construction, the date of survey, the materials of the block and the border, the presence of trees, the type of block, etc. intersection-type road assets represent the intersections of motorways located in the public domain and which are part of the local or arterial road network. Intersections are represented by polygons that are cut according to the number of traffic axes. Information associated with an intersecting object includes the construction date, resurfacing date, survey date, survey date, intersection materials, foundation type, bike lane presence, etc. sidewalk-type road assets represent sidewalks and curbs juxtaposed with roadways in the public domain that are part of the local or arterial road network. Sidewalks and curbs are represented by polygons differentiated by category and type. Among the information associated with a sidewalk-type object is the construction date, the survey date, the type of sidewalk and curb, the materials of the sidewalk, the border and the developed strip, the presence of trees, the presence of a projection, the presence of a bicycle path, the use, etc. zone-type road assets represent the regions located between other road assets and which do not not part of the local or arterial road network. The areas are represented by polygons. Among the information associated with a zone-type object is the type of zone, etc. The data is also available in separate sets on the portal to support several uses: - Roadway and intersection - Sidewalk and islet - Off-street zone - Sidewalk and block Warnings - The data released on road assets are those in the possession of the City's geomatics team and are not necessarily up to date throughout the country. - The data disseminated on road assets are provided for information purposes only and should not be used for the purposes of designing or carrying out works or for the location of assets.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This library was produced as part of the Darwin Plus- funded project, 'Marine Spatial Planning for the Falkland Islands' (July 2014-July 2016), and the Falkland Islands Environmental Studies Budget project, 'Mapping whale distribution around the Falkland Islands using best available knowledge'. Newspaper articles, book excerpts, government documents, letters, reports, and photographs related to whale sightings in Falklands' waters were gathered and catalogued into a Zotero Database. The literature provides specific information on whales and whaling in the Falkland Islands' waters (e.g. information on New Island Station), and more general information on whales and whaling worldwide. Zotero is an open-source literature library that can be downloaded at: https://www.zotero.org/download/

The United States Geological Survey (USGS) - Science Analytics and Synthesis (SAS) - Gap Analysis Project (GAP) manages the Protected Areas Database of the United States (PAD-US), an Arc10x geodatabase, that includes a full inventory of areas dedicated to the preservation of biological diversity and to other natural, recreation, historic, and cultural uses, managed for these purposes through legal or other effective means (www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/protected-areas). The PAD-US is developed in partnership with many organizations, including coordination groups at the [U.S.] Federal level, lead organizations for each State, and a number of national and other non-governmental organizations whose work is closely related to the PAD-US. Learn more about the USGS PAD-US partners program here: www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/pad-us-data-stewards. The United Nations Environmental Program - World Conservation Monitoring Centre (UNEP-WCMC) tracks global progress toward biodiversity protection targets enacted by the Convention on Biological Diversity (CBD) through the World Database on Protected Areas (WDPA) and World Database on Other Effective Area-based Conservation Measures (WD-OECM) available at: www.protectedplanet.net. See the Aichi Target 11 dashboard (www.protectedplanet.net/en/thematic-areas/global-partnership-on-aichi-target-11) for official protection statistics recognized globally and developed for the CBD, or here for more information and statistics on the United States of America's protected areas: www.protectedplanet.net/country/USA. It is important to note statistics published by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas (MPA) Center (www.marineprotectedareas.noaa.gov/dataanalysis/mpainventory/) and the USGS-GAP (www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/pad-us-statistics-and-reports) differ from statistics published by the UNEP-WCMC as methods to remove overlapping designations differ slightly and U.S. Territories are reported separately by the UNEP-WCMC (e.g. The largest MPA, "Pacific Remote Islands Marine Monument" is attributed to the United States Minor Outlying Islands statistics). At the time of PAD-US 2.1 publication (USGS-GAP, 2020), NOAA reported 26% of U.S. marine waters (including the Great Lakes) as protected in an MPA that meets the International Union for Conservation of Nature (IUCN) definition of biodiversity protection (www.iucn.org/theme/protected-areas/about). USGS-GAP released PAD-US 3.0 Statistics and Reports in the summer of 2022. The relationship between the USGS, the NOAA, and the UNEP-WCMC is as follows: - USGS manages and publishes the full inventory of U.S. marine and terrestrial protected areas data in the PAD-US representing many values, developed in collaboration with a partnership network in the U.S. and; - USGS is the primary source of U.S. marine and terrestrial protected areas data for the WDPA, developed from a subset of the PAD-US in collaboration with the NOAA, other agencies and non-governmental organizations in the U.S., and the UNEP-WCMC and; - UNEP-WCMC is the authoritative source of global protected area statistics from the WDPA and WD-OECM and; - NOAA is the authoritative source of MPA data in the PAD-US and MPA statistics in the U.S. and; - USGS is the authoritative source of PAD-US statistics (including areas primarily managed for biodiversity, multiple uses including natural resource extraction, and public access). The PAD-US 3.0 Combined Marine, Fee, Designation, Easement feature class (GAP Status Code 1 and 2 only) is the source of protected areas data in this WDPA update. Tribal areas and military lands represented in the PAD-US Proclamation feature class as GAP Status Code 4 (no known mandate for biodiversity protection) are not included as spatial data to represent internal protected areas are not available at this time. The USGS submitted more than 51,000 protected areas from PAD-US 3.0, including all 50 U.S. States and 6 U.S. Territories, to the UNEP-WCMC for inclusion in the WDPA, available at www.protectedplanet.net. The NOAA is the sole source of MPAs in PAD-US and the National Conservation Easement Database (NCED, www.conservationeasement.us/) is the source of conservation easements. The USGS aggregates authoritative federal lands data directly from managing agencies for PAD-US (https://ngda-gov-units-geoplatform.hub.arcgis.com/pages/federal-lands-workgroup), while a network of State data-stewards provide state, local government lands, and some land trust preserves. National nongovernmental organizations contribute spatial data directly (www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/pad-us-data-stewards). The USGS translates the biodiversity focused subset of PAD-US into the WDPA schema (UNEP-WCMC, 2019) for efficient aggregation by the UNEP-WCMC. The USGS maintains WDPA Site Identifiers (WDPAID, WDPA_PID), a persistent identifier for each protected area, provided by UNEP-WCMC. Agency partners are encouraged to track WDPA Site Identifier values in source datasets to improve the efficiency and accuracy of PAD-US and WDPA updates. The IUCN protected areas in the U.S. are managed by thousands of agencies and organizations across the country and include over 51,000 designated sites such as National Parks, National Wildlife Refuges, National Monuments, Wilderness Areas, some State Parks, State Wildlife Management Areas, Local Nature Preserves, City Natural Areas, The Nature Conservancy and other Land Trust Preserves, and Conservation Easements. The boundaries of these protected places (some overlap) are represented as polygons in the PAD-US, along with informative descriptions such as Unit Name, Manager Name, and Designation Type. As the WDPA is a global dataset, their data standards (UNEP-WCMC 2019) require simplification to reduce the number of records included, focusing on the protected area site name and management authority as described in the Supplemental Information section in this metadata record. Given the numerous organizations involved, sites may be added or removed from the WDPA between PAD-US updates. These differences may reflect actual change in protected area status; however, they also reflect the dynamic nature of spatial data or Geographic Information Systems (GIS). Many agencies and non-governmental organizations are working to improve the accuracy of protected area boundaries, the consistency of attributes, and inventory completeness between PAD-US updates. In addition, USGS continually seeks partners to review and refine the assignment of conservation measures in the PAD-US.

The Rare Plant Occurrences geodatabase is an element occurrence data system with about 10,000 records of rare plant observations on the 6 northernmost California Channel Islands. It is a live database created with the purpose of bringing together in one space all discoverable historic and current information on the localities of about 180 rare and sensitive plants of the northern Channel Islands, California. The list of taxa was developed from agency databases, supplemented with a 1-day workshop with area botanists in 1993; the list has been updated as new information emerges. Data records range from the late 1880s to 2019, including information from herbarium labels, published and unpublished literature, agency files, botanist field notes, incidental observations and results of targeted surveys for individual taxa. The data come from authoritative sources, but the records are of varying quality, related to the nature of the original observation. Consequently, each record contains ...

Comprehensive dataset of 12 Islands in Konya, Turkey as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

This is a series-level metadata record. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. States and equivalent entities are the primary governmental divisions of the United States. In addition to the fifty States, the Census Bureau treats the District of Columbia, Puerto Rico, and each of the Island Areas (American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the U.S. Virgin Islands) as the statistical equivalents of States for the purpose of data presentation.

This is the first published database of Bathynellacea. It includes data of bathynellids (Crustacea, Bathynellacea) from the Iberian Peninsula and Balearic Island collected along 64 years (1949 to 2013). The samples come from groundwater (caves, springs, wells and hyporrheic habitat associated rivers) from both sampling campaigns and occasional sampling conducted throughout the Iberian Peninsula and Balearic Islands. The dataset lists ocurrence data of bathynellids distribution, sampling sites (with localities, county and geographic coordinates), taxonomic information (from family to species level) and sampling sources (collector and sampling dates) for all records. The data were compiled by A.I. Camacho (AIC) and come from own samples, literature and samples donated by several Spanish and foreign researchers which were studied by AIC. The descriptions of new species and species identifications have been carried out by an expert taxonomist (AIC) with 25 years experience in the bathynellids studies. Many of the sampling sites are type localities of endemic species from Iberian Peninsula. The data set includes 409 samples record corresponding to two families, 12 genera and 60 species, 42 of them formally described plus 18 taxa unpublished. This represents everything known for the study area, and nearly a quarter of all known species of Bathynellacea in the world. The main collectors are J. Notenboom & I. Meijers, R. Rouch et coll., A.I. Camacho et coll. (C. Puch, F. Molinero, A.G. Valdecasas, J. Rodriguez, members of G.E. Edelweiss and G. E. Bathynellidae).

The TCRMP is a central component of coral reef management and research in the US Virgin Islands. The TCRMP has contributed critical information on land-based sources of pollution, coral bleaching, and fisheries status since its inception in 2001. The program consists of annual to semi-annual assessments of coral health, benthic community structure, fish community structure, and physical dynamics at 33 sites down to 65 m (220 ft) depth. The TCRMP is funded by and coordinated with the NOAA Coral Reef Conservation Program, NOAA Protected Species, and the USVI Department of Planning and Natural Resources and collaborates with the VI NSF-Experimental Program to Stimulate Competitive Research (EPSCoR), and NOAA National Marine Fisheries. The objectives of the TCRMP include: (1) Monitor the status and trajectories of coral reefs across a majority of habitats and threats, including land-based sources of pollution and thermal stress, (2) Link changes in coral reef health with specific stressors, indicating specific management interventions most effective for preserving reefs, (3) Integrate assessments of understudied mesophotic coral reef ecosystems and threatened species in the USVI, and (4) Provide data, outputs, and advice to stakeholders and create a nexus of information in reef research. At each site, benthic cover surveys are conducted annually along six 10 m long permanent transects marked with steel or brass rods. Video sampling consists of one diver traversing each transect videotaping the benthic cover using a high-definition digital video recorder. After taping, images from each transect are captured and imported into RStudio where twenty randomly allocated points are superimposed on each image. Analysis consists of identifying the substrate located under each point. For each transect, the percent cover of coral, epilithic algae (EAC), macroalgae, sponges, gorgonians, and sand/sediment are calculated by dividing the number of random dots falling on that substrate type by the total number of dots for that transect.

At each site, coral health surveys are conducted annually along six 10 m long permanent transects marked with steel or brass rods. All coral colonies located directly under the transect lines are assessed in situ for signs of mortality and disease following a modified Atlantic and Gulf Rapid Reef Assessment protocol (Kramer et al. 2005). Partial mortality of coral colonies is broken into two categories: recent partial mortality and old partial mortality.

Diseases are conservatively categorized into recognized Caribbean scleractinian diseases and syndromes that include bleaching, black band disease, dark spots disease, white plague, and yellow band (blotch) disease (following Bruckner 2007). Bleaching is assessed as abnormal paling of the colony, and, when present, the severity of the bleaching (paling or total whitening) and the area of the colony affected are assessed. A major bleaching event occurred between September and December 2005, affecting all monitoring sites, and a mild bleaching event occurred between September and October 2010. For each transect, the prevalence of coral impairment categories is calculated as the number of colonies with partial mortality, disease, or bleaching divided by the number of colonies assessed. After the completion of coral health, algae heights are measured along the same permanent transects. Heights are recorded perpendicular to the growth substrate without disturbing the algae every 50 cm. Heights are differentiated to genus except for turf algae and crustose coralline algae which are recorded as such.

Fish surveys have been historically conducted at 14 sites around St. Croix and 10 sites around St. Thomas and, starting in 2012, are conducted at 32 of the 33-monitoring sites. Ten replicate belt transects and three replicate roving dive surveys are conducted at each site. Belt transects are 25 x 4 m and are conducted in 15 minutes per replicate. Roving replicates are also 15 minutes. All fish encountered are recorded except blennies and most gobies. Divers also assess the abundance of Diadema antillarum sea urchins along the 25 x 2 m belt transects. The mean number of sea urchins per 50 m2 is calculated for each site.

Benthic temperatures are recorded at each site with a HoboTemp™ thermistor data logger (Onset Computer Corporation, Bourne, Massachusetts). Thermistors are affixed within transects and set to record at intervals of 15 minutes. Records are presented as daily averages across months.