Context

The United States Census Bureau’s international dataset provides estimates of country populations since 1950 and projections through 2050. Specifically, the dataset includes midyear population figures broken down by age and gender assignment at birth. Additionally, time-series data is provided for attributes including fertility rates, birth rates, death rates, and migration rates.

Querying BigQuery tables

You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.census_bureau_international.

Sample Query 1

What countries have the longest life expectancy? In this query, 2016 census information is retrieved by joining the mortality_life_expectancy and country_names_area tables for countries larger than 25,000 km2. Without the size constraint, Monaco is the top result with an average life expectancy of over 89 years!

standardSQL

SELECT age.country_name, age.life_expectancy, size.country_area FROM ( SELECT country_name, life_expectancy FROM bigquery-public-data.census_bureau_international.mortality_life_expectancy WHERE year = 2016) age INNER JOIN ( SELECT country_name, country_area FROM bigquery-public-data.census_bureau_international.country_names_area where country_area > 25000) size ON age.country_name = size.country_name ORDER BY 2 DESC /* Limit removed for Data Studio Visualization */ LIMIT 10

Sample Query 2

Which countries have the largest proportion of their population under 25? Over 40% of the world’s population is under 25 and greater than 50% of the world’s population is under 30! This query retrieves the countries with the largest proportion of young people by joining the age-specific population table with the midyear (total) population table.

standardSQL

SELECT age.country_name, SUM(age.population) AS under_25, pop.midyear_population AS total, ROUND((SUM(age.population) / pop.midyear_population) * 100,2) AS pct_under_25 FROM ( SELECT country_name, population, country_code FROM bigquery-public-data.census_bureau_international.midyear_population_agespecific WHERE year =2017 AND age < 25) age INNER JOIN ( SELECT midyear_population, country_code FROM bigquery-public-data.census_bureau_international.midyear_population WHERE year = 2017) pop ON age.country_code = pop.country_code GROUP BY 1, 3 ORDER BY 4 DESC /* Remove limit for visualization*/ LIMIT 10

Sample Query 3

The International Census dataset contains growth information in the form of birth rates, death rates, and migration rates. Net migration is the net number of migrants per 1,000 population, an important component of total population and one that often drives the work of the United Nations Refugee Agency. This query joins the growth rate table with the area table to retrieve 2017 data for countries greater than 500 km2.

SELECT growth.country_name, growth.net_migration, CAST(area.country_area AS INT64) AS country_area FROM ( SELECT country_name, net_migration, country_code FROM bigquery-public-data.census_bureau_international.birth_death_growth_rates WHERE year = 2017) growth INNER JOIN ( SELECT country_area, country_code FROM bigquery-public-data.census_bureau_international.country_names_area

Update frequency

Historic (none)

Dataset source

United States Census Bureau

Terms of use: This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

See the GCP Marketplace listing for more details and sample queries: https://console.cloud.google.com/marketplace/details/united-states-census-bureau/international-census-data

This dataset provides values for GDP reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Which county has the most Facebook users?

              There are more than 378 million Facebook users in India alone, making it the leading country in terms of Facebook audience size. To put this into context, if India’s Facebook audience were a country then it would be ranked third in terms of largest population worldwide. Apart from India, there are several other markets with more than 100 million Facebook users each: The United States, Indonesia, and Brazil with 193.8 million, 119.05 million, and 112.55 million Facebook users respectively.

              Facebook – the most used social media

              Meta, the company that was previously called Facebook, owns four of the most popular social media platforms worldwide, WhatsApp, Facebook Messenger, Facebook, and Instagram. As of the third quarter of 2021, there were around 3,5 billion cumulative monthly users of the company’s products worldwide. With around 2.9 billion monthly active users, Facebook is the most popular social media worldwide. With an audience of this scale, it is no surprise that the vast majority of Facebook’s revenue is generated through advertising.

              Facebook usage by device
              As of July 2021, it was found that 98.5 percent of active users accessed their Facebook account from mobile devices. In fact, almost 81.8 percent of Facebook audiences worldwide access the platform only via mobile phone. Facebook is not only available through mobile browser as the company has published several mobile apps for users to access their products and services. As of the third quarter 2021, the four core Meta products were leading the ranking of most downloaded mobile apps worldwide, with WhatsApp amassing approximately six billion downloads.

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Walmart is one of the world's largest and most well-known retail chains, often referred to as a "Global Superstore." Founded in 1962 by Sam Walton in Rogers, Arkansas, Walmart has grown to become a multinational retail giant with a presence in various countries. It's known for its vast and diverse product offerings, including groceries, electronics, clothing, household goods, and more.

Here are some key points that highlight Walmart's status as a Global Superstore:

• International Presence: Walmart operates in multiple countries across the globe, making it a truly global retailer. Its international expansion began in the 1990s, and it now has a presence in numerous countries, including the United States, Mexico, Canada, the United Kingdom, China, India, Brazil, and many others.

• Extensive Product Range: Walmart offers an extensive and diverse range of products, from everyday groceries to electronics, apparel, furniture, automotive supplies, and more. This vast selection of goods under one roof makes it a one-stop shop for a wide variety of consumer needs.

• Competitive Pricing: Walmart is known for its commitment to offering low prices, often leveraging its buying power to negotiate favorable deals with suppliers and pass those savings on to customers. This has helped it attract price-conscious shoppers and maintain a competitive edge.

• E-commerce and Online Presence: In addition to its physical stores, Walmart has a significant online presence through its e-commerce platform. It has invested heavily in expanding its digital retail capabilities, including online ordering, home delivery, and curbside pickup, to meet the changing shopping preferences of consumers.

• Private Label Brands: Walmart offers a range of private-label or store-brand products, providing more affordable alternatives to well-known brands. These private label products cover a wide range of categories and help draw budget-conscious customers.

• Sustainability Efforts: Walmart has made significant efforts to enhance its sustainability practices. It aims to reduce its environmental footprint by using renewable energy, improving energy efficiency, and implementing sustainable sourcing practices.

• Community Engagement: Walmart is actively involved in philanthropic activities and community engagement. The company supports various social and charitable initiatives, including education, hunger relief, and disaster relief efforts.

• Employment and Economic Impact: Walmart is one of the world's largest employers, providing jobs to millions of people across its global operations. Its presence in many communities contributes to local economies and often influences pricing and employment trends in those areas.

• Supply Chain and Logistics: Walmart is renowned for its efficient supply chain and distribution systems, which allow it to stock products, restock shelves, and move goods efficiently. This logistical expertise is a key element of its success as a Global Superstore.

Overall, Walmart's status as a Global Superstore is characterized by its massive reach, diverse product offerings, competitive pricing, and continuous efforts to adapt to changing consumer preferences and demands. Its global footprint and influence in the retail industry make it a prominent player in the world of commerce.

This dataset provides values for GOLD RESERVES reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This dataset provides values for CORONAVIRUS DEATHS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This dataset tracks the average applied tariff rates in both industrial and developing countries. Data is averaged for the years 1981-2005. Figures for 2005 have been estimated. Notes: All tariff rates are based on unweighted averages for all goods in ad valorem rates, or applied rates, or MFN rates whichever data is available in a longer period. Tariff data is primarily based on UNCTAD TRAINS database and then used WTO IDB data for gap filling if possible. Data in 1980s is taken from other source.** Tariff data in these countries came from IMF Global Monitoring Tariff file in 2004 which might include other duties or charges. Country codes are based on the classifications by income in WDI 2006, where 1 = low income, 2 = middle income, 3 = high incone non-OECDs, and 4 = high income OECD countries. Sources: UNCTAD TRAINS database (through WITS); WTO IDB database (through WITS); WTO IDB CD ROMs, various years and Trade Policy Review -- Country Reports in various issues, 1990-2005; UNCTAD Handbook of Trade Control Measures of Developing Countries -- Supplement 1987 and Directory of Import Regimes 1994; World Bank Trade Policy Reform in Developing Countries since 1985, WB Discussion Paper #267, 1994 and World Development Indicators, 1998-2006; The Uruguay Round: Statistics on Tariffs Concessions Given and Received, 1996; OECD Indicators of Tariff and Non-Tariff Trade Barriers, 1996 and 2000; and IMF Global Monitoring Tariff data file 2004. Data source: http://go.worldbank.org/LGOXFTV550 Access Date: October 17, 2007

We present the GLOBAL ROADKILL DATA, the largest worldwide compilation of roadkill data on terrestrial vertebrates. We outline the workflow (Fig. 1) to illustrate the sequential steps of the study, in which we merged local-scale survey datasets and opportunistic records into a unified roadkill large dataset comprising 208,570 roadkill records. These records include 2283 species and subspecies from 54 countries across six continents, ranging from 1971 to 2024.Large roadkill datasets offer the advantage ofpreventing the collection of redundant data and are valuable resources for both local and macro-scale analyses regarding roadkill rates, road and landscape features associated with roadkill risk, species more vulnerable to road traffic, and populations at risk due to additional mortality. The standardization of data - such as scientific names, projection coordinates, and units - in a user-friendly format, makes themreadily accessible to a broader scientific and non-scientific community, including NGOs, consultants, public administration officials, and road managers. The open-access approach promotes collaboration among researchers and road practitioners, facilitating the replication of studies, validation of findings, and expansion of previous work. Moreover, researchers can utilize suchdatasets to develop new hypotheses, conduct meta-analyses, address pressing challenges more efficiently and strengthen the robustness of road ecology research. Ensuring widespreadaccess to roadkill data fosters a more diverse and inclusive research community. This not only grants researchers in emerging economies with more data for analysis, but also cultivates a diverse array of perspectives and insightspromoting the advance of infrastructure ecology.MethodsInformation sources: A core team from different continents performed a systematic literature search in Web of Science and Google Scholar for published peer-reviewed papers and dissertations. It was searched for the following terms: “roadkill* OR “road-kill” OR “road mortality” AND (country) in English, Portuguese, Spanish, French and/or Mandarin. This initiative was also disseminated to the mailing lists associated with transport infrastructure: The CCSG Transport Working Group (WTG), Infrastructure & Ecology Network Europe (IENE) and Latin American & Caribbean Transport Working Group (LACTWG) (Fig. 1). The core team identified 750 scientific papers and dissertations with information on roadkill and contacted the first authors of the publications to request georeferenced locations of roadkill andofferco-authorship to this data paper. Of the 824 authors contacted, 145agreed to sharegeoreferenced roadkill locations, often involving additional colleagues who contributed to data collection. Since our main goal was to provide open access to data that had never been shared in this format before, data from citizen science projects (e.g., globalroakill.net) that are already available were not included.Data compilation: A total of 423 co-authors compiled the following information: continent, country, latitude and longitude in WGS 84 decimal degrees of the roadkill, coordinates uncertainty, class, order, family, scientific name of the roadkill, vernacular name, IUCN status, number of roadkill, year, month, and day of the record, identification of the road, type of road, survey type, references, and observers that recorded the roadkill (Supplementary Information Table S1 - description of the fields and Table S2 - reference list). When roadkill data were derived from systematic surveys, the dataset included additional information on road length that was surveyed, latitude and longitude of the road (initial and final part of the road segment), survey period, start year of the survey, final year of the survey, 1st month of the year surveyed, last month of the year surveyed, and frequency of the survey. We consolidated 142 valid datasets into a single dataset. We complemented this data with OccurenceID (a UUID generated using Java code), basisOfRecord, countryCode, locality using OpenStreetMap’s API (https://www.openstreetmap.org), geodeticDatum, verbatimScientificName, Kingdom, phylum, genus, specificEpithet, infraspecificEpithet, acceptedNameUsage, scientific name authorship, matchType, taxonRank using Darwin Core Reference Guide (https://dwc.tdwg.org/terms/#dwc:coordinateUncertaintyInMeters) and link of the associatedReference (URL).Data standardization - We conducted a clustering analysis on all text fields to identify similar entries with minor variations, such as typos, and corrected them using OpenRefine (http://openrefine.org). Wealsostandardized all date values using OpenRefine. Coordinate uncertainties listed as 0 m were adjusted to either 30m or 100m, depending on whether they were recorded after or before 2000, respectively, following the recommendation in the Darwin Core Reference Guide (https://dwc.tdwg.org/terms/#dwc:coordinateUncertaintyInMeters).Taxonomy - We cross-referenced all species names with the Global Biodiversity Information Facility (GBIF) Backbone Taxonomy using Java and GBIF’s API (https://doi.org/10.15468/39omei). This process aimed to rectify classification errors, include additional fields such as Kingdom, Phylum, and scientific authorship, and gather comprehensive taxonomic information to address any gap withinthe datasets. For species not automatically matched (matchType - Table S1), we manually searched for correct synonyms when available.Species conservation status - Using the species names, we retrieved their conservation status and also vernacular names by cross-referencing with the database downloaded from the IUCNRed List of Threatened Species (https://www.iucnredlist.org). Species without a match were categorized as "Not Evaluated".Data RecordsGLOBAL ROADKILL DATA is available at Figshare27 https://doi.org/10.6084/m9.figshare.25714233. The dataset incorporates opportunistic (collected incidentally without data collection efforts) and systematic data (collected through planned, structured, and controlled methods designed to ensure consistency and reliability). In total, it comprises 208,570 roadkill records across 177,428 different locations(Fig. 2). Data were collected from the road network of 54 countries from 6 continents: Europe (n = 19), Asia (n = 16), South America (n=7), North America (n = 4), Africa (n = 6) and Oceania (n = 2).(Figure 2 goes here)All data are georeferenced in WGS84 decimals with maximum uncertainty of 5000 m. Approximately 92% of records have a location uncertainty of 30 m or less, with only 1138 records having location uncertainties ranging from 1000 to 5000 m. Mammals have the highest number of roadkill records (61%), followed by amphibians (21%), reptiles (10%) and birds (8%). The species with the highest number of records were roe deer (Capreolus capreolus, n = 44,268), pool frog (Pelophylax lessonae, n = 11,999) and European fallow deer (Dama dama, n = 7,426).We collected information on 126 threatened species with a total of 4570 records. Among the threatened species, the giant anteater (Myrmecophaga tridactyla, VULNERABLE) has the highest number of records n = 1199), followed by the common fire salamander (Salamandra salamandra, VULNERABLE, n=1043), and European rabbit (Oryctolagus cuniculus, ENDANGERED, n = 440). Records ranged from 1971 and 2024, comprising 72% of the roadkill recorded since 2013. Over 46% of the records were obtained from systematic surveys, with road length and survey period averaging, respectively, 66 km (min-max: 0.09-855 km) and 780 days (1-25,720 days).Technical ValidationWe employed the OpenStreetMap API through Java todetect location inaccuracies, andvalidate whether the geographic coordinates aligned with the specified country. We calculated the distance of each occurrence to the nearest road using the GRIP global roads database28, ensuring that all records were within the defined coordinate uncertainty. We verified if the survey duration matched the provided initial and final survey dates. We calculated the distance between the provided initial and final road coordinates and cross-checked it with the given road length. We identified and merged duplicate entries within the same dataset (same location, species, and date), aggregating the number of roadkills for each occurrence.Usage NotesThe GLOBAL ROADKILL DATA is a compilation of roadkill records and was designed to serve as a valuable resource for a wide range of analyses. Nevertheless, to prevent the generation of meaningless results, users should be aware of the followinglimitations:- Geographic representation – There is an evident bias in the distribution of records. Data originatedpredominantly from Europe (60% of records), South America (22%), and North America (12%). Conversely, there is a notable lack of records from Asia (5%), Oceania (1%) and Africa (0.3%). This dataset represents 36% of the initial contacts that provided geo-referenced records, which may not necessarily correspond to locations where high-impact roads are present.- Location accuracy - Insufficient location accuracy was observed for 1% of the data (ranging from 1000 to 5000 m), that was associated with various factors, such as survey methods, recording practices, or timing of the survey.- Sampling effort - This dataset comprised both opportunistic data and records from systematic surveys, with a high variability in survey duration and frequency. As a result, the use of both opportunistic and systematic surveys may affect the relative abundance of roadkill making it hard to make sound comparisons among species or areas.- Detectability and carcass removal bias - Although several studies had a high frequency of road surveys,the duration of carcass persistence on roads may vary with species size and environmental conditions, affecting detectability. Accordingly, several approaches account for survey frequency and target speciesto estimate more

Member countries are allocated votes at the time of membership and subsequently for additional subscriptions to capital. Votes are allocated differently in each organization. Each member receives votes consisting of share votes (one vote for each share of the Bank's capital stock held by the member) plus basic votes (calculated so that the sum of all basic votes is equal to 5.55 percent of the sum of basic votes and share votes for all members). Latest information about voting power is available at http://www.worldbank.org/en/about/leadership/votingpowers

Papua New Guinea, the land of diversity and last frontier for Biodiversity Conservation. Situated north of Australia, Papua New Guinea is a Pacific Island country that comprises the eastern half of the Island of New Guinea and four islands bordered by the Solomon Islands to the east and Indonesia to the west. It is one of the largest tropical islands on earth, New Guinea remains covered by the 3rd largest rainforest in the world, after the Amazon and the Congo Basin.

The country’s forests consist of diverse lowland (57% of total forest cover), montane forest (29%), swamp forest (10%), dry evergreen forest (2%) and mangrove (2%). Papua New Guinea’s vast coastline of approximately 20,197 km2 accounts for almost 44% of the country’s land area. Situated within the center of the Coral Triangle, the reefs and marine ecosystems around Papua New Guinea is also home to over 600 species of corals that host up to 3,000 species of fish. PNG also hosts one of the extensive and species-rich mangrove forests that is home to up to 43 species

This dataset provides values for INFLATION RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

The 2007 World Bank Group Entrepreneurship Survey measures entrepreneurial activity in 84 developing and industrial countries over the period 2003-2005. The database includes cross-country, time-series data on the number of total and newly registered businesses, collected directly from Registrar of Companies around the world. In its second year, this survey incorporates improvements in methodology, and expanded participation from countries covered, allowing for greater cross-border compatibility of data compared with the 2006 survey. This joint effort by the IFC SME Department and the World Bank Developing Research Group is the most comprehensive dataset on cross-country firm entry data available today. This database The World Bank Group Entrepreneurship Dataaset presents data collected primarily from country business registries using the first annual World Bank Group Questionnaire on Entrepreneurship (alternative sources were tax authorities, finance ministries, and national statistics offices). For more information on the author of the database, Leora Klapper, visit: http://go.worldbank.org/DK5AHCQSO0. This data was access at the preceeding link, on October 11, 2007. Please visit the link for more information in regards to this dataset.

This dataset is a point based representation of major port and harbors. The dataset layer is comprised of 4792 derivative vector framework library features derived based on 1:3 000 000 data originally from RWDBII. The layer provides nominal analytical/mapping at 1:3 000 000. Data processing complete globally. This data was collected from: http://www.fao.org/geonetwork/srv/en/metadata.show?id=29042&currTab=simple Access Date: October 15, 2007.

This dataset shows the locations of the 50 companies that had the largest number of employees among the Fortune Global 500. The dataset also shows the company's revenue rank for 2007 The list comes from cnnmoney.com whose Fortune section does analysis on the top corporations throughout the world

This is a point based representation of Airports. The dataset is comprised of 15044 features derived based on 1:3 000 000 data originally from RWDBII. The layer provides nominal at 1:3 000 000. Data processing complete globally. This data was collected from: http://www.fao.org/geonetwork/srv/en/metadata.show?id=29037&currTab=simple access date: October 15, 2007

The boundaries of the CLME Project encompass the Caribbean Sea LME and the North Brazil Shelf LME and include 26 countries and 19 dependent territories of France, the Netherlands, United Kingdom and United States. These countries range from among the largest (e.g. Brazil, USA) to among the smallest (e.g. Barbados, St. Kitts and Nevis), and from the most developed to the least developed. Consequently, there is an extremely wide range in their capacities for living marine resource management. Throughout the region, the majority of the population inhabits the coastal zone, and there is a very high dependence on marine resources for livelihoods from fishing and tourism, particularly among the small island developing states (SIDS), of which there are 16. In addition 18 of the 19 dependent territories are SIDS. The region is characterized by a diversity of national and regional governance and institution arrangements, stemming primarily from the governance structures established by the countries that colonized the region. Physical and geographical characteristics The Caribbean Sea is a semi-enclosed ocean basin bounded by the Lesser Antilles to the east and southeast, the Greater Antilles (Cuba, Hispaniola, and Puerto Rico) to the north, and by Central America to the west and southwest. It is located within the tropics and covers 1,943,000 km2. The Wider Caribbean, which includes the Gulf of Mexico, the Caribbean Sea and the adjacent parts of the Atlantic Ocean encompasses an area of 2,515,900 km2 and is the second largest sea in the world. (Bjorn 1997, Sheppard 2000, IUCN 2003). It is noted for its many islands, including the Leeward and Windward Islands situated on its eastern boundary, Cuba, Hispaniola, Puerto Rico, Jamaica and the Cayman Islands. There is little seasonal variation in surface water temperatures. Temperatures range from 25.5 °C in the winter to 28 °C in the summer. The adjacent region of the North Brazil Shelf Large Marine Ecosystem is characterized by its tropical climate. It extends in the Atlantic Ocean from the boundary with the Caribbean Sea to the Paraiba River estuary in Brazil. The LME owes its unity to the North Brazil Current, which flows parallel to Brazil’s coast and is an extension of the South Equatorial Current coming from the East. The LME is characterized by a wide shelf, and features macrotides and upwellings along the shelf edge. It has moderately diverse food webs and high production due in part to the high levels of nutrients coming from the Amazon and Tocantins rivers, as well as from the smaller rivers of the Amapa and western Para coastal plains. The Caribbean Sea averages depths of 2,200 m, with the deepest part, known as the Cayman trench, plunging to 7,100 m. The drainage basin of the Wider Caribbean covers 7.5 million km2 and encompasses eight major river systems, from the Mississippi to the Orinoco (Hinrichsen 1998). The region is highly susceptible to natural disasters. Most of the islands and the Central American countries lie within the hurricane belt and are vulnerable to frequent damage from strong winds and storm surges. Recent major natural disasters include hurricanes Gilbert (1988) and Hugo (1989), the eruptions of the Soufriere Hills Volcano in Montserrat (1997) and the Piparo Mud Volcano in Trinidad (1997), as well as drought conditions in Cuba and Jamaica during 1997-98, attributed to the El Niño phenomenon. More recently Hurricane Georges devastated large areas, as did Hurricanes Mitch and Ivan (2004). In the case of Ivan, damages were extensive to both natural and infrastructural assets, with estimates reported by Grenada of US$815 million, the Cayman Islands US$1.85 billion, Jamaica US$360 million and Cuba US$1.2 billion. Although the intense category 5 hurricanes Katrina and Rita did not make landfall in the Caribbean, in 2005, Hurricane Wilma devastated the Yucatan peninsula and has the distinction of being the most intense hurricane on record in the Atlantic. Ecological status The marine and coastal systems of the region support a complex interaction of distinct ecosystems, with an enormous biodiversity, and are among the most productive in the world. As mentioned above, several of the world's largest and most productive estuaries (Amazon and Orinoco) are found in the region. The coast of Belize has the second largest barrier reef in the world extending some 250 kilometers and covering approximately 22,800 km2. The region's coastal zone is significant, encompassing entire countries for many of the island nations. Fish and Fisheries A wide range of fisheries activities (industrial, artisanal and recreational) coexist in the CLME Project area. Overall landings from the main fisheries rose from around 177,000 tonnes in 1975 to a peak of 1,000,000 tonnes in 1995 before declining to around 800,000 tonnes in 2005. The total landings from all fisheries shows the decline over the last decade. In the reef fish fisheries, declines in overall landings are rarely observed; instead, there are shifts in species composition. For instance a decline in the percentage of snapper and grouper in the catch, the larger, long-lived predators, is an indication of over exploitation; although not in the Caribbean Large Marine Ecosystem, this pattern was evident in Bermuda between 1969 and 1975 where the percentage of snappers and groupers declined from 67% to 38% and also on the north coast of Jamaica between 1981 and 1990 where the 11 decline was from 26% to 12%. According to an FAO assessment, some 35% of the region's stocks are overexploited. The fisheries of the Caribbean Region are based upon a diverse array of resources. The fisheries of greatest importance are for offshore pelagics, reef fishes, lobster, conch, shrimps, continental shelf demersal fishes, deep slope and bank fishes and coastal pelagics. There is a variety of less important fisheries such as for marine mammals, sea turtles, sea urchins, and seaweeds. The management and governance of these fisheries varies greatly and is fragmented with incomplete or absent frameworks at the sub-regional and regional levels and weak vertical and horizontal linkages. The fishery types vary widely in exploitation; vessel and gear used, and approach to their development and management. However, most coastal resources are considered to be overexploited and there is increasing evidence that pelagic predator biomass has been severely depleted (FAO 1998, Mahon 2002, Myers and Worm 2003). Recreational fishing, an important but undocumented contributor to tourism economies, is an important link between shared resource management and tourism, as the preferred species are mainly predatory migratory pelagics (e.g. billfishes, wahoo, and dolphinfish). This aspect of shared resource management has received minimal attention in most Caribbean countries (Mahon and McConney 2004). Pollution and Ecosystem Health Pollution, mainly from land-based sources, and degradation of nearshore habitats are among the major threats to the region’s living marine resources. The CLME is showing signs of environmental stress, particularly in the shallow waters of coral reef systems and in semi-enclosed bays. Coastal water quality has been declining throughout the region, due to a number of factors including rapid population growth in coastal areas, poor land-use practices and increasing discharges of untreated municipal and industrial waste and agricultural pesticides and fertilizers. Throughout the region, pollution by a range of substances and sources including sewage, nutrients, sediments, petroleum hydrocarbons and heavy metals is of increasing concern. The GIWA studies identified a number of pollution hotspots in the region, mainly around the coastal cities. Pollution has significant transboundary implications, as a result of the high potential for transport across EEZs in wind and ocean currents. Not only could this cause degradation of living marine resources in places far from the source, but it could also pose a threat to human and animal health by the introduction of pathogens. Pollution has been implicated in the increasing episodes of fish kills in the region, although this is not conclusive. Socio-economic situation The physical expanse of the region's coastal zone is significant, encompassing the entire land mass for many of the islands. Additionally, for countries such as the island nations of the Caribbean, Panama and Costa Rica, marine territory represents more than 50% of the total area under national sovereignty. In general, the region’s coastal zone is where the majority of it human population live and where most economic activities also take place. In 2001, the population of the Caribbean Sea region (not including the United States) was around 102 million, of which it is estimated that 59% is in Colombia and Venezuela, 27% is in Cuba and Hispaniola, 10% is in Central America and Mexico, and 3% is in the Small Islands. Taking into account the population growth rate for each country in the Caribbean Sea region, it is expected that the number of inhabitants would be close to 123 million in 2020. When the population for Guyana, Suriname, French Guiana, and the regions of Brazil and Florida that comprise the CLME Project are included, this number is expected to increase to approximately 130 million. Almost all the countries in the region are among the world’s premier tourism destinations, providing an important source of income for their economies. The population in the Caribbean Sea region swells during the tourist season by the influx of millions of tourists, mostly in beach destinations. In 2004, for example, the Mexican state of Quintana Roo received 10.8 million tourists with over 35% of those arriving by cruise ships. There is a high dependence on living marine resources for food, employment and income from fishing and tourism, particularly among the SIDS. Although its contribution to GDP is relatively low, marine

Exports in Germany decreased to 129.67 EUR Billion in August from 130.28 EUR Billion in July of 2025. This dataset provides - Germany Exports - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset displays the number of television receivers by country for the time period covering 1990 through 1997. Covered throughout this dataset is 150+ countries, This dataset was gathered from the United Nations Statistics Division. http://unstats.un.org/unsd/databases.htm Access Date: October 31, 2007

This is the World Freedom index, By the State of World Liberty Project. It ranks various countries by various forms of freedom and created an index to see which countries had the most freedom. USA finished 8th, with Estonia in 1st place and North Korea having the least freedom. Source URL: http://www.stateofworldliberty.org/report/rankings.html This Dataset has a ranking for the countries, just to be clear, when you map out the rankings of countries, the highest ranked countries will not be the brightest on the map. Estonia is Ranked #1, but the value of 1 is lower than the value assigned to North Korea (158). so just be aware of that. In short, for mapping, use the Scores not the Ranks.

This dataset provides values for GDP reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.