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

This web site includes statistics on poverty and other distributional and social variables from 25 Latin American and Caribbean (LAC) countries. All statistics are computed from microdata of the main household surveys carried out in these countries using a homogenous methodology (data permitting). SEDLAC allows users to monitor the trends in poverty and other distributional and social indicators in the region. The database is available in the form of brief reports, charts and electronic Excel tables with information for each country/year. In addition, the website visitor can carry out dynamic searches online. - Periodicity: Annual - Number of Economies: 24 - In each period the sample of countries represents more than 97% of LAC total population. The database mainly covers the 1990s and 2000s, although we also present information for previous decades in a few countries. Statistics are updated periodically. - Update Frequency: Biannually - Update Schedule: Fall and Spring - Access Option: Query tool

This table summarizes the income of people in the Caribbean Netherlands; the islands of Bonaire, St. Eustatius, and Saba. Persons are differentiated according to sex, age, socio-economic category, position in the household and income level. The income level quartile groups are determined per island, since the income differences between the islands make a classification for the Caribbean Netherlands as a total difficult to interpret.

Population: The population consists of the people in private households with income observed. The reference date is December 31 of the year under review.

Data is available starting from 2011.

Status of the figures: The figures for 2011 to 2021 are final. The figures for 2022 are provisional.

Changes June 28, 2024: The figures for 2016 to 2020 have changed. For 2016 and later (more) complete registration declaration data are available. The correction leads to higher incomes, in particular for the working- and the wealthy population. The final figures for 2021 and the provisional figures for 2022 are added.

When will new figures be published? New figures are expected in September 2025.

Genetic structures, historical events, habitat preferences, and geographic barriers might result in distinct patterns in insular versus mainland populations. Comparison between these two biogeographic systems provides an opportunity to investigate the relative role of isolation in phylogeographic patterns and to elucidate the importance of evolution and demographic history in population structure. Herein we use a genotype by sequencing approach (GBS) to explore population structure within three species of mastiff bats (Molossus molossus, M. coibensis, and M. milleri), which represent different ecological histories and geographical distributions in the genus to explore phylogeographic patterns and better understand the role of geographic barriers in their dispersal and gene flow. We tested the hypotheses that oceanic straits serve as barriers to dispersal in Caribbean bats and that isolated island populations are more likely to experience genetic drift and bottlenecks relative to highly connected ones, which should have different phylogeographic patterns. We show that population structures vary according to general habitat preferences, to levels of population isolation, and to historical fluctuations in climate. In our dataset, mainland geographic barriers played only a small role in isolation of lineages. However, oceanic straits posed a partial barrier to the dispersal for some populations within some species (M. milleri), but do not seem to disrupt gene flow in others (M. molossus). Lineages on distant islands undergo genetic bottlenecks more frequently than island lineages closer to the mainland, which have a greater exchange of haplotypes.

This table provides the income inequality between private households in the Caribbean Netherlands; the islands of Bonaire, St. Eustatius, and Saba. Inequality is summarized by means of the Gini coefficient and 80/20 Ratio.

Population: The population consists of the people in private households with income observed. The reference date is December 31 of the year under review.

Data is available starting from: 2011.

Status of the figures: The figures for 2011 to 2021 are final. The figures for 2022 are provisional.

Changes June 28, 2024: The figures for 2016 to 2020 have changed. For 2016 and later (more) complete registration declaration data are available. The correction leads to higher incomes, in particular for the working- and the wealthy population. The final figures for 2021 and the provisional figures for 2022 are added.

When will new figures be published? New figures are expected in September 2025.

This table summarizes figures on (persons in) private households with income up to the social minimum benchmark in the Caribbean Netherlands; the islands Bonaire, St. Eustatius and Saba. This benchmark is determined by the Ministry of Social Affairs and Employment for various types of households. For households, persons and minor children the figures are presented in both absolute and relative (as a percentage of the total population with benchmark defined) numbers. Besides, the table differentiates several levels relative to the social minimum benchmark.

Population: The population consists of (persons in) private households with income observed. The reference date is December 31 of the year under review.

Data is available starting from: 2018.

Status of the figures: The figures for 2018 to 2021 are final. The figures for 2022 are provisional.

Changes June 28, 2024: The figures for 2018 to 2020 have changed. For these years (more) complete registration declaration data are available. The correction leads to higher incomes, in particular for the working- and the wealthy population. The final figures for 2021 and the provisional figures for 2022 are added.

When will new figures be published? New figures are expected in September 2025.

This table shows the gross domestic product (GDP) per capita of Bonaire, St. Eustatius, Saba and total Caribbean Netherlands. GDP is a macroeconomic concept.

Note: GDP per capita has been calculated in all years using the most current figures for GDP and population size. No correction has been made for the following two breaks in population time series: - Between 1 January 2015 and 1 January 2016, the population register of St. Eustatius was updated. As a result, approximately 600 individuals were classified as emigrants. These people were still registered in the population register of St. Eustatius, but a check-up revealed that they did not live on the island anymore. - Between 1 Januari 2018 en 1 Januari 2019, the population register of both St. Eustatius and Saba was updated. As a result, approximately 200 individuals on Sint Eustatius and over 200 individuals on Saba were classified as emigrants. These people were still registered in the population register of respectively St. Eustatius and Saba, but a check-up revealed that they did not live on these islands anymore.

Data available from: 2012

Status of the figures: The figures in this table are final.

Changes as of 26 September 2024: Data of 2022 have been added to this table.

When will new figures be published? New figures of the GDP per capita of 2023 will be published in the autumn of 2025.

Diffuse attenuation coefficient (Kd) for light in reef water of Great Lameshur Bay. These data describe how light is attenuated with depth in seawater in Lameshur Bay, with the coefficient calculated using standard procedures constrain (as described in the ms) by using surface light instead of immediately sub surface access_formats=.htmlTable,.csv,.json,.mat,.nc,.tsv acquisition_description=Light was measured as the radiant energy between 400 and 700 nm wavelength (i.e., PAR, \u03bcmol quanta m-2 s-1) as Photosynthetic Photon Flux Density (PPFD). In situ light was measured using two logging meters fitted with a cosine-corrected PAR sensor and wiper (Compact LW, JFE Advantech Co., Ltd, Japan), that were deployed at ~ 19.1-m depth (height of the sensor) in Great Lameshur Bay (18\u00b0 18 \u0301 37.04N, 63\u00b0 43 \u0301 23.17W).

These instruments recorded downwelling PAR, and were deployed six times from 2014and 2017, from August to March and from March to August. The meters were operated in burst mode, during which they would wake up, clean the sensor with a wiper, and record a burst of multiple records before returning to sleep. The Compact LW meter is designed for oceanographic applications to 200 m depths, is fitted with a photodiode sensor, and has a stated accuracy of \u00b1 4% (over 0\u20132000 \u03bcmol photons m2 s-1) and resolution of 0.1 \u03bcmol photons m2 s-1. Both meters were purchased new for this study, and were deployed individually and sequentially between field samplings with comparisons between consecutive deployments used to screen for calibration drift. One sensor was used for a combined duration of 16 months during, and the other sensor was used for 4 months, returned to the manufacturer for servicing (May 2016), and then used again for 3 months. In between deployments, sensors were inspected for abrasions that would affect calibration, and were carefully cleaned with vinegar.

Different configurations of the meter were employed to prolong battery life. In the first and second deployments (starting 21 August 2014 and 19 March 2015, respectively), a burst of 10 measurements was recorded at 0.033 Hz (i.e., every 30 s) every 1.5 h; the instrument failed during the third deployment (starting August 2015); in the fourth and fifth deployments (starting 16 March 2016 and 29 July 2016, respectively) a burst of 10 measurements was recorded at 0.033 Hz every 1.0 h; and in the sixth deployment(starting 23 February 2017) a burst of 30 measurements was recorded at 0.100 Hz (i.e.,every 10 s) every 2.0 h. The timing of bursts was not standardized to local time and, therefore, the number and timing of bursts bracketing noon (which were used to calculate transmission, described below) differed among deployments. The sampling frequency within each burst was sufficient to alleviate the bias resulting from wave-induced light flecking (Zheng et al. 2002). As a result of varying power demands of each sampling configuration, the meter did not always record for the full duration of each deployment.\u00a0

Surface light was recorded with two cosine-corrected PAR sensor (S-LIA-M003, OnsetComputer Corporation) attached to loggers (Micro Station Data Logger H21-002, OnsetComputer Corporation) recording at 0.0033 Hz (i.e., every 5 minutes). The sensors were calibrated by the manufacturers, and were mounted ~ 4-m above sea level adjacent to Great Lameshur Bay (18\u00b0 19 \u0301 6.61N, 64\u00b0 43 \u0301 27.73W), and ~ 0.875 km from the sensor recording in situ light. The paired surface sensors were used to ensure data integrity should one sensor fail, and the paired deployments provided a means to detect erroneous records due to sensor drift or failure. The surface sensors were downloaded, reprogrammed, and cleaned in July of each year, and have been deployed for 11 y(from 2007). Here, surface light data for 2014-2017 are presented to provide temporal concordance with the submerged sensor. awards_0_award_nid=562085 awards_0_award_number=OCE-1332915 awards_0_data_url=http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1332915 awards_0_funder_name=NSF Division of Ocean Sciences awards_0_funding_acronym=NSF OCE awards_0_funding_source_nid=355 awards_0_program_manager=David L. Garrison awards_0_program_manager_nid=50534 awards_1_award_nid=562593 awards_1_award_number=DEB-1350146 awards_1_data_url=http://www.nsf.gov/awardsearch/showAward?AWD_ID=1350146 awards_1_funder_name=NSF Division of Environmental Biology awards_1_funding_acronym=NSF DEB awards_1_funding_source_nid=550432 awards_1_program_manager=Betsy Von Holle awards_1_program_manager_nid=701685 cdm_data_type=Other comment=Kd PAR Values P. Edmunds, PI Data associated with Fig. 2 of: Edmunds, Coral Reefs (2018) Long-term variation in light intensity on a coral reef. Version 13 July 2018 Conventions=COARDS, CF-1.6, ACDD-1.3 data_source=extract_data_as_tsv version 2.3 19 Dec 2019 defaultDataQuery=&time<now doi=10.1575/1912/bco-dmo.744503 infoUrl=https://www.bco-dmo.org/dataset/739882 institution=BCO-DMO instruments_0_acronym=LI-COR Biospherical PAR instruments_0_dataset_instrument_description=Used to determine PAR instruments_0_dataset_instrument_nid=742233 instruments_0_description=The LI-COR Biospherical PAR Sensor is used to measure Photosynthetically Available Radiation (PAR) in the water column. This instrument designation is used when specific make and model are not known. instruments_0_instrument_external_identifier=https://vocab.nerc.ac.uk/collection/L22/current/TOOL0074/ instruments_0_instrument_name=LI-COR Biospherical PAR Sensor instruments_0_instrument_nid=480 instruments_0_supplied_name=PAR Sensor metadata_source=https://www.bco-dmo.org/api/dataset/739882 param_mapping={'739882': {}} parameter_source=https://www.bco-dmo.org/mapserver/dataset/739882/parameters people_0_affiliation=California State University Northridge people_0_affiliation_acronym=CSU-Northridge people_0_person_name=Peter J. Edmunds people_0_person_nid=51536 people_0_role=Principal Investigator people_0_role_type=originator people_1_affiliation=Woods Hole Oceanographic Institution people_1_affiliation_acronym=WHOI BCO-DMO people_1_person_name=Hannah Ake people_1_person_nid=650173 people_1_role=BCO-DMO Data Manager people_1_role_type=related project=VI Octocorals,RUI-LTREB projects_0_acronym=VI Octocorals projects_0_description=The recent past has not been good for coral reefs, and journals have been filled with examples of declining coral cover, crashing fish populations, rising cover of macroalgae, and a future potentially filled with slime. However, reefs are more than the corals and fishes for which they are known best, and their biodiversity is affected strongly by other groups of organisms. The non-coral fauna of reefs is being neglected in the rush to evaluate the loss of corals and fishes, and this project will add on to an on-going long term ecological study by studying soft corals. This project will be focused on the ecology of soft corals on reefs in St. John, USVI to understand the Past, Present and the Future community structure of soft corals in a changing world. For the Past, the principal investigators will complete a retrospective analysis of octocoral abundance in St. John between 1992 and the present, as well as Caribbean-wide since the 1960's. For the Present, they will: (i) evaluate spatio-temporal changes between soft corals and corals, (ii) test for the role of competition with macroalgae and between soft corals and corals as processes driving the rising abundance of soft corals, and (iii) explore the role of soft corals as "animal forests" in modifying physical conditions beneath their canopy, thereby modulating recruitment dynamics. For the Future the project will conduct demographic analyses on key soft corals to evaluate annual variation in population processes and project populations into a future impacted by global climate change. This project was funded to provide and independent "overlay" to the ongoing LTREB award (DEB-1350146, co-funded by OCE, PI Edmunds) focused on the long-term dynamics of coral reefs in St. John. Note: This project is closely associated with the project "RAPID: Resilience of Caribbean octocorals following Hurricanes Irma and Maria". See: https://www.bco-dmo.org/project/749653. The following publications and data resulted from this project: 2017 Tsounis, G., and P. J. Edmunds. Three decades of coral reef community dynamics in St. John, USVI: a contrast of scleractinians and octocorals. Ecosphere 8(1):e01646. DOI: 10.1002/ecs2.1646Rainfall and temperature dataCoral and macroalgae abundance and distributionDescriptions of hurricanes affecting St. John 2016 Gambrel, B. and Lasker, H.R. Marine Ecology Progress Series 546: 85–95, DOI: 10.3354/meps11670Colony to colony interactionsEunicea flexuosa interactionsGorgonia ventalina asymmetryNearest neighbor surveys 2015 Lenz EA, Bramanti L, Lasker HR, Edmunds PJ. Long-term variation of octocoral populations in St. John, US Virgin Islands. Coral Reefs DOI 10.1007/s00338-015-1315-xoctocoral survey - densitiesoctocoral counts - photoquadrats vs. insitu surveyoctocoral literature reviewDownload complete data for this publication (Excel file) 2015 Privitera-Johnson, K., et al., Density-associated recruitment in octocoral communities in St. John, US Virgin Islands, J.Exp. Mar. Biol. Ecol. DOI: 10.1016/j.jembe.2015.08.006octocoral density dependenceDownload complete data for this publication (Excel file) Other datasets related to this project:octocoral transects - adult colony height projects_0_end_date=2016-08 projects_0_geolocation=St. John, US Virgin Islands: 18.3185, 64.7242 projects_0_name=Ecology and functional biology of octocoral communities projects_0_project_nid=562086 projects_0_project_website=http://coralreefs.csun.edu/ projects_0_start_date=2013-09 projects_1_acronym=RUI-LTREB projects_1_description=Describing how ecosystems like coral reefs are changing is at the

ALDER one-reference admixture dates and mixture proportions.