Spatial datasets utilized to conduct the spatial analysis and additional information from the research article: Coastal proximity of populations in 22 Pacific Island Countries and Territories. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0223249 https://sdd.spc.int/mapping-coastal

In 2023, Washington, D.C. had the highest population density in the United States, with 11,130.69 people per square mile. As a whole, there were about 94.83 residents per square mile in the U.S., and Alaska was the state with the lowest population density, with 1.29 residents per square mile. The problem of population density Simply put, population density is the population of a country divided by the area of the country. While this can be an interesting measure of how many people live in a country and how large the country is, it does not account for the degree of urbanization, or the share of people who live in urban centers. For example, Russia is the largest country in the world and has a comparatively low population, so its population density is very low. However, much of the country is uninhabited, so cities in Russia are much more densely populated than the rest of the country. Urbanization in the United States While the United States is not very densely populated compared to other countries, its population density has increased significantly over the past few decades. The degree of urbanization has also increased, and well over half of the population lives in urban centers.

The West Africa Coastal Vulnerability Mapping: Population Projections, 2030 and 2050 data set is based on an unreleased working version of the Gridded Population of the World (GPW), Version 4, year 2010 population count raster but at a coarser 5 arc-minute resolution. Bryan Jones of Baruch College produced country-level projections based on the Shared Socioeconomic Pathway 4 (SSP4). SSP4 reflects a divided world where cities that have relatively high standards of living, are attractive to internal and international migrants. In low income countries, rapidly growing rural populations live on shrinking areas of arable land due to both high population pressure and expansion of large-scale mechanized farming by international agricultural firms. This pressure induces large migration flow to the cities, contributing to fast urbanization, although urban areas do not provide many opportUnities for the poor and there is a massive expansion of slums and squatter settlements. This scenario may not be the most likely for the West Africa region, but it has internal coherence and is at least plausible.

These files contain the key distribution metrics of center of gravity, range limits, and depth for each species in the portal. This data set covers 8 regions of the United States: Northeast, Southeast, Gulf of Mexico, West Coast, Bering Sea, Aleutian Islands, Gulf of Alaska, and Hawai'i Islands.

The West Africa Coastal Vulnerability Mapping: Demographic and Health Survey Data Sets present grids of maternal education levels and household wealth based on Demographic and Health Survey (DHS) cluster level data for ten West African countries. While the maternal education levels are comparable across countries, owing to different underlying indicators, the household wealth index is not. Education can directly influence risk perception, skills and knowledge and indirectly reduce poverty, improve health, and promote access to information and resources. When facing natural hazards or climate risks, educated individuals, households, and societies are assumed to be more empowered and more adaptive in their response to, preparation for, and recovery from disasters. Education is a key background indicator that helps contextualize a country's health and development situation. The household wealth index is a composite measure of a household's cumulative living standard. The wealth index is calculated using easy-to-collect data on a household's ownership of selected assets, such as televisions and bicycles, materials used for housing construction, and types of water access and sanitation facilities. Bayesian spatial interpolation methods were employed to create country level grids based on DHS cluster point data for each country. Data are from the following dates by country: Benin (2006), Cameroon (2011), Cote d'Ivoire (2012), Ghana (2008), Guinea (2012), Liberia (2011), Nigeria (2010), Sierra Leone (2008), and Togo (1998).

Content

Population density is a measure of average population per square mile. Density levels have been higher across the Eastern seaboard and the Pacific coastline and lower in much of the West.

Acknowledgements

Data was taken from the USA Government 2010 Census.

The West Africa Coastal Vulnerability Mapping: Social Vulnerability Indices data set includes three indices: Social Vulnerability, Population Exposure, and Poverty and Adaptive Capacity. The Social Vulnerability Index (SVI) was developed using six indicators: population density (2010), population growth (2000-2010), subnational poverty and extreme poverty (2005), maternal education levels circa 2008, market accessibility (travel time to markets) circa 2000, and conflict data for political violence (1997-2013). Because areas of high population density and growth (high vulnerability) are generally associated with urban areas that have lower levels of poverty and higher degrees of adaptive capacity (low vulnerability), to some degree, the population factors cancel out the poverty and adaptive capacity indicators. To account for this, the data set includes two sub-indices, a Population Exposure Index (PEI), which only includes population density and population growth; and a Poverty and Adaptive Capacity Index (PACI), composed of subnational poverty, maternal education levels, market accessibility, and conflict. These sub-indices are able to isolate the population indicators from the poverty and conflict metrics. The indices represent Social Vulnerability in the West Africa region within 200 kilometers of the coast.

SFWMD has compiled this dataset from information submitted by the utilities and verified by staff. This data is updated by SFWMD's water supply planning regions in 5 year cycles. This dataset represents the utilities best estimate of current and additional future served areas. Each region's planning cycle is typically projected 20 to 25 years in the future. The primary purpose of this dataset is to determine future population and associated water use demands, and to prepare maps in support of Water Supply Plan updates for the South Florida Water Management District's five regional planning areas (Lower West Coast, Upper East Coast, Lower East Coast, Lower Kissimmee Basin and the Central Florida Water Initiative (CFWI).

Transient killers whales inhabit the West Coast of the United States. Their range and movement patterns are difficult to ascertain, but are vital to understanding killer whale population dynamics and abundance trends. Satellite tagging of West Coast transient killer whales to determine range and movement patterns will provide data to assist in understanding transient killer whale populations. Locational data.

The dataset includes age- and length-based catch per unit effort data for commercial fish species collected during the Scottish West Coast Bottom Trawl Survey. This is a new survey from 2011, replacing the historical DATRAS SWC-IBTS dataset

The West Africa Coastal Vulnerability Mapping: GPW Version 4 Population Density, Preliminary Release 1, 2010, represents the number of persons per square kilometer, and was calculated by dividing an unreleased working version of the Gridded Population of the World (GPW), Version 4, year 2010 population count raster for the West Africa region by a land area raster and cropping the result to within 200 kilometers of the coast. GPW provides globally consistent and spatially explicit human population information and data for use in research, policy making, and communications. This is a gridded (raster) data product that renders global population data at the scale and extent required to demonstrate the spatial relationship of human populations and the environment across the globe. The gridded data set is constructed from national or subnational input Units (usually administrative Units) of varying resolutions. The native grid cell resolution of GPWv4 is 30 arc-second, or ~1 km at the equator.

Dedicated version of the StreamNet Coordinated Assessments Population Boundaries Layer for puposes of supporing the MAFAC Dashboard. This version carries some custom attributes used to drive dashboard interactivity. This version is derived from the Coordinated Assessments Population Boundaries Layers which originates from NOAA's official Population Boundaries dataset, aka ESA Species Ranges (WCR). For those Northwest Salmon Populations that have been officially defined by NOAA's Technical Recovery Team (TRT) led process, PSFMC/StreamNet strives to keep boundaries and core attributes in synch with the official NOAA dataset for the West Coast Region. Main differences between NOAA's dataset and this modified version include: 1) The addition of some value added attributes developed to support the Coordinated Assessments Project, 2) The addition of some non-listed, non-TRT populations to support the sharing of data among partners for species of concern. For these non-TRT populations, the [GIS_Source] field identifies the source agency and basis for defining the boundary. In most cases, the geometry is derived from WBD ridgelines, 3) The addition of 'Super Populations' which are aggregations of both TRT and non-TRT defined populations and include groupings such as Marine Fisheries Advisory Committee (MAFAC) Stocks that are useful for reporting and data filtering purposes to support a number of fisheries management and recovery planning initiatives. NOTE: Population attributes presented here were joined to the GIS Dataset from the "Populations" table in the StreamNet_API database where core attributes are collaboratively managed and edited by StreamNet partners. [PopID] serves as the foreign key between the spatial and tabular database. Attributes were last joined and updated on June 30, 2023. See the full metadata record for additional details about these particular data. StreamNet is a cooperative information management and data dissemination project focused on fisheries and aquatic data and data-related services in the Pacific Northwest, with a focus on the Columbia River Basin. The Coordinated Assessments Partnership (CAP) is a collaborative process to efficiently share and provide access to standardized derived information, such as fish population-scale high-level indicators (HLIs) and supporting metrics.

The West Africa Coastal Vulnerability Mapping: Economic Systems Index is a composite index based on several spatial indicators, including gridded Gross Domestic Product (GDP), nighttime lights as a proxy for urban built-up and industrial areas, and cocoa, coconut, palm oil, rubber, and banana production in metric tons. It covers the coastal region of West Africa within 200 km of the coast. Population growth in the coastal zone is mostly a function of migration related to coastal economic activities; this indicator provides insights into highly exposed coastal areas that not only have high levels of economic activity but also high population growth and migration.

SFWMD has compiled this dataset from information submitted by the utilities and verified by staff. This data is updated by SFWMD's water supply planning regions in 5 year cycles. Utility service area boundaries may also receive updates during the annual WaSUP process implemented by the Water Supply Bureau. The primary purpose of this dataset is to determine current population and associated water use demands, and to prepare maps in support of Water Supply Plan updates for the South Florida Water Management District's five regional planning areas (Lower West Coast, Upper East Coast, Lower East Coast, Lower Kissimmee Basin and the Central Florida Water Initiative (CFWI). Note, a utility may or may not have a larger permitted area/franchise area than the actual areas currently served. To view the full permitted boundaries, please refer to the SFWMD Regulation Water Use Permit datasets.

These files contain the spatial boundaries of the NOAA Fisheries Bottom-trawl surveys. This data set covers 8 regions of the United States: Northeast, Southeast, Gulf of Mexico, West Coast, Bering Sea, Aleutian Islands, Gulf of Alaska, and Hawai'i Islands.

This data set contains observations of dead or alive harbor porpoises made by the public, mostly around the Swedish coast. A few observations are from Norwegian, Danish, Finish and German waters. Each observation of harbor porpoise is verified at the Swedish Museum of Natural History before it is approved and published on the web. The verification consists of controlling the accuracy of number of animals sighted, if the coordinates are correct and if pictures are attached that they really show a porpoise and not another species. If any of these three seem unlikely, the reporter is contacted and asked more detailed questions. The report is approved or denied depending on the answers given. Pictures and movies that can’t be uploaded to the database due to size problems are saved at the museum server and marked with the identification number given by the database. By the end of the year the data is submitted to HELCOM who then summarize all the member state’s data from the Baltic proper to the Kattegat basin.

The porpoise is one of the smallest tooth whales in the world and the only whale species that breeds in Swedish waters. They are to be found in temperate water in the northern hemisphere where they live in small groups of 1-3 individuals. The females give birth to a calf in the summer months which then suckles for about 10 months before it is left on its own and she has a new calf. The porpoises around Sweden are divided in to three groups that don’t mix very often. The North Sea population is found on the west coast in Skagerrak down to the Falkenberg area. The Belt Sea population is to be found a bit north of Falkenberg down to Blekinge archipelago in the Baltic. The Baltic proper population is the smallest population and consists only of a few hundred animals and is considered as an endangered sub species. They are most commonly found from the Blekinge archipelago up to Åland Sea with a hot spot area south of Gotland at Hoburg’s bank and the Mid-Sea bank.

The Porpoise Observation Database was started in 2005 at the request of the Swedish Environmental Protection Agency to get a better understanding of where to find porpoises with the idea to use the public to expand the “survey area”. The first year 26 sightings were reported, where 4 was from the Baltic Sea. The museum is particularly interested in sightings from the Baltic Sea due to the low numbers of animals and lack of data and knowledge about this group. In the beginning only live sightings were reported but later also found dead animals were added.

Some of the animals that are reported dead are collected. Depending on where it is found and its state of decay, the animal can be subsampled in the field. A piece of blubber and some teeth are then send in by mail and stored in the Environmental Specimen Bank at the Swedish Museum of Natural History in Stockholm. If the whole animal is collected an autopsy is performed at the National Veterinary Institute in Uppsala to try and determine cause of death. Organs, teeth and parasites are sampled and saved at the Environmental Specimen Bank as well. Information about the animal i.e. location, founding date, sex, age, length, weight, blubber thickness as well as type of organ and the amount that is sampled is then added to the Specimen Bank database. If there is an interest in getting samples or data from the Specimen Bank, one have to send in an application to the Department of Environmental research and monitoring and state the purpose of the study and the amount of samples needed.

Original provider: Cascadia Research Collective

Dataset credits: Cascadia Research

Abstract: This dataset consists of 6,560 sighting records, including at least 1,803 uniquely identified blue whales. These were collected by Cascadia Research and collaborators from the eastern North Pacific from 1975 through 2004 (data collection is continuing). The primary extent of this dataset includes waters off California, Oregon, and Washington from 1986 to 2004, which accounts for over 6,000 of the records. Additional sighting records are from other regions of the North Pacific including the Eastern Tropical Pacific, British Columbia, and Alaska. These data represent the most extensive database of blue whale sightings available from the waters off the western United States and have provided the primary information available on movements and abundance of eastern North Pacific blue whales. Effort was not evenly distributed throughout the region so sighting locations are biased towards areas of highest effort. ID field links resightings of the same individual.

Purpose: Data were gathered to document movements, population structure and abundance of blue whales in the eastern North Pacific (see Calambokidis and Barlow 2004, Calambokidis and Steiger 1997, Calambokidis et al. 1990).

Supplemental information: Updated on March 30, 2006, expanding the dataset up to 2004.

The Pacific coast population of the western snowy plover (Charadrius alexandrinus nivosus) (western snowy plover) is federally listed as threatened. The current Pacific coast breeding population extends from Damon Point, Washington, south to Bahia Magdalena, Baja California, Mexico (including both Pacific and Gulf of California coasts). The western snowy plover winters mainly in coastal areas from southern Washington to Central America. The primary objective of this recovery plan is to remove the Pacific coast population of the western snowy plover from the List of Endangered and Threatened Wildlife and Plants by: (1) increasing population numbers distributed across the range of the Pacific coast population of the western snowy plover; (2) conducting intensive ongoing management for the species and its habitat and developing mechanisms to ensure management in perpetuity; and (3) monitoring western snowy plover populations and threats to determine success of recovery actions and refine management actions.

Dedicated version of the StreamNet Coordinated Assessments Population Boundaries Layer for puposes of supporing the MAFAC Dashboard. This version carries some custom attributes used to drive dashboard interactivity. This version is derived from the Coordinated Assessments Population Boundaries Layers which originates from NOAA's official Population Boundaries dataset, aka ESA Species Ranges (WCR). For those Northwest Salmon Populations that have been officially defined by NOAA's Technical Recovery Team (TRT) led process, PSFMC/StreamNet strives to keep boundaries and core attributes in synch with the official NOAA dataset for the West Coast Region. Main differences between NOAA's dataset and this modified version include: 1) The addition of some value added attributes developed to support the Coordinated Assessments Project, 2) The addition of some non-listed, non-TRT populations to support the sharing of data among partners for species of concern. For these non-TRT populations, the [GIS_Source] field identifies the source agency and basis for defining the boundary. In most cases, the geometry is derived from WBD ridgelines, 3) The addition of 'Super Populations' which are aggregations of both TRT and non-TRT defined populations and include groupings such as Marine Fisheries Advisory Committee (MAFAC) Stocks that are useful for reporting and data filtering purposes to support a number of fisheries management and recovery planning initiatives. NOTE: Population attributes presented here were joined to the GIS Dataset from the "Populations" table in the StreamNet_API database where core attributes are collaboratively managed and edited by StreamNet partners. [PopID] serves as the foreign key between the spatial and tabular database. Attributes were last joined and updated on June 30, 2023. See the full metadata record for additional details about these particular data. StreamNet is a cooperative information management and data dissemination project focused on fisheries and aquatic data and data-related services in the Pacific Northwest, with a focus on the Columbia River Basin. The Coordinated Assessments Partnership (CAP) is a collaborative process to efficiently share and provide access to standardized derived information, such as fish population-scale high-level indicators (HLIs) and supporting metrics.

Non-native Pacific oyster Magallana gigas (Thunberg, 1793) was introduced to the Mediterranean Sea for aquaculture purposes in the 1960s. Although this species was not introduced for aquaculture to the Croatian part of the Adriatic Sea, in the 1970s, it was reported in the Lim Bay, in the North-eastern Adriatic. Until recently, there has been no research on the species in the Croatian part of the Adriatic. The aim of this research was to summarize existing and novel data on the distribution of M. gigas in coastal areas of the Eastern Adriatic and to provide a baseline for the future monitoring and assessment programmes of the species. Distribution of M. gigas was determined by three different methods: (i) a visual census of the presence of M. gigas specimens in the medio-littoral zone; (ii) DNA identification of M. gigas larvae in the water column; and (iii) the presence of M. gigas in the subtidal zone at 25 to 40 m depth. Magallana gigas has a well-established population in the medio-littoral zone of natural and anthropogenic habitats along the coast of the North-eastern Adriatic Sea (west coast of Istria), but it is not present in the deeper layers (25 - 40m). In the Central-eastern and South-eastern Adriatic Sea, the species was either absent or sporadically recorded with no evidence of fully established populations. Considering the great invasion success of M. gigas worldwide and effects that this species could have on the invaded ecosystem (e.g. competition for food and space with native species), detailed future monitoring are needed for the Eastern Adriatic Sea.