This statistic shows the change in the regional distribution of the U.S. population each decade from 1790 to 2021. In 2021, 17.2 percent of the population in the United States lived in the Northeast.

Since the turn of the century, the United States has undergone a redistribution of population from rural and rust belt counties to urban counties; particularly those along the Northern and Southern Atlantic Seaboard, the Pacific Coast and parts of the Southwest region. 41 percent or 1,295 counties had population declines from 2000 to 2016, with 15 counties experiencing declines of more than 25,000 people or 2.4 percent of the total population.Over the same period, total population for the nation grew by 42 million, 8 percent of which has migrated from declining rural and rust belt counties to growing urban counties along the East and West Coast, and in the Southwest, resulting in a 23 percent increase in population occurring in 60 percent of counties in the United States. The data indicates that the majority of this growth is occurring in just 12 percent of counties, including the San Francisco Bay Region which has experienced a 2.4 percent increase in population.

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.

NOAA Fisheries and its partners conduct fisheries-independent surveys in 8 regions in the US (Northeast, Southeast, Gulf of Mexico, West Coast, Gulf of Alaska, Bering Sea, Aleutian Islands, Hawai’i Islands). These surveys are designed to collect information on the seasonal distribution, relative abundance, and biodiversity of fish and invertebrate species found in U.S. waters. Over 900 species of fish and invertebrates have been identified in these surveys.

NOAA Fisheries and its partners conduct fisheries-independent surveys in 8 regions in the US (Northeast, Southeast, Gulf of Mexico, West Coast, Gulf of Alaska, Bering Sea, Aleutian Islands, Hawai’i Islands). These surveys are designed to collect information on the seasonal distribution, relative abundance, and biodiversity of fish and invertebrate species found in U.S. waters. Over 900 species of fish and invertebrates have been identified in these surveys.

NOAA Fisheries and its partners conduct fisheries-independent surveys in 8 regions in the US (Northeast, Southeast, Gulf of Mexico, West Coast, Gulf of Alaska, Bering Sea, Aleutian Islands, Hawai’i Islands). These surveys are designed to collect information on the seasonal distribution, relative abundance, and biodiversity of fish and invertebrate species found in U.S. waters. Over 900 species of fish and invertebrates have been identified in these surveys.

This is a feature layer created from the Survey123 form to collect a baseline of data for the SNPL during annual window surveys. This data is designed for use across the entire west coast portion of the species range, in collaboration with partners and cooperators. The form was created based on an initial version that was field tested in Recovery Unit 2. This form will similarly be tested across the range for it's field usability and data format creation. The intent is to continue to take feedback and improve the form for use across all recovery units.Western Snowy Plover (Charadrius nivosus nivosus; plover) Census and Monitoring Surveys – United States Fish and Wildlife Service (Service). This project focuses on electronic data collection (using Survey123) for Western Snowy Plover annual monitoring surveys in all Recovery Units (1-6) which covers coastal California, Oregon and Washington.The plover was listed as a federally threatened species under the Endangered Species Act in 1993. The U.S. Fish and Wildlife Service’s Western Snowy Plover Pacific Coast Population Recovery Plan was published in 2007. The 2007 Recovery Plan provides reasonable actions believed to be required to recover and/or protect plovers. The first action needed from the Recovery Plan is to monitor breeding and wintering populations and habitats of the Pacific coast population of the western snowy plover to determine progress of recovery actions to maximize survival and productivity. The census and monitoring surveys are critical data for determining if the recovery criteria have been met. Recovery criteria for delisting the plover includes: 1) An average of 3,000 breeding adults has been maintained for 10 years and 2) A yearly average productivity of at least one (1.0) fledged chick per male has been maintained in each recovery unit in the last 5 years prior to delisting. The survey effort is a collaboration between multiple FWS Field Offices, contracted partners, and official volunteers.For more information:Here is a direct link to the Data Management Plan for this project, the ServCat reference page, the Survey123 link, and a link to the relevant program page for Arcata Fish & Wildlife Office.

Biologically important areas (BIAs) for cetaceans were defined by compiling the best available information from scientific literature (including books, peer-reviewed articles, and government or contract reports), unpublished data (sighting, acoustic, tagging, genetic, photo identification), and expert knowledge. This information was then used to create written summaries and maps highlighting areas shoreward of the U.S. Exclusive Economic Zone that are biologically important to cetacean species (or populations), either seasonally or year-round. This collection contains the data displayed by BIA type, including feeding, migratory corridors, reproduction, and small and resident populations. Feeding BIAs include areas and months within which a particular species or population selectively feeds. These may either be found consistently in space and time, or may be associated with ephemeral features that are less predictable but can be delineated and are generally located within a larger identifiable area. Migratory Corridor BIAs include areas and months within which a substantial portion of a species or population is known to migrate. Reproduction BIAs include areas and months within which a particular species or population selectively mates, gives birth, or is found with neonates or other sensitive age classes. Small and Resident Population BIAs include areas and months within which small and resident populations occupy a limited geographic extent.

A growing body of evidence suggests that spatial population structure can develop in marine species despite large population sizes and high gene flow. Characterizing population structure is important for the effective management of exploited species, as it can be used to identify appropriate scales of management in fishery and aquaculture contexts. The California sea cucumber, Apostichopus californicus, is one such exploited species whose management could benefit from further characterization of population structure. Using restriction site-associated DNA (RAD) sequencing, we developed 2,075 single nucleotide polymorphisms (SNPs) to quantify genetic structure over a broad section of the species’ range along the North American west coast and within the Salish Sea, a region supporting the Washington State A. californicus fishery and developing aquaculture production of the species. We found evidence for population structure (global fixation index (FST) = 0.0068) with limited dispersal driving two patterns of differentiation: isolation-by-distance and a latitudinal gradient of differentiation. Notably, we found detectable population differences among collection sites within the Salish Sea (pairwise FST = 0.001–0.006). Using FST outlier detection and gene-environment association, we identified 10.2% of total SNPs as putatively adaptive. Environmental variables (e.g., temperature, salinity) from the sea surface were more correlated with genetic variation than those same variables measured near the benthos, suggesting that selection on pelagic larvae may drive adaptive differentiation to a greater degree than selection on adults. Our results were consistent with previous estimates of, and patterns in, population structure for this species in other extents of the range. Additionally, we found that patterns of neutral and adaptive differentiation co-varied, suggesting that adaptive barriers may limit dispersal. Our study provides guidance to decision-makers regarding the designation of management units for A. californicus and adds to the growing body of literature identifying genetic population differentiation in marine species despite large, nominally connected populations. Methods Approximately 50 adult A. californicus were collected by scuba divers from nine collection sites along the Pacific Coast of North America, ranging from Alaska to Oregon, including four collection sites within the southern Salish Sea. For each animal, a tissue sample was excised from a radial muscle band and stored in 100% ethanol. DNA was extracted from tissue samples using the EZNA Mollusc DNA Kit (OMEGA Bio-tek, Norcross, GA, USA) and the Qiagen DNeasy Kit (Qiagen, Germantown, MD, USA). DNA was quantified using the Quant-iT PicoGreen dsDNA Assay Kit (Thermo Fisher Scientific, Waltham, MA, USA) and DNA quality was checked by gel electrophoresis. DNA concentration was normalized to 500 ng in 20 μL of PCR-grade water. We selected samples with high DNA quality for restriction site associated DNA (RAD) sequencing and RAD libraries were prepared following standard protocols1. Briefly, DNA samples were barcoded with an individual six-base identifier sequence attached to an Illumina P1 adapter. Samples were then pooled into sub-libraries, containing approximately 12 individuals. Sub-libraries were sheared using a Bioruptor sonicator and size selected to 200-400 bp using a MinElute Gel Extraction Kit (Qiagen, Germantown, MD, USA). P2 adapters were ligated to DNA in sub-libraries and amplified with PCR using 12–18 cycles as in Etter et al. (2011). Finally, amplified sub-libraries were combined into pools of approximately 72 individuals. Paired-end 2 x 150-base pair sequencing was performed on an Illumina HiSeq4000 (San Diego, California, USA) at the Beijing Genomics Institute and the University of Oregon Genomics and Cell Characterization Core Facility. Only forward reads were used for analysis. To estimate genotyping error, 14 individuals were sequenced twice. Raw RAD sequencing data were demultiplexed using the process_radtags module in the pipeline STACKS v.1.442. A threshold of 800,000 reads was used to exclude poorly sequenced individuals. Because a genome was not available for A. californicus, we aligned individual sequences to the genome of a closely related species, A. parvimensis (GenBank accession number = GCA_000934455.1). The A. parvimensis genome was 760,654,621 bp, with 21,559 scaffolds and an N50 size of 9,587. We retained reads with a minimum mapping quality score of 20. Then, we used dDocent v.2.7.8 to perform a reference-guided locus assembly using the filtered reads and default parameters3. Additionally, a parallel de novo assembly was performed, which produced nearly identical results for population structure and 1.8–2.8% lower mean expected heterozygosity, 0.9–1.8% higher mean observed heterozygosity, and 1.2–3.3% higher proportions of polymorphic SNPs than in the with-reference assembly, although with similar patterns across collection sites. The reference-guided assembly was retained for further analyses due to decreased confidence in identifying genotyping errors in the de novo assembly4. We used vcftools v.0.1.165 to remove indels and to retain only single nucleotide polymorphisms (SNPs) with a minimum quality score of 20, minimum minor allele frequency of 0.05 and maximum missing data per locus of 30% across collection sites. Individuals with more than 30% missing data across SNPs were removed. In cases of multiple SNPs per RAD tag, we retained the SNP with the highest minor allele frequency6. SNPs that were not in Hardy Weinberg Equilibrium (HWE) were considered sequencing errors or poorly assembled loci and were removed from our data set, as selection and inbreeding are unlikely to cause significant deviations from HWE equilibrium at biallelic loci7. We tested SNPs for deviations from HWE using the R package genepop v.1.1.4 (Rousset, 2008). SNPs were identified as being out of HWE if they had a q-value below 0.05 in at least 2 of the collection sites after correcting for false discovery rate, following Waples (2015). We used a suite of R packages, stand-alone software, and custom scripts in the programming language R v.3.5.0 9 to quantify genetic diversity and population structure. Mean expected heterozygosity, observed heterozygosity, and the inbreeding coefficient (FIS) per SNP were calculated using the R package genepop. The proportion of polymorphic SNPs per collection site was calculated using a custom R script. To investigate population structure, we first calculated Weir-Cockerham fixation index (FST)10 to quantify population differentiation using the R packages genepop and hierfstat v.0.5.7. Exact G-tests11 were used to test for significant genic differentiation using the R package genepop. To investigate patterns of spatial differentiation among collection sites, the R package adegenet v.2.1.112 was used to conduct discriminant analyses of principal components (DAPC), a multivariate method that summarizes the between-group variation (i.e., population structure), while minimizing within-group variation13. The built-in optimization algorithm was used to retain the number of principal components that minimized over-fitting and under-fitting of the model. To determine the potential number of underlying populations, the program ADMIXTURE v.1.3.0 was used to conduct a clustering analysis14. Specifically, ADMIXTURE uses a maximum likelihood-based approach to estimate individual ancestries across different assumed numbers of populations, with the best fit selected using cross-validation. To examine the presence of hierarchical population structure, we conducted analyses of molecular variance (AMOVA) using the ade4 method of the R package poppr v.2.8.115. Significance of AMOVAs was determined using permutation tests with 1,000 iterations. Using AMOVA, we investigated whether the following oceanographic barriers limit dispersal: 1) the Victoria Sill (Victoria Sill grouping), 2) Admiralty Inlet (Admiralty Inlet grouping), and 3) the North Pacific Current (NPC grouping). Because AMOVAs for each oceanographic barrier include sites in an area with other potential oceanographic barriers, we added a fourth grouping of all three oceanographic barriers (All Barriers grouping) to investigate the relative role of oceanographic barriers compared to other factors. Additionally, we conducted an AMOVA by state or province (State grouping). Although not biologically meaningful, we included the State grouping to determine how much genetic variation is captured by regional management boundaries. Isolation-by-distance (IBD) was tested with Mantel tests16 in R as linear correlation between linearized FST17 using all SNPs and shortest Euclidean distance through water (in-water distance hereafter) approximated in Google Maps18 Following Xuereb et al (2018), we also tested IBD in the northern and southern population section separately. Following Buonaccorsi et al. (2005), we estimated mean dispersal distance from the slope of the regression of linearized FST and in-water distance. We used this 1-dimensional model because it is an appropriate approximation for coastal species with dispersal dimensions greater than one dimension of the habitat (e.g., dispersal distance likely greater than water depth for A. californicus). We estimated mean dispersal distance from a set of potential population density estimates as population density estimates were unavailable. We used two approaches to investigate putatively adaptive SNPs: FST outlier detection and gene-environment association. FST outlier detection is used to identify loci potentially under spatial selection20,21, although this method does not identify the potential cause of selection. Although gene-environment association does not explicitly test whether such associations are adaptive, this method is used to identify locus-environment associations as evidence for potential local

Drosophila melanogaster is postulated to have colonized North America in the past several 100 years in two waves. Flies from Europe colonized the east coast United States while flies from Africa inhabited the Caribbean, which if true, make the south-east US and Caribbean Islands a secondary contact zone for African and European D. melanogaster. This scenario has been proposed based on phenotypes and limited genetic data. In our study, we have sequenced individual whole genomes of flies from populations in the south-east US and Caribbean Islands and examined these populations in conjunction with population sequences from the west coast US, Africa, and Europe. We find that west coast US populations are closely related to the European population, likely reflecting a rapid westward expansion upon first settlements into North America. We also find genomic evidence of African and European admixture in south-east US and Caribbean populations, with a clinal pattern of decreasing proportions of ...

This is a feature layer created from the Survey123 form to collect a baseline of data for the Western Snowy Plover during annual window surveys. This data is designed for use across the entire west coast portion of the species range, in collaboration with partners and cooperators. The form was created based on an initial version that was field tested in Recovery Unit 2. This form will similarly be tested across the range for it's field usability and data format creation. The intent is to continue to take feedback and improve the form for use across all recovery units.Western Snowy Plover (Charadrius nivosus nivosus; plover) Census and Monitoring Surveys – United States Fish and Wildlife Service (Service). This project focuses on electronic data collection (using Survey123) for Western Snowy Plover annual monitoring surveys in all Recovery Units (1-6) which covers coastal California, Oregon and Washington.The plover was listed as a federally threatened species under the Endangered Species Act in 1993. The U.S. Fish and Wildlife Service’s Western Snowy Plover Pacific Coast Population Recovery Plan was published in 2007. The 2007 Recovery Plan provides reasonable actions believed to be required to recover and/or protect plovers. The first action needed from the Recovery Plan is to monitor breeding and wintering populations and habitats of the Pacific coast population of the western snowy plover to determine progress of recovery actions to maximize survival and productivity. The census and monitoring surveys are critical data for determining if the recovery criteria have been met. Recovery criteria for delisting the plover includes: 1) An average of 3,000 breeding adults has been maintained for 10 years and 2) A yearly average productivity of at least one (1.0) fledged chick per male has been maintained in each recovery unit in the last 5 years prior to delisting. The survey effort is a collaboration between multiple FWS Field Offices, contracted partners, and official volunteers.For more information:Here is a direct link to the Data Management Plan for this project, the ServCat reference page, the Survey123 link, and a link to the relevant program page for Arcata Fish & Wildlife Office.

The prevailing demographic model for Drosophila melanogaster suggests that the colonization of North America occurred very recently from a subset of European flies that rapidly expanded across the continent. This model implies a sudden population growth and range expansion consistent with very low or no population subdivision. As flies adapt to new environments, local adaptation events may be expected. To describe demographic and selective events during North American colonization, we have generated a data set of 35 individual whole-genome sequences from inbred lines of D. melanogaster from a west coast US population (Winters, California, USA) and compared them with a public genome data set from Raleigh (Raleigh, North Carolina, USA). We analysed nuclear and mitochondrial genomes and described levels of variation and divergence within and between these two North American D. melanogaster populations. Both populations exhibit negative values of Tajima's D across the genome, a common signature of demographic expansion. We also detected a low but significant level of genome-wide differentiation between the two populations, as well as multiple allele surfing events, which can be the result of gene drift in local subpopulations on the edge of an expansion wave. In contrast to this genome-wide pattern, we uncovered a 50-kilobase segment in chromosome arm 3L that showed all the hallmarks of a soft selective sweep in both populations. A comparison of allele frequencies within this divergent region among six populations from three continents allowed us to cluster these populations in two differentiated groups, providing evidence for the action of natural selection on a global scale.

NOAA Fisheries and its partners conduct fisheries-independent surveys in 8 regions in the US (Northeast, Southeast, Gulf of Mexico, West Coast, Gulf of Alaska, Bering Sea, Aleutian Islands, Hawai’i Islands). These surveys are designed to collect information on the seasonal distribution, relative abundance, and biodiversity of fish and invertebrate species found in U.S. waters. Over 9...

Patterns of population structure, genetic demographics, and gene flow in the small coastal shark Carcharhinus isodon (finetooth shark) sampled from two discrete nurseries along the southeastern US coast (Atlantic) and three nurseries in the northern Gulf of Mexico (Gulf), were assessed using 16 nuclear-encoded microsatellites and 1077 base pairs of the mitochondrial DNA (mtDNA) control region. Significant heterogeneity in microsatellite allele distributions was detected among all localities except between the two in the Atlantic. Significant heterogeneity in mtDNA haplotypes was not detected, a result likely due to extremely low mtDNA diversity. The genetic discontinuities combined with seasonal movement patterns, a patchy distribution of appropriate nursery habitat, the apparent absence of sex-biased gene flow, and the occurrence of mating in the vicinity of nursery areas, suggest that both male and female finetooth sharks display regional philopatry to discrete nursery areas. Global and local tests of neutrality, using mtDNA haplotypes, and demographic model testing, using Approximate Bayesian Computation of microsatellite alleles, supported a range-wide expansion of finetooth sharks into US waters occurring less than ∼9000 years ago. These findings add to the growing number of studies in a variety of coastally distributed marine fishes documenting significant barriers to gene flow around peninsular Florida and in the eastern Gulf. The findings also provide further evidence that the traditional model of behavioural ecology, based on large coastal sharks, may not be appropriate for understanding and conserving small coastal sharks.

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.

Between the weeks of February 3 and March 9, 2020, the DMA (Designated Market Area) in the United States with the highest increased in viewership of local news on major broadcast networks among adults aged 25 to 54 years old was San Francisco, with a **** percent audience increase in March 2020 compared to the same week in February that year. The coronavirus spread rapidly across the United States in early to mid-March, sparking an increase the number of individuals self-isolating at home, quarantining, and turning to their preferred news sources to keep up to date with the outbreak. The West Coast of the U.S. was hit earlier than other parts of the country, explaining the high viewership increase in the key demographic in San Francisco, LA, and Seattle.

Three approaches used to calculate local limit reference points (LRPs) for western Pacific leatherback turtles in the U.S. West Coast Exclusive Economic Zone (WCEEZ). JMW = Jamursba Medi and Wermon beaches in West Papua, Indonesia, where the vast majority of nesting for boreal-summer-nesting western Pacific leatherbacks occurs. RVLL = Reproductive Value Loss Limit. PBR = Potential Biological Removal.Three approaches to limit reference point calculation.

description: Appendix to the Recovery Plan. Locations of current or historical Snowy Plover breeding and wintering areas. The following maps (Figures A-1 through A-7) show the general locations of current or historical western snowy plover breeding or wintering areas on the U.S. Pacific coast within each recovery unit. The breeding and wintering locations and recovery units include only the coastal beaches, estuaries, gravel bars and salt ponds that provide western snowy plover habitat; inland areas of counties are illustrated on Figures A-1 through A-7 solely for reference. Location numbers on the maps are referenced to the numbers in parentheses shown after the location names found in the left-hand column of Table B-1 (Appendix B) and Table C-1 (Appendix C). Detailed maps of each of these locations are given in Appendix L.; abstract: Appendix to the Recovery Plan. Locations of current or historical Snowy Plover breeding and wintering areas. The following maps (Figures A-1 through A-7) show the general locations of current or historical western snowy plover breeding or wintering areas on the U.S. Pacific coast within each recovery unit. The breeding and wintering locations and recovery units include only the coastal beaches, estuaries, gravel bars and salt ponds that provide western snowy plover habitat; inland areas of counties are illustrated on Figures A-1 through A-7 solely for reference. Location numbers on the maps are referenced to the numbers in parentheses shown after the location names found in the left-hand column of Table B-1 (Appendix B) and Table C-1 (Appendix C). Detailed maps of each of these locations are given in Appendix L.

Population statistics and molecular diversity indexes for Planorbella trivolvis populations in the West Coast, separated by gene and watershed.

Population ΦST values for Planorbella trivolvis populations between watersheds in the West Coast, separated by gene.