In the past four centuries, the population of the Thirteen Colonies and United States of America has grown from a recorded 350 people around the Jamestown colony in Virginia in 1610, to an estimated 346 million in 2025. While the fertility rate has now dropped well below replacement level, and the population is on track to go into a natural decline in the 2040s, projected high net immigration rates mean the population will continue growing well into the next century, crossing the 400 million mark in the 2070s. Indigenous population Early population figures for the Thirteen Colonies and United States come with certain caveats. Official records excluded the indigenous population, and they generally remained excluded until the late 1800s. In 1500, in the first decade of European colonization of the Americas, the native population living within the modern U.S. borders was believed to be around 1.9 million people. The spread of Old World diseases, such as smallpox, measles, and influenza, to biologically defenseless populations in the New World then wreaked havoc across the continent, often wiping out large portions of the population in areas that had not yet made contact with Europeans. By the time of Jamestown's founding in 1607, it is believed the native population within current U.S. borders had dropped by almost 60 percent. As the U.S. expanded, indigenous populations were largely still excluded from population figures as they were driven westward, however taxpaying Natives were included in the census from 1870 to 1890, before all were included thereafter. It should be noted that estimates for indigenous populations in the Americas vary significantly by source and time period. Migration and expansion fuels population growth The arrival of European settlers and African slaves was the key driver of population growth in North America in the 17th century. Settlers from Britain were the dominant group in the Thirteen Colonies, before settlers from elsewhere in Europe, particularly Germany and Ireland, made a large impact in the mid-19th century. By the end of the 19th century, improvements in transport technology and increasing economic opportunities saw migration to the United States increase further, particularly from southern and Eastern Europe, and in the first decade of the 1900s the number of migrants to the U.S. exceeded one million people in some years. It is also estimated that almost 400,000 African slaves were transported directly across the Atlantic to mainland North America between 1500 and 1866 (although the importation of slaves was abolished in 1808). Blacks made up a much larger share of the population before slavery's abolition. Twentieth and twenty-first century The U.S. population has grown steadily since 1900, reaching one hundred million in the 1910s, two hundred million in the 1960s, and three hundred million in 2007. Since WWII, the U.S. has established itself as the world's foremost superpower, with the world's largest economy, and most powerful military. This growth in prosperity has been accompanied by increases in living standards, particularly through medical advances, infrastructure improvements, clean water accessibility. These have all contributed to higher infant and child survival rates, as well as an increase in life expectancy (doubling from roughly 40 to 80 years in the past 150 years), which have also played a large part in population growth. As fertility rates decline and increases in life expectancy slows, migration remains the largest factor in population growth. Since the 1960s, Latin America has now become the most common origin for migrants in the U.S., while immigration rates from Asia have also increased significantly. It remains to be seen how immigration restrictions of the current administration affect long-term population projections for the United States.

The world's population first reached one billion people in 1805, and reached eight billion in 2022, and will peak at almost 10.2 billion by the end of the century. Although it took thousands of years to reach one billion people, it did so at the beginning of a phenomenon known as the demographic transition; from this point onwards, population growth has skyrocketed, and since the 1960s the population has increased by one billion people every 12 to 15 years. The demographic transition sees a sharp drop in mortality due to factors such as vaccination, sanitation, and improved food supply; the population boom that follows is due to increased survival rates among children and higher life expectancy among the general population; and fertility then drops in response to this population growth. Regional differences The demographic transition is a global phenomenon, but it has taken place at different times across the world. The industrialized countries of Europe and North America were the first to go through this process, followed by some states in the Western Pacific. Latin America's population then began growing at the turn of the 20th century, but the most significant period of global population growth occurred as Asia progressed in the late-1900s. As of the early 21st century, almost two-thirds of the world's population lives in Asia, although this is set to change significantly in the coming decades. Future growth The growth of Africa's population, particularly in Sub-Saharan Africa, will have the largest impact on global demographics in this century. From 2000 to 2100, it is expected that Africa's population will have increased by a factor of almost five. It overtook Europe in size in the late 1990s, and overtook the Americas a few years later. In contrast to Africa, Europe's population is now in decline, as birth rates are consistently below death rates in many countries, especially in the south and east, resulting in natural population decline. Similarly, the population of the Americas and Asia are expected to go into decline in the second half of this century, and only Oceania's population will still be growing alongside Africa. By 2100, the world's population will have over three billion more than today, with the vast majority of this concentrated in Africa. Demographers predict that climate change is exacerbating many of the challenges that currently hinder progress in Africa, such as political and food instability; if Africa's transition is prolonged, then it may result in further population growth that would place a strain on the region's resources, however, curbing this growth earlier would alleviate some of the pressure created by climate change.

About this dataset

Context

The dataset tabulates the American Fork population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of American Fork across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of American Fork was 38,549, a 3.46% increase year-by-year from 2022. Previously, in 2022, American Fork population was 37,260, an increase of 8.19% compared to a population of 34,439 in 2021. Over the last 20 plus years, between 2000 and 2023, population of American Fork increased by 16,007. In this period, the peak population was 38,549 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the American Fork is shown in this column.
• Year on Year Change: This column displays the change in American Fork population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for American Fork Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Young America township population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Young America township across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Young America township was 679, a 0.29% decrease year-by-year from 2021. Previously, in 2021, Young America township population was 681, an increase of 0.15% compared to a population of 680 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Young America township decreased by 153. In this period, the peak population was 876 in the year 2009. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Young America township is shown in this column.
• Year on Year Change: This column displays the change in Young America township population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Young America township Population by Year. You can refer the same here

Graph and download economic data for Population, Total for United States (POPTOTUSA647NWDB) from 1960 to 2024 about population and USA.

Graph and download economic data for Population Growth for the United States (SPPOPGROWUSA) from 1961 to 2024 about population, rate, and USA.

In 2023, about 17.7 percent of the American population was 65 years old or over; an increase from the last few years and a figure which is expected to reach 22.8 percent by 2050. This is a significant increase from 1950, when only eight percent of the population was 65 or over. A rapidly aging population In recent years, the aging population of the United States has come into focus as a cause for concern, as the nature of work and retirement is expected to change to keep up. If a population is expected to live longer than the generations before, the economy will have to change as well to fulfill the needs of the citizens. In addition, the birth rate in the U.S. has been falling over the last 20 years, meaning that there are not as many young people to replace the individuals leaving the workforce. The future population It’s not only the American population that is aging -- the global population is, too. By 2025, the median age of the global workforce is expected to be 39.6 years, up from 33.8 years in 1990. Additionally, it is projected that there will be over three million people worldwide aged 100 years and over by 2050.

This graph shows the population of the U.S. by race and ethnic group from 2000 to 2023. In 2023, there were around 21.39 million people of Asian origin living in the United States. A ranking of the most spoken languages across the world can be accessed here. U.S. populationCurrently, the white population makes up the vast majority of the United States’ population, accounting for some 252.07 million people in 2023. This ethnicity group contributes to the highest share of the population in every region, but is especially noticeable in the Midwestern region. The Black or African American resident population totaled 45.76 million people in the same year. The overall population in the United States is expected to increase annually from 2022, with the 320.92 million people in 2015 expected to rise to 341.69 million people by 2027. Thus, population densities have also increased, totaling 36.3 inhabitants per square kilometer as of 2021. Despite being one of the most populous countries in the world, following China and India, the United States is not even among the top 150 most densely populated countries due to its large land mass. Monaco is the most densely populated country in the world and has a population density of 24,621.5 inhabitants per square kilometer as of 2021. As population numbers in the U.S. continues to grow, the Hispanic population has also seen a similar trend from 35.7 million inhabitants in the country in 2000 to some 62.65 million inhabitants in 2021. This growing population group is a significant source of population growth in the country due to both high immigration and birth rates. The United States is one of the most racially diverse countries in the world.

About this dataset

Context

The dataset tabulates the American Canyon population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of American Canyon across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of American Canyon was 21,432, a 0.79% decrease year-by-year from 2021. Previously, in 2021, American Canyon population was 21,602, a decline of 0.80% compared to a population of 21,777 in 2020. Over the last 20 plus years, between 2000 and 2022, population of American Canyon increased by 11,486. In this period, the peak population was 21,777 in the year 2020. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the American Canyon is shown in this column.
• Year on Year Change: This column displays the change in American Canyon population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for American Canyon Population by Year. You can refer the same here

This statistic depicts the age distribution in the United States from 2014 to 2024. In 2024, about 17.32 percent of the U.S. population fell into the 0-14 year category, 64.75 percent into the 15-64 age group and 17.93 percent of the population were over 65 years of age. The increasing population of the United States The United States of America is one of the most populated countries in the world, trailing just behind China and India. A total population count of around 320 million inhabitants and a more-or-less steady population growth over the past decade indicate that the country has steadily improved its living conditions and standards for the population. Leading healthier lifestyles and improved living conditions have resulted in a steady increase of the life expectancy at birth in the United States. Life expectancies of men and women at birth in the United States were at a record high in 2012. Furthermore, a constant fertility rate in recent years and a decrease in the death rate and infant mortality, all due to the improved standard of living and health care conditions, have helped not only the American population to increase but as a result, the share of the population younger than 15 and older than 65 years has also increased in recent years, as can be seen above.

In 2023, the annual population growth in the United States stood at 0.49 percent. Between 1961 and 2023, the figure dropped by 1.17 percentage points, though the decline followed an uneven course rather than a steady trajectory.

Bumble bees (Bombus) are vitally important pollinators of wild plants and agricultural crops worldwide. Fragmentary observations, however, have suggested population declines in several North American species. Despite rising concern over these observations in the United States, highlighted in a recent National Academy of Sciences report, a national assessment of the geographic scope and possible causal factors of bumble bee decline is lacking. Here, we report results of a 3-y interdisciplinary study of changing distributions, population genetic structure, and levels of pathogen infection in bumble bee populations across the United States. We compare current and historical distributions of eight species, compiling a database of >73,000 museum records for comparison with data from intensive nationwide surveys of >16,000 specimens. We show that the relative abundances of four species have declined by up to 96% and that their surveyed geographic ranges have contracted by 23–87%, some within the last 20 y. We also show that declining populations have significantly higher infection levels of the microsporidian pathogen Nosema bombi and lower genetic diversity compared with co-occurring populations of the stable (nondeclining) species. Higher pathogen prevalence and reduced genetic diversity are, thus, realistic predictors of these alarming patterns of decline in North America, although cause and effect remain uncertain. Bumble bees (Bombus) are integral wild pollinators within native plant communities throughout temperate ecosystems, and recent domestication has boosted their economic importance in crop pollination to a level surpassed only by the honey bee. Their robust size, long tongues, and buzz-pollination behavior (high-frequency buzzing to release pollen from flowers) significantly increase the efficiency of pollen transfer in multibillion dollar crops such as tomatoes and berries. Disturbing reports of bumble bee population declines in Europe have recently spilled over into North America, fueling environmental and economic concerns of global decline. However, the evidence for large-scale range reductions across North America is lacking. Many reports of decline are unpublished, and the few published studies are limited to independent local surveys in northern California/southern Oregon, Ontario, Canada, and Illinois. Furthermore, causal factors leading to the alleged decline of bumble bee populations in North America remain speculative. One compelling but untested hypothesis for the cause of decline in the United States entails the spread of a putatively introduced pathogen, Nosema bombi, which is an obligate intracellular microsporidian parasite found commonly in bumble bees throughout Europe but largely unstudied in North America. Pathogenic effects of N. bombi may vary depending on the host species and reproductive caste and include reductions in colony growth and individual life span and fitness. Population genetic factors could also play a role in Bombus population decline. For instance, small effective population sizes and reduced gene flow among fragmented habitats can result in losses of genetic diversity with negative consequences, and the detrimental impacts of these genetic factors can be especially intensified in bees. Population genetic studies of Bombus are rare worldwide. A single study in the United States identified lower genetic diversity and elevated genetic differentiation (FST) among Illinois populations of the putatively declining B. pensylvanicus relative to those of a codistributed stable species. Similar patterns have been observed in comparative studies of some European species, but most investigations have been geographically restricted and based on limited sampling within and among populations. Although the investigations to date have provided important information on the increasing rarity of some bumble bee species in local populations, the different survey protocols and limited geographic scope of these studies cannot fully capture the general patterns necessary to evaluate the underlying processes or overall gravity of declines. Furthermore, valid tests of the N. bombi hypothesis and its risk to populations across North America call for data on its geographic distribution and infection prevalence among species. Likewise, testing the general importance of population genetic factors in bumble bee decline requires genetic comparisons derived from sampling of multiple stable and declining populations on a large geographic scale. From such range-wide comparisons, we provide incontrovertible evidence that multiple Bombus species have experienced sharp population declines at the national level. We also show that declining populations are associated with both high N. bombi infection levels and low genetic diversity. This data was used in the paper "Patterns of widespread decline in North American bumble bees" published in the Proceedings of the National Academy of United States of America. For more information about this dataset contact: Sydney A. Cameron: scameron@life.illinois.edu James Strange: James.Strange@ars.usda.gov Resources in this dataset:Resource Title: Data from: Patterns of Widespread Decline in North American Bumble Bees (Data Dictionary). File Name: meta.xmlResource Description: This is an XML data dictionary for Data from: Patterns of Widespread Decline in North American Bumble Bees.Resource Title: Patterns of Widespread Decline in North American Bumble Bees (DWC Archive). File Name: occurrence.csvResource Description: File modified to remove fields with no recorded values.Resource Title: Patterns of Widespread Decline in North American Bumble Bees (DWC Archive). File Name: dwca-usda-ars-patternsofwidespreaddecline-bumblebees-v1.1.zipResource Description: Data from: Patterns of Widespread Decline in North American Bumble Bees -- this is a Darwin Core Archive file. The Darwin Core Archive is a zip file that contains three documents. The occurrence data is stored in the occurrence.txt file. The metadata that describes the columns of this document is called meta.xml. This document is also the data dictionary for this dataset. The metadata that describes the dataset, including author and contact information for this dataset is called eml.xml. Find the data files at https://bison.usgs.gov/ipt/resource?r=usda-ars-patternsofwidespreaddecline-bumblebees

Infectious diseases can cause steep declines in wildlife populations, leading to changes in genetic diversity that may affect the susceptibility of individuals to infection and the overall resilience of populations to pathogen outbreaks. Here, we examine evidence for a genetic bottleneck in a population of American crows (Corvus brachyrhynchos) before and after the emergence of West Nile virus (WNV). More than 50% of marked birds in this population were lost over the two-year period of the epizootic, representing a 10-fold increase in adult mortality. Using analyses of SNPs and microsatellite markers, we tested for evidence of a genetic bottleneck and compared levels of inbreeding and immigration in the pre- and post-WNV populations. Counter to expectations, genetic diversity (allelic diversity and the number of new alleles) increased after WNV emergence. This was likely due to increases in immigration, as the estimated membership coefficients were lower in the post-WNV population. Simultaneously, however, the frequency of inbreeding appeared to increase: mean inbreeding coefficients were higher among SNP markers, and heterozygosity-heterozygosity correlations were stronger among microsatellite markers, in the post-WNV population. These results indicate that loss of genetic diversity at the population level is not an inevitable consequence of a population decline, particularly in the presence of gene flow. The changes observed in post-WNV crows could have very different implications for their response to future pathogen risks, potentially making the population as a whole more resilient to a changing pathogen community, while increasing the frequency of inbred individuals with elevated susceptibility to disease. Methods Study population and data collection. Crows in the Ithaca, New York, population are cooperative breeders. They live in groups of up to 14 birds, including a socially bonded pair of adults as well as 0-12 auxiliary birds, which are usually offspring from previous broods). Although auxiliaries usually do not contribute offspring to the brood, molecular work in the post-WNV population indicates that auxiliary males occasionally do sire extra-pair offspring with the female breeder, arising both through incest (mothers mating with their adult auxiliary sons) and through matings between non-relatives (e.g., unrelated step-mothers and adult auxiliary males). Genetic samples were collected from crow nestlings from 1990–2011. We collected blood (~150 ul) from the brachial vein of nestlings and banded them with unique combinations of metal bands, color bands, and patagial tags on days 24–30 after hatching. DNA was extracted from samples using DNeasy tissue kits (Qiagen, Valencia, CA) following the manufacturer’s protocol. All fieldwork with American crows was carried out under protocols approved by the Institutional Animal Care and Use Committees of Binghamton University (no. 537-03 and 607-07) and Cornell University (no. 1988–0210). The pre-WNV dataset included samples collected between 1990 and 2002. The 2002 nestlings were sampled prior to WNV emergence, as nestlings fledge the nest between May and July, whereas WNV mortality typically occurs between August and October in this crow population. The post-WNV samples were collected between 2005 and 2011. Samples collected immediately after WNV emergence (2003 and 2004) were not included in the analysis to allow time for the birds to respond to the population loss. We maximized independence of the birds selected for analysis by including only one randomly chosen offspring per brood and no more than two broods per family group in the pre-and post-WNV samples, with each brood per family group separated by the maximum number of years possible within the pre- or post-WNV sampling periods (1990–2002 pre-WNV; 2005–2011 post-WNV; Figure S1). Birds were randomly and independently selected (with replacement) for the SNP and microsatellite analyses; therefore, there was little overlap among individual birds included in these marker sets. Of the 286 individual birds included in this analysis, 22 were common to both marker sets (15 pre-WNV; 7 post-WNV). The 20-year time period of this study may have encompassed 2–4 breeding cohorts (approximately 1–2 pre- and 1–2 post-WNV, with a sharp turn-over immediately after WNV emergence). Crows can produce offspring as early as two years after hatching, but most do not begin breeding independently until at least 3–4 years after hatching. Breeding initiation is limited at least in part by breeding vacancies, which are created by the death of one or both members of an established breeding pair. Such breeding vacancies likely increased in availability after the emergence of WNV. Microsatellite genotyping. A total of 222 crows (n = 113 and 109 crows pre- and post-WNV, respectively) were genotyped at 34 polymorphic microsatellite loci that were optimized for American crows. Alleles were scored using the microsatellite plugin for Geneious 9.1.8. We used GenePop version 4.7 to test for linkage disequilibrium between all pairs of loci, departures from Hardy–Weinberg equilibrium (HWE), and null allele frequency. Locus characteristics (e.g., alleles/ locus, tests of Hardy–Weinberg equilibrium and null allele frequencies) are given in the supplementary materials (Table S1). Departures from HWE expectations were observed at two loci (PnuA3w from the pre-WNV sample and Cb06 from the post-WNV sample) after Bonferroni correction (Table S1); these loci were removed from subsequent analysis. In 561 pairwise comparisons, four pairs of loci appeared to be in linkage disequilibrium (Cb20 and Cb21; Cb14 and CoBr36; CoBr22 and Cb17, and CoBr12 and Cb10), but this linkage was only apparent at both time points (the pre-WNV and post-WNV populations) for Cb20 and Cb21. We removed both Cb20 and Cb21 from the analysis but retained the other loci because apparent linkage at only a single time point was unlikely to be a result of physical linkage. Two additional loci (Cb17 and Cb10) had a high frequency of null alleles (> 0.1) and were removed from the dataset. All subsequent analyses are therefore based on 28 loci. We scored all birds at a minimum of 26 of these 28 loci, and most (>98%) were scored at all loci (mean proportion of loci typed >0.99). Mean allelic diversity at these loci was 11.25 ± 1.17 alleles/locus (range: 3–31 alleles/locus). Double Digest Restriction Associated DNA (ddRAD) sequencing. We performed ddRAD sequencing on 86 randomly selected crows (43 pre-WNV and 43 post-WNV). 100-500 ng of DNA were digested with SbfI-HF (NEB, R3642L) and MspI-HF (NEB, R016S) restriction enzymes. Samples were ligated with a P2-MspI adapter and pooled in groups of 18-20, each with a unique P1 adapter. Pooled index groups were purified using 1.5X volumes of homemade MagNA made with Sera-Mag Magnetic Speed-beads (FisherSci). Fragments 450-600 bp long were selected using BluePippin (Sage Science) by the Cornell University Biotechnology Resource Center (BRC). After size selection, unique index barcodes were added to each index group by performing 11 cycles of PCR with Phusion® DNA polymerase (NEB). Reactions were purified using 0.7X volumes of MagNA beads and pooled in equimolar ratios for sequencing on the Illumina HiSeq 2500 at the BRC, with single end reads (100 bp). The sequencing was performed with an added Illumina PhiX control (15%) due to low 5’ complexity. Pre- and post-WNV samples were library prepared together and sequenced on a single lane to avoid the introduction of a library or lane effect. We used FASTQC v0.11.9 (Babraham Bioinformatics; http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) to assess read quality. We trimmed reads to 147 bp using fastX_trimmer (FASTX-Toolkit) to exclude low-quality data at the 3’ end of reads. Next, we eliminated reads with Phred scores below 10, then eliminated reads in which 5% or more bases had Phred scores below 20 (fastq_quality_filter). The fastq files were demultiplexed using the process_radtags module in STACKS v2.52 pipeline to create a file with sequences specific to each individual. We first scaffolded the American Crow reference genome (NCBI assembly: ASM69197v1, Accession no: GCA_000691975.1) into putative pseudochromosomes using the synteny-based Chromosemble tool in Satsuma2 (Grabherr et al. 2010) and the Hooded Crow genome (NCBI assembly: ASM73873v5, Accession no: GCA_000738735.5). We aligned sequence reads to the American Crow pseudochromosome assembly using BWA-MEM (Li & Durbin 2009). We called SNPs in ANGSD (Korneliussen et al. 2014) using the GATK model, requiring SNPs to be present in 80% of the individuals (0.95 postcutoff, SNP p-value 1e-6) with a minimum allele frequency of 0.015. We removed bases with quality scores below 20 (-minQ 20), bad reads (-remove_bads), mapping quality below 20 (-minMapQ20), base alignment quality below 1 (-baq), more than two alleles (-skipTriallelic), and heterozygote bias (-hetbias_pval 1e-5), requiring the minimum depth per individual to be at least two and read depth higher than 1,800. These filters resulted in 16,200 SNPs. To reduce differences in missingness between the pre- and post-WNV populations, we excluded loci that had less than 80% called genotypes per population, resulting in 5,151 SNPs.

The poly shapefile is based on Census data that compares Census 2000 population levels to estimates in July, 2006 for all the counties that are designated by NOAA (see the URL below) as "Coastal Region Counties". There are 645 jurisdictions, whose combined population in was over 146.6 million (Year 2000) and estimated to be 154.3 million in 2006. In both years, the largest and the smallest counties were Los Angeles, CA and Kenedy, TX. Flagler, FL registered the largest percent change (66.7%) and St. Bernard, LA registered the highest percent decrease (-76.9%). The later is direct result of the 2005 Katrina disaster. http://www.census.gov/geo/landview/lv6help/coastal_cty.pdf

This web map displays data from the voter registration database as the percent of registered voters by census tract in King County, Washington. The data for this web map is compiled from King County Elections voter registration data for the years 2013-2019. The total number of registered voters is based on the geo-location of the voter's registered address at the time of the general election for each year. The eligible voting population, age 18 and over, is based on the estimated population increase from the US Census Bureau and the Washington Office of Financial Management and was calculated as a projected 6 percent population increase for the years 2010-2013, 7 percent population increase for the years 2010-2014, 9 percent population increase for the years 2010-2015, 11 percent population increase for the years 2010-2016 & 2017, 14 percent population increase for the years 2010-2018 and 17 percent population increase for the years 2010-2019. The total population 18 and over in 2010 was 1,517,747 in King County, Washington. The percentage of registered voters represents the number of people who are registered to vote as compared to the eligible voting population, age 18 and over. The voter registration data by census tract was grouped into six percentage range estimates: 50% or below, 51-60%, 61-70%, 71-80%, 81-90% and 91% or above with an overall 84 percent registration rate. In the map the lighter colors represent a relatively low percentage range of voter registration and the darker colors represent a relatively high percentage range of voter registration. PDF maps of these data can be viewed at King County Elections downloadable voter registration maps. The 2019 General Election Voter Turnout layer is voter turnout data by historical precinct boundaries for the corresponding year. The data is grouped into six percentage ranges: 0-30%, 31-40%, 41-50% 51-60%, 61-70%, and 71-100%. The lighter colors represent lower turnout and the darker colors represent higher turnout. The King County Demographics Layer is census data for language, income, poverty, race and ethnicity at the census tract level and is based on the 2010-2014 American Community Survey 5 year Average provided by the United States Census Bureau. Since the data is based on a survey, they are considered to be estimates and should be used with that understanding. The demographic data sets were developed and are maintained by King County Staff to support the King County Equity and Social Justice program. Other data for this map is located in the King County GIS Spatial Data Catalog, where data is managed by the King County GIS Center, a multi-department enterprise GIS in King County, Washington. King County has nearly 1.3 million registered voters and is the largest jurisdiction in the United States to conduct all elections by mail. In the map you can view the percent of registered voters by census tract, compare registration within political districts, compare registration and demographic data, verify your voter registration or register to vote through a link to the VoteWA, Washington State Online Voter Registration web page.

Age-class-specific aerial survey data with corresponding annual totals and 90% confidence intervals for moose in northeastern Minnesota, USA, 2005–2020 [9]. Total abundance is corrected for sightability, abundance of calves, adult females, and adult males is derived from reported calf:adult female and adult male:adult female ratios.

About this dataset

Context

The dataset tabulates the data for the Rising Sun, MD population pyramid, which represents the Rising Sun population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Rising Sun, MD, is 42.1.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Rising Sun, MD, is 17.2.
• Total dependency ratio for Rising Sun, MD is 59.3.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Rising Sun, MD is 5.8.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Rising Sun population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Rising Sun for the selected age group is shown in the following column.
• Population (Female): The female population in the Rising Sun for the selected age group is shown in the following column.
• Total Population: The total population of the Rising Sun for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Rising Sun Population by Age. You can refer the same here

Graph and download economic data for Employment-Population Ratio (EMRATIO) from Jan 1948 to Aug 2025 about employment-population ratio, civilian, 16 years +, household survey, population, employment, and USA.

The annual population growth in Latin America & the Caribbean increased slightly to 0.7 percent since the previous year. Still, 2023 marks the lowest population growth during the observed period. Population growth deals with the annual change in total population, and is affected by factors such as fertility, mortality, and migration.

This dataset displays ridership statistics for major transit agencies across the USA for the first quarter of 2008 and compares them to the same figures from 2007. The findings show that the use of Public Transportation in the USA has increased dramatically in the past year. The Data comes from the American Public Transportation Association. The American Public Transportation Association (APTA) announced that Americans took 2.6 billion trips on public transportation in the first three months of 2008. This is almost 85 million more trips than last year for the same time period. Last year 10.3 billion trips were taken on U.S. public transportation the highest number of trips taken in fifty years. In the first quarter of 2008, public transportation continued to climb and rose by 3.3 percent. In contrast, the Federal Highway Administration has reported that the vehicle miles traveled on our nations roads declined by 2.3 percent in the first quarter. Light rail (modern streetcars, trolleys, and heritage trolleys) had the highest percentage of ridership increase among all modes, with a double digit 10.3 percent increase for the first quarter. Commuter rail posted the second largest ridership increase at 5.7 percent. Heavy rail (subways and elevated trains) ridership increased by 4.4 percent. Bus ridership saw an increase of 2 percent nationwide. Terms: A Trip is a trip on one transit vehicle regardless of the type of fare paid or transfer presented MODE CODES MB Bus TB Trolleybus DR Demand Response VP Vanpool JT Jitney HR Heavy Rail LR Light Rail CR Commuter Rail IR Intermediate Rail FB Ferryboat AG Automated Guideway IP Inclined Plane TOTAL Agency Total Blank Entries = Not calculable due to zero base or missing data