About this dataset

Context

The dataset tabulates the Western town 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 Western town 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 Western town was 1,795, a 0.28% decrease year-by-year from 2022. Previously, in 2022, Western town population was 1,800, a decline of 0.83% compared to a population of 1,815 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Western town decreased by 230. In this period, the peak population was 2,062 in the year 2005. 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 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 Western town is shown in this column.
• Year on Year Change: This column displays the change in Western town 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 Western town Population by Year. You can refer the same here

New York was the most populous state in the union in the year 1900. It had the largest white population, for both native born and foreign born persons, and together these groups made up over 7.1 million of New York's 7.2 million inhabitants at this time. The United States' industrial centers to the north and northeast were one of the most important economic draws during this period, and states in these regions had the largest foreign born white populations. Ethnic minorities Immigration into the agricultural southern states was much lower than the north, and these states had the largest Black populations due to the legacy of slavery - this balance would begin to shift in the following decades as a large share of the Black population migrated to urban centers to the north during the Great Migration. The Japanese and Chinese populations at this time were more concentrated in the West, as these states were the most common point of entry for Asians into the country. The states with the largest Native American populations were to the west and southwest, due to the legacy of forced displacement - this included the Indian Territory, an unorganized and independent territory assigned to the Native American population in the early 1800s, although this was incorporated into Oklahoma when it was admitted into the union in 1907. Additionally, non-taxpaying Native Americans were historically omitted from the U.S. Census, as they usually lived in separate communities and could not vote or hold office - more of an effort was made to count all Native Americans from 1890 onward, although there are likely inaccuracies in the figures given here. Changing distribution Internal migration in the 20th century greatly changed population distribution across the country, with California and Florida now ranking among the three most populous states in the U.S. today, while they were outside the top 20 in 1900. The growth of Western states' populations was largely due to the wave of internal migration during the Great Depression, where unemployment in the east saw many emigrate to "newer" states in search of opportunity, as well as significant immigration from Latin America (especially Mexico) and Asia since the mid-1900s.

This study contains an assortment of data files relating to the electoral and demographic history of New York State. Part 1, Mortality Statistics of the Seventh Census, 1850: Place of Birth for United States Cities, contains counts of persons by place of birth for United States cities as reported in the 1850 United States Census. Place of birth is coded for states and for selected foreign countries, and percentages are also included. Part 2, Selected Tables of New York State and United States Censuses of 1835-1875: New York State Counties, contains data from the New York State Censuses of 1835, 1845, 1855, 1865, and 1875, and includes data from the United States Censuses of 1840 and 1850. The bulk of the tables concern church and synagogue membership. The tables for 1835 and 1845 include counts of persons by sex, legal male voters, alien males, not taxed Colored, taxed Colored, and taxed Colored can vote. The 1840 tables include total population, employment by industry, and military pensioners. The 1855 tables provide counts of persons by place of birth. Part 3, New York State Negro Suffrage Referenda Returns, 1846, 1860, and 1869, by Election District, contains returns for 28 election districts on the issue of Negro suffrage, with information on number of votes for, against, and total votes. Also provided are percentages of votes for and against Negro suffrage. Part 4, New York State Liquor License Referendum Returns, 1846, Town Level, contains returns from the Liquor License Referendum held in May 1846. For each town the file provides total number of votes cast, votes for, votes against, and percentage of votes for and against. The source of the data are New York State Assembly Documents, 70 Session, 1847, Document 40. Part 5, New York State Censuses of 1845, 1855, 1865, and 1875: Counts of Churches and Church Membership by Denomination, contains counts of churches, total value of church property, church seating capacity, usual number of persons attending church, and number of church members from the New York State Censuses of 1845, 1855, 1865, and 1875. Counts are by denomination at the state summary level. Part 6, New York State Election Returns, Censuses, and Religious Censuses: Merged Tables, 1830-1875, Town Level, presents town-level data for the elections of 1830, 1834, 1838, 1840, and 1842. The file also includes various summary statistics from the New York State Censuses of 1835, 1845, 1855, and 1865 with limited data from the 1840 United States Census. The data for 1835 and 1845 include male eligible voters, aliens not naturalized, non-white persons not taxed, and non-white persons taxed. The data for 1840 include population, employment by industry, and military service pensioners. The data for 1845 cover total population and number of males, place of birth, and churches. The data for 1855 and 1865 provide counts of persons by place of birth, number of dwellings, total value of dwellings, counts of persons by race and sex, number of voters by native and foreign born, and number of families. The data for 1865 also include counts of Colored not taxed and data for churches and synagogues such as number, value, seating capacity, and attendance. The data for 1875 include population, native and foreign born, counts of persons by race, by place of birth, by native, by naturalized citizens, and by alien males aged 21 and over. Part 7, New York State Election Returns, Censuses, and Religious Censuses: Merged Tables, 1844-1865, Town Level, contains town-level data for the state of New York for the elections of 1844 and 1860. It also contains data for 1850 such as counts of persons by sex and race. Data for 1855 includes counts of churches, value of churches and real estate, seating capacity, and church membership. Data for 1860 include date church was founded and source of that information. Also provided are total population counts for the years 1790, 1800, 1814, 1820, 1825, 1830, 1835, 1845, 1856, 1850, 1855, 1860, and 1865. (ICPSR 3/16/2015)

In 2020, about 82.66 percent of the total population in the United States lived in cities and urban areas. As the United States was one of the earliest nations to industrialize, it has had a comparatively high rate of urbanization over the past two centuries. The urban population became larger than the rural population during the 1910s, and by the middle of the century it is expected that almost 90 percent of the population will live in an urban setting. Regional development of urbanization in the U.S. The United States began to urbanize on a larger scale in the 1830s, as technological advancements reduced the labor demand in agriculture, and as European migration began to rise. One major difference between early urbanization in the U.S. and other industrializing economies, such as the UK or Germany, was population distribution. Throughout the 1800s, the Northeastern U.S. became the most industrious and urban region of the country, as this was the main point of arrival for migrants. Disparities in industrialization and urbanization was a key contributor to the Union's victory in the Civil War, not only due to population sizes, but also through production capabilities and transport infrastructure. The Northeast's population reached an urban majority in the 1870s, whereas this did not occur in the South until the 1950s. As more people moved westward in the late 1800s, not only did their population growth increase, but the share of the urban population also rose, with an urban majority established in both the West and Midwest regions in the 1910s. The West would eventually become the most urbanized region in the 1960s, and over 90 percent of the West's population is urbanized today. Urbanization today New York City is the most populous city in the United States, with a population of 8.3 million, while California has the largest urban population of any state. California also has the highest urbanization rate, although the District of Columbia is considered 100 percent urban. Only four U.S. states still have a rural majority, these are Maine, Mississippi, Montana, and West Virginia.

This collection contains five modified data sets with mortality, population, and other demographic information for five American cities (Baltimore, Maryland; Boston, Massachusetts; New Orleans, Louisiana; New York City (Manhattan only), New York; and Philadelphia, Pennsylvania) from the early 19th century to the early 20th century. Mortality was represented by an annual crude death rate (deaths per 1000 population per year). The population was linearly interpolated from U.S. Census data and state census data (for Boston and New York City). All data sets include variables for year, total deaths, census populations, estimated annual linearly interpolated populations, and crude death rate. The Baltimore data set (DS0001) also provides birth and death rate variables based on race and slave status demographics, as well as a variable for stillbirths. The Philadelphia data set (DS0005) also includes variables for total births, total infant deaths, crude birth rate, and infant deaths per 1,000 live births.

At the end of the Revolutionary Period in United States history, the majority of white settlers in the United States of America had English heritage. The Thirteen Colonies, which claimed independence in 1776, was part of the British Empire until this point - English settlers and their descendants made up over 60 percent of the population by 1790. The English were the ethnic majority (among whites) in all states except Pennsylvania, which had a similarly-sized German population, while New York had a sizeable Dutch population as it was a former Dutch colony. The second-largest group was the Irish, where those from both the island's north and south made up a combined 10 percent of the population, followed by the Scottish and Germans at over eight percent each. Outside of the United States, the French and Spanish territories that would later be incorporated into the Union were majority French and Spanish - despite their large size they were relatively sparsely populated. The composition of the U.S. population would change drastically throughout the 19th century due largely to waves of migration from Europe.

Street tree data from the TreesCount! 2015 Street Tree Census, conducted by volunteers and staff organized by NYC Parks & Recreation and partner organizations. Tree data collected includes tree species, diameter and perception of health. Accompanying blockface data is available indicating status of data collection and data release citywide.

The 2015 tree census was the third decadal street tree census and largest citizen science initiative in NYC Parks’ history. Data collection ran from May 2015 to October 2016 and the results of the census show that there are 666,134 trees planted along NYC's streets. The data collected as part of the census represents a snapshot in time of trees under NYC Parks' jurisdiction.

The census data formed the basis of our operational database, the Forestry Management System (ForMS) which is used daily by our foresters and other staff for inventory and asset management: https://data.cityofnewyork.us/browse?sortBy=most_accessed&utf8=%E2%9C%93&Data-Collection_Data-Collection=Forestry+Management+System+%28ForMS%29

To learn more about the data collected and managed in ForMS, please refer to this user guide: https://docs.google.com/document/d/1PVPWFi-WExkG3rvnagQDoBbqfsGzxCKNmR6n678nUeU/edit. For information on the city's current tree population, use the ForMS datasets.

About this dataset

Context

The dataset tabulates the Genoa town 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 Genoa town 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 Genoa town was 1,788, a 0.67% decrease year-by-year from 2022. Previously, in 2022, Genoa town population was 1,800, a decline of 0.77% compared to a population of 1,814 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Genoa town decreased by 130. In this period, the peak population was 1,935 in the year 2019. 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 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 Genoa town is shown in this column.
• Year on Year Change: This column displays the change in Genoa town 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 Genoa town Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Weedsport 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 Weedsport 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 Weedsport was 1,784, a 0.89% decrease year-by-year from 2021. Previously, in 2021, Weedsport population was 1,800, a decline of 0.44% compared to a population of 1,808 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Weedsport decreased by 234. In this period, the peak population was 2,018 in the year 2000. 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 Weedsport is shown in this column.
• Year on Year Change: This column displays the change in Weedsport 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 Weedsport Population by Year. You can refer the same here

New York City besaß Schätzungen zufolge im Jahr 2023 rund 8,26 Millionen Einwohner. Damit ist der "Big Apple" gegenüber 2020 etwas geschrumpft. Zwischen 1759 und 1950 ist die Einwohnerzahl dagegen nahezu kontinuierlich gestiegen. Grund für die Stagnation beziehungsweise Abnahme der Bevölkerung in den folgenden Jahren und Jahrzehnten war unter anderem eine starke Steigerung der Kriminalität, die erst durch politische und polizeiliche Maßnahmen ab Anfang der 90er-Jahre wieder gesenkt werden konnte. Gründung der Stadt und Entwicklung bis 1800 New York City wurde als niederländische Kolonie im Jahr 1624 gegründet und bekam den Namen Nieuw Amsterdam. 1664 wurde die Stadt der britischen Marine kampflos eingenommen und bekam den Namen New York. Das 18. Jahrhundert war für die Stadt von erstem Wachstum geprägt, 1750 zählte die Stadt am Hudson River bereits 22.000 Einwohner, zur Jahrhundertwende waren es bereits mehr als 60.000. Geschichte der Stadt seit 1800 Ab dem 19. Jahrhundert beschleunigte sich das Wachstum: Ein neues Straßennetz, die Fertigstellung des Eriekanals (eine Verbindung zu den Großen Seen) und die Verbindung der heutigen Stadtbezirke Manhattan, Brooklyn, Richmond (Staten Island), Queens und der Bronx führten gemeinsam mit starken Zuwanderungszahlen aus den USA, Europa und Asien zu einem rasanten Wachstum: Um 1900 zählte die Stadt bereits deutlich mehr als drei Millionen Einwohner - im Jahr 1895 war New York City bereits die zweitgrößte Stadt der Welt.Weitere Informationen zu historischen Themen finden Sie hier.

New York has taken part in all U.S. presidential elections since 1792, and has cast the majority of its electoral votes for the nationwide winner in 47 elections, giving a success rate of 81 percent. New York has generally voted for the more liberal candidate in U.S. elections, and has been a safe Democratic state since the 1988 election. In the 2020 election, New York was a comfortable win for Democratic nominee Joe Biden, who carried the state by a 23 percent margin; however, the native New Yorker, Donald Trump, won in several of New York's more rural districts with around seventy percent of their popular vote, showing a stark contrast between urban and rural districts. Presidents from the Empire State A total of five U.S. presidents were born in New York; these were Martin Van Buren, Millard Fillmore, Theodore Roosevelt, Franklin D. Roosevelt and Donald Trump. These five men ran for president in eleven different elections, and carried their home state in six elections; Donald Trump is the only New Yorker to have won the election without carrying his home state. Several other losing candidates have carried their home state, with the most recent being Hillary Clinton in the 2016 election, and Thomas E. Dewey in 1948 (both held public office in New York, but were born elsewhere).

Declining significance Throughout most of U.S. history, New York was the most populous state, and therefore had the largest share of electoral votes. This began in the 1812 election, where New York had 29 electoral votes; the allocation then fluctuated throughout the rest of the 1800s and early 1900s, peaking at 47 votes in the 1930s and 1940s. Since the 1950s, however, New York's allocation of electoral votes has gradually declined, and it was overtaken by California in the 1972 election, and then Texas in 2004. This is due to differing population growth rates across various regions of the U.S., as growth rates along the southern border tend to be much higher than in states along the east coast. In the 2020 election, New York's allocation of electoral votes is 29; this is expected to fall again to 28 votes in the 2024 election, where it will likely be overtaken by Florida as the third-most populous state.

The Family Violence Prevention and Services Act of 1984 (FVPSA) provided funding, through the Office of Victims of Crime in the United States Department of Justice, for 23 law enforcement training projects across the nation from 1986 to 1992. FVPSA was enacted to assist states in (1) developing and maintaining programs for the prevention of family violence and for the provision of shelter to victims and their dependents and (2) providing training and technical assistance for personnel who provide services for victims of family violence. The National Institute of Justice awarded a grant to the Urban Institute in late 1992 to evaluate the police training projects. One of the program evaluation methods the Urban Institute used was to conduct surveys of victims in New York and Texas. The primary objectives of the survey were to find out, from victims who had contact with law enforcement officers in the pre-training period and/or in the post-training period, what their experiences and evaluations of law enforcement services were, how police interventions had changed over time, and how the quality of services and changes related to the police training funded under the FVPSA. Following the conclusion of training, victims of domestic assault in New York and Texas were surveyed through victim service programs across each state. Similar, but not identical, instruments were used at the two sites. Service providers were asked to distribute the questionnaires to victims of physical or sexual abuse who had contact with law enforcement officers. The survey instruments were developed to obtain information and victim perceptions of the following key subject areas: history of abuse, characteristics of the victim-abuser relationship, demographic characteristics of the abuser and the victim, history of law enforcement contacts, services received from law enforcement officers, and victims' evaluations of these services. Variables on history of abuse include types of abuse experienced, first and last time physically or sexually abused, and frequency of abuse. Characteristics of the victim-abuser relationship include length of involvement with the abuser, living arrangement and relationship status at time of last abuse, number of children the victim had, and number of children at home at the time of last abuse. Demographic variables provide age, race/ethnicity, employment status, and education level of the abuser and the victim. Variables on the history of law enforcement contacts and services received include number of times law enforcement officers were called because of assaults on the victim, number of times law enforcement officers actually came to the scene, first and last time officers came to the scene, number of times officers were involved because of assaults on the victim, number of times officers were involved in the last 12 months, and type of law enforcement agencies the officers were from. Data are also included on city size by population, city median household income, county population density, county crime rate, and region of state of the responding law enforcement agencies. Over 30 variables record the victims' evaluations of the officers' responsiveness, helpfulness, and attitudes.

In 2023, California had the highest Hispanic population in the United States, with over 15.76 million people claiming Hispanic heritage. Texas, Florida, New York, and Illinois rounded out the top five states for Hispanic residents in that year. History of Hispanic people Hispanic people are those whose heritage stems from a former Spanish colony. The Spanish Empire colonized most of Central and Latin America in the 15th century, which began when Christopher Columbus arrived in the Americas in 1492. The Spanish Empire expanded its territory throughout Central America and South America, but the colonization of the United States did not include the Northeastern part of the United States. Despite the number of Hispanic people living in the United States having increased, the median income of Hispanic households has fluctuated slightly since 1990. Hispanic population in the United States Hispanic people are the second-largest ethnic group in the United States, making Spanish the second most common language spoken in the country. In 2021, about one-fifth of Hispanic households in the United States made between 50,000 to 74,999 U.S. dollars. The unemployment rate of Hispanic Americans has fluctuated significantly since 1990, but has been on the decline since 2010, with the exception of 2020 and 2021, due to the impact of the coronavirus (COVID-19) pandemic.

This dataset was developed for studies of the population history of sixteenth-century Sweden, including its social and occupational structures, on national and local levels. The aim was to be able to study annual change on both national and local levels. The data may be used for further historical studies regarding these issues, especially on the local level (e.g., concerning royal estates, institutions, and towns), and for comparative histories of medieval and early modern population, agrarian, and economic change.

The dataset contains information from cadastres, accounts, wage lists and taxation registres. They contain the number of cadastral farms (including ownership status), the number of cottagers, craftsmen, and servants, division of farms, the number of employees at crown, church, and nobility estates, castles, hospitals, shipyards, metal industries etc., the number of people living in towns. All occupational titles are includes (from wage registres and from subsidy taxation records of 1535, 1571, and 1599–1600). The collection also includes the royal courts, as well as all nobility manors. The dataset includes calculations of the population of Sweden for each year 1530–1600 on the level of the hundred and the province, as well as calculations of the degree of urbanisation, the population share employed at crown and nobility estates, the population share that was cottagers, and the number of male servants in husbandry.

For a more detailed overview, please see the README file, as well as the main publication of the project (M. Andersson, A population history of sixteenth-century Sweden, Uppsala 2025). The manuscript sources for the database are listed below.

Riksarkivet (RA, Swedish National Archives), Stockholm Acta angående ridderskapet och adeln, vol. 14–17 Älvsborgs lösen 1571 Arv och eget Bååtska familjepapper, E 3388 Bergsbruk: Salbergets räkenskaper Bielkesamlingen, E 1991–1992 Blå nummer 690 Diplomatica Danica 730 Fogdarnas räkenskaper Furstendömenas räntekammare Gärder och hjälper 1535 Hogenskild Bielkes samling, E 1982–1984 Kammarkollegiets ämnessamlingar: Adeln och dess gods Kammarkollegiets ämnessamlingar: Bergsbruk Kammarkollegiets ämnessamlingar: Kyrkors, skolors och hospitals akter Kammarkollegiets ämnessamlingar: Slott och gårdar Kammarkollegiets ämnessamlingar: Städers akter Kungliga arkiv (K) Landskapshandlingar Landskapshandlingar: supplement Leijonhufvudska samlingen, E 4587 Lokala tullräkenskaper, vol. 439 Oxenstiernska samlingen, E 517–518, 520 Prostarnas tionderäkenskaper Provianträkenskaper Räntekammarböcker Riksarkivets ämnessamlingar: Bergverken Riksarkivets ämnessamlingar: Städers acta Riksarkivets ämnessamlingar: Topographica Rydboholmssamlingen, E 7446 Röda nummer Rosenbladska samlingen, vol. 3 Sandbergska samlingen Silverskatten 1560 Skeppsgårdshandlingar Strödda räkenskaper och handlingar t o m 1630: Brudskatten 1563 Strödda räkenskaper och handlingar t o m 1630: Brudskatten 1579 Strödda räkenskaper och handlingar t o m 1630: Förläningsregister Strödda räkenskaper och handlingar t o m 1630: Handlingar angående bördsrättsköpen under Johan III:s tid Strödda räkenskaper och handlingar t o m 1630: Köpsilverskatten 1573 Strödda räkenskaper och handlingar t o m 1630: Länsregister Strödda räkenskaper och handlingar t o m 1630: Löningsregister Strödda räkenskaper och handlingar t o m 1630: Silverskatten 1569 Strödda äldre räkenskaper, ny serie: Gärderäkenskaper Strödda äldre räkenskaper, ny serie: Mantalsregister Strödda äldre räkenskaper, ny serie: Oxregister Strödda kamerala handlingar Strödda militiehandlingar före 1631, C 1 Wijksamlingen, E 2741 Krigsarkivet (KrA), Stockholm Militieräkningar Slottsarkivet, Stockholm Hovförtäringsräkenskaper: Furstliga personers hovförtäringsräkenskaper

Landsarkivet i Göteborg (GLA) Ulricehamns rådhusrätt och magistrat, AIa:1

Landsarkivet i Härnösand (HLA) Västernorrlands landskontor, GIIIa:1

Landsarkivet i Vadstena (VLA) Vadstena rådhusrätt och magistrat, HV:1

Stockholms stadsarkiv (SSA) Borgmästare och råds arkiv före 1636, serie G

Kungliga biblioteket (KB) X 953 (Räkenskapsbok från Vreta kloster)  Uppsala universitetsbibliotek (UUB) X 265g–h (Papper rörande släkten Gera)

Lunds universitetsbibliotek (LUB) de la Gardiesamlingen: Topographica

Linköpings stiftsbibliotek N 28 (Joen Petri Klints järteckensbok)

Abstract (en): This study contains teaching materials developed over a period of years for a four-week workshop, Longitudinal Analysis of Historical Demographic Data (LAHDD), offered through the ICPSR Summer Program in 2006, 2007, 2009, 2011 and 2013, with one-day alumni workshops in 2010, 2012, and 2014. Instructors in the workshops are listed below. Funding was provided by The Eunice Kennedy Shriver National Institute of Child Health and Human Development, grants R25-HD040525 and R25-HD-049479, the ICPSR Summer Program and the ICPSR Director. The course was designed to teach students the theories, methods, and practices of historical demography and to give them first-hand experience working with historical data. This training is valuable not only to those interested in the analysis historical data. The techniques of historical demography rest on methodological insights that can be applied to many problems in population studies and other social sciences. While historical demography remains a flourishing research area with publications in key journals like Demography, Population Studies, and Population, practitioners were dispersed, and training was not available at any of the population research centers in the U.S. or elsewhere. One hundred and ten participants from around the globe took part in the workshops, and have gone on to establish courses of their own or teach in other workshops. We offer these materials here in the hopes that others will find them useful in developing courses on historical demography and/or longitudinal data analysis. The workshop was organized in three tracks: A brief tour of historical demography, event-history analysis, and data management for longitudinal data using Stata and Microsoft Access. The data management track includes 13 exercises designed for hands-on learning and reinforcement. Included in this project are the syllabii and reading lists for the three tracks, datasets used in the exercises, documents setting out each exercise, a file with the expected results, and for many of the exercises, an explanation. Video tutorials helpful with the Access exercises are accessible from ICPSR's YouTube channel https://www.youtube.com/playlist?list=PLqC9lrhW1Vvb9M1QpQH23z9UlPYxHbUMF. Users are encouraged to use these materials to develop their own courses and workshops in any of the topics covered. Please acknowledge NICHD R25-HD040525 and R25-HD-049479 whenever appropriate. Historical demography instructors: Myron P. Gutmann, University of Colorado Boulder Cameron Campbell, Hong Kong University of Science and Technology J. David Hacker, University of Minnesota Satomi Kurosu, Reitaku University Katherine A. Lynch, Carnegie Mellon University Event history instructors: Cameron Campbell, Hong Kong University of Science and Technology Glenn Deane, State University of New York at Albany Ken R. Smith, Huntsman Cancer Institute and University of Utah Database management instructors: George Alter, University of Michigan Susan Hautaniemi Leonard, University of Michigan Teaching Assistants: Mathew Creighton, University of Massachusetts Boston Emily Merchant, University of Michigan Luciana Quaranta, Lund University Kristine Witkowski, University of Michigan Project Manager: Susan Hautaniemi Leonard, University of Michigan Funding insitution(s): United States Department of Health and Human Services. National Institutes of Health. Eunice Kennedy Shriver National Institute of Child Health and Human Development (R25 HD040525).

Biologists aim to explain patterns of growth, reproduction, and ageing that characterize life histories, yet we are just beginning to understand the proximate mechanisms that generate this diversity. Existing research in this area has focused on telomeres but has generally overlooked the telomere’s most direct mediator, the shelterin protein complex. Shelterin proteins physically interact with the telomere to shape its shortening and repair. They also regulate metabolism and immune function, suggesting a potential role in life history variation in the wild. However, research on shelterin proteins is uncommon outside of biomolecular work. Intraspecific analyses can play an important role in resolving these unknowns because they reveal subtle variation in life history within and among populations. Here, we assessed ecogeographic variation in shelterin protein abundance across eight populations of tree swallow (Tachycineta bicolor) with previously documented variation in environmental and life history traits. Using blood gene expression of four shelterin proteins in 12-day old nestlings, we tested the hypothesis that shelterin protein gene expression varies latitudinally and in relation to both telomere length and life history. Shelterin protein gene expression differed among populations and tracked non-linear variation in latitude: nestlings from mid-latitudes expressed nearly double the shelterin mRNA on average than those at more northern and southern sites. However, telomere length was not significantly related to latitude. We next assessed whether telomere length and shelterin protein gene expression correlate with 12-day old body mass and wing length, two proxies of nestling growth linked to future fecundity and survival. We found that body mass and wing length correlated more strongly (and significantly) with shelterin protein gene expression than with telomere length. These results highlight telomere regulatory shelterin proteins as potential mediators of life history variation among populations. Together with existing research linking shelterin proteins and life history variation within populations, these ecogeographic patterns underscore the need for continued integration of ecology, evolution, and telomere biology, which together will advance understanding of the drivers of life history variation in nature. Methods Study populations: Data were collected from 8 populations in the eastern United States, spanning nearly 10 degrees of latitude (Table 1, Fig 2A): Ithaca, New York (42.28°N, 76.29°W); Amherst, Massachusetts (42.22°N, 72.31°W); Linesville, Pennsylvania (41.65°N, 80.43°W); Bloomington, Indiana (39.17°N, 86.53°W); Lexington, Kentucky (38.11°N, 84.49°W); Knoxville, Tennessee (35.90°N, 83.96°W); Davidson, North Carolina (35.53°N, 80.88°W); and Santee, South Carolina (33.49°N, 80.36°W). These populations do not represent the entire breeding range of this species and in particular, do not extend to the northern edge in Canada and Alaska. All methods were approved by institutional IACUCs and conducted with appropriate state and federal permits. Sampling of nestlings: Nest boxes were monitored for hatch dates, but in cases where hatch dates were missed (e.g., due to weather or COVID-related staffing shortages), hatch dates were estimated using existing growth curves (McCarty, 2001; Wolf et al., 2021) and accounted for in all statistical analyses. Data from multiple populations shows that the average peak of postnatal growth occurs around 6-days old (McCarty, 2001; Wolf et al., 2021). Growth then slows and plateaus near adult size by 12-days old, just as feather development accelerates. We targeted 12-day old nestlings because they have just completed the rapid period of postnatal growth. Many studies therefore use morphological data at this critical time period as a proxy of nestling growth (Gebhardt-Henrich & Richner, 1998; Haywood & Perrins, 1992; Magrath, 1991; Martin et al., 2018; McCarty, 2001). Population variation in growth rates occurs primarily after peak growth but does not map neatly onto latitude, at least not in the northern (historical) range where previous research has been focused (Ardia, 2006; McCarty, 2001). We sampled nestlings at 12.03 ± 0.01-days old (hatch day = day 1, range = 10 – 14 days). We sampled ~30 nests per population (Table 1), though logistical constraints prevented collection of RNA in Kentucky. Upon arrival at each nest, we immediately collected whole blood from the brachial vein of 2-3 nestlings per nest (≤ 200 µl, below the maximum suggested volume based on body mass; Gaunt et al., 1997), and we avoided obvious runts with atypical growth. We collected blood in separate tubes for DNA and RNA analyses. We banded nestlings with a USGS band and weighed them to the nearest 0.1g. We also measured flattened wing length using a wing ruler. We stored blood on ice or dry ice in the field, and later stored it at -80°C. Due to limited budgets, we made the decision a priori to conduct laboratory analyses for a single nestling per nest. When possible, we selected the nestling with the median mass. If the median-massed nestling was not bled or failed to produce a sufficient blood sample, we selected the nestling with the closest mass to the median. In nests with even brood sizes, we randomly selected one of the two nestlings with median mass for telomere and gene expression analyses. In all states except Indiana, telomere length and gene expression data come from the same individual. qPCR for Telomere length: We extracted DNA from whole blood (following Wolf et al., 2022) and used primers telc and telg (adapted from Cawthon, 2009) to quantify telomere length relative to the single copy gene GAPDH. Samples were run in triplicate, and mean values were used to calculate the T/S ratio of telomere repeat copy number (T) to our single gene copy number (S) using the formula: 2-∆∆Ct, where ∆∆Ct = (Ct telomere – Ct GAPDH) reference – (Ct telomere – Ct GAPDH) sample. The intraclass correlation coefficient (ICC) for intraplate repeatability was 0.951 ± 0.03 (95% CI = 0.944, 0.957) for GAPDH Ct values and 0.926 ± 0.09 (95% CI = 0.916, 0.935) for telomere Ct values. The ICCs for interplate repeatability were 0.96 ± 0.03 (95% CI = 0.87, 0.98) for GAPDH Ct values, 0.89 ± 0.06 (95% CI = 0.73, 0.95) for telomere Ct values, and 0.79 ± 0.10 (95% CI: 0.54 - 0.90) for the T/S ratio (based on 2-∆Ct values). Plates (n = 13) were balanced by population, sex, relative date of sampling within each population, and brood size. Nestling Sexing Protocol: Nestlings were molecularly sexed using DNA following established methods (Griffiths et al., 1998; Wolf et al., 2022). Shelterin Protein Primer Design: Shelterin proteins are relatively conserved across taxa (de Lange, 2018; Myler et al., 2021) and earlier work has identified at least four shelterin proteins in the chicken (De Rycker et al., 2003; Konrad et al., 1999; Tan et al., 2003; Wei & Price, 2004). Our shelterin protein primer sets were developed using the tree swallow transcriptome (accession #GSE126210; Bentz et al., 2019). TRF2 exhibits multiple variants in passerines, and a BLAST search confirmed that our primer set targets TRF2 in closely related barn swallows (Hirundo rustico). TPP1 and POT1 each have a single transcript in adult tree swallows that is highly expressed across tissues, and BLAST searches confirmed that our primer sets targeted TPP1 and POT1 genes, respectively, in multiple bird species. We also designed primers for RAP1 based on tree swallow transcripts of TRF2IP (TRF2-interacting protein), a common alias for RAP1. However, this study omits TRF1 due to negligible expression in nestling blood, and TIN2 because we could not confidently identify the passerine sequence for TIN2. Thus, altogether we quantified gene expression for four key components of the shelterin complex: TRF2, RAP1, TPP1, and POT1 (primer sequences in Table S1). qPCR for Shelterin Protein Gene Expression: We extracted RNA using a phenol-chloroform-based Trizol method (Invitrogen, Carlsbad, CA) with PhaseLock tubes (5PRIME, #2302830). We synthesized cDNA using 1µg RNA and Superscript III reverse transcriptase (Invitrogen), treated with DNAase (Promega, Madison, WI) and RNase inhibitor (RNAsin N2111, Promega). For each gene of interest, we used the 2-∆∆Ct method of quantification (Livak & Schmittgen, 2001), in which expression is normalized to the geometric mean Ct of two reference genes for each sample (Vandesompele et al., 2002), and relative to a calibrator sample on each plate. Reference genes correct for technical variation in cDNA quantity across samples, and as such, must (i) be highly expressed, (ii) exhibit low variability among samples, and (iii) show no significant variation among biological categories of interest. Our reference genes were PPIA (peptidylprolyl isomerase A; Virgin & Rosvall, 2018) and MRPS25 (Mitochondrial Ribosomal Protein S25; Woodruff et al., 2022). Preliminary work showed that New York samples exhibited markedly higher gene expression of these and a third reference gene (GAPDH). This violates assumption (iii) of the 2-∆∆CT method, and we therefore had to omit New York gene expression data. The remaining six populations exhibited limited among-population variation in reference gene expression (non-significant state differences or ≤ 0.5 Ct of the study-wide average). Samples were run in triplicate alongside No Template Controls (NTCs), using PerfeCta SYBR Green FastMix with low ROX (Quanta Biosciences, Gaithersburg MD) on 384-well plates using an ABI Quantstudio 5 machine with Quantstudio Design & Analysis software (v1.4.3, Thermo Fisher Scientific, Foster City, CA). Each well included 3µL of cDNA diluted 1:50 (or 3µL water, for NTCs) and primers diluted to 0.3µM in a total volume of 10µL. All reactions use the following thermal profile: 10 min at 95°, followed by 40 cycles

Environmental gradients constrain physiological performance and thus species’ ranges, suggesting that species occurrence in diverse environments may be associated with local adaptation. Genome-environment association analyses (GEAA) have become central for studies of local adaptation, yet they are sensitive to the spatial orientation of historical range expansions relative to landscape gradients. To test whether potentially adaptive genotypes occur in varied climates in wide-ranged species, we implemented GEAA on the basis of genome-wide data from the anole lizards Anolis ortonii and A. punctatus, which expanded from Amazonia, presently dominated by warm and wet settings, into the cooler and less rainy Atlantic Forest. To examine whether local adaptation has been constrained by population structure and history, we estimated effective population sizes, divergence times, and gene flow under a coalescent framework. In both species, divergence between Amazonian and Atlantic Forest populations dates back to the mid-Pleistocene, with subsequent gene flow. We recovered eleven candidate genes involved with metabolism, immunity, development, and cell signaling in A. punctatus, and found no loci whose frequency is associated with environmental gradients in A. ortonii. Distinct signatures of adaptation between these species are not associated with historical constraints or distinct climatic space occupancies. Similar patterns of spatial structure between selected and neutral SNPs along the climatic gradient, as supported by patterns of genetic clustering in A. punctatus, may have led to conservative GEAA performance. This study illustrates how tests of local adaptation can benefit from knowledge about species histories to support hypothesis formulation, sampling design, and landscape gradient characterization.

Pleistocene climate cycles are well known to have shaped contemporary species distributions and genetic diversity. Northward range expansions in response to deglaciation following the Last Glacial Maximum (LGM; ~21,000 years ago) have been surmised to lead to population size expansions in terrestrial taxa and changes in seasonal migratory behaviour. Recent findings, however, suggest that some northern temperate populations may have been more stable than expected through the LGM. We modelled the demographic history of twenty co-distributed boreal-breeding bird species of North America from full mitochondrial gene sets and species-specific molecular rates. We used these demographic reconstructions to test how species with different migratory strategies were affected by glacial cycles. Our results suggest that effective population sizes increased in response to deglaciation during the middle Wisconsin period (~45,000 years ago) whereas genetic diversity was maintained throughout the LGM despite shifts in geographic range. We conclude that earlier glacial cycles prior to the LGM have most strongly shaped contemporary genetic diversity in these high-latitude species. We did not find differences in historic population dynamics between species differing in migratory behaviour, contributing to growing evidence that major switches in migratory strategy during the Last Glacial Maximum are unnecessary to explain contemporary migratory patterns.

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Stockbridge town by race. It includes the distribution of the Non-Hispanic population of Stockbridge town across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Stockbridge town across relevant racial categories.

Key observations

Of the Non-Hispanic population in Stockbridge town, the largest racial group is White alone with a population of 1,800 (96.36% of the total Non-Hispanic population).

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Stockbridge town
• Population: The population of the racial category (for Non-Hispanic) in the Stockbridge town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Stockbridge town total Non-Hispanic population. 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 Stockbridge town Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Hornby town by race. It includes the distribution of the Non-Hispanic population of Hornby town across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Hornby town across relevant racial categories.

Key observations

Of the Non-Hispanic population in Hornby town, the largest racial group is White alone with a population of 1,800 (97.72% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Hornby town
• Population: The population of the racial category (for Non-Hispanic) in the Hornby town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Hornby town total Non-Hispanic population. 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 Hornby town Population by Race & Ethnicity. You can refer the same here