In 1938, the year before the outbreak of the Second world War, the countries with the largest populations were China, the Soviet Union, and the United States, although the United Kingdom had the largest overall population when it's colonies, dominions, and metropole are combined. Alongside France, these were the five Allied "Great Powers" that emerged victorious from the Second World War. The Axis Powers in the war were led by Germany and Japan in their respective theaters, and their smaller populations were decisive factors in their defeat. Manpower as a resource In the context of the Second World War, a country or territory's population played a vital role in its ability to wage war on such a large scale. Not only were armies able to call upon their people to fight in the war and replenish their forces, but war economies were also dependent on their workforce being able to meet the agricultural, manufacturing, and logistical demands of the war. For the Axis powers, invasions and the annexation of territories were often motivated by the fact that it granted access to valuable resources that would further their own war effort - millions of people living in occupied territories were then forced to gather these resources, or forcibly transported to work in manufacturing in other Axis territories. Similarly, colonial powers were able to use resources taken from their territories to supply their armies, however this often had devastating consequences for the regions from which food was redirected, contributing to numerous food shortages and famines across Africa, Asia, and Europe. Men from annexed or colonized territories were also used in the armies of the war's Great Powers, and in the Axis armies especially. This meant that soldiers often fought alongside their former-enemies. Aftermath The Second World War was the costliest in human history, resulting in the deaths of between 70 and 85 million people. Due to the turmoil and destruction of the war, accurate records for death tolls generally do not exist, therefore pre-war populations (in combination with other statistics), are used to estimate death tolls. The Soviet Union is believed to have lost the largest amount of people during the war, suffering approximately 24 million fatalities by 1945, followed by China at around 20 million people. The Soviet death toll is equal to approximately 14 percent of its pre-war population - the countries with the highest relative death tolls in the war are found in Eastern Europe, due to the intensity of the conflict and the systematic genocide committed in the region during the war.

Until the 1800s, population growth was incredibly slow on a global level. The global population was estimated to have been around 188 million people in the year 1CE, and did not reach one billion until around 1803. However, since the 1800s, a phenomenon known as the demographic transition has seen population growth skyrocket, reaching eight billion people in 2023, and this is expected to peak at over 10 billion in the 2080s.

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.

Published in The Anthropocene Review. Abstract: Enormous growth of the world population during the last two centuries and its present slowing down pose questions about precedents in history and broader forces shaping the population size. Population estimates collected in an extensive survey of literature (873 estimates from 25 studies covering 1,000,000 BCE to 2100 CE) show that world population growth has proceeded in two distinct phases of acceleration followed by stoppage—from at least 25,000 BCE to 100 BCE, and from 400 CE to the present, interrupted by centuries of standstill and 10% decrease. Both phases can be fitted with a mathematical function that projects to a peak at 11.2 ± 1.5 billion around 2100 CE. An interaction model can account for this acceleration-stoppage pattern in quantitative detail: Technology grows exponentially, with rate boosted by population. Population grows exponentially, capped by Earth’s carrying capacity. Technology raises this cap, but only until it approaches Earth’s ultimate carrying capacity.

The Holocaust was the systematic extermination of Europe's Jewish population in the Second World War, during which time, up to six million Jews were murdered as part of Nazi Germany's "Final Solution to the Jewish Question". In the context of the Second World War, the term "Holocaust" is traditionally used to reference the genocide of Europe's Jews, although this coincided with the Nazi regime's genocide and ethnic cleansing of an additional eleven million people deemed "undesirable" due to their ethnicity, beliefs, disability or sexuality (among others). During the Holocaust, Poland's Jewish population suffered the largest number of fatalities, with approximately three million deaths. Additionally, at least one million Jews were murdered in the Soviet Union, while Hungary, Latvia, Lithuania, the Netherlands and Yugoslavia also lost the majority of their respective pre-war Jewish populations. The Holocaust in Poland In the interwar period, Europe's Jewish population was concentrated in the east, with roughly one third living in Poland; this can be traced back to the Middle Ages, when thousands of Jews flocked to Eastern Europe to escape persecution. At the outbreak of the Second World War, it is estimated that there were 3.4 million Jews living in Poland, which was approximately ten percent of the total population. Following the German invasion of Poland, Nazi authorities then segregated Jews in ghettos across most large towns and cities, and expanded their network of concentration camps throughout the country. In the ghettos, civilians were deprived of food, and hundreds of thousands died due to disease and starvation; while prison labor was implemented under extreme conditions in concentration camps to fuel the German war effort. In Poland, six extermination camps were also operational between December 1941 and January 1945, which saw the mass extermination of approximately 2.7 million people over the next three years (including many non-Poles, imported from other regions of Europe). While concentration camps housed prisoners of all backgrounds, extermination camps were purpose-built for the elimination of the Jewish race, and over 90% of their victims were Jewish. The majority of the victims in these extermination camps were executed by poison gas, although disease, starvation and overworking were also common causes of death. In addition to the camps and ghettos, SS death squads (Einsatzgruppen) and local collaborators also committed widespread atrocities across Eastern Europe. While the majority of these atrocities took place in the Balkan, Baltic and Soviet regions, they were still prevalent in Poland (particularly during the liquidation of the ghettos), and the Einsatzgruppen alone are estimated to have killed up to 1.3 million Jews throughout the Holocaust. By early 1945, Soviet forces had largely expelled the German armies from Poland and liberated the concentration and extermination camps; by this time, Poland had lost roughly ninety percent of its pre-war Jewish population, and suffered approximately three million further civilian and military deaths. By 1991, Poland's Jewish population was estimated to be just 15 thousand people, while there were fewer than two thousand Jews recorded as living in Poland in 2018.

Author: S Wicklund, educator, Minnesota Alliance for Geographic EducationGrade/Audience: high schoolResource type: lessonSubject topic(s): population, mapsRegion: worldStandards: Minnesota Social Studies Standards

Standard 1. People use geographic representations and geospatial technologies to acquire, process and report information within a spatial context.

Standard 3. Places have physical characteristics (such as climate, topography and vegetation) and human characteristics (such as culture, population, political and economic systems).

Standard 5. The characteristics, distribution and migration of human populations on the earth’s surface influence human systems (cultural, economic and political systems).Objectives: Students will be able to:

1. Use maps of population distribution to examine the history of world population growth.
2. Construct a dot map to show current world population distribution.
3. Describe the difference between arithmetic and physiological densities.
4. Craft a response to a prompt to evaluate the Negative Population Growth perspective. Summary: Students will use maps of population distribution to examine the history of world population growth. They will also examine current world population distribution. Students will role-play the difference between arithmetic and physiologic densities using Egypt as an example. They will then craft a response to a prompt where they evaluate the Negative Population Growth perspective.

Throughout most of human history, global population growth was very low; between 10,000BCE and 1700CE, the average annual increase was just 0.04 percent. Therefore, it took several thousand years for the global population to reach one billion people, doing so in 1803. However, this period marked the beginning of a global phenomenon known as the demographic transition, from which point population growth skyrocketed. With the introduction of modern medicines (especially vaccination), as well as improvements in water sanitation, food supply, and infrastructure, child mortality fell drastically and life expectancy increased, causing the population to grow. This process is linked to economic and technological development, and did not take place concurrently across the globe; it mostly began in Europe and other industrialized regions in the 19thcentury, before spreading across Asia and Latin America in the 20th century. As the most populous societies in the world are found in Asia, the demographic transition in this region coincided with the fastest period of global population growth. Today, Sub-Saharan Africa is the region at the earliest stage of this transition. As population growth slows across the other continents, with the populations of the Americas, Asia, and Europe expected to be in decline by the 2070s, Africa's population is expected to grow by three billion people by the end of the 21st century.

The founding of New World populations by Asian peoples is the focus of considerable archaeological and genetic research, and there persist important questions on when and how these events occurred. Genetic data offer great potential for the study of human population history, but there are significant challenges in discerning distinct demographic processes. A new method for the study of diverging populations was applied to questions on the founding and history of Amerind-speaking Native American populations. The model permits estimation of founding population sizes, changes in population size, time of population formation, and gene flow. Analyses of data from nine loci are consistent with the general portrait that has emerged from archaeological and other kinds of evidence. The estimated effective size of the founding population for the New World is fewer than 80 individuals, approximately 1% of the effective size of the estimated ancestral Asian population. By adding a splitting parameter to population divergence models it becomes possible to develop detailed portraits of human demographic history. Analyses of Asian and New World data support a model of a recent founding of the New World by a population of quite small effective size.

It is estimated that the Second World War was responsible for the deaths of approximately 3.76 percent of the world's population between 1939 and 1945. In 2022, where the world's population reached eight billion, this would be equal to the death of around 300 million people.

The region that experienced the largest loss of life relative to its population was the South Seas Mandate - these were former-German territories given to the Empire of Japan through the Treaty of Versailles following WWI, and they make up much of the present-day countries of the Marshall Islands, Micronesia, the Northern Mariana Islands (U.S. territory), and Palau. Due to the location and strategic importance of these islands, they were used by the Japanese as launching pads for their attacks on Pearl Harbor and in the South Pacific, while they were also taken as part of the Allies' island-hopping strategy in their counteroffensive against Japan. This came at a heavy cost for the local populations, a large share of whom were Japanese settlers who had moved there in the 1920s and 1930s. Exact figures for both pre-war populations and wartime losses fluctuate by source, however civilian losses in these islands were extremely high as the Japanese defenses resorted to more extreme measures in the war's final phase.

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

The 1970 National Fertility Survey (NFS) was the second in a series of three surveys that followed the Growth of American Families surveys (1955 and 1960) aimed at examining marital fertility and family planning in the United States. Women were queried on the following main topics: residence history, age and race, family background, pregnancies, abortions and miscarriages, marriage history, education, employment and income, religion, use of family planning clinics, current and past birth control pill use and other methods of contraception, sterility, ideals regarding childbearing, attitudes and opinions with respect to abortion, gender roles, sterilization and world population, and birth histories. Respondents were asked to give residence histories for themselves and their husbands. Specifically, they were asked about the state they grew up in, whether they had lived with both parents, whether they had lived on a farm growing up, and whether they were currently living on a farm. Respondents were asked to give their date of birth, current age and race, as well as that of their husband. Regarding family background, respondents were asked how many brothers and sisters that they had, whether their siblings were older or younger, and whether there were any twins in the family. Additionally, respondents were asked to summarize their pregnancy history by giving information with respect to total number of pregnancies, live births, miscarriages, and abortions. Regarding abortions, respondents also were asked to give the date of the abortion and if they had used any family planning techniques prior to the abortion. Respondents were queried about their marriage history, specifically they were asked whether this was their first marriage, whether it was their spouse's first marriage, and their total number of marriages. If previously married, respondents were asked about the dates of past marriages and reasons for the marriage ending (e.g., death, divorce, or annulment). Respondents were asked a series of questions about both their own and their spouse's education including number of grades completed, current educational status, schooling completed after marriage, highest grade completed, and highest grade the respondent and spouse hoped to complete. All respondents were queried about their own and their husband's employment situations, as well as their household income. Respondents were asked about employment prior to and after marriage, employment after the birth of their first child, reasons for working, future employment expectations, earned income for both the respondent and husband in 1970, and other sources of income. There was also a series of questions on religion including religious preferences growing up, current religious preferences, and the importance of religion for both the respondent and her husband. Respondents were asked whether they had ever been to a family planning clinic, whether methods of family planning were discussed with a doctor or other medically trained person, whether this had taken place in the last 12 months, and if not, when the last time was. Several questions were devoted to the respondent's current and past use of the birth control pill and other methods of contraception such as the IUD and the diaphragm. Specifically, respondents were asked how they obtained the method of contraception for the first time, whether the respondent had sought methods of contraception from a doctor, and whether they had discussed with a doctor problems related to the methods of contraception. Respondents were asked why they used the pill and other methods of contraception, why they had stopped using a particular method, whether the methods were being used for family planning, and during what intervals the methods were used. Respondents also were asked questions about sterility including whether they were able to have children, whether they or their husband had undergone a sterilization operation, and if so, what kind of operation it was, the motive for having such an operation, whether the respondent had arrived at menopause, and if they had seen a doctor if they were unable to have a baby. They were also asked about their ideals with respect to children including their ideal number of children, the ideal number of boys and girls, as well as the ideal age for having their first and last child. The survey also sough

Throughout history, the displacement and migration of Jewish populations has been a repeating theme. In ancient times, the worlds Jewish population was concentrated in the Middle East, especially around Judaism's spiritual homeland in present-day Israel. However, the population distribution of the world's Jewry began to shift in the Middle Ages, with an increasing share living in Europe. Initially, Western Europe (particularly France, Italy, and Spain) had the largest Jewish populations, before they then migrated eastward in later centuries. Between the 18th and mid-20th centuries, over half of the worl'd Jews lived in Europe, with over 80 percent of these living in Eastern Europe.

Poland had become a refuge for Jews fleeing persecution in the Middle Ages, although shifting borders and foreign influence meant that long-term security was never fully attained, and a series of pogroms in the Russian Empire in the 1800s, and rising anti-Semitism in Central Europe in the early-1900s contributred to waves of migration to the United States and Israel during this time. After the Holocaust saw the genocide of up to six million Jews (over one third of the world's Jewish population), the share of Jews living in Europe dropped drastically, and emmigration outside of Europe increased. Today, the United States has the world's largest Jewish population in the world at around 7.3 million people, just ahead of Israel with 7.1 million.

How were cities distributed globally in the past? How many people lived in these cities? How did cities influence their local and regional environments? This month's map seeks to answer these questions by illustrating the worlds population growth within cities over a span of 6,000 years.According to the map authors, By 2030, 75 percent of of the world's population is expected to be living in cities. Today, about 54 percent of us do. In 1960, only 34 percent of the world lived in cities.The dots on the map represent the approximate location and size of urban populations worldwide.An animated version showing the development of cities over time is available at https://mtc.maps.arcgis.com/apps/Cascade/index.html?appid=fb8666425e0c44a2a77c5bb84ceec6efSource: Metrocosm, June 2016 - Watch as the world’s cities appear one-by-one over 6,000 years

Between 1800 and 2021, the total population of each continent experienced consistent growth, however as growth rates varied by region, population distribution has fluctuated. In the early 19th century, almost 70 percent of the world's population lived in Asia, while fewer than 10 percent lived in Africa. By the end of this century, it is believed that Asia's share will fall to roughly 45 percent, while Africa's will be on course to reach 40 percent. 19th and 20th centuries Fewer than 2.5 percent of the world's population lived in the Americas in 1800, however the demographic transition, along with waves of migration, would see this share rise to almost 10 percent a century later, peaking at almost 14 percent in the 1960s. Europe's share of the global population also grew in the 19th century, to roughly a quarter in 1900, but fell thereafter and saw the largest relative decline during the 20th century. Asia, which has consistently been the world's most populous continent, saw its population share drop by the mid-1900s, but it has been around 60 percent since the 1970s. It is important to note that the world population has grown from approximately one to eight billion people between 1800 and the 2020s, and that declines in population distribution before 2020 have resulted from different growth rates across the continents. 21st century Africa's population share remained fairly constant throughout this time, fluctuating between 7.5 and 10 percent until the late-1900s, but it is set to see the largest change over the 21st century. As Europe's total population is now falling, and it is estimated that the total populations of Asia and the Americas will fall by the 2050s and 2070s respectively, rapid population growth in Africa will see a significant shift in population distribution. Africa's population is predicted to grow from 1.3 to 3.9 billion people over the next eight decades, and its share of the total population will rise to almost 40 percent. The only other continent whose population will still be growing at this time will be Oceania, although its share of the total population has never been more than 0.7 percent.

The world's Jewish population has had a complex and tumultuous history over the past millennia, regularly dealing with persecution, pogroms, and even genocide. The legacy of expulsion and persecution of Jews, including bans on land ownership, meant that Jewish communities disproportionately lived in urban areas, working as artisans or traders, and often lived in their own settlements separate to the rest of the urban population. This separation contributed to the impression that events such as pandemics, famines, or economic shocks did not affect Jews as much as other populations, and such factors came to form the basis of the mistrust and stereotypes of wealth (characterized as greed) that have made up anti-Semitic rhetoric for centuries. Development since the Middle Ages The concentration of Jewish populations across the world has shifted across different centuries. In the Middle Ages, the largest Jewish populations were found in Palestine and the wider Levant region, with other sizeable populations in present-day France, Italy, and Spain. Later, however, the Jewish disapora became increasingly concentrated in Eastern Europe after waves of pogroms in the west saw Jewish communities move eastward. Poland in particular was often considered a refuge for Jews from the late-Middle Ages until the 18th century, when it was then partitioned between Austria, Prussia, and Russia, and persecution increased. Push factors such as major pogroms in the Russian Empire in the 19th century and growing oppression in the west during the interwar period then saw many Jews migrate to the United States in search of opportunity.

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

There is a large body of research on utilizing online activity as a survey of political opinion to predict real world election outcomes. There is considerably less work, however, on using this data to understand topic-specific interest and opinion amongst the general population and specific demographic subgroups, as currently measured by relatively expensive surveys. Here we investigate this possibility by studying a full census of all Twitter activity during the 2012 election cycle along with the comprehensive search history of a large panel of Internet users during the same period, highlighting the challenges in interpreting online and social media activity as the results of a survey. As noted in existing work, the online population is a non-representative sample of the offline world (e.g., the U.S. voting population). We extend this work to show how demographic skew and user participation is non-stationary and difficult to predict over time. In addition, the nature of user contributions varies substantially around important events. Furthermore, we note subtle problems in mapping what people are sharing or consuming online to specific sentiment or opinion measures around a particular topic. We provide a framework, built around considering this data as an imperfect continuous panel survey, for addressing these issues so that meaningful insight about public interest and opinion can be reliably extracted from online and social media data.

The first version of this data base originally was set up for testing and validation of the so-called Integrated Model of the Greenhouse Effect (the IMAGE model; see Alcamo, 1994), developed at RIVM. The main aim of the model is to use state-of-the-art models to assist policy makers in the development and evaluation of future scenarios to mitigate the negative effects of global change. The modelling framework consists of several subsystems that cover the different aspects of the earth system.

    Many calculations in IMAGE and other models are performed on a 0.5o by 0.5o
    longitude/latitude grid. This is because nearly all potential impacts of
    climate change (impacts on ecosystems, agriculture and coastal flooding) have a
    strong spatial variability. Moreover, land use related greenhouse gas emissions
    depend on local environmental conditions and human activity. There are also
    other reasons for using grid-scale information. First, policy makers are
    interested in regional/national policies to address climate change. Secondly,
    grid-scale information makes model caluclations more testable against
    observations as compared to more aggregated models.

    Nevertheless, it is infeasable to perform grid-based calculations for economic
    models, because of the difficulty in specifying economic/demographic factors on
    a country scale for the entire world over the long horizon of the model.
    Therefore, the world has been divided into 19 world regions, according to
    economic and geographic similarity. This classification also takes into account
    the regional aggregations used by the IPCC, OECD, FAO, UN and IEA. It should be
    noted, however, that IMAGE has the additional requirement that countries within
    a region be adjacent or nearby because of the model's approach to global land
    cover simulation.

    An important initiative for the update the previous version of HYDE (Klein
    Goldewijk, 2001) was the publication of a new population density data base, the
    Gridded World Population v.3 (Balk et al, 2005), which is now used as a
    starting point for historical gridded population calculations. Because
    population data are important in many calculations, it resulted in modified
    land cover estimates, as well as estimates for GDP, value added, private
    consumption. Furthermore, numerous new data have been incorporated in many
    tables.

    Besides the testing of IMAGE, HYDE has already been used for integrated
    environmental assessents such as the Global Environmental Outlook (GEO) of the
    United Nations Enviromental Programme (UNEP, 1997), technical background
    reports for GEO (RIVM/UNEP, 1997), the TARGETS project (Rotmans and De Vries,
    1997), the Dutch National Environmental Outlook (RIVM, 1997) and the Mappae
    Mundi project (Goudsblom and De Vries, 2002). Also, HYDE has contributed to
    other research e.g. in the field of historical atmospheric trace gas
    inventories (e.g. Kroeze et al, 1999; den Elzen et al, 1999; van Aardenne et
    al, 2001; Pitman et al, 2000; Pielke et al, 2003 ), biological diversity (e.g.
    Gaston et al, 2003), and climate reconstructions (e.g. Matthews et al, 2003;
    Brovkin et al, 2004).

    Furthermore, this effort very much fits within the Land-Use and Land-Cover
    Change LUCC project, (activity 3; database development), part of the the
    International Human Dimensions Project (IHDP), and the PAGES (Human
    Interactions in Past Environmental Changes) - focus 3: Human Impacts on
    Terrestrial Ecosystems (HITE) initiative. PAGES is the International
    Geosphere-Biosphere Programme (IGBP) core project charged with providing a
    quantitative understanding of the Earth's past climate and environment.

    Please note that this data base is far from complete. Work is continuous in
    progress to update and extent the data series where possible.

    [Summary provided by MNP]

In 1800, the region of Germany was not a single, unified nation, but a collection of decentralized, independent states, bound together as part of the Holy Roman Empire. This empire was dissolved, however, in 1806, during the Revolutionary and Napoleonic eras in Europe, and the German Confederation was established in 1815. Napoleonic reforms led to the abolition of serfdom, extension of voting rights to property-owners, and an overall increase in living standards. The population grew throughout the remainder of the century, as improvements in sanitation and medicine (namely, mandatory vaccination policies) saw child mortality rates fall in later decades. As Germany industrialized and the economy grew, so too did the argument for nationhood; calls for pan-Germanism (the unification of all German-speaking lands) grew more popular among the lower classes in the mid-1800s, especially following the revolutions of 1948-49. In contrast, industrialization and poor harvests also saw high unemployment in rural regions, which led to waves of mass migration, particularly to the U.S.. In 1886, the Austro-Prussian War united northern Germany under a new Confederation, while the remaining German states (excluding Austria and Switzerland) joined following the Franco-Prussian War in 1871; this established the German Empire, under the Prussian leadership of Emperor Wilhelm I and Chancellor Otto von Bismarck. 1871 to 1945 - Unification to the Second World War The first decades of unification saw Germany rise to become one of Europe's strongest and most advanced nations, and challenge other world powers on an international scale, establishing colonies in Africa and the Pacific. These endeavors were cut short, however, when the Austro-Hungarian heir apparent was assassinated in Sarajevo; Germany promised a "blank check" of support for Austria's retaliation, who subsequently declared war on Serbia and set the First World War in motion. Viewed as the strongest of the Central Powers, Germany mobilized over 11 million men throughout the war, and its army fought in all theaters. As the war progressed, both the military and civilian populations grew increasingly weakened due to malnutrition, as Germany's resources became stretched. By the war's end in 1918, Germany suffered over 2 million civilian and military deaths due to conflict, and several hundred thousand more during the accompanying influenza pandemic. Mass displacement and the restructuring of Europe's borders through the Treaty of Versailles saw the population drop by several million more.

Reparations and economic mismanagement also financially crippled Germany and led to bitter indignation among many Germans in the interwar period; something that was exploited by Adolf Hitler on his rise to power. Reckless printing of money caused hyperinflation in 1923, when the currency became so worthless that basic items were priced at trillions of Marks; the introduction of the Rentenmark then stabilized the economy before the Great Depression of 1929 sent it back into dramatic decline. When Hitler became Chancellor of Germany in 1933, the Nazi government disregarded the Treaty of Versailles' restrictions and Germany rose once more to become an emerging superpower. Hitler's desire for territorial expansion into eastern Europe and the creation of an ethnically-homogenous German empire then led to the invasion of Poland in 1939, which is considered the beginning of the Second World War in Europe. Again, almost every aspect of German life contributed to the war effort, and more than 13 million men were mobilized. After six years of war, and over seven million German deaths, the Axis powers were defeated and Germany was divided into four zones administered by France, the Soviet Union, the UK, and the U.S.. Mass displacement, shifting borders, and the relocation of peoples based on ethnicity also greatly affected the population during this time. 1945 to 2020 - Partition and Reunification In the late 1940s, cold war tensions led to two distinct states emerging in Germany; the Soviet-controlled east became the communist German Democratic Republic (DDR), and the three western zones merged to form the democratic Federal Republic of Germany. Additionally, Berlin was split in a similar fashion, although its location deep inside DDR territory created series of problems and opportunities for the those on either side. Life quickly changed depending on which side of the border one lived. Within a decade, rapid economic recovery saw West Germany become western Europe's strongest economy and a key international player. In the east, living standards were much lower, although unemployment was almost non-existent; internationally, East Germany was the strongest economy in the Eastern Bloc (after the USSR), though it eventually fell behind the West by the 1970s. The restriction of movement between the two states also led to labor shortages in t...

See "01_ASDN_readme.txt" (under "Download Data" tab) for data author and contact information. Field data on shorebird ecology and environmental conditions were collected from 1993-2014 at 16 field sites in Alaska, Canada, and Russia. Data were not collected in every year at all sites. Studies of the population ecology of these birds included nest-monitoring to determine timing of reproduction and reproductive success; live capture of birds to collect blood samples, feathers, and fecal samples for investigations of population structure and pathogens; banding of birds to determine annual survival rates; resighting of color-banded birds to determine space use and site fidelity; and use of light-sensitive geolocators to investigate migratory movements. Data on climatic conditions, prey abundance, and predators were also collected. Environmental data included weather stations that recorded daily climatic conditions, surveys of seasonal snowmelt, weekly sampling of terrestrial and aquatic invertebrates that are prey of shorebirds, live trapping of small mammals (alternate prey for shorebird predators), and daily counts of potential predators (jaegers, falcons, foxes). Detailed field methods for each year are available in the ASDN_protocol_201X.pdf files. All research was conducted under permits from relevant federal, state and university authorities.

Potential users of these data should first contact the relevant data author(s), listed below. This will enable coordination in terms of updates/corrections to the data and ongoing analyses. Key analyses of the data are in progress and will be included in the theses and dissertations of graduate students who collected these field data.

Please acknowledge this dataset and the authors in any analysis, publication, presentation, or other output that uses these data. If you use the full dataset, we suggest you cite it as:
Lanctot, RB, SC Brown, and BK Sandercock. 2017. Arctic Shorebird Demographics Network. NSF Arctic Data Center. doi: INSERT HERE. If you use data from only one or a few sites, we suggest you cite data for each site as per this example:
Lanctot, RB and ST Saalfeld. 2017. Barrow, 2014. Arctic Shorebird Demographics Network. NSF Arctic Data Center. doi: INSERT HERE. Note that each updated version of the dataset has its own unique DOI.

Disclaimers: The dataset is distributed “as is” and with absolutely no warranty. The data providers have invested considerable effort to ensure that the data are of highest quality, but it is possible that undetected errors remain. Data have been processed with several steps for quality assurance, but the data providers accept no liability or guarantee that the data are up-to-date, correct, or complete. Access to data is provided on the understanding that the data providers are not responsible for any damages from inaccuracies in the data.