About this dataset

Context

The dataset tabulates the Manns Choice population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Manns Choice. The dataset can be utilized to understand the population distribution of Manns Choice by age. For example, using this dataset, we can identify the largest age group in Manns Choice.

Key observations

The largest age group in Manns Choice, PA was for the group of age Under 5 years years with a population of 39 (12.38%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Manns Choice, PA was the 85 years and over years with a population of 3 (0.95%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

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

Age groups:

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

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Manns Choice is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Manns Choice total 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 Manns Choice Population by Age. You can refer the same here

About this dataset

Context

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

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Manns Choice, PA, is 44.0.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Manns Choice, PA, is 29.1.
• Total dependency ratio for Manns Choice, PA is 73.1.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Manns Choice, PA is 3.4.

Content

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

Age groups:

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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

About this dataset

Context

The dataset tabulates the Manns Choice 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 Manns Choice 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 Manns Choice was 310, a 0.64% decrease year-by-year from 2022. Previously, in 2022, Manns Choice population was 312, a decline of 0.32% compared to a population of 313 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Manns Choice increased by 18. In this period, the peak population was 314 in the year 2020. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

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

Data Coverage:

• From 2000 to 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 Manns Choice is shown in this column.
• Year on Year Change: This column displays the change in Manns Choice 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 Manns Choice Population by Year. You can refer the same here

Modeled vote choice of geographic, demographic, and turnout subgroups with survey and ecological data in the US. The current version models Presidential vote choice in 2016 and 2020 for each contemporaneous congressional district and each of four racial groups. The methodology is introduced and explained in Kuriwaki et al. (2023). “The Geography of Racially Polarized Voting: Calibrating Surveys at the District Level.” American Political Science Review. https://osf.io/mk9e6/

Yearly citation counts for the publication titled "The effects of spatial population dataset choice on estimates of population at risk of disease".

Mate-choice copying is a type of social learning in which females can change their mate preference after observing the choice of others. This behaviour can potentially affect population evolution and ecology, namely through increased dispersal and reduced local adaptation. Here, we simulated the effects of mate-choice copying in populations expanding across an environmental gradient to understand whether it can accelerate or retard the expansion process. Two mate-choice copying strategies were used: when females target a single individual, and when females target similar individuals. We also simulated cases where the male trait singled out by females with mate-choice maps perfectly onto their genotype or is influenced by genotype-by-environment interactions. These rules have different effects on the results. When a trait is determined by genotype alone, populations where copier females target all similar males expand faster, and the number of potential copiers increases. However, when p..., , , # Mate-choice copying accelerates species range expansion

https://doi.org/10.5061/dryad.bzkh189jh

This database contains the code used to run the individual-based simulations used to study the effects of mate-choice copying in a population expanding through an environmental gradient. These simulations show that different preference rules and mate-choice copying strategies can affect the speed of population range expansion.

Description of the data and file structure

The simulation code is contained in 5 different files:

• main.c: This is the main file for the simulation. It contains the fixed parameters for the simulation (described in the comments of the code itself), the link to all the other files, and the main code to run each generation loop and the simulation itself.
• input.h: This is the file with the parameters that were changed during the different simulations. The file also contains a description of each parame...

As biparental care is crucial for breeding success in Procellariiformes seabirds (i.e., albatrosses and petrels), these species are expected to be choosy during pair formation. However, the choice of partners is limited in small-sized populations, which might lead to random pairing. In Procellariiformes, the consequences of such limitations for mating strategies have been examined in a single species. Here, we studied mate choice in another Procellariiforme, Bulwer’s petrel Bulweria bulwerii, in the Azores (ca 70 breeding pairs), where the species has suffered a dramatic population decline. We based our approach on both a 11-year demographic survey (capture-mark-recapture) and a genetic approach (microsatellites, n = 127 individuals). The genetic data suggest that this small population is not inbred and did not experience a genetic bottleneck. Moreover, pairing occurred randomly with respect to genetic relatedness, we detected no extrapair parentage (n = 35 offspring), and pair fecundit...

The selection pressures imposed by mate choice for species identity should impose strong stabilizing selection on traits that confer species identity to mates. Thus, we expect that such traits should show non-overlapping distributions among closely related species, but show little to no variance among populations within a species. We tested these predictions by comparing levels of population differentiation in the sizes and shapes of male cerci (i.e., the clasper structures used for species identity during mating) of six Enallagma damselfly species. Cerci shapes were non-overlapping among Enallagma species, and five of six Enallagma species showed no population variation across their entire species ranges. In contrast, cerci sizes overlapped among species and varied substantially among populations within species. These results, taken with previous studies, suggest that cerci shape is a primary feature used in species recognition used to discriminate conspecific from heterospecific...

About this dataset

Context

The dataset tabulates the population of Manns Choice by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Manns Choice. The dataset can be utilized to understand the population distribution of Manns Choice by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Manns Choice. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Manns Choice.

Key observations

Largest age group (population): Male # 0-4 years (32) | Female # 10-14 years (18). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Age groups:

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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Manns Choice population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Manns Choice is shown in the following column.
• Population (Female): The female population in the Manns Choice is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Manns Choice for each age group.

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 Manns Choice Population by Gender. You can refer the same here

There are two methods of standardising: direct and indirect. Both methods rely upon reference to a single standard population, which has a known population structure (in the case of direct standardisation) or known age-specific rates (in the case of indirect standardisation). The choice of standard population is important, as it influences the standardised rates or ratios obtained.

The effective management of fish populations requires understanding of both the biology of the species being managed and the behavior of the humans who harvest those species. For many marine fisheries, recreational harvests represent a significant portion of the total fishing mortality. For such fisheries, therefore, a model that captures the dynamics of angler choices and the fish population would be a valuable tool for fisheries management. In this study, we provide such a model, focusing on red drum and spotted seatrout, which are the two of the main recreational fishing targets in the Gulf of Mexico. The biological models are in the form of vector autoregressive models. The anglers’ decision model takes the discrete choice approach, in which anglers first decide whether to go fishing and then determine the location to fish based on the distance and expected catch of two species of fish if they decide to go fishing. The coupled model predicts that, under the level of fluctuation in the abundance of the two species experienced in the past 35 years, the number of trips that might be taken by anglers fluctuates moderately. This fluctuation is magnified as the cost of travel decreases because the anglers can travel long distance to seek better fishing conditions. On the other hand, as the cost of travel increases, their preference to fish in nearby areas increases regardless of the expected catch in other locations and variation in the trips taken declines. The model demonstrates the importance of incorporating anglers’ decision processes in understanding the changes in a fishing effort level. Although the model in this study still has a room for further improvement, it can be used for more effective management of fish and potentially other populations.

The statistic presents the ratings of the People's Choice Awards ceremonies in the United States from 2014 to 2018. According to the source, *** percent of adults aged 18 to 49 tuned into the 2018 ceremony following its switch from CBS to E!.

The nematode Caenorhabditis elegans is a central laboratory model system in almost all biological disciplines, yet its natural life history and population biology are largely unexplored. Such information is essential for in-depth understanding of the nematode's biology because its natural ecology provides the context, in which its traits and the underlying molecular mechanisms evolved. We characterized natural phenotypic and genetic variation among North German C. elegans isolates. We used the unique opportunity to compare samples collected 10 years apart from the same compost heap and additionally included recent samples for this and a second site, collected across a 1.5-year period. Our analysis revealed significant population genetic differentiation between locations, across the 10-year time period, but for only one location a trend across the shorter time frame. Significant variation was similarly found for phenotypic traits of likely importance in nature, such as choice behavior and population growth in the presence of pathogens or naturally associated bacteria. Phenotypic variation was significantly influenced by C. elegans genotype, time of isolation, and sampling site. The here studied C. elegans isolates may provide a valuable, genetically variable resource for future dissection of naturally relevant gene functions.

Cosmopolitan pests can consist of geographic populations that differ in their current host ranges or in their ability to colonize a novel host. We compared the responses of cowpea-adapted seed-beetle populations (Callosobruchus maculatus [F.]) from Africa, North America, and South America to four novel legumes: chickpea, lentil, mung bean, and pea. We also qualitatively compared these results to those obtained earlier for an Asian population. For each host, we measured larval survival to adult emergence, and used both no-choice and choice tests to estimate host acceptance. The pattern of larval survival was similar among populations: high or moderately high survival on cowpea, mung bean, and chickpea, intermediate survival on pea, and very low survival on lentil. One exception was unusually high survival of African larvae on pea, and there was modest variation among populations for survival on lentil. The African population was also an outlier with respect to host acceptance; under no-choice conditions, African females showed a much greater propensity to accept the two least preferred hosts, chickpea and lentil. However, greater acceptance of these hosts by African females was not evident in choice tests. Inferences about populations differences in host acceptance can thus strongly depend on experimental protocol. Future selection experiments can be used to determine whether the observed population differences in initial performance will affect the probability of producing self-sustaining populations on a marginal crop host.

How mate preferences evolve in the first place has been a major conundrum for sexual selection. Some hypotheses explaining this assume fitness benefit derived from subsequent generations. Major Histocompatibility Complex (MHC)-based mate choice is a representative example of the mate choice that is associated with such trans-generational mechanisms. To provide evidences for fitness benefit of MHC-based mate choice, previous studies assessed the association between own MHC genotype and own fitness components. However, the association between MHC-based mate choice in the parental generation and fitness components in the resultant offspring generation has only rarely been measured in wild populations. Focusing on the isolated population of the monogamous Ryukyu Scops Owl (Otus elegans interpositus) on Minami-daito Island, Japan, we found evidence of MHC-based mate choice. However, we found no evidence of MHC-based mate choice increasing own reproductive success or offspring survival. This is a rare case study that directly examines the existence of the trans-generational indirect benefit of MHC-based mate choice for genetic compatibility from trans-generational data in a wild bird population. By investigating the fitness benefits of mate choice, this study serves to facilitate our understanding of the evolution of MHC-based mate choice.

Abstract

The 2010 Population Census has been designed to meet various data needs, including as (1) the basis for updating population data bases up to the lowest level of administrative unit (village); (2) valuable input in monitoring the progress for achieving the Millennium Development Goals (MDGs); (3) the basis for preparing small area statistics; (4) basis for preparing population projection; (5) the basic data in developing sampling frame for various surveys conducted between 2010-2020.

During the 2010 Population Census it is estimated that the population of Indonesia would be around 232 million people who live in about 65 million households. Considering the huge number of population to be recorded the field enumeration will require more than 650.00 field workers, which consist about 450.000 enumerators, 150.000 team coordinators, and 15.000 field coordinators. Data collection is designed to be undertaken in groups, each group (team) consist of four persons, i.e. three numerators and one team coordinator. All field workers would have undertaken a three-day training before hand.

The peak of census operations will be during the months of May 2010 where field enumeration will be taking place simultaneously overall the geographical area of Indonesia. May 15 will be designated as the Census Date of the 2010 Population Census, therefore on the 15 of May 2010 the homeless and nomadic population will be canvassing.

Updating population data is a very crucial issue in the upcoming population census, in the sense that since the implementation of decentralization in 2001 the number of administrative units in the regions (province, district, sub district, and village) have been increasing tremendously, such that statistical measures could not appropriately follows the changes. Prior to decentralization the number of provinces was 27, districts 297, sub districts 4.200, and villages about 65.000. At present the number of provinces is 33, districts 497, sub districts about 7.000, and villages about 75.000.

Geographic coverage

National

Analysis unit

• Individuals;
• Households.

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Research instrument

In the modern context there is always an increasing demand for data and information, and this is not an exception for the census as well. A census being a huge national undertaking incurring substantial amount of money, while the resources are always constrained and limited. The choice of topic to be covered in a census mainly depends upon the user needs. However, as society becomes complex the demand of population data for development plans is not only increasing but the level of such information is switching to smaller administrative levels, while census being a complex and large operation has its own limitations in meeting all the demands of data users. Another main consideration for determining census topic is to maintain comparability and continuity of the census information.

There are three kind of questionnaires will be used in the 2010 Population Census, namely C1 (42 questions) for enumerate regular household who live in the areas that are covered in the mapping, C2 (14 questions) for enumerate population who live in the areas which are not included in the mapping such as remote areas, Indonesia corps diplomatic who live abroad and L2 (number and sex) for enumerate homeless people, boat people, and tribes.

The questionnaires hopefully can accommodate the data required for the compilations of MDG Indicators, which is essential for national policy making and monitoring. The census questionnaires are presently being developed taking into considerations of the relevant United Nation recommendations as well as the suitability of the items collected to meet local conditions.

In the past population censuses, data were collected basically by face-to-face interviews, where enumerators visited all households to interview persons therein one by one. In light of the changing lifestyle of big cities people and advancement of technology, new and additional means for data collection from the households will be introduced in the 2010 Population Census. Under the new multi-modal data collection approach, e-census on the Internet and self-enumeration will be rolled out, along with the traditional “interviewer” method.

Cleaning operations

The processing of data collected in a census constitutes one of the most important and challenging activities that have to be undertaken efficiently and expeditiously in order to justify the immense resources invested in a census. This activity entailed several processes: manual editing of the questionnaires after enumeration, data capture, data cleaning and validation, and finally tabulation. Intelligence character recognition (ICR) technology will be employed for data capture.

Government’s commitment to provide provisional results within two and half months after enumeration and final results within another six months greatly influenced the strategies and actions adopted at every stage of data processing in order to adhere to the commitment.

Data sets used to support analysis published by O'Corry-Crowe et al (2014) Crossing to safety: Dispersal, colonization and mate choice in evolutionarily distinct populations of Steller sea lions, Eumetopias jubatus. Molecular Ecology 23(22): 5415-5434. Data include Steller sea lion genetic data obtained from samples collected from pups on natal rookeries. The genetic data are genotypes at 16 microsatellite loci and haplotypes at mtDNA, spatial data, and allelic and haplotypic frequencies.

Age shapes fundamental processes related to behaviour, survival and reproduction. Where age influences reproductive success, non-random mating with respect to age can magnify or mitigate such effects. Consequently, the correlation in partners’ age across a population may influence its productivity. Despite widespread evidence for age-assortative mating, little is known about what drives this assortment and its variation. Specifically, the relative importance of active (same-age mate preference) and passive processes (assortment as a consequence of other spatial or temporal effects) in driving age-assortment is not well understood. In this paper, we compare breeding data from a great tit and mute swan population (51- and 31-year datasets respectively) to tease apart the contributions of pair retention, cohort age-structure, and active age-related mate selection to age-assortment in species with contrasting life-histories. Both species show age-assortative mating, and variable assortment...

Species with large geographic ranges provide an excellent model of how different populations respond to dissimilar local conditions, particularly variation in climate. Maternal effects, such as oviposition-site choice greatly affect offspring phenotypes and survival. Thus, maternal behavior has the potential to mitigate the effects of divergent climatic conditions across a species' range. We delineated natural nesting areas of six populations of painted turtles (Chrysemys picta) that span a broad latitudinal range and quantified spatial and temporal variation in nest characteristics. To quantify microhabitats available for females to choose, we also identified sites within the nesting area of each location that were representative of available thermal microhabitats. Across the range females nested non-randomly and targeted microhabitats that generally had less canopy cover and thus higher nest temperatures. Nest microhabitats differed among locations but did not predictably vary with latitude or historic mean air temperature during embryonic development. In conjunction with other studies of these populations, nest-site choice appears to be homogenizing nest environments, buffering embryos from thermally-induced selection, which could stymie evolution of embryonic traits. Thus, although effective at a macroclimatic scale, nest-site choice may be unable to compensate for novel stressors that rapidly increase local temperatures.

Biomarkers used in this study and number of observations for each data set.