About this dataset

Context

The dataset tabulates the Mesa 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 Mesa 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 Mesa was 385, a 0.52% decrease year-by-year from 2022. Previously, in 2022, Mesa population was 387, a decline of 0.51% compared to a population of 389 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Mesa decreased by 40. In this period, the peak population was 513 in the year 2018. 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 Mesa is shown in this column.
• Year on Year Change: This column displays the change in Mesa 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 Mesa Population by Year. You can refer the same here

City of Mesa population provided by Census Bureau Population Estimates Program (PEP) updated annually as of July 1. See Population and Housing Unit Estimates. Census PEP estimates are used for state revenue sharing per AZ statute (42-5033.01). This dataset is the authoritative source for all city metrics such as Crimes or Traffic Collisions per 1,000 residents.

2025-2040 population projections provided by Maricopa County Association of Governments (MAG) and adopted June 2023. MAG's planning area and incorporated jurisdiction projections are published at 2023 MAG Socioeconomic Projections

Other sources of population estimates include US Census American Community Survey 1-year and 5-year Estimates at https://citydata.mesaaz.gov/d/n5gn-m5c3 and https://citydata.mesaaz.gov/Economic-Development/d/9nqf-ygw6, Arizona Office of Economic Opportunity (OEO) at https://www.azcommerce.com/oeo/population/population-estimates/ (see link for OEO methodology which differs slightly from official US Census Estimates) and City of Mesa Office of Economic Development at https://www.selectmesa.com/business-environment/demographics (ESRI Community Analyst).

About this dataset

Context

The dataset tabulates the La Mesa population by year. The dataset can be utilized to understand the population trend of La Mesa.

Content

The dataset constitues the following datasets

• La Mesa, CA Population Dataset: Yearly Figures, Population Change, and Percent Change Analysis

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/.

Graph and download economic data for Resident Population in Phoenix-Mesa-Scottsdale, AZ (MSA) (PHXPOP) from 2000 to 2024 about Phoenix, AZ, residents, population, and USA.

In 2023, the population of the Phoenix-Mesa-Chandler metropolitan area in the United States was about 5.1 million people. This is a slight increase from the previous year, when the population was about 5.02 million people.

About this dataset

Context

The dataset tabulates the data for the Mesa County, CO population pyramid, which represents the Mesa County 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 Mesa County, CO, is 27.4.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Mesa County, CO, is 32.7.
• Total dependency ratio for Mesa County, CO is 60.1.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Mesa County, CO is 3.1.

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 Mesa County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Mesa County for the selected age group is shown in the following column.
• Population (Female): The female population in the Mesa County for the selected age group is shown in the following column.
• Total Population: The total population of the Mesa County 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 Mesa County Population by Age. You can refer the same here

The architecture of Las Mujeres (also known as Squaw Creek Ruin and NA 12555) was examined as part of the Legacies on the Landscape research project during the Spring 2007 field season. Room construction sequences, as indicated by bonded or abutted corners, are indicators of population growth. These patterns of bonded and abutted corners suggest whether a pueblo was built all at once or instead built incrementally through the gradual accretion of rooms. A gradual accretion of rooms could likely indicate a gradual increase in population, while a pueblo appearing to be built in once construction phase is more likely to indicate a rapid population increase.

Prehistoric farmers in the semi-arid American Southwest were challenged by marked spatial and temporal variation in, and overall low levels of, precipitation with which to grow their crops. One strategy they employed was to modify their landscape with rock alignments in order to concentrate surface water flow on their fields. A second challenge that has been less focused on by archaeologists is the need to maintain soil fertility by replenishing nutrients removed from the soil by agricultural crops. Numerous studies have shown that rock alignments can result in long-lasting impacts on soil properties and fertility. However, the direction and magnitude of change is highly variable. While previous work has emphasized the importance of overland flow in replenishing soil nutrient pools, none have investigated the influence of eolian deposition as a contributor of mineral-derived nutrients. This thesis explores the effects of the construction of rock alignments, agricultural harvest, and eolian deposition on soil properties and fertility on Perry Mesa within the Agua Fria National Monument. This site experienced dramatic population increase in the late 1200s and marked depopulation in the early 1400s. Since that time, although agriculture ceased, the rock alignments have remains, continuing to influence runoff and sediment deposition. In the summer of 2009, I investigated deep soil properties and mineral-derived nutrients on fields near Pueblo La Plata, one of the largest pueblos on Perry Mesa. To examine the effects of rock alignments and agricultural harvest independent of one another, I sampled soils from replicated plots behind alignments paired with nearby plots that are not bordered by an alignment in both areas of high and low prehistoric agricultural intensity. I investigated soil provenance and the influence of deposition on mineral-derived nutrients through analysis of the chemical composition of the soil, bedrock and dust. Agricultural rock alignments were significantly associated with differences in soil texture, but neither rock alignments nor agricultural history were associated with significant differences in mineral-derived nutrients. Instead, eolian deposition may explain why nutrient pools are similar across agricultural history and rock alignment presence. Eolian deposition homogenized the surface soil, reducing the spatial heterogeneity of soils. Dust is important both as a parent material to the soils on Perry Mesa, and also a source of mineral-derived nutrients. This investigation suggests that prehistoric agriculture on Perry Mesa was not likely limited by long term soil fertility, but instead could have been sustained by eolian inputs.

Habitat restoration efforts to conserve wildlife species are often conducted along a range of local site conditions, with limited information available to gauge relative outcomes for habitat suitability among sites and identify those that may lead to the greatest returns on restoration investment. We leveraged existing resource selection function models to generate heatmaps of spatially varying habitat suitability improvement potential for the Gunnison Sage-grouse (Centrocercus minimus) based on a suite of habitat restoration actions deployed across crucial habitats within six remaining satellite populations. We first simulated expected change in model covariates (habitat features) from a suite of restoration actions (increasing sagebrush, herbaceous, or litter cover, non-sagebrush shrub management, installation of mesic improvement structures, and removal of invasive plants) to generate modified input layers for each. We then reran the original models using these modified layers and calculated the predicted change in habitat suitability across space. The resulting heatmaps identify areas with the greatest improvement potential for each restoration action to help guide strategic restoration planning for the species. This data release, for the Pinon Mesa satellite population, includes a set of 15 total raster files. These include: 7 uncategorized heatmaps illustrating predicted change in Gunnison Sage-grouse habitat suitability across space following habitat restoration actions (either single or combined), 7 categorized heatmaps additionally showing areas where 1) new habitat was created, 2) non-habitat remained non-habitat despite management interventions, or 3) negative changes in suitability were observed, and 1 heatmap illustrating predicted changes in suitability following new or worsening pinyon-juniper invasion. Habitat restorations vary by population depending on the reference model. We only ran management action simulations when the reference model had covariates suitable for the simulation (for example, pinyon juniper removal was only run when pinyon juniper was a covariate; See Saher and others (2022) for model details). Raster file names are coded as follows: PMb = Pinon Mesa Breeding PMs = Pinon Mesa Summer combo = combined actions lit_incr = increase litter cover mes_impr = mesic improvements (increase in area) pj_inv = pinyon-juniper invasion (increase in area) pj_rm = pinyon-juniper removal (decrease in area) sgh_incr = increase sagebrush height shh_decr = decrease shrub height C = CATEGORIZED Maps V = UNCATEGORIZED Maps X = INVASION (categorized) Maps

About this dataset

Context

The dataset tabulates the Mesa 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 Mesa 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 Mesa was 385, a 0.26% decrease year-by-year from 2021. Previously, in 2021, Mesa population was 386, an increase of 0.26% compared to a population of 385 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Mesa decreased by 40. In this period, the peak population was 513 in the year 2018. 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 Mesa is shown in this column.
• Year on Year Change: This column displays the change in Mesa 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 Mesa Population by Year. You can refer the same here

Not many studies have documented climate and air quality changes of settlements at early stages of development. This is because high quality climate and air quality records are deficient for the periods of the early 18th century to mid 20th century when many U.S. cities were formed and grew. Dramatic landscape change induces substantial local climate change during the incipient stage of development. Rapid growth along the urban fringe in Phoenix, coupled with a fine-grained climate monitoring system, provide a unique opportunity to study the climate impacts of urban development as it unfolds. Generally, heat islands form, particularly at night, in proportion to city population size and morphological characteristics. Drier air is produced by replacement of the countryside's moist landscapes with dry, hot urbanized surfaces. Wind is increased due to turbulence induced by the built-up urban fabric and its morphology; although, depending on spatial densities of buildings on the land, wind may also decrease. Air quality conditions are worsened due to increased city emissions and surface disturbances. Depending on the diversity of microclimates in pre-existing rural landscapes and the land-use mosaic in cities, the introduction of settlements over time and space can increase or decrease the variety of microclimates within and near urban regions. These differences in microclimatic conditions can influence variations in health, ecological, architectural, economic, energy and water resources, and quality-of-life conditions in the city. Therefore, studying microclimatic conditions which change in the urban fringe over time and space is at the core of urban ecological goals as part of LTER aims. In analyzing Phoenix and Baltimore long-term rural/urban weather and climate stations, Brazel et al. (In progress) have discovered that long-term (i.e., 100 years) temperature changes do not correlate with populations changes in a linear manner, but rather in a third-order nonlinear response fashion. This nonlinear temporal change is consistent with the theories in boundary layer climatology that describe and explain the leading edge transition and energy balance theory. This pattern of urban vs. rural temperature response has been demonstrated in relation to spatial range of city sizes (using population data) for 305 rural vs. urban climate stations in the U.S. Our recent work on the two urban LTER sites has shown that a similar climate response pattern also occurs over time for climate stations that were initially located in rural locations have been overrun bu the urban fringe and subsequent urbanization (e.g., stations in Baltimore, Mesa, Phoenix, and Tempe). Lack of substantial numbers of weather and climate stations in cities has previously precluded small-scale analyses of geographic variations of urban climate, and the links to land-use change processes. With the advent of automated weather and climate station networks, remote-sensing technology, land-use history, and the focus on urban ecology, researchers can now analyze local climate responses as a function of the details of land-use change. Therefore, the basic research question of this study is: How does urban climate change over time and space at the place of maximum disturbance on the urban fringe? Hypotheses 1. Based on the leading edge theory of boundary layer climate change, largest changes should occur during the period of peak development of the land when land is being rapidly transformed from open desert and agriculture to residential, commercial, and industrial uses. 2. One would expect to observe, on average and on a temporal basis (several years), nonlinear temperature and humidity alterations across the station network at varying levels of urban development. 3. Based on past research on urban climate, one would expect to see in areas of the urban fringe, rapid changes in temperature (increases at night particularly), humidity (decreases in areas from agriculture to urban; increases from desert to urban), and wind speed (increases due to urban heating). 4. Changes of the surface climate on the urban fringe are expected to be altered as a function of various energy, moisture, and momentum control parameters, such as albedo, surface moisture, aerodynamic surface roughness, and thermal admittance. These parameters relate directly to population and land-use change (Lougeay et al. 1996).

About this dataset

Context

The dataset tabulates the Costa Mesa population by year. The dataset can be utilized to understand the population trend of Costa Mesa.

Content

The dataset constitues the following datasets

• Costa Mesa, CA Population Dataset: Yearly Figures, Population Change, and Percent Change Analysis

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/.

About this dataset

Context

The dataset tabulates the data for the Costa Mesa, CA population pyramid, which represents the Costa Mesa 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 Costa Mesa, CA, is 21.1.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Costa Mesa, CA, is 18.0.
• Total dependency ratio for Costa Mesa, CA is 39.1.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Costa Mesa, CA is 5.5.

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 Costa Mesa population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Costa Mesa for the selected age group is shown in the following column.
• Population (Female): The female population in the Costa Mesa for the selected age group is shown in the following column.
• Total Population: The total population of the Costa Mesa 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 Costa Mesa Population by Age. You can refer the same here