In 2023, the resident population of California was ***** million. This is a slight decrease from the previous year, with ***** million people in 2022. This makes it the most populous state in the U.S. Californian demographics Along with an increase in population, California’s gross domestic product (GDP) has also been increasing, from *** trillion U.S. dollars in 2000 to **** trillion U.S. dollars in 2023. In the same time period, the per-capita personal income has almost doubled, from ****** U.S. dollars in 2000 to ****** U.S. dollars in 2022. In 2023, the majority of California’s resident population was Hispanic or Latino, although the number of white residents followed as a close second, with Asian residents making up the third-largest demographic in the state. The dark side of the Golden State While California is one of the most well-known states in the U.S., is home to Silicon Valley, and one of the states where personal income has been increasing over the past 20 years, not everyone in California is so lucky: In 2023, the poverty rate in California was about ** percent, and the state had the fifth-highest rate of homelessness in the country during that same year, with an estimated ** homeless people per 10,000 of the population.

About this dataset

Context

The dataset tabulates the California 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 California 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 2024, the population of California was 39.43 million, a 0.59% increase year-by-year from 2023. Previously, in 2023, California population was 39.2 million, an increase of 0.14% compared to a population of 39.14 million in 2022. Over the last 20 plus years, between 2000 and 2024, population of California increased by 5.44 million. In this period, the peak population was 39.52 million 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 2024

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2024)
• Population: The population for the specific year for the California is shown in this column.
• Year on Year Change: This column displays the change in California 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 California Population by Year. You can refer the same here

Chart and table of population level and growth rate for the state of California from 1900 to 2024.

About this dataset

Context

The dataset tabulates the California City 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 California City 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 California City was 15,127, a 0.65% increase year-by-year from 2021. Previously, in 2021, California City population was 15,029, a decline of 0.15% compared to a population of 15,051 in 2020. Over the last 20 plus years, between 2000 and 2022, population of California City increased by 6,717. In this period, the peak population was 15,127 in the year 2022. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

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

Data Coverage:

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

20 year Projected Urban Growth scenarios. Base year is 2000. Projected year in this dataset is 2020.

By 2020, most forecasters agree, California will be home to between 43 and 46 million residents-up from 35 million today. Beyond 2020 the size of California's population is less certain. Depending on the composition of the population, and future fertility and migration rates, California's 2050 population could be as little as 50 million or as much as 70 million. One hundred years from now, if present trends continue, California could conceivably have as many as 90 million residents.

Where these future residents will live and work is unclear. For most of the 20th Century, two-thirds of Californians have lived south of the Tehachapi Mountains and west of the San Jacinto Mountains-in that part of the state commonly referred to as Southern California. Yet most of coastal Southern California is already highly urbanized, and there is relatively little vacant land available for new development. More recently, slow-growth policies in Northern California and declining developable land supplies in Southern California are squeezing ever more of the state's population growth into the San Joaquin Valley.

How future Californians will occupy the landscape is also unclear. Over the last fifty years, the state's population has grown increasingly urban. Today, nearly 95 percent of Californians live in metropolitan areas, mostly at densities less than ten persons per acre. Recent growth patterns have strongly favored locations near freeways, most of which where built in the 1950s and 1960s. With few new freeways on the planning horizon, how will California's future growth organize itself in space? By national standards, California's large urban areas are already reasonably dense, and economic theory suggests that densities should increase further as California's urban regions continue to grow. In practice, densities have been rising in some urban counties, but falling in others.

These are important issues as California plans its long-term future. Will California have enough land of the appropriate types and in the right locations to accommodate its projected population growth? Will future population growth consume ever-greater amounts of irreplaceable resource lands and habitat? Will jobs continue decentralizing, pushing out the boundaries of metropolitan areas? Will development densities be sufficient to support mass transit, or will future Californians be stuck in perpetual gridlock? Will urban and resort and recreational growth in the Sierra Nevada and Trinity Mountain regions lead to the over-fragmentation of precious natural habitat? How much water will be needed by California's future industries, farms, and residents, and where will that water be stored? Where should future highway, transit, and high-speed rail facilities and rights-of-way be located? Most of all, how much will all this growth cost, both economically, and in terms of changes in California's quality of life?

Clearly, the more precise our current understanding of how and where California is likely to grow, the sooner and more inexpensively appropriate lands can be acquired for purposes of conservation, recreation, and future facility siting. Similarly, the more clearly future urbanization patterns can be anticipated, the greater our collective ability to undertake sound city, metropolitan, rural, and bioregional planning.

Consider two scenarios for the year 2100. In the first, California's population would grow to 80 million persons and would occupy the landscape at an average density of eight persons per acre, the current statewide urban average. Under this scenario, and assuming that 10% percent of California's future population growth would occur through infill-that is, on existing urban land-California's expanding urban population would consume an additional 5.06 million acres of currently undeveloped land. As an alternative, assume the share of infill development were increased to 30%, and that new population were accommodated at a density of about 12 persons per acre-which is the current average density of the City of Los Angeles. Under this second scenario, California's urban population would consume an additional 2.6 million acres of currently undeveloped land. While both scenarios accommodate the same amount of population growth and generate large increments of additional urban development-indeed, some might say even the second scenario allows far too much growth and development-the second scenario is far kinder to California's unique natural landscape.

This report presents the results of a series of baseline population and urban growth projections for California's 38 urban counties through the year 2100. Presented in map and table form, these projections are based on extrapolations of current population trends and recent urban development trends. The next section, titled Approach, outlines the methodology and data used to develop the various projections. The following section, Baseline Scenario, reviews the projections themselves. A final section, entitled Baseline Impacts, quantitatively assesses the impacts of the baseline projections on wetland, hillside, farmland and habitat loss.

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) System (MTS). The MTS represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined because of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division or incorporated place boundaries in some states and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard Census Bureau geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous.

Graph and download economic data for Resident Population in California (CAPOP) from 1900 to 2024 about residents, CA, population, and USA.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

Study: Population decline for plants in the California Floristic Province: Does demography or geography determine climate change vulnerability?Included in this figshare are all of the results, files, and code to generate the results and figures in the study. We generated the population model results from the proprietary software RAMAS GIS 6 (Akçakaya and Root 2005), so we cannot provide those models. If you would like access the files to run in RAMAS GIS, please contact me.To generate the results and figures from the study:Download each folder and file from figshareMake sure all folders and files are in the same folderRun the code in R (highly recommend RStudio)Make sure you have all of the packages downloadedFigures saved in "figures" folderTables printed in R console

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

The Earth′s climate is warming, especially in the mid- and high latitudes of the Northern Hemisphere. The northern elephant seal (Mirounga angustirostris) breeds and haul-outs on islands and the mainland of Baja California, Mexico, and California, U.S.A. At the beginning of the 21st century, numbers of elephant seals in California are increasing, but the status of Baja California populations is unknown, and some data suggest they may be decreasing. We hypothesize that the elephant seal population of Baja California is experiencing a decline because the animals are not migrating as far south due to warming sea and air temperatures. Here we assessed population trends of the Baja California population, and climate change in the region. The numbers of northern elephant seals in Baja California colonies have been decreasing since the 1990s, and both the surface waters off Baja California and the local air temperatures have warmed during the last three decades. We propose that declining popul...

A. SUMMARY This dataset shows San Francisco COVID-19 deaths by population characteristics. This data may not be immediately available for recently reported deaths. Data updates as more information becomes available. Because of this, death totals may increase or decrease.

Population characteristics are subgroups, or demographic cross-sections, like age, race, or gender. The City tracks how deaths have been distributed among different subgroups. This information can reveal trends and disparities among groups.

B. HOW THE DATASET IS CREATED As of January 1, 2023, COVID-19 deaths are defined as persons who had COVID-19 listed as a cause of death or a significant condition contributing to their death on their death certificate. This definition is in alignment with the California Department of Public Health and the national https://preparedness.cste.org/wp-content/uploads/2022/12/CSTE-Revised-Classification-of-COVID-19-associated-Deaths.Final_.11.22.22.pdf">Council of State and Territorial Epidemiologists. Death certificates are maintained by the California Department of Public Health.

Data on the population characteristics of COVID-19 deaths are from: *Case reports *Medical records *Electronic lab reports *Death certificates

Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths.

To protect resident privacy, we summarize COVID-19 data by only one population characteristic at a time. Data are not shown until cumulative citywide deaths reach five or more.

Data notes on select population characteristic types are listed below.

Race/ethnicity * We include all race/ethnicity categories that are collected for COVID-19 cases.

Gender * The City collects information on gender identity using these guidelines.

C. UPDATE PROCESS Updates automatically at 06:30 and 07:30 AM Pacific Time on Wednesday each week.

Dataset will not update on the business day following any federal holiday.

D. HOW TO USE THIS DATASET Population estimates are only available for age groups and race/ethnicity categories. San Francisco population estimates for race/ethnicity and age groups can be found in a dataset based on the San Francisco Population and Demographic Census dataset.These population estimates are from the 2018-2022 5-year American Community Survey (ACS).

This dataset includes several characteristic types. Filter the “Characteristic Type” column to explore a topic area. Then, the “Characteristic Group” column shows each group or category within that topic area and the number of cumulative deaths.

Cumulative deaths are the running total of all San Francisco COVID-19 deaths in that characteristic group up to the date listed.

To explore data on the total number of deaths, use the COVID-19 Deaths Over Time dataset.

E. CHANGE LOG

The 2023 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some states and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census and beyond, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

Includes data used for analyses reported in this manuscript

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

The occurrence data is stored in the occurrence.txt file. The metadata that describes the columns of this document is called meta.xml. This document is also the data dictionary for this dataset. The metadata that describes the dataset, including author and contact information for this dataset is called eml.xml.

Find the data files at https://bison.usgs.gov/ipt/resource?r=usda-ars-patternsofwidespreaddecline-bumblebees

How climate change influences the dynamics of plant populations is not well understood, as few plant studies have measured responses of vital rates to climatic variables and modeled the impact on population growth. I used 25 years of demographic data to analyze how survival, growth, and fecundity respond to date of spring snow melt for a subalpine plant. Fecundity was estimated by seed production (over 15 years) and also divided into flower number, fruit set, seeds per fruit, and escape from seed predation. Despite no apparent effects on flower number, plants produced more seeds in years with later snowmelt. Survival and probability of flowering were reduced by early snow melt in the previous year. Based on demographic models, earlier snowmelt with warming is expected to lead to negative population growth, driven especially by changes in seedling establishment and seed production. These results provide a rare example of how climate change is expected to influence the dynamics of a plant population. They furthermore illustrate the potential for strong population impacts even in the absence of more commonly reported visual signs, such as earlier blooming or reduced floral display in early melting years.

Protected areas are one of the most widespread and accepted conservation interventions, yet their population trends are rarely compared to regional trends to gain insight into their effectiveness. Here, we leverage two long-term community science datasets to demonstrate mixed effects of protected areas on long-term bird population trends. We analyzed 31 years of bird transect data recorded by community volunteers across all major habitats of Stanford University’s Jasper Ridge Biological Preserve to determine the population trends for a sample of 66 species. We found that nearly a third of species experienced long-term declines, and on average, all species declined by 12%. Further, we averaged species trends by conservation status and key life history attributes to identify correlates and possible drivers of these trends. Observed increases in some cavity-nesters and declines of scrub-associated species suggest that long-term fire suppression may be a key driver, reshaping bird communities through changes in forest and chaparral structure and composition. Additionally, we compared our results to those of the North American Breeding Bird Survey’s Central California Coast region (n = 55 species) to place Jasper Ridge in a broader context. Most species experienced similar directional population trends inside vs. outside of the preserve, and only eight species (14.5%) did better inside this small, protected area. Therefore, we must identify relevant management strategies for declining populations and explicitly consider how existing protected areas target and manage each species. Further, this analysis underscores the importance of local and national community science for revealing nuanced long-term bird population trends. Methods

From 1989 to 2020, volunteer observers conducted monthly surveys of six sectors within Stanford University's Jasper Ridge Biological Preserve (JRBP). Each survey consisted of a trail-based transect in which a group of observers walked the trail in the morning and counted all birds detected over roughly 3 hours. Observers recorded the number of each species seen or heard along the route, regardless of the distance to the bird. Over 31 years of surveys, 192 observers conducted 2,055 transects and recorded a total of 473,401 observations of 184 species (91% of JRBP’s documented avian richness). We used these data to estimate long-term avian population trends at JRBP. Prior to analy- sis, we performed extensive data cleaning, including the standardization of species names and observer identity. Unlikely species without notes or supporting information were removed from the analysis. All transects with fewer than seven species (n = 30) were considered incidental and removed. These transects were often performed during suboptimal conditions (e.g. wind or rain) and/or were of abnormally short duration. Finally, we limited our analysis to the 100 most consistently detected species (those detected in the greatest number of transects).

The 2022 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some states and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census and beyond, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

The federal and state endangered California clapper rail, Rallus longirostris obsoletus. is a species that, until very recently, was on the verge of extinction. This secretive marsh bird's decline began over 100 years ago in the pristine marshes of San Francisco Bay (Bay) and the California coast (Fig. 1). In the earlier part of this century, the rail was found as far north as Humboldt Bay pd as far south as Morro Bay (Gill 1979) (Fig. 2). In the early 80s, the last known pair of rails outside of the Bay was seen at Elkhorn Slough in Monterey County. During the first half of this century, exploitation of the Bay's natural resources, including unrestricted filling and diking of the tidal marshes, began shrinking the rail's habitat in San Pablo Bay, Central and South San Francisco Bay from over 51,000 hectares to less than 9,000 hectares that now remain today (Dedrick 1993). The cumulative effects from this continued loss of critical habitat, combined with recent threats from increased predation, probable contamination, and other stresses associated with expanding urban growth, has created a crisis for our bay's indigenous rail. After the rail was listed as Endangered under the authority of the Endangered Species Act by the U.S. Fish and Wildlife Service (Service) in 1970, censuses of the population in the Bay were initiated. In the early 1970s, Gill estimated the total California clapper rail population at 4200 to 6000 individuals (1979). Surveys for the rail continued into the 80s (Moss 1980), with Harvey providing an estimate of 1200-1500 rails in 1981. The survey by Harvey was more accurate than the Gill estimate because an actual count was made, as compared to an average density which Gill applied to all suitable habitat. Subsequent censuses were sporadic and incomplete (Harvey 1987) until the Service, led by the San Francisco Bay National Wildlife Refuge (Refuge) began winter high tide surveys of South San Francisco Bay (South Bay) in 1988 (Foerster 1989). The Service began to suspect that the rail was in serious decline after the Refuge conducted a thorough survey of major South Bay marshes in the winter of 1988-89 and estimated a total population of only 700 rails. It was discovered that populations of rails in marshes on the east side of the bay were suffering the greatest declines and that predation by non-native predators was implicated as a primary factor (Foerster 1989). This hypothesis was confirmed by data collected by the Refuge and subsequently an Environmental Assessment and Predator Management Plan was implemented in March 1991 (Foerster and Takekawa 1991). Since 1988, the Refuge has continued to conduct annual winter high tide surveys of South Bay rail populations and some San Pablo Bay (North Bay) subpopulations (Figs. 2 and 3), with the assistance of the California Department of Fish and Game (CDFG) and other local organizations such as the San Francisco Bay Bird Observatory. This report summarizes data collected between November 1989 and January 1993, encompassing four annual winter surveys. During the last two years, the Refuge also initiated research into several factors which were implicated in rail population decline. The factors which were identified as significantly affecting rail survival included predation by non-native predators (Foerster and Takekawa 1991), and high levels of heavy metals in prey species (Lonzarich, et al. 1992). Continued analysis of these factors by the Service will culminate in a several reports to be released in late 1994.

Understanding the spatial structure of a population is critical for effective assessment and management. However, direct observation of spatial dynamics is generally difficult, particularly for marine mammals. California sea lions (Zalophus californianus) are polygynous pinnipeds distributed along the Pacific coast of North America. The species' range has been subdivided into 3 management stocks based on differences in mitochondrial DNA, but to date no studies have considered nuclear genetic variation, and thus we lack a comprehensive understanding of gene flow patterns among sea lion colonies. In light of recent population declines in the Gulf of California, Mexico, it is important to understand spatial structure to determine if declining sea lion colonies are genetically isolated from others. To define population subdivision and identify sex biases in gene flow we analyzed a 355bp sequence of the mitochondrial DNA control region and 10 polymorphic microsatellite loci from 355 tissue samples collected from 6 colonies distributed along Mexican waters. Using a novel approach to estimate sex biases in gene flow we found that male sea lions disperse on average 6.75 times more frequently than females. Analyses of population subdivision strongly suggest a pattern of isolation by distance among colonies and challenge current stock definitions. Based on these results, we propose an alternative classification that identifies 3 Mexican management units: Upper Gulf of California, Southern Baja Peninsula, and Upper Pacific Coast of Baja. This revised classification should be considered in future assessment and management of California sea lion populations in Mexican waters.