Graph and download economic data for Net County-to-County Migration Flow (5-year estimate) for Los Angeles County, CA (DISCONTINUED) (NETMIGNACS006037) from 2009 to 2020 about migration; Los Angeles County, CA; flow; Los Angeles; Net; 5-year; CA; and population.

Graph and download economic data for Net County-to-County Migration Flow (5-year estimate) for San Diego County, CA (DISCONTINUED) (NETMIGNACS006073) from 2009 to 2020 about San Diego County, CA; migration; San Diego; flow; Net; CA; 5-year; and population.

Graph and download economic data for Net County-to-County Migration Flow (5-year estimate) for Orange County, CA (DISCONTINUED) (NETMIGNACS006059) from 2009 to 2020 about Orange County, CA; migration; flow; Los Angeles; Net; 5-year; CA; and population.

The project leads for the collection of this data were Julie Garcia and Richard Shinn. Female mule deer were captured in February 2017 and equipped with satellite collars manufactured by Lotek, which collected GPS data to June 2020. Additional GPS data was collected from deer in 1999-2001 and included in the analysis to supplement the small sample size of the 2017-2020 dataset. The data was collected from deer throughout Modoc County with a priority to ascertain general distributions, survival, and home range and not to model migration routes, hence the low sample sizes in specific winter ranges. The Modoc Interstate deer herd migrates from a winter range near Clear Lake Reservoir in Modoc County, California north into Oregon in Klamath and Lake counties for the summer. GPS locations were fixed at 12-hour intervals in the 2017-2020 dataset and 8-hour intervals in the 1999-2001 dataset. Migration lines as symbolized connect GPS data points per deer per seasonal migration. GPS points were extracted only during migrations using net-squared displacement graphs. Sixteen migration sequences from 12 deer, with an average migration time of 23.89 days and an average migration distance of 69.71 km, were obtained from the 1999-2001 dataset. Thirty-six migration sequences from 9 deer, with an average migration time of 19.53 days and an average migration distance of 87.57 km, were obtained from the 2017-2020 dataset.

Graph and download economic data for Net County-to-County Migration Flow (5-year estimate) for Shasta County, CA (DISCONTINUED) (NETMIGNACS006089) from 2009 to 2020 about Shasta County, CA; Redding; migration; flow; Net; 5-year; CA; and population.

Over ****** persons were returned to the three countries that make up the Northern Triangle of Central America (Guatemala, El Salvador, and Honduras) in 2020. During that year, nearly ** percent of migrants were repatriated from Mexico. The vast majority of migrants were deported by either Mexico or the U.S.

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.

The project leads for the collection of this data were Erin Zulliger and Richard Shinn. Elk (6 adult females, 3 juvenile males, and 2 juvenile females) were captured in 2017 and equipped with Lotek satellite GPS collars or VHF tags, transmitting data from 2017-2020. Additional GPS data was collected from elk (6 females) in 2001-2002 and included in the analysis to supplement the small sample size of the 2017-2020 dataset. The Egg Lake elk herd migrates from a winter range surrounding Egg Lake in Modoc County, California eastward into Siskiyou County for the summer. GPS locations were fixed at 4-hour intervals in the 2017-2020 dataset and 3 to 8-hour intervals in the 2001-2002 dataset. Migration lines as symbolized connect GPS data points per elk per seasonal migration. GPS points were extracted only during migrations using net-squared displacement graphs. Nine migration sequences from 5 elk, with an average migration time of 6.78 days and an average migration distance of 26.83 km, were used from the 2000-2001 dataset. Fourteen migration sequences from 6 elk, with an average migration time of 7.79 days and an average migration distance of 42.40 km, were used from the 2017-2020 dataset.

The project leads for the collection of this data were Julie Garcia and Evan King. Mule deer (32 adult females) from the Kern River herd were captured and equipped with Lotek LiteTrack Iridium collars, transmitting data from 2020-2022. GPS fixes were set for 2-hour intervals. The Kern River herd migrates from winter ranges in Sequoia National Forest north of Johnsondale and east of Slate Mountain northward to the area around Redrocks Meadows and along the Kern Canyon ridgeline to Sequoia National Park. Due to a high percentage of poor fixes, likely due to highly variable topographic terrain, between 2-18% of GPS locations per deer, or 5.78% of the entire dataset, were fixed in 2-dimensional space and removed to ensure locational accuracy. The methodology used for this migration analysis allowed for the mapping of winter ranges and the identification of migration corridors and stopovers. Brownian Bridge Movement Models (BBMMs; Sawyer et al. 2009) were constructed with GPS collar data from 27 migrating deer, including 75 migration sequences, location, date, time, and average location error as inputs in Migration Mapper. The average migration time and average migration distance for deer was 15.76 days and 31.51 km, respectively. Corridors and stopovers were prioritized based on the number of animals moving through a particular area. Separate models using Brownian bridge movement models (BMMM) and fixed motion variances (FMV) of 1000 were produced per migration sequence. Due to high variances, Only FMV models were retained. Corridors were produced at a spatial resolution of 50 m using a sequential fix interval of less than 27 hours. Winter range analyses were based on data from 28 individual deer and 59 wintering sequences using a fixed motion variance of 1000. Winter range designations for this herd may expand with a larger sample, filling in some of the gaps between winter range polygons in the map. Additional migration routes and winter range areas likely exist beyond what was modeled in our output.Corridors are visualized based on deer use per cell in the BBMMs, with greater than or equal to 1 deer, greater than or equal to3 deer (10% of the sample), and greater than or equal to 6 deer (20% of the sample) representing migration corridors, moderate use, and high use corridors, respectively. Stopovers were calculated as the top 10 percent of the population level utilization distribution during migrations and can be interpreted as high use areas. Stopover polygon areas less than 20,000 m2 were removed, but remaining small stopovers may be interpreted as short-term resting sites, likely based on a small concentration of points from an individual animal. Winter range is visualized as the 50th percentile contour of the winter range utilization distribution.

The Modoc Interstate mule deer (Odocoileus hemionus) herd migrates from a winter range near Clear Lake Reservoir in Modoc County, California north into Oregon in Klamath and Lake counties for the summer. Much of this herd likely resides in Oregon year-round as California population estimates (2000-3000) are lower than Oregon estimates (~15,000). Female mule deer were captured in Modoc in February 2017 and equipped with satellite collars manufactured by Lotek. Additional GPS data was collected between 1999-2001 from deer captured in 1999, and was included to supplement the small sample size of the 2017-2020 dataset. The data was collected with a priority to ascertain general distributions, survival, and home range, and not to model migration routes, hence the low sample sizes. Threats to this herd include increased fire frequency and conversion to non-native annual grass. Moreover, increased juniper woodlands has resulted in a loss of forbs, grass, and shrubs. These data provide the location of migration routes for mule deer in the Modoc Interstate population in California and Oregon. They were developed from 52 migration sequences collected from a sample size of 21 animals comprising GPS locations collected every 8-12 hours.

Net County-to-County Migration Flow (5-year estimate) for Stanislaus County, CA was -2368.00000 Persons in January of 2020, according to the United States Federal Reserve. Historically, Net County-to-County Migration Flow (5-year estimate) for Stanislaus County, CA reached a record high of 1925.00000 in January of 2014 and a record low of -2368.00000 in January of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for Net County-to-County Migration Flow (5-year estimate) for Stanislaus County, CA - last updated from the United States Federal Reserve on September of 2025.

The Likely Tables herd contains migrants, but this herd does not migrate between traditional summer and winter seasonal ranges. Instead, much of the herd displays a nomadic tendency, slowly migrating north for the summer using various high use areas as they move. Therefore, annual ranges were modeled using year-round data to demarcate high use areas in lieu modeling specific winter ranges. A high use area being used during winter by many of the collared animals is west of the Warner Mountains, east of U.S. Highway 395, and north of Moon Lake. Some animals live in the agricultural fields west of U.S. Highway 395. There appears to be little if any movement across the highway, which is fenced on both sides in this area. Summer ranges are spread out, with some individuals moving as far north as Goose Lake. A few outliers in the herd moved long distances south toward the Lassen herd or east to Nevada. Drought, increasing fire frequency, invasive annual grasses, and juniper encroachment negatively affect pronghorn habitat. Recent population surveys indicate a declining population (Trausch and others, 2020). Juniper removal on public and private lands have potential to improve habitat quality and potentially reduce predation (Ewanyk, 2020). Fences on public and private lands affect movement corridors and increase crossing and/or migration times. Recent fence modifications on BLM lands have shown potential to ease pronghorn movements (Hudgens, 2022). These mapping layers show the location of the migration corridors for pronghorn (Antilocapra americana) in the Likely Tables population in California. They were developed from 29 migration sequences collected from a sample size of 17 animals comprising GPS locations collected every 1-4 hours.

All of the inhabitants in the Holy See, the home of the leader of the Roman Catholic Church, were immigrants in 2020, meaning that they were born outside of the country. Perhaps more interesting are the Gulf States the United Arab Emirates, Qatar, and Kuwait, all with an immigrant population of over ** percent of their total populations, underlining the high importance of migrant workers to these countries' economies. In terms of numbers, the United States had the highest number of immigrants in 2020. Migration to Gulf Cooperation Council states The United Arab Emirates, Qatar, and Kuwait, all members of the Gulf Cooperation Council (GCC), have a significant amount of migrant labor. The United Arab Emirates and Qatar both rank high in quality-of-life rankings for immigrants. A significant number of migrant workers in the GCC originate from Asia, with the most originating from Bangladesh. As of 2022, nearly ***** thousand Bangladeshi citizens expatriated to work in GCC nations. The American melting pot The United States is known for having high levels of diversity and migration. Migration to the United States experienced peaks from the periods of 1990-1999 as well as 1900-1909. Currently, Latin Americans are the largest migrant group in the United States, followed by migrants from Asia. Out of each state, California has some of the highest naturalization rates. In 2021, ******* people in California naturalized as U.S. citizens, followed by Florida, New York, Texas, and New Jersey.

Graph and download economic data for Net County-to-County Migration Flow (5-year estimate) for Riverside County, CA (DISCONTINUED) (NETMIGNACS006065) from 2009 to 2020 about Riverside County, CA; Riverside; migration; flow; Net; 5-year; CA; and population.

The Clear Lake herd contains migrants, but this herd does not migrate between traditional summer and winter seasonal ranges. Instead, much of the herd displays a nomadic tendency, slowly migrating north, east, or south for the summer using various high use areas as they move. Therefore, annual ranges were modeled using year-round data to demarcate high use areas in lieu of modeling specific winter ranges. The areas adjacent to Clear Lake Reservoir were heavily used during winter by many of the collared animals. A few collared individuals persisted west of State Route 139 year-round, seemingly separated from the rest of the herd due to this highway barrier. However, some pronghorn cross this road near Cornell and join this subgroup. Summer ranges are spread out, with many individuals moving southeast through protected forests or over the state border into Oregon. A few outliers in the herd moved long distances south, crossing State Route 139 to Oak Ridge, or east into Likely Tables pronghorn herd areas. Drought, increasing fire frequency, invasive annual grasses, and juniper encroachment negatively affect pronghorn habitat. Recent population surveys indicate a declining population (Trausch and others, 2020). Juniper removal on public and private lands has potential to improve habitat quality and potentially reduce predation (Ewanyk, 2020). These mapping layers show the location of the migration corridors for pronghorn (Antilocapra americana) in the Clear Lake population in California. They were developed from 72 migration sequences collected from a sample size of 23 animals comprising GPS locations collected every 1-6 hours.

Annual number of interprovincial migrants by province of origin and destination, Canada, provinces and territories.

Net County-to-County Migration Flow (5-year estimate) for San Francisco County/city, CA was -21393.00000 Persons in January of 2020, according to the United States Federal Reserve. Historically, Net County-to-County Migration Flow (5-year estimate) for San Francisco County/city, CA reached a record high of -3435.00000 in January of 2010 and a record low of -21393.00000 in January of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for Net County-to-County Migration Flow (5-year estimate) for San Francisco County/city, CA - last updated from the United States Federal Reserve on September of 2025.

Migratory mule deer (Odocoileus hemionus) within the San Joaquin Watershed occupy most of the watershed above Kerckhoff Reservoir, Fresno and Madera Counties, California. Human infrastructure in the watershed is widespread and includes residential, water control, hydroelectric power, and recreational use developments. Steep topography between winter and summer range limit crossing points along the San Joaquin River. Habitat conditions favoring deer declined from a peak around 1950, resulting in a reduction in the deer population. The current deer population is believed to be about 4,000. A massive wildfire burned through most of the watershed in 2020, dramatically changing habitat conditions in some areas. These data provide the location of migration routes for mule deer in the Upper San Joaquin Watershed population in California. They were developed from 55 migration sequences collected from a sample size of 30 animals comprising GPS locations collected every 2-12 hours.