Chart and table of population level and growth rate for the state of Hawaii from 1950 to 2024.

[Metadata] 2020 Census Tract Boundaries, with population, for the State of Hawaii, excluding northwest Hawaiian Islands and clipped to the coastline. Source: US Census Bureau, September 2021. Added tract name, county and island fields, April 2022. Note: The Hawaii Statewide GIS Program was notified in Feb 2023 that the tract names for the Kalawao and Sprecklesville census tracts were reversed (both tracts have census tract number 319). The GIS staff corrected the error and re-published the layer, March 2, 2023. For additional information about this layer, please refer to metadata at https://files.hawaii.gov/dbedt/op/gis/data/tracts20.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

[Metadata] 2020 Census Designated Places (CDP), with population, for the State of Hawaii, excluding northwest Hawaiian Islands and clipped to the coastline. Source: US Census Bureau, September 2021. For additional information about this layer, please refer to metadata at https://files.hawaii.gov/dbedt/op/gis/data/cdplc20.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

[Metadata] 2020 Census Hawaiian Homeland Boundaries, with population, for the State of Hawaii, excluding northwest Hawaiian Islands and clipped to the coastline. Source: US Census Bureau, September 2021. NOTE: The 2020 Census Hawaiian Homelands layer erroneously depicts lands in Makaha as Hawaiian Home Lands. DHHL does not own property in Makaha. For additional information about this layer, please refer to metadata at https://files.hawaii.gov/dbedt/op/gis/data/hhl20.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

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 blocks are statistical areas bounded on all sides by visible features, such as streets, roads, streams, and railroad tracks, and/or by nonvisible boundaries such as city, town, township, and county limits, and short line-of-sight extensions of streets and roads. Census blocks are relatively small in area; for example, a block in a city bounded by streets. However, census blocks in remote areas are often large and irregular and may even be many square miles in area. A common misunderstanding is that census blocks are used geographically to build all other census geographic areas, rather all other census geographic areas are updated and then used as the primary constraints, along with roads and water features, to delineate the tabulation blocks. As a result, all 2020 Census blocks nest within every other 2020 Census geographic area, so that Census Bureau statistical data can be tabulated at the block level and aggregated up to the appropriate geographic areas. Census blocks cover all territory in the United States, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands). Blocks are the smallest geographic areas for which the Census Bureau publishes data from the decennial census. A block may consist of one or more faces.

[Metadata] 2020 Census County Division Boundaries (aka Districts), with population, for the State of Hawaii, excluding northwest Hawaiian Islands and clipped to the coastline. Source: US Census Bureau, September 2021. For additional information about this layer, please refer to metadata at https://files.hawaii.gov/dbedt/op/gis/data/ccd20.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

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. Public Use Microdata Areas (PUMAs) are decennial census areas that permit the tabulation and dissemination of Public Use Microdata Sample (PUMS) data, American Community Survey (ACS) data, and data from other census and surveys. For the 2020 Census, the State Data Centers (SDCs) in each state, the District of Columbia, and the Commonwealth of Puerto Rico had the opportunity to delineate PUMAS within their state or statistically equivalent entity. All PUMAs must nest within states and have a minimum population threshold of 100,000 persons. 2020 PUMAs consist of census tracts and cover the entirety of the United States, Puerto Rico and Guam. American Samoa, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands do not contain any 2020 PUMAs because the population is less than the minimum population requirement. Each PUMA is identified by a 5-character numeric census code that may contain leading zeros and a descriptive name. The 2020 PUMAs will appear in the 2022 TIGER/Line Shapefiles.

The 2020 cartographic boundary KMLs 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. Public Use Microdata Areas (PUMAs) are decennial census areas that permit the tabulation and dissemination of Public Use Microdata Sample (PUMS) data, American Community Survey (ACS) data, and data from other census and surveys. For the 2020 Census, the State Data Centers (SDCs) in each state, the District of Columbia, and the Commonwealth of Puerto Rico had the opportunity to delineate PUMAS within their state or statistically equivalent entity. All PUMAs must nest within states and have a minimum population threshold of 100,000 persons. 2020 PUMAs consist of census tracts and cover the entirety of the United States, Puerto Rico and Guam. American Samoa, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands do not contain any 2020 PUMAs because the population is less than the minimum population requirement. Each PUMA is identified by a 5-character numeric census code that may contain leading zeros and a descriptive name.

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) 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. Public Use Microdata Areas (PUMAs) are decennial census areas that permit the tabulation and dissemination of Public Use Microdata Sample (PUMS) data, American Community Survey (ACS) data, and data from other census and surveys. For the 2020 Census, the State Data Centers (SDCs) in each state, the District of Columbia, and the Commonwealth of Puerto Rico had the opportunity to delineate PUMAS within their state or statistically equivalent entity. All PUMAs must nest within states and have a minimum population threshold of 100,000 persons. 2020 PUMAs consist of census tracts and cover the entirety of the United States, Puerto Rico and Guam. American Samoa, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands do not contain any 2020 PUMAs because the population is less than the minimum population requirement. Each PUMA is identified by a 5-character numeric census code that may contain leading zeros and a descriptive name.

Use this application to view the pattern of concentrations of people by race and Hispanic or Latino ethnicity. Data are provided at the U.S. Census block group level, one of the smallest Census geographies, to provide a detailed picture of these patterns. The data is sourced from the U.S Census Bureau, 2020 Census Redistricting Data (Public Law 94-171) Summary File. Definitions: Definitions of the Census Bureau’s categories are provided below. This interactive map shows patterns for all categories except American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander. The total population countywide for these two categories is small (1,582 and 263 respectively). The Census Bureau uses the following race categories:Population by RaceWhite – A person having origins in any of the original peoples of Europe, the Middle East, or North Africa.Black or African American – A person having origins in any of the Black racial groups of Africa.American Indian or Alaska Native – A person having origins in any of the original peoples of North and South America (including Central America) and who maintains tribal affiliation or community attachment.Asian – A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam.Native Hawaiian or Other Pacific Islander – A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands.Some Other Race - this category is chosen by people who do not identify with any of the categories listed above. People can identify with more than one race. These people are included in the Two or More Races Hispanic or Latino PopulationThe Hispanic/Latino population is an ethnic group. Hispanic/Latino people may be of any race.Other layers provided in this tool included the Loudoun County Census block groups, towns and Dulles airport, and the Loudoun County 2021 aerial imagery.

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. Public Use Microdata Areas (PUMAs) are decennial census areas that permit the tabulation and dissemination of Public Use Microdata Sample (PUMS) data, American Community Survey (ACS) data, and data from other census and surveys. For the 2020 Census, the State Data Centers (SDCs) in each state, the District of Columbia, and the Commonwealth of Puerto Rico had the opportunity to delineate PUMAS within their state or statistically equivalent entity. All PUMAs must nest within states and have a minimum population threshold of 100,000 persons. 2020 PUMAs consist of census tracts and cover the entirety of the United States, Puerto Rico and Guam. American Samoa, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands do not contain any 2020 PUMAs because the population is less than the minimum population requirement. Each PUMA is identified by a 5-character numeric census code that may contain leading zeros and a descriptive name. The 2020 PUMAs will appear in the 2022 TIGER/Line Shapefiles.

Where stable source populations of at-risk species exist, translocation may be a reasonable strategy for re-establishing extirpated populations. However, the success rates of such efforts are mixed, necessitating thorough preliminary investigation. Stochastic population modeling can be a useful method of assessing the potential success of translocations. Here, we report on the results of modeling translocation success for the Hawaiian Common Gallinule (‘alae ‘ula; Gallinula galeata sandvicensis), an endangered waterbird endemic to the Hawaiian Islands. Using updated vital rates, we constructed a model simulating three existing extant (wild) source populations and a hypothetical recipient site on another island. We then projected the effects of six different translocation scenarios and sensitivity of the results to variation of three important demographic parameters on the probability of extinction (PE) of the reintroduced and donor populations. Larger translocations, of at least 30 birds, had low probability of extinction in the reintroduced population, but raised extinction risk of the smallest source population. Spacing out translocations in time (e.g., 10 birds translocated in total in three installments over nine years), led to lower PE than translocating all individuals at once (i.e., bulk translocations) for both the source and reintroduced populations. Brood size and hatch-year juvenile survival had a disproportionate impact on reintroduced population viability. Importantly, the reported juvenile survival rate is very near the threshold for population failure. This suggests that post-introduction and subsequent management of wetlands, particularly predator control, could be critical to reintroduction success. We recommend that individuals should be translocated from multiple, genetically distinct subpopulations to reduce the possibility of inbreeding depression. Based on this analysis, the recipient wetland should be sufficiently large that it can support at least 25 pairs of gallinules. Based on recent estimates of population densities on O‘ahu, such a wetland would need to be between 3.75-74.6 ha. Where stable source populations of at-risk species exist, translocation may be a reasonable strategy for re-establishing extirpated populations. However, the success rates of such efforts are mixed, necessitating thorough preliminary investigation. Stochastic population modeling can be a useful method of assessing the potential success of translocations. Here, we report on the results of modeling translocation success for the Hawaiian Common Gallinule (‘alae ‘ula; Gallinula galeata sandvicensis), an endangered waterbird endemic to the Hawaiian Islands. Using updated vital rates, we constructed a model simulating three existing extant (wild) source populations and a hypothetical recipient site on another island. We then projected the effects of six different translocation scenarios and sensitivity of the results to variation of three important demographic parameters on the probability of extinction (PE) of the reintroduced and donor populations. Larger translocations, of at least 30 birds, had low probability of extinction in the reintroduced population, but raised extinction risk of the smallest source population. Spacing out translocations in time (e.g., 10 birds translocated in total in three installments over nine years), led to lower PE than translocating all individuals at once (i.e., bulk translocations) for both the source and reintroduced populations. Brood size and hatch-year juvenile survival had a disproportionate impact on reintroduced population viability. Importantly, the reported juvenile survival rate is very near the threshold for population failure. This suggests that post-introduction and subsequent management of wetlands, particularly predator control, could be critical to reintroduction success. We recommend that individuals should be translocated from multiple, genetically distinct subpopulations to reduce the possibility of inbreeding depression. Based on this analysis, the recipient wetland should be sufficiently large that it can support at least 25 pairs of gallinules. Based on recent estimates of population densities on O‘ahu, such a wetland would need to be between 3.75-74.6 ha. Methods Reproductive rate data (HAGAVitalRates_9-10-23_Export) We acquired nest data from recent monitoring projects run through the state of Hawaii Department of Land and Natural Resources, Division of Forestry and Wildlife (DOFAW) on O‘ahu, and graduate dissertation work conducted at Hanalei National Wildlife Refuge on Kaua‘i (by BW). Nests on O‘ahu were located during routine weekly or biweekly surveys using an area-search survey. A team of 3–7 observers walked meandering transects with the goal of locating all nests in a given area. All nests were visually checked 2 times per week until hatching or failure. DOFAW nest monitoring continued throughout the annual cycle. A subset of Hawaiian Gallinule nests on O‘ahu was monitored from January through December 2020–2023. All nests were visually checked at least twice weekly, and a subset was monitored from January through December 2020–2023 using SPYPOINT Solar Dark (GG Telecom, Quebec, Canada) passive infrared cameras (trigger speed: 0.07 s) placed about 1 m from the nest, mounted on a 7.6 cm wide metal post 1.8 m long, fixed with a fully adjustable camera mount that allows a camera angle of 0–90. Cameras were programmed to take 2 images back-to-back immediately upon infrared motion activation. Cameras were programmed to take photos instantly for each activation (Instant setting recovery speed: 0.3 s). Cameras were checked weekly for battery life and SD card data retrieval and were removed either immediately after a nest wasconfirmed failed or after a nest was confirmed successful. A nest was considered successful if at least 1 egg hatched and was considered failed if the eggs all disappeared before the expected hatch date or if signs of predation (e.g., predator scat/tracks in the nest or destroyed eggs adjacent to the nest), flooding (e.g., intact eggs outside nest following an increase in water level or nest submerged under water), or abandonment (e.g., eggs cold to the touch in the morning, hot to the touch in the afternoon) were apparent. On Kaua‘i, nests were found by conducting systematic searches. In wetland units managed strictly for waterbirds, transects spaced 10 m apart were walked, while in taro that was grown on the refuge searches were done by walking the pond perimeter. Although Hawaiian Gallinules can nest year-round (Shallenberger 1977, Byrd and Zeillemaker 1981), searches were concentrated during the main breeding season. Nests also were found incidentally during regular activities by refuge staff and taro farmers. Nests on Kaua‘i were monitored with and without cameras (see Webber 2022 for details of monitoring and assessment of nest fates). All nests were checked every 3–5 d to monitor nest status; if the brood continued to use the nest after hatching and the camera was available, monitoring continued for brood survival data. Brood Survival Data (BroodDatabase_8-24-22) Due to some methodological differences in brood monitoring among datasets compiled in this study, we resampled data to a matching, lowest common temporal resolution. Brood data from Keawawa wetland (O‘ahu) were recorded via multiple daily surveys for the first 60þ d posthatch by a group of trained citizen science volunteers. Brood encounter data on Kaua‘i were collected based on 4 d encounter intervals, recording presence and number of chicks if the brood was detected on any day within the interval. All brood records in our Kaua‘i dataset were collected by BW, and they were monitored by surveying telemetered adults (see Webber 2022 for details). Territories with known nests were monitored starting at what was estimated to be mid-incubation, and visited at least once every 4 d. At James Campbell National Wildlife Refuge (O‘ahu), brood encounters were opportunistic. Except for data from Keawawa, most brood monitoring ended after the first month post-hatch. Based on these data formats, we reduced our combined data to 4 d intervals and the first 30 d post-hatch to avoid estimating parameters with a sparse dataset.

A new species endemic to Hawaiʻi Island, Tetramolopium stemmermanniae, is described and illustrated. Molecular and morphological evidence support Tetramolopium stemmermanniae as being distinct from Tetramolopium arenarium var. arenarium, Tetramolopium consanguineum ssp. leptophyllum, and Tetramolopium humile ssp. humile, which occur at Pōhakuloa Training Area, Hawaiʻi Island. Tetramolopium stemmermanniae shares an upright and multibranched habit as that of Tetramolopium arenarium var. arenarium and Tetramolopium consanguineum ssp. leptophyllum. It differs in ray and disc flower color and number, and in having an open, paniculate inflorescence. We provide a description of the new taxon, include a key to the Tetramolopium species of Hawaiʻi, and a brief description of the habitat where it occurs. Methods Plant specimens were collected from 10 individuals of the new form of Tetramolopium at Pōhakuloa Training Area, (Fig. 1) from 2009–2020. Five collections for type specimens were made from one locality in 2020 because of the small number of individuals at the other locations. Collected specimens were compared with voucher specimens of other Tetramolopium taxa held at the Bishop Museum Herbarium (BISH). Voucher specimens of field-collected plants are deposited at Bishop Museum Herbarium, United States National Herbarium at the Smithsonian Institution (US), Colorado State University Center for Environmental Management of Military Lands Herbarium (CMML) at Colorado State University, and Pōhakuloa Training Area Herbarium (PTA). All material was legally collected with appropriate permits. Plant leaf tissue of 68 individuals from three Tetramolopium species found at PTA was collected into silica gel in August and September 2014 for a molecular population study. The collections include 32 individuals of the new form representing six sites, 9 individuals of T. arenarium representing three sites, and 27 individuals of T. consanguineum representing eight sites. Seven Tetramolopium species (total of 14 samples from the Hawaiian Islands including four samples used in population study) were obtained for the phylogenetic analysis; included two herbarium samples contributed by Dr. Timothy Lowrey; Keysseria erici (Forbes) Cabrera for use as an outgroup taxon in the phylogenetic work (Appendix 1). DNA was extracted from all samples and purified following previously established laboratory protocols described in Morden et al. (1996). Each sample was assigned an accession number in the Hawaiian Plant DNA Library (HPDL; Morden et al. 1996; Randell and Morden 1999; http://www.botany.hawaii.edu/hawaiian-plant-dna-library; Appendix 1). The concentration and quality of the extracted DNA were assessed using a Nano Drop Spectrophotometer (ND-1000, ver. 3.6.0, Thermo Fisher Scientific, Waltham, Massachusetts). All DNA samples were diluted to 10–15 ng/μl and stored at -20°C until used. Sequence-related amplified polymorphism (SRAP) markers were utilized to investigate genetic variation within and among populations of T. arenarium, T. consanguineum and the new form of Tetramolopium (Li and Quiros 2001; Robarts and Wolfe 2014; Zagorcheva et al. 2020). DNA from one to a few individuals of each species were surveyed with 100 combinations of 10 forward and 10 reverse SRAP primers (Budak et al. 2004). SRAP analyses were conducted using a 15 μl PCR reaction mixture consisting of: 1xPCR buffer [10 mM Tris-HCl (pH 9.0 at 25°C), 50 mM KCl and 0.1% Triton X-100, Promega, Madison, Wisconsin], 1.5 mM MgCl2, 0.25 mg BSA, 0.2 mM dNTPs, 0.5 mM of each forward and reverse primers (IDT, Coralville, Iowa), 1 unit of Taq DNA polymerase (Promega), and approximately 10–15 ng of total DNA. All reactions were carried out in an MJ Research (GMI, Inc. Ramsey, Minnesota) or Eppendorf thermal cycler (Eppendorf AG, Hamburg, Germany) with cycling conditions following that established by Li and Quiros (2001). PCR amplified products were mixed with loading dye and separated on a 2% agarose gel, stained with ethidium bromide (EtBr), and visualized with a UV light source. Negative control reactions were run without DNA for all PCR amplifications to ensure reaction components were uncontaminated. Each primer combination was repeated at least once with selected samples to confirm the reproducibility of the genetic markers. Size of amplification products was estimated using either a 100 bp ladder (Promega) or a pBS plasmid (Stratgene, La Jolla, California) digested with restriction enzymes to produce fragments in a size range from 0.448–2.96 Kb. Final gel products were viewed using a Gel Doc XR (BIO-RAD, Hercules, California) and digitally recorded using Quantity One software (BIO-RAD, ver. 4.5.1). SRAP markers were scored either present (1) or absent (0). The scored data were entered into a binary matrix and assessed for polymorphic, unique loci. From this observed and expected heterozygosity were calculated using GenAlEx6.502 (Peakall and Smouse 2006, 2012). Principal coordinates analysis (PCO) using Gower general similarity coefficients (Gower 1971) were calculated using MVSP 3.1 (Kovach 2007). Pairwise similarities were averaged for individuals within and among species. The SRAP binary matrix was also used to resolve an unrooted neighbor joining (NJ) tree from a mean Euclidean distance matrix with 1,000 bootstrap replicates to assess clade support using DARwin v6.0.021 (Perrier et al. 2003). DNA Sequence variation was analyzed for four nuclear rDNA regions and five chloroplast DNA regions. The non-coding nuclear regions included rDNA ITS (Baldwin 1992), ETS (Baldwin and Markos 1998), 5S-NTS (Cox et al. 1992; Sastri et al. 1992), and nuclear NIA (Levin et al. 2009). Chloroplast loci included the rpl16 intron (Shaw et al. 2005), the psbA–trnH spacer (Shaw et al. 2005), trnT-L spacer, trnL intron, and the trnL-F spacer (Taberlet et al. 1991). Samples were PCR amplified in 25 µl volumes with the following components: 25 ng of DNA, ca. 0.2 mM each of dATP, dCTP, dGTP, dTTP, 1X Taq Polymerase buffer (10 mM Tris-HCl [pH 9.0 at 25°C], 50 mM KCl, and 0.1% Triton X-100 [Promega]), 1.5 mM MgCl2, 0.50 mg BSA, 0.2 mM forward and reverse primers, and ca. 1 unit of Taq DNA Polymerase (Promega). PCR reactions were performed using thermocycling conditions outlined in the original primer references. Positive PCR amplification was confirmed and digitally recorded as described above. The PCR products were purified using an Exo-Sap-It kit (Affymetrix, Santa Clara, California) according to the manufacturer’s instructions. PCR products were bidirectionally Sanger sequenced using amplification primers on an Applied Biosystems 3730XL DNA Analyzer (Applied Biosystems, Waltham, Massachusetts, USA) at the University of Hawaii’s facility for Advanced Studies in Genomics, Proteomics, and Bioinformatics. Sanger sequence results were edited and contiged using Sequencher® ver. 5.0 sequence analysis software (Gene Codes Corporation, Ann Arbor, Michigan) and aligned using MEGA6.06-mac (Tamura et al. 2013) using ClustalW with default parameters. Aligned sequences were converted by Mesquite ver. 3.03 (Maddison and Maddison 2015) to Nexus format for use in phylogenetic analyses. Phylogenetic Bayesian analysis was conducted using MrBayes on XSEDE (3.2.6) (Ronquist et al. 2012) from the CIPRES Portal (Miller et al. 2010). The GRT+I+G model was chosen for partitioned and combined data sets as proposed by Abadi et al. (2019) using four heated four chains run for 10 million generations with sampling every 1000 generations and the first 25% of trees discarded as burn-in. Branch support was evaluated by posterior probability. PAUP* v. 4.0b 10 (Altivec; Swofford 2002) was used for parsimony analysis using a branch-and-bound search option and bootstrap resampling (1000 pseudoreplicates) to calculate branch support (Felsenstein 1985). An additional set of phylogenetic analyses were conducted using a concatenated alignment containing only perfectly homologous and parsimony informative loci to ensure lineage-specific loci were not biasing the results. The trimmed matrix was analyzed using the BI procedures described above as well as an NJ method using the Tamura-Nei genetic distance model (Tamura and Nei 1993) and 1,000 jack knife replicates to assess clade support. Model Finder (Kalyaanamoorthy et al. 2017) and IQ-Tree (Version 2.2.0) (Nguyen et al. 2015) (www.igtree.ort);(http://iqtree.cibiv.univie.ac.at) were used to determine the best-fit model and to construct a maximum-likelihood tree for each locus respectively. Ultrafast bootstrap approximation (UFBoot) (Hoang et al. 2018) was used to obtain branch support values. Trees were visualized using FigTree (v. 1.4.4) (http://Tree.bio.ed.ac.ul/software/figtree/).

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. Public Use Microdata Areas (PUMAs) are decennial census areas that permit the tabulation and dissemination of Public Use Microdata Sample (PUMS) data, American Community Survey (ACS) data, and data from other censuses and surveys. For the 2020 Census, the State Data Centers (SDCs) in each state, the District of Columbia, and the Commonwealth of Puerto Rico had the opportunity to delineate PUMAS within their state or statistically equivalent entity. All PUMAs must nest within states and have a minimum population threshold of 100,000 persons. 2020 PUMAs consist of census tracts and cover the entirety of the United States, Puerto Rico and Guam. American Samoa, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands do not contain any 2020 PUMAs because the population is less than the minimum population requirement. Each PUMA is identified by a five-character numeric census code that may contain leading zeros and a descriptive name.

Genetic diversity levels, population structure, and effective population size estimates of the endangered Hawaiian hoary bat (Lasiurus semotus, also known as Aeorestes semotus) were examined across the islands of Hawai‘i, Maui, O‘ahu, and Kaua‘i using eighteen nuclear microsatellite loci and one mitochondrial gene from 339 individuals collected between 1988 and 2020. The study extracted DNA for population genetic analyses from tissue samples, collected from live bats captured as part of ongoing field studies or under rehabilitation care, from bat carcasses collected by local federal and state wildlife agencies and wind energy facilities, and from dried skin specimens at the Bernice Pauahi Bishop Museum. A region of the mitochondrial CO1 gene was sequenced in 321 individuals and eighteen nuclear microsatellite loci were amplified from 298 individuals. This dataset contains tissue collection site information and genetic testing groupings for the 339 individual bat samples used in the study.

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. Public Use Microdata Areas (PUMAs) are decennial census areas that permit the tabulation and dissemination of Public Use Microdata Sample (PUMS) data, American Community Survey (ACS) data, and data from other census and surveys. For the 2020 Census, the State Data Centers (SDCs) in each state, the District of Columbia, and the Commonwealth of Puerto Rico had the opportunity to delineate PUMAS within their state or statistically equivalent entity. All PUMAs must nest within states and have a minimum population threshold of 100,000 persons. 2020 PUMAs consist of census tracts and cover the entirety of the United States, Puerto Rico and Guam. American Samoa, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands do not contain any 2020 PUMAs because the population is less than the minimum population requirement. Each PUMA is identified by a 5-character numeric census code that may contain leading zeros and a descriptive name.

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. Congressional districts are the 435 areas from which people are elected to the U.S. House of Representatives. After the apportionment of congressional seats among the states based on census population counts, each state is responsible for establishing congressional districts for the purpose of electing representatives. Each congressional district is to be as equal in population to all other congressional districts in a state as practicable. The 118th Congress is seated from January 2023 through December 2024. In Connecticut, Illinois, and New Hampshire, the Redistricting Data Program (RDP) participant did not define the CDs to cover all of the state or state equivalent area. In these areas with no CDs defined, the code "ZZ" has been assigned, which is treated as a single CD for purposes of data presentation. The TIGER/Line shapefiles for the District of Columbia, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands) each contain a single record for the non-voting delegate district in these areas. The boundaries of all other congressional districts reflect information provided to the Census Bureau by the states by August 31, 2022.

Although the founding fathers declared American independence in 1776, and the subsequent Revolutionary War ended in 1783, individual states did not officially join the union until 1787. The first states to ratify the U.S. Constitution were Delaware, Pennsylvania and New Jersey, in December 1787, and they were joined by the remainder of the thirteen ex-British colonies by 1790. Another three states joined before the turn of the nineteenth century, and there were 45 states by 1900. The final states, Alaska and Hawaii, were admitted to the union in 1959, almost 172 years after the first colonies became federal states. Secession in the American Civil War The issues of slavery and territorial expansion in the mid nineteenth century eventually led to the American Civil War, which lasted from 1861 until 1865. As the U.S. expanded westwards, a moral and economic argument developed about the legality of slavery in these new states; northern states were generally opposed to the expansion of slavery, whereas the southern states (who were economically dependent on slavery) saw this lack of extension as a stepping stone towards nationwide abolition. In 1861, eleven southern states seceded from the Union, and formed the Confederate States of America. When President Lincoln refused to relinquish federal property in the south, the Confederacy attacked, setting in motion the American Civil War. After four years, the Union emerged victorious, and the Confederate States of America was disbanded, and each individual state was readmitted to Congress gradually, between 1866 and 1870. Expansion of other territories Along with the fifty U.S. states, there is one federal district (Washington D.C., the capital city), and fourteen overseas territories, five of which with a resident population (American Samoa, Guam, the Northern Mariana Islands, Puerto Rico, and the U.S. Virgin Islands). In 2019, President Trump inquired about the U.S. purchasing the territory of Greenland from Denmark, and, although Denmark's response indicated that this would be unlikely, this does suggest that the US may be open to further expansion of it's states and territories in the future. There is also a movement to make Washington D.C. the 51st state to be admitted to the union, as citizens of the nation's capital (over 700,000 people) do not have voting representation in the houses of Congress nor control over many local affairs; as of 2020, the U.S. public appears to be divided on the issue, and politicians are split along party lines, as D.C. votes overwhelmingly for the Democratic nominee in presidential elections.

This data set contains estimated teen birth rates for age group 15–19 (expressed per 1,000 females aged 15–19) by county and year. DEFINITIONS Estimated teen birth rate: Model-based estimates of teen birth rates for age group 15–19 (expressed per 1,000 females aged 15–19) for a specific county and year. Estimated county teen birth rates were obtained using the methods described elsewhere (1,2,3,4). These annual county-level teen birth estimates “borrow strength” across counties and years to generate accurate estimates where data are sparse due to small population size (1,2,3,4). The inferential method uses information—including the estimated teen birth rates from neighboring counties across years and the associated explanatory variables—to provide a stable estimate of the county teen birth rate. Median teen birth rate: The middle value of the estimated teen birth rates for the age group 15–19 for counties in a state. Bayesian credible intervals: A range of values within which there is a 95% probability that the actual teen birth rate will fall, based on the observed teen births data and the model. NOTES Data on the number of live births for women aged 15–19 years were extracted from the National Center for Health Statistics’ (NCHS) National Vital Statistics System birth data files for 2003–2015 (5). Population estimates were extracted from the files containing intercensal and postcensal bridged-race population estimates provided by NCHS. For each year, the July population estimates were used, with the exception of the year of the decennial census, 2010, for which the April estimates were used. Hierarchical Bayesian space–time models were used to generate hierarchical Bayesian estimates of county teen birth rates for each year during 2003–2015 (1,2,3,4). The Bayesian analogue of the frequentist confidence interval is defined as the Bayesian credible interval. A 100*(1-α)% Bayesian credible interval for an unknown parameter vector θ and observed data vector y is a subset C of parameter space Ф such that 1-α≤P({C│y})=∫p{θ │y}dθ, where integration is performed over the set and is replaced by summation for discrete components of θ. The probability that θ lies in C given the observed data y is at least (1- α) (6). County borders in Alaska changed, and new counties were formed and others were merged, during 2003–2015. These changes were reflected in the population files but not in the natality files. For this reason, two counties in Alaska were collapsed so that the birth and population counts were comparable. Additionally, Kalawao County, a remote island county in Hawaii, recorded no births, and census estimates indicated a denominator of 0 (i.e., no females between the ages of 15 and 19 years residing in the county from 2003 through 2015). For this reason, Kalawao County was removed from the analysis. Also , Bedford City, Virginia, was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. For consistency, Bedford City was merged with Bedford County, Virginia, for the entire 2003–2015 period. Final analysis was conducted on 3,137 counties for each year from 2003 through 2015. County boundaries are consistent with the vintage 2005–2007 bridged-race population file geographies (7). SOURCES National Center for Health Statistics. Vital statistics data available online, Natality all-county files. Hyattsville, MD. Published annually. For details about file release and access policy, see NCHS data release and access policy for micro-data and compressed vital statistics files, available from: http://www.cdc.gov/nchs/nvss/dvs_data_release.htm. For natality public-use files, see vital statistics data available online, available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. National Center for Health Statistics. U.S. Census populations with bridged race categories. Estimated population data available. Postcensal and intercensal files. Hyattsville, MD