About this dataset

Context

The dataset tabulates the median household income in Grass Range. It can be utilized to understand the trend in median household income and to analyze the income distribution in Grass Range by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Grass Range, MT Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Grass Range, MT: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Grass Range, MT
• Grass Range, MT households by income brackets: family, non-family, and total, in 2022 inflation-adjusted dollars

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Grass Range median household income. You can refer the same here

particularly under uncertain growth of behind-the-meter renewable energy sources.

Dataset

This dataset was created by Sarkar Arpan

Released under CC0: Public Domain

Contents

About this dataset

Context

The dataset tabulates the population of Grass Range by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Grass Range across both sexes and to determine which sex constitutes the majority.

Key observations

There is a considerable majority of female population, with 71.13% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Grass Range is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Grass Range total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for Grass Range Population by Race & Ethnicity. You can refer the same here

Vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for Californias wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California. CWHR contains information on life history, management status, geographic distribution, and habitat relationships for wildlife species known to occur regularly in California. Range maps represent the maximum, current geographic extent of each species within California. They were originally delineated at a scale of 1:5,000,000 by species-level experts and have gradually been revised at a scale of 1:1,000,000. For more information about CWHR, visit the CWHR webpage (https://www.wildlife.ca.gov/Data/CWHR). The webpage provides links to download CWHR data and user documents such as a look up table of available range maps including species code, species name, and range map revision history; a full set of CWHR GIS data; .pdf files of each range map or species life history accounts; and a User Guide.

CDFW BIOS GIS Dataset, Contact: Damon Goodman, Description: This dataset depicts the estimated historic range and current distribution (2016) of Pacific Lamprey (Entosphenus tridentatus) in California.

This dataset contains GIS layers that depict the known spatial distributions (i.e., ranges) of the two subspecies of bearded seals (Erignathus barbatus). It was produced as part of a U.S. Endangered Species Act status review, which included delineating the species in question and assessing its risk of extinction within the foreseeable future throughout all or a significant portion of its range. Its boundaries are based on previously published range maps and/or descriptions of the species' distribution in published or unpublished accounts. All boundaries should be considered approximate. The approximate North American boundary between the two sub-species was changed to 130W (from 112W), based a re-analysis of the genetic data.

About this dataset

Context

The dataset tabulates the median household income in South Range. It can be utilized to understand the trend in median household income and to analyze the income distribution in South Range by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• South Range, MI Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in South Range, MI: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in South Range, MI
• South Range, MI households by income brackets: family, non-family, and total, in 2022 inflation-adjusted dollars

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of South Range median household income. You can refer the same here

INSPIRE Priority Data Set (Compliant) - BIRDS range

This dataset shows the literature survey used for analysis in manuscript Yalcin & Leroux (2017).Yalcin S, Leroux SJ. Diversity and suitabilityof existing methods and metrics for quantifying speciesrange shifts. Global Ecol Biogeogr. 2017;00:000–000.

Vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for Californias wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California. CWHR contains information on life history, management status, geographic distribution, and habitat relationships for wildlife species known to occur regularly in California. Range maps represent the maximum, current geographic extent of each species within California. They were originally delineated at a scale of 1:5,000,000 by species-level experts and have gradually been revised at a scale of 1:1,000,000. For more information about CWHR, visit the CWHR webpage (https://www.wildlife.ca.gov/Data/CWHR). The webpage provides links to download CWHR data and user documents such as a look up table of available range maps including species code, species name, and range map revision history; a full set of CWHR GIS data; .pdf files of each range map or species life history accounts; and a User Guide.

This table provides statistics on the Distribution of Gross Payments to Physicians by Payment Range and Specialty, based on fee-for-service payments under the Alberta Health Care Insurance Plan (AHCIP). This table is an Excel version of a table in the “Alberta Health Care Insurance Plan Statistical Supplement” report published annually by Alberta Health.

Invertebrates constitute the majority of animal species and are critical for ecosystem functioning and services. Nonetheless, global invertebrate biodiversity patterns and their congruences with vertebrates remain largely unknown. We resolve the first high-resolution (~20-km) global diversity map for a major invertebrate clade, ants, using biodiversity informatics, range modeling, and machine learning to synthesize existing knowledge and predict the distribution of undiscovered diversity. We find that ants and different vertebrate groups have distinct features in their patterns of richness and rarity, underscoring the need to consider a diversity of taxa in conservation. However, despite their phylogenetic and physiological divergence, ant distributions are not highly anomalous relative to variation among vertebrate clades. Furthermore, our models predict rarity centers largely overlap (78%), suggesting that general forces shape endemism patterns across taxa. This raises confidence that conservation of areas important for small-ranged vertebrates will benefit invertebrates while providing a "treasure map" to guide future discovery.

This dataset is about: (Table 2) Mean distribution of clay minerals and range of main species in the lithologic units of ODP Site 133-823. Please consult parent dataset @ https://doi.org/10.1594/PANGAEA.786568 for more information.

About this dataset

Context

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

Key observations

Largest age group (population): Male # 20-24 years (49) | Female # 20-24 years (50). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Age groups:

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

Scope of gender :

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for South Range Population by Gender. You can refer the same here

In coastal wetlands, one of the most striking examples of climate change is the poleward range expansion of mangrove forests in response to warming winters. In North America, the Cedar Key region has often been considered the range limit for mangroves along the western coast of Florida (USA). However, within the past several decades, robust stands of Avicennia germinans and Rhizophora mangle have been observed in the Apalachicola Bay region, which is 200 km northwest of Cedar Key. This dataset characterizes the distribution and structure of the mangroves in the Apalachicola Bay area of Florida identified via extensive ground surveys and photointerpretation of aerial imagery from 2018 to 2019.

This raster portrays the distribution of sagebrush within the geographic extent of the sagebrush biome in the United States. It was created for the Western Association of Fish and Wildlife Agency’s (WAFWA) Sagebrush Conservation Strategy publication as a visual for the schematic figures and to calculate summary statistics. This distribution incorporates the most recently available sagebrush cover mapping (Xian et al. 2015, Rigge et al. 2019) and classified LANDFIRE EVT (Department of Ecosystem Science, University of Wyoming 2016). Both datasets were rigorously evaluated and extensive ground measurements taken to evaluate accuracy by the respective authors. We created a combined binary sagebrush distribution by classifying the Rigge et al. (2019) product to a binary form where sagebrush cover was greater than 5%, which is equal to the root mean squared error of the analysis (RMSE = 5.09). The Rigge et al. (2019) raster is not complete across the sagebrush biome, so we filled in the areas of NoData with the 'Sagebrush-dominated Ecological Systems' pixels from binary sagebrush raster (Department of Ecosystem Science, University of Wyoming 2016) to create a continuous raster across the sagebrush biome. The input layers are informative to conditions circa the beginning of 2015.

This dataset contains GIS layers that depict the known spatial distributions (i.e., ranges) of the five subspecies of ringed seals (Phoca hispida). It was produced as part of a U.S. Endangered Species Act status review, which included delineating the species in question and assessing its risk of extinction within the foreseeable future throughout all or a significant portion of its range. Its boundaries are based on previously published range maps and/or descriptions of the species' distribution in published or unpublished accounts. All boundaries should be considered approximate.

Species distribution data provide the foundation for a wide range of ecological research studies and conservation management decisions. Two major efforts to provide marine species distributions at a global scale are the International Union for Conservation of Nature (IUCN), which provides expert-generated range maps that outline the complete extent of a species' distribution; and AquaMaps, which provides model-generated species distribution maps that predict areas occupied by the species. Together these databases represent 24,586 species (93.1% within AquaMaps, 16.4% within IUCN), with only 2,330 shared species. Differences in intent and methodology can result in very different predictions of species distributions, which bear important implications for scientists and decision makers who rely upon these datasets when conducting research or informing conservation policy and management actions. Comparing distributions for the small subset of species with maps in both datasets, we found that AquaMaps and IUCN range maps show strong agreement for many well-studied species, but our analysis highlights several key examples in which introduced errors drive differences in predicted species ranges. In particular, we find that IUCN maps greatly overpredict coral presence into unsuitably deep waters, and we show that some AquaMaps computer-generated default maps (only 5.7% of which have been reviewed by experts) can produce odd discontinuities at the extremes of a species’ predicted range. We illustrate the scientific and management implications of these tradeoffs by repeating a global analysis of gaps in coverage of marine protected areas, and find significantly different results depending on how the two datasets are used. By highlighting tradeoffs between the two datasets, we hope to encourage increased collaboration between taxa experts and large scale species distribution modeling efforts to further improve these foundational datasets, helping to better inform science and policy recommendations around understanding, managing, and protecting marine biodiversity.

A.atkinsiana and A.ancistrocarpa genotypesMicrosatellite genotypes and population locations for A.atkinsiana and A. ancistrocarpa in Genalex formatA.ancistrocarpa sequence dataChloroplast sequence data for A. ancistrocarpa in Nexus formatA.atkinsiana sequence dataChloroplast sequence data for A. atkinsiana in Nexus format