This data file is in long format, comprising time series of hunter abundance and behavior and duck abundance. Hunter information varies by administrative flyway (Mississippi and Central), whereas duck population abundance is summarized for both the Prairie Pothole Region and the continent. Duck information for the Prairie Pothole Region is for the U.S. portion only (Strata 41-49 of the May waterfowl survey) and for 12 duck species, mallard, American wigeon, blue-winged teal, canvasback, gadwall, lesser and greater scaup, green-winged teal, northern pintail, northern shoveler, redhead, ring-necked duck, and ruddy duck.

About this dataset

Context

The dataset tabulates the Hunters Hollow population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Hunters Hollow. The dataset can be utilized to understand the population distribution of Hunters Hollow by age. For example, using this dataset, we can identify the largest age group in Hunters Hollow.

Key observations

The largest age group in Hunters Hollow, KY was for the group of age 10 to 14 years years with a population of 43 (12.25%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Hunters Hollow, KY was the 80 to 84 years years with a population of 0 (0%). 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

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Hunters Hollow is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Hunters Hollow 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 Hunters Hollow Population by Age. You can refer the same here

Mapped hunt boundary is an approximation of regulations using best available data as of September 2015. Hunters are responsible for knowing the exact current boundary locations as described within the California Code of Regulations, Title 14, Section 485(d):(d) Crows may not be taken in the following areas:(1) Within the boundaries of the Trinity and Mendocino National Forests south of Highway 36.(2) North and east of a line beginning at the mouth of the Eel River; south along the Eel River to the town of Alton; east on Highway 36 from the town of Alton to Highway 89 west of Chester; south and east on Highways 89 and 395 to Interstate 15 near Hesperia; south on Interstate 15 to Interstate 10; and east on Interstate 10 to the California-Arizona border.

About this dataset

Context

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

Key observations

There is a majority of male population, with 54.7% of total population being male. 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 Hunters Hollow is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Hunters Hollow 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 Hunters Hollow Population by Race & Ethnicity. You can refer the same here

Ramsey County conducts special permit archery hunts each fall in partnership with the Metro Bowhunters Resource Base. This dataset shares archery harvest totals. The annual hunts have been conducted since 2000. All participating hunters attend a pre-hunt orientation, agree to special hunt rules and pass an archery safety class and shooting proficiency test. Archers may keep their deer or donate the venison to local food shelves. During the hunts, entire parks or portions of a park may be closed. Archery hunting is the county's preferred method of deer population control.

This report is based on three years of research during which the author conducted a pair of studies on American attitudes and perceptions of animals. More than any other single subject, views for and against hunting provided a kind of barometer for assessing people’s much broader understanding of the natural world. Most of the material presented in this report is based on data collected over these three years. The first study -- involving personally conducted, in-depth largely unconstructed interviews -- provided much of the first-person accounts and was mainly descriptive. The second study involved a national investigation in which over 550 randomly selected Americans were personally interviewed to complete a highly-structured close-ended, 45-minute questionnaire. The information collected in this latter investigation provides most of the statistical data that will be presented.

The Digital Surficial Geologic-GIS Map of the Hunters 15' Quadrangle, Washington is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (htrs_surficial_geology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (htrs_surficial_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (htrs_surficial_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (laro_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (laro_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (htrs_surficial_geology_metadata_faq.pdf). Please read the laro_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Bureau of Reclamation. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (htrs_surficial_geology_metadata.txt or htrs_surficial_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:62,500 and United States National Map Accuracy Standards features are within (horizontally) 31.8 meters or 104.2 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

About this dataset

Context

The dataset tabulates the data for the Hunters Hollow, KY population pyramid, which represents the Hunters Hollow population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Hunters Hollow, KY, is 26.5.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Hunters Hollow, KY, is 14.5.
• Total dependency ratio for Hunters Hollow, KY is 41.0.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Hunters Hollow, KY is 6.9.

Content

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

Age groups:

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

Variables / Data Columns

• Age Group: This column displays the age group for the Hunters Hollow population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Hunters Hollow for the selected age group is shown in the following column.
• Population (Female): The female population in the Hunters Hollow for the selected age group is shown in the following column.
• Total Population: The total population of the Hunters Hollow for the selected age group is shown in the following column.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for Hunters Hollow Population by Age. You can refer the same here

Tag allocation systems that were used for analysis in each state with the corresponding years of antlerless harvest records. Cells marked with an asterisk (*) indicate that the relevant bag limit was invariant throughout the data set which resulted in no effect size estimate, but still allowed for an intercept estimate.

Identifying the specific environmental features and associated density-dependent processes that limit population growth is central to both ecology and conservation. Comparative assessments of sympatric species allow for inference into how ecologically similar species differentially respond to their shared environment, which can be used to inform community-level conservation strategies. Comparative assessments can nevertheless be complicated by interactions and feedback loops among the species in question. We developed an integrated population model based on sixty-one years of ecological data describing the demographic histories of Canvasbacks (Aythya valisineria) and Redheads (Aythya americana), two species of migratory diving ducks that utilize similar breeding habitats and affect each other’s demography through interspecific nest parasitism. We combined this model with a transient life table response experiment to determine the extent that demographic rates, and their contributions to population growth, were similar between these two species. We found that demographic rates and, to a lesser extent, their contributions to population growth covaried between Canvasbacks and Redheads, but the trajectories of population abundances widely diverged between the two species during the end of the 20th century due to inherent differences between the species life-histories and sensitivities to both environmental variation and harvest pressure. We found that annual survival of both species increased during years of restrictive harvest regulations; however, recent harvest pressure on female Canvasbacks may be contributing to population declines. Despite periodic, and often dramatic, increases in breeding abundance during wet years, the number of breeding Canvasbacks declined by 13% whereas the number of breeding Redheads has increased by 37% since 1961. Reductions in harvest pressure and improvements in submerged aquatic vegetation throughout the wintering grounds have mediated the extent to which populations of both species contracted during dry years in the Prairie Pothole Region. However, continued degradation of breeding habitats through climate-related shifts in wetland hydrology and agricultural conversion of surrounding grassland habitats may have exceeded the capacity for demographic compensation during the non-breeding season. Methods DATA COLLECTION We combined a series of long-term data sets into a single integrated population model that provided insights into how variation in seasonal survival (band releases and recoveries) and offspring production (harvest age-ratios) contributed to fluctuations in population growth (breeding survey, harvest estimates) for Canvasbacks and Redheads from 1961–2021. Banding Data – Information regarding the banding and subsequent harvest of ducks was acquired from the GameBirds Database CD (Bird Banding Lab, USGS Patuxent Wildlife Research Center, Laurel MD, USA, version August 2022). Male and female Canvasbacks and Redheads were captured following breeding but prior to the hunting season (Pre-Hunting) as ducklings (Local) or hatch year (HY; fledged juvenile) individuals as well as after hatch year (AHY; adult) individuals or following the hunting season (Post-Hunting) as an undifferentiated mixture of second year (SY) and after second year (ASY) individuals captured and released across North America from 1961–2022. We limited the pre-harvest banding data for both species to include all individuals banded and released alive in areas within the Canadian provinces of Alberta, Manitoba, Saskatchewan, as well as the states of Minnesota, Montana, North Dakota, and South Dakota within the USA (Fig. 1). For the pre-hunting banding group, we retained individuals captured between 1961–2021 during the late summer (Jul 15th – Sep 15th) with a known sex (M or F) and age-class (local, HY or AHY) that were released without any additional markers considered to meaningfully affect survival of an individual (e.g., nasal saddles or dual banding were permissible but telemetered individuals were excluded; Lameris & Kleyheeg, 2017). For post-hunting banding, we limited the spatial boundary of banding efforts to only consider individuals released from the Atlantic, Central, or Mississippi Flyways (Fig. 1). We followed the same data selection procedures, but limited releases to occur between Jan. 1st – March 15th from 1962–2022. Because too few banders differentiated SY from ASY at time of banding, we treated all post-hunting samples as AHY adults. Individuals banded during this period that were reported to be harvested during the winter they were originally banded were censored from the analysis, as the underlying model assumption was that this cohort of individuals had already survived the current hunting season. For both seasonal banding efforts, we only included recoveries of hunter-shot individuals harvested between September and February in which a known year-of-death could be ascertained. In addition to self-reported recoveries (i.e., reported by the hunter), we included hunter-harvested individuals that were instead reported by federal, state, or provincial entities (e.g., outcomes of hunter check stations or other forms of solicitation). We limited the dataset to only include recoveries of hunter-harvested individuals killed within 15 years of initial banding, which represented > 99% of pre-hunting and post-hunting recoveries. This cut-off was arbitrarily selected but did not meaningfully bias parameter estimation while vastly improving computational efficiency by bypassing the estimation of hundreds of zero-equivalent cell probabilities (personal communication S. Bonner). Harvest Intensity – We used the average number of Canvasbacks or Redheads allowed to be harvested per day (i.e., bag limit; (Appendix S1: Tables S1a-b) across the U.S. portions of the Atlantic, Mississippi, Central, and Pacific flyways during each year of the study as an index of harvest regulatory pressure. Annual harvest restrictions were acquired from the published literature (Péron et al., 2012), the annual release of the Late-Season Migratory Bird Hunting Regulations (e.g., USFWS 2022), and direct requests to the U.S. Fish and Wildlife Service. For these species, liberal harvest regulations were bag limits of two (Canvasbacks) and two to four (Redheads) allowable harvest per day, whereas conservative harvest regulations were either a bag limit of one individual per day or total closure. Harvest Composition – Data describing the age and sex structure of the harvested Canvasback and Redhead populations were derived from the annual Parts Collection surveys conducted by the U.S. Fish and Wildlife Service (USFWS) where a subset of hunters submit a wing from every duck they harvested (Pearse et al. 2014). These data were acquired through a direct request to the U.S. Fish and Wildlife Service. Additionally, estimates of the total number of Canvasbacks and Redheads harvested in the United States and Canada were derived from the Harvest Information Program (Steeg et al., 2002) and Canadian National Harvest Survey (Smith et al., 2022), respectively. Breeding Duck and Pond Densities – The relative number of breeding Canvasbacks and Redheads, as well as the relative amount of their breeding habitat (i.e., flooded ponds) within the Prairies were calculated using count data from the USFWS Waterfowl Breeding Population and Habitat Survey (hereafter BPOP; Smith, 1995), which has conducted an annual survey of breeding waterfowl and their habitats throughout the core part of these species’ breeding ranges (i.e., central Canada and the north-central United States) during the spring from 1961 through 2022 (U.S. Fish and Wildlife Service, 2022). However, BPOP surveys did not occur during 2020 and 2021. For the purposes of this study, we limited the spatial extent of BPOP survey to only include transects flown within Alberta, Manitoba, Saskatchewan, Montana, North Dakota, and South Dakota. Agriculture Development – The amounts of active cropland in the Prairies during each year of the study were estimated from Canada and United States Agriculture Census data (see Buderman et al., 2020). Annual estimates of active cropland acreages were summarized to represent an index of agricultural development during 1961–2021. Although agricultural development is predicted to have greater impact on upland-nesting dabbling ducks (Duncan and Devries 2018), it also impacts the wetland habitats in which Canvasbacks and Redheads forage and nest, as well as the predator communities that can access overwater nesting pochards (Sargeant et al. 1993, Bartzen et al. 2010). Winter Habitat – Winter habitat conditions were assumed to be related to submerged aquatic vegetation (SAV) within the Chesapeake for Canvasbacks and environmental salinity (TDS; total dissolved solids) in the Laguna Madre for Redheads. Although Redheads likely respond to variation in SAV, time series data describing SAV were not available for the Laguna Madre. Therefore, we assumed that annual fluctuations in salinity were an informative proxy of both SAV conditions and osmotic constraints (Quammen and Onuf 1993, Moore 2009), which in turn was representative of winter habitat conditions that simultaneously influenced Redhead food availability and harvest risk (Ballard et al. 2021).. Climate Data – We used the average Pacific/North American (PNA; Leathers et al., 1991) teleconnection pattern from April–July as an index of drought severity or environmental stress during the breeding season throughout the Prairies, and average sea-surface temperatures (SST) from September–March in the Chesapeake and Laguna Madre as an index of winter severity for Canvasbacks and Redheads, respectively (see Data Availability statement).

Snapshot img

Hunting Apparel Market Size 2025-2029

The hunting apparel market size is forecast to increase by USD 265.8 million at a CAGR of 3.5% between 2024 and 2029.

The market is experiencing significant growth, driven by key trends such as product innovation and product line extension, which contribute to the premiumization of hunting gear. These advancements cater to the increasing demand for smart clothing. 
Additionally, the growing number of hunting license holders fuels market expansion. Specialty hunting stores cater to this market, offering a diverse selection of jackets, pants, and other apparel designed for specific hunting seasons and climates, with the added convenience of e-commerce that allows customers to browse and purchase gear online from anywhere However, regulations on hunting and hunting bans in certain regions pose challenges to market growth. 
Adherence to these regulations is crucial for market players to maintain their market position and ensure ethical and sustainable hunting practices. The market is expected to continue its growth trajectory, with a focus on providing functional, comfortable, and stylish clothing for hunters.

What will be the Size of the Hunting Apparel Market During the Forecast Period?

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The market encompasses a wide range of clothing designed for hunters to blend into their natural environment while ensuring protection and comfort. Key product categories include camouflaged jackets, pants, gloves, and other accessories. Camouflage patterns, derived from foliage and climate, are essential for concealment. Hunters prioritize durability, weather resistance, and quiet fabrics to withstand various conditions. Insulation, moisture-wicking fabrics, and scent control technologies are crucial for maintaining body temperature and minimizing detection by game animals. Ethically sourced materials and recycled fabrics are gaining popularity among environmentally-conscious hunters. Layering systems enable hunters to adapt to changing temperatures and moisture levels during their hunt.

How is the Hunting Apparel Industry segmented and which is the largest segment?

The industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Distribution Channel

  Offline
  Online


Type

  Top wear
  Bottom wear
  Footwear
  Others


End-user

  Men
  Women


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK
    France
    Italy
    Spain


  APAC

    China
    India
    Japan


  South America



  Middle East and Africa

By Distribution Channel Insights

The offline segment is estimated to witness significant growth during the forecast period. The market experienced significant growth in 2024, with specialty stores accounting for the largest market share in offline distribution. The popularity of hunting apparel and accessories has led to an increase in the number of specialty retail stores. These stores offer a wide selection of brands and product portfolios, setting them apart from department stores. Companies are investing in marketing, advertising, promotions, brand building, training, and IT support to differentiate themselves. Exclusive designer collections and private-label brands provide a competitive edge. Hunters prioritize functionality, durability, and weather resistance in their apparel choices, including jackets, pants, gloves, and moisture-wicking fabrics.
Camouflage patterns, scent control technologies, and layering systems cater to varying temperatures, moisture levels, and hunting conditions. Consumer preferences for ethically sourced and recycled materials, as well as compliance with regulations, are also influencing market trends. Online platforms and retail networks expand hunting apparel accessibility, with a global presence and brand recognition driving consumer trust and loyalty.

Get a glance at the market report of share of various segments Request Free Sample

The Offline segment was valued at USD 948.00 million in 2019 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 45% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period. The North American market is dominated by the United States and Canada, driven by the large hunter population in these countries. Trophy hunting, a recreational activity, is popular among North American hunters, leading them to travel to destinations such as Canada, Mexico, and Africa.

For more insights on the market size of various regions, Request Free Sample

Hunting apparel is essential for hunters to bl

The data set contains concentration, load, and daily discharge data for Devils Icebox Cave and Hunters Cave from 1999 to 2002. The data are available in Microsoft Excel 2010 format. Sheet 1 (Cave Streams Metadata) contains supporting information regarding the length of record, site locations, parameters measured, parameter units, method detection limits, describes the meaning of zero and blank cells, and briefly describes unit area load computations. Sheet 2 (Devils Icebox Concentration Data) contains concentration data from all samples collected from 1999 to 2002 at the Devils Icebox site for 12 analytes and two computed nutrient parameters. Sheet 3 (Devils Icebox SS Conc Data) contains 15-minute suspended sediment (SS) concentrations estimated from turbidity sensor data for the Devils Icebox site. Sheet 4 (Devils Icebox Load & Discharge Data) contains daily data for discharge, load, and unit area loads for the Devils Icebox site. Sheet 5 (Hunters Cave Concentration Data) contains concentration data from all samples collected from 1999 to 2002 at the Hunters Cave site for 12 analytes and two computed nutrient parameters. Sheet 6 (Hunters Cave SS Conc Data) contains 15-minute SS concentrations estimated from turbidity sensor data for the Hunters Cave site. Sheet 7 (Hunters Cave Load & Discharge Data) contains daily data for discharge, load, and unit area loads for the Hunters Cave site.

     Atrazine concentrations in Goodwater Creek Experimental
             Watershed (GCEW) were shown to be among the very highest of any watershed in the United States based on comparisons using
             the national Watershed Regressions for Pesticides (WARP) model and by direct comparison with the 112 watersheds used in the
             development of WARP. The herbicide data collected in GCEW are documented at plot, field, and watershed scales. This 20-yr-long
             (1991-2010) effort was augmented with a spatially broad effort within the Central Mississippi River Basin encompassing 12
             related claypan watersheds in the Salt River Basin, two cave streams on the fringe of the Central Claypan Areas in the Bonne
             Femme watershed, and 95 streams in northern Missouri and southern Iowa. The research effort on herbicide transport has highlighted
             the importance of restrictive soil layers with smectitic mineralogy to the risk of transport vulnerability. Near-surface soil
             features, such as claypans and argillic horizons, result in greater herbicide transport than soils with high saturated hydraulic
             conductivities and low smectitic clay content.

This dataset provides daily and annual air temperature, river water level, and leaf drop dates coincident with the moose (Alces alces) hunting season (September) for the area surrounding the rural communities of Nulato, Koyukuk, Kaltag, Galena, Ruby, Huslia, and Hughes in interior Alaska, USA, over the period 2000-2016. The main objective of the study was to assess how the environmental conditions impacted the success of hunters who rely on moose as a subsistence resource.

High white-tailed deer abundance in the United States represents an ecological and human health threat. Reducing deer populations by lethal means and facilitating return of large predators are two potential, but controversial, management options. We used an online questionnaire to measure perspectives on deer management and predator return among a stratified sample of New York State residents. We found widespread acceptance (>70%) for reducing deer populations using lethal means if doing so would reduce Lyme disease, increase forest regeneration, protect native plants and animals, and improve road safety. Acceptance for shooting more deer was unaffected by ethnicity but strongest among respondents who were older, identified as hunters or conservationists, owned more land, and considered health and safety while answering our questionnaire. Respondents who identified as animal protectionists were least accepting. Restoring regionally extirpated wolves and cougars had limited acceptance (< 30%) but was strongest among those who identified as hunters or conservationists. Contrary to commonly held beliefs, preferences for deer management or predator restoration did not differ among urban and rural respondents. This common ground needs to be reflected in deer management in the state due to legal obligations to represent interests of all residents. Methods This dataset contains data from an online questionnaire we used to assess perspectives of New York State residents on deer management and potential return of large predators. Qualtrics LLC (www.qualtrics.com) recruited 1,206 adults (aged 18 or older) living in New York State who answered our questionnaire from 6 - 28 June 2022. To reduce sampling error and increase external validity, we stratified our sample to approximate the population of New York State in terms of age, ethnicity, and gender identity according to the most recent American Community Survey statistics (U.S. Census Bureau, 2020). We oversampled from rural areas to permit more powerful rural-urban comparisons. Respondents reported beliefs about who should participate in deer management; how acceptable it would be for people who shoot deer to use meat and other parts in various ways; how acceptable it would be for land managers to allow shooting more deer if doing so would help achieve various ecological and socioeconomic objectives; and how acceptable if would be for wolves and cougars to return to New York, either by natural recolonization or deliberate reintroduction, in order to help manage deer. We recorded responses using seven-point Likert-type items with the additional option of “I don’t know”. Individuals indicated relevance of ethical concerns when responding to previous blocks using four-point ordinal scales. Respondents described their perceptions and experiences with deer using a combination of ordinal and seven-point Likert scales. Respondents provided additional demographic and social identity information. To discover potential distinguishing characteristics of individuals who perceived shooting more deer generally to be more or less acceptable, we created a composite score of their responses to 11 items on deer management. We first converted the seven-point Likert scale to a numerical scale (strongly disagree = 1, disagree = 2, somewhat disagree = 3, neither agree nor disagree = 4, somewhat agree = 5, agree = 6, strongly agree = 7), and calculated the mean of these values across items for each respondent, excluding “I don’t know” responses. Following this method, we also created composite scores for responses to questions on whether wolves and cougars should be allowed to return or be reintroduced, and whether respondents would welcome them to their local area. The composite deer and predator scores served as our response variables in analyses, with respondents' answers to other survey questions as the predictor variables.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Hunters Hollow, KY, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 24,513, while the mean income for the highest quintile (20% of households with the highest income) is 134,615. This indicates that the top earners earn 5 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 146,806, which is 109.06% higher compared to the highest quintile, and 598.89% higher compared to the lowest quintile.

Content

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

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

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 Hunters Hollow median household income. You can refer the same here

The world is filled with nature watchers, from trampers to hunters, birders to beach-combers, and pros to school kids. Many of us keep notes of what we find. What if all those observations could be shared online? You might learn about the butterflies that live in your neighbourhood, or discover someone who knows all about the plants in your favourite reserve. For a long time, everyone's notes have been scattered in notebooks, private spreadsheets and dusty library shelves. As a society, we have seen a lot but collectively we remain blind to most changes in our biodiversity. If enough people record their observations on NatureWatch NZ, we can change all this. We can build a living record of life in New Zealand that scientists and environmental managers can use to monitor changes in biodiversity, and that anyone can use to learn more about New Zealand's amazing natural history. Only "research-quality" observations are used in this data set - that is observations that have their species identification peer-reviewed by at least one independent source. All biodiversity observations are available at http://naturewatch.org.nz/. NatureWatch NZ is run by the New Zealand Bio-Recording Network Trust, a charitable trust dedicated to bio-recording. Our lofty aims are: (1) To increase knowledge, understanding, and appreciation of New Zealand's natural history.(2) To engage and assist New Zealanders in observing and recording biological information.(3)To develop and support online tools to assist individuals and groups to record, view, share and use biological information. (4) To collaborate with people and groups interested in bio-recording. (5) To promote and provide secure, open, and ethical sources of biological information for the public.

About this dataset

Context

The dataset tabulates the Hunters Creek Village population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Hunters Creek Village. The dataset can be utilized to understand the population distribution of Hunters Creek Village by age. For example, using this dataset, we can identify the largest age group in Hunters Creek Village.

Key observations

The largest age group in Hunters Creek Village, TX was for the group of age 45 to 49 years years with a population of 532 (12.21%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Hunters Creek Village, TX was the 85 years and over years with a population of 35 (0.80%). 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

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Hunters Creek Village is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Hunters Creek Village 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 Hunters Creek Village Population by Age. You can refer the same here

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Hunters Hollow. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Hunters Hollow. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2022

In terms of income distribution across age cohorts, in Hunters Hollow, the median household income stands at $76,792 for householders within the 25 to 44 years age group, followed by $74,189 for the 45 to 64 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $56,835.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific 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 Hunters Hollow median household income by age. You can refer the same here

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Hunters Hollow: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 4(3.10%) households where the householder is under 25 years old, 61(47.29%) households with a householder aged between 25 and 44 years, 43(33.33%) households with a householder aged between 45 and 64 years, and 21(16.28%) households where the householder is over 65 years old.
• In Hunters Hollow, the age group of 25 to 44 years stands out with both the highest median income and the maximum share of households. This alignment suggests a financially stable demographic, indicating an established community with stable careers and higher incomes.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Hunters Hollow median household income by age. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Hunters Hollow by race. It includes the population of Hunters Hollow across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Hunters Hollow across relevant racial categories.

Key observations

The percent distribution of Hunters Hollow population by race (across all racial categories recognized by the U.S. Census Bureau): 88.99% are white, 2.14% are some other race and 8.87% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Hunters Hollow
• Population: The population of the racial category (excluding ethnicity) in the Hunters Hollow is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Hunters Hollow 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 Hunters Hollow Population by Race & Ethnicity. You can refer the same here