14 datasets found
  1. TIGER/Line Shapefile, 2022, State, Wisconsin, WI, Census Tract

    • catalog.data.gov
    Updated Jan 27, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, State, Wisconsin, WI, Census Tract [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-state-wisconsin-wi-census-tract
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    Dataset updated
    Jan 27, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Wisconsin
    Description

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

  2. Data from: North Temperate Lakes site, station Oneida County, WI (FIPS...

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    • portal.edirepository.org
    Updated Mar 11, 2015
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    Inter-University Consortium for Political and Social Research; Michael R. Haines; Nichole Rosamilia; Christopher Boone; Ted Gragson; U.S. Bureau of the Census; EcoTrends Project (2015). North Temperate Lakes site, station Oneida County, WI (FIPS 55085), study of human population density in units of numberPerKilometerSquared on a yearly timescale [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fecotrends%2F11116%2F2
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    Dataset updated
    Mar 11, 2015
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    Inter-University Consortium for Political and Social Research; Michael R. Haines; Nichole Rosamilia; Christopher Boone; Ted Gragson; U.S. Bureau of the Census; EcoTrends Project
    Time period covered
    Jan 1, 1900 - Jan 1, 2000
    Area covered
    Variables measured
    YEAR, S_DEV, S_ERR, ID_OBS, N_TRACE, N_INVALID, N_MISSING, N_EXPECTED, N_OBSERVED, N_ESTIMATED, and 3 more
    Description

    The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from North Temperate Lakes (NTL) contains human population density measurements in numberPerKilometerSquared units and were aggregated to a yearly timescale.

  3. North Temperate Lakes site, station Oneida County, WI (FIPS 55085), study of...

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    Updated Mar 11, 2015
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    Christopher Boone; Inter-University Consortium for Political and Social Research; U.S. Bureau of the Census; Ted Gragson; Michael R. Haines; Nichole Rosamilia; EcoTrends Project (2015). North Temperate Lakes site, station Oneida County, WI (FIPS 55085), study of percent urban population in units of percent on a yearly timescale [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fecotrends%2F11115%2F2
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    Dataset updated
    Mar 11, 2015
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    Christopher Boone; Inter-University Consortium for Political and Social Research; U.S. Bureau of the Census; Ted Gragson; Michael R. Haines; Nichole Rosamilia; EcoTrends Project
    Time period covered
    Jan 1, 1890 - Jan 1, 2000
    Area covered
    Variables measured
    YEAR, S_DEV, S_ERR, ID_OBS, N_TRACE, N_INVALID, N_MISSING, N_EXPECTED, N_OBSERVED, N_ESTIMATED, and 3 more
    Description

    The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from North Temperate Lakes (NTL) contains percent urban population measurements in percent units and were aggregated to a yearly timescale.

  4. d

    2015 Cartographic Boundary File, Urban Area-State-County for Wisconsin,...

    • catalog.data.gov
    Updated Jan 13, 2021
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    (2021). 2015 Cartographic Boundary File, Urban Area-State-County for Wisconsin, 1:500,000 [Dataset]. https://catalog.data.gov/dataset/2015-cartographic-boundary-file-urban-area-state-county-for-wisconsin-1-500000
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    Dataset updated
    Jan 13, 2021
    Area covered
    Wisconsin
    Description

    The 2015 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. The records in this file allow users to map the parts of Urban Areas that overlap a particular county. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the "urban footprint." There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The boundaries for counties and equivalent entities are as of January 1, 2010.

  5. Wisconsin Heat Vulnerability Index

    • data.dhsgis.wi.gov
    Updated Feb 12, 2024
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    Wisconsin Department of Health Services (2024). Wisconsin Heat Vulnerability Index [Dataset]. https://data.dhsgis.wi.gov/datasets/wisconsin-heat-vulnerability-index
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    Dataset updated
    Feb 12, 2024
    Dataset authored and provided by
    Wisconsin Department of Health Serviceshttp://dhs.wisconsin.gov/
    Area covered
    Description

    The Wisconsin Heat Vulnerability Index (HVI) is based on multiple indicators associated with risk for heat related illness and mortality. The index analysis was created as a measure of vulnerability by U.S. Census block groups during an extreme heat-related event. The measure includes health factors, demographic and household characteristics, natural and built environment factors (e.g. air quality, temperature, land cover) and population density.

  6. d

    Atlas of the Biosphere

    • search.dataone.org
    Updated Nov 17, 2014
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    Olejniczak, Nicholas; Foley, Jonathan (2014). Atlas of the Biosphere [Dataset]. https://search.dataone.org/view/Atlas_of_the_Biosphere.xml
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    Dataset updated
    Nov 17, 2014
    Dataset provided by
    Regional and Global Biogeochemical Dynamics Data (RGD)
    Authors
    Olejniczak, Nicholas; Foley, Jonathan
    Time period covered
    Jan 1, 1995
    Area covered
    Earth
    Description

    The Atlas of the Biosphere is a product of the Center for Sustainability and the Global Environment (SAGE), part of the Gaylord Nelson Institute for Environmental Studies at the University of Wisconsin - Madison. The goal is to provide more information about the environment, and human interactions with the environment, than any other source.

    The Atlas provides maps of an ever-growing number of environmental variables, under the following categories:

    Human Impacts (Humans and the environment from a socio-economic perspective; i.e., Population, Life Expectancy, Literacy Rates);

    Land Use (How humans are using the land; i.e., Croplands, Pastures, Urban Lands);

    Ecosystems (The natural ecosystems of the world; i.e., Potential Vegetation, Temperature, Soil Texture); and

    Water Resources (Water in the biosphere; i.e., Runoff, Precipitation, Lakes and Wetlands).

    Map coverages are global and regional in spatial extent. Users can download map images (jpg) and data (a GIS grid of the data in ESRI ArcView Format), and can view metadata online.

  7. Data from: North Temperate Lakes site, station Dane County, WI (FIPS 55025),...

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    • portal.edirepository.org
    Updated Mar 11, 2015
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    Inter-University Consortium for Political and Social Research; U.S. Bureau of the Census; Ted Gragson; Christopher Boone; Michael R. Haines; Nichole Rosamilia; EcoTrends Project (2015). North Temperate Lakes site, station Dane County, WI (FIPS 55025), study of percent urban population in units of percent on a yearly timescale [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fecotrends%2F11086%2F2
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    Dataset updated
    Mar 11, 2015
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    Inter-University Consortium for Political and Social Research; U.S. Bureau of the Census; Ted Gragson; Christopher Boone; Michael R. Haines; Nichole Rosamilia; EcoTrends Project
    Time period covered
    Jan 1, 1840 - Jan 1, 2000
    Area covered
    Variables measured
    YEAR, S_DEV, S_ERR, ID_OBS, N_TRACE, N_INVALID, N_MISSING, N_EXPECTED, N_OBSERVED, N_ESTIMATED, and 3 more
    Description

    The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from North Temperate Lakes (NTL) contains percent urban population measurements in percent units and were aggregated to a yearly timescale.

  8. Data from: North Temperate Lakes site, station Vilas County, WI (FIPS...

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    • portal.edirepository.org
    Updated Mar 11, 2015
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    U.S. Bureau of the Census; Nichole Rosamilia; Michael R. Haines; Inter-University Consortium for Political and Social Research; Christopher Boone; Ted Gragson; EcoTrends Project (2015). North Temperate Lakes site, station Vilas County, WI (FIPS 55125), study of percent urban population in units of percent on a yearly timescale [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fecotrends%2F11126%2F2
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    Dataset updated
    Mar 11, 2015
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    U.S. Bureau of the Census; Nichole Rosamilia; Michael R. Haines; Inter-University Consortium for Political and Social Research; Christopher Boone; Ted Gragson; EcoTrends Project
    Time period covered
    Jan 1, 1900 - Jan 1, 2000
    Area covered
    Variables measured
    YEAR, S_DEV, S_ERR, ID_OBS, N_TRACE, N_INVALID, N_MISSING, N_EXPECTED, N_OBSERVED, N_ESTIMATED, and 3 more
    Description

    The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from North Temperate Lakes (NTL) contains percent urban population measurements in percent units and were aggregated to a yearly timescale.

  9. d

    Use of camera traps to understand Wisconsin mammal diel activity under...

    • datadryad.org
    • dataone.org
    zip
    Updated Sep 25, 2025
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    Annabelle Majerus; Laura Berman; Fabian Schneider; Ryan Pavlick; Jennifer Stenglein; Philip Townsend (2025). Use of camera traps to understand Wisconsin mammal diel activity under anthropogenic pressures [Dataset]. http://doi.org/10.5061/dryad.69p8cz9g9
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    zipAvailable download formats
    Dataset updated
    Sep 25, 2025
    Dataset provided by
    Dryad
    Authors
    Annabelle Majerus; Laura Berman; Fabian Schneider; Ryan Pavlick; Jennifer Stenglein; Philip Townsend
    Time period covered
    Aug 8, 2025
    Area covered
    Wisconsin
    Description

    This data uses Snapshot Wisconsin (Townsend et al. 2021) data and geospatial variables pertaining to nighttime light (NTL, Li et al. 2020), human population density (GPW, CIESIN 2018, Doxsey-Whitfield et al. 2015), access to cities (Weiss et al. 2018), impacting sound (Mennitt et al. 2013), and global human modification of terrestrial systems (GHM, Kennedy et al. 2019). The aim of using this data is to understand how anthropogenic variables influence mammal diel activity in Wisconsin, USA. This dataset contains the relevant information for the geospatial variables used as well as the camera trap data spatially matched to them.

  10. Data from: North Temperate Lakes site, station Iron County, WI (FIPS 55051),...

    • search.dataone.org
    • portal.edirepository.org
    Updated Mar 11, 2015
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    Inter-University Consortium for Political and Social Research; Ted Gragson; Michael R. Haines; Christopher Boone; Nichole Rosamilia; U.S. Bureau of the Census; EcoTrends Project (2015). North Temperate Lakes site, station Iron County, WI (FIPS 55051), study of percent urban population in units of percent on a yearly timescale [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fecotrends%2F11105%2F2
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    Dataset updated
    Mar 11, 2015
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    Inter-University Consortium for Political and Social Research; Ted Gragson; Michael R. Haines; Christopher Boone; Nichole Rosamilia; U.S. Bureau of the Census; EcoTrends Project
    Time period covered
    Jan 1, 1900 - Jan 1, 2000
    Area covered
    Variables measured
    YEAR, S_DEV, S_ERR, ID_OBS, N_TRACE, N_INVALID, N_MISSING, N_EXPECTED, N_OBSERVED, N_ESTIMATED, and 3 more
    Description

    The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from North Temperate Lakes (NTL) contains percent urban population measurements in percent units and were aggregated to a yearly timescale.

  11. Model selection results for fitted models ranked by AICc with number of...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 9, 2023
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    Clay M. Wilton; Emily E. Puckett; Jeff Beringer; Beth Gardner; Lori S. Eggert; Jerrold L. Belant (2023). Model selection results for fitted models ranked by AICc with number of parameters (K), log likelihood (LL), and AICc weights (wi) to estimate black bear density in south-central Missouri, USA, for extensive and intensive sampling designs. [Dataset]. http://doi.org/10.1371/journal.pone.0111257.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 9, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Clay M. Wilton; Emily E. Puckett; Jeff Beringer; Beth Gardner; Lori S. Eggert; Jerrold L. Belant
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States, Missouri
    Description

    We fitted models using the half-normal detection function with baseline capture probability (g0) and scale parameter (σ). Effects on g0 and σ included time as a factor (t), global learned response (b), snare-specific learned response (bk), and a snare-specific Markovian response (Bk), and sex. Parameters with “.” indicate no effect.Model selection results for fitted models ranked by AICc with number of parameters (K), log likelihood (LL), and AICc weights (wi) to estimate black bear density in south-central Missouri, USA, for extensive and intensive sampling designs.

  12. Data_Sheet_2_Architectural Response of Wheat Cultivars to Row Spacing...

    • frontiersin.figshare.com
    xlsx
    Updated Jun 1, 2023
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    Mariem Abichou; Benoit de Solan; Bruno Andrieu (2023). Data_Sheet_2_Architectural Response of Wheat Cultivars to Row Spacing Reveals Altered Perception of Plant Density.xlsx [Dataset]. http://doi.org/10.3389/fpls.2019.00999.s002
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    xlsxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Frontiers Mediahttp://www.frontiersin.org/
    Authors
    Mariem Abichou; Benoit de Solan; Bruno Andrieu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Achieving novel improvements in crop management may require changing interrow distance in cultivated fields. Such changes would benefit from a better understanding of plant responses to the spatial heterogeneity in their environment. Our work investigates the architectural plasticity of wheat plants in response to increasing row spacing and evaluates the hypothesis of a foraging behavior in response to neighboring plants. A field experiment was conducted with five commercial winter wheat cultivars possessing unique architectures, grown under narrow (NI, 17.5 cm) or wide interrows (WI, 35 cm) at the same population density (170 seeds/m2). We characterized the development (leaf emergence, tillering), the morphology (dimension of organs, leaf area index), and the geometry (ground cover, leaf angle, organ spreading, and orientation). All cultivars showed a lower number of emerged tillers in WI compared to NI, which was later partly compensated by lower tiller mortality. Besides, the upper leaf blades were larger in WI. Finally the leaf area index at flowering showed little difference between WI and NI treatments. The rate of leaf emergence and the final leaf number were higher in WI compared to NI, except for one cultivar. Around the start of stem elongation, pseudo-stems were more erect in WI, while around the time of flowering, stems were more inclined and leaves were more planophile. Cultivars differed in their degrees of responses, with one appearing to prospect more specifically within the interrow space in WI treatment. Altogether, our results suggest that altering interrow distance leads to changes in the perceived extent of competition by plants, with responses first mimicking the effect of a higher plant density and later the effect of a lower plant density. Only one cultivar showed responses that suggested a perception of the heterogeneity of the environment. These findings improve our understanding of plant responses to spatial heterogeneity and provide novel information to simulate light capture in plant 3D models, depending on cultivar behavior.

  13. f

    Appendix F. AICc differences (Δi) and AICc weights (wi) for three growth...

    • figshare.com
    • wiley.figshare.com
    html
    Updated May 31, 2023
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    Dennis L. Murray; Michael G. Anderson; Todd D. Steury (2023). Appendix F. AICc differences (Δi) and AICc weights (wi) for three growth models fit to population time series for 10 duck species. [Dataset]. http://doi.org/10.6084/m9.figshare.3544322.v1
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    htmlAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    Wiley
    Authors
    Dennis L. Murray; Michael G. Anderson; Todd D. Steury
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    AICc differences (Δi) and AICc weights (wi) for three growth models fit to population time series for 10 duck species.

  14. d

    Density-dependent declines of Wisconsin bats from white-nose syndrome

    • search.dataone.org
    • datadryad.org
    Updated Aug 21, 2025
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    Heather Kaarakka; Kate Langwig (2025). Density-dependent declines of Wisconsin bats from white-nose syndrome [Dataset]. http://doi.org/10.5061/dryad.zgmsbccp7
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    Dataset updated
    Aug 21, 2025
    Dataset provided by
    Dryad Digital Repository
    Authors
    Heather Kaarakka; Kate Langwig
    Description

    White-nose syndrome is a fungal infection that affects hibernating bats in North America. The disease caused signficant declines in multiple species of bats, including the once common little brown bat (Myotis lucifugus). Though density dependence These data and analyses , , , # Density-dependent declines of Wisconsin bats from white-nose syndrome

    https://doi.org/10.5061/dryad.zgmsbccp7

    Description of the data and file structure

    This dataset is comprised of colony counts of little brown bat summer roosts and winter hibernation sites in Wisconsin during the invasion of the bat fungal disease white-nose syndrome (WNS). These are the data used in the manuscript entitled Positive density-dependence promotes host persistence in the face of infectious disease. Bat colony counts from summer (summerdeclines_dataall_Nov2021.csv) and winter (midwest_density_dependence_analysesNEW.csv) sites were used to analyze population growth rates (lambda) during white-nose syndrome invasion in Wisconsin. Data were collected over 11 years from 2011-2021. The summer and winter datasets contain year of survey, population size during year of survey, population growth rate, years since WNS arrival for each site, and landscape and site-...,

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U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, State, Wisconsin, WI, Census Tract [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-state-wisconsin-wi-census-tract
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TIGER/Line Shapefile, 2022, State, Wisconsin, WI, Census Tract

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Dataset updated
Jan 27, 2024
Dataset provided by
United States Census Bureauhttp://census.gov/
Area covered
Wisconsin
Description

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

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