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.

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.

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.

Household data are collected as of March.

As stated in the Census's "Source and Accuracy of Estimates for Income, Poverty, and Health Insurance Coverage in the United States: 2011" (http://www.census.gov/hhes/www/p60_243sa.pdf):

Estimation of Median Incomes. The Census Bureau has changed the methodology for computing median income over time. The Census Bureau has computed medians using either Pareto interpolation or linear interpolation. Currently, we are using linear interpolation to estimate all medians. Pareto interpolation assumes a decreasing density of population within an income interval, whereas linear interpolation assumes a constant density of population within an income interval. The Census Bureau calculated estimates of median income and associated standard errors for 1979 through 1987 using Pareto interpolation if the estimate was larger than $20,000 for people or $40,000 for families and households. This is because the width of the income interval containing the estimate is greater than $2,500.

We calculated estimates of median income and associated standard errors for 1976, 1977, and 1978 using Pareto interpolation if the estimate was larger than $12,000 for people or $18,000 for families and households. This is because the width of the income interval containing the estimate is greater than $1,000. All other estimates of median income and associated standard errors for 1976 through 2011 (2012 ASEC) and almost all of the estimates of median income and associated standard errors for 1975 and earlier were calculated using linear interpolation.

Thus, use caution when comparing median incomes above $12,000 for people or $18,000 for families and households for different years. Median incomes below those levels are more comparable from year to year since they have always been calculated using linear interpolation. For an indication of the comparability of medians calculated using Pareto interpolation with medians calculated using linear interpolation, see Series P-60, Number 114, Money Income in 1976 of Families and Persons in the United States (www2.census.gov/prod2/popscan/p60-114.pdf).

The Heat Vulnerability Index (HVI) layer is hosted by the WI Department of Health Services which employs a color gradient to signify varying levels of heat vulnerability across different geographic regions of WI. This layer incorporates critical data layers, including population density, age demographics, existing health conditions, and access to cooling resources, to create a multifaceted view of risk factors. This data serves as a vital tool for public health officials to assess where interventions are most needed during extreme heat events. By highlighting areas with heightened vulnerability, stakeholders can implement targeted outreach and preparation efforts. Additionally, the HVI layer can assist in strategic planning for future urban development and climate resilience initiatives.This copy of this layer was updated on February 12, 2024. Link to data source for download: https://data.dhsgis.wi.gov/datasets/wi-dhs::wisconsin-heat-vulnerability-index/explore

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.

The 2015 cartographic boundary shapefiles 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.

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.

description: This shapefile contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of Wisconsin. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of Wisconsin. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative of conditions in the past 10 years, and (4) of sufficient spatial resolution that they could be used to make valid comparisons among local catchment units. In this data set, these variables are linked to the catchments of the National Hydrography Dataset Plus Version 1 (NHDPlusV1) using the COMID identifier. They can also be linked to the reaches of the NHDPlusV1 using the COMID identifier. Catchment attributes are available for both local catchments (defined as the land area draining directly to a reach; attributes begin with "L_" prefix) and network catchments (defined by all upstream contributing catchments to the reach's outlet, including the reach's own local catchment; attributes begin with "N_" prefix). This shapefile also includes habitat condition scores created based on responsiveness of biological metrics to anthropogenic landscape disturbances throughout ecoregions. Separate scores were created by considering disturbances within local catchments, network catchments, and a cumulative score that accounted for the most limiting disturbance operating on a given biological metric in either local or network catchments. This assessment only scored reaches representing streams and rivers (see the process section for more details). Please use the following citation: Esselman, P., D.M. Infante, L. Wang, W. Taylor, W. Daniel, R. Tingley, J. Fenner, A. Cooper, D. Wieferich, D. Thornbrugh and J. Ross. (April 2011) National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Wisconsin. National Fish Habitat Partnership Data System. http://dx.doi.org/doi:10.5066/F70C4SSR:; abstract: This shapefile contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of Wisconsin. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of Wisconsin. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative of conditions in the past 10 years, and (4) of sufficient spatial resolution that they could be used to make valid comparisons among local catchment units. In this data set, these variables are linked to the catchments of the National Hydrography Dataset Plus Version 1 (NHDPlusV1) using the COMID identifier. They can also be linked to the reaches of the NHDPlusV1 using the COMID identifier. Catchment attributes are available for both local catchments (defined as the land area draining directly to a reach; attributes begin with "L_" prefix) and network catchments (defined by all upstream contributing catchments to the reach's outlet, including the reach's own local catchment; attributes begin with "N_" prefix). This shapefile also includes habitat condition scores created based on responsiveness of biological metrics to anthropogenic landscape disturbances throughout ecoregions. Separate scores were created by considering disturbances within local catchments, network catchments, and a cumulative score that accounted for the most limiting disturbance operating on a given biological metric in either local or network catchments. This assessment only scored reaches representing streams and rivers (see the process section for more details). Please use the following citation: Esselman, P., D.M. Infante, L. Wang, W. Taylor, W. Daniel, R. Tingley, J. Fenner, A. Cooper, D. Wieferich, D. Thornbrugh and J. Ross. (April 2011) National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Wisconsin. National Fish Habitat Partnership Data System. http://dx.doi.org/doi:10.5066/F70C4SSR:

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.

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

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.

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.

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.

The Little Rock Acidification Experiment was a joint project involving the USEPA (Duluth Lab), University of Minnesota-Twin Cities, University of Wisconsin-Superior, University of Wisconsin-Madison, and the Wisconsin Department of Natural Resources. Little Rock Lake is a bi-lobed lake in Vilas County, Wisconsin, USA. In 1983 the lake was divided in half by an impermeable curtain and from 1984-1989 the northern basin of the lake was acidified with sulfuric acid in three two-year stages. The target pHs for 1984-5, 1986-7, and 1988-9 were 5.7, 5.2, and 4.7, respectively. Starting in 1990 the lake was allowed to recover naturally with the curtain still in place. Data were collected through 2000. The main objective was to understand the population, community, and ecosystem responses to whole-lake acidification. Funding for this project was provided by the USEPA and NSF. Zooplankton samples are collected from the treatment and reference basins of Little Rock Lake at at two to nine depths using a 30L Schindler Patalas trap (53um mesh). Zooplankton samples are preserved in buffered formalin and archived. Data are summed over sex and stage and integrated volumetrically over the water column to provide a lake-wide estimate of organisms per liter for each species. Sampling Frequency: varies - Number of sites: 2

Marine bird land sighting and other data were collected from platforms from Pribilof Island from 23 June 1975 to 11 August 1975. Data were collected by the University of Wisconsin - Madison as part of the Outer Continental Shelf Environmental Assessment Program (OCSEAP). Data were processed by NODC to the NODC standard F034 Marine Bird Land format. Full format description is available from NODC at www.nodc.noaa.gov/. An analog file for this accession is available from NODC user services.

The F034 format contains data from field observations of marine birds made along land survey tracks. These data are collected to provide information on population density and distribution and breeding locales. The contents and structure of data type file are similar to Marine Bird Sighting, Aircraft Census (F033), although the transect distance of land surveys will normally be shorter than that of ship and aircraft surveys. In this data type the investigator defines the lateral dimension of survey distance unit (a specified number of whole meters). Start and end position, date and elapsed time, and number of distance units are reported for each survey. Environmental information may include meteorological and adjacent sea surface conditions, distance to nearest shoreline, ice characteristics, and debris, including oil slicks. Species data may include age, sex, color, plumage, number of individuals, flight direction, behavior, and food source association. Any number of species may be reported within one observation time span.

Marine bird sighting and other data were collected from a platform in the Bering Sea from 06 May 1976 to 19 August 1976. Data were collected by the University of Wisconsin as part of the Outer Continental Shelf Environmental Assessment Program (OCSEAP). Data were processed by NODC to the NODC standard F034 Marine Bird Land format. Full format description is available from NODC at www.nodc.noaa.gov/. An analog file for this accession is available from NODC user services.

The F034 format contains data from field observations of marine birds made along land survey tracks. These data are collected to provide information on population density and distribution and breeding locales. The contents and structure of data type file are similar to Marine Bird Sighting, Aircraft Census (F033), although the transect distance of land surveys will normally be shorter than that of ship and aircraft surveys. In this data type the investigator defines the lateral dimension of survey distance unit (a specified number of whole meters). Start and end position, date and elapsed time, and number of distance units are reported for each survey. Environmental information may include meteorological and adjacent sea surface conditions, distance to nearest shoreline, ice characteristics, and debris, including oil slicks. Species data may include age, sex, color, plumage, number of individuals, flight direction, behavior, and food source association. Any number of species may be reported within one observation time span.