File List e001_arssnlvl0.csv (MD5: 75f21b9949b87c018f3499b5d2a093e7) e001_arssnlvl3.csv (MD5: 02cefd1cdb16fc25968f4e7d96a43378) e026_aslit.csv (MD5: eea09f91f81dc7e5801d8f67ccded5c1) e054_arssprecip.csv (MD5: 1d62c9ab92a6a1fc4caa53787d2c0cf1) e120_bmins.csv (MD5: e8699cfd2d2c9a11d43abd572b6f3cd8) e120_invnit1_2.csv (MD5: 6c023c438eb4c6e2625f526fafd9c17d) e120_invnit4_8.csv (MD5: a304786a833b5c6e53063472b97ef93d) e120_invnit16.csv (MD5: bda824cec8f8fdc2992c8732e03aa109) e120_nitbm.csv (MD5: 212637b7ab08d0cc2146f26602061b64) find_number_of_observations.R (MD5: a6a097d6633ee66b9c3531676320b929) multispatialCCM.zip (MD5: 64647cc7d14d2df5398a76af9ec73e2a)

  Description
    e001_arssnlvl0.csv is a comma-separated text file containing the data for Agroypron (Elymus) repens and Schizachyrium scoparium dynamics in unfertilized plots for experiment 001 at Cedar Creek. Column definitions are:


     1."index": concatenated text including the plot, field, and year sampled
     2. "Exp": Cedar Creek experiment number
     3. "Year": year data was sampled
     4. "Field": ID for field that was sampled
     5. "Plot": plot number for sample
     6. "Ntrt": categorical fertilization treatment
     7. "Nadd": g nitrogen added per square meter per year for each treatment
     8. "NitrAdd": g nitrate added per square meter per year for each treatment
     9. "Natm.Nadd": g nitrogen added per square meter per year for each treatment, including 1 g/m2/year atmospheric deposition
     10. "fg": plant functional group: C3/C4 for grasses with C3/C4 photosynthetic pathway, F for non-legume forb, L for legume.
     11. "isspecies": Binary indicator describing whether or not a row had plant species found in it that year (should be 1 for all rows)
     12. "richness": Species richness for all species found in the sample
     13. "Agropyron repens": g dry aboveground biomass per meter square of A. repens
     14. "Schizachyrium scoparium": g dry aboveground biomass per meter square of S. scoparium
     15. "Miscellaneous litter": g dry aboveground biomass per meter square of leaf litter
     16. "Ncat": Fertilization intensity category, with 1 being the lowest and 3 being the highest
     17. "FieldPlot": concatenated text including the field and plot

    e001_arssnlvl3.csv is a comma-separated text file containing the data for Agroypron (Elymus) repens and Schizachyrium scoparium dynamics in heavily plots for experiment 001 at Cedar Creek. Column definitions are as described for e001_arssnlvl0.csv.
    e026_aslit.csv is a comma-separated text file containing the data for Agrostic scabra and leaf litter dynamics in plots with varying soil fertility in experiment 026 at Cedar Creek. Column definitions are:

     1. "monoculture": plant species grown in subplot (should always be A. scabra)
     2. "litbiomass": g dry aboveground biomass per meter square of leaf litter
     3. "year": year of sampling
     4. "plot": plot sampled (soil N treatments vary among plots)
     5. "subplot": subplot sampled
     6. "abvbiomass": g dry aboveground biomass per meter square of A. scabra
     7. "totaln": total soil nitrogen (in percent of soil by mass)
     8. "exp": Cedar Creek experiment number
     9. "yearest": year in which the experiment was established
     10. "nlevel": categorical level for total soil nitrogen treatment
     11. "plotsubplot": concatenated text including the plot and subplot
     12. "Field": ID for field that was sampled
     13. "FieldPlot": concatenated text including the field and plot

    e054_arssprecip.csv is a comma-separated text file containing the data for A. repens, S. scoparium, leaf litter, and precipitation dynamics for experiment 054 at Cedar Creek. Column definitions are:

     1. "index": concatenated text including the year, field, plot, transect sampled
     2. "Exp": experiment number
     3. "Year": year of sample
     4. "OldField": old field ID
     5. "Plot": plot number for sample
     6. "Transect": transect ID
     7. "YearAb": Year that the field was abandoned from agricultural use
     8. "Agropyron repens": g dry aboveground biomass per meter square of A. repens
     9. "Schizachyrium scoparium": g dry aboveground biomass per meter square of S. scoparium
     10: "Miscellaneous litter": g dry aboveground biomass per meter square of leaf litter
     11: "precipmm": total summer annual precipitation (June-August) in mm
     12: "FieldPlot": concatenated text including the field and plot

    e120_bmins.csv is a comma-separated text file describing plant biomass and insect dynamics for Cedar Creek experiment 120. Column definitions are:

     1. "Exp": Cedar Creek experiment number
     2. "Year": sampling year
     3. "Month": sampling month
     4. "Plot": plot sampled
     5. "NumSp": number of species in treatment
     6. "SpNum": number of species maintained in plot
     7. "AbvBioAnnProd": g plant aboveground biomass harvested per square meter per year
     8. "noh020tot": mg soil nitrate per kg soil, sampled in top 20 cm of soil
     9. "insectcount": number of insect individuals in sweep net sample
     10. "insectsp": number of insect species in sweep net sample
     11. "Field": field ID
     12. "FieldPlot": concatenated text including the field and plot

    e120_invnit1_2.csv is a comma-separated text file describing invading plant species dynamics and soil nitrate dynamics in monoculture plots for experiment 120 at Cedar Creek. Column definitions are as described for e120_bmins.csv, except for:

     9. “invrichness”: number of non-planted “invading” plant species


    e120_invnit4_8.csv is a comma-separated text file describing invading plant species dynamics and soil nitrate dynamics in 4 and 8 species mixture plots for experiment 120 at Cedar Creek. Column definitions are as described for e120_invnit1_2.csv.

    e120_invnit16.csv is a comma-separated text file describing invading plant species dynamics and soil nitrate dynamics in 16 species mixture plots for experiment 120 at Cedar Creek. Column definitions are as described for e120_invnit1_2.csv.

    e120_nitbm.csv is a comma-separated text file describing soil nitrate and aboveground plant biomass dynamics. Column definitions are as described for e120_bmins.csv.

    find_number_of_observations.R is an R source code file that can be used to determine the number of sequential observations in subplots for all of the data sets listed above. The data should be in the working directory of R when the R code is run.

    multispatialCCM.zip...

Dataset Overview

This dataset provides a comprehensive overview of Brazil’s 2022 Census data, focusing on São Paulo’s neighbourhoods. The data combines demographic and socioeconomic information with geospatial shapefiles of São Paulo’s neighbourhoods, enabling users to perform statistical and spatial analyses.

Users can explore patterns, trends, and transformations in São Paulo’s urban landscape by linking census sectors to neighbourhood boundaries.

Key Components

Census 2022 Data

• Source: Brazil's 2022 Census (IBGE)
• Content: Demographic data including age, gender, income, education levels, household size, and population density across census sectors.
• Format: CSV

São Paulo Neighborhood Shapefile

• Source: GIS-based shapefiles for São Paulo neighbourhoods (IBGE Census Sectors and Manually created Neighbourhoods)
• Content: Spatial geometry for São Paulo's neighbourhoods with census sector identifiers.
• Format: Parquet

Use Cases

• Neighborhood Demographics Analysis: Combine census data with shapefiles to generate neighborhood-level demographic reports.
• Urban Development Studies: Study how São Paulo neighbourhoods have grown using historical context and 2022 Census data.
• Spatial Data Visualizations: Create maps showing income distribution, population density, or other demographic factors across neighbourhoods.
• Policy Planning & Research: Support urban planning, resource allocation, and policy development in São Paulo.

Potential Applications

• Analyze the relationship between neighbourhood demographics and urban growth patterns.
• Visualize inequalities in population distribution, income, or education levels.
• Identify trends in housing and population density for urban studies.
• Provide insights into São Paulo’s historical and ongoing transformations.

Why Use This Dataset?

• Comprehensive Coverage: Detailed census data and spatial boundaries allow in-depth analyses.
• Flexible Integration: Easily combine demographic data with shapefiles to enable advanced spatial analyses.

Dataset Details

• File Formats: CSV (Census Data), GeoJSON/Shapefile (Neighborhood Shapefiles)
• Spatial Resolution: Census sector linked to São Paulo’s neighbourhood boundaries

Geographic Scope: São Paulo, Brazil

This dataset is ideal for data scientists, urban planners, and researchers seeking to uncover the dynamics of São Paulo’s neighbourhoods through an intersection of demographic and spatial data.

Contribute to new insights and empower decision-making in understanding Brazil’s largest city!

Data and data sources for the CouSCOUS project.

Geographic Information System (GIS) analyses are an essential part of natural resource management and research. Calculating and summarizing data within intersecting GIS layers is common practice for analysts and researchers. However, the various tools and steps required to complete this process are slow and tedious, requiring many tools iterating over hundreds, or even thousands of datasets. USGS scientists will combine a series of ArcGIS geoprocessing capabilities with custom scripts to create tools that will calculate, summarize, and organize large amounts of data that can span many temporal and spatial scales with minimal user input. The tools work with polygons, lines, points, and rasters to calculate relevant summary data and combine them into a single output table that can be easily incorporated into statistical analyses. These tools are useful for anyone interested in using an automated script to quickly compile summary information within all areas of interest in a GIS dataset