The data sets in this repository allow users to link people among the U.S. decennial censuses, using the "histid" identifier. The census data sets users will need are indexed by Ancestry.com and are hosted by IPUMS at https://usa.ipums.org/usa-action/samples. Users will need to download the full-count census for each year and be sure to select the "histid" variable that is available under the Person/Historical Technical drop-down menu.As of 7/12/21, links are available between the 1900-1910, 1910-1920, and 1900-1920 censuses.A detailed account of how these links are created and a description of the data and its characteristics are available in the following article:Price, J., Buckles, K., Van Leeuwen, J., & Riley, I. (2021). Combining family history and machine learning to link historical records: The Census Tree data set. Explorations in Economic History, 80, 101391.https://www.sciencedirect.com/science/article/pii/S0014498321000024

This dataset consists of data collected during the October 2021 census. A few trees were also measured in January 2022 as they could not be accessed in 2021. The data collection includes treeID, position, DBH_cm (girth in cm), observations, POM_cm (Point of measurement) status, census, date, family, genus and species. Botanical identification was done by Julien Engel (IRD). Trees were positioned using TLS scan by Olivier Martin. This tree census was funded by CNES (France).

The Barro Colorado Island Tree Reproduction Dataset can be found in BCITreeGrowthSurvival.csv, a csv text file containing the data records on seed production described above. The dataset contains the following labels (columns): spcode = species code family = taxonomic family species = latin species name tag = unique id for individual trees. Corresponds to metal tags attached to individual trees in each 4ha plot or the 50-ha FDP census (data DOI: 10.5479/data.bci.20130603). year = year in which lianas scores were recorded. census = referring to the plot, either Tow (towerplots) or Ing (referring to the census by Ingwell et al. 2010 in the 50 ha plot). dbh1,2 = diameter of tree in mm at 1.3 meters height or above buttresses at time point 1 (2005 for trees from the Ingwell et al. census in the 50-ha FDP see dataset, and 2003-2004 for Tower plot trees) and time point 2 (2010 for Ingwell et al. census and 2014 for the towerplots). liana = five-point scale for liana load in the first census with zero indicating a liana free tree and scores 1 - 4 indicating trees with 1-25%, 26-50%, 51-75% and 76-100% of the crown bearing lianas. status = status of the tree at the second measurement, scored as alive (A) or dead (D). References 1.Condit, R. (1998). Tropical Forest Census Plots. Springer-Verlag and R. G. Landes Company, Berlin, Germany, and Georgetown, Texas 2.Visser, M.D., Bruijning, M., Wright, S.J., Muller-Landau, H. C. Jongejans, E., Comita, L.S. & de Kroon, H. (2016). Functional traits as predictors of vital rates across the life-cycle of tropical trees. Funct. Ecol., 30, 168–180 3.Visser, M.D., Wright, S.J., Muller-Landau, H. C. Jongejans, E., Comita, L.S., de Kroon, H. & Schnitzer, S. (2017). Tree species vary widely in their tolerance for liana infestation: a case study of differential host response to generalist parasites. J. Ecol., in press 4.Wright, S.J., Jaramillo, M.A., Pavon, J., Condit, R., Hubbell, S.P. & Foster, R.B. (2005). Reproductive size thresholds in tropical trees: variation among individuals, species and forests. J. Trop. Ecol., 21, 307–315

Description:

Tree census data from the SAFE Project 2011-12. Data includes measurements of DBH and estimates of tree height for all stems, fruiting and flowering estimates, estimates of epiphyte and liana cover, and taxonomic IDs.

Project: This dataset was collected as part of the following SAFE research project: Above ground net primary productivity

Funding: These data were collected as part of research funded by:

• Sime Darby Foundation (Research grant, SAFE Project)

This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.

XML metadata: GEMINI compliant metadata for this dataset is available here

Files: This consists of 1 file: TreeCensus11_12.xlsx

TreeCensus11_12.xlsx

This file contains dataset metadata and 1 data tables:

1. Census11_12 (described in worksheet Census11_12)

   Description: Census data from 2011 and 2012

   Number of fields: 45

   Number of data rows: 3507

   Fields:

   • Block: SAFE sampling block (Field type: id)
   • Plot: SAFE plot number (Field type: id)
   • PlotID: SAFE plot code (Field type: location)
   • Stem_suffix: Stem number; some trees have multiple stems that were measured (Field type: id)
   • X_m_IND: x-coordinate of a tree centre [in m] (the centre of the plot marked by PVC tube has xyz coordinates 0, 0, 0) (Field type: numeric)
   • Y_m_IND: y-coordinate of a tree centre [in m] (the centre of the plot marked by PVC tube has xyz coordinates 0, 0, 0) (Field type: numeric)
   • Habit_IND: Functional type of the tree (Field type: categorical)
   • Dead_year_IND: Year of tree death (Field type: numeric)
   • FirstRecord_year_IND: year of the first record of a tree (Field type: numeric)
   • NewRecruit_year_IND: year of the first record of a new recruit (Field type: numeric)
   • Note_IND: Notes (Field type: comments)
   • FinalFamily: Family leve ID (Field type: taxa)
   • FinalGenus: Genus level ID (Field type: taxa)
   • FinalSpecies: Species level ID (Field type: id)
   • TaxaName: Taxonomic info to finest resolution available (Field type: taxa)
   • TaxaLevel: Taxonomic level identified to (Field type: categorical)
   • BasedOn: How was the ID recorded? (Field type: comments)
   • Confidence: How reliable is the idenfication? (Field type: categorical)
   • DeterminationNotes: Notes related to determining taxonomic ID (Field type: comments)
   • Species_group: Functional trait category (Field type: categorical trait)
   • TagStem_2011: tree tag number for year 2011; consists of a tree tag number and a stem number where relevant (given as a suffix) (Field type: id)
   • TagStem_latest: tree tag number in most recent census; consists of a tree tag number and a stem number where relevant (given as a suffix) (Field type: id)
   • StemCode_2011: Set of codes describing features of the tree A=Alive normal;B=Stem broken below POM;C=Leaning stem;D=Fallen;E=Fluted;F=Hollow;G=Rotten;I=No or few leaves;J=Burnt;K=Stem broken above POM;L=Liana >10cm dbh present;M=Main stem of multiple;N=New recruit;O=Lighting damage;P=Cut;Q=Peeling bark;R=Deformed;S=Strangling fig present;T=Is a strangler fig;W#=Liana/climber, entangling tree;X=Dead (mati);Y=Not found (maybe X but not seen);Z=Near death of disease (Field type: comments)
   • Length_m_2011: stem (i.e., tree) height [in m] in year 2011 (Field type: numeric trait)
   • Climber_Upper_2011: coverage of the upper half of a tree by climber (Field type: ordered categorical)
   • Epiphyte_2011: presence of epiphytes on a tree (Field type: ordered categorical)
   • Fruit_2011: Proportion of tree canopy with fruit (Field type: ordered categorical trait)
   • Flower_2011: Proportion of tree canopy with flowers (Field type: ordered categorical trait)
   • TreeStemEntered_2011: tag nr. of the tree that a liana occupies (Field type: id)
   • HOM_2011: height of the point of measurement [in m] (typically 1.3 m above the ground) (Field type: numeric)
   • DPOM_2011_CTFS: stem diameter at the point of measurement [in mm] (minimum diameter limit: 100 mm), measured 1.3 m along the side of the stem closest to the ground, following the bend of the trunk (CTFS protocol rule) in year 2011 (Field type: numeric trait)
   • Note_2011_original: original note for 2011 (Field type: comments)
   • Note_2011_ms: note for data cleaning (Field type: comments)
   • Date_of_DBH_measurement_2011: date of dbh measurement (Field type: date)
   • TagStem_2012: tree tag number for year 2012; consists of a tree tag number and a stem number where relevant (given as a suffix) (Field type: id)
   • StemCode_2012: Set of codes describing features of the tree A=Alive normal;B=Stem broken below POM;C=Leaning stem;D=Fallen;E=Fluted;F=Hollow;G=Rotten;I=No or few leaves;J=Burnt;K=Stem broken above POM;L=Liana >10cm dbh present;M=Main stem of multiple;N=New recruit;O=Lighting damage;P=Cut;Q=Peeling bark;R=Deformed;S=Strangling fig present;T=Is a strangler fig;W#=Liana/climber, entangling tree;X=Dead (mati);Y=Not found (maybe X but not seen);Z=Near death of disease (Field type: comments)
   • Climber_Upper_2012: coverage of the upper half of a tree by climber (Field type: ordered categorical)
   • Epiphyte_2012: presence of epiphytes on a tree (Field type: ordered categorical)
   • Fruit_2012: Proportion of tree canopy with fruit (Field type: ordered categorical trait)
   • Flower_2012: Proportion of tree canopy with flowers (Field type: ordered categorical trait)
   • HOM_2012: height of the point of measurement [in m] (typically 1.3 m above the ground) (Field type: numeric)
   • DPOM_2012_CTFS: stem diameter at the point of measurement [in mm] (minimum diameter limit: 100 mm), measured 1.3 m along the side of the stem closest to the ground, following the bend of the trunk (CTFS protocol rule) in year 2011 (Field type: numeric trait)
   • Note_2012_original: Field notes about the tree (Field type: comments)
   • Note_2012_ms: Notes related to data cleaning (Field type: comments)
   • Date_of_DBH_measurement_2012: date of dbh measurement (Field type: date)

Date range: 2010-07-01 to 2012-01-19

Latitudinal extent: 4.6353 to 4.7714

Longitudinal extent: 116.9477 to 117.7028

Taxonomic coverage:
All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.

 -  Plantae
 -  -  Tracheophyta
 -  -  -  Liliopsida
 -  -  -  -  Arecales
 -  -  -  -  -  Arecaceae
 -  -  -  -  -  -  Elaeis
 -  -  -  -  -  -  -  Elaeis guineensis
 -  -  -  Magnoliopsida
 -  -  -  -  Fagales
 -  -  -  -  -  Fagaceae
 -  -  -  -  -  -  Castanopsis
 -  -  -  -  -  -  Lithocarpus
 -  -  -  -  Sapindales
 -  -  -  -  -  Anacardiaceae
 -  -  -  -  -  -  Buchanania
 -  -  -  -  -  -  Gluta
 -  -  -  -  -  -  Parishia
 -  -  -  -  -  Burseraceae
 -  -  -  -  -  Meliaceae
 -  -  -  -  -  -  Aglaia
 -  -  -  -  -  -  Lansium
 -  -  -  -  -  -  Walsura
 -  -  -  -  -  -  -  Walsura pinnata
 -  -  -  -  -  Rutaceae
 -  -  -  -  -  -  Melicope
 -  -  -  -  -  Sapindaceae
 -  -  -  -  -  -  Dimocarpus
 -  -  -  -  -  -  -  Dimocarpus longan
 -  -  -  -  -  -  Nephelium
 -  -  -  -  -  -  Paranephelium
 -  -  -  -  - 

About this dataset

Context

The dataset presents median household incomes for various household sizes in Green Tree, PA, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Green Tree did not include 6, or 7-person households. Across the different household sizes in Green Tree the mean income is $106,883, and the standard deviation is $41,801. The coefficient of variation (CV) is 39.11%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $36,157. It then further increased to $121,677 for 5-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/green-tree-pa-median-household-income-by-household-size.jpeg" alt="Green Tree, PA median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

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 Green Tree median household income. You can refer the same here

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Green Tree, PA, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Green Tree, PA reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Green Tree households based on income levels.

Key observations

• For Family Households: In Green Tree, the majority of family households, representing 17.61%, earn $150,000 to $199,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $15,000 to $19,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Green Tree, the majority of non-family households, accounting for 13.61%, have income Less than $10,000, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $15,000 to $19,999, representing a smaller, yet notable, portion of non-family households in the community.

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:

• 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
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Green Tree, PA (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Green Tree, PA
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Green Tree, PA
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Green Tree, PA

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 Green Tree median household income. You can refer the same here

The dataset contains the Diameter at Breast Height (DBH) of trees > 10 cm along with botanical identification (family and species). Data were obtained via forest inventories, in annual campaigns (from 2017 to 2019) conducted in May, with exception of the first campaign, which was from June to November, due to the species identification activity. The research was conducted in a field site approximately 80 km north of Manaus, in the state of Amazonas, Brasil. The dendrometer dataset contains the distance in circumference (mm) from a window on the dendrometer band installed in the tree and measured with a digital caliper, where that distance changes when the trunk grows. Dendrometric bands data were collected from April 2018 to January 2020. Full details about this dataset can be found at https://doi.org/10.5285/c2587e20-ba4a-4444-8ce9-ccdec15b0aa3

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Green Tree, PA, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Green Tree, PA reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Green Tree households based on income levels.

Key observations

• For Family Households: In Green Tree, the majority of family households, representing 17.54%, earn $100,000 to $124,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $200,000 or more, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Green Tree, the majority of non-family households, accounting for 18.21%, have income $75,000 to $99,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $200,000 or more, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income Levels:

• 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
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Green Tree, PA (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Green Tree, PA
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Green Tree, PA
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Green Tree, PA

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 Green Tree median household income. You can refer the same here

As per Cognitive Market Research's latest published report, the Global Genealogy Products and Services Market size will be USD 5,093.64 Million by 2028. Genealogy Products and Services Industry's Compound Annual Growth Rate will be 7.97% from 2023 to 2030.

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Market Dynamics of Genealogy Products and Services

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Key Trends for Genealogy Products and Services

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Genealogy is study of family and their history, tracing lineages, obtaining information about family, ancestors and it comprises DNA testing cemetery records, family tree creation, newspapers, online records, blogs, links that provides access to database for obtaining information about family members.

There are various institutions, advanced applications that are mobile based used for finding information about ancestors. The market is growing rapidly with adoption of emerging technologies that boost its growth in the market.

There is increasing technological advancement in the genealogical studies and its benefits in effectively find out information about ancestors has gained popularity across globe that drives the growth of genealogy products and service market.

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There are various benefits such as genealogical data provides medical history of...

This dataset contains tree canopy cover layers as derived and calculated via a land cover classification for the City of Tempe and Guadalupe using 2019 NAIP Imagery. The land cover classification utilized a Support Vector Machine Classifier and was calculated for various areas including city boundary, census tracts, census blocks, character areas, etc.

This dataset also contains the point locations and attributes of trees maintained by the City of Tempe. The point dataset was obtained by WCA from WCA in Oct 2021. The attributes of interest to this study included unique TreeID, Exact DBH, DBH Range, Height Range, Botanical Name, Common Name, Latitude, and Longitude. Updates to the tree layer were made by joining the results from the Oct 2021 i-Tree report. An i-Tree Eco Analysis was run in Oct 2021 using i-Tree Eco v6.0.22 and the results were joined based on unique tree ID to the Tempe’s tree inventory. Attributes added were: Structural Value ($), Carbon Storage (lb), Carbon Storage ($), Gross Carbon Sequestration (lb/yr), Gross Carbon Sequestration ($/yr), Avoided Runoff (cubicFT/yr), Avoided Runoff ($/yr), Pollution Removal (oz/yr), Pollution Removal ($/yr), Total Annual Benefits ($/yr), Height (ft), Canopy Cover (sqft), Tree Condition, Leaf Area (sqft), Leaf Biomass (lb), Leaf Area Index Basal Area (sqft), Cond, i-Tree_ID_BotName, i-Tree_ID_ComName and i-Tree_ID Genus. The exact definitions, meanings, calculations, etc. for the i-Tree Values can be found on i-Tree’s website via the i-Tree Eco User Manual. For certain layers the individual i-Tree values were aggregated by census tract, census block, zip code, etc. These results can be seen in the polygon layers with the following attribute values: CanopyCoverPer_Final, COUNT_Tree_ID, SUM_Replacement_Value_, SUM_Carbon_Storage_lb_, SUM_Carbon_Storage_, SUM_Gross_Carbon_Sequestration_lb_, SUM_Gross_Carbon_Sequestration_y, SUM_Avoided_Runoff_ftÂ_yr_, SUM_Avoided_Runoff_yr_, SUM_Pollution_Removal_oz_yr_, SUM_Pollution_Removal_yr_, and SUM_Total_Annual_Benefits_yr_

This dataset also contains the Tree Equity Score from American Forests. The Tree Equity Score is a product of American Forests and is a metric that helps cities assess how well they are delivering equitable tree canopy cover to all residents. The score combines measures of tree canopy cover need and priority for trees in urban neighborhoods. It is derived from tree canopy cover, climate, demographic and socioeconomic data. For more information please visit American Forests Tree Equity Score

Projected Coordinate System: NAD 1983 StatePlane Arizona Central FIPS 0202 (Intl Feet)

The data were collected between 2017 and 2020 from 27 forest monitoring plots (0.5 ha each) in five locations along an altitudinal (lowland, mid-elevation, and highland forests) and forest perturbation (low, medium, and high perturbation levels) gradient in Andean ecosystems in Colombia. The dataset includes information on tree diameter and height, scientific and family names following APG III, Above Ground Biomass (AGB), perturbation gradient, altitude, and plot code. The aim of this data collection is to investigate the factors influencing forest change across various gradients, and to evaluate the forest composition of these forests. This data set was obtained within the framework of the BioResilience project, a transdisciplinary investigation that seeks to understand the resilience of forest ecosystems after the post-conflict period in Colombia. Full details about this dataset can be found at https://doi.org/10.5285/a46f0ac4-5ca1-4259-a4f8-d825b5d81d63

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Marked Tree, AR, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Marked Tree, AR reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Marked Tree households based on income levels.

Key observations

• For Family Households: In Marked Tree, the majority of family households, representing 22.07%, earn $75,000 to $99,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $100,000 to $124,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Marked Tree, the majority of non-family households, accounting for 24.48%, have income $10,000 to $14,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $100,000 to $124,999, representing a smaller, yet notable, portion of non-family households in the community.

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:

• 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
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Marked Tree, AR (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Marked Tree, AR
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Marked Tree, AR
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Marked Tree, AR

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 Marked Tree median household income. You can refer the same here

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Lone Tree, CO, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Lone Tree, CO reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Lone Tree households based on income levels.

Key observations

• For Family Households: In Lone Tree, the majority of family households, representing 41.95%, earn $200,000 or more, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.17%, have incomes falling $30,000 to $34,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Lone Tree, the majority of non-family households, accounting for 14.97%, have income $75,000 to $99,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $30,000 to $34,999, representing a smaller, yet notable, portion of non-family households in the community.

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:

• 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
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Lone Tree, CO (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Lone Tree, CO
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Lone Tree, CO
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Lone Tree, CO

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 Lone Tree median household income. You can refer the same here

1860 United States Federal Census contains records from Philadelphia, Pennsylvania, USA by Year: 1860; Census Place: Philadelphia Ward 16 East Division, Philadelphia, Pennsylvania; Roll: M653_1166; Page: 77; Family History Library Film: 805166 - .

Data Link

This is a link to a dataset affiliated with SEARRP but that is stored in a different repository. Please find the link to the dataset below, and be sure to cite the data correctly via that repository.

Correct Citation

Burslem, D.F.R.P.; Banin, L.F.; Bartholomew, D.C.; Bin Suis, M.A.F.; Bittencourt, P.R.L.; Chapman, D.; Dent, D.H.; Hayward, R.M.; O’Brien, M.J.; Rowland, L.M. (2022). Tropical forest seedling census data from Danum Valley, Sabah, Malaysia, 2019-2021. NERC EDS Environmental Information Data Centre. (Dataset). https://doi.org/10.5285/c1813d0d-193f-4f23-82c6-333d5d099b42

Abstract

Southeast Asian tropical forests have been subjected to recent intense pressure due to selective logging and widespread clearance for Oil Palm cultivation. Consequently there is an emerging interest in restoring degraded forests using either natural regeneration or active restoration treatments. However, the reproductive biology of Southeast Asian tropical forest trees limits research on the effectiveness of these approaches, because most large canopy trees only flower and fruit very rarely. These sporadic mass reproductive events are responsible for establishing new cohorts of seedlings that grow up to become the next generation of adult canopy trees, and it is critical to discover whether the success of these episodic attempts at regeneration is as great in forests that have been degraded by logging as they are in primary forests, and whether the processes leading to seedling recruitment are restored effectively in forests where treatments such as tree planting and climber cutting have been applied. However, because these regeneration events occur so infrequently and unpredictably it is very difficult to incorporate them into the conventional planning cycle for research, despite the critical importance of the events that occur early in the life cycle of trees to future forests. In this project we will rapidly establish sampling sites in Sabah, Malaysia, where we know that a mass flowering of canopy trees was initiated in May 2019, for the first time since 2010. We aim to compare the amount and diversity of fruits and seedlings produced during this masting event in primary (undisturbed, unlogged) forests, and in adjacent forests that have been logged and either left to regenerate naturally or restored by planting tree seedlings and maintaining them for five years by climber cutting. Because the restoration of logged forests began more than 20 years ago, the original cohort of planted seedlings are now, in some cases, large canopy trees that may contribute seeds and seedlings for the first time during the reproductive event this year. We will also measure the expression of traits that determine how plants capture and use resources such as light and nutrients for the most common species that occur in each of the three types of forest, which will determine whether the community of seedlings that establish in the restored forests functions in a more similar way to that in the undisturbed primary forest than in the forests left to regenerate naturally after logging. A key focus on this study will be on species of the dominant family of canopy and emergent trees, the Dipterocarpaceae, which are targeted for logging. Logged forests possess a lower density of large reproductively mature dipterocarp individuals, and a key aim of restoration is to re-establish the dominance and diversity of this family by planting and maintaining dipterocarp seedlings. Dipterocarps possess an unusual trait for the tree flora of tropical forests, which is that they form mutualistic associations with root-colonising ectomycorrhizal fungi (ECM), whereas most other species in the forest form a different type of root association with arbuscular mycorrhizas (AM). Our recent research has shown that ECM seedlings benefit from proximity to a high density of ECM adults, possibly because they exchange resources through a common below-ground fungal network and because ECM species suppress root pathogens. In contrast, AM seedlings have lower survival when located close to a high density of adults of the same species. A final aim of our project is to test whether the beneficial effects of high adult density for ECM species is reduced in logged forests where the density of ECM adults is much lower, and whether these effects are offset by restoration. This research will therefore contribute results that are vital to understanding how Southeast Asian forests regenerate during masting events, and whether the negative effects of logging can be mitigated by restoration.

Link to project website: GtR (ukri.org)

Link to data repository: DOI

About this dataset

Context

The dataset presents median household incomes for various household sizes in Lone Tree, IA, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Lone Tree did not include 1, 6, or 7-person households. Across the different household sizes in Lone Tree the mean income is $85,349, and the standard deviation is $10,751. The coefficient of variation (CV) is 12.60%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 2-person households, with an income of $87,824. It then further decreased to 74,313 for 5-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/lone-tree-ia-median-household-income-by-household-size.jpeg" alt="Lone Tree, IA median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

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 Lone Tree median household income. You can refer the same here

1870 United States Federal Census contains records from Lyndon, Aroostook, Maine, USA by Year: 1870; Census Place: Lyndon, Aroostook, Maine; Roll: M593_538; Page: 236A; Family History Library Film: 552037 - .

Context. This historical dataset stems from the project of automatic extraction of 72 census records of Lausanne, Switzerland. The complete dataset covers a century of historical demography in Lausanne (1805-1898), which corresponds to 18,831 pages, and nearly 6 million cells.

Content. The data published in this repository correspond to a first release, i.e. a diachronic slice of one register every 8 to 9 years. Unfortunately, the remaining data are currently under embargo. Their publication will take place as soon as possible, and at the latest by the end of 2023. In the meantime, the data presented here correspond to a large subset of 2,844 pages, which already allows to investigate most research hypotheses.

Description. The population censuses, digitized by the Archives of the city of Lausanne, continuously cover the evolution of the population in Lausanne throughout the 19th century, starting in 1805, with only one long interruption from 1814 to 1831. Highly detailed, they are an invaluable source for studying migration, economic and social history, and traces of cultural exchanges not only with Bern, but also with France and Italy. Indeed, the system of tracing family origin, specific to Switzerland, allows to follow the migratory movements of families long before the censuses appeared. The bourgeoisie is also an essential economic tracer. In addition, censuses extensively describe the organization of the social fabric into family nuclei, around which gravitate various boarders, workers, servants or apprentices, often living in the same apartment with the family.

Production. The structure and richness of censuses have also provided an opportunity to develop automatic methods for processing structured documents. The processing of censuses includes several steps, from the identification of text segments to the restructuring of information as digital tabular data, through Handwritten Text Recognition and the automatic segmentation of the structure using neural networks. Please note that the detailed extraction methodology, as well as the complete evaluation of performance and reliability is published in:

Petitpierre R., Rappo L., Kramer M. (2023). An end-to-end pipeline for historical censuses processing. International Journal on Document Analysis and Recognition (IJDAR). doi: 10.1007/s10032-023-00428-9

Data structure. The data are structured in rows and columns, with each row corresponding to a household. Multiple entries in the same column for a single household are separated by vertical bars ⟨|⟩. The center point ⟨·⟩ indicates an empty entry. For some columns (e.g., street name, house number, owner name), an empty entry indicates that the last non-empty value should be carried over. The page number is in the last column.

Liability. The data presented here are not curated nor verified. They are the raw results of the extraction, the reliability of which was thoroughly assessed in the above-mentioned publication. We insist on the fact that for any reuse of this data for research purposes, the implementation of an appropriate methodology is necessary. This may typically include string distance heuristics, or statistical methodologies to deal with noise and uncertainty.

Description: The research site is one of the existing intensive carbon plots (Tower Plot) at the SAFE Project Experimental area. The area where the plot is located will be converted into oil palm plantation during 2015-2017 (for commercial purposes, not for research). The overarching aim of the project is to assess how the termination of the transport of sugars and defoliation alter forest ecosystem functioning and structure.The aim of the project is:1. To quantify the contribution of photosynthate supply to soil respiration: via the contribution of roots and soil microbial communities utilising root-derived carbon.2. To assess whether there is a relationship between root respiration and tree species.To address these aims, we girdled trees in one half of the plot (0.5 ha), leaving the other half (0.5 ha) as a control. In girdling, a strip of bark (including cambium and phloem) was removed from around the trunk, with the aim of stopping the transport of sugars from the foliage into the roots and soil. The transport of sugars stop immediately, allowing us to quantify their role in the root and soil processes. The girdled trees will gradually defoliate and die due to the carbon starvation of the roots. We wish to emphasise that these trees would have been felled anyway during the conversion to oil palm - this project is not causing any additional deforestation.The processes measured are:- CO2 fluxes from soil measured with portable chambers from which a gas sample is drawn and analysed in the field with a portable instrument (CO2) - Changes in tree circumference monitored with automatic dendrometer bands.- Terrestrial laser scanning (T-lidar), non-destructive method to quantify the 3D structure of the forest stand.Pre-girdling data of all processes will be collected, starting at least two months before the girdling. The girdling took place in early 2016, and the monitoring continued for twelve months afterwards. Project: This dataset was collected as part of the following SAFE research project: Tree girdling - BALI project Funding: These data were collected as part of research funded by:

NERC, the Ministry of Education, Youth and Sports of the Czech Republic (Grant, NE/K01627X/1, NE/G018278/1, INTER-TRANSFER LTT19018) This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.

Permits: These data were collected under permit from the following authorities:

Sabah Biodiversity Council (Research licence JKM/MBS.1000-2/2 JLD.4 (3))

XML metadata: GEMINI compliant metadata for this dataset is available here Files: This consists of 1 file: BALI_Nottingham_Girdling_Data_2021_rev.xlsx BALI_Nottingham_Girdling_Data_2021_rev.xlsx This file contains dataset metadata and 2 data tables:

CO2 and H2O data (described in worksheet CO2_H2O_data) Description: Tree identity and mortality collected taken January 2016- January 2017; Soil respiration, soil temperature and January moisture measurements taken January- March 2016 in a girdled tropical forest using a LiCor 8100a Number of fields: 12 Number of data rows: 12548 Fields:

PlotName: reference to the experiment location within the SAFE plot network (experiment took place in the 'Tower plot / SAF-05'') (Field type: location) daynight: defined by 6pm to 6am (Field type: categorical) date: date of measurement (Field type: date) plot: subplot' in manuscript (Field type: id) Rday: relative data to the start of girdling (girdling day = 0) (Field type: id) CO2: soil CO2 efflux (Field type: numeric) H2O: soil volumetric moisture (Field type: numeric) T: soil temperature (Field type: numeric) port: refers to soil collar location (we allocated chamber port to soil collar location) (Field type: id) portplot: soil collar location nested within plot (Field type: id) time: time of measurement (24h) (Field type: numeric) phase: measurement period (see manuscript for phase definitions) (Field type: categorical)

Tree mortality data (described in worksheet Mortality_data) Description: Tree census of trees surroudings the points where Licor 8100a measurements were taken Number of fields: 20 Number of data rows: 259 Fields:

PlotName: reference to the experiment location within the SAFE plot network (experiment took place in the 'Tower plot / SAF-05'') (Field type: location) ForestPlotsCode: reference to the experiment location within the SAFE plot network (experiment took place in the 'Tower plot / SAF-05'') (Field type: id) Subplot: subplots 1-12 included in the manuscript (Field type: id) CensusDate: date when trees were originally measured (Field type: date) TagNumber: tree tag identity (Field type: id) Height_m: tree height (Field type: numeric) Comments: comments about the tree (Field type: comments) Family: tree family (Field type: taxa) Genus: tree genus (Field type: taxa) SpeciesName: tree species (Field type: comments) WoodDensity: wood density (Field type: numeric) CrownProjection_Area_m2_in2016: Crown Projection Area in 2016 (Field type: numeric) X_m: coordinates (Latitude) (Field type: numeric) Y_m: coordinates (Longitude) (Field type: numeric) GirdlingDeathDate: girdling tree death date (Field type: date) Biomass_kgPerStem: Biomass_kgPerStem (Field type: numeric) Carbon_kgCperStem: Carbon_kgCperStem (Field type: numeric) mortality: mortality (Field type: categorical) DBHgrowth_cm_year: DBHgrowth_cm_year (Field type: numeric) DBHAnnualGrowthRate: DBHAnnualGrowthRate (Field type: numeric) Date range: 2015-08-04 to 2017-02-07 Latitudinal extent: 4.5000 to 5.0700 Longitudinal extent: 116.7500 to 117.8200 Taxonomic coverage: All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.  -  Plantae  -  -  Tracheophyta  -  -  -  Magnoliopsida  -  -  -  -  Lamiales  -  -  -  -  -  Lamiaceae  -  -  -  -  -  -  Callicarpa  -  -  -  -  Rosales  -  -  -  -  -  Urticaceae  -  -  -  -  -  -  Pipturus  -  -  -  -  -  -  Dendrocnide  -  -  -  -  -  -  Oreocnide  -  -  -  -  -  Moraceae  -  -  -  -  -  -  Ficus  -  -  -  -  Malpighiales  -  -  -  -  -  Achariaceae  -  -  -  -  -  -  Hydnocarpus  -  -  -  -  -  Euphorbiaceae  -  -  -  -  -  -  Macaranga  -  -  -  -  -  -  Cephalomappa  -  -  -  -  -  -  Mallotus  -  -  -  -  -  Phyllanthaceae  -  -  -  -  -  -  Aporosa  -  -  -  -  -  Ixonanthaceae  -  -  -  -  -  -  Ixonanthes  -  -  -  -  -  Calophyllaceae  -  -  -  -  -  -  Calophyllum  -  -  -  -  -  Violaceae  -  -  -  -  -  -  Rinorea  -  -  -  -  Ericales  -  -  -  -  -  Pentaphylacaceae  -  -  -  -  -  -  Adinandra  -  -  -  -  -  Sapotaceae  -  -  -  -  -  -  Palaquium  -  -  -  -  -  Symplocaceae  -  -  -  -  -  -  Symplocos  -  -  -  -  -  Ebenaceae  -  -  -  -  -  -  Diospyros  -  -  -  -  Malvales  -  -  -  -  -  Dipterocarpaceae  -  -  -  -  -  -  Shorea  -  -  -  -  -  -  Dipterocarpus  -  -  -  -  -  -  Dryobalanops  -  -  -  -  -  -  Parashorea  -  -  -  -  -  Malvaceae  -  -  -  -  -  -  Pterospermum  -  -  -  -  -  -  Scaphium  -  -  -  -  -  -  Brownlowia  -  -  -  -  -  -  Sterculia  -  -  -  -  -  -  Microcos  -  -  -  -  -  -  Neesia  -  -  -  -  -  -  Diplodiscus  -  -  -  -  Laurales  -  -  -  -  -  Lauraceae  -  -  -  -  -  -  Actinodaphne  -  -  -  -  -  -  Litsea  -  -  -  -  -  -  Eusideroxylon  -  -  -  -  Celastrales  -  -  -  -  -  Celastraceae  -  -  -  -  -  -  Lophopetalum  -  -  -  -  Magnoliales  -  -  -  -  -  Myristicaceae  -  -  -  -  -  -  Knema  -  -  -  -  -  Annonaceae  -  -  -  -  -  -  Goniothalamus  -  -  -  -  -  -  Polyalthia  -  -  -  -  -  -  Maasia  -  -  -  -  Vitales  -  -  -  -  -  Vitaceae  -  -  -  -  -  -  Leea  -  -  -  -  Myrtales  -  -  -  -  -  Myrtaceae  -  -  -  -  -  -  Syzygium  -  -  -  -  -  Lythraceae  -  -  -  -  -  -  Duabanga  -  -  -  -  Cornales  -  -  -  -  -  Cornaceae  -  -  -  -  -  -  Alangium  -  -  -  -  Gentianales  -  -  -  -  -  Rubiaceae  -  -  -  -  -  -  Neolamarckia  -  -  -  -  -  -