Abstract Knowledge about the Brazilian fungal diversity was, until 2010, recorded in few taxonomy and ecology publications, as well as in a handful of species lists. With the publication of the Catálogo de Plantas e Fungos do Brasil and the continued availability of an online list, it has been possible to aggregate this dispersed knowledge. The version presented here adds 2,111 species names to the 3,608 listed in 2010. A total of 5,719 species of fungi distributed in 1,246 genera, 102 orders and 13 phyla represents a considerable increase over the last five years, when only 924 genera and 78 orders were registered. Basidiomycota (2,741 species in 22 orders) and Ascomycota (1,881 species in 41 orders) predominate over other groups. The Atlantic Rainforest has the largest number of records, with 3,017 species, followed by Amazon Rainforest (1,050), Caatinga (999), Cerrado (638) and Pampa and Pantanal with 84 and 35 species, respectively. The Northeast region has the greatest richness (2,617 species), followed by Southeast (2,252), South (1,995), North (1,301) and Central-West (488 species). Regarding the States of the Federation, São Paulo with 1,846 species, Pernambuco with 1,611 and Rio Grande do Sul with 1,377 species are the most diverse.

As of March 2023, around ** percent of online content creators surveyed in Brazil identified as white. Brown and Black digital influencers accounted for ** and ** percent of the respondents, respectively. There were an estimated *** million internet users in Brazil in 2023.

Brazil Population: Southeast data was reported at 87,711,946.000 Person in 2018. This records an increase from the previous number of 86,949,714.000 Person for 2017. Brazil Population: Southeast data is updated yearly, averaging 71,616,953.000 Person from Jun 1980 (Median) to 2018, with 39 observations. The data reached an all-time high of 87,711,946.000 Person in 2018 and a record low of 52,766,074.000 Person in 1980. Brazil Population: Southeast data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAA001: Population.

About this dataset

Context

The dataset presents the median household income across different racial categories in Brazil. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Brazil population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 94% of the total residents in Brazil. Notably, the median household income for White households is $48,925. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $48,925.

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Content

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

Racial categories include:

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

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Brazil.
• Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

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 Brazil median household income by race. You can refer the same here

Brazil Population Census: Age 25 to 29 Years data was reported at 15,469,723.000 Person in 2022. This records a decrease from the previous number of 17,104,414.000 Person for 2010. Brazil Population Census: Age 25 to 29 Years data is updated yearly, averaging 15,469,723.000 Person from Jul 2000 (Median) to 2022, with 3 observations. The data reached an all-time high of 17,104,414.000 Person in 2010 and a record low of 13,849,665.000 Person in 2000. Brazil Population Census: Age 25 to 29 Years data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAC002: Population Census: by Age.

Abstract To understand future changes in community composition due to global changes, the knowledge about community dynamics is of crucial importance. To improve our understanding about processes and patterns involved in maintaining species rich neotropical ecosystems, we provide here a dataset from the one hectare Forest of Seu Nico (FSN) Dynamics Plot from Southeastern Brazil. We report diameter at breast height, basal area and height measurements of 2868 trees and treelets identified during two census spanning over a nine-year period. Furthermore, soil properties and understory light availability of all 100 10 x 10m subplots from the one hectare FSN Dynamics Plot during the second census are given.

Resumo This paper presents a revision about the elderly population in Brazil, addressing aspects of the demographic transition as it relates to socio-economic conditions and some consequences and trends associated with policies affecting Brazil’s elderly. Since a demographic transition has been occurring as a result of the aging of the Brazilian population, we identify a majority profile of Brazilian elderly as White women who live in urban areas in couple-without-children households, and possessing on average an education of 6.1 years and a smaller than minimum wage. We show that the vast majority of the elderly in Brazil receive some form of government income transfer that have a positive effect on poverty reduction in the segment. Finally, we show that there will be some future natural consequences and trends affecting the profile of the aging population, and that adjustments will need to be made by the government in terms of health and social security spending in order to mitigate the increased demands in these areas as the country's demographic change.

ABSTRACT Recent studies have shown that diversity in race and gender is important to improve competitiveness, creativity and innovation. However, many studies have shown that the universe of science is not diverse in none of these criteria. In this work, we quantify the gender and geographic diversity in the Brazilian science. We study in detail the profile of the titular members of the most prestigious academic institution of Brazil, the Brazilian Academy of Sciences (ABC). Our analysis shows that the members of the ABC concentrates 80% in the Southeast region and that the overwhelming majority is composed by men. We show that female and male researchers have roughly the same amount of publication per year but women produce more human resources. Using the Brazilian Researchers’ Fellowship databank we show that the gender and diversity both in gender and in geography decreases along the researchers’ career.

Abstract Genetic diversity is an essential factor for the success of any plant breeding program and should be considered to ensure genetic gain through breeding. In Brazil, research on the genetic diversity and population structure of soybean is required since the species is an important commodity of the country. The study addressed the genetic diversity and population structure of 77 soybean genotypes using 35 SSR markers. The estimate of the diversity index showed that the level of genetic diversity in the soybean collection is low. Similarly, the Jaccard coefficient and Bayesian model based on clustering analysis confirmed the low diversity among soybean genotypes, providing evidence for the assumption of a genetic bottleneck effect on Brazilian soybean genotypes. The results also reinforced the importance of finding and incorporating new genetic resources of soybean in the genetic pool of Brazilian soybean to warrant genetic gain in soybean breeding in the future.

This dataset contains the digitized treatments in Plazi based on the original journal article Pilatti, Patricia, Benathar, Thayse, da Rocha, Patrício A., Koroiva, Ricardo, Carmignotto, Ana P., Gonçalves, Camila F., Beltrão, Mayara Guimarães, Moratelli, Ricardo, Astúa, Diego (2024): Hsunycteris (Chiroptera, Phyllostomidae, Lonchophyllinae) hidden diversity in Brazil: new records encompassing new biomes reveal the presence of an unnamed species in the Brazilian Atlantic Forest. Acta Chiropterologica 26 (2): 153-170, DOI: 10.3161/15081109ACC2024.26.2.002, URL: https://doi.org/10.3161/15081109acc2024.26.2.002

According to a *****-year survey, the share of Brazilian respondents without access to a banking account more than ****** between 2017 and 2024. The decline seems especially fueled by the major decline of "unbanked" population - or those who did not access to the services of a bank or another, similar financial organization - among the youngest respondents, as the share of 15-to 24-year-olds respondents declined from **** percent in 2017 to **** percent in 2024. The report adds that women in Brazil were more likely than men to be financially excluded from services like ATM machines, credit cards, or financial products like insurance or mortgages. The declining figures for unbanked population are reflected in the decreasing market share of cash in Brazilian physical stores.

Reef fish communities were assessed using visual census techniques across 100 reefs spanning over 2.000 km of coastline. Each reef was considered a sample unit and species densities per 100 m² was used for calculating true diversity measures.

Diversity patterns were investigated using “true diversity” measures (sensu Jost 2006), considering the effective number of species equal to Hill numbers (qD). Values in dataset correspond to number of effective species per reef (α diversity, Dα), for q = 0, 1 and 2, using sampled area as weights. Each line represents a reef, labeled by a Code, followed by Brazilian State, Location name, Latitude, Longitude and Source of the species data. Predictors used for adjusting GLMs are presented next: Reef morphotype (categorical predictor), with five levels corresponding to Brazilian reef morphological structures (cemented terraces, fringing, patch, bank and pinnacle reefs, see Appendix S1 for a detailed description). Depth, as the average depth of the reef in meters, measured in situ, isolation, as the linear distance between the reef to the nearest point in mainland, are also presented.

We conducted a survey of tadpoles and adult anurans in several ponds in the State of Minas Gerais, Brazil. We determined the taxonomic identities of the tadpoles by matching the tadpole DNA barcodes (16S) with the respective barcodes of adults. We provide descriptions and illustrations of the larval morphology of these anurans, including their coloration in life. The tadpoles we collected were screened for symptoms of Batrachochytrium dendrobatidis (Bd) infection, by visually inspecting the keratinous mouth parts under a dissecting microscope.

O conjunto de dados utilizado neste estudo tem como finalidade analisar a presença e a distribuição da população brasileira em 34 cidades médias da Espanha, com foco na evolução da imigração e nos padrões de segregação residencial. A natureza dos dados é quantitativa, com base em registros administrativos oficiais, permitindo uma abordagem comparativa, multiescalar e temporal. O escopo geográfico está delimitado por áreas urbanas articuladas por cidades médias que não pertencem a regiões metropolitanas maiores, tampouco se situam em áreas litorâneas, com população urbana entre 50 mil e 400 mil habitantes, conforme critérios do projeto de pesquisa financiado pelo Ministério da Ciência e Inovação do governo espanhol. Os dados foram organizados em duas frentes analíticas: (1) a evolução demográfica da imigração brasileira nas cidades selecionadas, com base na Estatística do Padrão Contínuo de Habitantes do Instituto Nacional de Estatística (INE), abrangendo os anos de 2003, 2007, 2012, 2017 e 2022; e (2) a segregação residencial da população brasileira, a partir do Censo de 2021 e do Atlas de Renda dos Domicílios, utilizando o Índice de Segregação Residencial (ISR). Essa estrutura metodológica oferece um panorama detalhado das dinâmicas migratórias e das desigualdades espaciais, com foco na população brasileira, em cidades de porte intermediário e contextos urbanos não centrais, contribuindo para o entendimento das transformações urbanas e dos desafios de coesão social no interior da geografia espanhola.

The history of modern Brazil begins in the year 1500 when Pedro Álvares Cabral arrived with a small fleet and claimed the land for the Portuguese Empire. With the Treaty of Torsedillas in 1494, Spain and Portugal agreed to split the New World peacefully, thus allowing Portugal to take control of the area with little competition from other European powers. As the Portuguese did not arrive with large numbers, and the indigenous population was overwhelmed with disease, large numbers of African slaves were transported across the Atlantic and forced to harvest or mine Brazil's wealth of natural resources. These slaves were forced to work in sugar, coffee and rubber plantations and gold and diamond mines, which helped fund Portuguese expansion across the globe. In modern history, transatlantic slavery brought more Africans to Brazil than any other country in the world. This combination of European, African and indigenous peoples set the foundation for what has become one of the most ethnically diverse countries across the globe.

Independence and Monarchy By the early eighteenth century, Portugal had established control over most of modern-day Brazil, and the population more than doubled in each half of the 1800s. The capital of the Portuguese empire was moved to Rio de Janeiro in 1808 (as Napoleon's forces moved closer towards Lisbon), making this the only time in European history where a capital was moved to another continent. The United Kingdom of Portugal, Brazil and the Algarves was established in 1815, and when the Portuguese monarchy and capital returned to Lisbon in 1821, the King's son, Dom Pedro, remained in Brazil as regent. The following year, Dom Pedro declared Brazil's independence, and within three years, most other major powers (including Portugal) recognized the Empire of Brazil as an independent monarchy and formed economic relations with it; this was a much more peaceful transition to independence than many of the ex-Spanish colonies in the Americas. Under the reign of Dom Pedro II, Brazil's political stability remained relatively intact, and the economy grew through its exportation of raw materials and economic alliances with Portugal and Britain. Despite pressure from political opponents, Pedro II abolished slavery in 1850 (as part of a trade agreement with Britain), and Brazil remained a powerful, stable and progressive nation under Pedro II's leadership, in stark contrast to its South American neighbors. The booming economy also attracted millions of migrants from Europe and Asia around the turn of the twentieth century, which has had a profound impact on Brazil's demography and culture to this day.

The New Republic

Despite his popularity, King Pedro II was overthrown in a military coup in 1889, ending his 58 year reign and initiating six decades of political instability and economic difficulties. A series of military coups, failed attempts to restore stability, and the decline of Brazil's overseas influence contributed greatly to a weakened economy in the early 1900s. The 1930s saw the emergence of Getúlio Vargas, who ruled as a fascist dictator for two decades. Despite a growing economy and Brazil's alliance with the Allied Powers in the Second World War, the end of fascism in Europe weakened Vargas' position in Brazil, and he was eventually overthrown by the military, who then re-introduced democracy to Brazil in 1945. Vargas was then elected to power in 1951, and remained popular among the general public, however political opposition to his beliefs and methods led to his suicide in 1954. Further political instability ensued and a brutal, yet prosperous, military dictatorship took control in the 1960s and 1970s, but Brazil gradually returned to a democratic nation in the 1980s. Brazil's economic and political stability fluctuated over the subsequent four decades, and a corruption scandal in the 2010s saw the impeachment of President Dilma Rousseff. Despite all of this economic instability and political turmoil, Brazil is one of the world's largest economies and is sometimes seen as a potential superpower. The World Bank classifies it as a upper-middle income country and it has the largest share of global wealth in Latin America. It is the largest Lusophone (Portuguese-speaking), and sixth most populous country in the world, with a population of more than 210 million people.

Comparison of pvama1 genetic diversity among isolates from Brazil.

Abstract This compilation of ferns and lycophytes in Brazil is an update of the one published in 2010 in Catálogo de Plantas e Fungos do Brasil. The methodology consisted in collecting data from regional checklists, taxonomic revisions, and selected databases. Invited specialists improved the list accessing a website housed at the Jardim Botânico do Rio de Janeiro. The results show 1,253 species: 1,111 of ferns and 142 of lycophytes. This number is 6.5% higher than the previous one (1,176 spp.). The percentage of endemic species decreased from 38.2% to 36.7%. We recognized 36 families and 133 genera (vs. 33 families, 121 genera in 2010). The 10 most diverse families are Pteridaceae (196 spp.), Dryopteridaceae (179), Polypodiaceae (164), Hymenophyllaceae (90), Thelypteridaceae (86), Aspleniaceae (78), Lycopodiaceae (64), Selaginellaceae (55), Anemiaceae (51), and Cyatheaceae (45). The three most diverse genera are still Elaphoglossum (87 spp.), Thelypteris (85), and Asplenium (74). The richest phytogeographic domain continues to be in the Atlantic Rainforest with 883 species which also has the largest number of endemic and threatened species, followed by the Amazon Rainforest (503), Cerrado (269), Pantanal (30), Caatinga (26), and Pampa (eight). Minas Gerais remains as the richest state (657 spp. vs. 580 in 2010).

Brazil Population Census: South: Rio Grande do Sul: Santa Maria data was reported at 261,031.000 Person in 2010. This records a decrease from the previous number of 263,403.000 Person for 2007. Brazil Population Census: South: Rio Grande do Sul: Santa Maria data is updated yearly, averaging 252,321.000 Person from Jul 1996 (Median) to 2010, with 4 observations. The data reached an all-time high of 263,403.000 Person in 2007 and a record low of 233,351.000 Person in 1996. Brazil Population Census: South: Rio Grande do Sul: Santa Maria data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAC058: Population Census: by Municipality: South: Rio Grande do Sul.

This dataset consists of two tables. The first is a presence-absence table that provides an updated list of testate amoebae found in the state of Rio de Janeiro, Brazil. It includes both historical records and new occurrence data, offering a comprehensive overview of the biogeography of testate amoebae in the region. The second table compiles previous studies on testate amoebae in the state of Rio de Janeiro, with its primary purpose being to document the collection methods used in each research effort. Data collection was conducted in April 2024 using the research databases Scopus, Web of Science, Google Scholar, and SciELO, with search keywords in both Portuguese and English: "Testate Amoebae," "Thecamoebian," "Zooplankton" combined with "Rio de Janeiro."

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!