Folhelhos Negros da Formação Estiva (Cenomaniano Superior-Turoniano) da Bacia Pernambuco: Condições Deposicionais e Implicações para o Potencial Petrolífero

Bacia Pernambuco compreende uma das bacias sedimentares marginais do Atlântico Sul, estando sua evolução associada aos eventos de separação do continente Gondwana. Este estudo foi realizado nos folhelhos negros da Formação Estiva (fase drifte) de idade Cenomaniano superior-Turoniano (99,6-93,9 Ma). Esta unidade compreende o estabelecimento da plataforma carbonática marinha na Bacia Pernambuco. A partir de análises geoquímicas, averiguaram-se condições mineralógicas, composição da rocha-fonte e paleoredox. Os elementos químicos Si, Ti, Al e Zr estão associados a fases minerais detríticas. A relação K2O/Al2O3 sugere condições químicas para a formação de ilita como principal argilomineral. Por outro lado, elementos químicos Ca, Mg, Mn, Fe estão associados a fases minerais carbonáticas. As relações TiO2/Al2O3 e TiO2/Zr sugerem que a rocha-fonte possua composições intermediárias à acidas. As condições redox, através do fator Mn (Mn*) e a razão e Mn/Al, indicaram que os folhelhos investigados foram depositados sob condições anóxicas, em ambiente marinho proximal. Por outro lado, as relações entre Fet, ST e COT e a razão Fet/Al indicaram condições óxicas à sub-óxicas em um ambiente deposicional marinho amplo. Dessa forma, os folhelhos investigados estão relacionados a um ambiente marinho raso, predominantemente em condições sub-óxicas e baixa produtividade orgânica com baixa expectativa de geração de hidrocarbonetos (COT até 1,8%), para este intervalo estratigráfico, principalmente na região do Gráben do Cupe

Leituras e leitores de Richard Morse: a trajetória de um livro sobre a formação da metrópole paulista

De comunidade à metrópole: a biografia de São Paulo, was first published in 1954 and then re published in 1970 as Formação histórica de São Paulo: de comunidade à metrópole. Written by a young US researcher fascinated by Latin America, this material was originally submitted as his PhD thesis at Columbia University in 1952. Since then, Richard Morse's (1922-2001) work has come a long way and is now considered a primary reference in the history of urban development of São Paulo. This article briefly recovers the reader's response when Morse's research was first published, and how it ensured the book's importance in the Brazilian historiography. The aim is to draw a parallel trajectory of the book and its author - the young researcher at Columbia who became a professor of Latin American History at Yale - and to discuss the meanings regarding its importance in São Paulo's historiography as well as its contribution to a better understanding of the city.O livro De comunidade à metrópole: a biografia de São Paulo, publicado em 1954 e reeditado em 1970 com um novo título, Formação histórica de São Paulo: de comunidade à metrópole, foi escrito por um jovem norte-americano encantado com a América Latina, tendo sido inicialmente apresentado como tese de doutorado na Universidade de Columbia, em 1952. Desde então, essa obra de Richard Morse (1922-2001) percorreu um longo caminho, sendo hoje considerada "um clássico" sobre a evolução urbana da capital paulista. Retoma-se sinteticamente aqui a recepção da publicação, recuperando leitores e leituras que acabaram por garantir ao livro de Morse esse lugar na historiografia paulistana e brasileira. Busca-se, desse modo, traçar um paralelo entra a trajetória do livro e a de seu autor - que de jovem investigador em Columbia torna-se professor de História da América Latina na Universidade de Yale - para discutir o sentido do livro na historiografia e na própria interpretação que o livro fundaria sobre a cidade de São Paulo

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost