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

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

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

Termo de Compromisso de Estágio de Agosto e Setembro de 2010

O Termo de Compromisso de Estágio Obrigatório ou não inclui um programa de atividade de estágio relacionadas a formação complementar do estagiário no curso

Foreign policy of the New Left: explaining Brazil's Southern partnerships

Abstract The purpose of this study is to consider the relationship between domestic change and foreign policy in Brazil, a country seeking to become Latin America's hegemon, and achieve greater global status. It focuses on Brazil's partnerships with other countries in the Global South. It argues that, due to the combination of institutions and interests behind foreign policy-making in Brazil, there is no coherent project of South-South engagement. As a result, South-South ties tend to contradict the Brazilian government's foreign policy objective of acting as a global equaliser. The study also examines the drivers of Brazil's foreign conduct, and argues that the politico-economic determinants of foreign policy differ from those of domestic policy

Incidência de tuberculose em pacientes com artrite reumatoide em uso de bloqueadores do TNF no Brasil: dados do Registro Brasileiro de Monitoração de Terapias Biológicas BiobadaBrasil

Objectives: To assess the incidence of tuberculosis and to screen for latent tuberculosis infection among Brazilians with rheumatoid arthritis using biologics in clinical practice. Patients and methods: This cohort study used data from the Brazilian Registry of Biological Therapies in Rheumatic Diseases (Registro Brasileiro de Monitoração de Terapias Biológicas - BiobadaBrasil), from 01/2009 to 05/2013, encompassing 1552 treatments, including 415 with only synthetic disease-modifying anti-rheumatic drugs, 942 synthetic DMARDs combined with anti-tumor necrosis factor (etanercept, infliximab, adalimumab) and 195 synthetic DMARDs combined with other biologics (abatacept, rituximab and tocilizumab). The occurrence of tuberculosis and the drug exposure time were assessed, and screening for tuberculosis was performed. Statistical analysis: Unpaired t-test and Fisher's two-tailed test; p < 0.05. Results: The exposure times were 981 patient-years in the controls, 1744 patient-years in the anti-TNF group (adalimumab = 676, infliximab = 547 and etanercept = 521 patient-years) and 336 patient-years in the other biologics group. The incidence rates of tuberculosis were 1.01/1000 patient-years in the controls and 2.87 patient-years among anti-TNF users (adalimumab = 4.43/1000 patient-years; etanercept = 1.92/1000 patient-years and infliximab = 1.82/1000 patient-years). No cases of tuberculosis occurred in the other biologics group. The mean drug exposure time until the occurrence of tuberculosis was 27(11) months for the anti-TNF group. Conclusions: The incidence of tuberculosis was higher among users of synthetic DMARDs and anti-TNF than among users of synthetic DMARDs and synthetic DMARDs and non-anti-TNF biologics and also occurred later, suggesting infection during treatment and no screening failure.Objetivos: Avaliar incidência de tuberculose e triagem para tuberculose latente em brasileiros com artrite reumatoide em uso de agentes biológicos na prática clinica. Pacientes e métodos: Estudo de coorte com dados do Registro Brasileiro de Monitoração de Terapias Biológicas (BiobadaBrasil), de 01/2009 a 05/2013, abrangeu 1.552 tratamentos, 415 somente com drogas modificadoras do curso da doença (MMCDs) sintéticas, 942 MMCDs sintéticas em associação com anti-TNF (etanercepte, infliximabe, adalimumabe) e 195 MMCDs sintéticas em associação com outros biológicos (abatacepte, rituximabe e tocilizumabe). Avaliaram-se ocorrência de tuberculose, tempo de exposição às drogas e triagem para TB. Análise estatística: teste t não pareado e teste de Fisher bicaudal; p < 0,05. Resultados: O tempo de exposição dos controles foi de 981 pacientes-ano, do grupo de anti-TNF foi de 1.744 pacientes-ano (adalimumabe = 676, infliximabe = 547 e etanercepte = 521 pacientes-ano) e o de outros biológicos de 336 pacientes-ano. A incidência de TB foi de 1,01/1.000 pacientes-ano nos controles e de 2,87 pacientes-ano nos usuários de anti-TNF (adalimumabe = 4,43/1.000 pacientes-ano; etanercepte = 1,92/1.000 pacientes-ano e infliximabe = 1,82/1.000 pacientes-ano). Não houve casos de tuberculose no grupo de outros biológicos. O tempo médio de exposição até a ocorrência de tuberculose foi de 27(11) meses para o grupo anti-TNF. Conclusões: A incidência de tuberculose foi maior nos usuários de MMCDs sintéticas e anti-TNF do que nos usuários de MMCDs sintéticas e de MMCDs sintéticas e biológicos não anti-TNF, e também mais tardia, sugerindo infecção durante o tratamento, e não falha na triagem