Unidade básica educadora popular em saúde

Objetivo: Relatar a experiência dos profissionais da Estratégia Saúde da Família de uma Unidade Básica de Saúde em sua formação de Educadores Populares em Saúde. Método: A experiência começou na reunião em equipe quando decidimos matricular as enfermeiras, os agentes comunitários de saúde, as técnicas de enfermagem, a psicóloga do NASF e uma das dentistas da Unidade Básica de Saúde do Poti Velho no curso de Educação Popular em Saúde (EPS) que estava sendo oferecido pela FIOCRUZ em parceria com a Universidade Federal do Piauí. Em fevereiro de 2014, 15 profissionais da ESF do Poti velho assistiram o curso de formação em educadores populares em saúde, durante uma semana às aulas aconteceram no horário diurno, em seguida acompanhamos o curso através do ambiente virtual de aprendizagem (AVA), desenvolvendo trabalhos com as comunidades assistidas pelas equipes capacitadas e postando-os no AVA, como forma de demonstrar e compartilhar o que aprendemos durante o curso.  Resultados: incorporação de uma nova forma de trabalhar educação em saúde, valorizando o conhecimento da comunidade, trazendo os usuários para as reflexões propostas e a criação do núcleo de Educação Popular em Saúde

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

Unidade básica educadora popular em saúde

Objetivo: Relatar a experiência dos profissionais da Estratégia Saúde da Família de uma Unidade Básica de Saúde em sua formação de Educadores Populares em Saúde. Método: A experiência começou na reunião em equipe quando decidimos matricular as enfermeiras, os agentes comunitários de saúde, as técnicas de enfermagem, a psicóloga do NASF e uma das dentistas da Unidade Básica de Saúde do Poti Velho no curso de Educação Popular em Saúde (EPS) que estava sendo oferecido pela FIOCRUZ em parceria com a Universidade Federal do Piauí. Em fevereiro de 2014, 15 profissionais da ESF do Poti velho assistiram o curso de formação em educadores populares em saúde, durante uma semana às aulas aconteceram no horário diurno, em seguida acompanhamos o curso através do ambiente virtual de aprendizagem (AVA), desenvolvendo trabalhos com as comunidades assistidas pelas equipes capacitadas e postando-os no AVA, como forma de demonstrar e compartilhar o que aprendemos durante o curso. Resultados: incorporação de uma nova forma de trabalhar educação em saúde, valorizando o conhecimento da comunidade, trazendo os usuários para as reflexões propostas e a criação do núcleo de Educação Popular em Saúde

Núcleos de Ensino da Unesp: artigos 2008

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq