IDENTIFICAÇÃO DE ÁREAS ALAGADAS NO BIOMA PANTANAL – BRASIL – UTILIZANDO DADOS MULTITEMPORAIS TERRA/MODIS

O Pantanal é a maior área úmida tropical do planeta e a principal área alagada do Brasil. As inundações sazonais são uma das principais características deste bioma sendo um fator ecológico fundamental na região. As séries temporais de imagens de sensoriamento remoto são uma importante ferramenta para auxiliar no monitoramento destas áreas. O objetivo deste trabalho foi identificar as áreas alagadas do Bioma Pantanal a partir das variações espaciais e temporais dos valores do índice de vegetação EVI (Enhanced Vegetation Index) extraídos das imagens do sensor MODIS (Moderate Resolution Imaging Spectroradiometer) empregando a análise por componentes principais. Foram utilizadas 217 imagens de EVI do período de 2000 a 2008, e dados de precipitação do Tropical Rainfall Measuring Mission (TRMM). A partir da análise por componentes principais buscou-se representar a variabilidade no tempo de cada pixel que compõe a imagem da região. As áreas que apresentaram maior variabilidade foram classificadas como áreas alagadas. Neste trabalho, foi possível identificar a dinâmica da região, ou seja, períodos de seca e alagamento e obter informações sobre a sazonalidade da vegetação bem como o perfil temporal do EVI para as áreas inundáveis na região Palavras-chave: Sensoriamento remoto. Análise de componentes principais. Índice de vegetação. Identification flooded areas of the Pantanal Biome – Brazil – using multitemporal terra/MODIS data The Pantanal is the largest tropical wetland on the planet and the major flooded area of Brazil. The seasonal floods are one of the major characteristics of this biome being a fundamental ecological factor in the region. The time series of remotely sensed images are an important tool to supervise the monitoring of these areas. The objective of this work was to identify the flooded areas of the Pantanal biome based on the spatial and temporal variation of the EVI (Enhanced Vegetation Index) values extracted from the MODIS (Moderate Resolution Imaging Spectroradiometer) images using principal components analysis. We used 217 EVI images from the period of 2000 to 2008, and precipitation data from the Tropical Rainfall Measuring Mission (TRMM). From the principal components analysis the variability in time of each pixel that composes the image was obtained for the entire region. Areas that presented the greatest variability were classified as flooded areas. In this work, it was possible to identify the dynamics of the region, i.e., periods of drought and flooding; and to obtain information about vegetation seasonality as well as the temporal profile of the EVI for flooded areas in the region. Key words: Remote sensing. Principal components analysis. Vegetation index

Perfil epidemiologico dos pacientes portadores de Artrite Reumatóide que tratam com imunobiológicos no Centro Especializado de Atendimento de Cascavel/PR

Introdução: A Artrite Reumatóide (AR) é uma doença inflamatória autoimune e crônica que acomete, principalmente, as articulações. Na ausência de tratamento adequado, a doença gera deformidades que, muitas vezes, impossibilitam o paciente de realizar suas atividades de vida diárias. Por se tratar de uma doença crônica e sem cura, é preciso controlar a sua evolução por meio de  terapias medicamentosas e não medicamentosas com o objetivo de garantir uma melhor qualidade de vida. O tratamento medicamentoso é realizado com Anti-inflamatórios não esteroidais (AINEs), Analgésicos, Corticoesteróides, DMARD (Drogas modificadoras do curso da doença) convencionais e DMARD biológicas. Objetivo: Realizar uma análise do perfil epidemiológico dos pacientes portadores de Artrite Reumatóide que realizam tratamento com Imunobiológicos no Centro de Atendimento de Especialidades de Cascavel, no Paraná. Métodos: Estudo observacional, transversal e descritivo, desenvolvido pela avaliação de prontuários médicos dos pacientes portadores de Artrite Reumatóide que tratam com Imunobiológicos no Centro de Atendimento Especializado de Cascavel, no Paraná entre 2018 e 2022. Resultados: Foram analisados 32 prontuários médicos de pacientes com AR em uso de Imunobiológicos, sendo entre 50-60 anos (37,5%) a faixa etária mais acometida. Em relação ao sexo, há maior prevalência em mulheres (87,5%). Quanto a raça, há uma superioridade no acometimento dos indivíduos da raça branca (65,625%). Observou-se ainda que a grande maioria dos pacientes apresentam Fator Reumatóide positivo (71,875%). Dentre os pacientes com Fator Reumatóide negativo, 18,75% possuem anti-CCP negativo. Em relação as comorbidades associadas a AR, evidenciou-se o predomínio da Hipertensão Arterial Sistêmica. Conclusão: O estudo proporcionou uma visão parcial dos pacientes portadores de AR que tratam com Imunobiológicos, afim de recomendar o uso dessa classe de medicamento em pacientes com as mesmas características citadas na pesquisa

Prevalence of bat viruses associated with land-use change in the Atlantic Forest, Brazil

Introduction: Bats are critical to maintaining healthy ecosystems and many species are threatened primarily due to global habitat loss. Bats are also important hosts of a range of viruses, several of which have had significant impacts on global public health. The emergence of these viruses has been associated with land-use change and decreased host species richness. Yet, few studies have assessed how bat communities and the viruses they host alter with land-use change, particularly in highly biodiverse sites. Methods: In this study, we investigate the effects of deforestation on bat host species richness and diversity, and viral prevalence and richness across five forested sites and three nearby deforested sites in the interior Atlantic Forest of southern Brazil. Nested-PCR and qPCR were used to amplify and detect viral genetic sequence from six viral families (corona-, adeno-, herpes-, hanta-, paramyxo-, and astro-viridae) in 944 blood, saliva and rectal samples collected from 335 bats. Results: We found that deforested sites had a less diverse bat community than forested sites, but higher viral prevalence and richness after controlling for confounding factors. Viral detection was more likely in juvenile males located in deforested sites. Interestingly, we also found a significant effect of host bat species on viral prevalence indicating that viral taxa were detected more frequently in some species than others. In particular, viruses from the Coronaviridae family were detected more frequently in generalist species compared to specialist species. Discussion: Our findings suggest that deforestation may drive changes in the ecosystem which reduce bat host diversity while increasing the abundance of generalist species which host a wider range of viruses

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

Image_1_Prevalence of bat viruses associated with land-use change in the Atlantic Forest, Brazil.png

IntroductionBats are critical to maintaining healthy ecosystems and many species are threatened primarily due to global habitat loss. Bats are also important hosts of a range of viruses, several of which have had significant impacts on global public health. The emergence of these viruses has been associated with land-use change and decreased host species richness. Yet, few studies have assessed how bat communities and the viruses they host alter with land-use change, particularly in highly biodiverse sites.MethodsIn this study, we investigate the effects of deforestation on bat host species richness and diversity, and viral prevalence and richness across five forested sites and three nearby deforested sites in the interior Atlantic Forest of southern Brazil. Nested-PCR and qPCR were used to amplify and detect viral genetic sequence from six viral families (corona-, adeno-, herpes-, hanta-, paramyxo-, and astro-viridae) in 944 blood, saliva and rectal samples collected from 335 bats.ResultsWe found that deforested sites had a less diverse bat community than forested sites, but higher viral prevalence and richness after controlling for confounding factors. Viral detection was more likely in juvenile males located in deforested sites. Interestingly, we also found a significant effect of host bat species on viral prevalence indicating that viral taxa were detected more frequently in some species than others. In particular, viruses from the Coronaviridae family were detected more frequently in generalist species compared to specialist species.DiscussionOur findings suggest that deforestation may drive changes in the ecosystem which reduce bat host diversity while increasing the abundance of generalist species which host a wider range of viruses.</p

Image_3_Prevalence of bat viruses associated with land-use change in the Atlantic Forest, Brazil.png

IntroductionBats are critical to maintaining healthy ecosystems and many species are threatened primarily due to global habitat loss. Bats are also important hosts of a range of viruses, several of which have had significant impacts on global public health. The emergence of these viruses has been associated with land-use change and decreased host species richness. Yet, few studies have assessed how bat communities and the viruses they host alter with land-use change, particularly in highly biodiverse sites.MethodsIn this study, we investigate the effects of deforestation on bat host species richness and diversity, and viral prevalence and richness across five forested sites and three nearby deforested sites in the interior Atlantic Forest of southern Brazil. Nested-PCR and qPCR were used to amplify and detect viral genetic sequence from six viral families (corona-, adeno-, herpes-, hanta-, paramyxo-, and astro-viridae) in 944 blood, saliva and rectal samples collected from 335 bats.ResultsWe found that deforested sites had a less diverse bat community than forested sites, but higher viral prevalence and richness after controlling for confounding factors. Viral detection was more likely in juvenile males located in deforested sites. Interestingly, we also found a significant effect of host bat species on viral prevalence indicating that viral taxa were detected more frequently in some species than others. In particular, viruses from the Coronaviridae family were detected more frequently in generalist species compared to specialist species.DiscussionOur findings suggest that deforestation may drive changes in the ecosystem which reduce bat host diversity while increasing the abundance of generalist species which host a wider range of viruses.</p