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

Aspectos ecológicos da leishmaniose tegumentar americana: 9. Prevalência/incidência da infecção humana nos municípios de Pedro de Toledo e Miracatu, São Paulo, Brasil

The epidemiological study was conducted during the 1973-1984 period. The clinical prospective exam and Montenegro skin, immunoflurescent and passive hemagglutination tests have been carried out in three small localities between Pedro de Toledo e Miracatu municipalities, São Paulo, Brazil. The retrospective study of human-cases involved 108 and 65 cases registered in Pedro de Toledo e Miracatu, respectively. In the three communities studied, 273 people were examinated clinically and serologically. Twenty two individuals had had signals of cutaneous leishmaniasis; 10.2 and 12.8% were seropositive to IF and HA. Leishmanin skin testing of a sample of 154 people residents in Pedra do Largo showed prevalence of Leishmania infection in 25.5%. This result involved individual of all ages and sex. However, 5.8% of them were from 0 to 9 years old. The data confirmed that active parasite transmission didn't occur every year, either. The human infection seems not to depend on man contact with a forest. The incidence relatively low suggests low endemic area for cutaneous leishmaniasis and an explosive behavior of the cases. The temporal distribution of disease was irregular and the epidemiological pattern seen was different from the other endemic area of South AmericaEste trabalho apresenta aspectos epidemiológicos da leishmaniose tegumentar nos municípios de Pedro de Toledo e Miracatu, região do Vale do Ribeira, estado de São Paulo, referente ao período 1973-1984. Foi feita uma análise retrospectiva de 108 e 65 casos humanos, respectivamente, para os dois municípios acima. Outro estudo prospectivo foi realizado através do exame clínico e testes de Montenegro, imunofluorescência indireta (IF) e hemaglutinação passiva (HA). Duzentos e setenta e três pessoas foram examinadas, sendo que 22 tinham leishmaniose clínica; 10,2 e 12,8% foram soropositivos à IF e HA, respectivamente. O teste de Montenegro foi aplicado em 154 indivíduos residentes em Pedra do Largo, com prevalência de 25,5% de infecção humana. Destes, 5,8% eram crianças com idade entre 0 e 9 anos. A morbidade mostrou-se variável no tempo, manifestada sob a forma de surtos epidêmicos explosivos e sugerindo feição cíclica ainda mal definida. Notou-se tendência para incidência nula em período subseqüente a cada surto. O aspecto epidemiológico geral mostra uma leishmaniose tegumentar com baixa endemicidade. O padrão de transmissão pareceu não depender do contato do homem com a floresta e a infecção humana sem distinção entre crianças e adulto

Núcleos de Ensino da Unesp: artigos 2010: volume 6: políticas públicas e organização escolar

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES

Núcleos de Ensino da Unesp: artigos 2008

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq