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

The Brazilian version of the 20-item rapid estimate of adult literacy in medicine and dentistry

Background The misunderstanding of specific vocabulary may hamper the patient-health provider communication. The 20-item Rapid Estimate Adult Literacy in Medicine and Dentistry (REALMD-20) was constructed to screen patients by their ability in reading medical/dental terminologies in a simple and rapid way. This study aimed to perform the cross-cultural adaptation and validation of this instrument for its application in Brazilian dental patients. Methods The cross-cultural adaptation was performed through conceptual equivalence, verbatim translation, semantic, item and operational equivalence, and back-translation. After that, 200 participants responded the adapted version of the REALMD-20, the Brazilian version of the Rapid Estimate of Adult Literacy in Dentistry (BREALD-30), ten questions of the Brazilian National Functional Literacy Index (BNFLI), and a questionnaire with socio-demographic and oral health-related questions. Statistical analysis was conducted to assess the reliability and validity of the REALMD-20 (P < 0.05). Results The sample was composed predominantly by women (55.5%) and white/brown (76%) individuals, with an average age of 39.02 years old (±15.28). The average REALMD-20 score was 17.48 (±2.59, range 8–20). It displayed a good internal consistency (Cronbach’s alpha = 0.789) and test-retest reliability (ICC = 0.73; 95% CI [0.66 − 0.79]). In the exploratory factor analysis, six factors were extracted according to Kaiser’s criterion. The factor I (eigenvalue = 4.53) comprised four terms— “Jaundice”, “Amalgam”, “Periodontitis” and “Abscess”—accounted for 25.18% of total variance, while the factor II (eigenvalue = 1.88) comprised other four terms—“Gingivitis”, “Instruction”, “Osteoporosis” and “Constipation”—accounted for 10.46% of total variance. The first four factors accounted for 52.1% of total variance. The REALMD-20 was positively correlated with the BREALD-30 (Rs = 0.73, P < 0.001) and BNFLI (Rs = 0.60, P < 0.001). The scores were significantly higher among health professionals, more educated people, and individuals who reported good/excellent oral health conditions, and who sought preventive dental services. Distinctly, REALMD-20 scores were similar between both participants who visited a dentist <1 year ago and ≥1 year. Also, REALMD-20 was a significant predictor of self-reported oral health status in a multivariate logistic regression model, considering socio-demographic and oral health-related confounding variables. Conclusion The Brazilian version of the REALMD-20 demonstrated adequate psychometric properties for screening dental patients in relation to their recognition of health specific terms. This instrument can contribute to identify individuals with important dental/medical vocabulary limitations in order to improve the health education and outcomes in a person-centered care model

Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

International audienceThe shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiversity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxonomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world's known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world's most biodiverse countries. We further identify collection gaps and summarize future goals that extend beyond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still unequally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the country. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora