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

Rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART): Study protocol for a randomized controlled trial

Background: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality. Alveolar recruitment followed by ventilation at optimal titrated PEEP may reduce ventilator-induced lung injury and improve oxygenation in patients with ARDS, but the effects on mortality and other clinical outcomes remain unknown. This article reports the rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART). Methods/Design: ART is a pragmatic, multicenter, randomized (concealed), controlled trial, which aims to determine if maximum stepwise alveolar recruitment associated with PEEP titration is able to increase 28-day survival in patients with ARDS compared to conventional treatment (ARDSNet strategy). We will enroll adult patients with ARDS of less than 72 h duration. The intervention group will receive an alveolar recruitment maneuver, with stepwise increases of PEEP achieving 45 cmH(2)O and peak pressure of 60 cmH2O, followed by ventilation with optimal PEEP titrated according to the static compliance of the respiratory system. In the control group, mechanical ventilation will follow a conventional protocol (ARDSNet). In both groups, we will use controlled volume mode with low tidal volumes (4 to 6 mL/kg of predicted body weight) and targeting plateau pressure <= 30 cmH2O. The primary outcome is 28-day survival, and the secondary outcomes are: length of ICU stay; length of hospital stay; pneumothorax requiring chest tube during first 7 days; barotrauma during first 7 days; mechanical ventilation-free days from days 1 to 28; ICU, in-hospital, and 6-month survival. ART is an event-guided trial planned to last until 520 events (deaths within 28 days) are observed. These events allow detection of a hazard ratio of 0.75, with 90% power and two-tailed type I error of 5%. All analysis will follow the intention-to-treat principle. Discussion: If the ART strategy with maximum recruitment and PEEP titration improves 28-day survival, this will represent a notable advance to the care of ARDS patients. Conversely, if the ART strategy is similar or inferior to the current evidence-based strategy (ARDSNet), this should also change current practice as many institutions routinely employ recruitment maneuvers and set PEEP levels according to some titration method.Hospital do Coracao (HCor) as part of the Program 'Hospitais de Excelencia a Servico do SUS (PROADI-SUS)'Brazilian Ministry of Healt

COMPORTAMENTO DOS PREÇOS DA MANGA EXPORTADA DO BRASIL: 2004-2012

Mais de 90% das exportações brasileiras de manga são provenientes do Submédio do Vale do São Francisco, região que produz a fruta em praticamente todos os meses do ano. O volume exportado pelo Brasil tem crescido nos últimos anos, sendo que dentre as frutas, a manga é a que gera a maior receita de exportação. Este trabalho tem por objetivo identificar e analisar os componentes de tendência e sazonalidade nos preços da manga exportada pelo Brasil com vistas à melhor compreensão de seu comportamento. Os dados utilizados foram obtidos no site AliceWeb2 do MDIC/SECEX, no período do primeiro trimestre de 2004 até o quarto trimestre de 2012. Constatou-se que a tendência apresenta um comportamento crescente e bastante significativo. Foi detectada sazonalidade determinística e estocástica. Assim, a série foi modelada por um SARIMA (4,1,1)x(0,1,3)2 , sendo observado o impacto negativo do efeito sazonal e também correlações negativas semestrais e anuais. ----- Over 90% of the Brazilian mango export is originated from the Submedio River Valley São Francisco, a region that produces the fruit in every month of the year. The volume exported by Brazil has grown in recent years, and among the fruits, the mango is the one that generates the most revenue from exports. This study aims to identify and analyze the tendency components and seasonality in the prices of mango exported by Brazil with a view to better understanding of their pattern. The data used were obtained from the website AliceWeb2 of MDIC/SECEX, during the first trimester 2004 to the fourth trimester 2012. It was found that the trend shows an increasing pattern and quite significant and was detected deterministic and stochastic seasonality. Therefore, the serie was modeled by SARIMA (4,1,1)x(0,1,3)2 and the negative impact of the seasonal effect and negative semiannual and annual correlations also were observed

Vigor da cultivar BMX Potência RR de soja durante o beneficiamento e períodos de armazenamento

Objetivou-se, com este trabalho, avaliar o vigor das sementes de soja durante as etapas do beneficiamento e ao longo do armazenamento. O experimento foi desenvolvido no Instituto Federal Goiano, Câmpus Rio Verde, e na empresa Sementes Goiás. Utilizou-se o delineamento inteiramente casualizado, segundo o esquema fatorial triplo 6 x 2 x 4 (seis etapas do beneficiamento, duas condições de armazenamento e quatro tempos de armazenamento) com três repetições. Foram utilizadas sementes de soja Glycine max (L.) Merrill, cultivar BMX Potência RR. As sementes foram avaliadas ao longo do armazenamento (0, 3, 6 e 9 meses) quanto ao teor de água, teste de tetrazólio e emergência em areia. Os dados foram analisados por meio de análise de variância e regressão adotando-se o nível de 0,05 de significância. Concluiu-se que o beneficiamento das sementes de soja não afetou a qualidade fisiológica das sementes e a cultivar BMX Potência RR apresentou qualidade fisiológica superior pelo teste tetrazólio (acima de 80%) apesar do vigor, germinação e emergência se apresentarem altos durante nove meses de armazenamento e o comprimento de raiz e de plantas jovens normais foi influenciado negativamente pelo tempo. Em câmara climatizada as sementes apresentam maior viabilidade dependendo do teor de água do produto