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

Spatial and temporal analysis of stem bleeding disease in coconut palm in the state of sergipe, Brazil

ABSTRACT Stem bleeding disease (resinosis) of coconut palm is caused by Thielaviopsis paradoxa and is very important in the state of Sergipe, Brazil. Understanding the epidemiological behavior of the disease is essential for establishing more efficient control strategies. Thus, we characterized the temporal progression and spatial distribution of stem bleeding in a commercial orchard under conditions of natural infection in the area of Neopolis, Sergipe. Three plots with 729 plants each were selected and evaluated every two months for stem bleeding incidence. In the temporal analysis, the monomolecular model gave the best fit to data on disease incidence, as it accurately showed the temporal dynamics of the disease during the experiment period. The spatial pattern of stem bleeding varied over time, with initial infections presenting random pattern and then evolving to aggregate pattern during evaluations. This indicates that the disease may have originated from the pathogen survival structures, followed by auto infections caused by dissemination from plant to plant, either by humans, by contact between roots, or by the vector Rhynchophorus palmarum

Análise do crescimento de mudas de jatobá (Hymenaea courbaril L.) em diferentes níveis de água no solo

O objetivo deste trabalho foi analisar o crescimento de mudas de jatobá (Hymenaea courbaril L.) sob déficit hídrico. As plantas foram cultivadas em vasos contendo 8 kg de solo oriundo do local de coleta das sementes. Foram utilizados blocos casualizados como delineamento experimental, com quatro tratamentos hídricos (100%, 75%, 50% e 25% da capacidade de pote) e seis repetições. Semanalmente foram avaliados a altura das plantas, o número de folhas e o diâmetro do caule. No final do período experimental, foram determinados a área foliar, a razão de área foliar e a área foliar específica, a produção de matéria seca das folhas, do caule, das raízes e total, e a alocação de biomassa para as folhas, o caule e as raízes. Verificou-se que o déficit hídrico afetou o crescimento das plantas quanto à altura, ao diâmetro do caule e à produção de matéria seca para os diversos órgãos, quando cultivadas em níveis a partir de 50% da CP. O número de folhas reduziu-se em todos os níveis de estresse, quando comparados com o tratamento 100% da CP. O padrão de alocação de biomassa, a relação raiz/parte aérea, razão de área foliar e área foliar específica, mas, não foram afetados pelo estresse. O número de folhas foi a variável mais sensível ao estresse. Mudas de jatobá não paralisaram o seu crescimento quando cultivadas com baixa disponibilidade de água no solo, na fase inicial do desenvolvimento. No entanto, seu crescimento foi severamente afetado em níveis de água abaixo de 50% da capacidade de retenção de água no solo

Effect of lung recruitment and titrated Positive End-Expiratory Pressure (PEEP) vs low PEEP on mortality in patients with acute respiratory distress syndrome - A randomized clinical trial

IMPORTANCE: The effects of recruitment maneuvers and positive end-expiratory pressure (PEEP) titration on clinical outcomes in patients with acute respiratory distress syndrome (ARDS) remain uncertain. OBJECTIVE: To determine if lung recruitment associated with PEEP titration according to the best respiratory-system compliance decreases 28-day mortality of patients with moderate to severe ARDS compared with a conventional low-PEEP strategy. DESIGN, SETTING, AND PARTICIPANTS: Multicenter, randomized trial conducted at 120 intensive care units (ICUs) from 9 countries from November 17, 2011, through April 25, 2017, enrolling adults with moderate to severe ARDS. INTERVENTIONS: An experimental strategy with a lung recruitment maneuver and PEEP titration according to the best respiratory-system compliance (n = 501; experimental group) or a control strategy of low PEEP (n = 509). All patients received volume-assist control mode until weaning. MAIN OUTCOMES AND MEASURES: The primary outcome was all-cause mortality until 28 days. Secondary outcomes were length of ICU and hospital stay; ventilator-free days through day 28; pneumothorax requiring drainage within 7 days; barotrauma within 7 days; and ICU, in-hospital, and 6-month mortality. RESULTS: A total of 1010 patients (37.5% female; mean [SD] age, 50.9 [17.4] years) were enrolled and followed up. At 28 days, 277 of 501 patients (55.3%) in the experimental group and 251 of 509 patients (49.3%) in the control group had died (hazard ratio [HR], 1.20; 95% CI, 1.01 to 1.42; P = .041). Compared with the control group, the experimental group strategy increased 6-month mortality (65.3% vs 59.9%; HR, 1.18; 95% CI, 1.01 to 1.38; P = .04), decreased the number of mean ventilator-free days (5.3 vs 6.4; difference, −1.1; 95% CI, −2.1 to −0.1; P = .03), increased the risk of pneumothorax requiring drainage (3.2% vs 1.2%; difference, 2.0%; 95% CI, 0.0% to 4.0%; P = .03), and the risk of barotrauma (5.6% vs 1.6%; difference, 4.0%; 95% CI, 1.5% to 6.5%; P = .001). There were no significant differences in the length of ICU stay, length of hospital stay, ICU mortality, and in-hospital mortality. CONCLUSIONS AND RELEVANCE: In patients with moderate to severe ARDS, a strategy with lung recruitment and titrated PEEP compared with low PEEP increased 28-day all-cause mortality. These findings do not support the routine use of lung recruitment maneuver and PEEP titration in these patients. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT01374022