Spatial variability of grain yield of irrigated corn and its correlation with explanatory plant variables

Em decorrência da instabilidade da produtividade das principais culturas associada ao déficit hídrico, tem se tornado cada vez mais frequente a necessidade do uso de tecnologias como a irrigação e a agricultura de precisão (AP). O presente trabalho objetivou avaliar a variabilidade espacial da produtividade de grãos de milho e sua correlação com variáveis explicativas de planta em área irrigada. O estudo foi conduzido nas safras agrícolas 2010/2011 e 2011/2012, em área de 35ha, manejada em sistema plantio direto e irrigação por pivô central. Os componentes de produtividade e a produtividade de grãos foram avaliados seguindo uma malha amostral de 100x100m. A produtividade de grãos e a maior parte dos componentes de produtividade apresentaram baixa dispersão dos dados, condicionando a normalidade dos dados. A produtividade de grãos, mesmo com a irrigação, apresentou elevada variabilidade espacial. Na análise de trilha, verificaram-se altos coeficientes de determinação dos componentes de produtividade com a produtividade de grãos.Due to yield instability of main crops associated to drought, the use of technologies such irrigation and precision agriculture (PA) have been recently adopted in large scale. This study had the objective to assess the spatial variability of corn yield and its correlation with explanatory plant variables in an irrigated field. The study was carried out during the growing seasons 2010/2011 and 2011/2012, in an area of 35ha managed under notill and center-pivot irrigation. Corn yield and yield components were evaluated following a sampling grid of 100x100m. Grain yield and most yield components showed low dispersion data, resulting in data normality. Even under irrigation, corn yield showed high spatial variability. In path analysis, it was found high determination coefficients of corn yield with yield components

Determinants of intensive insulin therapeutic regimens in patients with type 1 diabetes: data from a nationwide multicenter survey in Brazil

Background: To evaluate the determinants of intensive insulin regimens (ITs) in patients with type 1 diabetes (T1D).Methods: This multicenter study was conducted between December 2008 and December 2010 in 28 public clinics in 20 Brazilian cities. Data were obtained from 3,591 patients (56.0% female, 57.1% Caucasian). Insulin regimens were classified as follows: group 1, conventional therapy (CT) (intermediate human insulin, one to two injections daily); group 2 (three or more insulin injections of intermediate plus regular human insulin); group 3 (three or more insulin injections of intermediate human insulin plus short-acting insulin analogues); group 4, basal-bolus (one or two insulin injections of long-acting plus short-acting insulin analogues or regular insulin); and group 5, basal-bolus with continuous subcutaneous insulin infusion (CSII). Groups 2 to 5 were considered IT groups.Results: We obtained complete data from 2,961 patients. Combined intermediate plus regular human insulin was the most used therapeutic regimen. CSII was used by 37 (1.2%) patients and IT by 2,669 (90.2%) patients. More patients on IT performed self-monitoring of blood glucose and were treated at the tertiary care level compared to CT patients (p < 0.001). the majority of patients from all groups had HbA1c levels above the target. Overweight or obesity was not associated with insulin regimen. Logistic regression analysis showed that economic status, age, ethnicity, and level of care were associated with IT (p < 0.001).Conclusions: Given the prevalence of intensive treatment for T1D in Brazil, more effective therapeutic strategies are needed for long term-health benefits.Farmanguinhos/Fundacao Oswaldo Cruz/National Health MinistryBrazilian Diabetes SocietyFundacao do Amparo a Pesquisa do Estado do Rio de JaneiroConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Univ Estado Rio de Janeiro, Unit Diabet, BR-20551030 Rio de Janeiro, BrazilBaurus Diabet Assoc, São Paulo, BrazilFed Univ São Paulo State, Diabet Unit, São Paulo, BrazilFed Univ Hosp Porto Alegre, Porto Alegre, BrazilUniv Hosp São Paulo, Diabet Unit, São Paulo, BrazilUniv Fed Rio de Janeiro, Rio de Janeiro, BrazilUniv Fed Ceara, Fortaleza, Ceara, BrazilSanta Casa Misericordia, Belo Horizonte, MG, BrazilSanta Casa Misericordia São Paulo, São Paulo, BrazilUniv Fed Amazonas, Manaus, Amazonas, BrazilHosp Geral de Bonsucesso, Rio de Janeiro, BrazilHosp Univ Clementino Fraga Filho IPPMG, Rio de Janeiro, BrazilUniv Hosp São Paulo, São Paulo, BrazilFac Ciencias Med Santa Casa São Paulo, São Paulo, BrazilUniv São Paulo, Inst Crianca, Hosp Clin, São Paulo, BrazilUniv São Paulo, Fac Med Ribeirao Preto, Hosp Clin, Ribeirao Preto, BrazilAmbulatorio Fac Estadual Med Sao Jose Rio Preto, Ribeirao Preto, BrazilEscola Paulista Med, Ctr Diabet, Ribeirao Preto, BrazilClin Endocrinol Santa Casa Belo Horizonte, Belo Horizonte, MG, BrazilUniv Estadual Londrina, Londrina, BrazilUniv Fed Parana, Hosp Clin, Porto Alegre, RS, BrazilInst Crianca Com Diabet Rio Grande Sul, Rio Grande Do Sul, RS, BrazilGrp Hosp Conceicao, Inst Crianca Com Diabet, Porto Alegre, RS, BrazilHosp Univ Santa Catarina, Florianopolis, SC, BrazilInst Diabet Endocrinol Joinville, Joinville, BrazilHosp Reg Taguatinga, Brasilia, DF, BrazilHosp Geral Goiania, Goiania, Go, BrazilCtr Diabet & Endocrinol Estado Bahia, Goiania, Go, BrazilUniv Fed Maranhao, Sao Luis, BrazilCtr Integrado Diabet & Hipertensao Ceara, Fortaleza, Ceara, BrazilUniv Fed Sergipe, Aracaju, BrazilHosp Univ Alcides Carneiro, Campina Grande, BrazilHosp Univ Joao de Barros Barreto, Belem, Para, BrazilFed Univ São Paulo State, Diabet Unit, São Paulo, BrazilUniv Hosp São Paulo, Diabet Unit, São Paulo, BrazilUniv Hosp São Paulo, São Paulo, BrazilEscola Paulista Med, Ctr Diabet, Ribeirao Preto, BrazilWeb of Scienc

Health-related quality of life in patients with type 1 diabetes mellitus in the different geographical regions of Brazil : data from the Brazilian Type 1 Diabetes Study Group

Background: In type 1 diabetes mellitus (T1DM) management, enhancing health-related quality of life (HRQoL) is as important as good metabolic control and prevention of secondary complications. This study aims to evaluate possible regional differences in HRQoL, demographic features and clinical characteristics of patients with T1DM in Brazil, a country of continental proportions, as well as investigate which variables could influence the HRQoL of these individuals and contribute to these regional disparities. Methods: This was a retrospective, cross-sectional, multicenter study performed by the Brazilian Type 1 Diabetes Study Group (BrazDiab1SG), by analyzing EuroQol scores from 3005 participants with T1DM, in 28 public clinics, among all geographical regions of Brazil. Data on demography, economic status, chronic complications, glycemic control and lipid profile were also collected. Results: We have found that the North-Northeast region presents a higher index in the assessment of the overall health status (EQ-VAS) compared to the Southeast (74.6 ± 30 and 70.4 ± 19, respectively; p < 0.05). In addition, North- Northeast presented a lower frequency of self-reported anxiety-depression compared to all regions of the country (North-Northeast: 1.53 ± 0.6; Southeast: 1.65 ± 0.7; South: 1.72 ± 0.7; Midwest: 1.67 ± 0.7; p < 0.05). These findings could not be entirely explained by the HbA1c levels or the other variables examined. Conclusions: Our study points to the existence of additional factors not yet evaluated that could be determinant in the HRQoL of people with T1DM and contribute to these regional disparities

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

Taking the pulse of Earth's tropical forests using networks of highly distributed plots

Tropical forests are the most diverse and productive ecosystems on Earth. While better understanding of these forests is critical for our collective future, until quite recently efforts to measure and monitor them have been largely disconnected. Networking is essential to discover the answers to questions that transcend borders and the horizons of funding agencies. Here we show how a global community is responding to the challenges of tropical ecosystem research with diverse teams measuring forests tree-by-tree in thousands of long-term plots. We review the major scientific discoveries of this work and show how this process is changing tropical forest science. Our core approach involves linking long-term grassroots initiatives with standardized protocols and data management to generate robust scaled-up results. By connecting tropical researchers and elevating their status, our Social Research Network model recognises the key role of the data originator in scientific discovery. Conceived in 1999 with RAINFOR (South America), our permanent plot networks have been adapted to Africa (AfriTRON) and Southeast Asia (T-FORCES) and widely emulated worldwide. Now these multiple initiatives are integrated via ForestPlots.net cyber-infrastructure, linking colleagues from 54 countries across 24 plot networks. Collectively these are transforming understanding of tropical forests and their biospheric role. Together we have discovered how, where and why forest carbon and biodiversity are responding to climate change, and how they feedback on it. This long-term pan-tropical collaboration has revealed a large long-term carbon sink and its trends, as well as making clear which drivers are most important, which forest processes are affected, where they are changing, what the lags are, and the likely future responses of tropical forests as the climate continues to change. By leveraging a remarkably old technology, plot networks are sparking a very modern revolution in tropical forest science. In the future, humanity can benefit greatly by nurturing the grassroots communities now collectively capable of generating unique, long-term understanding of Earth's most precious forests. Resumen Los bosques tropicales son los ecosistemas más diversos y productivos del mundo y entender su funcionamiento es crítico para nuestro futuro colectivo. Sin embargo, hasta hace muy poco, los esfuerzos para medirlos y monitorearlos han estado muy desconectados. El trabajo en redes es esencial para descubrir las respuestas a preguntas que trascienden las fronteras y los plazos de las agencias de financiamiento. Aquí mostramos cómo una comunidad global está respondiendo a los desafíos de la investigación en ecosistemas tropicales a través de diversos equipos realizando mediciones árbol por árbol en miles de parcelas permanentes de largo plazo. Revisamos los descubrimientos más importantes de este trabajo y discutimos cómo este proceso está cambiando la ciencia relacionada a los bosques tropicales. El enfoque central de nuestro esfuerzo implica la conexión de iniciativas locales de largo plazo con protocolos estandarizados y manejo de datos para producir resultados que se puedan trasladar a múltiples escalas. Conectando investigadores tropicales, elevando su posición y estatus, nuestro modelo de Red Social de Investigación reconoce el rol fundamental que tienen, para el descubrimiento científico, quienes generan o producen los datos. Concebida en 1999 con RAINFOR (Suramérica), nuestras redes de parcelas permanentes han sido adaptadas en África (AfriTRON) y el sureste asiático (T-FORCES) y ampliamente replicadas en el mundo. Actualmente todas estas iniciativas están integradas a través de la ciber-infraestructura de ForestPlots.net, conectando colegas de 54 países en 24 redes diferentes de parcelas. Colectivamente, estas redes están transformando nuestro conocimiento sobre los bosques tropicales y el rol de éstos en la biósfera. Juntos hemos descubierto cómo, dónde y porqué el carbono y la biodiversidad de los bosques tropicales está respondiendo al cambio climático y cómo se retroalimentan. Esta colaboración pan-tropical de largo plazo ha expuesto un gran sumidero de carbono y sus tendencias, mostrando claramente cuáles son los factores más importantes, qué procesos se ven afectados, dónde ocurren los cambios, los tiempos de reacción y las probables respuestas futuras mientras el clima continúa cambiando. Apalancando lo que realmente es una tecnología antigua, las redes de parcelas están generando una verdadera y moderna revolución en la ciencia tropical. En el futuro, la humanidad puede beneficiarse enormemente si se nutren y cultivan comunidades de investigadores de base, actualmente con la capacidad de generar información única y de largo plazo para entender los que probablemente son los bosques más preciados de la tierra. Resumo Florestas tropicais são os ecossistemas mais diversos e produtivos da Terra. Embora uma boa compreensão destas florestas seja crucial para o nosso futuro coletivo, até muito recentemente os esforços de medições e monitoramento foram amplamente desconexos. É essencial formarmos redes para obtermos respostas que transcendem fronteiras e horizontes de agências financiadoras. Neste estudo nós mostramos como uma comunidade global está respondendo aos desafios da pesquisa de ecossistemas tropicais, com equipes diversas medindo florestas, árvore por árvore, em milhares de parcelas monitoradas à longo prazo. Nós revisamos as maiores descobertas científicas deste trabalho, e mostramos também como este processo está mudando a ciência de florestas tropicais. Nossa abordagem principal envolve unir iniciativas de base a protocolos padronizados e gerenciamento de dados a fim de gerar resultados robustos em escalas ampliadas. Ao conectar pesquisadores tropicais e elevar seus status, nosso modelo de Rede de Pesquisa Social reconhece o papel-chave do produtor dos dados na descoberta científica. Concebida em 1999 com o RAINFOR (América do Sul), nossa rede de parcelas permanentes foi adaptada para África (AfriTRON) e Sudeste asiático (T-FORCES), e tem sido extensamente reproduzida em todo o mundo. Agora estas múltiplas iniciativas estão integradas através de uma infraestrutura cibernética do ForestPlots.net, conectando colegas de 54 países de 24 redes de parcelas. Estas iniciativas estão transformando coletivamente o entendimento das florestas tropicais e seus papéis na biosfera. Juntos nós descobrimos como, onde e por que o carbono e a biodiversidade da floresta estão respondendo às mudanças climáticas, e seus efeitos de retroalimentação. Esta duradoura colaboração pantropical revelou um grande sumidouro de carbono persistente e suas tendências, assim como tem evidenciado quais direcionadores são mais importantes, quais processos florestais são mais afetados, onde eles estão mudando, seus atrasos no tempo de resposta, e as prováveis respostas das florestas tropicais conforme o clima continua a mudar. Dessa forma, aproveitando uma notável tecnologia antiga, redes de parcelas acendem faíscas de uma moderna revolução na ciência das florestas tropicais. No futuro a humanidade pode se beneficiar incentivando estas comunidades basais que agora são coletivamente capazes de gerar conhecimentos únicos e duradouros sobre as florestas mais preciosas da Terra. Résume Les forêts tropicales sont les écosystèmes les plus diversifiés et les plus productifs de la planète. Si une meilleure compréhension de ces forêts est essentielle pour notre avenir collectif, jusqu'à tout récemment, les efforts déployés pour les mesurer et les surveiller ont été largement déconnectés. La mise en réseau est essentielle pour découvrir les réponses à des questions qui dépassent les frontières et les horizons des organismes de financement. Nous montrons ici comment une communauté mondiale relève les défis de la recherche sur les écosystèmes tropicaux avec diverses équipes qui mesurent les forêts arbre après arbre dans de milliers de parcelles permanentes. Nous passons en revue les principales découvertes scientifiques de ces travaux et montrons comment ce processus modifie la science des forêts tropicales. Notre approche principale consiste à relier les initiatives de base à long terme à des protocoles standardisés et une gestion de données afin de générer des résultats solides à grande échelle. En reliant les chercheurs tropicaux et en élevant leur statut, notre modèle de réseau de recherche sociale reconnaît le rôle clé de l'auteur des données dans la découverte scientifique. Conçus en 1999 avec RAINFOR (Amérique du Sud), nos réseaux de parcelles permanentes ont été adaptés à l'Afrique (AfriTRON) et à l'Asie du Sud-Est (T-FORCES) et largement imités dans le monde entier. Ces multiples initiatives sont désormais intégrées via l'infrastructure ForestPlots.net, qui relie des collègues de 54 pays à travers 24 réseaux de parcelles. Ensemble, elles transforment la compréhension des forêts tropicales et de leur rôle biosphérique. Ensemble, nous avons découvert comment, où et pourquoi le carbone forestier et la biodiversité réagissent au changement climatique, et comment ils y réagissent. Cette collaboration pan-tropicale à long terme a révélé un important puits de carbone à long terme et ses tendances, tout en mettant en évidence les facteurs les plus importants, les processus forestiers qui sont affectés, les endroits où ils changent, les décalages et les réactions futures probables des forêts tropicales à mesure que le climat continue de changer. En tirant parti d'une technologie remarquablement ancienne, les réseaux de parcelles déclenchent une révolution très moderne dans la science des forêts tropicales. À l'avenir, l'humanité pourra grandement bénéficier du soutien des communautés de base qui sont maintenant collectivement capables de générer une compréhension unique et à long terme des forêts les plus précieuses de la Terre. Abstrak Hutan tropika adalah di antara ekosistem yang paling produktif dan mempunyai kepelbagaian biodiversiti yang tinggi di seluruh dunia. Walaupun pemahaman mengenai hutan tropika amat penting untuk masa depan kita, usaha-usaha untuk mengkaji dan mengawas hutah-hutan tersebut baru sekarang menjadi lebih diperhubungkan. Perangkaian adalah sangat penting untuk mencari jawapan kepada soalan-soalan yang menjangkaui sempadan dan batasan agensi pendanaan. Di sini kami menunjukkan bagaimana sebuah komuniti global bertindak balas terhadap cabaran penyelidikan ekosistem tropika melalui penglibatan pelbagai kumpulan yang mengukur hutan secara pokok demi pokok dalam beribu-ribu plot jangka panjang. Kami meninjau semula penemuan saintifik utama daripada kerja ini dan menunjukkan bagaimana proses ini sedang mengubah bidang sains hutan tropika. Teras pendekatan kami memberi tumpuan terhadap penghubungan inisiatif akar umbi jangka panjang dengan protokol standar serta pengurusan data untuk mendapatkan hasil skala besar yang kukuh. Dengan menghubungkan penyelidik-penyelidik tropika dan meningkatkan status mereka, model Rangkaian Penyelidikan Sosial kami mengiktiraf kepentingan peranan pengasas data dalam penemuan saintifik. Bermula dengan pengasasan RAINFOR (Amerika Selatan) pada tahun 1999, rangkaian-rangkaian plot kekal kami kemudian disesuaikan untuk Afrika (AfriTRON) dan Asia Tenggara (T-FORCES) dan selanjutnya telah banyak dicontohi di seluruh dunia. Kini, inisiatif-inisiatif tersebut disepadukan melalui infrastruktur siber ForestPlots.net yang menghubungkan rakan sekerja dari 54 negara di 24 buah rangkaian plot. Secara kolektif, rangkaian ini sedang mengubah pemahaman tentang hutan tropika dan peranannya dalam biosfera. Kami telah bekerjasama untuk menemukan bagaimana, di mana dan mengapa karbon serta biodiversiti hutan bertindak balas terhadap perubahan iklim dan juga bagaimana mereka saling bermaklum balas. Kolaborasi pan-tropika jangka panjang ini telah mendedahkan sebuah sinki karbon jangka panjang serta arah alirannya dan juga menjelaskan pemandu-pemandu perubahan yang terpenting, di mana dan bagaimana proses hutan terjejas, masa susul yang ada dan kemungkinan tindakbalas hutan tropika pada perubahan iklim secara berterusan di masa depan. Dengan memanfaatkan pendekatan lama, rangkaian plot sedang menyalakan revolusi yang amat moden dalam sains hutan tropika. Pada masa akan datang, manusia sejagat akan banyak mendapat manfaat jika memupuk komuniti-komuniti akar umbi yang kini berkemampuan secara kolektif menghasilkan pemahaman unik dan jangka panjang mengenai hutan-hutan yang paling berharga di dunia

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