Estimación de la demanda hídrica del trigo y sorgo en el Estado de México mediante la recalibración de KT

En este estudio se realizó la estimación de la demanda hídrica del trigo y sorgo en el Estado de México mediante la recalibración del coeficiente KT, para la estimación de la evpotranspiración de referencia (ETo). Debido a que el método recomendado por la FAO es el de Penman-Monteith y a veces las variables necesarias son escasas, la tendencia es usar métodos más simples como el método del Tanque Evaporímetro. Debido a esto, el objetivo de esta investigación se centra en la recalibración del coeficiente KT para la estimación de ETo y determinar el déficit hídrico del trigo y sorgo de forma espacial para el Estado de México, a través de la implementación de la base de datos meteorológicos de CONAGUA- SMN. La comparación de los métodos fue realizada mediante la desviación estándar del error, índice de correspondencia y el cociente entre ambas estimaciones de ETo. Los resultados indican que el déficit hídrico promedio para el cultivo de trigo y sorgo fue de 88 mm y 10 mm, para el periodo mayo-septiembre y mayo-agosto, respectivamente. Además, el método del Tanque Evaporímetro recalibrado mediante su coeficiente KT, puede ser utilizado para estimar ETo y disminuir la sobreestimación o subestimación del método

Contributions of mean and shape of blood pressure distribution to worldwide trends and variations in raised blood pressure: A pooled analysis of 1018 population-based measurement studies with 88.6 million participants

© The Author(s) 2018. Background: Change in the prevalence of raised blood pressure could be due to both shifts in the entire distribution of blood pressure (representing the combined effects of public health interventions and secular trends) and changes in its high-blood-pressure tail (representing successful clinical interventions to control blood pressure in the hypertensive population). Our aim was to quantify the contributions of these two phenomena to the worldwide trends in the prevalence of raised blood pressure. Methods: We pooled 1018 population-based studies with blood pressure measurements on 88.6 million participants from 1985 to 2016. We first calculated mean systolic blood pressure (SBP), mean diastolic blood pressure (DBP) and prevalence of raised blood pressure by sex and 10-year age group from 20-29 years to 70-79 years in each study, taking into account complex survey design and survey sample weights, where relevant. We used a linear mixed effect model to quantify the association between (probittransformed) prevalence of raised blood pressure and age-group- and sex-specific mean blood pressure. We calculated the contributions of change in mean SBP and DBP, and of change in the prevalence-mean association, to the change in prevalence of raised blood pressure. Results: In 2005-16, at the same level of population mean SBP and DBP, men and women in South Asia and in Central Asia, the Middle East and North Africa would have the highest prevalence of raised blood pressure, and men and women in the highincome Asia Pacific and high-income Western regions would have the lowest. In most region-sex-age groups where the prevalence of raised blood pressure declined, one half or more of the decline was due to the decline in mean blood pressure. Where prevalence of raised blood pressure has increased, the change was entirely driven by increasing mean blood pressure, offset partly by the change in the prevalence-mean association. Conclusions: Change in mean blood pressure is the main driver of the worldwide change in the prevalence of raised blood pressure, but change in the high-blood-pressure tail of the distribution has also contributed to the change in prevalence, especially in older age groups

Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants.

BACKGROUND: Hypertension can be detected at the primary health-care level and low-cost treatments can effectively control hypertension. We aimed to measure the prevalence of hypertension and progress in its detection, treatment, and control from 1990 to 2019 for 200 countries and territories. METHODS: We used data from 1990 to 2019 on people aged 30-79 years from population-representative studies with measurement of blood pressure and data on blood pressure treatment. We defined hypertension as having systolic blood pressure 140 mm Hg or greater, diastolic blood pressure 90 mm Hg or greater, or taking medication for hypertension. We applied a Bayesian hierarchical model to estimate the prevalence of hypertension and the proportion of people with hypertension who had a previous diagnosis (detection), who were taking medication for hypertension (treatment), and whose hypertension was controlled to below 140/90 mm Hg (control). The model allowed for trends over time to be non-linear and to vary by age. FINDINGS: The number of people aged 30-79 years with hypertension doubled from 1990 to 2019, from 331 (95% credible interval 306-359) million women and 317 (292-344) million men in 1990 to 626 (584-668) million women and 652 (604-698) million men in 2019, despite stable global age-standardised prevalence. In 2019, age-standardised hypertension prevalence was lowest in Canada and Peru for both men and women; in Taiwan, South Korea, Japan, and some countries in western Europe including Switzerland, Spain, and the UK for women; and in several low-income and middle-income countries such as Eritrea, Bangladesh, Ethiopia, and Solomon Islands for men. Hypertension prevalence surpassed 50% for women in two countries and men in nine countries, in central and eastern Europe, central Asia, Oceania, and Latin America. Globally, 59% (55-62) of women and 49% (46-52) of men with hypertension reported a previous diagnosis of hypertension in 2019, and 47% (43-51) of women and 38% (35-41) of men were treated. Control rates among people with hypertension in 2019 were 23% (20-27) for women and 18% (16-21) for men. In 2019, treatment and control rates were highest in South Korea, Canada, and Iceland (treatment >70%; control >50%), followed by the USA, Costa Rica, Germany, Portugal, and Taiwan. Treatment rates were less than 25% for women and less than 20% for men in Nepal, Indonesia, and some countries in sub-Saharan Africa and Oceania. Control rates were below 10% for women and men in these countries and for men in some countries in north Africa, central and south Asia, and eastern Europe. Treatment and control rates have improved in most countries since 1990, but we found little change in most countries in sub-Saharan Africa and Oceania. Improvements were largest in high-income countries, central Europe, and some upper-middle-income and recently high-income countries including Costa Rica, Taiwan, Kazakhstan, South Africa, Brazil, Chile, Turkey, and Iran. INTERPRETATION: Improvements in the detection, treatment, and control of hypertension have varied substantially across countries, with some middle-income countries now outperforming most high-income nations. The dual approach of reducing hypertension prevalence through primary prevention and enhancing its treatment and control is achievable not only in high-income countries but also in low-income and middle-income settings. FUNDING: WHO

Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants

Background Hypertension can be detected at the primary health-care level and low-cost treatments can effectively control hypertension. We aimed to measure the prevalence of hypertension and progress in its detection, treatment, and control from 1990 to 2019 for 200 countries and territories. Methods We used data from 1990 to 2019 on people aged 30-79 years from population-representative studies with measurement of blood pressure and data on blood pressure treatment. We defined hypertension as having systolic blood pressure 140 mm Hg or greater, diastolic blood pressure 90 mm Hg or greater, or taking medication for hypertension. We applied a Bayesian hierarchical model to estimate the prevalence of hypertension and the proportion of people with hypertension who had a previous diagnosis (detection), who were taking medication for hypertension (treatment), and whose hypertension was controlled to below 140/90 mm Hg (control). The model allowed for trends over time to be non-linear and to vary by age. Findings The number of people aged 30-79 years with hypertension doubled from 1990 to 2019, from 331 (95% credible interval 306-359) million women and 317 (292-344) million men in 1990 to 626 (584-668) million women and 652 (604-698) million men in 2019, despite stable global age-standardised prevalence. In 2019, age-standardised hypertension prevalence was lowest in Canada and Peru for both men and women; in Taiwan, South Korea, Japan, and some countries in western Europe including Switzerland, Spain, and the UK for women; and in several low-income and middle-income countries such as Eritrea, Bangladesh, Ethiopia, and Solomon Islands for men. Hypertension prevalence surpassed 50% for women in two countries and men in nine countries, in central and eastern Europe, central Asia, Oceania, and Latin America. Globally, 59% (55-62) of women and 49% (46-52) of men with hypertension reported a previous diagnosis of hypertension in 2019, and 47% (43-51) of women and 38% (35-41) of men were treated. Control rates among people with hypertension in 2019 were 23% (20-27) for women and 18% (16-21) for men. In 2019, treatment and control rates were highest in South Korea, Canada, and Iceland (treatment >70%; control >50%), followed by the USA, Costa Rica, Germany, Portugal, and Taiwan. Treatment rates were less than 25% for women and less than 20% for men in Nepal, Indonesia, and some countries in sub-Saharan Africa and Oceania. Control rates were below 10% for women and men in these countries and for men in some countries in north Africa, central and south Asia, and eastern Europe. Treatment and control rates have improved in most countries since 1990, but we found little change in most countries in sub-Saharan Africa and Oceania. Improvements were largest in high-income countries, central Europe, and some upper-middle-income and recently high-income countries including Costa Rica, Taiwan, Kazakhstan, South Africa, Brazil, Chile, Turkey, and Iran. Interpretation Improvements in the detection, treatment, and control of hypertension have varied substantially across countries, with some middle-income countries now outperforming most high-income nations. The dual approach of reducing hypertension prevalence through primary prevention and enhancing its treatment and control is achievable not only in high-income countries but also in low-income and middle-income settings. Copyright (C) 2021 World Health Organization; licensee Elsevier

Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants

Background Hypertension can be detected at the primary health-care level and low-cost treatments can effectively control hypertension. We aimed to measure the prevalence of hypertension and progress in its detection, treatment, and control from 1990 to 2019 for 200 countries and territories. Methods We used data from 1990 to 2019 on people aged 30–79 years from population-representative studies with measurement of blood pressure and data on blood pressure treatment. We defined hypertension as having systolic blood pressure 140 mm Hg or greater, diastolic blood pressure 90 mm Hg or greater, or taking medication for hypertension. We applied a Bayesian hierarchical model to estimate the prevalence of hypertension and the proportion of people with hypertension who had a previous diagnosis (detection), who were taking medication for hypertension (treatment), and whose hypertension was controlled to below 140/90 mm Hg (control). The model allowed for trends over time to be non-linear and to vary by age. Findings The number of people aged 30–79 years with hypertension doubled from 1990 to 2019, from 331 (95% credible interval 306–359) million women and 317 (292–344) million men in 1990 to 626 (584–668) million women and 652 (604–698) million men in 2019, despite stable global age-standardised prevalence. In 2019, age-standardised hypertension prevalence was lowest in Canada and Peru for both men and women; in Taiwan, South Korea, Japan, and some countries in western Europe including Switzerland, Spain, and the UK for women; and in several low-income and middle-income countries such as Eritrea, Bangladesh, Ethiopia, and Solomon Islands for men. Hypertension prevalence surpassed 50% for women in two countries and men in nine countries, in central and eastern Europe, central Asia, Oceania, and Latin America. Globally, 59% (55–62) of women and 49% (46–52) of men with hypertension reported a previous diagnosis of hypertension in 2019, and 47% (43–51) of women and 38% (35–41) of men were treated. Control rates among people with hypertension in 2019 were 23% (20–27) for women and 18% (16–21) for men. In 2019, treatment and control rates were highest in South Korea, Canada, and Iceland (treatment >70%; control >50%), followed by the USA, Costa Rica, Germany, Portugal, and Taiwan. Treatment rates were less than 25% for women and less than 20% for men in Nepal, Indonesia, and some countries in sub-Saharan Africa and Oceania. Control rates were below 10% for women and men in these countries and for men in some countries in north Africa, central and south Asia, and eastern Europe. Treatment and control rates have improved in most countries since 1990, but we found little change in most countries in sub-Saharan Africa and Oceania. Improvements were largest in high-income countries, central Europe, and some upper-middle-income and recently high-income countries including Costa Rica, Taiwan, Kazakhstan, South Africa, Brazil, Chile, Turkey, and Iran. Interpretation Improvements in the detection, treatment, and control of hypertension have varied substantially across countries, with some middle-income countries now outperforming most high-income nations. The dual approach of reducing hypertension prevalence through primary prevention and enhancing its treatment and control is achievable not only in high-income countries but also in low-income and middle-income settings

Global variations in diabetes mellitus based on fasting glucose and haemogloblin A1c

Fasting plasma glucose (FPG) and haemoglobin A1c (HbA1c) are both used to diagnose diabetes, but may identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening had elevated FPG, HbA1c, or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardised proportion of diabetes that was previously undiagnosed, and detected in survey screening, ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the agestandardised proportion who had elevated levels of both FPG and HbA1c was 29-39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global gap in diabetes diagnosis and surveillance.peer-reviewe

Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants

Background Hypertension can be detected at the primary health-care level and low-cost treatments can effectively control hypertension. We aimed to measure the prevalence of hypertension and progress in its detection, treatment, and control from 1990 to 2019 for 200 countries and territories. Methods We used data from 1990 to 2019 on people aged 30–79 years from population-representative studies with measurement of blood pressure and data on blood pressure treatment. We defined hypertension as having systolic blood pressure 140 mm Hg or greater, diastolic blood pressure 90 mm Hg or greater, or taking medication for hypertension. We applied a Bayesian hierarchical model to estimate the prevalence of hypertension and the proportion of people with hypertension who had a previous diagnosis (detection), who were taking medication for hypertension (treatment), and whose hypertension was controlled to below 140/90 mm Hg (control). The model allowed for trends over time to be non-linear and to vary by age. Findings The number of people aged 30–79 years with hypertension doubled from 1990 to 2019, from 331 (95% credible interval 306–359) million women and 317 (292–344) million men in 1990 to 626 (584–668) million women and 652 (604–698) million men in 2019, despite stable global age-standardised prevalence. In 2019, age-standardised hypertension prevalence was lowest in Canada and Peru for both men and women; in Taiwan, South Korea, Japan, and some countries in western Europe including Switzerland, Spain, and the UK for women; and in several low-income and middle-income countries such as Eritrea, Bangladesh, Ethiopia, and Solomon Islands for men. Hypertension prevalence surpassed 50% for women in two countries and men in nine countries, in central and eastern Europe, central Asia, Oceania, and Latin America. Globally, 59% (55–62) of women and 49% (46–52) of men with hypertension reported a previous diagnosis of hypertension in 2019, and 47% (43–51) of women and 38% (35–41) of men were treated. Control rates among people with hypertension in 2019 were 23% (20–27) for women and 18% (16–21) for men. In 2019, treatment and control rates were highest in South Korea, Canada, and Iceland (treatment >70%; control >50%), followed by the USA, Costa Rica, Germany, Portugal, and Taiwan. Treatment rates were less than 25% for women and less than 20% for men in Nepal, Indonesia, and some countries in sub-Saharan Africa and Oceania. Control rates were below 10% for women and men in these countries and for men in some countries in north Africa, central and south Asia, and eastern Europe. Treatment and control rates have improved in most countries since 1990, but we found little change in most countries in sub-Saharan Africa and Oceania. Improvements were largest in high-income countries, central Europe, and some upper-middle-income and recently high-income countries including Costa Rica, Taiwan, Kazakhstan, South Africa, Brazil, Chile, Turkey, and Iran. Interpretation Improvements in the detection, treatment, and control of hypertension have varied substantially across countries, with some middle-income countries now outperforming most high-income nations. The dual approach of reducing hypertension prevalence through primary prevention and enhancing its treatment and control is achievable not only in high-income countries but also in low-income and middle-income settings

Trends in cardiometabolic risk factors in the Americas between 1980 and 2014: a pooled analysis of population-based surveys

Background: Describing the prevalence and trends of cardiometabolic risk factors that are associated with noncommunicable diseases (NCDs) is crucial for monitoring progress, planning prevention, and providing evidence to support policy efforts. We aimed to analyse the transition in body-mass index (BMI), obesity, blood pressure, raised blood pressure, and diabetes in the Americas, between 1980 and 2014. Methods: We did a pooled analysis of population-based studies with data on anthropometric measurements, biomarkers for diabetes, and blood pressure from adults aged 18 years or older. A Bayesian model was used to estimate trends in BMI, raised blood pressure (systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg), and diabetes (fasting plasma glucose ≥7•0 mmol/L, history of diabetes, or diabetes treatment) from 1980 to 2014, in 37 countries and six subregions of the Americas. Findings: 389 population-based surveys from the Americas were available. Comparing prevalence estimates from 2014 with those of 1980, in the non-English speaking Caribbean subregion, the prevalence of obesity increased from 3•9% (95% CI 2•2–6•3) in 1980, to 18•6% (14•3–23•3) in 2014, in men; and from 12•2% (8•2–17•0) in 1980, to 30•5% (25•7–35•5) in 2014, in women. The English-speaking Caribbean subregion had the largest increase in the prevalence of diabetes, from 5•2% (2•1–10•4) in men and 6•4% (2•6–10•4) in women in 1980, to 11•1% (6•4–17•3) in men and 13•6% (8•2–21•0) in women in 2014). Conversely, the prevalence of raised blood pressure has decreased in all subregions; the largest decrease was found in North America from 27•6% (22•3–33•2) in men and 19•9% (15•8–24•4) in women in 1980, to 15•5% (11•1–20•9) in men and 10•7% (7•7–14•5) in women in 2014. Interpretation: Despite the generally high prevalence of cardiometabolic risk factors across the Americas, estimates also showed a high level of heterogeneity in the transition between countries. The increasing prevalence of obesity and diabetes observed over time requires appropriate measures to deal with these public health challenges. Our results support a diversification of health interventions across subregions and countries.Fil: Miranda, J. Jaime. Universidad Peruana Cayetano Heredia; PerúFil: Carrillo-Larco, Rodrigo M.. Imperial College London; Reino UnidoFil: Ferreccio, Catterina. Pontificia Universidad Católica de Chile; ChileFil: Hambleton, Ian R.. The University Of The West Indies; BarbadosFil: Lotufo, Paulo A.. Universidade de Sao Paulo; BrasilFil: Nieto-Martinez, Ramfis. Miami Veterans Affairs Healthcare System; Estados UnidosFil: Zhou, Bin. Imperial College London; Reino UnidoFil: Bentham, James. University Of Kent; Reino UnidoFil: Bixby, Honor. Imperial College London; Reino UnidoFil: Hajifathalian, Kaveh. Cleveland Clinic; Estados UnidosFil: Lu, Yuan. University of Yale; Estados UnidosFil: Taddei, Cristina. Imperial College London; Reino UnidoFil: Abarca-Gomez, Leandra. Caja Costarricense de Seguro Social; Costa RicaFil: Acosta-Cazares, Benjamin. Instituto Mexicano del Seguro Social; MéxicoFil: Aguilar-Salinas, Carlos A.. (Instituto Nacional de Ciencias Médicas y Nutrición; MéxicoFil: Andrade, Dolores S.. Universidad de Cuenca; EcuadorFil: Assunção, Maria Cecilia F.. Universidade Federal de Pelotas; BrasilFil: Barcelo, Alberto. Pan American Health Organization; Estados UnidosFil: Barros, Aluisio J.D.. Universidade Federal de Pelotas; BrasilFil: Barros, Mauro V.G.. Universidade de Pernambuco; BrasilFil: Bata, Iqbal. Dalhousie University Halifax; CanadáFil: Batista, Rosangela L.. Universidade Federal Do Maranhao; BrasilFil: Benet, Mikhail. Cafam University Foundation; ColombiaFil: Bernabe-Ortiz, Antonio. Universidad Peruana Cayetano Heredia; PerúFil: Bettiol, Heloisa. Universidade de Sao Paulo; BrasilFil: Boggia, Jose G.. Universidad de la Republica; UruguayFil: Boissonnet, Carlos P.. Centro de Educación Médica e Investigaciones Clínicas; ArgentinaFil: Brewster, Lizzy M.. University of Amsterdam; Países BajosFil: Cameron, Christine. Canadian Fitness and Lifestyle Research Institute; CanadáFil: Cândido, Ana Paula C.. Universidade Federal de Juiz de Fora; BrasilFil: Cardoso, Viviane C.. Universidade de Sao Paulo; BrasilFil: Chan, Queenie. Imperial College London; Reino UnidoFil: Christofaro, Diego G.. Universidade Estadual Paulista; BrasilFil: Confortin, Susana C.. Universidade Federal de Santa Catarina; BrasilFil: Craig, Cora L.. Canadian Fitness and Lifestyle Research Institute; CanadáFil: d'Orsi, Eleonora. Universidade Federal de Santa Catarina; BrasilFil: Delisle, Hélène. University of Montreal; CanadáFil: De Oliveira, Paula Duarte. Universidade Federal de Pelotas; BrasilFil: Dias-da-Costa, Juvenal Soares. Universidade do Vale do Rio Dos Sinos; BrasilFil: Diaz, Alberto Alejandro. Universidad Nacional del Centro de la Provincia de Buenos Aires. Escuela Superior de Ciencias de la Salud. Instituto de Investigación en Ciencias de la Salud; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Provincia de Buenos Aires. Municipalidad de Tandil. Hospital Municipal Ramón Santamarina; ArgentinaFil: Donoso, Silvana P.. Universidad de Cuenca; EcuadorFil: Elliott, Paul. Imperial College London; Reino UnidoFil: Escobedo-de La Peña, Jorge. Instituto Mexicano del Seguro Social; MéxicoFil: Ferguson, Trevor S.. The University of The West Indies; JamaicaFil: Fernandes, Romulo A.. Universidade Estadual Paulista; BrasilFil: Ferrante, Daniel. Ministerio de Salud; ArgentinaFil: Flores, Eric Monterubio. Instituto Nacional de Salud Pública; MéxicoFil: Francis, Damian K.. The University of The West Indies; JamaicaFil: Do Carmo Franco, Maria. Universidade Federal de Sao Paulo; BrasilFil: Fuchs, Flavio D.. Hospital de Clinicas de Porto Alegre; BrasilFil: Fuchs, Sandra C.. Universidade Federal do Rio Grande do Sul; BrasilFil: Goltzman, David. Université McGill; CanadáFil: Gonçalves, Helen. Universidade Federal de Pelotas; BrasilFil: Gonzalez-Rivas, Juan P.. The Andes Clinic Of Cardio-Metabolic Studies; VenezuelaFil: Gorbea, Mariano Bonet. Instituto Nacional de Higiene, Epidemiología y Microbiología; CubaFil: Gregor, Ronald D.. Dalhousie University Halifax; CanadáFil: Guerrero, Ramiro. Universidad Icesi; ColombiaFil: Guimaraes, Andre L.. Universidade Estadual de Montes Claros; BrasilFil: Gulliford, Martin C.. King’s College London; Reino UnidoFil: Gutierrez, Laura. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Hernandez Cadena, Leticia. Instituto Nacional de Salud Pública; MéxicoFil: Herrera, Víctor M.. (Universidad Autónoma de Bucaramanga; ColombiaFil: Hopman, Wilma M.. Kingston General Hospital; CanadáFil: Horimoto, Andrea RVR. Instituto do Coração; BrasilFil: Hormiga, Claudia M.. Fundación Oftalmológica de Santander; ColombiaFil: Horta, Bernardo L.. Universidade Federal de Pelotas; BrasilFil: Howitt, Christina. The University of the West Indies; BarbadosFil: Irazola, Wilma E.. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Jiménez-Acosta, Santa Magaly. Instituto Nacional de Higiene, Epidemiología y Microbiología; CubaFil: Joffres, Michel. Simon Fraser University; CanadáFil: Kolsteren, Patricia. (Institute of Tropical Medicine; BélgicaFil: Landrove, Orlando. Ministerio de Salud Pública; CubaFil: Li, Yanping. Harvard TH Chan School of Public Health; Estados UnidosFil: Lilly, Christa L.. West Virginia University; Estados UnidosFil: Lima-Costa, M. Fernanda. Fundação Oswaldo Cruz; BrasilFil: Louzada Strufaldi, Maria Wany. Universidade Federal de Sao Paulo; BrasilFil: Machado-Coelho, George L. L.. Universidade Federal de Ouro Preto; BrasilFil: Makdisse, Marcia. Hospital Israelita Albert Einstein; BrasilFil: Margozzini, Paula. Pontificia Universidad Católica de Chile; ChileFil: Pruner Marques, Larissa. Universidade Federal de Santa Catarina; BrasilFil: Martorell, Reynaldo. Emory University; Estados UnidosFil: Mascarenhas, Luis. Universidade Federal do Paraná; BrasilFil: Matijasevich, Alicia. Universidade Federal de Sao Paulo; BrasilFil: Mc Donald Posso, Anselmo J.. Gorgas Memorial Institute of Health Studies; PanamáFil: McFarlane, Shelly R.. The University of the West Indies; JamaicaFil: McLean, Scott B.. (Statistics Canada; CanadáFil: Menezes, Ana Maria B.. Universidade Federal de Pelotas; BrasilFil: Miquel, Juan Francisco. Pontificia Universidad Católica de Chile; ChileFil: Mohanna, Salim. Universidad Peruana Cayetano Heredia; PerúFil: Monterrubio, Eric A.. Instituto Nacional de Salud Pública; MéxicoFil: Moreira, Leila B.. Universidade Federal do Rio Grande do Sul; BrasilFil: Morejon, Alain. Universidad de Ciencias Médicas; CubaFil: Motta, Jorge. Gorgas Memorial Institute of Public Health; PanamáFil: Neal, William A.. West Virginia University; Estados UnidosFil: Nervi, Flavio. Pontificia Universidad Católica de Chile; ChileFil: Noboa, Oscar A.. Universidad de la República; UruguayFil: Ochoa-Avilés, Angélica M.. Universidad de Cuenca; EcuadorFil: Olinto, Maria Teresa Anselmo. Universidad de Vale do Rio dos Sinos; BrasilFil: Oliveira, Isabel O.. Universidade Federal de Pelotas; BrasilFil: Ono, Lariane M.. Universidade Federal de Santa Catarina; BrasilFil: Ordunez, Pedro. Pan American Health Organization; Estados UnidosFil: Ortiz, Ana P.. Universidad de Puerto Rico; Puerto RicoFil: Otero, Johanna A.. Fundación Oftalmológica de Santander; ColombiaFil: Palloni, Alberto. University of Wisconsin-Madison; Estados UnidosFil: Viana Peixoto, Sergio. Fundação Oswaldo Cruz; BrasilFil: Pereira, Alexandre C.. Instituto do Coração; BrasilFil: Pérez, Cynthia M.. Universidad de Puerto Rico; Puerto RicoFil: Rangel Reina, Daniel A.. Gorgas Memorial Institute of Health Studies; PanamáFil: Ribeiro, Robespierre. Secretaria de Estado de Saúde de Minas Gerais; BrasilFil: Ritti-Dias, Raphael M.. Universidade Nove de Julho; BrasilFil: Rivera, Juan A.. Instituto Nacional de Salud Pública; MéxicoFil: Robitaille, Cynthia. Public Health Agency of Canada; CanadáFil: Rodríguez-Villamizar, Laura A.. Universidad Industrial de Santander; ColombiaFil: Rojas-Martinez, Rosalba. Instituto Nacional de Salud Pública; MéxicoFil: Roy, Joel G. R.. Statistics Canada; CanadáFil: Rubinstein, Adolfo Luis. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Ruiz-Betancourt, Blanca Sandra. Instituto Mexicano del Seguro Social; MéxicoFil: Salazar Martinez, Eduardo. Instituto Nacional de Salud Pública; MéxicoFil: Sánchez-Abanto, José. Instituto Nacional de Salud; PerúFil: Santos , Ina S.. Universidade Federal de Pelotas; BrasilFil: dos Santos, Renata Nunes. Universidade Federal de Sao Paulo; BrasilFil: Scazufca, Marcia. Universidade Federal de Sao Paulo; BrasilFil: Schargrodsky, Herman. Hospital Italiano; ArgentinaFil: Silva, Antonio M.. Universidade Federal do Maranhao; BrasilFil: Santos Silva, Diego Augusto. Universidade Federal de Santa Catarina; BrasilFil: Stein, Aryeh D.. Emory University; Estados UnidosFil: Suárez-Medina, Ramón. Instituto Nacional de Higiene, Epidemiología y Microbiología; CubaFil: Tarqui-Mamani, Carolina B.. Instituto Nacional de Salud; PerúFil: Tulloch-Reid, Marshall K.. The University of the West Indies; JamaicaFil: Ueda, Peter. Harvard TH Chan School of Public Health; Estados UnidosFil: Ugel, Eunice E.. Universidad Centro-Occidental Lisandro Alvarado; VenezuelaFil: Valdivia, Gonzalo. Pontificia Universidad Católica de Chile; ChileFil: Varona, Patricia. Instituto Nacional de Higiene, Epidemiología y Microbiología; CubaFil: Velasquez-Melendez, Gustavo. Universidade Federal de Minas Gerais; BrasilFil: Verstraeten, Roosmarijn. Institute of Tropical Medicine; BélgicaFil: Victora, Cesar G.. Universidade Federal de Pelotas; BrasilFil: Wanderley Jr, Rildo S.. Universidade Federal de Pernambuco; BrasilFil: Wang, Ming-Dong. Public Health Agency of Canada; CanadáFil: Wilks, Rainford J.. The University of the West Indies; JamaicaFil: Wong-McClure, Roy A.. Caja Costarricense de Seguro Social; Costa RicaFil: Younger-Coleman, Novie O.. The University of the West Indies; JamaicaFil: Zuñiga Cisneros, Julio. Gorgas Memorial Institute of Public Health; PanamáFil: Danaei, Goodarz. Harvard TH Chan School of Public Health; Estados UnidosFil: Stevens, Gretchen A.. World Health Organization; SuizaFil: Riley, Leanne M.. World Health Organization; SuizaFil: Ezzati, Majid. (Imperial College London; Reino UnidoFil: Di Cesare, Mariachiara. Middlesex University; Reino Unid

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 tem sido amplamente desconexos. É essencial formarmos redes para obtermos respostas que transcendam as fronteiras e horizontes das 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 a longo prazo. Nós revisamos as maiores descobertas científicas deste esforço global, e mostramos também como este processo vem 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 grandes escalas. 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 da infraestrutura cibernética do ForestPlots.net, conectando colegas de 54 países e 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 os fatores que influenciam essas tendências, 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 as faíscas de uma moderna revolução na ciência das florestas tropicais. No futuro a humanidade pode se beneficiar incentivando estas comunidades locais 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