Occurrence of Intestinal Parasites in Alouatta caraya of the Zoobotanical Park of Teresina, Piauí, Brazil

Background: The animals of the genus Alouatta are popularly known as Bugios, barbados, roncadores and guaribas, being the neotropical primates better studied in the world. They originate in South America, with records in Argentina, Bolivia, Paraguay and Uruguay. Because of their migrations, many are found debilitated and taken to captivity until their rehabilitation and most cannot be reinserted in nature. They tend to live in extensive areas, having a low resistance against parasitic infections because of low exposure and when kept in captivity, the risks of these infections increase. Some diagnostic techniques can aid in the detection of parasites of zoo animals and can identify the parasitic fauna of these animals. The objective of this work was to investigate and report the presence of intestinal parasites in a female Bugio-preta (Alouatta caraya) captive of the Zoobotanical Park of the municipality of Teresina, Piauí, Brazil.Case: The animal presented a constipation signs before clinical signs of apathy, anorexia, diarrhea and weight loss, suggestive signs of parasitosis, Sterile papers were placed on the floor of the animal enclosure and collected fresh stools shortly after defecation, the feces were removed using gloves, stored in a capped containers, identified and taken to the Laboratory of Parasitology of the Department of Parasitology and Microbiology of the Federal University of Piauí, for further evaluation. The fecal samples were submitted to the techniques of spontaneous sedimentation (HPJ), centrifugation-flotation (Faust) and flotation method in hyper saturated sucrose solution (Willis-Mollay), obtaining slides that were analyzed under an optical microscope in the 10x and 40x objective, confirming the presence of ascarids and hookworms.Discussion: The results showed the presence of eggs of Ascaris sp. and Ancylostoma sp. in all of the analyzed techniques, thus maintaining an alert, since they are considered helminths of zoonotic character. The general state of the animal may have influenced considerably the result of mixed infection by helminths, since it had episodes of diarrhea and was skinny at the time of diagnosis. Diarrheal feces and slimming favor the encounter of mixed infection, since the parasites in large quantity can cause to their hosts a decrease in the absorption of nutrients and an intestinal peristalsis increase. Other works with primates also revealed the presence of parasites in animals, including protozoans. The collection moment and evaluation of the fecal samples of the Bugio coincided with the rainy period in the region. This fact can favor the increase of eggs and larvae of parasites in the environment and, consequently, can contaminate the animals. Regarding to sanitary management of zoos, areas full of plants and trees make it difficult to hygienize the enclosures and in these places is common the presence of other animals that can serve as carriers of pathogens. The available diagnostic great relevance to assess the degree of animal infection, the possibility of transmission and the sanitary conditions of the environment. It was concluded that the female Bugio of the Teresina Zoobotanical Park was parasitized by ascarids and hookworms and the techniques of parasitological exams performed represented great relevance for the early diagnosis and an appropriate treatment, being able to be used for the control of diseases parasites, mainly zoonoses

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

Long-term thermal sensitivity of Earth’s tropical forests

The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (−9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth’s climate

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

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

ATLANTIC EPIPHYTES: a data set of vascular and non-vascular epiphyte plants and lichens from the Atlantic Forest

Epiphytes are hyper-diverse and one of the frequently undervalued life forms in plant surveys and biodiversity inventories. Epiphytes of the Atlantic Forest, one of the most endangered ecosystems in the world, have high endemism and radiated recently in the Pliocene. We aimed to (1) compile an extensive Atlantic Forest data set on vascular, non-vascular plants (including hemiepiphytes), and lichen epiphyte species occurrence and abundance; (2) describe the epiphyte distribution in the Atlantic Forest, in order to indicate future sampling efforts. Our work presents the first epiphyte data set with information on abundance and occurrence of epiphyte phorophyte species. All data compiled here come from three main sources provided by the authors: published sources (comprising peer-reviewed articles, books, and theses), unpublished data, and herbarium data. We compiled a data set composed of 2,095 species, from 89,270 holo/hemiepiphyte records, in the Atlantic Forest of Brazil, Argentina, Paraguay, and Uruguay, recorded from 1824 to early 2018. Most of the records were from qualitative data (occurrence only, 88%), well distributed throughout the Atlantic Forest. For quantitative records, the most common sampling method was individual trees (71%), followed by plot sampling (19%), and transect sampling (10%). Angiosperms (81%) were the most frequently registered group, and Bromeliaceae and Orchidaceae were the families with the greatest number of records (27,272 and 21,945, respectively). Ferns and Lycophytes presented fewer records than Angiosperms, and Polypodiaceae were the most recorded family, and more concentrated in the Southern and Southeastern regions. Data on non-vascular plants and lichens were scarce, with a few disjunct records concentrated in the Northeastern region of the Atlantic Forest. For all non-vascular plant records, Lejeuneaceae, a family of liverworts, was the most recorded family. We hope that our effort to organize scattered epiphyte data help advance the knowledge of epiphyte ecology, as well as our understanding of macroecological and biogeographical patterns in the Atlantic Forest. No copyright restrictions are associated with the data set. Please cite this Ecology Data Paper if the data are used in publication and teaching events. © 2019 The Authors. Ecology © 2019 The Ecological Society of Americ

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.Additional co-authors: Susan Laurance, William Laurance, Francoise Yoko Ishida, Andrew Marshall, Catherine Waite, Hannsjoerg Woell, Jean-Francois Bastin, Marijn Bauters, Hans Beeckman, Pfascal Boeckx, Jan Bogaert, Charles De Canniere, Thales de Haulleville, Jean-Louis Doucet, Olivier Hardy, Wannes Hubau, Elizabeth Kearsley, Hans Verbeeck, Jason Vleminckx, Steven W. Brewer, Alfredo Alarcón, Alejandro Araujo-Murakami, Eric Arets, Luzmila Arroyo, Ezequiel Chavez, Todd Fredericksen, René Guillén Villaroel, Gloria Gutierrez Sibauty, Timothy Killeen, Juan Carlos Licona, John Lleigue, Casimiro Mendoza, Samaria Murakami, Alexander Parada Gutierrez, Guido Pardo, Marielos Peña-Claros, Lourens Poorter, Marisol Toledo, Jeanneth Villalobos Cayo, Laura Jessica Viscarra, Vincent Vos, Jorge Ahumada, Everton Almeida, Jarcilene Almeida, Edmar Almeida de Oliveira, Wesley Alves da Cruz, Atila Alves de Oliveira, Fabrício Alvim Carvalho, Flávio Amorim Obermuller, Ana Andrade, Fernanda Antunes Carvalho, Simone Aparecida Vieira, Ana Carla Aquino, Luiz Aragão, Ana Claudia Araújo, Marco Antonio Assis, Jose Ataliba Mantelli Aboin Gomes, Fabrício Baccaro, Plínio Barbosa de Camargo, Paulo Barni, Jorcely Barroso, Luis Carlos Bernacci, Kauane Bordin, Marcelo Brilhante de Medeiros, Igor Broggio, José Luís Camargo, Domingos Cardoso, Maria Antonia Carniello, Andre Luis Casarin Rochelle, Carolina Castilho, Antonio Alberto Jorge Farias Castro, Wendeson Castro, Sabina Cerruto Ribeiro, Flávia Costa, Rodrigo Costa de Oliveira, Italo Coutinho, John Cunha, Lola da Costa, Lucia da Costa Ferreira, Richarlly da Costa Silva, Marta da Graça Zacarias Simbine, Vitor de Andrade Kamimura, Haroldo Cavalcante de Lima, Lia de Oliveira Melo, Luciano de Queiroz, José Romualdo de Sousa Lima, Mário do Espírito Santo, Tomas Domingues, Nayane Cristina dos Santos Prestes, Steffan Eduardo Silva Carneiro, Fernando Elias, Gabriel Eliseu, Thaise Emilio, Camila Laís Farrapo, Letícia Fernandes, Gustavo Ferreira, Joice Ferreira, Leandro Ferreira, Socorro Ferreira, Marcelo Fragomeni Simon, Maria Aparecida Freitas, Queila S. García, Angelo Gilberto Manzatto, Paulo Graça, Frederico Guilherme, Eduardo Hase, Niro Higuchi, Mariana Iguatemy, Reinaldo Imbrozio Barbosa, Margarita Jaramillo, Carlos Joly, Joice Klipel, Iêda Leão do Amaral, Carolina Levis, Antonio S. Lima, Maurício Lima Dan, Aline Lopes, Herison Madeiros, William E. Magnusson, Rubens Manoel dos Santos, Beatriz Marimon, Ben Hur Marimon Junior, Roberta Marotti Martelletti Grillo, Luiz Martinelli, Simone Matias Reis, Salomão Medeiros, Milton Meira-Junior, Thiago Metzker, Paulo Morandi, Natanael Moreira do Nascimento, Magna Moura, Sandra Cristina Müller, Laszlo Nagy, Henrique Nascimento, Marcelo Nascimento, Adriano Nogueira Lima, Raimunda Oliveira de Araújo, Jhonathan Oliveira Silva, Marcelo Pansonato, Gabriel Pavan Sabino, Karla Maria Pedra de Abreu, Pablo José Francisco Pena Rodrigues, Maria Piedade, Domingos Rodrigues, José Roberto Rodrigues Pinto, Carlos Quesada, Eliana Ramos, Rafael Ramos, Priscyla Rodrigues, Thaiane Rodrigues de Sousa, Rafael Salomão, Flávia Santana, Marcos Scaranello, Rodrigo Scarton Bergamin, Juliana Schietti, Jochen Schöngart, Gustavo Schwartz, Natalino Silva, Marcos Silveira, Cristiana Simão Seixas, Marta Simbine, Ana Claudia Souza, Priscila Souza, Rodolfo Souza, Tereza Sposito, Edson Stefani Junior, Julio Daniel do Vale, Ima Célia Guimarães Vieira, Dora Villela, Marcos Vital, Haron Xaud, Katia Zanini, Charles Eugene Zartman, Nur Khalish Hafizhah Ideris, Faizah binti Hj Metali, Kamariah Abu Salim, Muhd Shahruney Saparudin, Rafizah Mat Serudin, Rahayu Sukmaria Sukri, Serge Begne, George Chuyong, Marie Noel Djuikouo, Christelle Gonmadje, Murielle Simo-Droissart, Bonaventure Sonké, Hermann Taedoumg, Lise Zemagho, Sean Thomas, Fidèle Baya, Gustavo Saiz, Javier Silva Espejo, Dexiang Chen, Alan Hamilton, Yide Li, Tushou Luo, Shukui Niu, Han Xu, Zhang Zhou, Esteban Álvarez-Dávila, Juan Carlos Andrés Escobar, Henry Arellano-Peña, Jaime Cabezas Duarte, Jhon Calderón, Lina Maria Corrales Bravo, Borish Cuadrado, Hermes Cuadros, Alvaro Duque, Luisa Fernanda Duque, Sandra Milena Espinosa, Rebeca Franke-Ante, Hernando García, Alejandro Gómez, Roy González-M., Álvaro Idárraga-Piedrahíta, Eliana Jimenez, Rubén Jurado, Wilmar López Oviedo, René López-Camacho, Omar Aurelio Melo Cruz, Irina Mendoza Polo, Edwin Paky, Karen Pérez, Angel Pijachi, Camila Pizano, Adriana Prieto, Laura Ramos, Zorayda Restrepo Correa, James Richardson, Elkin Rodríguez, Gina M. Rodriguez M., Agustín Rudas, Pablo Stevenson, Markéta Chudomelová, Martin Dancak, Radim Hédl, Stanislav Lhota, Martin Svatek, Jacques Mukinzi, Corneille Ewango, Terese Hart, Emmanuel Kasongo Yakusu, Janvier Lisingo, Jean-Remy Makana, Faustin Mbayu, Benjamin Toirambe, John Tshibamba Mukendi, Lars Kvist, Gustav Nebel, Selene Báez, Carlos Céron, Daniel M. Griffith, Juan Ernesto Guevara Andino, David Neill, Walter Palacios, Maria Cristina Peñuela-Mora, Gonzalo Rivas-Torres, Gorky Villa, Sheleme Demissie, Tadesse Gole, Techane Gonfa, Kalle Ruokolainen, Michel Baisie, Fabrice Bénédet, Wemo Betian, Vincent Bezard, Damien Bonal, Jerôme Chave, Vincent Droissart, Sylvie Gourlet-Fleury, Annette Hladik, Nicolas Labrière, Pétrus Naisso, Maxime Réjou-Méchain, Plinio Sist, Lilian Blanc, Benoit Burban, Géraldine Derroire, Aurélie Dourdain, Clement Stahl, Natacha Nssi Bengone, Eric Chezeaux, Fidèle Evouna Ondo, Vincent Medjibe, Vianet Mihindou, Lee White, Heike Culmsee, Cristabel Durán Rangel, Viviana Horna, Florian Wittmann, Stephen Adu-Bredu, Kofi Affum-Baffoe, Ernest Foli, Michael Balinga, Anand Roopsind, James Singh, Raquel Thomas, Roderick Zagt, Indu K. Murthy, Kuswata Kartawinata, Edi Mirmanto, Hari Priyadi, Ismayadi Samsoedin, Terry Sunderland, Ishak Yassir, Francesco Rovero, Barbara Vinceti, Bruno Hérault, Shin-Ichiro Aiba, Kanehiro Kitayama, Armandu Daniels, Darlington Tuagben, John T. Woods, Muhammad Fitriadi, Alexander Karolus, Kho Lip Khoon, Noreen Majalap, Colin Maycock, Reuben Nilus, Sylvester Tan, Almeida Sitoe, Indiana Coronado G., Lucas Ojo, Rafael de Assis, Axel Dalberg Poulsen, Douglas Sheil, Karen Arévalo Pezo, Hans Buttgenbach Verde, Victor Chama Moscoso, Jimmy Cesar Cordova Oroche, Fernando Cornejo Valverde, Massiel Corrales Medina, Nallaret Davila Cardozo, Jano de Rutte Corzo, Jhon del Aguila Pasquel, Gerardo Flores Llampazo, Luis Freitas, Darcy Galiano Cabrera, Roosevelt García Villacorta, Karina Garcia Cabrera, Diego García Soria, Leticia Gatica Saboya, Julio Miguel Grandez Rios, Gabriel Hidalgo Pizango, Eurídice Honorio Coronado, Isau Huamantupa-Chuquimaco, Walter Huaraca Huasco, Yuri Tomas Huillca Aedo, Jose Luis Marcelo Peña, Abel Monteagudo Mendoza, Vanesa Moreano Rodriguez, Percy Núñez Vargas, Sonia Cesarina Palacios Ramos, Nadir Pallqui Camacho, Antonio Peña Cruz, Freddy Ramirez Arevalo, José Reyna Huaymacari, Carlos Reynel Rodriguez, Marcos Antonio Ríos Paredes, Lily Rodriguez Bayona, Rocio del Pilar Rojas Gonzales, Maria Elena Rojas Peña, Norma Salinas Revilla, Yahn Carlos Soto Shareva, Raul Tupayachi Trujillo, Luis Valenzuela Gamarra, Rodolfo Vasquez Martinez, Jim Vega Arenas, Christian Amani, Suspense Averti Ifo, Yannick Bocko, Patrick Boundja, Romeo Ekoungoulou, Mireille Hockemba, Donatien Nzala, Alusine Fofanah, David Taylor, Guillermo Bañares-de Dios, Luis Cayuela, Íñigo Granzow-de la Cerda, Manuel Macía, Juliana Stropp, Maureen Playfair, Verginia Wortel, Toby Gardner, Robert Muscarella, Hari Priyadi, Ervan Rutishauser, Kuo-Jung Chao, Pantaleo Munishi, Olaf Bánki, Frans Bongers, Rene Boot, Gabriella Fredriksson, Jan Reitsma, Hans ter Steege, Tinde van Andel, Peter van de Meer, Peter van der Hout, Mark van Nieuwstadt, Bert van Ulft, Elmar Veenendaal, Ronald Vernimmen, Pieter Zuidema, Joeri Zwerts, Perpetra Akite, Robert Bitariho, Colin Chapman, Eilu Gerald, Miguel Leal, Patrick Mucunguzi, Miguel Alexiades, Timothy R. Baker, Karina Banda, Lindsay Banin, Jos Barlow, Amy Bennett, Erika Berenguer, Nicholas Berry, Neil M. Bird, George A. Blackburn, Francis Brearley, Roel Brienen, David Burslem, Lidiany Carvalho, Percival Cho, Fernanda Coelho, Murray Collins, David Coomes, Aida Cuni-Sanchez, Greta Dargie, Kyle Dexter, Mat Disney, Freddie Draper, Muying Duan, Adriane Esquivel-Muelbert, Robert Ewers, Belen Fadrique, Sophie Fauset, Ted R. Feldpausch, Filipe França, David Galbraith, Martin Gilpin, Emanuel Gloor, John Grace, Keith Hamer, David Harris, Tommaso Jucker, Michelle Kalamandeen, Bente Klitgaard, Aurora Levesley, Simon L. Lewis, Jeremy Lindsell, Gabriela Lopez-Gonzalez, Jon Lovett, Yadvinder Malhi, Toby Marthews, Emma McIntosh, Karina Melgaço, William Milliken, Edward Mitchard, Peter Moonlight, Sam Moore, Alexandra Morel, Julie Peacock, Kelvin Peh, Colin Pendry, R. Toby Pennington, Luciana de Oliveira Pereira, Carlos Peres, Oliver L. Phillips, Georgia Pickavance, Thomas Pugh, Lan Qie, Terhi Riutta, Katherine Roucoux, Casey Ryan, Tiina Sarkinen, Camila Silva Valeria, Dominick Spracklen, Suzanne Stas, Martin Sullivan, Michael Swaine, Joey Talbot, James Taplin, Geertje van der Heijden, Laura Vedovato, Simon Willcock, Mathew Williams, Luciana Alves, Patricia Alvarez Loayza, Gabriel Arellano, Cheryl Asa, Peter Ashton, Gregory Asner, Terry Brncic, Foster Brown, Robyn Burnham, Connie Clark, James Comiskey, Gabriel Damasco, Stuart Davies, Tony Di Fiore, Terry Erwin, William Farfan-Rios, Jefferson Hall, David Kenfack, Thomas Lovejoy, Roberta Martin, Olga Martha Montiel, John Pipoly, Nigel Pitman, John Poulsen, Richard Primack, Miles Silman, Marc Steininger, Varun Swamy, John Terborgh, Duncan Thomas, Peter Umunay, Maria Uriarte, Emilio Vilanova Torre, Ophelia Wang, Kenneth Young, Gerardo A. Aymard C., Lionel Hernández, Rafael Herrera Fernández, Hirma Ramírez-Angulo, Pedro Salcedo, Elio Sanoja, Julio Serrano, Armando Torres-Lezama, Tinh Cong Le, Trai Trong Le, Hieu Dang Tra

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Rhizobacteria induces resistance against Fusarium wilt of tomato by increasing the activity of defense enzymes

Fusarium wilt, caused by Fusarium oxysporum f.sp. lycopersici (Fol), is one of the most important diseases that affect tomato yield worldwide. This study investigated the potential of three antagonists, Streptomyces setonii (UFV 618), Bacillus cereus (UFV 592) and Serratia marcescens (UFV 252), and as positive control the hormone jasmonic acid (JA), to reduce Fusarium wilt symptoms and to potentiate the defense enzymes in the stem tissues of tomato plants infected by Fol. The seeds were microbiolized with each antagonist, and the soil was also drenched with them. The plants were sprayed with JA 48 h before Fol inoculation. The area under the Fusarium wilt index progress curve was reduced by 54, 48, 47 and 45% for the UFV 618, JA, UFV 592 and UFV 252 treatments, respectively. The three antagonists, and even the JA spray, efficiently reduced the Fusarium wilt symptoms on the tomato plant stems, which can be explained by the lower malondialdehyde concentration (an indication of oxidative damage to lipids in the plasma membranes) and the greater activities of peroxidases, polyphenoloxidases, glucanases, chitinases, phenylalanine ammonia-lyases and lipoxygenases, which are commonly involved in host resistance against fungal diseases. These results present a novel alternative that can be used in the integrated management of Fusarium wilt on tomatoes