Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

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

Population fluctuations in the pink hibiscus mealybug and its natural enemies in Annona squamosa (Annonaceae) in Roraima, Brazil

<div><p>ABSTRACT Maconellicoccus hirsutus (Hemiptera, Pseudococcidae), a species of economic interest, especially for fruit plants, is expanding on the South American continent. Information about the population dynamics of this pest associated with control by natural enemies and cultural practices is fundamental for its management. Our objective was to study the population fluctuations in M. hirsutus and its natural enemies in a sugar-apple (Annona squamosa) orchard in Roraima, northern Brazil. Trees were evaluated monthly over a 12-month period. Infestation rates by M. hirsutus and its parasitism were also estimated for potential host plants around the study area. Highest infestation occurred in August and February-March. Alternative hosts were infested during the off-season, mainly fruit. Lacewings and the parasitoid Anagyrus kamali (Hymenoptera, Encyrtidae) were abundant natural enemies. Average parasitism by A. kamali in fruits was 50%, with highest rates in periods of greatest infestation by M. hirsutus. Fruitification pruning reduced M. hirsutus populations.</p></div

Serological markers of recent Campylobacter jejuni infection in patients with Guillain–Barré Syndrome in the State of Piauí, Brazil, 2014–2016

The Instituto Evandro Chagas provided a grant for this study, as well as Conselho Nacional de Desenvolvimento Cientíıfico e Tecnológico (CNPq) and Fundação de Amparo à Pesquisa do Estado do Piauí (FAPEPI).Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil / Teresina Municipal Health Secretariat. Department of Health Surveillance. Teresina, PI, Brazil / Piauí State Health Secretariat. Natan Portella Institute of Tropical Medicine. Teresina, PI, Brazil.Piauí State Health Secretariat. Department of Health Surveillance. Teresina, PI, Brazil.Teresina Municipal Health Secretariat. Department of Health Surveillance. Teresina, PI, Brazil / Piauí State Health Secretariat. Natan Portella Institute of Tropical Medicine. Teresina, PI, Brazil.Novafapi University. Medicine School. Teresina, PI, Brazil.Piauí State University Hospital. Department of Health Surveillance. Teresina, PI, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Piauí State Health Secretariat. Natan Portella Institute of Tropical Medicine. Teresina, PI, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Federal University of Piauí. Department of Mother and Child Health. Teresina, PI, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.In countries where poliomyelitis has been eradicated, Guillain–Barré syndrome (GBS) is the leading cause of acute flaccid paralysis. The range of infections that precede GBS in Brazil is unknown. Campylobacter jejuni infection is the most frequent trigger of GBS worldwide. Given the lack of systematic surveillance of diarrheal diseases, particularly in adults, the incidence of enteritis caused by C. jejuni in developing countries is unknown. From 2014 to 2016, pretreatment serum samples from 63 GBS patients were tested by immunoglobulin M (IgM) enzyme-linked immunosorbent assay for C. jejuni. Campylobacter jejuni IgM antibodies were detected in 17% (11/63) of the samples. There was no association between serological positivity (IgM) for C. jejuni and the occurrence of diarrhea among the investigated cases (P = 0.36). Hygiene measures, basic sanitation, and precautions during handling and preparation of food of animal origin may help prevent acute flaccid paralysis