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

Heating on the volatile composition and sensory aspects of extra-virgin olive oil

The main ways by which extra-virgin olive oil is consumed include direct application on salads or as an ingredient in sauces, but it is also been used by some for cooking, including frying and baking. However, it has been reported that under heat stress, some nonglyceridic components of olive oil are degraded. So, the effect of heating (at 50, 100, 150, and 200 °C for 2 h) on the volatile composition and sensory aspects of extra-virgin olive oil were evaluated. Heating altered the volatile composition of extra-virgin olive oil, mainly at higher temperatures (above 150 °C). The main modifications were related to the formation of large amounts of oxidized compounds, particularly large chain aldehydes. Sensory aspects were also altered when the oil was heated to higher temperatures, which might have occurred because of color alterations and mainly changes in the volatile composition of the oil

Núcleos de Ensino da Unesp: artigos 2007

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

Genomic epidemiology reveals how restriction measures shaped the SARS-CoV-2 epidemic in Brazil

Abstract Brazil has experienced some of the highest numbers of COVID-19 infections and deaths globally and made Latin America a pandemic epicenter from May 2021. Although SARS-CoV-2 established sustained transmission in Brazil early in the pandemic, important gaps remain in our understanding of local virus transmission dynamics. Here, we describe the genomic epidemiology of SARS-CoV-2 using near-full genomes sampled from 27 Brazilian states and an adjacent country - Paraguay. We show that the early stage of the pandemic in Brazil was characterised by the co-circulation of multiple viral lineages, linked to multiple importations predominantly from Europe, and subsequently characterized by large local transmission clusters. As the epidemic progressed, the absence of effective restriction measures led to the local emergence and international spread of Variants of Concern (VOC) and under monitoring (VUM), including the Gamma (P.1) and Zeta (P.2) variants. In addition, we provide a preliminary genomic overview of the epidemic in Paraguay, showing evidence of importation from Brazil. These data reinforce the need for the implementation of widespread genomic surveillance in South America as a toolkit for pandemic monitoring and providing a means to follow the real-time spread of emerging SARS-CoV-2 variants with possible implications for public health and immunization strategies

Núcleos de Ensino da Unesp: artigos 2008

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq