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

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Characterization of the Austenite Reformation Mechanisms as a Function of the Initial Ferritic State in a UNS S32304 Duplex Stainless Steel

<div><p>Aiming to better understand the effects of heat treatment parameters on Ferrite-Austenite phase transformation in a 2304 duplex stainless steel different thermal cycles were applied to this steel in a quenching dilatometer. The obtained microstructures were characterized by optical microscopy, transmission electron microscopy and electron backscatter diffraction. It was noticed that the austenite formation mechanism is strongly dependent on initial ferritized state. If the initial structure is completely ferritized, the nitrogen supersaturated solid solution leads to chromium nitrides precipitation and the rate of austenite nucleation decreases. For higher cooling rates, the ferrite grain boundaries control the austenite nucleation rate. The higher the ferrite grain size, the lower the final austenite fraction. If the steel is cooled from a partial ferritized state, the ferrite-austenite phase boundaries work as austenite nucleation site and the austenite growth rate is favored due to the high interfacial energy and the austenitic structures becomes coarser.</p></div

Panorama of wind energy in the state of Rio Grande do Norte in 2004-2017

The objective of this paper is to provide an overview of wind energy in the state of Rio Grande do Norte between 2004 and 2017, demonstrating the state’s strength in electric power generation from wind. This objective is achieved through an extensive bibliographic survey of academic sources and websites of official wind energy organizations. Exponential growth of wind energy generation had been observed at this state. Between 2004 and 2017, installed capacity grew from 1.8 MW to 3,3625.50 MW. Rio Grande do Norte accounts for 32.72% of all wind energy generation in Brazil and for 38.95% in the Northeastern region, totaling 13.24TWh with 133 wind farms established at the state. Rio Grande do Norte has an average generation capacity factor of 44.4%, the 5th position in the Brazilian ranking, behind the states of Maranhão (68%), Bahia (48.5%), Pernambuco (48.3%), and Piauí (46.1%). Despite this, the state’s generation capacity factor is higher than the national average (42.9%) and the global average (24.7%). Although Rio Grande do Norte has experienced vertiginous growth in wind energy generation, there is much room for further growth. Federal and local governments must develop incentive policies for wind energy to ensure that Rio Grande do Norte will achieve its maximum potential of clean electricity generation at competitive costs compared to other energy sources.Este trabalho tem como objetivo apresentar um panorama do setor de energia eólica do estado do Rio Grande do Norte (RN) entre o período de 2004-2017, mostrando a força do estado na geração de energia elétrica proveniente dos ventos. Para isso, foi realizado um amplo levantamento bibliográfico em materiais acadêmicos e páginas eletrônicas de órgãos oficiais deste setor. Observou-se que a energia eólica tem experimentado um exponencial e virtuoso crescimento no estado. Entre 2004 e 2017, a potência instalada saltou de 1,8 MW para 3.625,50 MW. Em relação à geração, o RN é responsável por 32,72% de toda a geração de energia eólica do país e 38,95% da região Nordeste, atingindo a marca de 13,24 TWh nos 133 parques eólicos fixados no estado. O RN possui fator de capacidade médio de geração de 44,4%, ocupando a 5° posição no ranking brasileiro, logo atrás dos estados do Maranhão (68%), Bahia (48,5%), Pernambuco (48,3%) e Piauí (46,1%). Apesar disso, o fator de capacidade de geração do RN é superior à média nacional (42,9%) e global (24,7%). Por fim, constatou-se que, embora o RN tenha experimentado um crescimento vertiginoso na geração de energia de origem eólica, ainda há um campo vasto para crescimento do setor, mas para isso, são necessários incentivos e ações federais e, sobretudo, estadual para que o RN desfrute do seu potencial máximo de geração de energia limpa em escala e preço competitivo frente às outras tecnologias de geração

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data

Characterisation of microbial attack on archaeological bone

As part of an EU funded project to investigate the factors influencing bone preservation in the archaeological record, more than 250 bones from 41 archaeological sites in five countries spanning four climatic regions were studied for diagenetic alteration. Sites were selected to cover a range of environmental conditions and archaeological contexts. Microscopic and physical (mercury intrusion porosimetry) analyses of these bones revealed that the majority (68%) had suffered microbial attack. Furthermore, significant differences were found between animal and human bone in both the state of preservation and the type of microbial attack present. These differences in preservation might result from differences in early taphonomy of the bones. © 2003 Elsevier Science Ltd. All rights reserved