Modelling the response of urban lichens to broad-scale changes in air pollution and climate

To create more resilient cities, it is important that we understand the effects of the global change drivers in cities. Biodiversity-based ecological indicators (EIs) can be used for this, as biodiversity is the basis of ecosystem structure, composition, and function. In previous studies, lichens have been used as EIs to monitor the effects of global change drivers in an urban context, but only in single-city studies. Thus, we currently do not understand how lichens are affected by drivers that work on a broader scale. Therefore, our aim was to quantify the variance in lichen biodiversity-based metrics (taxonomic and trait-based) that can be explained by environmental drivers working on a broad spatial scale, in an urban context where local drivers are superimposed. To this end, we performed an unprecedented effort to sample epiphytic lichens in 219 green spaces across a continental gradient from Portugal to Estonia. Twenty-six broad-scale drivers were retrieved, including air pollution and bio-climatic variables, and their dimensionality reduced by means of a principal component analysis (PCA). Thirty-eight lichen metrics were then modelled against the scores of the first two axes of each PCA, and their variance partitioned into pollution and climate components. For the first time, we determined that 15% of the metric variance was explained by broad-scale drivers, with broad-scale air pollution showing more importance than climate across the majority of metrics. Taxonomic metrics were better explained by air pollution, as expected, while climate did not surpass air pollution in any of the trait-based metric groups. Consequently, 85% of the metric variance was shown to occur at the local scale. This suggests that further work is necessary to decipher the effects of climate change. Furthermore, although drivers working within cities are prevailing, both spatial scales must be considered simultaneously if we are to use lichens as EIs in cities at continental to global scales.info:eu-repo/semantics/publishedVersio

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

Modelling the response of urban lichens to broad-scale changes in air pollution and climate

To create more resilient cities, it is important that we understand the effects of the global change drivers in cities. Biodiversity-based ecological indicators (EIs) can be used for this, as biodiversity is the basis of ecosystem structure, composition, and function. In previous studies, lichens have been used as EIs to monitor the effects of global change drivers in an urban context, but only in single-city studies. Thus, we currently do not understand how lichens are affected by drivers that work on a broader scale. Therefore, our aim was to quantify the variance in lichen biodiversity-based metrics (taxonomic and trait-based) that can be explained by environmental drivers working on a broad spatial scale, in an urban context where local drivers are superimposed. To this end, we performed an unprecedented effort to sample epiphytic lichens in 219 green spaces across a continental gradient from Portugal to Estonia. Twenty-six broad-scale drivers were retrieved, including air pollution and bio-climatic variables, and their dimensionality reduced by means of a principal component analysis (PCA). Thirty-eight lichen metrics were then modelled against the scores of the first two axes of each PCA, and their variance partitioned into pollution and climate components. For the first time, we determined that 15% of the metric variance was explained by broad-scale drivers, with broad-scale air pollution showing more importance than climate across the majority of metrics. Taxonomic metrics were better explained by air pollution, as expected, while climate did not surpass air pollution in any of the trait-based metric groups. Consequently, 85% of the metric variance was shown to occur at the local scale. This suggests that further work is necessary to decipher the effects of climate change. Furthermore, although drivers working within cities are prevailing, both spatial scales must be considered simultaneously if we are to use lichens as EIs in cities at continental to global scales.ISSN:0269-7491ISSN:1878-2450ISSN:1873-642

Satellite

The fifth generation (5G) Wireless Communication systems development has brought out a paradigm shift using advanced technologies e.g., softwarization, virtualization, Massive MIMO, ultra-densification and introduction of new frequency bands. However, as the societal needs grow, and to satisfy UN's Sustainable Development Goals (SDGs), 6G and beyond systems are envisioned. Non- Terrestrial Networks including satellite systems, Unmanned Aerial Vehicles (UAVs) and High-Altitude Platforms (HAPs) provide the best solutions to connect the unconnected, unserved and underserved in remote and rural areas in particular. Over the past few decades, Geo Synchronous Orbits (GSO) satellite systems have been deployed to support broadband services, backhauling, Disaster Recovery and Continuity of Operations (DR-COOP) and emergency services. Recently, there is a considerable renewed interest in planning and developing non-GSO satellite systems. Within the next few years several thousands of Low Earth Orbit (LEO) satellites and mega LEO constellations will be ready to provide global Internet services. This report is the 2022 Edition of the INGR Satellite Working Group Report, subsequent to the previous two editions [1] [2]. The topics considered in this INGR Satellite WG 2022 Edition of the roadmap are the following taking 6G systems into account: applications and services, reference architectures (both backhaul and direct access), satellite loT, mm Wave use for satellite networks, machine learning and artificial intelligence, edge computing, QoS/QoE, security, network management and standardization. The work on the roadmap will continue towards the next edition of the roadmap addressing new challenges and potential solutions for future networks

The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

The PREDICTS project—Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)—has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity