Publications

Red Sea elasmobranch populations are facing alarming declines. Effective conservation efforts require management strategies informed by extensive datasets and by developing an understanding of distribution patterns within the basin, which is currently lacking. This study introduces CERSE (Central and Eastern Red Sea Elasmobranchs), a comprehensive compilation of elasmobranch observations in the central and eastern Red Sea basin following the route of the Red Sea Decade Expedition. The data set was curated from surveys conducted during two scientific cruises, a time-series survey within Red Sea Global project areas (Tabuk province), and observations extracted from peer-reviewed literature. Through the use of diverse methodologies, we provide a holistic view of elasmobranchs distribution in the region, for a total of 2,847 sightings recorded. By consolidating dispersed information from across the region, this dataset forms a comprehensive foundation for future research and monitoring endeavors focused on elasmobranch fauna, and will serve as a cornerstone for informing targeted conservation initiatives aimed at safeguarding endangered elasmobranch species in this region.

Despite the remarkable evolutionary success of insects at colonizing every conceivable terrestrial and aquatic habitat, only five Halobates (Heteroptera: Gerridae) species (~0.0001% of all known insect species) have succeeded at colonizing the open ocean - the largest biome on Earth. This remarkable evolutionary achievement likely required unique adaptations for them to survive and thrive in the challenging oceanic environment. For the first time, we explore the morphology and behavior of an open-ocean Halobates germanus and a related coastal species H. hayanus to understand mechanisms of these adaptations. We provide direct experimental evidence based on high-speed videos which reveal that Halobates exploit their specialized and self-groomed body hair to achieve extreme water repellence, which facilitates rapid skating and plastron respiration under water. Moreover, the grooming behavior and presence of cuticular wax aids in the maintenance of superhydrophobicity. Further, reductions of their body mass and size enable them to achieve impressive accelerations (~400 ms

Abstract Aim A central question in evolutionary ecology is the nature of environmental barriers that can limit gene flow and induce population genetic divergence, a first step towards speciation. Here we study the geographical barrier constituted by the transition zone between the Atlantic Ocean and the Mediterranean Sea, using as our model Cymodocea nodosa , a seagrass distributed throughout the Mediterranean and in the Atlantic, from central Portugal to Mauritania. We also test predictions about the genetic footprints of Pleistocene glaciations. Location The Atlantic–Mediterranean transition region and adjacent areas in the Atlantic (Mauritania to south‐west Portugal) and the Mediterranean. Methods We used eight microsatellite markers to compare 20 seagrass meadows in the Atlantic and 27 meadows in the Mediterranean, focusing on the transition between these basins. Results Populations from these two regions form coherent groups containing several unique, high‐frequency alleles for the Atlantic and for the Mediterranean, with some admixture west of the Almeria–Oran Front (Portugal, south‐west Spain and Morocco). These are populations where only one or a few genotypes were found, for all but Cadiz, but remarkably still show the footprint of a contact zone. This extremely low genotypic richness at the Atlantic northern edge contrasts with the high values (low clonality) at the Atlantic southern edge and in most of the Mediterranean. The most divergent populations are those at the higher temperature range limits: the southernmost Atlantic populations and the easternmost Mediterranean, both potential footprints of vicariance. Main conclusions A biogeographical transition region occurs close to the Almeria–Oran front. A secondary contact zone in Atlantic Iberia and Morocco results from two distinct dispersal sources: the Mediterranean and southernmost Atlantic populations, possibly during warmer interglacial or post‐glacial periods. The presence of high‐frequency diagnostic alleles in present‐day disjunct populations from the southernmost Atlantic region indicates that their separation from all remaining populations is ancient, and suggests an old, stable rear edge.

Abstract Social media (e.g., Twitter) has been an extremely popular tool for public health surveillance. The novel coronavirus disease 2019 (COVID-19) is the first pandemic experienced by a world connected through the internet. We analyzed 105+ million tweets collected between March 1 and May 15, 2020, and Weibo messages compiled between January 20 and May 15, 2020, covering six languages (English, Spanish, Arabic, French, Italian, and Chinese) and represented an estimated 2.4 billion citizens worldwide. To examine fine-grained emotions during a pandemic, we built machine learning classification models based on deep learning language models to identify emotions in social media conversations about COVID-19, including positive expressions ( optimistic, thankful , and empathetic ), negative expressions ( pessimistic, anxious, sad, annoyed , and denial ), and a complicated expression, joking , which has not been explored before. Our analysis indicates a rapid increase and a slow decline in the volume of social media conversations regarding the pandemic in all six languages. The upsurge was triggered by a combination of economic collapse and confinement measures across the regions to which all the six languages belonged except for Chinese, where only the latter drove conversations. Tweets in all analyzed languages conveyed remarkably similar emotional states as the epidemic was elevated to pandemic status, including feelings dominated by a mixture of joking with anxious / pessimistic / annoyed as the volume of conversation surged and shifted to a general increase in positive states ( optimistic , thankful , and empathetic ), the strongest being expressed in Arabic tweets, as the pandemic came under control.

Abstract Genes of unknown function are among the biggest challenges in molecular biology, especially in microbial systems, where 40%-60% of the predicted genes are unknown. Despite previous attempts, systematic approaches to include the unknown fraction into analytical workflows are still lacking. Here, we propose a conceptual framework and a computational workflow that bridge the known-unknown gap in genomes and metagenomes. We showcase our approach by exploring 415,971,742 genes predicted from 1,749 metagenomes and 28,941 bacterial and archaeal genomes. We quantify the extent of the unknown fraction, its diversity, and its relevance across multiple biomes. Furthermore, we provide a collection of 283,874 lineage-specific genes of unknown function for Cand . Patescibacteria, being a significant resource to expand our understanding of their unusual biology. Finally, by identifying a target gene of unknown function for antibiotic resistance, we demonstrate how we can enable the generation of hypotheses that can be used to augment experimental data.

ABSTRACT Microbial eukaryotes are key components of the ocean plankton. Yet, our understanding of their community composition and activity in different water layers of the ocean is limited, particularly for picoeukaryotes (0.2-3 µ m cell size). Here we examined the picoeukaryotic communities inhabiting different vertical zones of the tropical and subtropical global ocean: surface, deep chlorophyll maximum, mesopelagic (including the deep scattering layer and minimum oxygen zone) and bathypelagic. Communities were analysed by high-throughput sequencing of the 18S rRNA gene, as represented by DNA (community structure) and RNA (metabolic expression), followed by delineation of Operational Taxonomic Units (OTUs). We found a clear stratification of the picoeukaryotic communities along the water column, with two differentiated assemblages corresponding to the sunlit and dark ocean. Specific taxonomic groups either increased or decreased their abundances with depth. We used the rRNA:rDNA ratio of each individual OTU as a proxy of its metabolic activity. The highest relative activity was found in the mesopelagic layer for most taxonomic groups, and the lowest in the bathypelagic. Overall, our results characterize the change in community structure and activity of picoeukaryotes in the global-ocean water column, suggesting that the mesopeagic layer is a hot-spot of picoeukaryotic activity.

Association for the Sciences of Limnology and Oceanography (ASLO) Summer Meeting, 5-10 June 2016, Santa Fe, New Mexico

Mangrove ecosystems provide important ecological benefits and ecosystem services, including carbon storage and coastline stabilization, but they also suffer great anthropogenic pressures. Microorganisms associated with mangrove sediments and the rhizosphere play key roles in this ecosystem and make essential contributions to its productivity and carbon budget. Understanding this nexus and moving from descriptive studies of microbial taxonomy to hypothesis-driven field and lab studies will facilitate a mechanistic understanding of mangrove ecosystem interaction webs and open opportunities for microorganism-mediated approaches to mangrove protection and rehabilitation. Such an effort calls for a multidisciplinary and collaborative approach, involving chemists, ecologists, evolutionary biologists, microbiologists, oceanographers, plant scientists, conservation biologists, and stakeholders, and it requires standardized methods to support reproducible experiments. Here, we outline the Mangrove Microbiome Initiative, which is focused around three urgent priorities and three approaches for advancing mangrove microbiome research.