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This Science Project (SP) contributes to the estimation of the impacts of the invasive species on the European Biodiversity and Ecosystems. This topic is important for European Green Deal and the new European Biodiversity Strategy. The SP is also linked with the socio-economic issues because of the NIS implications to the local ecosystems and their services, and their societal goods and services. Since many of the above impacts may be of local scale, they may alter common practices in circular economies. The SP is implemented by: (a) Combining different sources of data and information; (b) Using a dual workflow to analyse the data; (c) Integrating its resources with core EOSC services and potentially horizontal services available; (d) Engaging the relevant scientific communities. The users will be able to: (a) Analyse distribution patterns of invasive species from different sources of data; (b) Compare the above patterns; (c) Provide managerial suggestions to relevant authorities; (d) Build on the existing infrastructure to address more complex questions (e.g. future scenarios).

The current knowledge on the risk of climate change for biodiversity and ecosystems needs to be improved by seeking evidence from cross-domain analyses. As a demonstration case, this study analyses how to investigate and monitor the rapid increase of Non-Indigenous Invasive Species (NIS) in European ecosystems. These species may not only replace indigenous ones but also alter habitats, interacting with the changing environment and eventually severely influence established socio-economic regimes. The challenge is to adopt a comprehensive approach by considering the bulk of the biotic and abiotic variables and their interactions, which may be even more important for the distribution of the NIS than the occurrence of the NIS. Such approaches require access to big datasets (from genomics to in situ and satellite borne environmental data) and high computational power, especially for those models with iterative algorithms. This study aims to: integrate data from different scientific disciplines in the marine subdomain (e.g. chemistry, physics, biodiversity, ecosystems, genomics, socio-economics) into an analytical framework in order to advance our knowledge on the impact of NIS on European marine biodiversity and ecosystems; to connect the analytical framework and federate access to relevant data infrastructures at the EOSC portal in order to mobilise and empower a larger community of researchers and potential data providers; and to demonstrate and promote the benefits and potential of web-based science using EOSC.A break-through Technical Composability Layer (Tesseract, which includes an additional option with Jupyter Notebook) is used in order to achieve the horizontal composability of the services. Only FAIR-compliant datasets are used in this study. However, because the nature of the project is primarily multidisciplinary and cross-domain, the only way to guarantee that the results deriving by the different disciplines/domains are comparable is to FAIR-ify the web services used, too. This way, it is ensured that both the quality and process potential in the different disciplines and domains are comparable and therefore so are their results.This paper brings together scientists making basic research on biodiversity and ecosystems, computer engineers, including software and web developers, in order to create a FAIR-compliant virtual research environment (VRE) to achieve both the scientific goals and the community engaged.

We report the draft genome sequences of three bacterial species isolated from freshwater ponds or features around monuments in Washington, DC, during a semester-long microbiology lab course at the George Washington University. Two of the isolates belong to potentially novel species but lost their viability and could not be revived.

The mitochondrial cytochrome C oxidase subunit I gene (COI) is commonly used in environmental DNA (eDNA) metabarcoding studies, especially for assessing metazoan diversity. Yet, a great number of COI operational taxonomic units (OTUs) or/and amplicon sequence variants (ASVs) retrieved from such studies do not get a taxonomic assignment with a reference sequence. To assess and investigate such sequences, we have developed the Dark mAtteR iNvestigator (DARN) software tool. For this purpose, a reference COI-oriented phylogenetic tree was built from 1,593 consensus sequences covering all the three domains of life. With respect to eukaryotes, consensus sequences at the family level were constructed from 183,330 sequences retrieved from the Midori reference 2 database, which represented 70% of the initial number of reference sequences. Similarly, sequences from 431 bacterial and 15 archaeal taxa at the family level (29% and 1% of the initial number of reference sequences respectively) were retrieved from the BOLD and the PFam databases. DARN makes use of this phylogenetic tree to investigate COI pre-processed sequences of amplicon samples to provide both a tabular and a graphical overview of their phylogenetic assignments. To evaluate DARN, both environmental and bulk metabarcoding samples from different aquatic environments using various primer sets were analysed. We demonstrate that a large proportion of non-target prokaryotic organisms, such as bacteria and archaea, are also amplified in eDNA samples and we suggest prokaryotic COI sequences to be included in the reference databases used for the taxonomy assignment to allow for further analyses of dark matter. DARN source code is available on GitHub at https://github.com/hariszaf/darn and as a Docker image at https://hub.docker.com/r/hariszaf/darn.

Microbial mats are vertically stratified communities of microorganisms characterized by pronounced physiochemical gradients allowing for high species diversity and a wide range of metabolic capabilities. High Throughput Sequencing has the potential to reveal the biodiversity and function of such ecosystems in the cycling of elements. The present study combines 16S rRNA amplicon sequencing and shotgun metagenomics on a hypersaline marsh in Tristomo bay (Karpathos, Greece). Samples were collected in July 2018 and November 2019 from microbial mats, deeper sediment, aggregates observed in the water overlying the sediment, as well as sediment samples with no apparent layering. Metagenomic samples’ coassembly and binning revealed 250 bacterial and 39 archaeal metagenome-assembled genomes, with completeness estimates higher than 70% and contamination less than 5%. All MAGs had KEGG Orthology terms related to osmoadaptation, with the ‘salt in’ strategy ones being prominent. Halobacteria and Bacteroidetes were the most abundant taxa in the mats. Photosynthesis was most likely performed by purple sulphur and nonsulphur bacteria. All samples had the capacity for sulphate reduction, dissimilatory arsenic reduction, and conversion of pyruvate to oxaloacetate. Overall, both sequencing methodologies resulted in similar taxonomic compositions and revealed that the formation of the microbial mat in this marsh exhibits seasonal variation.

Several imaging techniques are used in biological and biomedical studies. Micro-computed tomography (micro-CT) is a non-destructive imaging technique that allows the rapid digitisation of internal and external structures of a sample in three dimensions and with great resolution. In this review, the strengths and weaknesses of some common imaging techniques applied in biological and biomedical fields, such as optical microscopy, confocal laser scanning microscopy, and scanning electron microscopy, are presented and compared with the micro-CT technique through five use cases. Finally, the ability of micro-CT to create non-destructively 3D anatomical and morphological data in sub-micron resolution and the necessity to develop complementary methods with other imaging techniques, in order to overcome limitations caused by each technique, is emphasised.

High-performance computing (HPC) systems have become indispensable for modern marine research, providing support to an increasing number and diversity of users. Pairing with the impetus offered by high-throughput methods to key areas such as non-model organism studies, their operation continuously evolves to meet the corresponding computational challenges. Here, we present a Tier 2 (regional) HPC facility, operating for over a decade at the Institute of Marine Biology, Biotechnology, and Aquaculture of the Hellenic Centre for Marine Research in Greece. Strategic choices made in design and upgrades aimed to strike a balance between depth (the need for a few high-memory nodes) and breadth (a number of slimmer nodes), as dictated by the idiosyncrasy of the supported research. Qualitative computational requirement analysis of the latter revealed the diversity of marine fields, methods, and approaches adopted to translate data into knowledge. In addition, hardware and software architectures, usage statistics, policy, and user management aspects of the facility are presented. Drawing upon the last decade’s experience from the different levels of operation of the Institute of Marine Biology, Biotechnology, and Aquaculture HPC facility, a number of lessons are presented; these have contributed to the facility’s future directions in light of emerging distribution technologies (e.g., containers) and Research Infrastructure evolution. In combination with detailed knowledge of the facility usage and its upcoming upgrade, future collaborations in marine research and beyond are envisioned.

The mitochondrial cytochrome C oxidase subunit I gene (COI) is commonly used in eDNA metabarcoding studies, especially for assessing metazoan diversity. Yet, a great number of COI operational taxonomic units or/and amplicon sequence variants are retrieved from such studies and referred to as “dark matter”, and do not get a taxonomic assignment with a reference sequence. For a thorough investigation of this dark matter, we have developed the Dark mAtteR iNvestigator (DARN) software tool. A reference COI-oriented phylogenetic tree was built from 1,240 consensus sequences covering all the three domains of life, with more than 80% of those representing eukaryotic taxa. With respect to eukaryotes, consensus sequences at the family level were constructed from 183,330 retrieved from the Midori reference 2 database. Similarly, sequences from 559 bacterial genera and 41 archaeal were retrieved from the BOLD database. DARN makes use of the phylogenetic tree to investigate and quantify pre-processed sequences of amplicon samples to provide both a tabular and a graphical overview of phylogenetic assignments. To evaluate DARN, both environmental and bulk metabarcoding samples from different aquatic environments using various primer sets were analysed. We demonstrate that a large proportion of non-target prokaryotic organisms such as bacteria and archaea are also amplified in eDNA samples and we suggest bacterial COI sequences to be included in the reference databases used for the taxonomy assignment to allow for further analyses of dark matter. DARN source code is available on GitHub at https://github.com/hariszaf/darn and you may find it as a Docker at https://hub.docker.com/r/hariszaf/darn.Author summaryDARN is a software approach aiming to provide further insight in the COI amplicon data coming from environmental samples. Building a COI-oriented reference phylogeny tree is a challenging task especially considering the small number of microbial curated COI sequences deposited in reference databases; e.g ~4,000 bacterial and ~150 archaeal in BOLD. Apparently, as more and more such sequences are collated, the DARN approach improves. To provide a more interactive way of communicating both our approach and our results, we strongly suggest the reader to visit this Google Collab notebook where all steps are described step by step and also this GitHub page where our results are demonstrated. Our approach corroborates the known presence of microbial sequences in COI environmental sequencing samples and highlights the need for curated bacterial and archaeal COI sequences and their integration into reference databases (i.e. Midori, BOLD, etc). We argue that DARN will benefit researchers as a quality control tool for their sequenced samples in terms of distinguishing eukaryotic from non-eukaryotic OTUs/ASVs, but also in terms of understanding the unknown unknowns.

This preprint introduces key pieces of information of the IMBBC HPC facility regarding its history, usage statistics, user management and in-house developed containers/workflows along with accompanying data. It also intends to share them to the rest of the scientific community either directly as a data-presenting paper or by accompanying sister publications (where data interpretations and conclusions are given)., HZ and NG contributed equally at this work. Correspondence to: E. Pafilis; pafilis@hcmr.gr

This report will compile the outcomes of the work performed in Task 2.1 (Political and societal drivers and requirements), informing on the potential of evolving trends in technological progress in advancing contemporary marine environmental monitoring practices and examining the role any resulting changes in established operating paradigms could play in shaping the socio-political framework defining ocean observing needs at the global and European levels

Environmental DNA (eDNA) and metabarcoding have launched a new era in bio- and eco-assessment over the last years (Ruppert et al. 2019). The simultaneous identification, at the lowest taxonomic level possible, of a mixture of taxa from a great range of samples is now feasible; thus, the number of eDNA metabarcoding studies has increased radically (Deiner and 2017). While the experimental part of eDNA metabarcoding can be rather challenging depending on the special characteristics of the different studies, computational issues are considered to be its major bottlenecks. Among the latter, the bioinformatics analysis of metabarcoding data and especially the taxonomy assignment of the sequences are fundamental challenges. Many steps are required to obtain taxonomically assigned matrices from raw data. For most of these, a plethora of tools are available. However, each tool's execution parameters need to be tailored to reflect each experiment's idiosyncrasy; thus, tuning bioinformatics analysis has proved itself fundamental (Kamenova 2020). The computation capacity of high-performance computing systems (HPC) is frequently required for such analyses. On top of that, the non perfect completeness and correctness of the reference taxonomy databases is another important issue (Loos et al. 2020). Based on third-party tools, we have developed the Pipeline for Environmental Metabarcoding Analysis (PEMA), a HPC-centered, containerized assembly of key metabarcoding analysis tools. PEMA combines state-of-the art technologies and algorithms with an easy to get-set-use framework, allowing researchers to tune thoroughly each study thanks to roll-back checkpoints and on-demand partial pipeline execution features (Zafeiropoulos 2020). Once PEMA was released, there were two main pitfalls soon to be highlighted by users. PEMA supported 4 marker genes and was bounded by specific reference databases. In this new version of PEMA the analysis of any marker gene is now available since a new feature was added, allowing classifiers to train a user-provided reference database and use it for taxonomic assignment. Fig. 1 shows the taxonomy assignment related PEMA modules; all those out of the dashed box have been developed for this new PEMA release. As shown, the RDPClassifier has been trained with Midori reference 2 and has been added as an option, classifying not only metazoans but sequences from all taxonomic groups of Eukaryotes for the case of the COI marker gene. A PEMA documentation site is now also available. PEMA.v2 containers are available via the DockerHub and SingularityHub as well as through the Elixir Greece AAI Service. It has also been selected to be part of the LifeWatch ERIC Internal Joint Initiative for the analysis of ARMS data and soon will be available through the Tesseract VRE.

Environmental DNA and metabarcoding allow the identification of a mixture of species and launch a new era in bio- and eco-assessment. Many steps are required to obtain taxonomically assigned matrices from raw data. For most of these, a plethora of tools are available; each tool's execution parameters need to be tailored to reflect each experiment's idiosyncrasy. Adding to this complexity, the computation capacity of high-performance computing systems is frequently required for such analyses. To address the difficulties, bioinformatic pipelines need to combine state-of-the art technologies and algorithms with an easy to get-set-use framework, allowing researchers to tune each study. Software containerization technologies ease the sharing and running of software packages across operating systems; thus, they strongly facilitate pipeline development and usage. Likewise programming languages specialized for big data pipelines incorporate features like roll-back checkpoints and on-demand partial pipeline execution.PEMA is a containerized assembly of key metabarcoding analysis tools that requires low effort in setting up, running, and customizing to researchers' needs. Based on third-party tools, PEMA performs read pre-processing, (molecular) operational taxonomic unit clustering, amplicon sequence variant inference, and taxonomy assignment for 16S and 18S ribosomal RNA, as well as ITS and COI marker gene data. Owing to its simplified parameterization and checkpoint support, PEMA allows users to explore alternative algorithms for specific steps of the pipeline without the need of a complete re-execution. PEMA was evaluated against both mock communities and previously published datasets and achieved results of comparable quality.A high-performance computing-based approach was used to develop PEMA; however, it can be used in personal computers as well. PEMA's time-efficient performance and good results will allow it to be used for accurate environmental DNA metabarcoding analysis, thus enhancing the applicability of next-generation biodiversity assessment studies.

Genomic Observatories (GOs) are an increasingly important resource to study the effect of climate change on marine populations. The data gathered by GOs allow one to map and track how marine populations change with time and location, and how those changes relate to the local and global conditions. Such data may be used to calculate Essential Biodiversity Variables (EBVs) and can provide important information for predictive modelling of marine biodiversity. GOs are sites that are subject to long-term scientific research, including (but not limited to) the sustained study of genomic biodiversity from single-celled microbes to multicellular organisms. We are involved in a number of GO projects, including: Ocean Sampling Day (OSD): yearly, standardised water sampling from selected sites located all over the world. The data collected consist of (a)biotic parameters, DNA sequences extracted from the water samples, and species occurrences derived from analysis of the sequences. Marine Biodiversity Observation Network of Autonomous Reef Monitoring Structures (ARMS-MBON): yearly placement of sets of stacked plates along the harbours and coasts of Europe, deployed in place for months to allow species to settle on them. The data collected consist of images of the communities that settled on the plates, DNA sequences extracted from scrapings of the plates and the surrounding water, visual observations, and species occurrences derived from analysis of the sequences and the images. Ocean Sampling Day (OSD): yearly, standardised water sampling from selected sites located all over the world. The data collected consist of (a)biotic parameters, DNA sequences extracted from the water samples, and species occurrences derived from analysis of the sequences. Marine Biodiversity Observation Network of Autonomous Reef Monitoring Structures (ARMS-MBON): yearly placement of sets of stacked plates along the harbours and coasts of Europe, deployed in place for months to allow species to settle on them. The data collected consist of images of the communities that settled on the plates, DNA sequences extracted from scrapings of the plates and the surrounding water, visual observations, and species occurrences derived from analysis of the sequences and the images. The data collected from these GOs are not particularly complicated: sampling and sequencing protocols are well established and the images are taken with standard cameras. However, complexity arises when measurements need to be linked between multiple samples extracted from each event for each location and date, to all the data from all sampling events, and the results—species occurrences and abundances—obtained from the images and the sequences for each sample, must be linked together within that sampling event and between all sampling events of the GO project. measurements need to be linked between multiple samples extracted from each event for each location and date, to all the data from all sampling events, and the results—species occurrences and abundances—obtained from the images and the sequences for each sample, must be linked together within that sampling event and between all sampling events of the GO project. We also want to be able to compare data between different GO projects, and to be able to incorporate measurements from nearby monitoring stations, as this will allow for an enhanced analysis of the evolution of marine benthic populations in light of climate change. Our aim is to adopt the Darwin Core Archive (DwC-A) OBIS-ENV-DATA format for the data from ARMS-MBON and OSD, including the linkages to the images and sequences. ARMS-MBON presents a challenge because of the wide range of data collected. Our use-case for the data format we require contains the following elements: The ARMS-MBON data that are collected are the sequences obtained from the samples and the images taken of the communities on each ARMS plate. Species occurrences and added (a)biotic parameters only come later. However, we would like to adopt the DwC-A format already being widely used from the very beginning of our data management, with the species occurrences being added to the same DwC-A files when they are determined. The ARMS plate images will go through a few stages of processing: the raw images taken by the field scientists, and later annotated images created by the image-analysis software. We would like to link the raw and processed images to each other within the DwC-A files, so the user can obtain the processed image a species was identified in, and the raw image for its re-use. This same requirement applies to the sequence data. The ARMS plate images from each sampling event number many dozens. These are archived as ZIP files in the Marine Data Archive, and the links to them are made public via the metadata record in a catalogue. We would like to be able to add links in the DwC-A files to the individual images in the ZIP file that each species occurrence came from, and from which region(s) on the images they were found; so individual images can be referenced but the space saving advantage of ZIP can be used. In addition, we would like to explore the option of adding the images within the DwC-A (ZIP) file itself, rather than referencing them as URLs. For each sampling event we collect sequences and images, and species (occurrences) will be obtained from analysis of both types of data. It is necessary that these multiple and overlapping results can be linked to each other in a clear and consistent way. This means indicating clearly where sequences and images are of the same or of different material from any plate. The ARMS-MBON data that are collected are the sequences obtained from the samples and the images taken of the communities on each ARMS plate. Species occurrences and added (a)biotic parameters only come later. However, we would like to adopt the DwC-A format already being widely used from the very beginning of our data management, with the species occurrences being added to the same DwC-A files when they are determined. The ARMS plate images will go through a few stages of processing: the raw images taken by the field scientists, and later annotated images created by the image-analysis software. We would like to link the raw and processed images to each other within the DwC-A files, so the user can obtain the processed image a species was identified in, and the raw image for its re-use. This same requirement applies to the sequence data. The ARMS plate images from each sampling event number many dozens. These are archived as ZIP files in the Marine Data Archive, and the links to them are made public via the metadata record in a catalogue. We would like to be able to add links in the DwC-A files to the individual images in the ZIP file that each species occurrence came from, and from which region(s) on the images they were found; so individual images can be referenced but the space saving advantage of ZIP can be used. In addition, we would like to explore the option of adding the images within the DwC-A (ZIP) file itself, rather than referencing them as URLs. For each sampling event we collect sequences and images, and species (occurrences) will be obtained from analysis of both types of data. It is necessary that these multiple and overlapping results can be linked to each other in a clear and consistent way. This means indicating clearly where sequences and images are of the same or of different material from any plate. Clearly, a high degree of data standardisation is necessary to enable harmonisation of the data, to accommodate the multiple streams of linked data values, which will be added by multiple creators and users of the data.

In-situ oil burning (isOB) is one of the oil-spill mitigation measures and has been used after some major oil-spill events such as the Deepwater Horizon oil spill in the Gulf of Mexico. Although the ecological impact of oil spills and mitigation measures on the marine ecosystem are of great interest, the toxicity and biodegradation potential of isOB by-products have been poorly addressed and mainly are an unknown.We investigated the effects of burned oil residue and soot deposition on the marine plankton communities of the oligotrophic Eastern Mediterranean Sea using a mesocosm experimental approach. Coastal water (collected at 300 m from the coast, north of Crete, Greece) was incubated in 3.5 m3 mesocosms for 26 days. Three different treatments in triplicates were tested. In one treatment, 2 L of Iranian Crude Oil were added and burned (Burned treatment) while soot was collected and deposited in the form of artificial rain in more mesocosms (Soot treatment) using a custom-designed soot collection apparatus. The third treatment served as the non-contaminated control (Control treatment). Samples were collected at 9 time points (from Day 0 to Day 26) and the plankton, from viruses to micro-plankton, was studied using flow cytometry and inverted microscopy. Although the abundance of prokaryotes was slightly decreased in Burned and Soot treatments compared to the Control, the percentage of active heterotrophic bacteria and their relative size (based on their cytometric characteristics) was higher, which is an indication of increased bacterial activity in the contaminated treatments. Viral to Prokaryote Ratio and pico/nano-eukaryotic abundance were significantly increased in the Burned treatment compared to the Control, which could explain the lower bacterial abundance, despite the estimated increased activity, in the Burned treatment. Also, ciliate abundance was significantly lower in the Burned treatment while the opposite was observed in the Soot treatment (up to three orders of magnitude difference between Burned and Soot) compared to Control. Moreover, soot deposits seem to have had a positive effect on the abundance of dinoflagellates and diatoms.To our knowledge, this is the first experiment to study the effects of isOB on whole marine plankton communities. It is evident that the in-situ oil burning has a significant effect on the plankton communities not only at the event site but also on distant areas through the soot deposition.

Background Environmental DNA and metabarcoding allow the identification of a mixture of species and launch a new era in bio- and eco-assessment. Many steps are required to obtain taxonomically assigned matrices from raw data. For most of these, a plethora of tools are available; each tool's execution parameters need to be tailored to reflect each experiment's idiosyncrasy. Adding to this complexity, the computation capacity of high-performance computing systems is frequently required for such analyses. To address the difficulties, bioinformatic pipelines need to combine state-of-the art technologies and algorithms with an easy to get-set-use framework, allowing researchers to tune each study. Software containerization technologies ease the sharing and running of software packages across operating systems; thus, they strongly facilitate pipeline development and usage. Likewise programming languages specialized for big data pipelines incorporate features like roll-back checkpoints and on-demand partial pipeline execution. Findings PEMA is a containerized assembly of key metabarcoding analysis tools that requires low effort in setting up, running, and customizing to researchers’ needs. Based on third-party tools, PEMA performs read pre-processing, (molecular) operational taxonomic unit clustering, amplicon sequence variant inference, and taxonomy assignment for 16S and 18S ribosomal RNA, as well as ITS and COI marker gene data. Owing to its simplified parameterization and checkpoint support, PEMA allows users to explore alternative algorithms for specific steps of the pipeline without the need of a complete re-execution. PEMA was evaluated against both mock communities and previously published datasets and achieved results of comparable quality. Conclusions A high-performance computing–based approach was used to develop PEMA; however, it can be used in personal computers as well. PEMA's time-efficient performance and good results will allow it to be used for accurate environmental DNA metabarcoding analysis, thus enhancing the applicability of next-generation biodiversity assessment studies.

Genetic diversity and population distribution are influenced by environmental factors, yet information is scarce on the interrelations that define dispersal of populations. Transitional water ecosystems are hosting habitats with temporally and spatially variable conditions, which make them very useful in understanding the mechanisms affecting population establishment. For the study, seasonal samples were collected from four lagoons in the lagoonal complex of Amvrakikos Gulf (W Greece). The mitochondrial DNA (COI gene) was analysed from polychaetes ofNephtys hombergii, as it is considered an important component of these assemblages and shows great dispersal ability. The results of the genetic analysis showed intraspecific variability in all the lagoons, with genetic structuring tending to follow a seasonal pattern rather than a spatial one. The results of BIOENV analysis indicated correlation of the observed pattern with the water pH levels, the redox potential and the concentration of phosphate in the sediment. The complexity of the network suggested the enhancement of the local population with more recently established haplotypes. The findings of the study support the necessity of designing management strategies by taking into account genetic diversity and population demography approaches in addition to those based on species and habitats.

BackgroundEnvironmental DNA (eDNA) and metabarcoding, allow the identification of a mixture of individuals and launch a new era in bio- and eco-assessment. A number of steps are required to obtain taxonomically assigned (Molecular) Operational Taxonomic Unit ((M)OTU) tables from raw data. For most of these, a plethora of tools is available; each tool’s execution parameters need to be tailored to reflect each experiment’s idiosyncrasy. Adding to this complexity, for such analyses, the computation capacity of High Performance Computing (HPC) systems is frequently required.Software containerization technologies ease the sharing and running of software packages across operating systems; thus, they strongly facilitate pipeline development and usage. Likewise are programming languages specialized for big data pipelines, incorporating features like roll-back checkpoints and on-demand partial pipeline execution.FindingsPEMA is a containerized assembly of key metabarcoding analysis tools with a low effort in setting up, running and customizing to researchers’ needs. Based on third party tools, PEMA performs reads’ pre-processing, clustering to (M)OTUs and taxonomy assignment for 16S rRNA and COI marker gene data. Due to its simplified parameterisation and checkpoint support, PEMA allows users to explore alternative algorithms for specific steps of the pipeline without the need of a complete re-execution. PEMA was evaluated against previously published datasets and achieved comparable quality results.ConclusionsGiven its time-efficient performance and its quality results, it is suggested that PEMA can be used for accurate eDNA metabarcoding analysis, thus enhancing the applicability of next-generation biodiversity assessment studies.

Research Infrastructures (RIs) are facilities, resources and services used by scientists to perform research and support innovation. A number of EU research infrastructures [e.g. e-Science and Technology European Infrastructure for Biodiversity and Ecosystem Research (LifeWatch) European Research Iinfrastructures Consortium (ERIC); The European life-sciences Infrastructure for biological Information (ELIXIR); the European Marine Biological Resource Centre (EMBRC ERIC); the European Research Infrastructure for Imaging Technologies in Biological and Biomedical Sciences (uroBioImaging ERIC)] have been building Virtual Research Environments (VREs), which include many virtual laboratories (vLabs) offering, one stop data access to scientists, high computational capacity and collaborative research platforms in support of the requirements of the digital science. This presentation gives examples on the use of the vLabs developed by LifeWatch ERIC which have subsequently been taken up as web services by other RIs. The RvLab operates on a high-performance computer cluster, and has been used in order to analyse various properties of taxon equality, with a focus on marine species. This taxonomic information on marine biota is organized and made publicly available through the World Register of Marine Species (WoRMS) that delivers more than 250,000 described valid species names. Although scientists consider an equal status (in terms of contribution to overall diversity) to each taxon used in taxonomy, biogeography, ecology and biodiversity, the question “are all taxa equal?” has never been tested at a global scale. We present evidence that this question can be addressed by applying relatedness indices (Taxonomic Distinctness) over the entire WoRMS metazoan tree. The virtual micro-CT laboratory (Micro-CT vLab), which can be used by the members of the scientific community interested in the digitisation methods and biological collections, makes the micro-CT data exploration of natural history specimens freely available over the internet. Micro-CT vLab makes it possible the online exploration and dissemination of micro-CT datasets, which are only rarely made available to the public due to their very large size and a lack of dedicated online platforms supporting the interactive manipulation of 3D data. Examples of how these vLabs can be used by other RIs are provided.

The present study examines the genetic diversity (using cytochrome c oxidase subunit I (COI) haplotypes) of polychaete Hediste diversicolor populations in the Amvrakikos Gulf (western Greece) in order to test Cognetti's hypothesis on the formation of distinct isolated populations of species living in stressed transitional water habitats. To this purpose, the intraspecific diversity of H. diversicolor and the similarities among its populations in the brackish water habitats of the Eastern Mediterranean were investigated. Samples were collected from the lagoonal complex of Am - vrakikos Gulf in 2010 and 2011. Analysis showed that populations in the Amvrakikos Gulf share unique haplotypes which are distinct from the haplotypes hitherto reported, suggesting that these populations are highly isolated. This evidence partially supports Cognetti's hypothesis. The results indicate that the genetic differentiation in the studied populations was probably caused by the com- plete isolation of the gulf and periodic hypoxic conditions during its formation history. The occur- rence of unique haplotypes in the gulf underlines the importance of considering genetic diversity in the design of long-term biodiversity management and conservation plans.

The current article presents 18 new records from seven Mediterranean countries. These records include one rhodophyte, fournudibranchs, two crustaceans, one stingray and 10 bony fishes. They are grouped by country as follows: Lebanon - first record ofthe Striped bass Morone saxatilis, the stingray Himantura leoparda, the Areolate grouper Epinephelus areolatus and the Spot-finporcupinefish Diodon hystrix from various parts of the country; Turkey - first record of the invasive red alga Grateloupia turuturufrom the sea of Marmara (region of Bandırma), the sea slug Goniobranchus obsoletus and the crab Arcania brevifrons from theGulf of Antalya and the cladoceran Pleopis schmackeri from several locations along the Aegean Sea; Cyprus - first record of thealien sea slug Berthellina citrina from the region of Cape Greco and an observation of a butterflyfish Heniochus sp. from the northeasternside of the island; Greece - first record of the alien sea slug Anteaeolidiella lurana from the region of Heraklion in Creteand the record of the Atlantic spadefish Chaetodipterus faber and the Black surgeonfish Acanthurus cfr gahhm from SalaminaIsland; Slovenia - first record of the alien sea slug Thecacera pennigera from Izola; Italy - first record of the hybrid Striped bass(Morone saxatilis × Morone chrysops) from the northern Tyrrhenian Sea and a first record of the goldfish Carassius auratus fromthe region of Apulia; Libya - first record of the Red Sea goatfish Parupeneus forsskali and the African surgeonfish Acanthurusmonroviae, respectively from the eastern (Al-Tamimi area) and the western shore (Al-Khums area).

Within the COST action EMBOS (European Marine Biodiversity Observatory System) the degree and variation of the diversity and densities of soft-bottom communities from the lower intertidal or the shallow subtidal was measured at 28 marine sites along the European coastline (Baltic, Atlantic, Mediterranean) using jointly agreed and harmonized protocols, tools and indicators. The hypothesis tested was that the diversity for all taxonomic groups would decrease with increasing latitude. The EMBOS system delivered accurate and comparable data on the diversity and densities of the soft sediment macrozoobenthic community over a large-scale gradient along the European coastline. In contrast to general biogeographic theory, species diversity showed no linear relationship with latitude, yet a bell-shaped relation was found. The diversity and densities of benthos were mostly positively correlated with environmental factors such as temperature, salinity, mud and organic matter content in sediment, or wave height, and related with location characteristics such as system type (lagoons, estuaries, open coast) or stratum (intertidal, subtidal). For some relationships, a maximum (e.g. temperature from 15–20°C; mud content of sediment around 40%) or bimodal curve (e.g. salinity) was found. In lagoons the densities were twice higher than in other locations, and at open coasts the diversity was much lower than in other locations. We conclude that latitudinal trends and regional differences in diversity and densities are strongly influenced by, i.e. merely the result of, particular sets and ranges of environmental factors and location characteristics specific to certain areas, such as the Baltic, with typical salinity clines (favouring insects) and the Mediterranean, with higher temperatures (favouring crustaceans). Therefore, eventual trends with latitude are primarily indirect and so can be overcome by local variation of environmental factors.

Several models have been developed for the description of diversity in estuaries and other brackish habitats, with the most recognized being Remane’s Artenminimum (“species minimum”) concept. It was developed for the Baltic Sea, one of the world’s largest semi-enclosed brackish water body with a unique permanent salinity gradient, and it argues that taxonomic diversity of macrobenthic organisms is lowest within the horohalinicum (5 to 8 psu). The aim of the present study was to investigate the relationship between salinity and sediment microbial diversity at a freshwater-marine transect in Amvrakikos Gulf (Ionian Sea, Western Greece) and assess whether species composition and community function follow a generalized concept such as Remane’s. DNA was extracted from sediment samples from six stations along the aforementioned transect and sequenced for the 16S rRNA gene using high-throughput sequencing. The metabolic functions of the OTUs were predicted and the most abundant metabolic pathways were extracted. Key abiotic variables, i.e., salinity, temperature, chlorophyll-a and oxygen concentration etc., were measured and their relation with diversity and functional patterns was explored. Microbial communities were found to differ in the three habitats examined (river, lagoon and sea) with certain taxonomic groups being more abundant in the freshwater and less in the marine environment, andvice versa. Salinity was the environmental factor with the highest correlation to the microbial community pattern, while oxygen concentration was highly correlated to the metabolic functional pattern. The total number of OTUs showed a negative relationship with increasing salinity, thus the sediment microbial OTUs in this study area do not follow Remane’s concept.