Analysis of phytoplankton assemblage structure in the Mediterranean Sea based on high-throughput sequencing of partial 18S rRNA sequences.

Studying taxonomic and ecological diversity of phytoplankton assemblages is often difficult because morphological analysis cannot provide a complete description of their composition. Therefore, more robust and feasible approaches have to be chosen to elucidate the interactions between environmental and human pressures and phytoplankton assemblages. The Ocean Sampling Day (OSD) allowed collecting seawater samples from a wide range of oceanic regions including the Mediterranean Sea. In this study, a total of 754,167 V4-18S ribosomal DNA (rDNA) metabarcodes derived from 20 plankton samples collected at 19 sampling sites across the coastal areas of the Mediterranean Sea were analyzed to explore the relationships between phytoplankton assemblages' composition, sub-regional environmental features and human pressures. We reduced the whole set of autotroph plankton (1398 OTUs) to a smaller number of ecologically relevant entities (205 taxa) and used the latter for analysing the structure of phytoplankton assemblages. Chaetoceros was the only genus occurring in all the samples, while the number of taxa was maximum in the W Mediterranean. Based on the assigned OTUs, the structure of E Mediterranean phytoplankton was the most homogeneous. Further, phytoplankton assemblages from the three Mediterranean sub-regions (Western, Adriatic and Eastern) were significantly different (R=0.25, p=0.0136) based on Jaccard similarity. We also observed that phytoplankton diversity and human impact on marine ecosystems were not significantly related to each other based on Mantel's test.

BioVeL: a virtual laboratory for data analysis and modelling in biodiversity science and ecology.

BACKGROUND: Making forecasts about biodiversity and giving support to policy relies increasingly on large collections of data held electronically, and on substantial computational capability and capacity to analyse, model, simulate and predict using such data. However, the physically distributed nature of data resources and of expertise in advanced analytical tools creates many challenges for the modern scientist. Across the wider biological sciences, presenting such capabilities on the Internet (as "Web services") and using scientific workflow systems to compose them for particular tasks is a practical way to carry out robust "in silico" science. However, use of this approach in biodiversity science and ecology has thus far been quite limited. RESULTS: BioVeL is a virtual laboratory for data analysis and modelling in biodiversity science and ecology, freely accessible via the Internet. BioVeL includes functions for accessing and analysing data through curated Web services; for performing complex in silico analysis through exposure of R programs, workflows, and batch processing functions; for on-line collaboration through sharing of workflows and workflow runs; for experiment documentation through reproducibility and repeatability; and for computational support via seamless connections to supporting computing infrastructures. We developed and improved more than 60 Web services with significant potential in many different kinds of data analysis and modelling tasks. We composed reusable workflows using these Web services, also incorporating R programs. Deploying these tools into an easy-to-use and accessible 'virtual laboratory', free via the Internet, we applied the workflows in several diverse case studies. We opened the virtual laboratory for public use and through a programme of external engagement we actively encouraged scientists and third party application and tool developers to try out the services and contribute to the activity. CONCLUSIONS: Our work shows we can deliver an operational, scalable and flexible Internet-based virtual laboratory to meet new demands for data processing and analysis in biodiversity science and ecology. In particular, we have successfully integrated existing and popular tools and practices from different scientific disciplines to be used in biodiversity and ecological research.