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.

Evaluating the potential of ecological niche modelling as a component in marine non-indigenous species risk assessments.

Marine biological invasions have increased with the development of global trading, causing the homogenization of communities and the decline of biodiversity. A main vector is ballast water exchange from shipping. This study evaluates the use of ecological niche modelling (ENM) to predict the spread of 18 non-indigenous species (NIS) along shipping routes and their potential habitat suitability (hot/cold spots) in the Baltic Sea and Northeast Atlantic. Results show that, contrary to current risk assessment methods, temperature and sea ice concentration determine habitat suitability for 61% of species, rather than salinity (11%). We show high habitat suitability for NIS in the Skagerrak and Kattegat, a transitional area for NIS entering or leaving the Baltic Sea. As many cases of NIS introduction in the marine environment are associated with shipping pathways, we explore how ENM can be used to provide valuable information on the potential spread of NIS for ballast water risk assessment.

Mapping present and future potential distribution patterns for a meso-grazer guild in the Baltic Sea.

AIM: The Baltic Sea is one of the world's largest semi-enclosed brackish water bodies characterized by many special features, including endemic species that may be particularly threatened by climate change. We mapped potential distribution patterns under present and future conditions for a community with three trophic levels. We analysed climate-induced changes in the species' distribution patterns and examined possible consequences for the chosen food web. LOCATION: Baltic Sea and northern Europe. METHODS: We developed two open-source workflow-based analytical tools: one for ecological niche modelling and another for raster layer comparison to compute the extent and intensity of change in species' potential distributions. Individual ecological niche models were generated under present conditions and then projected into a future climate change scenario (2050) for a food web consisting of a guild of meso-grazers (Idotea spp.), their host algae (Fucus vesiculosus and Fucus radicans) and their fish predator (Gasterosteus aculeatus). We used occurrence data from the Global Biodiversity Information Facility (GBIF), literature and museum collections, together with five environmental layers at a resolution of 5 and 30 arc-minutes. RESULTS: Habitat suitability for Idotea balthica and Idotea chelipes in the Baltic Sea seems to be mostly determined by temperature and ice cover rather than by salinity. 2050 predictions for all modelled species show a northern/north-eastern shift in the Baltic Sea. The distribution ranges for Idotea granulosa and G. aculeatus are predicted to become patchier in the Baltic than in the rest of northern Europe, where the species will gain more suitable habitats. MAIN CONCLUSIONS: For the Baltic Sea, climate-induced changes resulted in a gain of suitable habitats for F. vesiculosus,I. chelipes and I. balthica, whereas lower habitat suitability was predicted for I. granulosa,F. radicans and G. aculeatus. The predicted north-eastern shift of I. balthica and I. chelipes into the distribution area of F. radicans in the Baltic Sea may result in increased grazing pressure. Such additional threats to isolated Baltic populations can lead to a higher extinction risk for the species, especially as climate changes are likely to be very rapid.