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.

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.

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.