A range of advanced modelling approaches has been used so far to assess the impact of global change on biodiversity and ecosystems. These assessments include advanced socio-economic scenarios and yield projections of the distribution of species, communities and biomes and the functioning of ecosystems. Future goods and services are then assessed from these projections. However, four main limitations remain associated with these approaches:
1. knowledge and data of past species’ distribution is still limited, yet necessary for testing them in the past before projecting them to the future
2. we miss sound estimates of species’ long distance migration rates in order to assess whether species will be able to keep pace with rapid global change
3. some key assumptions of models, such as niche stability over time and/or space, are not well tested
4. we need more reliable estimate of uncertainties in model predictions

Our project specifically proposes to go one step further by:
1. integrating different modelling approaches currently in use (niche-based, dynamic, dispersal, etc.), and by developing robust methodologies to estimate uncertainties associated with these projections
2. generating required new data (palaeo & migration) by using innovative DNA-based approaches, and global change scenarios
3. testing niche conservatism and temporal evolution of biological communities
4. using the new data in improved and integrated models to make projections more robust and realistic
5. testing these approaches in case study areas and expanding the current projections to all of Europe.

Our consortium encompasses a wide spectrum of skills required to meet these objectives. Our final goal is to provide data, scenarios and associated confidence limits so that policy markers and land managers can use them for anticipating societal problems and for designing sustainable conservation strategies by accounting the most likely global change effects on biodiversity and ecosystems.