ECOCHANGE

A range of advanced modelling approaches has been used to assess the impact of global change on biodiversity and ecosystems. These approaches yield projections of the distribution of species, communities and biomes and the functioning of ecosystems. Changes in the provision of 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 distributions is still limited, yet it is necessary for testing them in the past before projecting them to the future;
2. There is a lack of sound estimates of species' long distance migration rates that are necessary 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. There is a need for more reliable estimates of uncertainties in model predictions.

ECOCHANGE 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 specifically in ecosystems of Fennoscandian and the Alps and by expanding the current projections to all of Europe.

ECOCHANGE encompasses a wide spectrum of skills required to meet these objectives. The 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.

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