BIOME 6000: reconstructing global mid-Holocene vegetation patterns from palaeoecological records
Article first published online: 5 JAN 2002
1998 Blackwell Science Ltd.
Journal of Biogeography
Volume 25, Issue 6, pages 997–1005, November 1998
How to Cite
Prentice, I. C. and Webb III, T. (1998), BIOME 6000: reconstructing global mid-Holocene vegetation patterns from palaeoecological records. Journal of Biogeography, 25: 997–1005. doi: 10.1046/j.1365-2699.1998.00235.x
- Issue published online: 5 JAN 2002
- Article first published online: 5 JAN 2002
- Cited By
- plant functional type;
- climate change
Global change research needs data sets describing past states of the Earth system. Vegetation distributions for specified ‘time slices’ (with known forcings, such as changes in insolation patterns due to the Earth's orbital variations, changes in the extent of ice-sheets, and changes in atmospheric trace-gas composition) should provide a benchmark for coupled climate-biosphere models. Pollen and macrofossil records from dated sediments give spatially extensive coverage of data on vegetation distribution changes. Applications of such data have been delayed by the lack of a global synthesis. The BIOME 6000 project of IGBP aims at a synthesis for 6000 years bp. Success depends on community-wide participation for data compilation and quality assurance, and on a robust methodology for assigning palaeorecords to biomes. In the method summarized here, taxa are assigned to one or more plant functional types (PFTs) and biomes reconstructed using PFT-based definitions. By involving regional experts in PFT assignments, one can combine data from different floras without compromising global consistency in biome assignments. This article introduces a series of articles that substantially extend the BIOME 6000 data set. The list of PFTs and the reconstruction procedure itself are evolving. Some compromises (for example, restricted taxon lists in some regions) limit the precision of biome assignments and will become obsolete as primary data are put into community data bases. This trend will facilitate biome mapping for other time slices. Co-evolution of climate-biosphere modelling and palaeodata synthesis and analysis will continue.