Biome models allow the results of experiments with atmospheric general circulation models to be translated into global maps of potential natural vegetation. The use of biome models as a diagnostic tool for palaeoclimate simulations can yield maps that are directly comparable with palaeoecological (pollen and plant macrofossil) records provided these records are "biomized", i.e. assigned to biomes in a consistent way. This article describes a method for the objective biomization of pollen samples based on fuzzy logic. Pollen types (taxa) are assigned to one or more plant functional types (PFTs), then affinity scores are calculated for each biome in turn based on its list of characteristic PFTs. The pollen sample is assigned to the biome to which it has the highest affinity, subject to a tie-breaking rule. Modern pollen data from surface samples, reflecting present vegetation across Europe, are used to validate the method. Pollen data from dated sediment cores are then used to reconstruct European vegetation patterns for 6 ka. The reconstruction shows systematic differences from present that are consistent with previous interpretations. The method has proved robust with respect to human impacts on vegetation, and provides a rational way to interpret combinations of pollen types that do not have present-day analogs. The method demands minimal prior information and is therefore equally suitable for use in other regions with richer floras, and/or lower densities of available modern and fossil pollen samples, than Europe.
|Number of pages||10|
|Publication status||Published - Feb 1996|