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The necessity of accurate past climate reconstructions for climate modelling is a key issue in (paleo)ecology. Especially, dryland such as Arid Central Asian deserts may spread in the next decades in surrounding steppes due to aridification. Several methods already exist to convert pollen in quantitative climate (transfer functions) and biome (biomization). However, these methods are impeded by numerous biases, which could be overcome by current breakthrough in plant functional response to climate understanding.Few past pollen studies attempt to merge plant functional traits with pollen samples in order to reconstruct paleo-trait cover and functional vegetation dynamics. However, this approach has not been tested using modern samples. Especially, since the taxonomic resolution used in ecology is not the same as the one used in pollen studies (usually family or genus pollen identification), whether the phenotypic space of extant vegetation is consistent with that derived from pollen modern samples remains an open question.Here, we tested the performance of combining paleoecology and plant functional ecology to validate the use of pollen to infer the phenotypic space of past vegetation. The pollen surface sites from Arid Central Asia (n = 2393) have been extracted and the pollen-types have been used to aggregate traits (height, leaf area, leaf nitrogen, seed mass, specific leaf area and stem specific density from TRY, BIEN and GIFT databases). Then, the community-weighted mean (CWM) traits have been calculated using the pollen fractional abundances. These pollen-CWM traits have been compared with the vegetation-CWM (n = 21347). Finally, both have been related to current climate parameters.The preliminary results of this study show that the trait values aggregated by pollen-types respect the same plant economic spectrum than observed in botanical taxonomic resolution. Moreover, it validates the use of pollen as equivalent of vegetation plots to calculate the CWM. It also appears that the scheme of aggregation ...
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