Relative pollen productivity estimates for common taxa of the northern Siberian Arctic.

Abstract

Pollen productivity estimates (PPE) are used to quantitatively reconstruct variations in vegetation within a specific distance of the sampled pollen archive. Here, for the first time, PPEs from Siberia are presented. The study area (Khatanga region, Krasnoyarsk territory, Russia) is located in the Siberian Sub-arctic where Larixis the sole forest-line forming tree taxon. Pollen spectra from two different sedimentary environments, namely terrestrial mosses (n=16) and lakes (n=15, median radius ~100 m) and their surrounding vegetation were investigated to extract PPEs. Our results indicate some differences in pollen spectra between moss and lake pollen. Larix and Cyperaceae for example obtained higher representation in the lacustrine than in terrestrial moss samples. This highlights that in calibration studies modern and fossil dataset should be of similar sedimentary origin. The results of the Extended R-Value model were applied to assess the relevant source area of pollen (RSAP) and to calculate the PPEs for both datasets. As expected, the RSAP of the moss samples was very small (about 10 m) compared to the lacustrine samples (about 25 km). Calculation of PPEs for the six most common taxa yielded generally similar results for both datasets. Relative to Poaceae (reference taxon, PPE=1) Betula nana-type (PPEmoss: 1.8, PPElake: 1.8) and Alnusfruticosa-type (PPEmoss: 6.4, PPElake: 2.9) were overrepresented while Cyperaceae (PPEmoss: 0.5, PPElake: 0.1), Ericaceae (PPEmoss: 0.3, PPElake <0.01), Salix (PPEmoss: 0.03, PPElake <0.01) and Larix (PPEmoss <0.01, PPElake: 0.2) were under-represented in the pollen spectra compared to the vegetation in the RSAP. The estimation for the dominant tree in the region, Larixgmelinii, is the first published result for this species, but need to be considered very preliminary. The inferred sequence from over- to under-representation is mostly consistent with results from Europe; however, still the absolute values show some differences. Gathering vegetation data was limited by flowering season and low resolute satellite imagery and accessibility of the remote location of our study area. Therefore, our estimate may serve as first reference to strengthen future vegetation reconstructions in this climate-sensitive region.