Pollenproductivity estimates (PPE) areusedto quantitatively reconstruct variations invegetation withina specific distance of the sampled pollen archive. Here, for the first time, PPEs fromSiberia are presented. The study area (Khatanga region, Krasnoyarsk territory, Russia) is located in the Siberian Sub-arctic where Larix is 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 vegetationwere investigated to extract PPEs. Our results indicate some differences in pollen spectra betweenmoss 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 datasets should use archives of similar sedimentary origin. Results of an Extended R-Valuemodelwere applied to assess the relevant source area of pollen (RSAP) and to cal- culate the PPEs for both datasets. As expected, the RSAP of the moss samples was very small (about 10m) com- pared 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 Alnus fruticosa-type (PPEmoss:6.4, PPElake:2.9) were overrepresented while Cyperaceae (PPEmoss:0.5, PPElake:0.1), Ericaceae (PPEmoss: 0.3, PPElake b 0.01), Salix (PPEmoss:0.03, PPElake b 00.1) and Larix (PPEmoss: b0.01, 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, Larix gmelinii, is the first published result for this species, but needs to be considered very preliminary. The inferred sequence from over- to under- representation is mostly consistent with results from Europe; however, the absolute values show some differ- ences. Gathering vegetation datawas limited by the remoteness of our study area and a lack of high-resolute sat- ellite imagery and vegetation maps. Our estimate may serve as a first reference to strengthen future vegetation reconstructions in this climate-sensitive region.