| Summary: | Pollen-based reconstructions of land-cover by using the landscape reconstruction algorithm (LRA) have been produced for several years in the most populated areas of the world. This is not the case in the Arctic tundra, partly because of the lack of pollen productivity estimates (PPE) of the tundra vegetation, partly because the area is virtually uninhabited and hence not in a significant role when the focus is on land-use change and its role in the anthropogenic climate forcing. Reindeer (Rangifer tarandus) is the dominant large herbivore affecting the vegetation of the northern Eurasian tundra. It has been observed throughout the Arctic, and especially in Fennoscandia and northern Russia, that human-animal impact, e.g. concentrated grazing and trampling by semi-domesticated reindeer herds have changed the vegetation at large by creating graminoid dominated green patches, which have persisted over the centuries in some places. To be able to model the effects that the growing size of the reindeer herds has had on the vegetation since the beginning of the domestication about 1500 years ago, a set of PPEs from the Arctic tundra will be needed. Current work aims to produce the relative pollen productivity estimates for the most common taxa in tundra. The research area is located on the south side of the Yuribey River in the Central Yamal Peninsula, western Siberia, Russia. Vegetation in the area is grass and sedge dominated dwarf shrubs tundra, Betula nana and Salix sp. growing in the moist areas. A series of 46 surface pollen samples with the percentage cover of the vegetation estimated around them were collected during two summer field seasons in 2013 (30 samples) and 2014 (16 samples). The vegetation data for the distance weighted plant abundance will be combined from field observations and ground truthed very high resolution WorldView-2 satellite data. With the current set of data, the pollen productivity estimates are obtainable to Poaceae, Cyperaceae, Salix, Betula nana, Rubus chamaemorus, Artemisia, and to ...
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