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Pollen productivity estimates for quantitative reconstruction of vegetation cover on the Swiss Plateau

Palaeoecology, Institute of Environmental Biology, Faculty of Science, Utrecht University, Laboratory of Palaeobotany and Palynology, Budapestlaan 4, 3584 CD Utrecht, The Netherlands, welmoed.soepboer{at}gmail.com

Shinya Sugita

Department of Ecology, Evolution, and Behavior, University of Minnesota, 100 Ecology Building, 1987 Upper Buford Circle, St Paul MN 55108, USA

André F. Lotter

Palaeoecology, Institute of Environmental Biology, Faculty of Science, Utrecht University, Laboratory of Palaeobotany and Palynology, Budapestlaan 4, 3584 CD Utrecht, The Netherlands

Jacqueline F.N. van Leeuwen

Institute of Plant Sciences, University of Bern, Altenbergrain 21, CH-3013 Bern, Switzerland

Willem O. van der Knaap

Institute of Plant Sciences, University of Bern, Altenbergrain 21, CH-3013 Bern, Switzerland

We present the first step to quantitatively reconstruct vegetation cover in central Europe. Modern vegetation and pollen deposition were compared for 20 small to medium sized lakes and their catchments on the Swiss Plateau, a relatively flat region between the Jura Mountains and the Alps. To correct for the pollen dispersal bias in pollen assemblages, vegetation abundance was distance-weighted using three different approaches. The Relevant Source Area of Pollen (RSAP) and pollen productivity of 13 plant taxa were estimated using three different submodels of the Extended R-Value model (ERV-model). RSAP was 800 m regardless of the applied distance-weighting or ERV submodel. Pollen Productivity Estimates (PPE) varied from 10 to < 0.1 among pollen taxa and differed slightly between the models. Relative to grasses most trees were higher pollen producers and some were equal producers, whereas the herb taxa showed lower PPE. Generally, PPE from lowland Switzerland differ from those found in other European regions. Sampling strategies of vegetation and pollen samples are a likely cause for this variation. However, pollen productivity is also influenced by regionally different factors, such as climate, vegetation structure, geology and soil types. In addition, differences at genus or species level may occur between areas. Our comparison between the different regions in Europe shows that PPE of one region may not be directly applicable to other regions.

Key Words: Extended R-value model • pollen-vegetation relationships • Prentice-Sugita model • Relevant Source Area of Pollen • Pollen Productivity Estimates • Switzerland

The Holocene, Vol. 17, No. 1, 65-77 (2007)
DOI: 10.1177/0959683607073279


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