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- Gaillard, Marie-Jose, et al.
(author)
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The use of modelling and simulation approach in reconstructing past landscapes from fossil pollen data: a review and results from the POLLANDCAL network
- 2008
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In: Vegetation History and Archaeobotany. - : Springer Science and Business Media LLC. - 0939-6314 .- 1617-6278. ; 17:5, s. 419-443
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Journal article (peer-reviewed)abstract
- Information on past land cover in terms of absolute areas of different landscape units (forest, open land, pasture land, cultivated land, etc.) at local to regional scales is needed to test hypotheses and answer questions related to climate change (e.g. feedbacks effects of land-cover change), archaeological research, and nature conservancy (e.g. management strategy). The palaeoecological technique best suited to achieve quantitative reconstruction of past vegetation is pollen analysis. A simulation approach developed by Sugita (the computer model POLLSCAPE) which uses models based on the theory of pollen analysis is presented together with examples of application. POLLSCAPE has been adopted as the central tool for POLLANDCAL (POLlen/LANdscape CALibration), an international research network focusing on this topic. The theory behind models of the pollen-vegetation relationship and POLLSCAPE is reviewed. The two model outputs which receive greatest attention in this paper are the relevant source area of pollen (RSAP) and pollen loading in mires and lakes. Six examples of application of POLLSCAPE are presented, each of which explores a possible use of the POLLANDCAL tools and a means of validating or evaluating the models with empirical data. The landscape and vegetation factors influencing the size of the RSAP, the importance of pollen productivity estimates (PPEs) for the model outputs, the detection of small and rare patches of plant taxa in pollen records, and quantitative reconstructions of past vegetation and landscapes are discussed on the basis of these examples. The simulation approach is seen to be useful both for exploring different vegetation/landscape scenarios and for refuting hypotheses.
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