2014
DOI: 10.1016/j.quascirev.2014.02.013
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Holocene changes in vegetation composition in northern Europe: why quantitative pollen-based vegetation reconstructions matter

Abstract: International audienceWe present pollen-based reconstructions of the spatio-temporal dynamics of northern European regional vegetation abundance through the Holocene. We apply the Regional Estimates of VEgetation Abundance from Large Sites (REVEALS) model using fossil pollen records from eighteen sites within five modern biomes in the region. The eighteen sites are classified into four time-trajectory types on the basis of principal components analysis of both the REVEALS-based vegetation estimates (RVs) and t… Show more

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Cited by 114 publications
(109 citation statements)
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“…Recent advances in reconstruction approaches at the regional scale (considering vegetation composition in areas with radii 50-100km) show the potential of these methods (Marquer, et al 2014, Trondman, et al 2015, but by averaging a large number of small sites or using large (500ha plus In this paper, we show that linear regression of pollen influx from Tauber traps against distance weighted plant abundance generates RPP Quercus values for eight tree taxa which are comparable with previous European studies (e.g. Sugita, et al 1999;Mazier, et al 2012), whilst ERV analysis results were unreliable.…”
Section: Reconstruction Methodsmentioning
confidence: 99%
“…Recent advances in reconstruction approaches at the regional scale (considering vegetation composition in areas with radii 50-100km) show the potential of these methods (Marquer, et al 2014, Trondman, et al 2015, but by averaging a large number of small sites or using large (500ha plus In this paper, we show that linear regression of pollen influx from Tauber traps against distance weighted plant abundance generates RPP Quercus values for eight tree taxa which are comparable with previous European studies (e.g. Sugita, et al 1999;Mazier, et al 2012), whilst ERV analysis results were unreliable.…”
Section: Reconstruction Methodsmentioning
confidence: 99%
“…However, the issues described above present a problem: few independent observations have been available at appropriate spatial and temporal resolution with which to evaluate continental-and global-scale ALCC scenarios. Fortunately, recent developments in the quantitative reconstruction of land cover using paleoecological archives [37,38] and efforts to apply these methods in a synthetic way at continental scales [39][40][41] provide new opportunities for evaluating ALCC models and their scenarios.…”
Section: Introductionmentioning
confidence: 99%
“…While the theory for the quantitative reconstruction of land cover based on pollen records has existed for decades [42][43][44][45], large-scale reconstructions only became possible more recently with the development of computer programs [37,38,46], and the intensive field studies were needed to parameterize these models regionally [39,47,48]. The REVEALSmethod of quantitative pollen-based land cover reconstruction [37], has been applied in a number of regional studies in Europe [41,46,47,49] and in sub-continental syntheses for northwestern and northern Central Europe [40,50]. This large-scale synthesis provides, for the first time, an independent estimate of land cover at a spatial and temporal scale suitable for the evaluation of ALCC scenarios.…”
Section: Introductionmentioning
confidence: 99%
“…Although many palaeoecological studies have been undertaken in this general region, most of these have focused on the north-western and central parts of the East European Plain, Fennoscandia and eastern Baltic region (Khotinsky and Klimanov, 1997;Krementski et al, 2000, Seppä andBirks, 2001;Seppä and Poska, 2004;Saarse et al, 2010) with many fewer at the southern margin and little explicit consideration of the dynamics of the forest-steppe ecotone . At this ecotone there is evidence for a long history of human occupation which has driven change in vegetation in concert with climate (Marquer et al, 2014).…”
Section: Introductionmentioning
confidence: 99%