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Gaillard-Lehmdahl, Marie-José (2019): Holocene quantitative vegetation reconstruction from Europe. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.897303 (dataset in review)

Abstract:
The REVEALS model
Pollen percentages (or proportions) have a non-linear relationship with vegetation abundance (in percentage cover or proportions), which makes quantitative reconstructions of vegetation problematical (e.g. Sugita et al., 1998). Moreover, the pollen-vegetation relationship is influenced by inter-taxonomic differences in pollen productivity and dispersal properties, as well as by the size and type of the sedimentary basin (e.g. Sugita, 1994). The "Regional Estimates of VEgetation Abundance from Large Sites" (REVEALS) model developed by Sugita (2007a) accounts for these factors and corrects for some of the biases inherent in pollen data. Given that estimates of pollen productivity and fall speed of pollen are available for some plant taxa, the REVEALS model can calculate estimates of past, regional vegetation abundance in proportions or percentage cover using fossil pollen counts from large sites (>48 ha, i.e. mean radius of the site > ca. 390 m, according to simulations; Sugita, 2007a).
The spatial resolution of the REVEALS model-based reconstructions (ca. 100 km x 100 km) is appropriate for the study of land-cover-climate relationships within the LANDCLIM project because the regional climate model RCA3 and the dynamic vegetation model LPJ-GUESS models used in the project perform well at a spatial scale of 0.5° to 1º. Therefore, we use a common grid-cell size of 1ºx1º, which corresponds to an area of ca 100 km x 100 km or less depending on the latitudinal location, for the REVEALS-based reconstructions of regional vegetation/land-cover presented in this paper (i.e. grid-based REVEALS estimates abbreviated REVEALS).
Before deciding on the criteria for selection of sites and parameters for the LANDCLIM project, Mazier et al. (2012) used the Czech Quaternary Pollen Database (PALYCZ; Kuneš et al., 2009) to evaluate the extent to which the selection of different input data and parameters would affect the REVEALS reconstructions. The tested parameters were the number of 14C dates per pollen record used to establish the chronology (minimum of 3 or 5 dates), the basin type (lake or bog) and size (site radius), the number of taxa (25, 28, or 35 taxa), the PPEs (three different sets of estimates), and the value of Zmax (50, 100, or 200 km). Spearman's rank-order correlation coefficient rs (Siegel & Castellan, 1988) was used to compare the REVEALS PFTs between the different model outputs, and the significance of the correlation was tested. Spearman's rank-order correlation is a non-parametric statistic test that measures the degree of association between two sets of data, in this case REVEALS PFTs.
The PPE set "standard 2" was preferred because the causes behind differences in PPEs between studies and regions are still not fully understood. Possible explanations are the various types of pollen and vegetation data used for the calculation of PPEs (pollen data from lakes, bogs, or moss polsters; pollen and vegetation data from modern or historical time) or the different methods used in the vegetation surveys. Between-region differences might be due to contrasting climate, species composition, or land-use management (Broström et al., 2008).
Five time-windows of the Holocene were selected for the study. They represent contrasting land-cover in terms of vegetation composition and degree of vegetation openness (forested land versus open/non-forested land) (Gaillard et al., 2010). Moreover, because the error estimates of the REVEALS reconstructions will decrease (i.e. their precision increase) with the increase of the size of the pollen counts (Sugita, 2007a), we chose to work with 500 year-long time-windows (except for the two most recent ones) to maximise the number of counted levels within a time-window. The five time-windows studied in the LANDCLIM project are as follows (in calibrated years before present (BP = before 1950)):
1. x-0.1k BP (ca. 0.05k BP, "Present"/Recent past): industrial time (x = date of the core surface, e.g. AD 2005-100 BP if x= AD 2005),
2. 0.1k-0.35k BP (ca. 0.2k BP, end of the Little Ice Age): pre-industrial time,
3. 0.35k-0.7k BP (ca. 0.5k BP, Middle Ages): decreased human impact in parts of Europe,
4. 2.7k-3.2k BP (ca. 3k BP, Early/Late Bronze Age transition): relatively strong human impact in several parts of the study region,
5. 5.7k-6.2k BP (ca. 6k BP, Neolithic period/ Mesolithic-Early Neolithic boundary in southern Scandinavia, northern Germany. and northern Netherlands): low human activity.
Further details:
Broström, Anna; Nielsen, Anne Birgitte; Gaillard, Marie-José; Hjelle, Kari; Mazier, Florence; Binney, Heather; Bunting, M Jane; Fyfe, Ralph M; Meltsov, Viveca; Poska, Anneli; Räsänen, Satu; Soepboer, Welmoed; von Stedingk, Henrik; Suutari, Henna; Sugita, Shinya (2008): Pollen productivity estimates of key European plant taxa for quantitative reconstruction of past vegetation: a review. Vegetation History and Archaeobotany, 17(5), 461-478, https://doi.org/10.1007/s00334-008-0148-8
Gaillard, Marie-José; Sugita, Shinya; Mazier, Florence; Trondman, Anna-Kari; Broström, Anna; Hickler, Thomas; Kaplan, Jed O; Kjellström, Erik; Kokfelt, Ulla; Kunes, Petr; Lemmen, Carsten; Miller, P; Olofsson, Jörgen; Poska, A; Rundgren, M; Smith, Benjamin; Strandberg, Gustav; Fyfe, Ralph M; Nielsen, Anne Birgitte; Alenius, T; Balakauskas, L; Barnekow, L; Birks, H John B; Bjune, Anne Elisabeth; Björkman, L; Giesecke, Thomas; Hjelle, Kari; Kalnina, L; Kangur, M; van der Knaap, Pim Willem O; Koff, Tiiu; Lageras, P; Latalowa, Malgorzata; Leydet, Michelle; Lechterbeck, Jutta; Lindbladh, M; Odgaard, Bent V; Peglar, Sylvia; Segerström, Ulf; von Stedingk, Henrik; Seppä, Heikki (2010): Holocene land-cover reconstructions for studies on land cover-climate feedbacks. Climate of the Past Discussions, 6(2), 307-346, https://doi.org/10.5194/cpd-6-307-2010
Kunes, Petr; Abraham, Vojtěch; Kovařík, Oleg; Kopecký, Martin; PALYCZ contributors (2009): Czech Quaternary Palynological Database – PALYCZ: review and basic statistics of the data. Preslia, 81, 209-238
Mazier, Florence; Gaillard, Marie-José; Kunes, Petr; Sugita, Shinya; Trondman, Anna-Kari; Broström, Anna (2012): Testing the effect of site selection and parameter setting on REVEALS-model estimates of plant abundance using the Czech Quaternary Palynological Database. Review of Palaeobotany and Palynology, 187, 38-49, https://doi.org/10.1016/j.revpalbo.2012.07.017
Siegel, Sidney; Castellan, N John (1988): Nonparametric statistics for the behavioral sciences. McGraw-Hill International Editions, Boston
Sugita, Shinya (1994): Pollen Representation of Vegetation in Quaternary Sediments: Theory and Method in Patchy Vegetation. Journal of Ecology, 82(4), 881, https://doi.org/10.2307/2261452
Sugita, Shinya (2007): Theory of quantitative reconstruction of vegetation I: pollen from large sites REVEALS regional vegetation composition. The Holocene, 17(2), 229-241, https://doi.org/10.1177/0959683607075837
Parameter(s):
#NameShort NameUnitPrincipal InvestigatorMethodComment
1File contentContentGaillard-Lehmdahl, Marie-José
2File nameFile nameGaillard-Lehmdahl, Marie-José
3File formatFile formatGaillard-Lehmdahl, Marie-José
4File sizeFile sizekByteGaillard-Lehmdahl, Marie-José
5Uniform resource locator/link to fileURL fileGaillard-Lehmdahl, Marie-José
Size:
10 data points

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