Pollen-based reconstructions from Lake Fazilman, Uzbekistan - Dugerdil, Lucas; Ménot, Guillemette; Peyron, Odile; Egamberdieva, Dilfuza; Jouffroy-Bapicot, Isabelle; Vannière, Boris; Alimov, Jakhongir; Luneau, Elise; Lhuillier, Johanna; Joannin, Sébastien (In: Dugerdil, L et al. (2025): Holocene multi-proxy analyses from Lake Fazilman, Uzbekistan: pollen, NPPs, GDGTs, XRF, magnetic susceptibility, climate and vegetation quantitative reconstructions [dataset bundled publication]. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.987394 (DOI registration in progress), 2025)
This data table contains all the output from the modelling approaches based on pollen assemblages retrieved from the Lake Fazilman, Nuratau range, Uzbekistan: (1) climate reconstructions based on an ensemble averaging of quantitative climate modelling using Boosted Regression Trees (BRT; Salonen et al., 2012), Modern Analogue Technique (MAT; Guiot et al., 1990) and Weighted Averaging Partial Least Squares (WAPLS; Ter Braak et al., 1993) from calibration dataset presented in Dugerdil et al. (2025b); Community Weighted Mean (CWM) trait values following the method developped in Dugerdil et al. (2025a); and biomization-scores following the method from Prentice et al. (1996). Pollen types were assigned to Plant Functional Types (PFTs) using classical pollen to PFTs assignation matrices (Peyron et al., 1998; Tarasov et al., 1998), which were then aggregated into biome scores. The events corresponds to the samples retrieved from the Lake Fazilman composit sediment core. The sample depth is given in centimeters and the age in year calibrated BP (age-depth model performed with BACON and the IntCal20 calibration curve based on 15 radiocarbon dating; Blaauw et al., 2011; Reimer et al., 2020). The climate parameters correspond to Mean Annual Air Temperature (MAAT, °C), Aridity Index (AI, no unit), Mean Average temperature of months above Freezing (MAF, °C) and the Mean Precipitation of the Colder Quarter (MPCOQ, mm.yr-1). The reconstructed plant traits are the plant height (average adult plant height in metre), the leaf area (mm2), the N_Leaf (N content per unit leaf mass, mg.g-1), the seed mass (diaspore mass in mg), specific leaf area (SLA, the ratio of leaf area to oven-dry mass, in mm2.mg-1) and the stem specific density (SSD in mg.mm-3). The biomes predicted from the biomization approach are Cold Deciduous Forest (CLDE), Cold Mixed Forest (CLMX), Cold Conifer Forest (COCO), Cold Desert (CODE), Cool Mixed Forest (COMX), Cold Steppe (COST), Hot Desert (HODE), Taiga forest (TAIG), Temperate Deciduous Forest (TEDE), Tundra (TUND), Warm Mixed Forest (WAMX), Warm Steppe (WAST) and Xerophytic Shrubland (XERO).
Keywords: Arid Central Asia; biomization scheme; climate reconstruction; GDGTs; Holocene; human impact; Magnetic susceptibility; plant functional traits; Pollen; Uzbekistan; XRF