TY - JOUR A1 - Cao, Xianyong A1 - Herzschuh, Ulrike A1 - Telford, Richard J. A1 - Ni, Jian T1 - A modern pollen-climate dataset from China and Mongolia: assessing its potential for climate reconstruction JF - Review of palaeobotany and palynology : an international journal N2 - A modern pollen dataset from China and Mongolia (18-52 degrees N, 74-132 degrees E) is investigated for its potential use in climate reconstructions. The dataset includes 2559 samples, 229 terrestrial pollen taxa and four climatic variables - mean annual precipitation (P-ann): 35-2091 mm, mean annual temperature (T-ann): -12.1-25.8 degrees C, mean temperature in the coldest month (Mt(co).): -33.8-21.7 degrees C, and mean temperature in the warmest month (Mt(wa)): 03-29.8 degrees C. Modern pollen-climate relationships are assessed using canonical correspondence analysis (CCA), Huisman-Olff-Fresco (HOF) models, the modern analogue technique (MAT), and weighted averaging partial least squares (WA-PLS). Results indicate that P-ann is the most important climatic determinant of pollen distribution and the most promising climate variable for reconstructions, as assessed by the coefficient of determination between observed and predicted environmental values (r(2)) and root mean square error of prediction (RMSEP). Mt(co) and Mt(wa) may be reconstructed too, but with caution. Samples from different depositional environments influence the performance of cross-validation differently, with samples from lake sediment-surfaces and moss polsters having the best fit with the lowest RMSEP. The better model performances of MAT are most probably caused by spatial autocorrelation. Accordingly, the WA-PLS models of this dataset are deemed most suitable for reconstructing past climate quantitatively because of their more reliable predictive power. (C) 2014 Elsevier B.V. All rights reserved. KW - Calibration KW - Huisman-Olff-Fresco models KW - MAT KW - Pollen-climate transfer function KW - Spatial autocorrelation KW - WA-PLS Y1 - 2014 U6 - https://doi.org/10.1016/j.revpalbo.2014.08.007 SN - 0034-6667 SN - 1879-0615 VL - 211 SP - 87 EP - 96 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Kloss, Lena A1 - Fischer, Markus A1 - Durka, Walter T1 - Land-use effects on genetic structure of a common grassland herb a matter of scale JF - Basic and applied ecology : Journal of the Gesellschaft für Ökologie N2 - The most common management practices in European grasslands are grazing by livestock and mowing for silage and hay. Grazing and mowing differ in their potential effects on plant gene flow and resulting population genetic structure. After assessing its breeding system, we investigated the effect of land use on the population genetic structure in the common grassland plant Veronica chamaedrys using 63 study populations on meadows, mown pastures and pastures in three regions in Germany, the so-called Biodiversity Exploratories. We determined plant density and analysed the genetic diversity, differentiation and small-scale genetic structure using amplified fragment length polymorphism (AFLP) markers. The breeding system of V chamaedrys turned out as self-incompatible and outcrossing. Its genetic diversity did not differ among land-use types. This may be attributed to large population sizes and the strong dispersal ability of the species, which maintains genetically diverse populations not prone to genetic drift. Genetic differentiation among populations was low (overall F(ST) = 0.075) but significant among the three regions. Land use had only weak effects on population differentiation in only one region. However, land use affected small-scale genetic structure suggesting that gene flow within plots was more restricted on meadows than on mown and unmown pastures. Our study shows that land use influences genetic structure mainly at the small scale within populations, despite high gene flow. KW - Biodiversity exploratories KW - Mowing KW - Grazing KW - AFLP KW - Veronica KW - Breeding system KW - Pollination experiment KW - Pollen-ovule ratio KW - Isolation by distance KW - Spatial autocorrelation Y1 - 2011 U6 - https://doi.org/10.1016/j.baae.2011.06.001 SN - 1439-1791 VL - 12 IS - 5 SP - 440 EP - 448 PB - Elsevier CY - Jena ER -