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2010). The fields were mown twice a year but no further management was applied. Small patches of loess grasslands and, at lower elevations, alkali marshes, alkali wet meadows and alkali short grasslands were present in close proximity to most of the fields. In each field three 25-m2 sample blocks were chosen randomly. Within each block, the cover of vascular plants was recorded in four 1?m2 plots in early June, before the first mowing. In addition, within each block and near to the plots ( http://www.selleck.cn/products/BEZ235.html (i) a formerly heavy grazed Cynodonti-Po?tum stand, (ii) http://www.selleckchem.com/products/PLX-4032.html a species rich loess balk stand with Bromus inermis dominance, and (iii) a regularly mown species rich stand of Salvio nemorosae-Festucetum rupicolae grassland (for detailed species lists see Appendix S1 Supporting Information). We used the same sampling design as described above. Phytomass samples were dried (65?��C, 24?h), then sorted to litter, graminoids (Poaceae and Cyperaceae), lucerne and forbs. Dry weights were measured in a laboratory with an accuracy of 0��01?g. We classified the species into four functional groups using life-form (based on Raunkiaer��s life form system, Raunkiaer 1934) and morphological categories (grasses and forbs). These were perennial graminoids, perennial forbs, short-lived graminoids, and short-lived forbs. Annuals and biennials are short-lived, and geophytes, hemikryptophytes, and chamaephytes are perennials. The functional groups of the weed species were classified using Grime http://www.selleckchem.com/products/AZD2281(Olaparib).html C-S-R strategy types (Grime 1979) which was modified and adapted to local conditions by Borhidi (1995). The cover, species richness and phytomass data of the differently aged fields were compared using General Linear Mixed-Effect Models (GLMM) and Tukey test (Zuur et?al. 2009). Field age (time) was included as a fixed effect and field/block structure as a random effect. To analyse correlations between the different phytomass groups and sites we used DCA ordination, with square root transformed datasets. DCA was calculated by CANOCO 4.5 (ter Braak & ?milauer 2002). We used cover based Shannon diversity to characterise vegetation diversity, and S?rensen dissimilarity for vegetation changes. Characteristic species of differently aged lucerne fields and reference grasslands were identified by the IndVal procedure (Dufr��ne & Legendre 1997); during the calculations 10?000 random permutations were used. The IndVal procedure was executed by a revised version of the R code published as the electronic appendix of Bakker (2008).