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Halting the loss of grassland biodiversity and restoring degraded ecosystems are high priority tasks in the EU Biodiversity Strategy. Sowing low-diversity seed mixtures is widely used in grassland restoration because of its high predictability and fast, promising results. Generally, the sown perennial grasses establish within a few years and form a dense sward, which effectively suppresses weeds. Unfortunately, these grasslands are often species-poor because the sown grasses hamper the colonisation of target grassland forbs. Our aim was to test a novel approach to increase the diversity of species-poor grasslands. We selected eight 8-year-old grasslands restored by low-diversity seed sowing where we created 32 establishment gaps by breaking up the grass sward and sowing a high-diversity seed mixture (35 native species). Altogether, we established three grazed gaps (1m × 1m, 2m × 2m and 4m × 4m) and one fenced gap (4m × 4m) per site and monitored the presence and abundance of sown and non-sown species within a time frame of two years. We asked the following questions: (1) Which target species establish most successfully? (2) What is the effect of establishment gap size on the establishment success of target species and weeds? (3) What is the effect of management (grazed versus not managed) on the species composition of the establishment gaps? Our results showed that by creating establishment gaps and sowing diverse seed mixtures, we were able to overcome microsite and propagule limitation, successfully introducing target species into the species-poor grasslands. We found that all sown species established in the gaps, and the majority of the species maintained or even increased their first-year cover in the second year. Smaller gaps were characterised by lower cover of sown species and a quite stochastic development compared to the larger ones. Weed cover was moderate in the first year and decreased significantly in the second year, regardless of gap size. Therefore, in restoration practice, the use of larger establishment gaps is recommended. We found that the cover of sown species and weeds were similar in the grazed and unmanaged gaps during our study. However, management by extensive grazing might be crucial in the long-term because livestock can disperse target species propagules and create microsites. Our study shows that establishment gaps can serve as biodiversity hotspots. Further studies need to clarify to what extent they can improve the restoration success across the entire grassland.
Knowledge about the drivers of vegetation dynamics in grasslands is fundamental to select appropriate management for conservation purposes. In this study, we provide a detailed analysis of vegetation dynamics in alkali grasslands, a priority habitat of the Natura 2000 network. We studied vegetation dynamics in five stands of four alkali grassland types in the Hortobágy National Park (eastern Hungary), between 2009 and 2011. We analysed the effect of fluctuations in precipitation on both the overall vegetation composition and on the cover of each species using Self Organizing Map neural networks (SOM). We found that SOM is a promising tool to reveal plant community dynamics. As we analysed species cover and overall vegetation composition separately, we were able to identify the species re-sponsible for particular vegetation changes. Fluctuations in precipitation (a dry season, followed by a wet and an average season) caused quick shifts in plant species composition because of an increasing cover of halophyte forbs, probably because of salinisation. We observed a similar effect of stress from waterlogging in all studied grassland types. The species composition of Puccinellia grasslands was the most stable over the three years with varying precipitation. This was important as this grassland type contained many threatened halophyte species. Self-organising maps revealed small-scale vegetation changes and provided a detailed visualisation of short-term vegetation dynamics, thus we suggest that the application of this method is also promising to reveal community dynamics in more species-rich habitat types or landscapes.