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Prunus serotina is one of the worst invasive alien plants throughout Europe, able to rapidly replace autochthonous vegetation and form monospecific stands both in open lands and forested areas. Invasion by shrubs and trees due to abandonment of traditional management practices, is one of the major threats to the conservation of "European dry heaths", a priority habitat included in the Council Directive 92/43/EEC. The aim of this study was to assess the effects of P. serotina invasion on heathland vegetation in terms of species composition and cover, with special regards to the dominant Calluna vulgaris and Molinia arundinacea, in an area of North-Western Italy subjected to massive invasion by this alien species. We collected data on the plant cover along an invasion gradient in 10 linear transects running from P. serotina invaded stands towards non invaded ones. P. serotina differently affected the heathland vegetation. In particular, the cover of C. vulgaris and other typical heathland species such as Cytisus scoparius sharply decreased at P. serotina cover increasing. On the contrary, positive or no effect of P. serotina cover was found on M. arundinacea. Our results showed that shaded conditions created by the alien tree disfavored light demanding C. vulgaris and C. scoparius, enabling fast grower M. arundinacea to outcompete and replace them. This study emphasizes the urgency to develop management strategies to effectively control P. serotina spread in the area and to restore typical heathland species. [ABSTRACT FROM AUTHOR]

Established plants may disrupt patterns of seed deposition by physically trapping dispersing seed. In this study we quantified seed trapping at very fine spatial scales, by measuring seed fall of two ericaceous dwarf shrub species at a range of distances from allospecific shrubs within a matrix of short grass vegetation. Next to allospecific bushes, seed deposition densities of Calluna vulgaris and Erica cinerea were between 7- and 20-fold higher than those in the short grass. This increase is comparable to deposition densities next to conspecific bushes, caused by local dispersal, which were 19–33-fold greater than the background seed rain. Seed densities decayed rapidly with distance from the allospecific bush, so that in general the bush’s influence on deposition extended <0.1 m. By causing localised, extreme peaks in seed density around established plants, seed trapping could have large effects on the fitness of plants dispersing seed and on the spatial pattern of recruitment across plant communities. [Copyright &y& Elsevier]

The size and shape of the tail of the seed dispersal curve is important in determining the spatial dynamics of plants, but is difficult to quantify. We devised an experimental protocol to measure long-distance dispersal which involved measuring dispersal by wind from isolated individuals at a range of distances from the source, but maintaining a large and constant sampling intensity at each distance. Seeds were trapped up to 80 m from the plants, the furthest a dispersal curve for an individual plant has been measured for a non-tree species. Standard empirical negative exponential and inverse power models were fitted using likelihood methods. The latter always had a better fit than the former, but in most cases neither described the data well, and strongly under-estimated the tail of the dispersal curve. An alternative model formulation with two kernel components had a much better fit in most cases and described the tail data more accurately. Mechanistic models provide an alternative to direct measurement of dispersal. However, while a previous mechanistic model accurately predicted the modal dispersal distance, it always under-predicted the measured tail. Long-distance dispersal may be caused by rare extremes in horizontal wind speed or turbulence. Therefore, under-estimation of the tail by standard empirical models and mechanistic models may indicate a lack of flexibility to take account of such extremes. Future studies should examine carefully whether the widely used exponential and power models are, in fact, valid, and investigate alternative models. [ABSTRACT FROM AUTHOR]