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Institutionen för naturgeografi och kvartärgeologi The role of past and present management in the seed dispersal of grassland plants in the rural landscape Alistair G. Auffret Licentiatavhandling i naturgeografi 2010 Cover illustration: Richard Swan www.themoonunderground.com Abstract The destruction and fragmentation of semi-natural grasslands due to agricultural industrialisation during the past 150 years has had serious consequences for biodiversity in the rural landscape. Currently, plant communities are usually better explained by historical than by present day landscape configurations, and the ability for plant species to disperse in space and in time, within and between remaining habitat fragments or to restoration sites will be an important factor in the future diversity in the landscape. Here, I present a landscape scale seed bank and seed rain experiment covering semi-natural grasslands, pastures on former arable fields, abandoned grasslands and small remnant habitats. The results suggest that in addition to grassland specialists remaining in the field layer of abandoned grasslands, remnant seed banks have the potential to be important contributors to the future diversity of the rural landscape. However, unsuitable grazing intensities in current pastures are limiting the potential for dispersal of target species across the landscape. Despite large changes in agricultural practice, there still exists the opportunity for humanmediated seed dispersal to increase functional connectivity in fragmented landscapes, and I also present a review article in which I assess past and present human-mediated seed dispersal vectors, and give recommendations for management and further research. List of papers. I. Auffret, A. G., Cousins, S. A. O, Seed bank and seed rain as sources of future diversity in the rural landscape, Manuscript II. Auffret, A. G., Human mediated seed dispersal for conservation in the European rural landscape, Manuscript submitted to Applied Vegetation Science Introduction Habitat destruction and land use change are currently the most serious threat to terrestrial species worldwide (Sala et al. 2000; Baillie et al. 2004), and the associated fragmentation of remaining habitats results in the biological impoverishment of what is left (Harrison & Bruna 1999). The species-area relationship is a long known ecological theory which states that smaller areas of habitat support fewer species and vice versa (Arrhenius 1921), mediated by the effect of distance from a larger species source (MacArthur & Wilson 1967). After habitat loss, there often exists a time-lag before a reduction in the number of species, the 'extinction debt' (Tilman et al. 1994). The extinction debt is an example of how land use history can affect current and future ecological patterns, and indeed, site history is embedded in the structure and function of all ecosystems (Foster et al. 2003). In Europe, species-rich semi-natural grasslands have been created and maintained by the long history of grazing by wild animals and livestock (Vera 2000), but agricultural industrialisation in the nineteenth and twentieth century has resulted in the widespread and severe loss of semi-natural grassland habitat. Investigations comparing maps pre- and post-industrialisation have found that between around 70% up to almost 100% of grasslands have been either converted to arable land or abandoned to become deciduous woodland (Fuller 1987; Pärtel, Mandla & Zobel 1999; Cousins 2001; Luoto et al. 2003; Bender et al. 2005; Adriaens, Honnay & Hermy 2006). The high species richness of remaining fragments (Kull & Zobel 1991; Klimeš et al. 2001; Eriksson et al. 2006) has contributed to the extinction debt in European rural landscapes, where present-day biodiversity patterns are better explained by former land-use (Lindborg & Eriksson 2004; Helm, Hanski & Pärtel 2006; Gustavsson, Lennartsson & Emanuelsson 2007; Chýlová & Münzbergová 2008; Krauss et al. 2010). The existence of grassland plant populations in abandoned grasslands and small and linear habitats, such as mid-field islets, road verges and field boundaries (Smart et al. 2002; Cousins 2006; Johansson, Cousins & Eriksson 2010) adds further to the diversity of the rural landscape. The severity of the habitat loss, in addition to the high biodiversity value of remaining fragments highlights the importance of conserving and restoring semi-natural grasslands, at broad spatial scales incorporating present day, abandoned and converted grasslands habitats. The maintenance and re-creation of species-rich grasslands have both been key goals in agrienvironmental schemes in the EU, of which the effects for biodiversity are largely unknown (Kleijn & Sutherland 2003). In order for existing grassland populations to persist, and for the recolonisation of abandoned or former arable sites after restoration, it is essential that plant species can disperse to 1 these target areas. The dispersal failure associated with the loss of structural habitat connectivity resulting from the fragmentation of semi-natural grasslands has already contributed to species loss (Ozinga et al. 2009). Functional connectivity, when the movement of organisms through the landscape is facilitated by landscape structure and other factors (Taylor, Fahrig & With 2006), is increased when a dispersal vector can move seeds between fragmented plant communities. In addition to dispersal in space, plant species are also able to disperse in time, through the longevity of seeds in the soil, the combination of which is often seen as a trade-off (Venable & Brown 1988; Rees 1993; Thompson et al. 2002). A general lack of dispersal in space to target sites on former arable fields means that the formation of species-rich grassland communities is expected to take several decades (Gibson & Brown 1992; Smith et al. 2000). These sites are dispersal limited, and require seed sowing in order to enhance recruitment of desirable species (Pywell et al. 2002; Lindborg 2006; Kardol et al. 2008). Such investigations, however, take place on very small experimental scales, which may reduce the likelihood of spontaneous recolonisation, which has in fact been recorded on former arable fields (Ruprecht 2006; Cousins & Aggemyr 2008; Dahlström, Rydin & Borgegård 2010). Evidence of dispersal in time, of grassland species in the seed banks of abandoned grasslands has regularly been found (Falińska 1999; Mitlacher et al. 2002; Wagner, Poschlod & Setchfield 2003; Bisteau & Mahy 2005; Bossuyt & Honnay 2008). Restoration of grassland communities relying upon the seed bank is however generally thought to be unfeasable (Bossuyt & Honnay 2008). The re-creation of species-rich grassland from abandoned sites with only cutting and mowing management, and therefore relying heavily on the contribution of the seed bank, has had mixed results (Pärtel et al. 1998; Stampfli & Zeiter 1999; Klimeš, Jongepierová & Jongepier 2000; Hellström et al. 2006). Again, these investigations focus on small scale species richness for short periods, and further research into how remnant populations in seed banks can contribute to species richness after restoration is required. It is clear that dispersal in space is important for populations of grassland plants in the rural landscape today. Dispersal is still general poorly studied (Bullock et al. 2002), and measuring dispersal is difficult, especially between patches and at large spatial scales (Eriksson 1996; Nathan et al. 2003). It is this rare long-distance dispersal, however, which has a disproportionately large impact upon species distributions and dynamics (Nathan 2006; Ozinga et al. 2009), and it may often occur via non-standard means, i.e with a different dispersal vector to which the seed has evoloved to 2 disperse (Higgins, Nathan & Cain 2003). Humans have long influenced the dispersal of plant species through their actions (Hodkinson & Thompson 1997), and this human-mediated dispersal can be seeds dispersed directly by humans, as well as by human associated vectors, such as transport and livestock (Wichmann et al. 2009). In rural Europe, past agricultural practices have provided several dispersal vectors, such as the free roaming of livestock throughout the landscape and fertilising with manure (Poschlod & Bonn 1998). It is these vectors which have contributed to the seed dispersal for hundreds of years, and should also be considered in the modern context. Land use, history and dispersal are all important factors for the conservation and restoration of species-rich grassland communities in the landscape today, but all are relatively poorly studied. In this licentiate thesis I assess how seed dispersal in time and space is affected by past and present land use, and how this affects the grassland plant communities in the rural landscape. In Paper I, I present a a landscape scale seed bank and seed rain experiment in a rural area in southern Sweden, where I: [1] Determine whether or not seed bank and seed rain patterns can be distinguished at large spatial scales. [2] Assess whether seed bank and seed rain can be predicted by current surrounding vegetation, or if are they more similar to past or intended future plant communities. Paper II is the first review paper summarising the recent research into human-mediated seed dispersal in the Eurean rural landscape, assessing the potential of different vectors for the conservation and restoration management of species-rich grasslands. Methods Study area The empirical part of this thesis (Paper I) was carried out in a 36 km 2 agricultural landscape in the county of Södermanland in southern Sweden (58°54’N, 17°00’E, see Fig. 1). The region has a long history of anthropogenic influence, containing several runestones and burial sites dating from the Bronze Age, and has been managed for agriculture since at least the Iron Age. Like much of rural 3 Europe, the landscape consists of a mosaic of arable fields, semi-natural and old field pastures, managed and unmanaged woodland, small and linear habitats and settlements (Fig. 1). Sampling and analysis In Paper I, seed bank, seed rain and above-ground vegetation was investigated in ten replicates of four habitat types in the landscape described above: abandoned semi-natural grasslands, former arable fields, mid-field islets and semi-natural fields (Fig. 1, Table 1), covering a spectrum of habitat types and sizes in the rural landscape. Sites were chosen after examining historical maps and aerial photographs (1600s, 1901, 1950s, present day) of the area, consulting land managers, and visiting the landscape. In each site, thirty plots were created (total 1200). In each plot, seed bank samples were taken, and a seed trap was left in the field during the summer of 2008. Vegetation inventories were carried out during 2008 and 2009, identifying all plant species present in the 1 m 2 surrounding each plot, and by walking around the site to find additional species. Sites were unfenced, allowing the free movement of people and animals through them, resulting in the loss of some samples during the investigation. Abandoned grassland Semi-natural grassland Grazed former arable field Mid-field islet Figure 1. Aerial photograph showing part of the study landscape from Paper I, highlighting the different habitat types sampled. Photo: Sara Cousins, November 2008. After the collection of seed traps from the field, seed bank and seed rain samples were grown in an unheated greenhouse for seven months. Emerging seedlings were identified, counted and removed, and those not immediately identifiable were grown separately until identification was possible. 4 Table 1. Short descriptions of the habitat types investigated in Paper I. Abandoned semi-natural grassland (ABA) Deciduous forest/scrub, historically grazed or cut for hay, but subsequently abandoned and subject to secondary succession. Mid-field islet (MFI) Small, rocky habitats, formerly managed as part of larger pasture or meadow, but surrounded by crop fields during agricultural industrialisation. Former arable field (FAF) Relatively flat, ditched pastures, which have previously been cultivated and treated with chemical herbicides and fertilisers. Semi-natural grassland (SNG) Open species-rich grassland which has never been cultivated, and has been managed as pasture or meadow for much of the last 300 years or more. May have been briefly abandoned and subsequently re-cleared. In total, 1190 seed bank, 797 seed rain, and 1026 vegetation samples were analysed. All analyses were performed using R 2.11.0 (R Core Development Team 2009). Chao similarity (Chao et al. 2005), a method which accounts for differences in sample sizes caused by the loss of seed traps, was used as a basis for a permutation test comparing seed bank, seed rain and above-ground vegetation communities at the site level, as well as for assessing the similarity of the seed bank and seed rain with above-ground vegetation between habitat types. Characteristic species of seminatural grassland above-ground vegetation were determined using IndVal analysis (Dufrêne & Legendre 1997), modified by Roberts (2010). The predictive capacity for the above ground vegetation community to predict the species composition of the seed bank and seed rain was examined using co-correspondence analysis (CoCA- see ter Braak & Schaffers (2004); Simpson (2009) for a full description of the method). First, a predictive CoCA related the species compositions of the two communities (vegetation and bank, vegetation and rain), before leave-one-out cross-validation was used to determine the predictive accuracy of the model. Models were created at three scales (Fig. 2): [1] prediction of the plot level seed bank and rain communities by the presence/absence of plant species in the vegetation in the plot (plot vs plot), [2] prediction of plot level seed bank and seed rain by vegetation in the site (site vs plot), and [3] prediction of the site level seed bank and seed rain communities by the site vegetation (site vs site). Models were made at each scale for all habitat types, where data were available for both sources (bank, rain, vegetation) considered. In all cases, models were chosen with the number of axes corresponding to the highest prediction ability (% cross-validatory fit). Significance (p= 0.05) of pairwise differences between models was tested using a one sample permutation t-test of the mean prediction error sum of squares for each site 5 between all models within each source and scale, between sources at the same scale, and corresponding models between scales. [1] Plot Vegetation v Plot Bank/Rain Plot Plot Site [2] Site Vegetation v Plot Bank/Rain Plot Plot Plot Site [3] Site Vegetation v Site Bank/Rain Figure 2. Visualisation of the three scales used for the co-correpondence analysis in Paper I. In Paper II, a thorough literature search was conducted using the ISI Web of Science®, plus studies referenced within relevant search results, of seeds dispersed via human-mediated vectors under natural conditions (i.e. samples taken from vector without any seed addition) in Europe. Studies relevant to the subject of human-mediated dispersal in the rural landscape through time were also retrieved for discussion with regard to the conservation and restoration of semi-natural grasslands. Results and Discussion Paper I A total of 54 357 seedlings of 188 species were counted and identified from the seed bank and seed rain samples. The inventory of the vegetation found 277 species, with a total of 296 species identified in the whole investigation. Table 2 shows a summary of the results broken down by source and habitat. The permutation test revealed significant differences in community composition between habitats for the seed bank (F = 7.013, R2 = 0.369, P = 0.001), seed rain (F = 4.538, R2 = 0.286, P = 0.002) and above-ground vegetation (F = 14.749, R2 = 0.558, P = 0.001). This shows that through taking a number of samples in several replicate sites, broad patterns in the seed bank, seed rain and above6 ground vegetation at the landscape scale can be picked up. This allows the discussion of dispersal patterns at a larger spatial scale, and relate the habitats making up the mosaic of past, present and future species-rich grasslands. Table 2. Number of seeds, species and recovered samples from the seed bank and seed rain experiment, and the above ground vegetation inventory. ABA = Abandoned semi-natural grasslands, FAF = Former arable fields, MFI = Mid-field islets and SNG = Semi-natural grasslands. Seed bank Seed rain Vegetation Seedlings Species Samples Seedlings Species Samples Species ABA 7704 130 299 3461 91 242 133 FAF 13 336 116 299 2581 79 183 82 MFI 9937 139 296 2542 104 255 142 SNG 13 419 129 296 1396 74 116 151 Total 44 396 177 1190 9980 144 797 239 All but one (ABA seed rain, site vs site) of predictive CoCA cross-validations gave results higher than zero (Fig. 3), meaning that the predictive ability of the model was better than by chance. Predictive ability was, however, generally quite low, with at most 11.55% of the semi-natural grassland seed bank plots predicted by the plot vegetation. The site level vegetation was not able to predict the composition of the seed bank or seed rain better than the plot level vegetation, nor were the site level bank and rain communities ever as accurately predicted by the surrounding vegetation as were the plot level communities. The vegetation of the ABA, MFI and SNG habitats predicted the seed bank better than it did the seed rain, whereas the reverse was true for former arable fields, and the plot level seed rain communities were significantly better predicted by surrounding vegetation in FAF than in SNG habitats. Seed banks can be seen as the accumulation of several years of seed rain, and therefore it should be expected that the seed bank better represents the community feeding it. Jakobsson, Eriksson & Bruun (2006) found a strong positive relationship between abundance of reproductive ramets and abundance in the seed bank and seed rain, indicating that it is not the species present in the vegetation which are important, but those which are able to set seed. In the investigated landscape, the former arable field sites were characterised by a low grazing intensity, and communities were therefore able to complete their reproductive cycle and set seed, probably explaining the relatively high predictability of the seed rain by the above-ground vegetation in this habitat. 7 Figure 3. Prediction (% cross-validatory fit) of seed bank and seed rain communities by surrounding vegetation in four habitat types at three scales: [1] plot bank/rain by plot vegetation (plot vs plot), [2] plot bank/rain by site vegetation (site vs plot), and [3] site bank/rain by site vegetation (site vs site). Significance (p=0.05) of pairwise differences shown, where letters in common indicate no difference between habitats at the same source and same scale. Significant differences between source and within scale are denoted by an asterix. Models predicting communities at the plot scale were always significantly different to corresponding models predicting site communities, while corresponding models predicting at the plot vs Plot and site vs plot scales were never significantly different (not denoted). The plot level seed bank communities were significantly better predicted by surrounding vegetation in SNG than in ABA and MFI habitats. This is probably due to the continuous history of management, whereas the seed banks of the other habitat types appear out of synchrony with current vegetation, which has developed relatively recently due to abandonment. Given longer time without management, abandoned grasslands eventually become more similar to the above-ground vegetation, forming characteristic forest seed banks (Plue et al. 2010). Twenty-two characteristic (specialist) semi-natural grassland species were identified by the IndVal analysis. Table 3 shows that many of these species are present in the bank, rain and vegetation of the other habitats. Ajuga pyramidalis, Alchemilla spp., Erophila verna, Lotus corniculatus and Primula veris remained in the seed banks of the former grassland, despite having disappeared completely from the above-ground vegetation. The Chao similarity analysis indicated that the seed bank and rain communities of most habitats were most similar to the above-ground vegetation of the same habitat (Fig. 4), with the exception that seed banks of the MFI and ABA habitats were more similar to the SNG above-ground vegetation, and the SNG seed rain were most similar to the 8 vegetation of the FAF sites. These results support the conclusion drawn from the CoCA analysis, that semi-natural grasslands subjected to abandonment are out of synchrony with the above vegetation, as the ABA and MFI sites contained populations of grassland specialists in their seed banks, and the whole seed bank communities were more similar to the above-ground vegetation in existing grasslands than to their own. Furthermore, the presence of specialists in the vegetation and seed rain indicates reproducing populations and/or dispersal from nearby populations. The results imply that in addition to grassland specialists remaining in the vegetative layer, remnant seed banks have the potential to be important contributors to the future diversity of the rural landscape. 0.17 0.29 0.24 0.25 Seed Rain ABA FAF MFI SNG Vegetation ABA FAF MFI SNG Seed Bank ABA FAF MFI SNG 0.29 0.37 0.28 0.39 Figure 4. Similarity of seed bank and seed rain communities to the habitat type vegetation to which they are most similar. Arrows connect seed bank and seed rain communities to the vegetation community to which they are most similar. Values are Chao similarity (0-1) between the connected habitat types. where ABA = Abandoned semi-natural grasslands, FAF = Former arable fields, MFI = Mid-field islets and SNG = Semi-natural grasslands. The poor predictive power of the CoCA models for the SNG seed rain, and the correspondence between the SNG seed rain and the FAF vegetation (Figs. 3 and 4) suggests that in contrast to former arable fields, few species in semi-natural grasslands are currently setting seed, and those that are are probably common throughout the landscape. Semi-natural grasslands in the study landscape are heavily grazed, and a high grazing intensity can could be limiting the number of propagules to contribute to the existing population, create a seed bank, or to disperse to other areas in the seed rain. 9 Table 3. Number of sites for each habitat where local grassland specialists were found in the seed bank, seed rain and above-ground vegetation. ABA = Abandoned semi-natural grasslands, FAF = Former arable fields, MFI = Mid-field islets and SNG = Semi-natural grasslands. Species IndVal ABA Bank n=10 Rain n=10 Veg n=9 FAF MFI SNG Bank Rain Veg n=10 n=10 n=10 Bank Rain Veg n=10 n=10 n=10 Bank Rain Veg n=10 n=8 n=10 Plantago lanceolata 0.8000 0 0 0 0 0 0 0 0 0 5 1 8 Lotus corniculatus 0.7800 4 4 0 1 0 1 2 0 0 3 0 8 Filipendula vulgaris 0.6440 0 0 3 0 1 1 0 0 1 0 0 8 Campanula rotundifolia 0.6344 7 7 8 0 1 1 8 4 5 7 2 9 Pimpinella saxifraga 0.6009 0 0 4 0 0 2 0 1 6 1 1 10 Trifolium arvense 0.5455 0 0 0 1 1 0 0 0 1 6 0 6 Rumex acetosa 0.5020 2 2 6 3 2 6 2 1 5 4 2 9 Viola canina 0.4777 6 6 2 0 0 0 3 1 1 4 0 6 Veronica chamaedrys 0.4600 9 9 9 8 3 8 8 6 5 10 5 10 Trifolium pratense 0.4410 3 3 1 5 4 7 3 0 5 9 1 9 Anthoxanthum odoratum 0.4361 2 2 3 0 1 1 2 1 2 5 0 8 Alchemilla spp 0.4286 2 2 0 4 1 2 3 0 0 2 0 5 Ranunculus auricomus/bulbosus 0.4233 1 1 4 4 0 5 1 0 3 2 0 8 Arabidopsis thaliana 0.4000 4 4 0 6 0 0 7 0 0 6 3 4 Scleranthus annuus 0.4000 0 0 0 0 0 0 0 0 0 1 1 4 Festuca ovina 0.3862 3 3 4 1 1 1 5 2 4 8 2 6 Carex spicata 0.3667 0 0 0 0 0 1 0 0 0 0 0 4 Primula veris 0.3429 1 1 0 0 0 1 1 0 0 1 1 4 Potentilla argentea 0.3415 6 6 1 7 3 0 10 4 3 10 2 4 Veronica officinalis 0.3390 10 10 2 1 0 2 6 0 2 8 3 6 Ajuga pyramidalis 0.3000 4 4 0 0 0 0 2 0 0 4 1 3 Erophila verna 0.3000 Total species per site/source 1 1 0 2 0 0 3 1 0 9 1 3 16 16 12 12 10 14 16 9 13 20 14 22 Paper II The literature search yielded 23 articles investigating seed dispersal via human mediated vectors (Table 4). Grazing animals Most of the articles found (16) are concerned with seed dispersal via grazing animals, both epi (outside)- and endozoochorously (inside the animal), and show the large amount of seeds and species which can be dispersed in this manner. It is not only seeds with appendages designed for attachment which can be dispersed epizoochorously, as unappendaged, small and smooth seeds can all attach to the fur of different grazing animals (Fischer, Poschlod & Beinlich 1996; Couvreur et al. 2004; Römermann, Tackenberg & Poschlod 2005; de Pablos & Peco 2007). 10 Table 4. Human-mediated seed transport in natural conditions in the European rural landscape. Methods vary widely between studies. Reference Country Vector Number of replicates* Epizoochory Endozoochory Couvreur et al. 2004 Belgium Couvreur et al. 2005 Fischer, Poschlod & Beinlich 1996 Wessels et al. 2008 Belgium Germany Germany Bakker & Olff 2003 Bruun and Poschlod 2006 Cosyns et al. 2005 Cosyns et al. 2006 Netherlands Germany Belgium Belgium Cosyns & Hoffmann 2005 Couvreur et al. 2005 Dai 2000 Eichberg, Storm & Schwabe 2007 Kuiters & Huiskes 2010 Malo & Suárez 1995 Pakeman, Digneffe & Small 2002 France/Belgium Belgium Sweden Germany Belgium/Netherlands Spain Spain Sweden Netherlands Netherlands Netherlands Netherlands Netherlands UK Hodkinson and Thompson 1997 Mayer 2000 UK Germany Schmidt 1989 Strykstra, Verweij & Bakker 1997 Zwaenepoel, Roovers & Hermy 2006 Germany Mitlacher et al. 2002 Mouissie et al. 2005 11 Motor Vehicles Humans Belgium Total seeds* Cattle Donkey Horse Donkey Sheep Sheep 125 46 30 41 16 41-63 3692 2483 210 NA 8511 9420 Number of identified species* 63 33 20 29 85 56 Cattle Cattle Cattle and Horse Cattle Horse Horse Donkey Cattle Sheep Sheep Cattle (Spring) Cattle (Winter) Cattle and Sheep Cattle Cattle Cattle Horse Sheep Sheep 30 48 51 12 12 56 14 30 32 24 8 8 29 50 10 15 10 10 12 6124 14703 59049 18974 10808 53493 NA 393 2669 11130 1373 17 1504 1161 (kg-1) 4605 (kg-1) 1095 (kg-1) 661(kg-1) 527 (kg-1) 359 (kg-1) 35 56 117 50 49 106 53 26 28 72 46 5 44 51 34 39 35 31 21 Car Tractor† Plough† Heavy cultivator† Rotary tiller† Rotary harrow† Curry comb† Car Mowing machinery Car 201 1 1 1 1 1 1 4 7 240 367 6 1945 844 320 658 460 3926 NA 690 37 4 35 28 30 25 11 124 27 33 Clifford 1956 Ireland Boots Unknown (22.1g) 65 11 Wooderuffe-Peacock 1918 UK Clothes 3 NA 19 * As far as can be deduced from the text. This includes both replication and pseudoreplication, i.e. 75 could mean either 75 individuals, or one individual sampled 75 times. Epizoochorous units are animals, endozoochorous are “samples”. † In this study, machinery was driven through mud of varying soil dry matter, but species lists are not given. Displayed here are the individual runs that yielded the most seeds and species. Endozoochory also has the potential to disperse seeds with a range of other dispersal adaptations (Couvreur et al. 2005; Bruun & Poschlod 2006). Large grazers have a remarkable capacity for endzoochorous seed dispersal, with approximately 1 200 000 seeds per individual per summer calculated for both cattle and horses in a coastal dune landscape in Belgium (Cosyns et al. 2005), up to 2 600 000 seeds per year for cattle in the Netherlands (Mouissie et al. 2005), and an estimated 1510 seeds per square metre per year deposited by grazing cattle in a Mediterranean wooded pasture (Malo, Jiménez & Suarez 2000). Both epi- and endozoochory are important for the diversity of the rural landscape, and are known to disperse specialist and red-listed species (Fischer, Poschlod & Beinlich 1996; Eichberg, Storm & Schwabe 2007; Wessels et al. 2008). The two vectors have been found to complement one another with regards to species dispersed (Couvreur et al. 2005), and the contents of Table 4 indicate a complementarity between different grazing animals, with the larger mammals transporting a large number of seeds internally, and sheep transporting far more on their coats than other animals. Investigations have shown that each studied herbivore species transport the diaspores of plant species not transported by any other herbivore study species (Couvreur et al. 2004; Cosyns et al. 2005). Despite the obvious potential of zoochorous seed dispersal in the rural landscape, very little is now realised. Where mixed grazing animals were once allowed to roam almost freely throughout the landscape (Clout 1998; Dahlström 2006), this is now a less common practice, and single species are often kept in the same small pastures for the whole grazing season. Even longer distance dispersal was possible via transhumance, which is the seasonal movement of livestock between pastures. This practice was widespread for centuries (Whyte 1998), facilitating the movement of seeds between landscapes and even countries, but has been progressively abandoned as a result of economic development (Manzano & Malo 2006). Experimentally attached seedlings were found to travel hundreds of kilometres in two of Europe's last remaining transhumance drives (Fischer, Poschlod & Beinlich 1996; Manzano & Malo 2006). In today's landscape, long distance dispersal via grazing animals can occur via management practices such as the movement of transportation of grazing animals between isolated nature reserves (Couvreur et al. 2004; Wessels et al. 2008), or by the recreation of extensive forest-pasture mosaics (Kumm 2004). 12 Motor Vehicles Whereas movement of grazing animals within and between landscapes has reduced through time, the invention of motor vehicles and agricultural machinery has introduced a new potential for seed dispersal in the rural landscape (see Table 4). Not surprisingly other published motor vehicle dispersal studies state that most species transported are typical of local roadsides and ruderal land (Clifford 1959; Wace 1977; Schmidt 1989; Hodkinson & Thompson 1997; Schmidt et al. 2004; Zwaenepoel, Roovers & Hermy 2006; Von der Lippe & Kowarik 2007) and regularly managed road verges can act as remnant habitats for grassland specialists (Milberg & Persson 1994; Cousins 2006). No plant species have evolved to be dispersed via motor vehicles, but Zwaenepoel, Roovers & Hermy (2006) found a significantly higher proportion of seeds with persistent seed banks were dispersed this way. Furthermore, the seed banks of verges can be important repositories for grassland species (Milberg & Persson 1994; Berge & Hestmark 1997), and therefore motor vehcles could be an important, non-standard long distance dispersal vector of the grassland plant species which are traditionally dispersed through time. Mowing machinery operating in species-rich meadows has also been found to be an effective dispersal agent, where small subsamples of material collected post-mowing contained 27 of 52 species found in the meadow system (Strykstra, Verweij & Bakker 1997). Larger agricultural machinery has been shown to transport seeds between arable fields (Mayer 2000), but this has not been studied in semi-natural grasslands. These vehicles are used on pastures, and in addition to the potential seeds dispersed, the physical disturbance can promote the generation of new seedlings, an effect documented on grassland with other heavy vehicles (Hirst et al. 2003). Road verges should have the same mowing regimes as ancient meadows. This would maintain species richness and allow plants to reach the reproductive stage (Jantunen et al. 2007), in turn allowing the effectiveness of motor vehicles to disperse grassland species to aid in grassland connectivity. Humans Humans themselves can also be non-standard, long-distance dispersers of seeds through the landscape . Recently, two species of Brassica were regularly found to remain attached to the mud on boots after 5 km walking, which was almost fifty times further than the maximum value calculated for wind dispersal, which is their primary vector (Wichmann et al. 2009). A study from Australia (Mount & Pickering 2009) has shown the capacity for clothing to disperse seeds of both native and 13 alien plants, where 207 clothing samples yielded almost 25 000 seeds of 70 taxa. The paper also contains a useful summary of the few published clothing dispersal studies, which is dominated by work from the Southern Hemisphere focussing on alien species (Healy 1943; Whinam, Chilcott & Bergstrom 2005). There is a clear absence of recent work from Europe quantifying the number of seeds and species dispersed with humans, which is limited to Clifford (1956), where material attached to shoes were found to contain seeds of 44 species representing a range of dispersal adaptations, and Woodruffe-Peacock (1918), who identified mud from boots, as well as clothing and hair as the sources of seeds for a number of species colonising a newly created fox covert. Figure 5. Human-mediated seed dispersal vectors in the modern rural landscape. Mechanisation of agriculture has meant there are fewer humans working in the landscape, but the potential for dispersal by recreational walkers (and ecologists) remains. Many people walking through the modern landscape are accompanied by dogs, and these can also be effective dispersers of seeds (Heinken 2000; Graae 2002). Seeds transported on humans and their pets will also travel in cars and other modes of transport, increasing dispersal distances further. The studies summarised in Table 4 show that human-mediated dispersal can be important in terms of both number of seeds and species. It is clear, however, that modern land-use change and agricultural intensification has negatively affected this potential. In order to preserve, conserve and restore high species richness in semi-natural grassland landscapes, it is therefore important to draw inspiration from past land use and its dispersal vectors, to increase functional connectivity where structural connectivity has been lost. It is equally important is not to overlook the potential of those dispersal vectors that modern life and agriculture has introduced. A great deal of research into 14 human-mediated seed dispersal has been done during the past decade, but there is still more to be done, and in the case of semi-natural grasslands, it is vital that both agricultural history and the landscape scale are considered. Conclusions and future directions Paper I shows how past land use has left an imprint on the dispersal of grassland plant species in time and space. The seed banks of abandoned semi-natural grasslands and mid-field islets can give an important contribution to the future biodiversity of the rural landscape. The high degree of fragmentation, as well as the intense grazing on existing species-rich grasslands, however, appears to be limiting the dispersal through space within and between semi-natural grassland fragments. It is clear from Paper II that agricultural change in the twentieth century has not only negatively affected diversity in the rural landscape, but also the potential dispersal of plants across it. There is, however, a potential for successful dispersal of grassland plants, both by drawing inspiration from past practices, as well as by facilitating dispersal by more non-standard means in the modern landscape (Fig. 5). Such dispersal vectors certainly warrant further research, and during the rest of my PhD studies, I will investigate endozoochorous seed dispersal in both an island nature reserve in the Stockholm archipelago, as well as in the study landscape from Paper I, where I will also evaluate dispersal via motor vehicles. I also plan to publish the first investigation into seed dispersal via humans in the northern hemisphere for several decades. The results of these empirical studies will be used to model dispersal in time and space in fragmented landscape, and provide recommendations for management Acknowledgements First I will thank my supervisor Sara Cousins for the opportunity to start this exciting research project, and for being just the kind of supervisor I need. Thanks also to my other supervisors Ove Eriksson and Johan Berg for attending meetings, reading manuscripts and answering emails extremely promptly. The various members of the Landscape Ecology group at INK have all helped me in their various ways, and along with the PhD student group, the academic and non-academic staff, they have made the department a very nice place to work. The seed bank and seed rain project would have been a total disaster were it not for the sterling efforts in dreadful conditions of Nils Hedberg, Ewa Hedberg, Hedvig Nenzen, Alexander Norberg and Isabell Wärmé. 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