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Keywords:

  • disturbance;
  • forest restoration;
  • functional diversity;
  • Prunus serotina;
  • Robinia pseudoacacia;
  • tree invasion

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. LITERATURE CITED
  9. Supporting Information

Soil seed banks are the ecological memory of plant communities and might represent their regeneration potential. This study examines the soil seed bank in hardwood floodplain forests of the biosphere reserve “Valle del Ticino” (Northern Italy) to find out whether the natural forest vegetation can potentially be restored by the soil seed bank. We compared near natural forests of the phytosociological association Polygonato multiflori–Quercetum roboris with stands dominated by the nonnative tree species Robinia pseudoacacia and Prunus serotina in order to investigate whether the composition of the soil seed bank is significantly influenced by the composition of the main canopy tree species and soil properties. Soil seed bank samples were taken from 20 randomly selected plots in stands that were differentiated into four groups related to the dominant forest canopy species. The germinated plants were counted and their species determined. A total of 2,427 plants belonging to 84 species were recorded. The composition of the dominant tree species and soil parameters significantly influence the composition of the seed bank. The similarity with the standing vegetation was very low. Only 13% of the species in the soil seed bank represent the target vegetation. The low percentage of target species and the high percentage of nonnative species imply that the regeneration of near-natural forest vegetation from the soil seed bank is not feasible. Consequently, disturbances that may activate the soil seed bank should be minimized. Thus, we recommend stopping the mechanical removal of the nonnative tree species in the Ticino Park.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. LITERATURE CITED
  9. Supporting Information

Soil seed banks provide information on the former composition of the standing vegetation, and thus about the regeneration potential (Hille Ris Lambers et al. 2005). They have an impact on vegetation structure and dynamics and can be of vital importance to the regeneration of plant communities after disturbances or for the colonization of new areas (Bakker et al. 1996; Thompson 2000). Whether soil seed banks play an important role for regeneration depends on the longevity of the seeds. Only persistent seeds that remain in the soil for more than 5 years are able to respond to any disturbance over time, but information about the longevity is not available for all species (Thompson et al. 1998; Zerbe & Wiegleb 2009).

Soil seed banks of temperate deciduous forests are the ecological memory, reflecting the land use of the last 150 years (Plue et al. 2010). In forest ecosystems, the similarity between soil seed bank and standing vegetation is much higher compared to wetlands or grasslands, and decreases with time since the last disturbance (Hopfensperger 2007; Bossuyt & Honnay 2008). After a disturbance, pioneer, edge, and invasive species produce persistent seeds, which remain in the soil but cannot establish later on, as they are mostly shade-intolerant species that cannot germinate under the cover of a closed forest canopy. Late succession species often produce transient seed banks or reproduce vegetatively (Deiller et al. 2003). For this reason, soil seed banks of forest ecosystems often lack target species, and their regeneration depends more on dispersal than on the soil seed bank (Hopfensperger 2007; Bossuyt & Honnay 2008). Whether the soil seed bank contributes to the regeneration process depends on the competitive ability of the target species and the presence of nontarget species in the seed bank, which can inhibit the establishment of the target species. According to Kratochwil and Schwabe (2001), target species are considered to be those species which are of high relevance for management and nature conservation objectives. While numerous studies deal with the negative impacts of nonnative species on the standing vegetation (e.g. Nentwig 2006; Zerbe & Wirth 2006; Kowarik 2010), the impact on the soil seed bank has received less attention. Nevertheless, evidence showing that invasive species significantly influence the soil seed bank has been published recently (Vilà & Gimeno, 2007; Giantomasi et al. 2008; Gioria & Osborne 2009). Invasive species can form transient or persistent seed banks and, accordingly, have an enduring influence on the composition of the standing vegetation with all the associated consequences for ecosystem functioning, resistance, and resilience. Those changes may decrease biodiversity and further threaten endangered species and plant communities. Additionally, soil seed banks can serve as a reservoir for the future spread of invasive species (Gioria & Osborne 2009). In invaded areas, soil seed banks are often dominated by very few species (Bossuyt & Honnay 2008). Therefore, there are serious doubts about the contribution of soil seed banks to the regeneration process. However, persistent seeds of typical native, and thus target species may remain in the soil seed bank during the invasion and contribute to the regeneration in areas cleared of the nonnative species. In systems with a high percentage of invasive species, seed bank studies may show which species are likely to play a key role in the regeneration process after the successful control of invasive species. Seed banks can have a positive effect on regeneration if they contain a high percentage of native species, but are considered to have a negative effect if they are dominated by nontarget species.

The objective of this study was to examine the influence of two nonnative tree species, Robinia pseudoacacia L. (Black locust, Fabaceae) and Prunus serotina Ehrh. (Black cherry, Rosaceae), on the soil seed bank in a biosphere reserve in Northern Italy. Both species originated from North America and were deliberately introduced to Europe (Starfinger et al. 2003; Kowarik 2010). Soil seed bank samples were collected from forest stands with differing canopy proportions of the two nonnative tree species, and the native target tree species Carpinus betulus L. (European hornbeam, Betulaceae) and Quercus robur L. (Pedunculate oak, Fagaceae), and were analyzed for variation in composition and functional diversity. In addition, the relationship between soil seed bank parameters and soil properties was examined. As soil parameters, the C/N ratio and pH were investigated, because nutrient availability is important for the establishment of individuals, and pH value was expected to be relevant for the germination capacity (Erenler et al. 2010). Furthermore, the soil seed bank composition was compared to the standing vegetation and to the target species in order to draw conclusions concerning the regeneration potential. Consequently, this study examined whether:

  1. The composition of the soil seed bank is correlated to the composition of the dominant canopy tree species and soil properties.
  2. The soil seed bank can contribute to the restoration of near-natural floodplain forests in the biosphere reserve Valle del Ticino.

Based on these results, management recommendations are presented for Robinia pseudoacacia and Prunus serotina stands in the nature conservation area Valle del Ticino in Northern Italy.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. LITERATURE CITED
  9. Supporting Information

Study Area

The study area was the biosphere reserve “Valle del Ticino,” west of the city Milan in Northern Italy (Fig. 1). Situated on the border between the regions Lombardy and Piedmont, the reserve stretches along the Ticino river, and ranges from the Lago Maggiore in the northwest (5069455 N, 1468221 E; WGS 84) to where it joins the Po River in the southeast (4994813 N, 1522708 E; WGS 84). The reserve has a north–south extension of 110 km and an east–west extension of 5–15 km. The total area of the reserve is about 97,971 ha (Furlanetto et al. 2008). It represents the largest continuous woodland area of the Po plain and is an important ecological corridor connecting the Alps and the Apennine mountains. The main natural floodplain forest association is the Polygonato multiflori–Quercetum roboris association (Sartori 1984), which occurs mainly on sandy–clayey substrate. The climate is mild continental in the north to humid subtropical in the south. The mean annual precipitation for the city of Pavía, situated in the south of the biosphere reserve, is about 820 mm, while for Malpensa in the north of the park, it is about 1,212 mm. The mean annual temperature of 12.6°C for Pavía is slightly higher than 11.4°C for Malpensa.

image

Figure 1. Location of the study area in northern Italy and sample sites (differentiated for the four groups, 1 = Nonnative_Rob, 2 = Nonnative_RobPrun, 3 = Native_Quer, 4 = Native_QuerCarp) in the biosphere reserve Parco del Ticino, composed by regional and nature park.

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Throughout its land-use history, the area of the biosphere reserve has been influenced by various human activities, such as agriculture, forestry, and the use of firewood. Today, more than 50% of the area is used for agriculture, about 20% is urban area, and only about 20% is woodland. Nonnative tree species such as Robinia pseudoacacia, Prunus serotina, and Quercus rubra (Red oak) account for 37.4% of the woodland area. Robinia pseudoacacia was first introduced to the park area at the end of the 19th century (Motta et al. 2009). Prunus serotina, also native to North America, was first detected in northern Italy in 1922 close to Milan (Sartori 1988).

Sampling and Greenhouse Experiment

In February 2011, soil seed bank samples were taken from 20 plots in the hardwood floodplain forest. On the basis of the forest association maps created by Boschetti et al. (2007) the Ticino forest types were identified, differentiated, and assigned to four groups according to the dominant tree species. The plots were then randomly placed within the areas that were representative for these four forest groups. The distance between the plots ranged from about 0.5–10 km (see Fig. 1). While the first and second forest groups were dominated by the two nonnative tree species R. pseudoacacia and P. serotina, they were not present in the tree layers of the third and fourth group. Thus, the four groups were dominated by: group 1: Q. robur, R. pseudoacacia, and C. betulus (consecutively called “Nonnative_Rob”); group 2: Q. robur, R. pseudoacacia, C. betulus, and P. serotina (Nonnative_RobPrun); group 3: Q. robur (Native_Quer); and group 4: Q. robur and C. betulus (Native_QuerCarp). The nomenclature of the plant species followed Fischer et al. (2008). The plots had a size of 20 × 20 m. All plots were subdivided into four subplots of 5 × 5 m. In the center of each subplot, one soil seed bank sample was taken with a soil corer which had a diameter of 8 cm and a length of 23 cm. In the greenhouse, the soil seed bank samples were sieved with a mesh size of 1.5 × 1.5 cm to remove stones, roots, and rhizomes. Sterile plant trays (30 × 50 cm) containing the soil seed bank samples were positioned randomly in the greenhouse and irrigated daily. As a control treatment, four trays of sterilized potting mix were randomly positioned between the other trays to quantify any externally introduced seeds for the duration of the experiment. For a period of five months, from March to July 2011, the germinated plants were counted weekly and identified as soon as possible. The average monthly temperature was between 21°C in March and 26°C in July.

Vegetation surveys were conducted on the total area of each plot during the time from June to August 2010 using the Braun-Blanquet methodology (1964).

Soil Analysis

The soil samples were collected in summer 2010 (June–August) during the vegetation survey. Two soil samples were taken on every plot from the middle of the two opposite boundary lines of the plot. After drying the samples at 170°C and sieving them to 1 mm, the soil was analyzed with regard to pH value (in CaCl2), total carbon (C) and total nitrogen (N) content, for a depth of 5 cm. Total C and total N were analyzed by quantitative elemental analysis in the soil laboratory of the Free University of Bozen-Bolzano.

Data Analysis

Number of species, number of seedlings, Shannon index, and dominance index were derived and calculated for each plot. The differences between the soil seed banks of the four groups regarding those parameters were examined using a univariate one-way PERMANOVA (Anderson 2005). A multivariate one-way PERMANOVA was used to test for differences in the composition of the soil seed bank of the four groups. A SIMPER analysis (Clarke 1993) was performed to examine which species contribute most to the dissimilarity between the four groups. The statistical program PAST 2.0 (Hammer et al. 2001) was used to perform both tests.

In order to analyze the functional diversity, the percentage of life forms according to Raunkiær (Pignatti 1997) and the percentage of strategy types according to Grime (Klotz et al. 2002) were examined. Additionally, the percentage of nonnative species following Celesti-Grapow et al. (2009) was investigated.

The Bray–Curtis similarity coefficient and the Sørensen similarity coefficient were calculated to compare the soil seed bank to the standing vegetation. A cluster analysis was then performed with each coefficient, also using PAST 2.0. Spearman correlation analysis was used to relate the soil parameters (pH value, C and N content, and C/N ratio) to soil seed bank parameters (species number and seed density), using SPSS 18.0.0.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. LITERATURE CITED
  9. Supporting Information

Soil Seed Bank Composition

The PERMANOVA test showed significant differences between the soil seed bank composition of the four groups.

While the fern Athyrium filix-femina dominated in group Nonnative_Rob and group Native_QuerCarp, Equisetum arvense and Centaurium erythraea were found most frequently in group Nonnative_RobPrun. In group Native_Quer, Juncus effusus was the most abundant species. The SIMPER analysis showed that these four species alone contribute to the dissimilarity with more than 50% (Table 1).

Table 1. Contribution of the most important species present in the soil seed bank to the dissimilarity between the groups as result of the SIMPER-analysis
Species Name (According to Fischer et al. 2008)Dissimilarity Contribution in %Cumulative Contribution in %Average Abundance
Group Nonnative_RobGroup Nonnative_Rob PrunGroup Native_QuerGroup Native_Quer Carp
  1. a

    Indicating nonnative species.

Athyrium filix-femina20.6826.9374.8015.207.0067.50
Juncus effusus6.7135.684.671.2035.601.00
Equisetum arvense6.1243.6617.508.006.4010.00
Centaurium erythraea5.6851.0512.5012.204.206.00
Stellaria nemorum3.6055.7310.800.400.604.75
Juncus articulatus3.2960.028.171.206.603.75
Cyperus michelianus2.5863.395.170.207.800.00
Lindernia procumbens2.4266.554.830.006.400.50
Hypericum perforatum1.6568.701.173.401.600.25
Pteridium aquilinum1.4370.565.171.601.200.75
Lythrum salicaria1.3972.361.670.605.000.00
Rubus caesius1.2173.942.832.001.600.75
Juncus tenuisa1.2075.514.830.001.600.25
Carex umbrosa1.0776.901.831.800.200.50
Carex sylvatica1.0478.250.501.603.800.50
Erigeron canadensisa1.0379.600.502.203.200.00

The PERMANOVA test used to compare all plots with nonnative tree species in the tree layer (plots of groups Nonnative_Rob and Nonnative_RobPrun) to all plots without nonnative tree species in the tree layer (plots of groups Native_Quer and Native_QuerCarp) did not reveal a significant difference.

Functional Diversity and Percentage of Nonnative Species

The percentage of nonnative species in the soil seed bank was about 20% for the groups Nonnative_Rob, Nonnative_RobPrun, and Native_Quer and around 10% for the group Native_QuerCarp. The most abundant nonnative species were Juncus tenuis, Erigeron canadensis, Phytolacca americana, Buddleja davidii, and Oenothera glazoviana. The average percentages of nonnative species in the tree, shrub, and herb strata of the standing vegetation were the following: 16% for the group Nonnative_Rob, 41% for the group Nonnative_RobPrun, 3% for the group Native_Quer, and 1% for the group Native_QuerCarp.

In the soil seed bank, hemicryptophytes were the most highly represented life form in all groups, followed by therophytes and phanerophytes (Fig. 2).

image

Figure 2. Percentage of the life forms according to Raunkiær (1934) in the soil seed bank of the four groups, 1 = Nonnative_Rob, 2 = Nonnative_RobPrun, 3 = Native_Quer, 4 = Native_QuerCarp.

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For all groups, 43–60% of all species were ruderals (ruderals, competitors-ruderals, stress tolerators-ruderals, and competitors-stress tolerators-ruderals) and 40–57% of all species were nonruderals (competitors, stress tolerators and competitors-stress tolerators type), as shown in Figure 3.

image

Figure 3. Percentage of the strategy types according to Grime (1974) in the soil seed bank of the four groups, 1 = Nonnative_Rob, 2 = Nonnative_RobPrun, 3 = Native_Quer, 4 = Native_QuerCarp.

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Correlation of the Soil Seed Bank with Standing Vegetation and Soil Parameters

Both Bray–Curtis and Sørensen coefficients showed that the species similarity between soil seed bank and standing vegetation was very low. The group average for the Bray–Curtis coefficient was between 0.02 and 0.06, and the group average for the Sørensen coefficient ranged between from 0.12 to 0.16. The cluster analysis confirmed these results, and showed that the species composition of the standing vegetation and the soil seed bank are more similar among one another than compared with each other (Fig. 4). The soil seed banks are mostly dominated by Athyrium filix-femina, Juncus effusus, Equisetum arvense, and Centaurium erythraea. For the standing vegetation, characteristic species of the tree layer are Q. robur, with different proportions of Ulmus minor, C. betulus, R. pseudoacacia, and P. serotina, typical species of the shrub layer are Coryllus avellana, Crataegus monogyna, Euonymus europaeus, and Prunus padus, and in the herb layer the most frequently appearing species are Carex brizoides, Carex pilosa, Hedera helix, Oplismenus undulatifolius, Rubus caesius, Rubus sect. Rubus, and Vinca minor.

image

Figure 4. Cluster analysis for the standing vegetation and the soil seed bank (each with 20 samples) using Bray–Curtis coefficient, SB-seed bank, V-standing vegetation, G-group number, P-plot number, Group codes: 1 = Nonnative_Rob, 2 = Nonnative_RobPrun, 3 = Native_Quer, 4 = Native_QuerCarp.

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A comparison of the soil seed bank with the plant community Polygonato multiflori–Quercetum roboris, which represents the target vegetation for the floodplain hardwood forests in the study area, showed that there are only few similarities. Just 11 out of 52 target species (Q. robur, Clematis vitalba, Glechoma hederacea, C. pilosa, Populus alba, R. caesius, H. helix, Carex sylvatica, C. betulus, Stellaria media, and Anemone nemorosa) were present in the seed bank. This corresponds to 13% of the total number of species and only 5% of the total number of individuals. The composition of the soil seed bank and the standing vegetation of all plots is shown in the Tables S1–S4.

The comparison between the soil seed bank and the soil parameters revealed a significant positive correlation between species numbers and soil pH, and a significant negative correlation between species number and C/N ratio in a depth of 5 cm (Fig. 5).

image

Figure 5. Results of the correlation analysis relating species number in the soil seed bank to pH-value (CaCl2) and C:N ratio (in 5-cm soil depth).

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Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. LITERATURE CITED
  9. Supporting Information

In the following, we will first discuss the different factors influencing the composition of the soil seed bank and examine which functional group performed best in the soil seed bank. Secondly, we will analyze the regeneration potential of the soil seed bank and discuss implications for the management of R. pseudoacacia and P. serotina. For all four analyzed groups, both the species composition of the forest canopy and soil parameters significantly influenced the species composition of the soil seed bank. However, the cluster analysis revealed that some of the plots of a given forest type are more similar to plots of other groups than to plots of their own group, so other factors aside of canopy composition must have had a large impact on the seed bank. Possible factors are the location within the park, which stretches about 100 km from north to south, the distance of the plots from the river bank, and the former land use, which is fundamental for the composition of the seed bank (Plue et al. 2010). It can be assumed that after World War II the forests on our plots were almost completely destroyed due to excessive wood use for energy production (Furlanetto 2002). Thus, the stands considered here represent succession stages. The high percentage of therophytes, ruderals, and pioneer species in the forest stands support this assumption.

The percentage of nonnative species in the soil seed bank amounted to 20%. This is higher than the average percentage of nonnative species in the flora of Italy (13.4%; Celesti-Grapow et al. 2009) and in the flora of Lombardy (16.9%). Such high values are not uncommon for forest ecosystems, as many nonnative species form persistent seeds, which remain in the soil for a long time but cannot germinate because their germination requirements are not met under the cover of a closed forest canopy (Hopfensperger 2007; Bossuyt & Honnay 2008). Our focal tree species R. pseudoacacia and P. serotina amounted to 0.37% and 0.04% of the soil seed bank, respectively.

Compared to the average percentage of life forms in floodplain forests in Central Europe (Korneck et al. 1998), the soil seed banks here contained more therophytes and less phanerophytes, chamephytes, geophytes, and hydrophytes. The generally higher percentage of therophytes in soil seed banks is easily explained by the fact that they tend to survive in unfavorable conditions as seeds. Additionally, the former forest destruction is considered a key factor in the high proportion of therophytes. For all groups, about 50% of the species in the seed bank were ruderals (such as Cyperus flavescens, Erigeron canadensis, Oxalis stricta, Eragrostis pilosa, Erigeron annuus, Centaurium erythraea, Stellaria media (s. str.), and Lindernia procumbens) and 50% of them were nonruderals (such as Athyrium filix-femina, Juncus effusus, Cyperus michelianus, Pteridium aquilinum, and Juncus tenuis).

Some of the species are adapted to high or changing soil wetness. The longevity index of group Nonnative_RobPrun, containing those stands with all four tree species in the canopy, corresponded to the typical longevity index of forest ecosystems. In contrast, the longevity indices of the other groups corresponded more to the typical values for grassland (Korneck et al. 1998). This indicates that the soil seed bank does not only contain species typical for forest stands, but also a lot of species from surrounding areas such as grassland, agricultural areas, uncultivated land, or wetlands. All these ecosystems have a higher average longevity index than forest ecosystems (Thompson et al. 1998).

The correlation between the examined soil parameters and the species number and seed density in the soil seed bank can be explained by direct and indirect effects. Species number increased with pH most likely because a higher pH-value positively affects the species number in the standing vegetation, which influences the species number in the soil seed bank (c.f. Erenler et al. 2010). Another influencing factor might be that soil pH and nutrient availability affect the activity of soil organisms, which are responsible for integrating the seeds into the soil (Schmidt et al. 2009).

The comparison of the standing vegetation with the soil seed bank using the Bray–Curtis and Sørensen similarity coefficients showed that not only the species composition, but also their abundance, was very different between the studied plots and forest types. Those high dissimilarities are typical for forest ecosystems, generally showing the highest differences compared to other ecosystems (Hopfensperger 2007; Schmidt et al. 2009). As the similarity generally decreases with time since the last major disturbance, it can be assumed that the last disturbance event took place a long time ago.

The similarity to the typical vegetation of the Polygonato multiflori–Quercetum roboris association was also very low, caused by the fact that the soil seed bank is dominated by a few nontarget species, such as Athyrium filix-femina, Equisetum arvense, Juncus effusus, Centaurium erythraea, Juncus articulatus, Stellaria nemorum, and Cyperus michelianus, which represent about 70% of the total number of individuals. The dominance of a few nontarget species is typical for the soil seed banks of forests (Hopfensperger 2007; Bossuyt & Honnay 2008). Therefore, it is rather improbable that the regeneration of target species from the soil seed bank is possible. The regeneration will depend more on seed dispersal and recruitment than on the soil seed bank. Additionally, the high percentage of pioneer species and invasive species in the soil seed bank may hamper the establishment of the target vegetation if restoration management only relies on natural regeneration processes (Bossuyt & Honnay 2008; Zerbe 2009).

These findings have to be taken into account for the management of nonnative species in the Ticino Park, where the nonnative tree species (mainly R. pseudoacacia and P. serotina) reach a cover percentage of about 50–60% in the park's northern forest stands and about 25–30% in southern forest stands.

First introduced into the park for reforestation and honey production, R. pseudoacacia now occupies about 27% of the total forest area. Because of this wide distribution, the elimination of R. pseudoacacia is unrealistic. The soil seed bank analysis showed that R. pseudoacacia occurred in the seed bank on those plots where it was also present in the tree layer. The seeds of this species may persist in the soil for a long time, but need sites with low competition to establish. In forests with a closed canopy, R. pseudoacacia will naturally be suppressed by more shade tolerant species (Boring & Swank, 1984; Kowarik 2010). Such suppression by other species during later successional stages was also found for other anthropogenic forest types, e.g. pine monocultures in NE Germany (Zerbe & Wirth 2006) or oak forests in northern Italy (Motta et al. 2009). However, when disturbances occur and create gaps, the soil seed bank is activated and R. pseudoacacia can regenerate (Kowarik 2010). The vegetative regeneration of this species is also increased by disturbances. At present, disturbances creating larger gaps are mainly a consequence of the measures conducted to combat P. serotina in the park.

At present, P. serotina can be found in only 7% of the total park area and is only present in the northern and central parts of the reserve so far. However, it seems to have the potential to claim a larger range in Europe (e.g. Verheyen et al. 2007) and still shows a range expansion (Klotz 2009; Vanhellemont et al. 2011). The species is regarded as a more dangerous threat to the park's biodiversity than R. pseudoacacia, because of its ability to significantly reduce species numbers (e.g. Starfinger 1990, 1997; Schepker 1998; Verheyen et al. 2007; Caronni 2009), which could cause a shift in species composition away from the native species (Spaeth et al. 1994). The analysis of the soil seed bank showed that P. serotina is present in the seed bank on plots where it can be found in the tree layer. The ability of the seeds to survive in the soil seed bank for more than 5 years (Kowarik 2010), and the strong vegetative regeneration potential, explain why many attempts to eliminate P. serotina were not successful (Schepker & Kowarik 2001). At the moment, the park administration intends to prevent the further spread of the species by cutting and tending measures (Annighöfer et al. 2012). The mainly mechanical combat of this species in the park resulted in costs of about 830,000€ during a 10-year period. At the moment there is an ongoing discussion whether the use of herbicides may lead to better results, and which impacts on fauna and flora could be expected (Caronni 2009). The use of herbicides is critically discussed across Europe (Ammer et al. 2011; McCarthy et al. 2011). Annighöfer et al. (2012) tested different mechanical control methods to combat P. serotina. They showed that girdling might be a successful mechanical strategy to reduce the abundance of P. serotina; however, this might be quite expensive and labor intensive. Alternatively, it may be possible to harvest P. serotina in an economical way for fuel wood and energy production, while constantly reducing its abundance at the same time by repeated harvests.

However, taking the results of the seed bank analysis into account, the use of mechanical and/or chemical measures should be examined critically, as they inevitably cause disturbances and gaps in the forest canopy, which activate the soil seed bank. Furthermore, nontarget and invasive species present in the soil seed bank may be able to regenerate, which can lead to an unwanted change in species composition (see also Decocq et al. 2004; Albrecht et al. 2011). Therefore, the question arises if it might not be more efficient to leave the forest stands undisturbed, casting as much shade as possible. During further natural forest succession, P. serotina may lose its dominant position in the understory (Kowarik 2010).

Implications for Practice

Provided that maintaining and developing near-natural forests consisting of native species is the present and future objective for the biosphere reserve Valle del Ticino, we make the following recommendations:

  • As disturbances that are caused by the mechanical or chemical combat against invasive species (especially R. pseudoacacia and P. serotina) may activate the soil seed bank and give invasive and other nontarget species the opportunity to regenerate, we strongly recommend preventing or minimizing these kinds of measures unless carried out repeatedly in short intervals and consistently over long time periods. Other disturbances of the soil and the forest canopy should be avoided.
  • If interventions are believed to be the only solution to get rid of the invasive tree species underplanting shade-tolerant tree species such as C. betulus is suggested in order to outcompete the more light demanding species R. pseudoacacia and P. serotina in the long run.
  • Due to the low number of target species in the soil seed bank, facilitating the dispersal at the landscape level by creating corridors and stepping stones for vector-supported diaspore transport will be essential for successful regeneration of isolated floodplain forests.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. LITERATURE CITED
  9. Supporting Information

We would like to thank the Laimburg Research Center for Agriculture and Forestry in South Tyrol, Italy for kindly providing us the greenhouse space for our investigations. This study was funded by the Stemmler Foundation and the Marianne and Dr. Fritz Walter Fischer Foundation within the Stifterverband für die Deutsche Wissenschaft.

LITERATURE CITED

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. LITERATURE CITED
  9. Supporting Information
  • Albrecht, H., E. Eder, T. Langbehn, and C. Tschiersch. 2011. The soil seed bank and its relationship to the established vegetation in urban wastelands. Landscape and Urban Planning 100:8797.
  • Ammer, C., P. Balandier, N. Bentsen, L. Coll, and M. Löf. 2011. Forest vegetation management under debate: an introduction. European Journal of Forest Research 130:15.
  • Anderson, M. J. 2005. PERMANOVA: A FORTRAN computer program for permutational multivariate analysis of variance. Department of Statistics, University of Auckland, New Zealand.
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Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. LITERATURE CITED
  9. Supporting Information
FilenameFormatSizeDescription
rec12027-sup-0001-TableS1.pdfPDF document90KTable S1. Seed bank structure of groups Nonnative_Rob and Nonnative_RobPrun (species composition, total number of species and individuals, seed bank density, Shannon index, and dominance index).
rec12027-sup-0002-TableS2.pdfPDF document90KTable S2. Seed bank structure of groups Native_Quer and Native_QuerCarp (species composition, total number of species and individuals, seed bank density, Shannon index, and dominance index).
rec12027-sup-0003-TableS3.pdfPDF document95KTable S3. Species composition and vegetation cover of the standing vegetation in the different vegetation strata for the groups “Nonnative_Rob” and “Nonnative_RobPrun” (cover classes according to the methodology of Braun-Blanquet (1964) with r = 1 individual; + = 2–5 ind.; 1 = 6–50 ind., <5% cover; 2m = >50 ind., <5% cov.; 2a = 5–15% cov.; 2b = 16–25% cov.; 3 = 26–50% cov.; 4 = 51–75% cov.; 5 = 76–100% cov.; *indicating nonnative species, nomenclature follows Fischer et al. 2008).
rec12027-sup-0004-TableS4.pdfPDF document90KTable S4. Species composition and vegetation cover of the standing vegetation in the different vegetation strata for the groups “Native_Quer” and “Native_QuerCarp” (cover classes according to the methodology of Braun-Blanquet (1964) with r = 1 individual; + = 2–5 ind.; 1 = 6–50 ind., <5% cover; 2m = >50 ind., <5% cov.; 2a = 5–15% cov.; 2b = 16–25% cov.; 3 = 26–50% cov.; 4 = 51–75% cov.; 5 = 76–100% cov; *indicating nonnative species, nomenclature follows Fischer et al. 2008).

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