Many alien invasive plants disperse against the direction of stream flow in riparian areas

Many alien invasive plants disperse against the direction of stream flow in riparian areas

Ecological Complexity 15 (2013) 26–32 Contents lists available at SciVerse ScienceDirect Ecological Complexity journal homepage: www.elsevier.com/lo...

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Ecological Complexity 15 (2013) 26–32

Contents lists available at SciVerse ScienceDirect

Ecological Complexity journal homepage: www.elsevier.com/locate/ecocom

Many alien invasive plants disperse against the direction of stream flow in riparian areas Takeshi Osawa a,*, Hiromune Mitsuhashi b, Hideyuki Niwa b a b

National Institute for Agro-Environmental Sciences, 3-1-3, Kannondai, Tsukuba, Ibaraki Pref., 305-8604, Japan The Museum of Nature and Human Activities Hyogo, 6, Yayoigaoka, Sanda, Hyogo Pref., 669-1546, Japan

A R T I C L E I N F O

A B S T R A C T

Article history: Received 24 July 2012 Received in revised form 28 January 2013 Accepted 29 January 2013 Available online 5 March 2013

Propagule pressure plays an important role in the invasion of alien plants into riparian areas. In this study, we focused on propagule pressure from both neighboring riparian areas and anthropogenic landuse areas because propagules are likely to originate from both sources. We tested the effects of whether neighboring units contained the alien plant species, focusing on the direction of invasion by alien plant species into the focal unit, and how much anthropogenic land was contained within the unit, focusing on both farmland and urbanized areas, on alien plant occurrences in Hyogo Prefecture, Japan. We modeled the occurrence of 10 alien plants using generalized linear models to evaluate species invasions by both propagules from both neighboring units and anthropogenic land within a unit. We also investigated the biological and ecological plant attributes that are likely related to invasion success, such as seed dispersal methods, seed size, and clonality, and tested the relationships between the model results and each species’ attributes. Results showed that the occurrence of an affected neighboring unit was positively associated with the occurrence of all 10 alien plants. Note that two alien invasive species were influenced by upstream flow direction, six species by downstream flow direction, and in two species, propagule supply was not distinguished by direction. In short, the dominant direction of dispersal was against the stream current, while dispersal in the downstream direction was less common. Species attributes were associated with these directions of dispersal. In addition, anthropogenic land was positively associated with the occurrence of most alien plants, although this effect was weaker than the neighbor unit effects. These results indicate that alien plants spreading into riparian areas do not always follow the natural flow regime; rather, they spread against the flow regime in some cases. We discuss an ecological explanation for these results and provide perspectives for future river management of alien plants that invade the riparian zone. ß 2013 Elsevier B.V. All rights reserved.

Keywords: Alien invader plant Invasion success Neighboring effect Propagule pressure River managements Spreading

1. Introduction Natural riparian zones constitute an interface between aquatic and terrestrial ecosystems and contain diverse habitats that help to conserve high biodiversity (Burkart, 2001; Naiman et al., 1993; Whited et al., 2007). At the same time, riparian zone biodiversity is strongly threatened by alien invasive species (AIS; Birken and Cooper, 2006; Hood and Naiman, 2000; Richardson et al., 2007). AIS negatively affect native species through predation, competition, and the spread of pathogens (Cameron et al., 2011) and can modify ecosystem functioning and abiotic features of the environment (Ricciardi, 2007; Strayer et al., 2006). Successful invasion of AIS into a particular location requires dispersal, colonization, and establishment (Ficetola et al., 2009;

* Corresponding author. Tel.: +81 29 838 8148; fax: +81 29 838 8199. E-mail addresses: [email protected] (T. Osawa), [email protected] (H. Mitsuhashi), [email protected] (H. Niwa). 1476-945X/$ – see front matter ß 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ecocom.2013.01.009

Puth and Post, 2005; Richardson et al., 2000). Dispersal success varies with the quantity of dispersing propagules (Holle and Simberloff, 2005) and the landscape being invaded (With, 2002). In particular, propagule pressure, that is, the rate of spread of alien plant propagules into new areas (Chytry et al., 2009; Holle and Simberloff, 2005; Lockwood et al., 2005), often plays a much more important role in determining the distribution of species than environmental conditions in several ecosystems worldwide (Holle and Simberloff, 2005; Lockwood et al., 2005). Riparian ecosystems exhibit downstream connectivity via their natural flow regime. Hydrological connectivity in river–floodplain ecosystems strongly disperses propagules downstream, based on hydrochory (dispersal by water flow and/or rain; Pysek and Prach, 1993; Richardson et al., 2007). Thus, hydrochory is likely to serve as one of the most important dispersal methods for invasion success in riparian areas. However, plant species exhibit several dispersal methods other than hydrochory, such as anemochory (dispersal by wind) and zoochory (dispersal by humans and/or other animals). These dispersal mechanisms are not likely to be

T. Osawa et al. / Ecological Complexity 15 (2013) 26–32

strongly influenced by natural stream flow. For example, for species that exhibit anemochory, the direction of dispersal depends on the wind direction, which is likely to function in no specific direction. The direction of dispersal for zoochoric species depends on the movement of courier terrestrial animals, which also might not exhibit a strong relationship with stream flow. However, the most important dispersal method within riparian areas, particularly for AIS, remains unclear. Determining the most crucial dispersal method for invasion success in riparian areas could aid in predicting which AIS pose a high risk of invasion in terms of their dispersal mechanism. Drezner et al. (2001) showed that the distribution of plant species in riparian areas is related to their dispersal methods. Thus, we hypothesized that analyzing the relationships between AIS dispersal methods and their distribution patterns would determine the most important dispersal mechanism for invasion success in riparian areas. The first objective of this study was to clearly document the most important dispersal method, and related attributes, for invasion success in riparian areas. To this end, we analyzed the relationships between AIS dispersal methods and their distribution patterns. Similar to vegetation patches, human land uses such as farmland and urbanized areas can also act as propagule sources of AIS (Chytry et al., 2009). Therefore, we also evaluated the effects of anthropogenic land-use areas as substitute variables for the power of AIS propagule pressure. We used substitute variables because directly evaluating the effects of propagule pressure is

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quite difficult. Namely, we assumed that large areas of specific land uses would supply many propagules. We used two substitute variables, farmland and urban/industrial land areas, which strongly influence invasion into riparian areas (Chytry et al., 2008, 2009; Meek et al., 2010; Pino et al., 2005). Previous studies have suggested that these substitute variables are useful indicators of propagule pressure (Chytry et al., 2008, 2009; Pino et al., 2005). The second objective of the study was to determine the efficiency of various propagule pressures from anthropogenic land uses, specifically farmland and urban/industrial areas. Thus, we simultaneously focused on propagule pressure from both neighboring riparian areas as well as anthropogenic land-use areas. Our results may provide important insights for predicting invasion risk and planning river management. In this study, we tested relationships between successful invasion of AIS and multiple propagule pressures by analyzing the spatial distribution patterns of 10 AIS plants that exhibit various dispersal methods in riparian areas of Hyogo Prefecture, Japan. We expected that successful invasion of AIS would be closely related to neighbor-invaded areas as a propagule source and that the direction of propagule pressure would be closely related to the dispersal method of the species. For example, propagules of hydrochoric species are likely to be supplied from upstreaminvaded areas because stream flow acts as a dispersal corridor (Wilson et al., 2009), whereas other dispersal methods may not necessarily occur in the direction of stream flow. First, we tested the most effective propagule pressure direction from neighboring

Fig. 1. Location of rivers and researched units in Hyogo Prefecture, Japan.

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Table 1 List of plants species and status in the study. NOIS means ‘‘Noxious invasive species’’, ATIS means Attension invasive species respectively, and both assigned by Japan government. ESJ worst 100 is problematic 100 invasive species selected by Ecological Society of Japan. Main concerns were derived from list of invasive species in Japan, Ministry of Environment. Species name

Family

NOIS

Sicyos angulatus L. Ambrosia trifida L. Festuca arundinacea Schreb. Helianthus tuberosus L. Paspalum distichum L. Bidens pilosa L. var. pilosa Eragrostis curvula (Schrad.) Nees Solidago altissima L. Sorghum halepense (L.) Pers.

Cucurbitaceae Compositae Poaceae Compositae Poaceae Compositae Poaceae Compositae Poaceae

+

Conyza canadensis (L.) Cronquist

Compositae

ATIS + + + + + + +

ESJ worst 100

Other

Main concern

+ + +

+ + Harmful weed in worldwide

+

areas for each of the 10 AIS. Subsequently, we evaluated the relationships between the most effective direction and dispersal methods in each species. At the same time, we also tested the effects of land-use areas as substitute variables on propagule pressure. On the basis of the results, we discuss the significance of dispersal method in the successful invasion of AIS and perspectives for future river management. 2. Methods 2.1. Study area and data sources The study was conducted in Hyogo Prefecture, Japan (34841’N, 135812’E, 8395.61 km2; Fig. 1). The mean annual precipitation is 1264.7 mm, and the mean annual temperature is 16.9 8C (Japan Meteorological Agency). We used the Research about the Natural Environment of Rivers, Hyogo (RNER) invader-vegetation data set from surveys conducted between 2002 and 2006 to investigate riparian vegetation in alluvial river sections (total length, 680 km). RNER identified the edges of vegetation patches from aerial photographs. Subsequently, extensive field surveys were conducted to classify the types of vegetation in the patches (Hyogo Prefecture, 2007). Vegetation surveys were conducted according to Braun-Blanquet phytosociology methods: quadrats were established in each vegetation patch, all species and their abundances were recorded, and vegetation types were defined according to dominant species (Braun-Blanquet, 1964; Hyogo Prefecture, 2007). The data set classified vegetation patches into 91 types based on the dominant species. Land use and unvegetated areas (e.g., natural bare ground, open water, and artificial areas) were also classified into five types, and the vegetation/land-cover types were summarized as patches on a vegetation map. Vegetation was mainly distributed within 50 m of the river line, and each vegetation patch was input as digital polygon data into a geographic information system (GIS).

Compete Compete Compete Compete Compete Compete Compete Compete Compete

against against against against against against against against against

native native native native native native native native crop

species species species species species species species species

and and and and and

crop crop crop crop crop

Compete against native species and crop

2.2. Data sets We selected 10 AIS-dominated vegetation types from the RNER data set. The selected vegetations were dominated by Ambrosia trifida L., Bidens pilosa L. var. pilosa, Conyza canadensis (L.) Cronquist, Eragrostis curvula (Schrad.) Nees, Festuca arundinacea Schreb., Helianthus tuberosus L., Paspalum distichum L., Sicyos angulatus L., Solidago altissima L., and Sorghum halepense (L.) Pers. (Table 1). These 10 AIS were selected because their occurrence was higher than those of other species in the data sets (>50 presence units; described below) and because they are well-known riparian AIS (Shimizu et al., 2001). These 10 AIS are distributed across wide areas in Japan (Ministry of the Environment, Japan) and are known to compete against native plants and/or crops (Table 1); additional knowledge of these species is required to mitigate their invasion (Ministry of the Environment, Japan). Determining the period of invasion by AIS is important for evaluating the spread of distribution because after invasion, some AIS rapidly invade extensive areas (Cadotte et al., 2006), whereas some others exhibit time lags in their expansion (Crooks and Soule, 1999). This difference in the rate of invasion relates to their biological attributes (Akasaka et al., 2012) and can complicate evaluations of the spread of their distribution. In this study, we considered that our 10 AIS had already reached steady-state growth because they had been present in Japan for at least a half century (Table 2). 2.3. Dispersal attributes of each AIS We investigated species attributes, such as the dispersal methods of anemochory, hydrochory, and zoochory, as well as ecological attributes that were likely to influence invasion success, such as seed size (four classes: 1, 1 mm; 2, 5 mm; 3, 10 mm; 4, >10 mm) and clonality (apparent or not) in each AIS. To obtain this information, we referred to specialized AIS books in Japan

Table 2 List of plant species and attributes examined in the study. Life form

Species name

First record year in Japan

Seed dispersal methods

Seed size

Annual Annual Perennial Perennial Perennial Annual Perennial Perennial Perennial Annual

Sicyos angulatus L. Ambrosia trifida L. Festuca arundinacea Schreb. Helianthus tuberosus L. Paspalum distichum L. Bidens pilosa L. var. pilosa Eragrostis curvula (Schrad.) Nees Solidago altissima L. Sorghum halepense (L.) Pers. Conyza canadensis (L.) Cronquist

1952 1953 1960 Before 1945 Before Before Before 1945 Before

hc, zc hc, zc ac, hc, zc

3 3 3 3 2 4 2 1 2 1

1912 1868 1941 1912 1912

Seed size: 1, 1 mm,; 2, 5 mm; 3, 10 mm; 4, 10 mm. Dispersal method: ac, anemochory; hc, hydrochory; zc, zoochory.

hc, zc zc ac, hc, zc ac ac ac, hc, zc

Clone

+ + + + + +

Number of presence meshes 90 232 57 70 275 274 62 656 78 110

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(Murakami and Washitani, 2002; Shimizu et al., 2001) and the specialized AIS Web database systems (Invasive Species of Japan; Invasive Species List) and filled data gaps using other literature (Nakayama et al., 2004; Shimizu et al., 2005). Seed number, which is important for invasion success, was not used because seed numbers are generally negatively correlated with seed size.

Subject mesh

29

River

3rd mesh

2.4. Data preparation We used the Japanese Standard Third Mesh (approximately 1  1 km) as our analysis unit for two reasons. First, this unit size allowed us to analyze 10 species and to avoid zero-inflated data (i.e., data containing a large proportion of absence values) because analyzing such data sets is likely to lead to incorrect conclusions by violating basic assumptions of statistical inferences (Martin et al., 2005; Osawa et al., 2011). If a finer unit had been used, almost all data sets would have become zero-inflated data. Second, this unit size allowed us to avoid arbitrary effects on location because the location of the units was determined by the Japanese government (Ministry of Internal Affairs and Communications, Japan). Differences in the location of units could lead to different data and conclusions. For example, when one polygon and two mesh units larger than the polygon are overlaid to make a presence/absence mesh unit, two patterns can result depending on the location of the mesh unit: one presence and one absence, or both presences. Thus, it is preferable to avoid arbitrary definitions for analyzing units as much as possible. We overlaid the RNER riparian vegetation map (polygon data) and the mesh data and determined the presence/absence of each AIS per unit mesh (Fig. 1). In total, 1039 mesh units constituted the riparian vegetation area. Subsequently, we calculated the total areas of farmland, urbanized areas, and total riparian vegetation areas per unit mesh. Farmland and urbanized area data were obtained from Green Census data, which is a major land-use/landcover GIS polygon data set for Japan (Ministry of the Environment; Biodiversity Center of Japan), and total riparian vegetation area was derived from the RNER data set. We distinguished three types of direction on propagules from neighboring units (hereafter neighbor effects): (a) propagules from upstream, (b) propagules from downstream, and (c) propagules from the immediate vicinity (Fig. 2). A propagule from upstream (type a) was defined when a neighboring mesh unit that was adjacent and upstream had AIS vegetation, and type (b) defined the case when a neighboring mesh unit that was adjacent and downstream had AIS vegetation. Type (c) defined the case when a neighboring mesh unit contained AIS vegetation without clear upor downstream direction (Fig. 2). Thus, type (c) included both (a) and (b). All calculations were conducted using GIS software (ArcView 3.3 ESRI Japan). 2.5. Statistical analyses We tested the presence/absence of neighbor effects and landuse patterns of the 10 AIS in all riparian areas using generalized linear models (GLMs) and model selection based on Akaike’s information criteria (AIC; Burnham and Anderson, 2002). A GLM approach is a flexible generalization of ordinary linear regression that allows for response variables that do not have normal (Gaussian) distribution. In our case, we used a binomial distribution to model the presence/absence data set as the response variable. A model with a lower AIC value is more plausible because it has higher explanatory power and fewer explanatory variables (Burnham and Anderson, 2002). Parameters were estimated using maximum likelihood methods. This analysis consisted of two steps: (1) determine the most effective neighbor effects and (2) determine the best model step. The

River

Invader species vegetation

(a) Upstream

(b) Downstream

(c) Immediate vicinity

Fig. 2. Diagram of the three types of neighbor effects. (a) Propagules from upstream, (b) propagules from downstream, and (c) propagules from the immediate vicinity. Type (c) includes both type (a) and (b).

response variable in all models was presence/absence of each AIS. For step 1, we compared AIC values among the three models using only the neighbor effect from upstream, downstream, or no direction as explanatory variables. We selected the lowest AIC model as the ‘‘best neighbor effect model’’ and used it in subsequent steps. If the lowest AIC model contained an upstream neighbor effect, we can conclude that the best neighbor effect for the AIS is from the upstream area. For step (2), our primary GLMs included all explanatory variables (best neighbor effect, total riparian vegetation area, farmland area, and urbanized area). We used the stepwise modelselection method to find the best model combination of variables with the lowest AIC. Stepwise model selection begins with the full model (with all explanatory variables) and eliminates explanatory variables one at a time, considering at each step whether the criterion will be improved by adding back a variable removed at a previous step (Venables and Ripley, 2002). The model-selection procedure suited our analyses because a reduction in explanatory variables simplifies understanding. All statistical analyses were conducted with statistical package R ver. 2.9.1 (R Development Core Team, 2009). 3. Results 3.1. Summary of data sets used The numbers of AIS present in the studied area are shown in Table 2. S. altissima L. had the highest (656) presence, and F. arundinacea Schreb. had the lowest (57). The attributes of each AIS are shown in Table 2. We could not find descriptions of the seed dispersal methods of H. tuberosus (Table 2). F. arundinacea, E. curvula, or C. canadensis employed all three dispersal methods, namely anemochory, hydrochory, and zoochory (Table 2). The seed sizes of four species were class 3, and only S. altissima was class 1 (Table 2). Six AIS had clonal reproductive attributes (Table 2).

T. Osawa et al. / Ecological Complexity 15 (2013) 26–32

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Table 3 Results of generalized linear model selection based on AIC for the presence/absence of each AIS. Best model contributions of positive (+) or negative ( ) are shown. n.s. indicates variables not selected by model selection procedures. Upstream/Downstream/Around indicate the best direction of neighbor effects for each AIS, also determined by AIC. AIC values that excluded explanatory variables from the best model are also shown. Species name

Neighbor effect

Vegetation area (m2)

Farmland area (m2)

Urbanized area (m2)

BM

+ + + + 375.90 371.18 365.85 (Upstream) 517.22 + n.s. Ambrosia trifida L. + n.s. 496.15 502.85 (Upstream) 981.95 n.s. + n.s. n.s. 361.1 Festuca arundinacea Schreb. (Around) 420.68 n.s. Helianthus tuberosus L. + n.s. + 338.6 (Downstream) 340.86 484.81 + + + Paspalum distichum L. + 605.50 619.05 619.05 (Downstream) 1086.08 n.s. + + n.s. 757.06 Bidens pilosa L. var. pilosa (Downstream) 760.35 1148.49 + n.s. Eragrostis curvula (Schrad.) Nees + + 219.17 220.93 (Downstream) 235.66 412.84 + + + + Solidago altissima L. 577.41 587.39 561.25 (Downstream) 1192.17 + + + Sorghum halepense (L.) Pers. + 270.64 269.92 278.25 (Around) 397.62 + + + Conyza canadensis (L.) Cronquist + 549.61 548.56 542.13 (Downstream) 644.41 BM and PM AICs mean AICs for the best models and primary models, respectively. PM AICs are not shown when primary models are best models. Sicyos angulatus L.

PM 362.86

499.92

365.04

340.21

602.7

760.61

220.99

559.47

267.69

539.27

Table 4 Relationships between types of propagule pressure and attributes of alien invasive species (AIS). Factor Neighbor effect Anthropogenic land use

Component

n

Dispersal methods

Seed size

Upstream Downstream Around Farmland Urbanized area

2 6 2 6 7

hc: 2, zc: ac: 3, hc: ac: 2, hc: ac: 2, hc: ac: 4, hc:

c1: c1: c1: c1: c1:

2 3, 1, 3, 4,

zc: zc: zc: zc:

4 1 4 4

0, 2, 0, 2, 2,

c2: c2: c2: c2: c2:

Clone 0, 1, 1, 2, 3,

c3: c3: c3: c3: c3:

2, 2, 1, 1, 2,

c4: c4: c4: c4: c4:

0 1 0 1 0

0 4 2 3 5

Seed size; c (class) 1: 1 mm, c2: 5 mm, c3: 10 mm, c4: 10 mm. Dispersal method: ac, anemochory; hc, hydrochory; zc, zoochory.

The mean riparian vegetation area, farmland area, and urbanized area of all research units were 40,797.49  44,024.34, 393,854.1  249,081.0, and 168,120.3  208,158.0 m2 (mean  SD), respectively.

area was positively correlated with the presence of AIS in the best models for six species. The urbanized area was positively correlated with the presence/absence of AIS in the best models for seven species.

3.2. Directions of the best neighbor effect

3.4. Relationships between propagule source and AIS attributes

The best neighbor effects for each AIS are shown in Table 3. Two AIS were from upstream, six were from downstream, and two had undistinguishable directions for the best neighbor effect (Table 3).

The relationships between propagule sources and AIS attributes are shown in Table 4. The two species that had upstream sources used hydrochory and zoochory and were relatively large in size (class 3) but did not have clonal reproductive attributes (Table 4). In contrast, the six species that had downstream sources exhibited several dispersal attributes. Three of the six species were both anemochoric and hydrochoric, and four of the six species were zoochoric and had clonal reproductive attributes (Table 4). Two species used anemochory and had clonal reproductive attributes (Table 4). Four of the six species influenced by farmland area used zoochory, and three of six species used hydrochory and had clonal reproductive attributes (Table 4). Four of seven species influenced by urban land use employed all three dispersal methods, and five of the seven had clonal reproductive attributes (Table 4).

3.3. Contribution of variables to the best models All variables included in the best models were positively correlated with the presence/absence of AIS (Table 3). All best models included the neighbor effect and variables that positively influenced the presence of each AIS (Table 3). The neighbor effect contributed the most among all variables according to AIC; i.e., if the neighbor effect were excluded, the AIC values increased more than if the other variables were excluded for all species (Table 3). The total riparian vegetation area was positively correlated with the presence of AIS in the best models for seven species. Farmland

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4. Discussion We modeled the occurrence of 10 alien plants to evaluate successful invasion focusing on propagule from both a neighboring invaded units and anthropogenic land use within the unit in a riparian area. Both the neighboring units and anthropogenic land use within the unit played important roles in AIS invasion. In particular, neighboring invaded units affected the invasion of all 10 AIS, but the most effective direction was against stream flow. Differences in the most effective direction of each AIS were likely related to species dispersal methods or related attributes. All 10 AIS occurrences were positively influenced by the neighbor effect (Table 2), suggesting that the invasion success of all 10 AIS was strongly influenced by propagule pressure from neighboring invaded areas. However, interestingly, only two AIS were influenced by upstream-invaded areas (Table 3), although upstream forces are generally considered a main propagule dispersal strategy. Six AIS were influenced by neighboring invaded areas against stream-flow direction, and two AIS were not influenced by specific directions (Table 3). These results suggest that stream flow is not always the most effective factor for supplying propagules to riparian areas; i.e., hydrochory may not be the most effective dispersal method. Naiman and Decamps (1997) noted that zoochory and anemochory may have more important roles than hydrochory for dispersal in riparian corridors (Naiman and Decamps, 1997). In fact, four of the six species in our study had dispersal directions against stream flow, and all employed a zoochoric method. In addition, the dispersal method of the two species that did not preferentially spread up- or downstream was anemochory (Table 4). Nevertheless, many previous studies have indicated that flowing water is important for spreading plant propagules along river systems (e.g., Boedeltje et al., 2004; Nilsson et al., 1991; Vogt et al., 2004), and therefore, free-flowing rivers are considered major pathways for plant dispersal (Johansson et al., 1996). However, our results did not support this conclusion, despite that six of 10 AIS employed a hydrochoric method (Table 2). Here, we propose one possible explanation for our results. Our results may have been caused by attributes specifically associated with AIS because the noteworthy difference between previous studies and our study is that our study used only AIS. The importance of flowing water as a propagule transfer mechanism to maintain native plants has already been shown in several studies (Boedeltje et al., 2004; Leyer, 2006; Vogt et al., 2004) but has been rarely shown for AIS. On the basis of these results, we considered that many AIS did not supply propagules by flowing water in riparian areas at least in Japan. AIS do not always grow in riparian areas of their native region. These species may not depend strongly on hydrochory for dispersal in invaded areas. As a result, almost all AIS did not disperse propagules along with stream flow, which differs from many native plants in riparian areas. In a similar case, Osawa et al. (2010) showed that seasonal flooding led to increases in the number of native annual species compared to nonnative species. Thus, natural phenomena in river ecosystems might only contribute to the introduction of native species and not to that of nonnative species (Osawa et al., 2010). Our results indicated that the expansion of six AIS may depend on dispersal methods other than hydrochory in riparian areas. Thus, the natural flow regime did not contribute strongly to the expansion of these six AIS in our study area in Japan. Some species attributes were related to dispersal direction. Two species with dispersal directions along with stream flow used both hydrochory and zoochory and had relatively large seeds (Table 4). These two species had common attributes, and both are widely distributed in Japanese riparian areas, defined as ‘‘noxious AIS’’ by Japanese law (Murakami and Washitani, 2002). These two species

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might grow in riparian areas in their native region, as their large seed size is a typical attribute of hydrochoric species. In fact, the native habitat of A. trifida is the floodplain (Murakami and Washitani, 2002). Therefore, these plants may have similar attributes to native plants that are adapted to riparian areas, particularly attributes related to dispersal strategies; thus, they mainly use stream flow as a propagule supplier. In contrast, four of the six species whose dispersal direction was against stream flow were zoochoric and had clonal growth attributes (Table 4). One possible explanation is that these species were brought into the area as propagules, e.g. as seed or piece of tissue, by anglers. Anglers often move from downstream to upstream areas to change fishing spots. Anglers may have brought AIS seeds and/or stems from downstream to upstream. Although the propagules of these six species were not moved by stream flow, animals including humans can strongly affect propagule dispersion. The two species that were not associated with a specific direction were anemochoric and had clonal growth attributes (Table 4). These results are considered reasonable because wind can change direction freely, and clonal reproduction, i.e., clonal growth, may not have specific growth directions. Land use is a factor related to AIS invasion (Didham et al., 2007). In our study, almost all AIS were influenced by farmland and/or urbanized areas. Farmland areas positively influenced the invasion success of seven species, and urbanized areas positively influenced the invasion success of six species (Table 3). The occurrence of two species, namely A. trifida and F. arundinacea, were influenced neither by agriculture nor urban land-use areas. Invasion by these two species might have been extremely influenced by propagule pressure from neighboring areas. Riparian vegetation area positively affected the invasion of seven species (Table 3). This result was not surprising because small patchy areas are likely to include a low number of species (Godefroid and Koedam, 2003). Our results suggest that AIS were not an exception to this trend. 5. Conclusions In this study, we showed two important features of riparian areas. First, stream flow is not always the most effective factor for supply of AIS propagules that have already reached steady-state growth in riparian areas. On the contrary, many AIS were influenced by neighboring invaded areas through propagule pressure against the stream-flow direction. Based on these results, we propose an idea for river managers. When building in riparian areas, managers should prevent alien plant invasion from neighboring areas because AIS growing in neighboring areas have a high risk of invasion. Importantly, it is not always true that lower river basin areas have a higher risk for AIS expansion. Rather, in some cases, the upstream area has a higher invasion risk. Depending on the situation, managers should pay less attention to invasion by AIS to upstream areas and should focus on invasion to downstream areas. In other cases, eradication efforts should concentrate on downstream areas that might act as propagule sources to upstream areas. Second, many AIS may not follow the native ecological process for propagule supply. Specifically, although the AIS examined in this study exist in riparian areas, they may not necessarily expand according to the natural flow regime because these AIS included several species that are adapted to areas other than riparian zones. Thus, a river maintaining a native flow regime and/or flooding can prevent AIS invasion (Osawa et al., 2010). However, river habitat alterations have been conducted worldwide (Poff et al., 1997; Rinaldi and Johnson, 1997; Washitani, 2001). As a result, many river environments might allow AIS invasion. Our suggestions provide such a future risk index for river management.

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