Are plant communities of roadside stormwater ponds similar to those found in natural wetlands?

doi:10.21203/rs.3.rs-3764595/v1

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Are plant communities of roadside stormwater ponds similar to those found in natural wetlands?

https://doi.org/10.21203/rs.3.rs-3764595/v1

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published 12 Sep, 2024

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Stormwater ponds (SP) are increasingly used for water management along roads and in urban environments. How these constructed wetlands compare to natural wetlands in terms of biodiversity remains unclear, however. Studies to date have evaluated the subject in general terms, without considering the different habitats in SP and wetlands (from aquatic, at the pond edge, to terrestrial, at the upper bank) or other local and regional factors. This project aimed to compare the taxonomic diversity and composition of plant communities established in four different habitats of SP with that in either roadside or remote natural wetlands. We also evaluated the effect of various local and regional factors on those communities. Our results show that, globally, the species composition of the lower, wetter habitats was similar between SP and reference wetlands, especially roadside wetlands, while higher, drier habitats showed significant differentiation. Factors explaining observed differences between SP and both roadside and remote natural wetlands were water level fluctuations, road proximity, slope, and age of the SP. Stormwater ponds also exhibited lower beta diversity than both types of wetlands. Nonetheless, our study suggests that with some improvements in design, SP have the potential to more closely resemble natural wetlands.

Stormwater ponds

wetlands

plant communities

biodiversity

beta diversity

roads

Wetlands are one of the most biodiverse habitats on Earth (Costanza et al. 1997; Dodds et al. 2008), displaying crucial ecological functions such as water level regulation, water filtration, and carbon sequestration (Temmink et al. 2022). However, these unique ecosystems are rapidly declining worldwide (Zedler and Kercher 2005; Davidson 2014; Dixon et al. 2016) due to land-use changes, with net losses estimated at 21% or more since 1700 (Fluet-Chouinard 2023). In order to manage the surplus surface water runoff resulting from both the loss of wetlands and the increase in impervious surfaces, the construction of stormwater ponds (SP) is becoming widespread in urban and peri-urban environments (Tixier et al. 2011, Birch et al. 2022).

In addition to their primary functions of water regulation and pollutant reduction (Starzec et al. 2005; Mitchell et al. 2007), SP often constitute habitats for plants and wildlife (Marsalek et al. 2005), increasing species connectivity in human-dominated landscapes (Birch et al. 2023). In turn, the presence of plants further contributes to the ecosystem functioning of SP, increasing the services provided (Engelhardt and Ritchie 2001; Shirdashtzadeh et al. 2022). However, to what extent plant communities in these constructed wetlands mirror those of reference ecosystems, i. e., natural wetlands in similar environmental contexts, remains to be explored. Such unmanaged reference ecosystems are used as a standard of comparison for evaluating restored or constructed sites (SERI 2004; Moreno-Mateos et al. 2012). This makes it possible to determine whether the attributes of the latter (e.g., composition, diversity, richness, strata, functions) follow the expected trajectory towards the restoration or construction objectives (Zedler and Callaway 1999; Campbell et al. 2002; Balcombe et al. 2005; Matthews et al. 2009).

Although some SP are planted or seeded with a set of species following construction, they are often rapidly colonized by invasive species that tend to exclude others, including native wetland species (Reinartz and Warne 1993; Kuntz et al. 2018). Studies assessing SP plant diversity show that reference wetlands are more diverse than SP, with upland as well as invasive wetland species such as Typha angustifolia and Phragmites australis subsp. australis being key drivers of this divergence (Reinartz and Warne 1993; Rooney et al. 2015; Kuntz et al. 2018). It follows that the richness of wetland obligate and facultative species has been found to be lower in SP than in reference wetlands (Rooney et al. 2015; Perron and Pick 2020), leading to lower ecological value (Rooney et al. 2015).

Roads are infrastructures for which the implementation of SP is often required in order to decrease the risk of flooding and avoid contaminant dispersion in the immediate environment (Birch et al. 2006; Hwang et al. 2019). This proximity with the road, however, exposes roadside SP plant communities to high levels of contaminants (nitrogen, metals, hydrocarbons, de-icing salts, etc.) that affect plant colonization, survival, and reproduction (Truscott et al. 2005; Khalid et al. 2006; Gülser and Erdogan 2008; Skultety and Matthews 2018). Roads have also been shown to have a detrimental impact on the plant community composition and diversity of natural wetlands (Findlay and Houlahan 1997; Findlay and Bourdages 2000; Avon et al. 2010), especially within 50 m of either side (Fakayode and Olu-Owolabi 2003; Gülser and Erdogan 2008; Khalid et al. 2018).

This study aims to determine whether roadside SP and natural wetlands in a North American context have similar plant communities, and how SP could be improved in order to harbour more natural plant communities and resemble natural wetlands more closely. Our investigation focused on the different habitats often found within such constructed environments. To achieve this objective, we measured the plant taxonomic alpha diversity of four different habitats: aquatic, wet littoral, dry littoral, and upper bank. We compared roadside SP to both roadside (less than 50 m away from a road) and remote (more than 50 m) reference wetlands. We compared these sites in terms of both alpha and beta diversity as well as community composition, looking at native, wetland obligate and facultative, exotic, and invasive species. We also explored the influence of local (e.g., design variables, water chemistry) and regional (e.g., landscape composition) factors on plant communities of SP. We predicted that 1) SP show higher alpha diversity and lower beta diversity than reference wetlands, due to the presence of drier, more terrestrial habitats; and that 2) SP resemble roadside wetlands more than remote ones.

Study area

We conducted our study along four roads located in southeastern Québec, Canada (Fig. 1) classified as intra-provincial highways with two to four lanes, depending on the segment. The annual average daily traffic ranged between 7000 cars (Highways 175 and 85) and 15 000 cars (Highways 367 and 73; MTQ 2018). The study area encompassed four bioclimatic domains (balsam fir-yellow birch; sugar maple-yellow birch; sugar maple-basswood; and balsam fir-white birch). For sites located north of the St. Lawrence River (Highways 175 and 367), mean annual temperatures vary from 0.5°C in the north to 4.7°C in the south, with mean annual precipitation of 1288 mm, of which 24% falls as snow. For sites located in the Highway 73 area, the mean annual temperature is 4.5°C, with mean annual precipitation of 1117 mm, of which 20% falls as snow. For sites along Highway 85, the mean annual temperature is 3.4°C, with mean annual precipitation of 1029 mm, of which 26% falls as snow (MELCC 2021).

Site selection

We first selected 174 potential stormwater pond (SP) sites from a database provided by the provincial transport agency, the Ministère des transports du Québec. We discarded all SP built after 2016 to ensure sufficient colonization by the local flora, as well as those located in urban areas, due to the absence of urban reference wetlands. Instead, we focussed on SP from the surrounding rural, mainly forested areas. From the remaining SP (28), we selected those situated at least 500 meters apart from each other, to limit spatial correlation. A total of 20 SP met these criteria, ranging in size from 0.14 to 1 ha (mean area: 0.46 ha). All 20 selected SP consisted of a circular or elongated body of open water surrounded by steep slopes (7 to 26%). Their bottom substrate consisted mainly of rockfill without an impervious membrane, and their shoreline had been enriched with 10 to 40 cm of organic soil. Banks from the 20 SP had been systematically hydroseeded with a mix of grasses, and some sites had been planted with herbs and shrubs (see Appendix A for list of species).

We paired two natural wetlands with each SP to serve as reference ecosystems. The first one was selected so as to be situated 50 meters or less from a paved road (hereafter roadside wetlands; RoW), and the other within 50 m to 1 km from a paved road (hereafter remote wetlands; ReW). Including both RoW and ReW allowed us to account for the effect of road disturbance on plant community composition and turnover between SP and reference wetlands. Selected reference wetlands corresponded to ponds surrounded by open vegetation. We only selected wetlands with a surface area of 1 ha or less, to be comparable to SP and avoid speciesarea bias. Overall, we sampled 60 sites: 20 from each type (SP, RoW, and ReW).

Vegetation sampling

We surveyed plants from June to August 2019, except for eight sites (located throughout the study region) that were surveyed at the end of July 2020. Sites surveyed before mid-July of 2019 were visited a second time during the season to validate species identification, since most species had not yet flowered at the initial visit. We divided the sites into three zones as homogenous as possible in terms of vegetation and noted the proportion of the site represented by each zone (Fig. 2). We placed a transect in the center of each zone, perpendicular to the shore and extending from the aquatic habitat to the upper bank. Along each transect, we sampled one plot from each of the four delineated habitats, namely: aquatic (maximum water depth: 1 m), wet littoral, dry littoral, and upper bank. We used rectangular plots of 5 m², and adapted length and width to the spatial structure of each habitat (plots varied from 1 m x 5 m to 2 m x 2,5 m). We identified all species within the plots and visually estimated their cover using six classes: <1%, 1–5%, 6–25%, 26–50%, 51–75%, and 76–100%. For each habitat on every site, mean species cover was calculated by using the median of each class, weighted using the spatial representativeness of the three zones. These four weighted mean cover values were averaged at the site level for part of the analyses.

Since SP were mowed during the summer, it was sometimes impossible to identify some grass species. In such cases, the observed plants were identified as "grass", encompassing the three species used for hydroseeding: Agrostis gigantea, Festuca rubra, and Poa pratensis. Consequently, all occurrences of these three species were pooled together in this category for all sites.

Local and regional factors

We measured the slope (%) of each transect with a clinometer and then averaged the values for the entire site We also measured water conductivity (µS/cm) and pH on a composite water sample taken at three locations across the pond surface. Landscape composition within a 1 km radius (i.e., forest, crops, and wetlands) was assessed using ArcGIS software (ESRI 2020). Geographical data was provided by Natural Resources Canada (forest areas), Financière Agricole du Québec (crop areas), as well as Ducks Unlimited and the provincial environment agency (Ministère de l'Environnement et de la Lute aux Changements Climatiques; wetland areas). Variables used for analyses are presented in Table 1.

Table 1

List of variables used for the analyses and number of sites (n) for which the variable was available.
Local factors		Regional factors
Variable	n	Variable	n
Slope (%)	60	Forest (m²)	60
Conductivity (µS/cm)	60	Crops (m²)	60
pH	60	Wetlands (m²)	60
Water level fluctuation (cm)	60
Age of SP (yr) ^a	20
Organic soil thickness (mm) ^a	13
Number of sown species^a	18
^aOnly available for SP

Information about SP construction was obtained from the provincial transport agency, but some data were missing. Available data included the age (available for n = 20 SP), pond bottom substrate (n = 11), organic soil thickness at the shoreline (n = 13), and a list of planted or sown species (n = 18), which consisted of herbaceous and shrub species ranging from wetland obligate to upland status. During SP construction, planting had been carried out on a small scale, covering only small portions of the SP and apart from the number of species planted, more precise information (e.g., the number and location of plants) was unavailable. As the information on pond substrate was missing for 45% of the SP, this factor could not be included in our analyses. Finally, water level fluctuation data was obtained using a time-lapse camera placed in front of a ruler installed in the open water on each site, and a photograph was taken every 24 hours between May 22 and September 9, 2019. Water level fluctuation corresponded to the difference between maximum and minimum water levels observed.

Statistical analyses

Taxonomic richness

We computed total taxonomic richness at each site as the number of distinct taxa found in all plots. Similarly, we assessed taxonomic richness for each habitat individually (aquatic, wet littoral, dry littoral, and upper bank) on each site. Performing an ANOVA on a linear model, we tested whether taxonomic richness differed between site types (SP, RoW, ReW), first, taking SP as a whole and second, testing each specific habitat separately. We verified that model residuals followed a normal distribution and displayed homogeneous variance (Shapiro-Wilk and Bartlett’s tests). When significant results were found, we conducted post hoc multiple comparisons using LSD tests. We adjusted p-values using Holm’s correction for multiple testing.

In addition, we evaluated whether the proportion of obligate wetland, facultative wetland, exotic, and invasive taxa (% of the total cover) differed between site types using Kruskal-Wallis nonparametric tests and performed multiple comparisons with Wilcoxon tests. Exotic and invasive species were analyzed separately, but all invasives were also exotic species. Wetland indicator status followed Bazoge et al. (2014) and the PLANTS Database (USDA and NRCS 2020), while species origin in Québec (native or exotic) followed VASCAN (Brouillet et al. 2020).

Beta diversity and species composition

Beta diversity for each type of site (SP, RoW, ReW) was calculated using the mean Hellinger distance of the sites to their respective group centroid. Specifically, we computed three site-by-species matrices using mean cover data and built site-by-site distance matrices using the Hellinger distance. We also analyzed differences in beta diversity between site types, using a distance-based permutation test for homogeneity of multivariate dispersions on a site-by-site distance matrix including all 60 sites (PERMDISP; Anderson et al. 2006) with 9 999 permutations. Finally, we conducted post hoc multiple comparisons using LSD tests. This was done for sites as a whole, as well as for each of the four habitats separately.

To detect a shift in species composition, we tested for location differences between centroids using PERMANOVA with pseudo-F ratios (9 999 permutations). Pairwise comparisons with Bonferroni corrections were made on site types to identify which ones differed. Because this test is sensitive to differences in multivariate dispersions, data visualization was used to support the interpretation of the statistical test. The differences in multivariate dispersion and composition were illustrated in principal coordinates analysis ordinations (PCoA).

Impact of local and regional factors on plant community composition

To assess differences in local variables between site types, we analyzed the slope, pH, and conductivity data by performing an ANOVA on a linear model. The factors associated with vegetation composition were then determined through a redundancy analysis (RDA) of the vegetation data constrained by all local and regional (landscape composition) variables, for all three site types. For the RDA, we removed rare species from the vegetation matrix (< 20%; 79 taxa remained) and applied Hellinger’s transformation. All explanatory variables were standardized, and the significance of the model was assessed using a permutation test with 9 999 randomized runs (Legendre and Legendre 2012).

To evaluate the specific influence of SP design on taxonomic composition, we only used data from the 20 SP for further analyses. Design variables included slope, water level fluctuation, SP age, thickness of organic soil, and number of sown species (Table 1). We calculated the mean ecological distance of each habitat of every SP to the corresponding habitats in the reference sites, RoW and ReW combined, using the site-by-site distance matrix from the beta diversity analyses. We then calculated the correlations and associated adjusted R² values between these distances and each of the aforementioned design variable.

All statistical analyses were performed using R 4.0.1 (R Core Team 2019). Analyses of variance were made with the Anova function from the “car” package (Fox et al. 2019). Shapiro-Wilk tests were done using the function shapiro.test, Bartlett tests with bartlett.test and Wilcoxon tests with wilcox.test, all from the “stats” package (R Core Team 2019). LSD tests were conducted using the LSD.test function and Kruskal-Wallis tests with the Kruskal function, both from the “agricolae” package (Mendiburu 2020). Hellinger distances were obtained with the vegdist function, multivariate dispersion analyses were done with betadisper, centroid position was measured with the adonis2 function, Hellinger transformations and standardizations were done with decostand, redundancy analyses with rda and permutational tests with the anova.cca function, all from the “vegan” package (Oksanen et al. 2019).

Taxonomic richness

We identified a total of 319 taxa on the 60 study sites: 207 in stormwater ponds (SP), 223 in roadside wetlands (RoW), and 200 in remote wetlands (ReW). Of these 319 taxa, 97 were wetland obligate and 79 were wetland facultative species, together representing 55% of the sampled flora. Moreover, 69 taxa (22%) were exotic species, among which 20 (6%) were also considered invasive (Appendix B). In SP, four of the ten most common taxa were exotic, and three were wetland indicators (Table 2). In both types of reference wetlands, however, the ten most frequent taxa were all native and, with the exception of Abies balsamea, wetland indicator species.

Table 2

Most common plant taxa found on the three types of sites. The frequency for each taxon (% sites where it was found) as well as their mean cover when present are indicated. Exotic species are indicated by a plus sign (+) and wetland indicator species are indicated in bold font. Taxonomy follows VASCAN (Brouillet et al. 2020)
Species	Frequency (%)	Mean cover (%)
Stormwater ponds
Solidago canadensis	100	19
Euthamia graminifolia	100	16
Vicia cracca⁺	90	16
Typha latifolia	80	31
Solidago rugosa	80	18
Scirpus atrocinctus	80	10
Leucanthemum vulgare⁺	80	6
Juncus effusus	80	8
Tussilago farfara⁺	75	26
Trifolium hybridum⁺	75	15
Roadside wetlands
Galium palustre	90	3
Calamagrostis canadensis	75	51
Spiraea alba var. latifolia	70	14
Lycopus uniflorus	70	5
Carex canescens	70	28
Scirpus microcarpus	65	31
Impatiens capensis	65	3
Fragaria virginiana	65	5
Euthamia graminifolia	65	7
Typha latifolia	60	38
Remote wetlands
Galium palustre	95	6
Calamagrostis canadensis	95	20
Scirpus atrocinctus	75	9
Carex canescens	70	7
Abies balsamea	70	3
Sparganium eurycarpum	65	7
Onoclea sensibilis	65	9
Juncus effusus	65	4
Impatiens capensis	65	5
Salix discolor	60	12

The mean taxa richness of SP sites was significantly higher than that of both types of reference ecosystems, between which it was similar (Fig. 3a). This higher richness of SP was mainly linked to the high richness of the SP dry littoral habitat (Fig. 3b). For other habitats, taxa richness was similar between site types (Fig. 3b).

Beta diversity and species composition

Taxonomic beta diversity differed significantly between SP and reference wetlands (F = 15.19; p < 0.001; Fig. 4). It was statistically higher in both types of reference wetlands, meaning that plant communities of SP were more homogeneous from site to site than those of reference wetlands. At the habitat level, beta diversity was similar between wetland types for the aquatic habitat but, again, was lower in SP than in reference wetlands for the three others (Fig. 5).

Taxonomic composition (i.e., distances between centroids) also differed significantly between SP and reference wetlands (F = 4.424; p < 0.001; Fig. 4). The two types of reference wetlands had similar species composition (overlapping ellipses and proximity of their two centroids). At the habitat level, plant species composition of the aquatic habitat of SP was similar to that of reference wetlands (similar centroids for the three groups; Fig. 5). Wet littoral species composition of the SP was significantly different from that of ReW, but not of RoW, which had an intermediate species composition. For the dry littoral and the upper bank, SP were clearly different from both RoW and ReW, which in turn had similar dry littoral but different upper bank plant species composition.

Obligate species cover was significantly lower in SP compared to RoW, but was similar to that of ReW (Fig. 6). Wetland facultative cover was significantly lower in SP than in both types of reference wetlands. Exotic and invasive species covers were both higher in SP than in reference wetlands. Even though the difference is not significant, RoW had mean exotic and invasive species covers at least double those of ReW.

Impact of local and regional factors on plant community composition

Variables included in the RDA analyses accounted for 21% of the total variance (Fig. 7). The first axis was strongly associated with local variables and clearly separated SP from reference wetlands. Stormwater ponds were characterized by higher pH and conductivity as well as steeper slopes (Fig. 8) and were associated with species identified as “grass” (Agrostis gigantea, Festuca rubra, and/or Poa pratensis), as well as Vicia cracca and Trifolium hybridum (Fig. 7). The second axis of the RDA was mostly related to landscape composition, and while significant, did not give any clear pattern, only slightly separating RoW and ReW, therefore explaining a limited portion of the total variance.

Mean ecological distance of SP to reference wetlands was correlated with three design variables, namely water level fluctuation, slope, and age (Fig. 9). Water level fluctuation was positively correlated to ecological distance in the aquatic habitat, meaning that SP with the least variation in water level across the season had aquatic communities more similar to those of reference wetlands. The slope was positively correlated to ecological distance in the wet littoral, indicating that gentler slopes supported wet littoral communities closer to those of reference wetlands. Finally, the age of the SP was negatively correlated to ecological distance in the dry littoral, indicating that dry littoral communities of SP became more similar to those of reference wetlands with time.

This study was designed to assess whether stormwater ponds (SP) are similar to wetlands in terms of taxonomic alpha and beta diversity, as well as community composition, and to evaluate the impact of local and regional factors on SP plant communities. Results revealed similarities between SP and wetlands, especially in the lower, wetter habitats. Moreover, water level fluctuation, slope, and age of SP influenced SP plant community composition.

Examining SP through the lens of specific habitats revealed similarities with wetlands through higher resolution, whereas previous studies mostly found differences (Reinartz and Warne 1993; Rooney et al. 2015; Kuntz et al. 2018; Perron and Pick 2020). Of the four habitats identified in this study, the two wetter habitats in SP exhibited a species composition similar to that in natural wetlands, especially roadside wetlands. The more terrestrial habitats were, however, quite different in terms of richness and composition. Stormwater ponds surveyed in this study could therefore be considered as small ponds surrounded by an extensive terrestrial bank.

The similarities between the aquatic and wet littoral habitats in SP and reference wetlands were correlated with two factors, water level fluctuations and slope. Higher fluctuations of the water level in SP increased their mean ecological distance from reference wetlands. Extended flooding can influence communities by two contrasting mechanisms: either by reducing the prevalence of upland species and promoting the diversity of wetland plants (Gathman et al. 2005; Drinkard et al. 2011), or by causing the loss of specialist wetland plants that require a specific hydroperiod or an intermediate water depth (Greenway et al. 2007). This leaves out space for colonization by invasive wetland plants that can withstand these fluctuations (Wei and Chow-Fraser 2006; Zhang et al. 2015; Sun et al. 2019; Bedell et al. 2021). The invasive P. australis subsp. australis, not yet widespread in the study region, can indeed withstand extreme fluctuations in water level (up to 120 cm; Hanslin and Saebo 2017). Thus, a stable water level will help prevent colonization by such species. This seemed to be the case in the studied SP, where mean water level fluctuation (10.8 cm) was comparable to that of reference wetlands (9.2 cm). On the other hand, slope was strongly correlated to ecological distance between SP and reference wetlands in the wet littoral. The slopes of SP were indeed much steeper (7 to 26%) than those of reference wetlands (0 to 17%). Stormwater ponds are usually designed with steep slopes to minimize their area for a certain volume of water retention. Moreover, while weaker slopes have sometimes been thought to favor invasive species establishment, no such relationship between invasive plants and slope was observed in our study (results not shown). This could also be due to the study region, where P. australis subsp. australis invasions are not widespread (Jodoin et al. 2007). These results concerning water level fluctuation and slope highlight the importance of SP design for the establishment of wetland plant communities.

In addition to differences in plant communities attributable to design factors, proximity to a road also exerted an influence on taxonomic composition of SP, more specifically in the wet littoral habitat. This was underlined by the fact that SP plant communities were similar to those of roadside wetlands, but not remote wetlands. Roads can impact wetlands through pollution as well as exotic and/or invasive species propagule pressure. Here, it seems that stormwater ponds were more vulnerable to the establishment of such species than roadside wetlands. Soil disturbance and low plant biomass during SP construction and time of establishment are known to favor invasion by exotic species (Davis and Froend 1999; Pearson et al. 2018). Moreover, many exotic species produce more seeds, and do so earlier in the season than native species, causing strong priority effects (Wilsey et al. 2014), which might explain their relative importance in SP (however, P. australis subsp. Australis produced seeds in late autumn and reproduces mostly vegetatively in the study region; Gervais et al. 1993, but see also Brisson et al. 2010).

The plant communities of the dry littoral and upper bank of SP were clearly different from those of the reference wetlands. Most of the dry area of SP was a terrestrial habitat unsuitable for wetland plant communities. However, there was a correlation between the age of the SP and the dry littoral plant communities: with time, dry littoral plant communities from SP became more similar to those of reference wetlands. Considering that it may take decades for plant communities to completely regenerate after restoration (Lebrija-Trejos and Bongers 2008; Bullock et al. 2011; Moreno-Mateos et al. 2012), succession processes are likely still taking place. Reference wetland dry littoral communities were characterized by a higher cover of shrubs and trees, at the expense of vines and forbs (results not shown).

The drier habitats of SP were characterized by grass species, sown to rapidly cover the soil and stabilize the banks, but still exhibited a higher proportion of exotic, as well as invasive plants. Planting shrubs or trees and reducing maintenance operations such as mowing could support the establishment of such taller plant species, which are found in reference wetlands, and bring heterogeneity, offering different microhabitats and eventually increasing beta diversity, as well as controlling for invasives (Lelong et al. 2009). Rather than being vegetated mainly with grass, this diversification of plant structure of the upper habitats could provide ecosystem services that extend beyond those of wetlands. As such, the two higher habitats could for example support pollinators through the introduction of flowering plants, thus offering further connectivity for the fauna (see for example Smith et al. 2019).

This study highlights the homogeneity of SP in terms of taxonomic composition, which mirrors findings in other studies (Reinartz and Warne 1993; Rooney et al. 2015; Kuntz et al. 2018; Perron and Pick 2020; Sinclair et al. 2020). Sinclair et al. (2020) identified two main explanatory factors, namely the choice of only a few similar species for pond construction and limited dispersion ability of species in an urban context. In our case, the homogeneity of SP could also be due to other factors, such as their recent construction, design homogeneity (mainly topography), high maintenance, and propagule pressure by roads.

This calls for a set of actions, the first of which could be the differentiation of SP through a variety of designs. Instead of a single “ideal” design, we should aim to develop a catalogue of options that could be tailored to specific regional needs in terms of plant diversity, wildlife habitat, and ecosystem services related to water. Native vegetation should be established as fast as possible in order to pre-empt invasion by exotic species. Maintenance operations such as mowing should be limited where possible, to allow natural processes of ecological succession. Other strategies to increase richness include seeding native species (Reinartz and Warne 1993; Balcombe et al. 2005; Mitsch et al. 2014), which would also limit colonization by unwanted species that use roads as dispersal corridors (Reinartz and Warne 1993), as well as increasing microtopographic heterogeneity by disking the soil (Moser et al. 2007). Finally, since the habitats that were found to be equivalent to reference wetlands were the two aquatic ones, which have a limited extent due to the strong slopes (Fig. 10), we also suggest that the perimeter of the littoral be increased by favoring more complex shorelines, increasing the perimeter-area ratio. Wetland perimeter length, more so than area, has an impact on species richness (Reinartz and Warne 1993).

In this study, we were able to characterize SP to a finer scale than usually reported in the literature, sampling different habitats from the aquatic to the upper bank and observing that the lower habitats in SP are indeed similar in some ways to those in natural wetlands. In investigating each of these habitats, we tested the impact of different variables associated with the SP design to determine the factors that could explain differences, and identified management improvements to foster the establishment of more natural communities. Although SP show extensive terrestrial banks, the lower levels should merit increased consideration by policy makers to increase their biotic value. Ponds, be they natural or man-made, have been shown to have a strong potential for conservation (Cégérhino et al. 2014). Keeping water level fluctuations to a minimum, lowering the slopes, enhancing the upper bank by promoting heterogeneity (by planting trees and shrubs) are the key strategies that were identified here, which concur with the conclusions of Rooney et al. (2015). Finally, complexifying the shoreline, keeping maintenance to a minimum, as well as promoting a diversity of SP designs, would be further means of enhancing beta diversity between SP.

Our study brings nuances to the existing literature: even if SP surveyed in this study were not comparable as a whole to remote natural wetlands, they did share similarities, having the potential to harbor wetland plant communities without being dominated by invasive or exotic species. These findings should encourage further research into how these green infrastructures could be valued, especially considering their ever-growing presence, and their importance in urban landscapes. It is important to remember, however, that this study was conducted outside of dense urban areas, and we believe that the higher disturbance experienced by urban SP could impact species composition of their wetter habitats.

Competing interests

The authors have no relevant financial or non-financial interests to disclose.

Funding

This work was supported by the Ministère des Transports du Québec (Grant number R803.1).

Author contributions

Conceptualization and methodology: P.-A. Bergeron D’Aoust, S. Pellerin, and M. Poulin; Formal analysis and investigation: P.-A. Bergeron D’Aoust and M. Vaillancourt; Writing – original draft: P.-A. Bergeron D’Aoust and M. Vaillancourt; Writing – review & editing: S. Pellerin and M. Poulin.

Acknowledgements

We would like to thank the Ministère des transports du Québec for their financial support, É. Bergeron de Pani, M. Mazerolle and M. Hayes for scientific advice and field assistance. We thank K. Grislis for linguistic revision and D. Bastien for taxonomic identifications.

Data availability

The datasets generated during the current study are available from the corresponding author on reasonable request.

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Are plant communities of roadside stormwater ponds similar to those found in natural wetlands?

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Abstract

Figures

Introduction

Methodology

Study area

Site selection

Vegetation sampling

Local and regional factors

Statistical analyses

Taxonomic richness

Beta diversity and species composition

Impact of local and regional factors on plant community composition

Results

Taxonomic richness

Beta diversity and species composition

Impact of local and regional factors on plant community composition

Discussion

Conclusion

Declarations

Competing interests

Funding

Author contributions

Acknowledgements

Data availability

References

Supplementary Files

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