Marine Environmental Research 105 (2015) 20e29

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Variation in rocky shore assemblages and abundances of key taxa along gradients of stormwater input Chloe M. Kinsella*, Tasman P. Crowe UCD School of Biology and Environmental Science and Earth Institute, University College Dublin, Belfield, Dublin 4, Ireland

a r t i c l e i n f o

a b s t r a c t

Article history: Received 4 November 2014 Received in revised form 21 January 2015 Accepted 23 January 2015 Available online 24 January 2015

Stormwater brings freshwater and terrestrially derived contaminants into coastal systems and is predicted to increase with climate change. This study aimed to characterise variation in rocky shore assemblages in relation to stormwater pollution. Intertidal assemblages were sampled in similar habitats at a range of distances (0 m, 10 m, 20 m, 60 m, and 100 m) from stormwater outfalls on three rocky shores north of Dublin. In general, taxon richness and algal cover increased after 20 m from a stormwater outfall. Limpet population structure and condition index showed no consistent patterns among shores. Assemblage structure at or near stormwater sites differed from that at sites 100 m away. These findings, ideally supplemented by experimental research, may be used to inform stormwater management and remediation approaches. © 2015 Elsevier Ltd. All rights reserved.

Keywords: Stormwater Marine biodiversity Assemblage structure Rocky shore Pollution

1. Introduction Society relies on marine ecosystems for a range of ecosystem services, such as provision of food, nutrient recycling and climate regulation (Millenium Ecosystem Assessment, 2003; TEEB, 2010; Liquete et al. 2013). Multiple anthropogenic stressors can alter the functioning of coastal ecosystems, reducing biodiversity and the provision of services to society (Johnston and Roberts, 2009; Bulling et al. 2010). Increased urbanization has led to an increase in a wide range of pollutants deposited on catchment surfaces which are transported with stormwater during wet weather periods and ultimately enter aquatic systems (Aryal et al. 2010). Significant changes are projected to occur in climate over this century, with an expected increase of 10e25% for Ireland's winter precipitation (McGrath et al. 2005). The generation of stormwater and its associated pollutants is determined by the level of precipitation that occurs (Patz et al. 2008), and is also affected by rainfall-related flooding (Dierkes et al. 2002). Stormwater is an important uncontrolled and unregulated source of pollution. The creation of stormwater pollutants in urban environments is complex and the pollutants arise from a large

* Corresponding author. E-mail addresses: [email protected] (C.M. Kinsella), tasman.crowe@ ucd.ie (T.P. Crowe). http://dx.doi.org/10.1016/j.marenvres.2015.01.003 0141-1136/© 2015 Elsevier Ltd. All rights reserved.

number of urban activities (Duncan, 1999). It can degrade water quality by introducing a combination of contaminants such as polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), heavy metals, freshwater, pesticides, sediment, nutrients, bacteria and sewerage (Makepeace et al. 1995). Stormwater can alter the quality, turbidity, salinity, temperature and pH of the water it enters (Corcoran et al. 2010) causing significant effects on marine biota (Pratt et al. 1981). The impact of stormwater pollutants on organisms depends on a number of factors such as total load of pollutants, their nature and concentration. Anthropogenic stressors such as this have the potential to alter the diversity and structure of natural assemblages. To date the ecological effects of stormwater run-off in marine ecosystems remains uncertain. Many stormwater studies have focused on the toxicity of stormwater on individual organisms (Schiff et al. 2003; Greenstein et al. 2004; Grapentine et al. 2008). Multiple interacting species in an assemblage serve as a better representation of an ecosystem as the contaminants may act as a stressor on any of the complex dynamics that affect assemblage integrity (Maher and Norris, 1990). A number of studies have explored the relationship between stormwater pollution and marine assemblage structure (Willemsen et al. 1990; Morrissey et al. 2003; Schiff and Bay, 2003; Ghedini et al. 2011) yet only weak biological effects have been observed. Many of these studies have looked at short term effects (i.e. single rainfall events). Further study is needed of the longer term changes associated with chronic

C.M. Kinsella, T.P. Crowe / Marine Environmental Research 105 (2015) 20e29

inputs of stormwater and its cumulative effects. Benthic communities provide a useful model for marine pollution assessment as they reflect not only conditions at the time of sampling but also conditions to which the community has previously been exposed (Reish, 1986). Some taxa, such as perennial algae and some grazing gastropods are particularly influential and may be sensitive to pollution (Borowitkza, 1972; Philips, 1977; Evans-White and Lamberti, 2009). Furthermore, the ratio of ephemeral to perennial algae can be used as an indicator of ecological status (Cusack et al. 2008) and it can be informative to characterise the effects on these groups of species. Changes in populations of these taxa would have potentially important indirect effects for the wider community and ecosystem processes (e.g. Menge, 1995; O'Connor and Crowe, 2005; Crowe et al. 2013). The aim of this study was to relate the distance from a stormwater outfall with the structure and taxon richness of rocky shore assemblages as well as with the abundance of selected taxa and with size structure and condition of limpets.

2. Materials and methods

21

dominated by Fucus serratus. This alga is a host to a diverse range of epibiota including molluscs, crustaceans and epiphytic algae (Boaden et al. 1975) and components of these assemblages have previously been found to be potential indicators of pollution (Atalah and Crowe, 2012). Intertidal assemblages of algae and invertebrates from the three rocky shores were compared to test whether patterns of assemblage structure matched current predictions about the effects of stormwater. As the spatial extent of the stormwater flows was not known, sampling was carried out using a ‘gradient’ design (Bayne et al. 1988; Wiens and Parker, 1995). Stormwater outfalls were located a minimum of 200 m apart on each shore. As the concentration of pollutants usually decreases with increasing distance from a point source (Bishop et al. 2002), sampling distances were chosen at a number of intervals between 0 m (source of pollution) and 100 m (maximum possible distance from pollution). Studies have shown that the effects of pollution have been localised and assemblages located 100 m from pollution serve as adequate controls (Terlizzi et al. 2002). Five distances from the stormwater outfall point were randomly selected on the lower mid shore (0 m, 10 m, 20 m, 60 m, 100 m), with five replicates at each distance (i.e. 25 replicates in total at each shore).

2.1. Study sites and sampling design Assemblages were sampled on three rocky shores in north County Dublin, Ireland: Malahide (53
260 N 42.4200 , 6
260 37.7400 W), Portmarnock (53
260 08.2000 , 6
070 17.7100 ) and Rush (53
310 02.5700, 6
05015.4800 ) (Fig. 1). All three shores featured man made shoreline stormwater outfall points that run into Dublin Bay. The three shores were classed as having high ecological status with water quality ranging from potentially eutrophic to unpolluted (McGarrigle et al. 2010). The shores comprised large slabs of limestone bedrock and each contained fucoid alga and associated fauna and had similar shore aspect, catchment activities (mixture of urban and low intensity agriculture), wave exposure, and background salinity (fully marine). All sampling took place on the lower mid shore, which was

2.2. Sampling Sampling was performed over 5 days in April 2012 during low tide. All sites were sampled during the same weather event, dry and cloudy. Preceding the survey there were no extreme precipitation events. This ensured that data collected were not affected by short term stormwater flows, but by any impacts that may have accumulated over time. Sampling consisted of four different methods to cover the range of species on the shore: Quadrat survey (large species), algal epibiota collection (organisms living on F. serratus), scrapings (small and cryptic species) and Patella vulgata collection (size and condition of key species).

Fig. 1. Location of stormwater outfalls (0 m ¼ closed triangle) and sampling sites (triangles; 0, 10, 20, 60 and 100 m distance) along the North Dublin coastline.

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Five 0.25 m2 quadrats were randomly placed on the lower mid-shore using random number tables and tape measures. Larger species were sampled in these quadrats and identified to appropriate taxonomic levels. Quadrats were subdivided into 25 squares and percentage cover of algae and number of individual macro-invertebrates in each quadrat were estimated using methodology based on Dethier et al. (1993). Canopy-forming species were sampled first, and then moved to one side to sample the understory. Due to overlapping algae, it was possible for total percentage cover to be greater than 100%. Five smaller quadrats (0.01 m2) were placed over F. serratus at each distance (smaller quadrats were placed outside the top left corner of the larger quadrat. If F. serratus was not present, the top right corner was selected). All F. serratus within the quadrat was removed, washed in a bucket of sea water for one minute and sieved (1 mm mesh) to remove any algal epibiota. The algae were then discarded and the organisms were fixed and preserved in 70% ethanol solution and returned to the laboratory for sorting and identification. Within the quadrat from which F. serratus had been removed, any remaining organisms (i.e. small and cryptic species) on the rock were scraped from the substratum, preserved in industrial methylated spirits and returned to the lab. Finally, 120 P. vulgata limpets were measured at each distance on each shore to generate size-frequency distributions. Twenty of these limpets were removed and transported back to the laboratory for analysis of condition index. Limpets were sampled by haphazardly placing quadrats on the shore and measuring the four limpets closest to the top left hand corner of the quadrat in each case. In the laboratory, algal epibiota and scrapings samples were placed under a microscope and all organisms were identified, counted and recorded. The P. vulgata samples were removed from the freezer and allowed to defrost for 24 h. The limpets were then individually weighed (total weight, shell weight and wet tissue weight) and measured (height and length). The limpet tissue was placed in an oven at 60
C for 48 h and then re-weighed (dry tissue weight). The condition index of each limpet was calculated as a percentage value using the following equation:

ðdry mass of soft tissues=shell weightÞ  100

multivariate analysis of variance (PERMANOVA) (Anderson, 2001) testing the null hypothesis of no difference in the structure and composition of assemblages between different distances from stormwater outfall point in different locations. Data were square root transformed to reduce influence of abundant species. Multivariate patterns were presented visually by non-metric multidimensional scaling (nMDS) ordination, using the BrayeCurtis similarity measure (Clarke, 1993). Where significant differences were found, pair-wise tests were done to investigate how levels of the factor ‘Distance’ differed. The SIMPER (‘‘similarity of percentages’’) (Clarke, 1993) routine was used to identify the taxa that made the greatest contribution to any differences among distances and locations identified in the NMDS plots and PERMANOVA tests (Clarke and Warwick, 1994). All multivariate analyses were done using PRIMER-E v6 software package (Primer-E). 3. Results In total, 112 taxa were identified (Appendix 1). 105 were distinct species, three were identified to genera and the remaining four taxa were aggregated at higher taxonomic levels (e.g. Phylum Nematoda). There were five taxa of green algae, eight brown algae and 16 red algae. There were 9 separate taxa of worms, 30 molluscs, 25 arthropods, nine cnidarians, one porifera, one fish, one terrestrial insect and one bryozoan. 3.1. Taxon richness and abundance of selected taxa Taxon richness increased from 10 to 60 m on two of three shores. At Malahide, taxon richness increased from 15.6 to 22.8 (Fig. 2, Table 1, SNK procedure). At Rush, an increase from 17 to 29.2 was recorded from 10 to 100 m (Fig. 2, Table 1, SNK procedure). There was no significant change in taxon richness at Portmarnock. Total algal percentage cover (comprising of species such as F. serratus, Chondrus crispus and Chorda filum) increased from 10 to 60 m, or 10e100 m on all three shores. At Malahide there was an increase in cover from 19.6 to 92.6 % from 10 to 60 m, at Portmarnock there was an increase from 43.4% to 106.2 % from 10 to 100 m, and at Rush there was an increase from 72 to 127.8 % from 10 to 100 m (Fig. 3, Table 1, SNK procedure). The percentage cover of ephemeral algae, such as Ectocarpus sp. and Cladophora rupestris, increased with increasing distance from the stormwater outfall on two of three shores (Fig. 4, Table 1, SNK

2.3. Data analyses Univariate and multivariate analyses were used to test and characterise the relationship between stormwater pollution and rocky shore assemblages. For statistical analysis, the data collected for large species, small and cryptic species and algal epibiota were combined. Differences in taxon richness, algal percentage cover and limpet condition index were analysed using a two-factor ANOVA. Factors were ‘Shore’ (random, 3 levels, Malahide, Portmarnock, Rush) and ‘Distance’ (random, 5 levels, 0 m, 10 m, 20 m, 60 m, 100 m). Prior to all ANOVAs, the assumption of homogeneity of variances was tested using Cochran's test. Where significant differences were found (p < 0.05), post-hoc tests (SNK test) of means were carried out. All ANOVAs were done using GMAV5 for Windows (Underwood et al. 1998). Size-frequency distributions of P. vulgata collected at different distances from stormwater outfalls at each site were compared with KolmogoroveSmirnov (KeS) tests (Sokal and Rohlf, 1969). Limpets collected at 0 m and 10 m distances were combined into putatively polluted populations and limpets collected at 60 m and 100 m were combined into putatively unpolluted populations for comparison. The same analytical structure was used in permutational

Fig. 2. Mean taxon richness from 0 to 100 m at each of the three shores (±S.E., n ¼ 5). * denotes significantly different from 0 m. y denotes significantly different from 10 m.

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23

Table 1 Analysis of variance to determine the distribution of taxon richness and percentage algal cover at distances from stormwater outfall. Cochran's C-test was not significant for all variables. Bold figures are statistically significant (P < 0.05). Source

df

Taxon richness

% Algal cover

% Cover of ephemeral algae

MS

F

MS

F

MS

F

MS

F

MS

F

MS

F

Shore (Sh) Distance (Di) Sh x Di Residual

2 4 8 60

103.48 103.65 25.25 11.07

4.1 4.1 2.8

35751.1 7643.1 1635.3 702.6

21.9 4.7 2.33

605.43 267.40 191.60 63.07

3.16 1.40 3.04

2699.21 1193.29 370.25 91.6

7.29 3.22 4.04

1679.85 120.69 236.69 140.47

7.10 0.51 1.69

161.76 73.12 61.11 16.92

2.65 1.20 3.61

Fig. 3. Mean % cover of algae from 0 to 100 m at each of the three shores (±S.E., n ¼ 5). * denotes significantly different from 0 m. y denotes significantly different from 10 m.

procedure). In Malahide the cover of ephemeral algae increased from 1 to 13.6 % from 10 to 100 m. In Rush, the cover increased from 9.4 to 26.4 % from 10 to 100 m. The percentage cover of perennial algae increased further away from the stormwater at two shores but not at Malahide. At Portmarnock, cover increased from 10.4 to 37.6 % from 10 to 100 m (Fig. 5, Table 1, SNK procedure). At Rush, cover increased from 7.8 to 36.2 % from 10 to 100 m (Fig. 5, Table 1, SNK procedure).

Fig. 4. Percentage cover of ephemeral from 0 to 100 m at each of the three shores (±S.E., n ¼ 5). * denotes significantly different from 0 m. y denotes significantly different from 10 m.

% Cover of perennial algae

Abundance of limpets

Condition index

Fig. 5. Percentage cover of perennial algae from 0 to 100 m at each of the three shores (±S.E., n ¼ 5). y denotes significantly different from 10 m.

The abundance of P. vulgata limpets did not vary significantly from 0 to 100 m (Fig. 6, Table 1). Limpet condition index increased from 12.8 to 17 from 0 to 60 m at Malahide (Fig. 7, Table 1, SNK procedure). On the other two shores, condition index decreased from 10 to 100 m. At Portmarnock, condition index decreased from 13.9 to 10.1, and from 17.1 to 13 at Rush (Fig. 7, Table 1, SNK procedure). The size frequency distribution of limpets differed significantly between sites near to stormwater input(0 and 10 m) and sites more distant from stormwater input (60 and 100 m) on all three shores (Figs. 8 and 9, P < 0.01, KolmogoroveSmirnov test). At Portmarnock and Rush, there was a tendency for limpet

Fig. 6. Abundance (A) of the limpet Patella vulgata from 0 to 100 m at each of the three shores (±S.E., n ¼ 5).

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C.M. Kinsella, T.P. Crowe / Marine Environmental Research 105 (2015) 20e29

stormwater. Of these N. lapillus tended to be more abundant closer to the outfalls and L. littorea and Lithothamnia sp. tended to be more abundant at greater distances from them. For each shore, certain species were absent at 0 and 10 m and present at greater distances. At Malahide, the algae Cystoclonium purpureum, Ectocarpus sp. and Chondrus crispis were all absent 0 m from the outfall but present 100 m from it. At Portmarnock, Lithothamnia sp., Littorina obtusata and Littorina mariae occurred in reduced quantities at 10 m in comparison to 100 m. At Rush, the alga Plocamium cartilagineum was absent at 0 m, and Gibbula umbilicalus (Gastropods), Semibalanus balanoides (barnacles), and Polysiphonia sp. (an alga)were all absent at 0 and 10 m, but present at 100 m.

4. Discussion

Fig. 7. Condition index of the limpet Patella vulgata from 0 to 100 m at each of the three shores (±S.E., n ¼ 5). * denotes significantly different from 0 m. y denotes significantly different from 10 m.

populations removed from stormwater to be characterised by larger average size, and for populations near to stormwater to contain smaller limpets on average. At Malahide, there was no clear trend in limpet size with distance from the stormwater outfall. 3.2. Multivariate community structure The community structure was significantly different between 0 and 100 m and 10 and 100 m on all three shores (Fig. 10, Tables 2 and 3). SIMPER analysis revealed that the gastropod Nucella lapillus, P. vulgata, and Littorina littorea, the bivalve Mytilus edulis and encrusting algae Lithothamnia sp.contributed most to dissimilarities between assemblages at different distances from the source of

Stormwater is a source of multiple stressors in marine environments. This study has revealed a relationship between distance from stormwater and rocky shore assemblage structure, which suggests an impact of the stormwater. Differences in taxon richness, percentage algal cover, size of P. vulgata limpets and assemblage structure occurred between assemblages close to a stormwater outfall (less than 20 m away), and assemblages located 60e100 m from the outfall. In some cases, diversity was relatively high at the outfall (0 m distance) compared to 10 m distance from it. The low biodiversity observed at 10 m on all shores suggests that the stormwater may be transported away from the immediate point of outfall due to local hydrodynamic effects (e.g. eddies). Although the impact of stormwater on receiving water quality and the physical environment have been abundantly reported (Bay et al. 2003; Schiff and Bay, 2003; Zgheib et al. 2011), detection of ecological impacts of stormwater has proven difficult (Roberts et al. 2007; Cox and Foster, 2013; Cox et al. 2013). In this study, assemblage structure at all three shores showed significant differences between sites near to stormwater input and sites more distant from stormwater input. Several authors have demonstrated a reduction

Fig. 8. Size frequency distribution of Patella vulgata limpets.

C.M. Kinsella, T.P. Crowe / Marine Environmental Research 105 (2015) 20e29

25

Fig. 9. Cumulative Fraction Plots for Malahide, Portmarnock and Rush. The broken line represents limpets collected at 0 and 10 m from outfalls (close to stormwater pollution). The solid line represents limpets collected at 60 and 100 m from outfalls (removed from stormwater pollution).

Fig. 10. Non multidimensional scaling (nMDS) representations of ranked dissimilarities between assemblages from distances at each shore. The legend displayed on the top corresponds to the nMDS plots for Malahide, Portmarnock and Rush. The bottom legend corresponds to the nMDS plot illustrating all shores.

Table 2 Permutational multivariate analysis of variance (PERMANOVA) of assemblage structure based on all taxa collected using all sampling approaches used at varying distances from stormwater outfalls. Terms significant at a ¼ 0.05 are in bold. Source

df SS

MS

Pseudo- P(permutations) Unique F permutations

Shore (Sh) 2 21898 10949 5.74 Distance 4 9999.1 2499.8 1.31 (Di) Sh x Di 8 15261 1907.6 2.26 Residual 60 50728 845.46 Total 74 97886

0.00 0.20

9929 9917

0.00

9823

of species richness in polluted marine environments (e.g. Stark et al. 2003; Fraschetti et al. 2006; Johnston and Roberts, 2009; O'Gorman et al. 2012). In the current study, the biota close to the

Table 3 Results of PERMANOVA pair-wise tests for assemblages at different distances at all three shores. Each row represents the comparison of assemblages at two distances from the stormwater outfall-shown in the first column, separated by commas. Terms significant at a ¼ 0.05 are in bold. Distances (metres)

0, 10 0, 20 0, 60 0, 100 10, 20 10, 60 10, 100 20, 60 20, 100 60, 100

Malahide

Portmarnock

Rush

t

P Value

t

P Value

t

P Value

1.17 1.27 1.51 1.53 1.25 1.71 1.66 1.50 1.55 1.40

0.20 0.10 0.02 0.01 0.08 0.01 0.01 0.02 0.01 0.03

1.25 1.51 1.30 1.51 1.50 1.65 1.88 2.05 2.00 1.82

0.1 0.01 0.06 0.01 0.05 0.01 0.01 0.01 0.01 0.02

1.89 1.46 1.85 1.52 1.48 1.98 1.70 1.45 1.42 1.46

0.01 0.02 0.01 0.01 0.05 0.01 0.01 0.02 0.01 0.01

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C.M. Kinsella, T.P. Crowe / Marine Environmental Research 105 (2015) 20e29

outfalls was generally less diverse than at sites that further from the outfalls. Taxon richness was lowest between 0 and 20 m from a stormwater outfall and highest after 20 m, with effects generally negated after 60 m. The lowest percentage cover of both perennial and ephemeral algae was recorded at 10 m for all shores. Although some studies (Diez et al. 2009) have reported lower algal cover close to the source of pollution, many studies have reported the proliferation of ephemeral algae in areas associated with pollution (Soltan et al. 2001; Barille-Boyer et al. 2004). An increase in ephemerals has been linked to direct enrichment by nutrients (Borowitkza, 1972) or a decrease in the number of grazers. In this study, grazers such as P. vulgata and Littorina gastropods were not reduced at sites close to stormwater pollution, so it is possible that the stormwater contained pollutants toxic to algae, such as heavy metals, and this reduced the cover of both perennial and ephemeral algae. Several studies have found shores polluted with nutrients and metals contain decreased richness of perennial algae (Farina and Castilla, 2001; Soltan et al. 2001). As perennial macroalgae are the major primary producers of many temperate rocky shores (Mann, 2009), a decrease in cover may cause a significant ecological disturbance. Patterns of variation in lengths and condition indices of limpets on different shores in the current study were variable. Lengths of the limpet P. vulgata significantly increased from 0 to 100 m in all three shores, suggesting that growth rate may be negatively impacted by stormwater or that limpets close to the sources of stormwater tend to suffer mortality before growing to full size. At Malahide, limpet condition was suppressed at 0, 10 and 20 m, which is consistent with studies indicating that stormwater can decrease the condition of molluscs (e.g. Mubiana et al. 2006). On the other hand, at Portmarnock and Rush, condition decreased between 10 and 100 m. Some studies have found that limpet condition can increase in areas of anthropogenic input, perhaps in association with increased concentrations of nutrients (Schone et al. 2005), and the resultant productivity of ephemeral algae and microbial films, upon which limpets feed (Crump et al. 2003). However, in this study, ephemeral algae did not increase in the proximity of the stormwater pollution, and length increased with increasing distance from the stormwater outfall. Patellid limpets are important herbivores on European Atlantic rocky shores, controlling the abundance of algae by their grazing activities (O'Connor and Crowe, 2005; Coleman et al. 2006; Davies et al. 2007). Even without changes in abundance, changes in limpet condition and size could have a range of indirect effects on rocky shore ecosystems, altering its diversity and functioning (as in Jochum et al. 2012). No species were consistently responsible for the difference in assemblage structure. Benthic diversity is often low in areas of pollution as a few opportunistic species tend to become dominant in the polluted zone (Borowitkza, 1972; Simboura et al. 1995), but this was not the case in the current study. SIMPER analysis suggested that some species were particularly sensitive to direct or indirect effects of stormwater pollution, others were apparently resistant and the patterns of variation along gradients of stormwater influence of some species varied among shores. Some taxa were found in equal abundance at distances near to and removed from the stormwater input. The abundance of Nereis worms, Chthamalus montaguii barnacles and the algae C. filum remained similar at all the distances from stormwater. Certain species such as M. edulis, and Littorina saxatilis were more abundant close to stormwater outfalls (0 and 10 m) while species such as Chondrus cripis, Lithothamnia sp. and Polysiphonia sp., which may be sensitive to stormwater and any contaminants it may contain, were more abundant at the sites further from the stormwater outfalls (60 and

100 m). In most cases, the apparent impact of stormwater in the current study extended only to between 20 and 60 m from stormwater outfalls. Although the distances over which stormwater may spread could increase during heavy rainfall events, any lasting effects would be detected in this survey, which effectively sought patterns associated with long term cumulative exposure to stormwater rather than short term, possibly transient responses immediately following a storm (as was the case, for example in Roberts et al. 2007) The results of this study suggest that the assemblages positioned further than 60 m from outfalls in areas like those studied here are less likely to be impacted by stormwater. The kinds of changes in diversity and assemblage structure reported here have been linked with changes in the functioning and productivity of ecosystems (Cameron, 2002; Naeem, 2002; Hooper et al. 2005; Stachowicz et al. 2007; Hooper et al. 2012). Local extinction of species is an important conservation concern, and is not readily reversed. For example, Schiel (2006) found that fucoid species have no functional equivalents in their areas of dominance on rocky shores and are the autogenic engineers on which most other species in their communities rely. Fucoids, among other species such as P. vulgata are key species whose relationship with stormwater input must be understood if the functioning of these areas is to be managed effectively. This loss of diversity may result in reduced ecosystem functioning, impacting a significant source of detrital material that underpins coastal food webs (Whittaker, 1975; Raffaelli and Hawkins, 1996). Stormwater from urban or agricultural catchments is generally a cocktail of anthropogenic pollutants, nutrients and freshwater (Eriksson et al. 2007). The causes of its effects may not be easy to disentangle as different components can modify each other's effects, either in the water column or in the ecosystem (e.g. Lyons et al. in press). The complex results described above could arise because different species may be responding positively or negatively to nutrients, pollutants or salinity or interactive effects of multiple components, or may be affected indirectly by effects on other taxa. The present study provides evidence of a correlation between distance from stormwater pollution and assemblage structure. To establish a causal link between stormwater and the patterns documented here and to identify which components of stormwater are most influential, experimental research is needed. The evidence presented here suggests that there is a limited footprint of individual stormwater outfalls (approximately 20 m and apparently no greater than 60 m along the coast). If this is the case, it can help to inform decisions about the management of multiple activities in coastal areas, to minimise overlap or overall detrimental effects, for example via marine spatial planning. [Ideally, further work would also include control sites at greater distances from stormwater, but in the current study system, stormwater outfalls were generally no more than 200 m apart and no more remote control sites could be found that were comparable. Evidence presented by Terlizzi et al. (2002) suggests that point sources input to moderately exposed rocky shores like these ted to have dissipated within 100 m]. Stormwater is a widespread chronic source of terrestrial input to coastal ecosystems. As precipitations and the frequency of extreme events increase due to climate change, so too will the quantity of stormwater run-off. This study has shown that rocky shore assemblages and abundances of key taxa vary along gradients of proximity to stormwater input. Further work is needed to establish whether there is a causal link between stormwater and the change in assemblage structure documented here and if so, to identify which components of stormwater are most detrimental. In this

C.M. Kinsella, T.P. Crowe / Marine Environmental Research 105 (2015) 20e29

Doctoral Studies Programme, funded by the Higher Education Authority (HEA) through the Programme for Research at Third Level Institutions, Cycle 5 (PRTLI-5) and is co-funded by the European Regional Development Fund (ERDF).

way, management efforts to reduce impacts can be appropriately targeted. Acknowledgements We would like to thank Jen Coughlan, Edward Casey, Maria Benson, Erin Gleeson, Thea Kinsella, Fingal County Council, and colleagues in the MARBEE research group, UCD Earth Institute, and UCD School of Biology and Environmental Sciences. The work was funded as part of the Earth and Natural Sciences

Taxon

Ephemeral

Algae

Perennial

Annelida

Polychaeta

Arthropoda

Appendix 1. Table of taxa identified in survey and the percentage cover (for algae) or presence/absence (for fauna) at each distance on each shore. Classification of ephemeral and perennial algae based on literature research and information collated on marlin.ac.uk

Malahide

Algae

Chaetomorpha linum Dictyosiphon foeniculaceus Gracilaria verrucosa Ceramium rubrum Cladophora rupestris Cystoclonium purpureum Ectocarpus sp. Nemalion helminthoides Leathesia difformis Plocamium cartilagineum Polysiphonia sp. Ptilota plumosa Seirospora interrupta Spongomorpha arcta Ulva compressa Ulva intestinalis Ulva lactuca Total cover of ephemeral algae Ahnfeltia plicata Catenella caespitosa Chondrus crispis Chorda filum Corallina officinalis Cryptopleura ramose Desmarestia ligulata Encrusting coraline algae Fucus serratus Fucus vesiculosis Gelidium pusillum Laurencia hybrid Lithothamnia sp. Lomentaria articulata Mastocarpus stellatus Osmundea pinnatifida Pelvetia canaliculata Total cover of perennial algae Total cover of all algae Capitella capitata Eteone picta Magelona mirabilis Nereis fucata Nereis pelagica Pomatoceros triqueter Sabellidae sp Spirorbis spirorbis Apherusa jurinei Apohyale prevostii Balanus balanus Carabidae (Terrerstrial) Carcinus maenas Chthamalus montagui Crab zoea Dexamine spinosa Diogenes pugilator Galathea intermedia Gammarus chevreuxi

27

Portmarnock

Rush

0

10

20

60

100 0

10

20

60

100

0

10

20

60

100

0.2 0 0 0.4 0 0 0 0 0 0.2 0.8 0 0 0 0 0 0.4 2 0 0 0 1.4 0.6 0 0 0.2 24.6 0 0 0 6 0.2 0 0.6 0 33.6 35.6 e þ e þ e e e e e þ e e e þ e þ e e e

0 0 0 0.2 0 0 0.4 0 0 0.2 0 0 0 0 0 0 0.2 1 0 0 0 0.2 0.2 0 0 0 10.8 0 0 0.8 5.8 0 0 0.6 0.2 18.6 19.6 e e e e e e e e þ þ e e e þ e þ e e e

0 0 0 0.4 0 0 0 0 0 0.2 0.2 0 0 0 0 0 0 0.8 0 0 0.2 1.4 1.4 0 0 0.2 17.4 0 0 0.4 11.2 0.2 0 0.2 0 32.6 33.4 e e e e e þ e þ þ e e e e þ e þ e e e

0 0 0 7.2 0.2 0.2 1 0 0 0.6 0 0.2 0 0 1.8 0 2.4 13.6 0 0 0 0.8 0.2 0.4 0 0 58 0 0 0.4 14.8 3.4 0 0.4 0.6 79 92.6 e e e e e e þ þ þ e e e þ þ þ þ e e e

0 0 0 3.4 0.4 2.2 1.6 0 0 0.2 0 0 0 0 0.2 0.2 5.4 13.6 0 0 1.2 1.2 0.2 0 0 0.8 10.6 0 0 0 1.4 0.6 0 0.2 0 16.2 29.8 e e e þ þ þ þ e e e e e þ þ þ þ e þ e

0 0 0 0.2 0 1.4 0.4 0 0 0.2 0.6 0 0 0 0 0 0.2 3 0 0 0.6 1.8 0.2 0 0 0 30 0 0 0 0.4 0.4 0 4.8 2.2 40.4 43.4 e e e e e þ e þ e e þ e e þ e þ e e e

0 0.6 0 8.2 0 1.4 0.4 0 0.4 0.2 0.2 0 0 0.2 5.2 0 2 18.8 0 0 0.2 1.6 0 0 0 0 40 0 0 0.4 4.8 0.4 0 5.4 0.2 53 71.8 e e e e e e e þ e e þ e e þ e þ þ e e

0 0 0 0 1.6 1 0.2 0 0 0.2 0 0 0 0 1.2 0 0 4.2 0 0 0.4 10.2 0.2 0 0 0.8 45.8 0 0 0.2 8.6 0 0 8.4 3.2 77.8 82 e e e e e þ e e e e e e e þ þ þ e þ e

0 0 0 0.2 0.6 2.4 1 0 0 0 0.2 0 0 0.6 1 0.2 0 6.2 0.2 0 2.6 1.4 0.2 0 0.2 0 62.4 0 0 0.6 20.2 1.6 0 10 0.6 100 106.2 e e e e e e e e e þ e e þ þ þ þ e þ e

0 0 0 2.8 7.2 4.2 0.2 0 0 0 0 0 0 0.2 3.2 0 3.6 21.4 0 0 6.6 0.8 1.2 0 0 1.6 82.4 0 0 0 5.8 0.8 0.2 17.8 1 118.2 139.6 e e e e e e e þ e e e e þ þ þ þ þ e e

0 0 0 3.6 1.6 0.4 0.2 0 0 0.2 0 0.2 0 0.2 0.4 0 2.6 9.4 0 0 0.2 0 2.8 0 0 0 54.8 0 0 0 0 0.6 0 4.2 0 62.6 72 þ e e þ þ e e þ e e e e e þ þ þ þ e e

0 0 0 0.4 4 0.4 0.8 0.2 0 1 0.2 0 0 0.8 4.6 0 0.2 12.6 0 0 2.6 0 6.8 0 0 0.4 56.2 0 0 0 13 2.6 0.4 10.8 0 92.8 105.4 e e þ e e e e þ e þ e þ e þ þ þ e e e

0 0 0 0.4 4 0.4 0.8 0.2 0 1 0.2 0 0 0.8 4.6 0 0.2 12.6 0 0.4 0.2 0 1.6 0 0 0.6 83.4 0 0 0 24 0.6 0 17.6 1 129.4 142 e e e þ þ þ þ þ e e e e þ þ e þ e e e

0.4 0 0.2 0.8 15.2 1 0.6 0.2 0 0.8 1.6 0 0 0.2 3.4 0 2 26.4 0 0 6.4 0.6 1.8 0 0 0.2 65.2 0.4 0.2 0 11.2 0 0.2 11.6 3.6 101.4 127.8 e e e e e þ þ þ þ þ e e þ þ e þ þ e þ

0 0 0 1 0 2.4 0 0.2 0 0.4 0 0 0.2 0 0.4 0 0.2 4.8 0 0 2 2.4 0.8 0 0.2 0.2 52.2 0 0.2 0.2 0.8 1.6 0.2 11 2 73.8 78.6 e e e e e þ e þ þ e e e e þ þ þ e e e

(continued on next page)

28

C.M. Kinsella, T.P. Crowe / Marine Environmental Research 105 (2015) 20e29

(continued ) Taxon

Bryozoa Chordata Cnidaria

Mollusca

Nematoda Porifera Taxon richness (fauna and flora)

Malahide

Gammarus duebeni Gammarus locusta Idotea chelipes Idotea granulosa Idotea neglecta Idotea pelagica Jaera nordmanni Leucothoe spinicarpa Microdeutopus gryllotalpa Orchestia gammarellus Pagurus prideaux Palaemon adspersus Processa canaliculata Semibalanus balanoides Xantho incisus Bryozoan Actinopterygii Limanda limanda Actinia equina Amphisbetia operculata Dynamena pumila Halecium halecium Obelia dichotoma Obelia geniculata Plumularia setacea Sertularella polyzonias Tubularia indivisa Cerithiopsis tubercularis Cingula trifasciata Epilepton clarkiae Gibbula cineraria Gibbula pennanti Gibbula umbilicalis Hinia incrassata Lacuna pallidula Lacuna parva Lacuna vincta Lamellaria perspicua Lasaea adansoni Lepton squamosum Littorina littorea Littorina mariae Littorina neglecta Littorina obtusata Littorina rudis Littorina saxatilis Mytilus edulis Nucella lapillus Odostomia conoidea Partulida spiralis Patella vulgata Raphitoma linearis Rissoa parva Rissoella opalina Skenea serpuloides Skeneopsis planorbis Trophon truncatus Nematode Halichondria panicea

References Anderson, M.J., 2001. A new method for non-parametric multivariate analysis of variance. Austral Ecol. 26, 32e46. Aryal, R., Vigneswaran, S., Kandasamy, J., Naidu, R., 2010. Urban stormwater quality and treatment. Korean J. Chem. Eng. 27, 1343e1359. Atalah, J., Crowe, T.P., 2012. Nutrient enrichment and variation in community structure and variation in rocky shores: the potential of molluscan assemblages for biomonitoring. Estuar. Coast. Shelf Sci. 99, 162e170. Barille-Boyer, A.L., Gruet, Y., Barille, L., Harin, N., 2004. Temporal changes in community structure of tide pools following the “Erika” oil spill. Aquat. Living Resour. 17, 323e328.

Portmarnock

Rush

0

10

20

60

100 0

10

20

60

100

0

10

20

60

100

e e e þ e e e e e þ e e e þ e þ e þ e e e þ e e þ e e e þ e e e e e e e e e e þ þ þ þ e þ þ þ e e þ e e e e e þ þ þ 17

þ e e þ e e e e e þ e e e þ e e e þ e e e e e þ e e e e þ e e e e e e e e e e þ þ þ þ þ þ þ þ e e þ e þ e e e e þ e 15.6

þ e e þ e e e e e þ e e e þ e þ þ þ e e e þ þ e þ e e e e e e e e þ e e e þ e þ þ þ e e þ þ þ e e þ e þ e e e e e þ 17.6

þ e e þ e þ e e e þ e e e þ e þ e þ e e e e e þ þ e e e e e e e e e þ e þ e e þ þ e þ e þ þ þ e e þ e e e e e e þ þ 22.8

e e e þ e þ þ e e þ e e e þ e þ e þ e þ þ þ e e þ e e e þ e e þ e e e e e e e þ þ e þ e e þ þ e e þ e e e e e e e e 20.2

þ e þ þ e e e e e e e e e þ e þ e þ e e e e e e þ þ e e e e þ e e e þ e e e e þ þ e þ e þ þ þ e e þ e e e e e e e þ 17.8

e e e þ e e þ e e þ e e e þ e e e e e e e þ e þ þ e e e e e e e e e e e e e e þ e e þ e e þ þ e e þ e þ e e e e þ e 18.6

e þ e e e e e e e e e e e þ e þ e þ e e e e e e þ e e e e e e þ e e þ e e e e þ þ e þ e þ þ þ e e þ þ þ e e e e þ e 19.4

e e e þ e e e e þ e e e e þ e þ e e e þ e e e e þ e e e e e e e e e þ e e e e þ þ e þ e e þ þ e e þ e e e e e e e þ 21

e e e e e þ e e e e e e e e e e e þ e e e þ e þ þ e e e e e e e e e e e e e e þ þ e þ e e þ þ e e þ e þ e e e e e e 19.6

e e e þ e e þ e þ e e e e e e e e þ e e e e e e þ e e e e e e e e þ e þ e e e þ þ e þ e e þ þ e e þ e þ e e e þ e e 17

þ e e þ e þ e e e e e e þ þ e þ e þ þ e þ e e e þ e e e e e e e e þ þ e e e e þ þ þ þ e þ þ þ e e þ e e þ e þ e þ e 22.8

e e e þ þ e e e e e e e e þ þ þ þ þ e e þ þ e e þ e e e e e e e e þ e e e e e þ þ þ þ e e þ þ e e þ e þ e e e e þ þ 23.6

þ þ e þ e þ e þ e e þ þ e þ e þ e þ e þ þ e e þ þ e þ e e e e þ þ þ þ e e e þ þ þ e þ e þ þ þ þ þ þ e þ e þ þ e þ þ 29.2

e þ þ þ e þ e þ e e e e e þ e e e þ e e e e e e þ e e þ e þ e þ e e e e e e e þ þ þ þ e e þ þ e e þ e e e e e e e e 19.6

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