Meiofauna and its sedimentary environment as an integrated indication of anthropogenic disturbance to sandy beach ecosystems.

Marine Pollution Bulletin xxx (2014) xxx–xxx

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Marine Pollution Bulletin journal homepage: www.elsevier.com/locate/marpolbul

Meiofauna and its sedimentary environment as an integrated indication of anthropogenic disturbance to sandy beach ecosystems Xinyu Sun, Hong Zhou ⇑, Er Hua, Shuhui Xu, Bingqing Cong, Zhinan Zhang College of Marine Life Science, Ocean University of China, 5 Yushan Road, Qingdao 266003, China

a r t i c l e

i n f o

Article history: Available online xxxx Keywords: Sandy beach Meiofauna Anthropogenic disturbance Nematode/Copepod index Principal components analysis

a b s t r a c t The accuracy and applicability of the Nematode/Copepod index (N/C) in monitoring the effects of environmental disturbances is controversial. In this study, we used an integrated approach that includes both meiofauna and the sedimentary environment to demonstrate a tourism-induced disturbance gradient among sampled beaches. We also analysed the relationships between meiofauna and environmental factors. The results showed that disturbed beaches were characterised by high values of meiofauna abundance, chlorophyll a content, total organic carbon content and N/C but lower levels of dissolved oxygen. The chlorophyll a and dissolved oxygen contents were found to be the most important factors for explaining the disturbance gradient amongst the beaches. The N/C index had a positive relationship with chlorophyll a and a negative relationship with dissolved oxygen. There was no significant relationship between N/C index and total organic carbon content. Ó 2014 Elsevier Ltd. All rights reserved.

1. Introduction Sandy beach is one of the most extensive intertidal systems worldwide (Wright and Short, 1983) and dominates a majority of temperate and tropical coastlines where it represents both important recreational assets and functions as a buffer zone against the sea (McLachlan, 1983). The interstitial environment of sandy beaches span a continuum between two extremes: from coarse sand reflective to fine sand dissipative beaches (Defeo and McLachlan, 2005). The coarse sand beaches with high energy experience low organic inputs and high filtration rates of large water volumes. These characteristics result in powerful hydrodynamic forces and better self-purification capacities. Conversely, the fine sand beaches are subject to high organic inputs and low filtration rates and result in material accumulation and stagnation (McLachlan et al., 1981; McLachlan and Turner, 1994). As a transition zone between sea and land, sandy beach ecosystem suffers most from various anthropogenic disturbances. The major disturbances on the coastal environment are linked to overexploitation of natural resources, pollution, industrialisation and erosion. However, the development of the beach tourism industry is also considered to be an important threat (Wynberg and Branch, 1994; Dronkers and de Vries, 1999). The impacts of tourism include human trampling on the beach itself, pollutants arising ⇑ Corresponding author. Tel./fax: +86 532 82032716.

from human activities and beach management (the construction of vacation facilities and mechanical beach cleaning) (Nordstrom et al., 2000; Gheskiere et al., 2005; Defeo et al., 2009). Except for the local-scale impacts of tourist activities, coastal eutrophication has fundamental impact on sandy beach ecosystem through the development of harmful green macroalgal blooms that affect numerous sandy beaches world-wide (Liu et al., 2009; Carriço et al., 2013). Sandy beach is the most dynamic soft bottom habitat and has abundant biological resources (de Ruyck and Hacking, 1996; McLachlan and Brown, 2010). While the variety of animal species in sandy beaches is less than that in rocky intertidal or shallow tidal flats, individual species are often abundant (Gheskiere et al., 2005). These species play important roles in the ecological function of the beach as primary producers (diatoms and algae), as decomposers (bacteria) and as first line (heterotrophic bacteria and meiobenthos) or second-line consumers (macrobenthos) (Knox and Knox, 2000). The benthic animals in sandy beaches are the most effective tool for assessing environmental variations of the habitat (Coull and Chandler, 1992; Giere, 1993). Benthos are useful tools because they remain in place and are subject to different environmental disturbances and react to these synergistically without any escape (Cibic et al., 2008). Relative to macrofauna, meiofauna exhibit a shorter response time and any perturbations are detectable because of its asynchronous reproduction, rapid turnover rate, and a lack of larval dispersal. As a result, the abundance of meiofauna is more sensitive and usually serves as a sensitive indicator of

E-mail address: [email protected] (H. Zhou). http://dx.doi.org/10.1016/j.marpolbul.2014.08.033 0025-326X/Ó 2014 Elsevier Ltd. All rights reserved.

Please cite this article in press as: Sun, X., et al. Meiofauna and its sedimentary environment as an integrated indication of anthropogenic disturbance to sandy beach ecosystems. Mar. Pollut. Bull. (2014), http://dx.doi.org/10.1016/j.marpolbul.2014.08.033

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X. Sun et al. / Marine Pollution Bulletin xxx (2014) xxx–xxx

disturbances (Coull and Chandler, 1992). Thus the Nematode/ Copepod ratio (N/C) was proposed as a potential indicator for monitoring organic pollution of sandy beaches (Raffaelli and Mason, 1981). However, the applicability of a single index as a measure of disturbance effect on the complex ecosystem is questionable and controversial. The sampling methodology, the effect of sediment nature on the index values and seasonal variability of meiofaunal abundance all could cause different results (Warwick, 1981; Rubal et al., 2009). To assess disturbance effects comprehensively we used meiofauna and its sedimentary environment from three different aspects of the sandy beach ecosystems as an integrated indication of anthropogenic disturbance. We examined hydrological features of interstitial water (temperature, salinity and dissolved oxygen), sediment characteristics (chlorophyll a content, total organic carbon content, sediment grain size and composition), and biological factors (Nematode/Copepod ratio, total meiofauna abundance and taxa number) in different seasons. It was noteworthy that the world’s largest macroalgal bloom (mainly Ulva prolifera) occurred in the southern and central Yellow Sea in 2008 (Liu et al., 2009). These green tides re-occurred from June to July 2011, which was during our sampling period. The beaches in Qingdao suffered from the algal bloom, especially No. 1 Bathing Beach and No. 3 Bathing Beach. The proliferation of U. prolifera influenced the marine ecosystem seriously and altered the natural balance of the algal community and the associated fauna communities (Ansell et al., 1998). Temporal fluctuation of meiofaunal abundance may be caused by the seasonal change of natural disturbance. For example, freshwater runoff from a ravine drastically eliminated intertidal meiofauna density, particularly nematodes, during the months of heavy rainfall in Canary Islands, Spain (Riera et al., 2012a). The impacts of anthropogenic disturbances on sandy beaches also present strong seasonal nature because the intensities of tourist activities vary seasonally. From 2008 to 2011, green macroalgal blooms occurred on the Qingdao beaches every June/July, just before the peak season (July/August) of tourism. Therefore, when we use meiofauna as an indicator for tourism-induced disturbance on sandy beaches, temporal variation of sedimentary environment in general and seasonal variation in particular could have remarkable influence on the meiofaunal abundance of different taxa and could cause the change in Nematode/Copepod ratio. Our surveys were conducted seasonally in Qingdao city and the Zhoushan archipelago. The No. 1 Bathing Beach, No. 3 Bathing Beach and Yangkou Bathing Beach were chosen to represent Qingdao’s sandy beach ecosystems. No. 1 Bathing Beach and No. 3 Bathing Beach are both famous Bathing Beaches in China and have many visitors during tourist seasons. The No. 1 Bathing Beach was once the largest bathing beach in Asia. The daily population flow of No. 1 Bathing Beach reached 350,000. The tourism brings profits for the city, but anthropogenic disturbances such as organic matter enrichment, building of tourism facilities and human trampling all influence the intertidal environment (Nordstrom, 2004; Speybroeck et al., 2006; McLachlan and Brown, 2010). Conversely, Yangkou Bathing Beach tends to have fewer visitors due to its remote location away from the downtown. The two beaches Dashali and Dongsha in Zhoushan archipelago were chosen to represent much cleaner habitats because they are not exploited and are non-tourist beaches. Based on different levels of tourism impacts on the studied beaches we hypothesised that a disturbance gradient existed: No. 1 and No. 3 Bathing Beach were highly disturbed, Yangkou Bathing Beach was moderately disturbed, and the beaches of Dashali and Dongsha were the least disturbed. The aim of this study was to test the existence of the assumed disturbance gradient by using a multivariate approach incorporating meiofauna and its sedimentary environmental variables as an integrated indication. Additionally,

we examined the relationships amongst different variables attempting to demonstrate the applicability of N/C ratio in pollution monitoring of sandy beaches and to uncover the underneath reasons for explaining the change of meiofaunal abundance and N/C ratio. 2. Materials and methods 2.1. Study sites Qingdao is a coastal tourist city in the Shandong province of China. It is located in the northern temperate zone and faces the Yellow Sea. The climate in Qingdao has significant marine characters. We selected three typical beaches, i.e., No. 1 Bathing Beach (N1), No. 3 Bathing Beach (N3) and Yangkou Bathing Beach (Y) as the study sites. The beach locations are shown in Fig. 1. The Zhoushan Archipelago in the Zhejiang province of China is located in the south of the Yangtze River Estuary and east of the Hangzhou Bay. The archipelago is comprised of 1390 islands and 3306 reefs. The environment in this region is less polluted and is suitable for the reproduction and growth of many biological communities (Zhu et al., 2010). The sampling beaches Dongsha (D) and Dashali (L) are located on the east side of Zhujiajian Island, which is the fifth largest island of the Zhoushan Archipelago (Fig. 1). Although situated in different geographical locations, the five sandy beaches were similar in sediment granulometry and beach types as they were all intermediate/dissipative beaches with well/moderately sorted medium sands (Table 1) and low fractions of very fine sands and silt/clay (Table 2). 2.2. Sampling strategy One month was chosen to represent each season (April 2011, July 2011, October 2011 and January 2012). The sampling was conducted at low tide. Two transects were chosen on each beach (Fig. 2), and surface sediments were sampled at three tidal zones (H, M, L) along each transect. The actual sampling positions were determined by GPS. There were five replicate core samples collected at each location using cylindrical corers with an inner diameter of 2.4 cm pushed into the sediment to the depth of 20 cm. Each core was sectioned vertically (0–4 cm, 4–8 cm, 8–12 cm, 12–16 cm, 16–20 cm). Three of the replicate samples were moved into bottles on site and were preserved in 10% buffered formalin for taxa identification and counting. For the other two samples (used for chlorophyll a, organic carbon content and grain size determination), sediments were removed into sealed bags and preserved at a temperature of 20 °C in the laboratory. During the sampling period an YSI600XLM (Yellow Spring Instrument Inc.) was used to detect the interstitial water temperature, salinity and dissolved oxygen (DO). 2.3. Sample processing The dry sieving technique (Giere et al., 1988) was used to measure cumulative percentage weights of sediment fractions for each Wentworth Scale grain size class (Table 2). The phi (u) notation transformation was used to express the median particle size (MDu). The total organic carbon (TOC) was measured using the chromic acid method (Wakeel el and Riley, 1956) after drying the samples at 90 °C until they reached a constant weight. The sediment chlorophyll pigments were extracted from fresh sediment with acetone. After storing at 4 °C overnight in the dark, a fluorescence spectrophotometer (RF-5301PC, Shimadzu) was used to determine the content of sediment chlorophyll a (Chl-a) (Greiser and Faubel, 1988). The meiofaunal data were converted into


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Fig. 1. Locations of No. 1 Bathing Beach (N1), No. 3 Bathing Beach (N3), Yangkou Bathing Beach (Y) in Qingdao, and Dashali (L), Dongsha (D) in Zhoushan.

Table 1 Detailed information on the beaches studied. Beach characters

Dashali

Dongsha

Yangkou Bathing Beach

No. 1 Bathing Beach

No. 3 Bathing Beach

Longitude Latitude Median grain size (u) Sediment texture Sediment sorting coefficient (u) Sorting class Beach type

122°240 560 0 E 29°560 200 0 N 1.73 ± 0.14 Medium sand 0.42 ± 0.19 Well sorted Intermediate/ dissipative

122°240 510 0 E 29°520 590 0 N 1.32 ± 0.19 Medium sand 0.44 ± 0.19 Well sorted Intermediate/ dissipative

120°400 250 0 E 36°140 380 0 N 1.39 ± 0.08 Medium sand 0.53 ± 0.20 Moderately sorted Intermediate/ dissipative



Table 2 Percentage composition (±SD) of sediments from sampling locations over the four seasons.

Gravels (%) Coarse sands (%) Medium sands (%) Fine sands (%) Very fine sands (%) Silt/clay (%)

Dashali

Dongsha

Yangkou Bathing Beach

No. 1 Bathing Beach

No. 3 Bathing Beach

1.07 ± 1.47 9.76 ± 3.32 51.63 ± 14.75 36.57 ± 9.84 0.95 ± 0.56 0.02 ± 0.03

9.22 ± 2.08 11.06 ± 1.50 61.83 ± 3.17 17.56 ± 6.67 0.33 ± 0.07 0.00 ± 0.00

5.36 ± 4.68 21.78 ± 4.59 57.35 ± 9.82 14.10 ± 2.50 0.81 ± 0.40 0.60 ± 0.30

3.95 ± 1.41 16.00 ± 2.79 46.38 ± 4.97 31.43 ± 5.15 1.78 ± 0.59 0.46 ± 0.15

1.79 ± 1.40 5.89 ± 3.42 60.78 ± 14.10 29.89 ± 17.97 1.10 ± 0.33 0.55 ± 0.24

abundance (number of individuals per 10 cm2) for total meiofauna and for each taxon, and the taxa number of each sample was counted. All data used were the mean values of replicate samples and are shown in Table 3. 2.4. Data analysis PRIMER 6 software (Clarke and Warwick, 2001) was used for multivariate statistical analyses of the data. A correlation-based Principal Components Analysis (PCA) was performed to show variation over an assumed disturbance gradient of sampling

beaches in different seasons. SPSS 18.0 was used to perform univariate analyses for single variables. The effects of disturbance, tidal zones and season on the univariate indices of meiofauna and its sedimentary environment were tested using a multi-factorial ANOVA, and Tukey multiple comparison tests were performed when there were significant differences. Essential transformations were employed for the original data prior to the analysis and Levene’s test was used to examine variance homogeneity both before and after data transformation. A Spearman rank correlation (test of significance: two-tailed) was performed to investigate the relationships between variables and disturbance degree.


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Fig. 2. Sampling stations (a) and sampling strategy (b). The letters (L, M, H) represent different tidal zones.

Table 3 Mean values of environmental and biological factors recorded seasonally from Dashali (L), Dongsha (D), Yangkou Bathing Beach (Y), No. 1 Bathing Beach (N1) and No. 3 Bathing Beach (N3).

L-April L-July L-October L-January D-July D-January Y-April Y-July Y-October Y-January N1-April N1-July N1-October N1-January N3-April N3-July N3-October N3-January

T (°C)

DO (mg/L)

Salinity

MDu

Chl-a (mg/Kg)

TOC (%)

Meiofaunal abundance (ind./10 cm2)

N/C

Taxa number

20.68 29.67 22.17 7.00 28.91 7.82 11.54 25.93 24.02 3.90 10.66 22.33 27.56 2.56 13.95 23.21 27.71 4.46

5.28 4.13 4.78 7.23 3.74 6.04 6.68 3.68 2.61 5.34 3.45 2.39 2.36 4.96 3.35 1.28 2.27 2.98

22.78 24.67 18.67 22.83 25.14 21.00 28.94 28.01 15.55 22.65 27.80 22.58 19.95 21.83 31.78 23.05 22.48 19.65

1.62 1.62 1.78 1.91 1.18 1.45 1.39 1.32 1.33 1.50 1.24 1.57 1.44 1.49 2.07 1.41 1.38 1.80

0.018 0.016 0.018 0.001 0.040 0.002 0.800 0.700 0.590 0.460 1.394 1.342 1.500 1.338 1.450 1.100 1.500 1.300

0.077 0.080 0.118 0.068 0.062 0.086 0.071 0.096 0.119 0.001 0.001 0.589 0.345 0.014 0.373 0.155 0.148 0.120

579 1043 1116 304 632 358 3464 1285 1431 862 3485 2343 2316 1988 3553 2253 2282 3541

7 6 11 9 6 3 47 9 7 5 442 154 134 164 145 750 767 429

9 11 10 10 13 9 13 12 11 9 13 10 12 11 11 9 9 8

3. Results 3.1. Meiofaunal abundance Meiofaunal abundance ranged from 304 ind./10 cm2 at Dashali in winter to 3553 ind./10 cm2 at No. 3 Bathing Beach in spring (Table 3). Meiofaunal abundance of the heavily disturbed beaches (No. 1 Bathing Beach and No. 3 Bathing Beach), the moderately disturbed beach (Yangkou Bathing Beach) and the least disturbed beaches (Dashali and Dongsha) were 2720 ± 677, 1760 ± 1161, 627 ± 340 ind./10 cm2, respectively. Nematode abundance showed a similar trend with meiofauna, ranging from 118 ind./10 cm2 at Dashali in winter to 3265 ind./10 cm2 at No. 3 Bathing Beach in spring (Fig. 3). Copepods had low abundance ranging from 1 ind./ 10 cm2 at No. 3 Bathing Beach in summer to 149 ind./10 cm2 at Yangkou Bathing Beach in autumn (Fig. 3).

3.2. A multivariate approach by PCA analysis The PCA results are presented in Fig. 4 and Table 4. Relationships among different samples and individual variables can be observed. The first component accounted for 39.7% of the total variance of the data. They were responsible for the major differences among the beaches with different levels of tourism impacts. PCA ordination of sampling sites suggested that the five beaches could be roughly classified into three groups (enclosed with circles in Fig. 4) along the first component (PC1). The combination was consistent with the supposed disturbance gradient (from the least

disturbed to the heavily disturbed). The highly positive values for PC1 were related to Chl-a, N/C ratio and total meiofauna abundance. The higher negative score was due to DO. The Chl-a, N/C and DO parameters did not strongly contribute to the second component (PC2). However, the second component (PC2) showed variation of the samples which was mainly explained by the sediment grain size (MDu) and the number of meiofaunal taxa. Temperature and salinity contributed most to PC3, but had little contributions to PC1. TOC had nearly equal contributions to the first two components (Table 4). The disturbance gradient shown by the PCA was mainly explained by the differences of meiofauna abundance, Chl-a, TOC, N/C and DO among the sampled beaches (Fig. 4). Both the No. 1 and No. 3 Bathing Beaches showed higher values of meiofauna abundance, Chl-a, TOC and N/C, but lower DO values. Each group was assigned a number (Dashali and Dongsha = 1, Yangkou Bathing Beach = 2, No. 1 and No. 3 Bathing Beach = 3) to represent the preset disturbance degrees verified by the result of PCA analysis. A Spearman correlation analysis was used to show the relationships for variables related to the disturbance gradient (Table 5). Chl-a, N/ C, meiofaunal abundance and DO had very significant correlations (p < 0.01) with disturbance degree.

3.3. Effects of disturbance, tidal zone and season The results of three-way ANOVA tests (Table 6) indicated that disturbance had very significant effects on Chl-a, TOC, DO and N/C (p < 0.01). Only Chl-a, however, showed significant differences


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Fig. 4. Ordination of samples by PCA analysis based on 9 environmental and biological variables from five sampling beaches. The sampling sites of different beaches are indicated in different symbols and numbers beside the symbols represent sampling months. The numbers 1–3 represent the three groups of sampled beaches with different disturbance degrees.

Table 4 Coefficients in the linear combinations of variables making up the first three PC axes.

T (°C) Salinity MDu Chl-a (mg/Kg) TOC (%) Meiofaunal abundance (ind./10 cm2) N/C DO (mg/L) Taxa number

PC1

PC2

PC3

0.083 0.059 0.020 0.490 0.346 0.474 0.478 0.420 0.010

0.305 0.343 0.538 0.028 0.308 0.099 0.058 0.026 0.625

0.598 0.501 0.241 0.194 0.160 0.196 0.154 0.434 0.139

Note: variables contributed most in PC axes are highlighted in bold.

3.4. N/C ratio and its relationships with sedimentary variables

Fig. 3. Mean abundances (±SD) of meiofauna in the five sandy beaches over the four seasons.

among tidal zones (p < 0.05). Seasonal effects were all significant for the sedimentary variables but not for N/C (p < 0.05). There were no significant interactions for all the indices (p > 0.05) except for TOC which showed significant interaction of season by disturbance (p < 0.05). Results of the present study suggested that the only factor affecting N/C ratio was disturbance. Effects of tidal zone, season and interactions of the multiple factors on N/C ratio were all insignificant. Fig. 5 shows the graphical summery of means and standard deviations for factors significantly correlated to disturbance degree in the PCA result (Chl-a, TOC, N/C and DO) for each tidal zone and the results of Tukey multiple comparison tests. There were differences in Chl-a, TOC, N/C and DO between beaches of different disturbance degrees for most tidal zones (except for TOC in high tidal zone and DO in mid tidal zone). The general effects of disturbances on the sandy beaches were increased Chl-a, TOC and N/C ratio, but decreased DO. These effects were consistent across different tidal zones.

The N/C ratio is a popular but controversial index to indicate the effects of disturbances. Usually this ratio is connected with the phenomenon of organic enrichment (shown by the values of the contents of chlorophyll a and total organic carbon in our study) and the sediment environment (represented by DO and MDu). The scatter diagrams showed its relationships with Chl-a and DO were more substantial than TOC (Fig. 6). There was no detectable relationship between N/C and MDu (Fig. 4). 4. Discussion 4.1. Applicability of N/C ratio in environmental monitoring The Nematode/Copepod index (N/C) was proposed as a fast, easy and reliable method to monitor the effects of organic pollution on sandy beaches (Raffaelli and Mason, 1981). The index is based on (1) the different habitat requirements of nematodes and copepods, (2) the ability of each to exhibit monotonic response, and (3) the degree of organic enrichment examined along a gradient (Raffaelli, 1987). However, the use of this index for ecological monitoring has been questioned because of its simplicity and the difficulties in interpreting the data (Coull et al., 1981; Lambshead, 1984). Refinements were made to add some precision to the practical application of this index in pollution monitoring by considering the size and feeding biology of


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Table 5 Spearman correlation analysis between disturbance degree and other variables.

Disturbance degree * **

Chl-a (mg/Kg)

TOC (%)

DO (mg/L)

Meiofaunal abundance (ind./10 cm2)

N/C

0.932**

0.437*

0.692**

0.613**

0.831**

p < 0.05. p < 0.01.

nematodes and copepods (Warwick, 1981) or by distinguishing between mesobenthic and epi/endobenthic copepods in the estimation of the N/C ratio (Sheills and Anderson, 1985). Although such indices have obvious limitations (Raffaelli, 1987), their simplicity remain attractive and gain general acceptance by most of intertidal (Warwick, 1981; Sheills and Anderson, 1985), subtidal (Amjad and Gray, 1983) and laboratory studies (Sandulli and De Nicola Giudici, 1989). Modern works have extended the application of this index to habitats other than sandy beaches like fish farms (Sutherland et al., 2007; Riera et al., 2011, 2012b) and to pollution types other than organic enrichment, e.g. heavy metals (Lee et al., 2001). Previous studies suggested a N/C ratio of 100 (Raffaelli and Mason, 1981) or 50 (Sutherland et al., 2007) as a pollution threshold for all habitat types (intertidal/subtidal, sandy/muddy) and a N/C ratio of 10 (Warwick, 1981) or 20 (Rubal et al., 2009) for intertidal sands. Of the five beaches studied, both No. 1 and No. 3 Bathing Beaches had N/C ratios of the four seasons all greater than 100. Whilst both Dashali and Dongsha had N/C ratios mostly below 10, the N/C ratio of Yangkou Bathing Beach was approaching 50 only in spring (Table 3). Our study suggested the feasibility of the N/C index as an indicator of pollution disturbance on sandy beaches. These results

were obtained by setting the presupposition of similar granulometry of the five beaches studied (Tables 1 and 2) and taking the seasonal variations into consideration. Although temporal variations (season, year) had significant effects on meiofaunal abundance and assemblage structure, and the N/C index showed strong temporal fluctuation in fish farms of shallow subtidal sands (Riera et al., 2011, 2012b), there was little evidence for supporting the significant seasonal variation in N/C index (Raffaelli and Mason, 1981; Riera et al., 2012b). Our data also showed no detectable seasonal effect on the N/C index (Table 6) but the inter-annual variability deserves to be investigated through a long term monitoring program. 4.2. An integrated approach with meiofauna: what sediment variables should be included? Since sediment properties and organic enrichment variables co-vary in nature, it is difficult to assess meiofaunal sensitivity to various stress and habitat types and many researchers have suggested that the Nematode/Copepod ratio should be not be used in isolation for pollution monitoring but as part of a suite of indicators across a variety of habitats and pollution gradients (Sutherland et al., 2007 and the references therein). Considering the drawback of univariate indices such as the N/C index for pollution monitoring, a multivariate PCA analysis incorporating meiofauna and its sedimentary environment was used in our study. Our approach showed the association of different samples and visualised the relationship between individual variable and samples. The sediment variables were used because they represented the different stresses that meiofauna respond to with respect to chemical, organic, and physical properties (Raffaelli, 1987). The variations of these variables were expected to coexist in a disturbance gradient. Our study showed that highly disturbed beaches have

Table 6 Results from three-way ANOVA and Tukey multiple comparison tests for univariate indices. The numbers 1–3 represent disturbance degrees (DD); the letters (L, M, H) represent different tidal zones; the numbers 1, 4, 7 and 10 represent seasons. Effect

df

F-value

p-value

Tukey test

Chl-a

DD Zone Season DD zone DD season Zone season DD zone season

2 2 3 4 6 6 12

1.427 0.063 0.051 0.024 0.017 0.009 0.004

117.469 5.211 4.173 1.984 1.371 0.753 0.294

0.000** 0.016* 0.021* 0.140 0.279 0.616 0.982

3>2>1 LPMPH 4 P 10 > 7 P 1

TOC


2 2 3 4 6 6 12

0.191 0.001 0.048 0.010 0.021 0.005 0.002

30.847 0.171 7.722 1.539 3.466 0.873 0.362

0.000** 0.844 0.002** 0.233 0.019* 0.534 0.961

3>2P1


2 2 3 4 6 6 12

0.368 0.011 0.127 0.015 0.008 0.009 0.009

44.338 1.313 15.297 1.750 0.921 1.033 1.068

0.000** 0.294 0.000** 0.183 0.503 0.437 0.437

1P2>3


2 2 3 4 6 6 12

13.247 0.509 0.284 0.864 0.286 0.055 0.097

23.610 0.907 0.506 1.539 0.510 0.097 0.173

0.000** 0.421 0.683 0.233 0.793 0.996 0.998

3>2P1

DO

N/C

* **

MS

7 P 1 P 10 > 4

1 P 4 > 7 P 10

p < 0.05. p < 0.01.



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Fig. 6. Relationships between N/C and DO, chlorophyll a and TOC. The value of R2 expresses the trend line fitting degree.

Fig. 5. (a) Total organic carbon (%), (b) chlorophyll a content (mg/Kg), (c) dissolved oxygen (mg/L) and (d) Nematode/Copepod ratio. All calculated by mean values and standard deviation of replicates from two sampling points per zone and per beach. The numbers 1–3 represent disturbance degrees. The letters (a–c) indicates intergroup significant differences between different disturbance degrees for each tidal zone (Tukey multiple comparison test results, p < 0.05).

higher values of meiofauna abundance, Chl-a, TOC and N/C index, but lower values of DO. The N/C index showed a positive relationship with Chl-a and a negative relationship with DO. However, there was no significant relationship with TOC. As sediment chloroplastic pigments often served as an indicator of photoautotrophic biomass related to primary productivity (Steele, 2006), they could be used as indicators of eutrophication processes (Sanger and Gorham, 1970). Eutrophication could lead to the increases of food supply and biological abundance, which decreases the dissolved oxygen in sediments (Raffaelli and Mason, 1981). This may explain the very significant relationships between Chl-a, DO and N/C index. The ratio of nematodes to copepods was originally proposed as a potential indicator for detecting organic pollution, so most studies on the ratio for pollution monitoring included organic

content and sediment grain size. Sutherland et al. (2007) carefully examined the relationship between N/C ratio and sediment variables consisted of free sulphide concentration, redox potential, organic content and sediment grain size. Few studies had included sedimentary Chl-a in the pollution monitoring with meiofauna. The integrated approach of the present study indicated significant relationship between Chl-a and N/C ratio and suggested the potential utility of integrating meiofauna with Chl-a and other sedimentary environmental variables for detecting anthropogenic disturbances to the sandy beach ecosystems. 4.3. The main stresses of tourism-disturbed beaches Previous studies in Mediterranean and Baltic coastal systems found that high tidal zones of tourism-disturbed beaches were characterised by lower percentages of total organic matter, lower meiofauna densities and species diversity compared to nearby locations (Gheskiere et al., 2005). Our study showed different results and we found that upper zones of disturbed beaches were characterised by increased Chl-a, but there were no changes in TOC. Threats to beaches arise from a range of anthropogenic disturbances that span a spectrum of impact scales from localised effects (e.g., trampling) to a truly global problem (e.g., sea-level rise)


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(Defeo et al., 2009). The main stresses of tourism-disturbed beaches in the Mediterranean and Baltic coasts were localised physical disturbances related to trampling. Our study suggested that the coastal eutrophication and organic enrichment have more extensive impacts and are possibly the predominant problems of disturbed beaches in Chinese coasts. 5. Conclusions Our study demonstrated the integrated approach of incorporating meiofauna and its sedimentary environment can indicate the disturbance gradient among the sampled beaches more comprehensively than a single index indicator. Eutrophication and organic enrichment were identified as the main problems for disturbed beaches. Highly disturbed beaches were characterised by higher values of meiofauna abundance, Chl-a, TOC and N/C but lower DO levels. Among these variables, sedimentary Chl-a, DO and N/C ratio had close relationships with each other and were found to play more important roles in explaining the gradient of anthropogenic disturbances to the sandy beaches under investigation. Our findings demonstrated the significance of incorporating N/C ratio together with Chl-a, DO and other sedimentary environmental variables for detecting anthropogenic disturbances to the sandy beach ecosystems. Acknowledgements This study was financially supported by the Grants to H.Z. (Nos. 41376146 and 41076090) and E.H. (No. 40906063) from Natural Science Foundation of China (NSFC). Special thanks go to the anonymous reviewers for their invaluable comments on the manuscript. References Amjad, S., Gray, J.S., 1983. Use of the nematode–copepod ratio as an index of organic pollution. Mar. Pollut. Bull. 14, 178–181. Ansell, A., Gibson, R., Barnes, M., Press, U., 1998. Ecological impact of green macroalgal blooms. Oceanogr. Mar. Biol. Annu. Rev. 36, 97–125. Carriço, R., Zeppilli, D., Quillien, N., Grall, J., 2013. Can meiofauna be a good biological indicator of the impacts of eutrophication caused by green macroalgal blooms? An aod-les cahiers naturalistes de l’Observatoire marin 2, 9–16. Cibic, T., Acquavita, A., Aleffi, F., Bettoso, N., Blasutto, O., De Vittor, C., Falconi, C., Falomo, J., Faresi, L., Predonzani, S., 2008. Integrated approach to sediment pollution: a case study in the Gulf of Trieste. Mar. Pollut. Bull. 56, 1650–1657. Clarke, K.R., Warwick, R.M., 2001. Change in Marine Communities: An Approach to Statistical Analysis and Interpretation, second ed. PRIMER-E Ltd., Plymouth Marine Laboratory, UK. Coull, B.C., Chandler, G.T., 1992. Pollution and meiofauna: field, laboratory, and mesocosm studies. Oceanogr. Mar. Biol. Annu. Rev. 30, 191–271. Coull, B.C., Hicks, G.R.F., Wells, J.B.J., 1981. Nematode/Copepod ratios for monitoring pollution: a rebuttal. Mar. Pollut. Bull. 12, 378–381. de Ruyck, A., Hacking, N., 1996. Community structure on sandy beaches: patterns of richness and zonation in relation to tide range and latitude. Revista Chilena de Historia Natural 69, 451–467. Defeo, O., McLachlan, A., 2005. Patterns, processes and regulatory mechanisms in sandy beach macrofauna: a multi-scale analysis. Mar. Ecol. Prog. Ser. 295, 1–20. Defeo, O., McLchlan, A., Schoeman, D.S., Schlacher, T.A., Dugan, J., Jones, A., Lastra, M., Scapini, F., 2009. Threats to sandy beach ecosystems: a review. Estuar. Coast. Shelf Sci. 81, 1–12. Dronkers, J., de Vries, I., 1999. Integrated coastal management: the challenge of transdisciplinarity. J. Coastal Conserv. 5, 97–102.

Gheskiere, T., Vincx, M., Weslawski, J.M., Scapini, F., Degraer, S., 2005. Meiofauna as descriptor of tourism-induced changes at sandy beaches. Mar. Environ. Res. 60, 245–265. Giere, O., 1993. The Microscopic Motile Fauna of Aquatic Sediments, second ed. Springer, Verlag, Berlin, Heidelberg. Giere, O., Eleftherious, A., Murison, D.J., 1988. Abiotic factors. In: Higgins, R.P., Thiel, H. (Eds.), Introduction to the Study of Meiofauna. Smithsonian Institution Press, Washington, D.C., pp. 61–78. Greiser, N., Faubel, A., 1988. Biotic factors. In: Higgins, R.P., Thiel, H. (Eds.), Introduction to the Study of Meiofauna. Smithsonian Institution Press, Washington, D.C., pp. 79–114. Knox, G.A., Knox, G., 2000. The Ecology of Seashores. CRC Press, Boca Raton, FL. Lambshead, P.J.D., 1984. The Nematode/Copepod ratio: some anomalous results from the firth of Clyde. Mar. Pollut. Bull. 15, 256–259. Lee, M.R., Correa, J.A., Castilla, J.C., 2001. An assessment of the potential use of the nematode to copepod ratio in the monitoring of metals pollution. The Canaral case. Mar. Pollut. Bull. 42, 696–701. Liu, D., Keesing, J.K., Xing, Q., Shi, P., 2009. World’s largest macroalgal bloom caused by expansion of seaweed aquaculture in China. Mar. Pollut. Bull. 58, 888–895. McLachlan, A., 1983. Sandy beach ecology: a review. In: McLachlan, A., Erasmus, T. (Eds.), Sandy Beaches as Ecosystems. W. Junk, The Hague, pp. 321–380. McLachlan, A., Brown, A.C., 2010. The Ecology of Sandy Shores, second ed. Academic Press, Burlington, MA. McLachlan, A., Turner, I., 1994. The interstitial environment of sandy beaches. Mar. Ecol. 15, 177–212. McLachlan, A., Dye, A., Harty, B., 1981. Simulation of the interstitial system of exposed sandy beaches. Estuar. Coast. Shelf Sci. 12, 267–278. Nordstrom, K.F., 2004. Beaches and Dunes of Developed Coasts. Cambridge University Press, Cambridge. Nordstrom, K.F., Lampe, R., Vandemark, L.M., 2000. Reestablishing naturally functioning dunes on developed coasts. Environ. Manage. 25, 37–51. Raffaelli, D., 1987. The behaviour of the Nematode/Copepod ratio in organic pollution studies. Mar. Environ. Res. 23, 135–152. Raffaelli, D., Mason, C., 1981. Pollution monitoring with meiofauna, using the ratio of nematodes to copepods. Mar. Pollut. Bull. 12, 158–163. Riera, R., Monterroso, Ó., Rodríguez, M., Ramos, E., Sacramento, A., 2011. Six-year study of meiofaunal dynamics in fish farms in Tenerife (Canary Islands, NE Atlantic Ocean). Aquat. Ecol. 45, 221–229. Riera, R., Núñez, J., Brito, M.C., 2012a. Influence of a freshwater runoff on temporal variations of an intertidal meiofauna assemblage. Vie et Milieu 62, 105–114. Riera, R., Sánchez-Jerez, P., Rodríguez, M., Monterroso, Ó., Ramos, E., 2012b. Longterm monitoring of fish farms: application of Nematode/Copepod index to oligotrophic conditions. Mar. Pollut. Bull. 64, 844–850. Rubal, M., Veiga, P., Besteiro, C., 2009. Nematode/Copepod index: importance of sedimentary parameters, sampling methodology and baseline values. Thalassas 25, 9–18. Sandulli, R., De Nicola Giudici, M., 1989. Effects of organic enrichment on meiofauna: a laboratory study. Mar. Pollut. Bull. 20, 223–227. Sanger, J.E., Gorham, E., 1970. The diversity of pigments in lake sediments and its ecological significance. Limnol. Oceanogr. 15, 59–69. Sheills, G.M., Anderson, K.J., 1985. Pollution monitoring using the Nematode/ Copepod ratio. Mar. Pollut. Bull. 16, 62–68. Speybroeck, J., Bonte, D., Courtens, W., Gheskiere, T., Grootaert, P., Maelfait, J.P., Mathys, M., Provoost, S., Sabbe, K., Stienen, E.W., 2006. Beach nourishment: an ecologically sound coastal defence alternative? a review. Aquat. Conserv. 16, 419–435. Steele, J.H., 2006. Environmental control of photosynthesis in the sea. Limnol. Oceanogr. 7, 137–150. Sutherland, T.F., Levings, C.D., Petersen, S.A., Poon, P., Piercey, B., 2007. The use of meiofauna as an indicator of benthic organic enrichment associated with salmonid aquaculture. Mar. Pollut. Bull. 54, 1249–1261. Wakeel el, S.K., Riley, J.P., 1956. The determination of organic carbon in marine muds. J. Conseil 22, 180–183. Warwick, R., 1981. The Nematode/Copepod ratio and its use in pollution ecology. Mar. Pollut. Bull. 12, 329–333. Wright, L., Short, A., 1983. Morphodynamics of beaches and surf zones in Australia. In: Komar, P.D. (Ed.), Handbook of Coastal Processes and Erosion. CRC Press, Boca Raton, FL, pp. 35–64. Wynberg, R.P., Branch, G.M., 1994. Disturbance associated with bait-collection for sandprawns (Callianassa kraussi) and mudprawns (Upogebia africana): longterm effects on the biota of intertidal sandflats. J. Mar. Res. 52, 523–558. Zhu, S.X., Zhou, W., Zhang, F.J., 2010. Macrobenthic animals community characters in summer in the intertidal zones of Zhoushan Archipelago, Zhejiang, China. J. Mar. Sci. 3, 23–33.


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