Trophic structure of common marine species in the Bohai Strait, North China Sea, based on carbon and nitrogen stable isotope ratios

Ecological Indicators 66 (2016) 405–415

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Trophic structure of common marine species in the Bohai Strait, North China Sea, based on carbon and nitrogen stable isotope ratios Pei Qu a,b , Qixiang Wang c , Min Pang b , Zhipeng Zhang a , Chengyue Liu a , Xuexi Tang a,∗ a b c

College of Marine Life Sciences, Ocean University of China, Qingdao 266003, China The First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China Marine Biology Institute of Shandong Province, Qingdao 266104, China

a r t i c l e

i n f o

Article history: Received 14 November 2015 Received in revised form 14 January 2016 Accepted 18 January 2016 Keywords: Stable isotopes Trophic level Food source Bohai Strait

a b s t r a c t Trophic relationships among common coastal species in the Bohai Strait, North China Sea, were investigated in this study using stable isotope ratios of carbon (13 C/12 C) and nitrogen (15 N/14 N) as tracers. During the research cruises of this study, 16 species of invertebrates and 18 species of fishes were collected, as were various food sources (phytoplankton, macroalgae, and sediment). The carbon and nitrogen isotope ratios of all collected samples were measured and used for trophic level analyses. The results showed that the grazers Oregonia gracilis, Notoacmea schrenckii, Chlorostoma rustica, and Chelon affinis, preferentially consumed Zostera marina (p < 0.01), whereas Anthocidaris crassispina preferred Ulva conglobata (p < 0.01). Two trophic models based on nitrogen isotope ratios were built to identify the trophic level of each species. The model that combined food sources was more appropriate than the model that used a single primary producer to identify the relative trophic positions of primary consumers. Scombermorus niphonius, an important fishery resource, was at the top trophic level. The seastar Asterias amurensis was at the highest level among the invertebrates and directly threatened production of shellfish. Based on the trophic level and food source relationships identified in this study, we gave some advice for ecological restoration, such as optimizing the structure of food source distribution, limiting seastar numbers, and improving the applicability of habitat for fishery species. © 2016 Published by Elsevier Ltd.

1. Introduction Nutrients from the mainland in epicontinental marine ecosystems are abundant and play a significant role in the growth of a wide variety of marine organisms, which are important food sources for humans. China is the main producer of marine products, with the most fish catches in the world (FAO, 2010) and 61.3% of the total world aquaculture production (Feng et al., 2014). However, fishery resources, especially those in north China seas, have been severely damaged due to overfishing, environmental pollution, and other anthropogenic effects. As a result, ecological restoration has become an important research focus with the goal of maintaining production and sustainability of existing fisheries (APEC Ocean and Fisheries Working Group, 2014). To relieve the adverse effects on the marine environment caused by fisheries and aquaculture, scientific methods are needed to support ecological restoration aimed at balancing trophic structure.

∗ Corresponding author at: 5 Yushan Road, Qingdao 266003, Shandong Province, China. Tel.: +86 532 82032952. E-mail address: [email protected] (X. Tang). http://dx.doi.org/10.1016/j.ecolind.2016.01.036 1470-160X/© 2016 Published by Elsevier Ltd.

Traditionally, food sources and trophic positions were determined by direct gut content analysis (Cortés, 1997; Hyslop, 1980), but trophic links between living marine species cannot be assessed by such methods. Thus, use of stable isotopes has become a powerful tool to study trophic relationships and the circulation of chemicals in marine ecosystems in recent years (Cabana and Rasmussen, 1996; Fry, 2006; Churchill et al., 2015; Cresson et al., 2014; Deehr et al., 2014; Dromard et al., 2015; Valls et al., 2014). Compared to the traditional dietary observation method, stable isotope analysis provides information about long-term accumulation of nutrients instead of a snap shot of food ingestion. It enhances the reliability of the food web model (Fry, 2006; Parnell et al., 2010) and offers a reliable approach to resolving questions about marine food web ecology (Ben-David and Flaherty, 2012). Trophic relationship models are now widely used in analysis of marine ecosystems, especially in the fields of marine protection (Colléter et al., 2012; Varkey et al., 2012), aquaculture production (Forrestal et al., 2012), and fisheries management (Downing et al., 2012). Application of these models to fisheries practices, management, and policy has shown that fishing can influence the trophic structure of the ecosystem (Tsehaye and Nagelkerke, 2008; Heymans et al., 2009; Wang et al., 2012).

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Fig. 1. Sampling area.

Isotope ratios of many elements, including carbon, nitrogen, oxygen, sulfur, and hydrogen, can be measured. Oxygen, sulfur, and hydrogen are not related to trophic relationships, but stable isotope ratios of carbon (13 C/12 C) and nitrogen (15 N/14 N) in organisms and food sources can be used as tracers to study the nutritional relationships among species (Michener and Lajtha, 2007). Stable isotope analyses of carbon and nitrogen can also serve as independent measures of trophic position. Laboratory and field studies revealed that carbon isotope compositions of animals can reflect their source diet (Vander Zanden and Rasmussen, 2001; Fry, 2006; Michener and Lajtha, 2007), and stable carbon isotope (␦13 C) values are indicative of the food source origin (Cherel et al., 2010). However, an organism’s diet does not consist of a single source but rather a mixture of sources, which complicates interpretation of carbon isotope data. Phillips et al. (2002, 2003, 2005, 2012) developed a computer program called IsoSource as a mixing model that takes into account the carbon isotope values of multiple food sources according to user-specified data, and applied it successfully in food web studies (Sarà et al., 2004; Burford and Lorenzen, 2004; Newsome et al., 2004). As carbon stable isotope values were more related to food sources with little discrimination in metabolism, they were more suitable for food source analysis (Vander Zanden and Rasmussen, 2001; Michener and Lajtha, 2007; Cherel et al., 2010). In contrast, nitrogen stable isotope values (␦15 N) changed with the trophic position of the consumer through isotopic fractionation during metabolism (Fry and Sherr, 1984; Fry, 2006). Controlled laboratory experiments showed that the ␦15 N values of animals were positively significantly correlated with the values of the prey consumed. Thus, ␦15 N values act a time-integrated indicator of trophic position (Wada et al., 1991; Vander Zanden and Rasmussen, 1999, 2001). Average increases of ␦15 N values per trophic level have been reported, but the assessment varies for different tissues and species. The most commonly reported values of per trophic level fractionation are 2–4‰ (Minagawa and Wada, 1984; Post, 2002; Sweeting et al., 2007; Caut et al., 2009). Based on these fractionation values, isotope mixing models were built to assess the trophic structure of food webs with multiple food sources (Phillips and Koch, 2002; Deehr et al., 2014). To date, only a few similar models have been used in studies of the China Sea (Chang et al., 2014; Feng et al., 2014; Zheng and You, 2014), and the use of ␦15 N and ␦13 C data to evaluate the relationship between fishing activities and trophic position in

the Bohai Strait has seldom been reported. The Bohai Strait, which lies near the Yellow River Estuary, is the main spawning grounds of various fishery resources and an ideal location to study trophic relationships. As such, it is an important fishery conservation area in the northern China Sea (Zheng and You, 2014). However, this area has experienced habitat deterioration due to human activities and changes in food web dynamics, which threaten the fisheries (Xu et al., 2010, 2011; Shan et al., 2012; Zheng and You, 2014). In this study, samples of primary food sources (phytoplankton, macroalgae, and sediment) and consumers (16 invertebrate species and 18 fish species) were collected in waters off Xiaoheishan Island. Their carbon and nitrogen stable isotope ratios were measured and used to conduct trophic relationship analyses. The objectives of the present study were to: (1) build two trophic level models based on isotope data from food sources and primary consumers, respectively, and compare the two models; and (2) identify the principal food source species and clarify the trophic relationships among the various species based on the stable isotope analyses. 2. Methods 2.1. Study area and sample collection The Bohai Strait, which is located between the Shandong and Liaodong Peninsulas, connects the Bohai Sea and the north Yellow Sea and provides the pathway for material exchange between the two seas. The study area was the open coastal water around Xiaoheishan Island located in the southern portion Bohai Strait. Samples were collected from 10 sites with depth <20 m (Fig. 1) during 2013 and 2014. Because the aquatic community may vary seasonally, five cruises in spring (April 2014), summer (June and August 2014), and autumn (November 2013 and 2014) were conducted to study the food web. Fishes and invertebrates were collected from each site using horizontal midwater and bottom trawls (Olivar et al., 2012). After onboard identification, the specimens were photographed and then frozen at −20 ◦ C until used for stable isotope analysis. Zooplankton samples were collected from vertical hauls using a 70 ␮m mesh plankton net, followed by sieving through a 500 ␮m mesh. In addition, the following potential food sources were collected: phytoplankton, macroalgae (Ulva conglobata, Sargassum thunbergii, and Zostera marina), and sediment. Phytoplankton samples were

P. Qu et al. / Ecological Indicators 66 (2016) 405–415

gathered from seawater filtered through a 1 ␮m nylon mesh. Macroalgae samples were manually picked, and sediment samples were gathered by clam bucket dredge in subtidal zone.

uncertainty and avoid misrepresenting the results, the distribution of feasible solutions should also be considered.



E(x) = 2.2. Sample pretreatment and stable isotope analyses

 13

C/12 Csample

13 C/12 C VPDB

 15 ␦15 N (‰) =

N/14 Nsample

15 N/14 N air



−1

× 1000

(1)

 −1

× 1000

100%

xf (x)dx

(3)

0

Whether samples were analyzed in part or in their entirety depended on the feeding habits of consumers. Mixed phytoplankton and zooplankton samples composed of individuals of several species were analyzed together, and fronds of macroalgae were collected for analysis. Because prey items in lower trophic levels often are consumed in their entirety, the whole bodies of benthic invertebrates were analyzed. In contrast, the tissues (e.g., muscles) of higher level organisms reflect long-term information about food selection (McIntyre and Flecker, 2006), thus the white dorsal muscles of fishes were removed and analyzed. Based on previous reports (Bode et al., 2003; Bunn et al., 1995; Letessier et al., 2012; Pinnegar and Polunin, 1999; Yokoyama et al., 2002), the pretreatment process was modified. All samples were cut into small pieces, oven dried for at least 48 h at 80 ◦ C until a constant weight was achieved, and then homogenized into fine powder using a mortar and pestle. Because acidification can remove carbonates (CaCO3 ) and also distort ␦15 N values in food sources (Kanaya et al., 2007), each individual sample was divided in half; one half was treated with acid (1 mol/L HCl) to remove CaCO3 for ␦13 C analysis, and the other non-acidified half was used directly for ␦15 N analysis. After pretreatment, carbon and nitrogen isotope ratios were determined by continuous flow isotope ratio mass spectrometry (CF-IRMS) using a Thermo Delta VTM isotope ratio mass spectrometer (Thermo Electron, Bremen, Germany). Stable isotope ratios were expressed in standard ␦ unit notation (␦13 C and ␦15 N), which is defined as follows: ␦13 C (‰) =

407

(2)

where 13 C/12 Csample and 15 N/14 Nsample are the ratios of heavy isotopes to light isotopes from the samples. 13 C/12 CVPDB represents the Vienna Pee Dee Belemnite (VPDB) standard for 13 C, and 15 N/14 Nair represents atmospheric N2 for 15 N. 2.3. Food source analysis When the number of food sources in a food web is small, isotope mixing models can provide unique solutions regarding their contributions to the diets of consumers. Phillips and Gregg (2003) created a Visual Basic program called IsoSource, which can help determine the ranges of food source contributions when the number of sources is too large to permit such unique solutions. The IsoSource model provides upper and lower limits for the contributions of each source, and all possible solutions for each source contribution (0–100%) are examined in small increments (1–2%). The frequency and range of potential source contributions can be represented with histograms. According to the series of reports by Phillips and coworkers (2002, 2003, 2005, and 2012) and Newsome et al. (2004), the IsoSource model is mainly applied to determine the distribution of all feasible solutions, and the uncertainty inherent in this model is that it generates a set of solutions rather than a unique value. When we further calculated the mathematical expectations (ranging from 0% to 100%) of each given food source using Eq. (3), the uncertainty appeared in this process ineluctably. To control the model

where E(x) is the plausible contribution of the given food source and f(x) is the percent frequency of x contribution. We used the ␦13 C data to determine the primary food sources of each predator. The ranges of food source contributions together with average and expected values for each consumer were calculated as well. In this study, the contributions of five food sources to the diets of local consumers were analyzed. The five sources were phytoplankton, sediment, and the three local dominant macroalgae species Z. marina, S. thunbergii, and U. conglobata. 2.4. Trophic level analysis Nitrogen isotope ratios can be enriched through the food chain, undergoing predictable changes with each successive level up the trophic ladder (Smit et al., 2005). Fractionation tends to cause isotopic differences between trophic levels, and the trophic level can be calculated according to the traditional model formula as follows: TL = 2 + (␦15 Nconsumer − ␦15 Nrefernce )/␦15 NTEF

(4)

where TL is the trophic level, ␦15 Nconsumer is the nitrogen isotope ratios of consumers, ␦15 Nreference is the nitrogen isotope ratios of marine primary consumers (zooplankton), and ␦15 NTEF is the trophic enrichment factor (TEF). As the primary consumers were at the base of the trophic ladder, they were assumed to occupy the second trophic level in the study. The trophic model uncertainty is derived from two key parameters: the ␦15 NTEF and the ␦15 Nrefernce . ␦15 NTEF determines the relative distance between two adjacent trophic levels in the TL model. It changes with territory and species (Post, 2002; Sweeting et al., 2006, 2007; Akin and Winemiller, 2008; Caut et al., 2009; Plass-Johnson et al., 2013). Caut et al. (2009) conducted an extensive review of 66 publications concerning estimates of ␦15 NTEF variation. Based on the supporting information for their study, we calculated that the ␦15 NTEF of fish ranges from −1.0 to 5.6, with an average of 2.516 and a standard deviation of 1.540, and that of invertebrates ranges from −3.2 to 9.2, with an average of 2.502 and a standard deviation of 2.244. Considering the variation of ␦15 NTEF in different research areas, the ␦15 NTEF value should be determined specifically for the local area. As a result, we adopted the ␦15 NTEF value of 2.5‰ reported in a previous study conducted in neighboring waters (Cai et al., 2005). This value approximates the average ␦15 NTEF of fish and invertebrate calculated in Caut’s research. ␦15 Nrefernce is the other key parameter for TL calculation using the traditional model formula, which determines the threshold of the trophic structure. Generally, in this formula, the nitrogen isotope ratios of primary consumers were considered as the ␦15 Nreference , such as zooplankton (Post, 2002; Fernández de Puelles et al., 2014) and bivalves (Cai et al., 2001, Vander Zanden and Rasmussen, 2001). However, both of them may be inappropriate for the study area of this present report, because zooplankton values are too variable, while bivalves mainly live in the benthic zone and thus are not preyed upon by consumers in the upper layer of the water column. Other researchers have used the mean values of primary producers (food sources) as the reference in the first trophic level of the model (Govender et al., 2011; Vinagre et al., 2008, 2011, 2012; Cresson et al., 2014). However, for the multiple food sources presented in the system, it is inappropriate to use the mean value of the isotope ratios of food sources as the reference. To control the model uncertainty from ␦15 Nrefernce , we added the weight function for

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each food source in formulae (5) and (6) to establish a more reliable trophic model. ␦15 Nreference = ␦15 N1 × P1 + ␦15 N2 × P2 + · · · + ␦15 Nn × Pn

(5)

where ␦15 Nn

is the nitrogen isotope ratio of the nth food source and Pn is the weight function of nth food source. The weight function was determined by the contribution value of each food source (phytoplankton, sediment, and macroalgae) to consumers calculated by IsoSource. Use of the weight function helps reflect the trophic levels more precisely and avoids the variations caused by a single food source. Then the trophic level can be calculated using the following revised formula: TL = 1 +

␦15 Nconsumer − ␦15 Nreference ␦15 NTEF

(6)

In this study we built two trophic models based on formulae (4) and (6), respectively, and compared the difference between them. 2.5. Statistical analysis Graphics were generated using ArcGIS software v.10.2.2 from ESRI (USA) and Microsoft Excel 2010. All statistical analyses were performed using statistics package SPSS 17.0 (SPSS Inc., Chicago, IL, USA). Calculation results were compared using the t-test and analysis of variance. 3. Results 3.1. Samples Sixteen species of invertebrates and 18 species of fishes (Table 1) were collected with the mixed zooplankton samples and subsequently used for carbon and nitrogen stable isotope ratio analyses. 3.2. Isotope ratio analysis Isotope ratio values of all samples collected in the coastal waters of Xiaoheishan Island ranged from −24.39‰ to −14.86‰ for ␦13 C and from 8.66‰ to 16.66‰ for ␦15 N. All ␦13 C values of samples were significantly different from ␦15 N values (F2,70 = 68.324, p < 0.001). Scombermorus niphonius had the highest mean value of ␦15 N, and the mean ␦15 N values of fishes was significantly higher than that of invertebrates (t-test, t35 = 7.176, p < 0.01) rather than ␦13 C (t-test, t35 = 0.449, p = 0.656). Fig. 2 shows the scatter plot of both the carbon and nitrogen isotope ratio values (␦15 N and ␦13 C, mean ± SD). The ␦13 C values of food sources ranged from −24.39‰ to −14.86‰, those of invertebrates ranged from −21.95‰ to −15.14‰, and those of fishes ranged from −21.34‰ to −16.70‰. When looking at the range of values for a given species, the mean values became narrower from food sources (range 9.54‰) to invertebrates (range 6.81‰) to fishes (range 4.64‰). ␦13 C values of food sources were more variable than those of consumers, which revealed the consumers’ assimilation from different sources (Viana et al., 2015). ␦15 N values of food sources ranged from 8.66‰ to 10.57‰, those of invertebrates ranged from 9.22‰ to 13.93‰, and those of fishes ranged from 12.66‰ to 16.66‰. When the intraspecific ranges of ␦15 N values were averaged and examined, they showed that the values increased from food sources (mean 10.41‰) to invertebrates (mean 11.36‰) to fishes (mean 14.58‰). Moreover, these values were distributed in the shape of a pyramid with few exceptions (Fig. 2). The food sources were at the base of the pyramid, invertebrates were distributed in the middle, and most fishes were at the top. This distribution was considered to reflect the true rudiments of trophic structure in this environment. Thus, fishes are at high trophic levels and invertebrates are at lower levels.

Fig. 2. Plot of ␦15 N and ␦13 C isotope ratio values (mean ± SD) for various organic components of the food web in the waters off Xiaoheishan Island.

3.3. IsoSource results Five food sources – phytoplankton, sediment, U. conglobata, S. thunbergii, and Z. marina – were selected as the primary food sources in the model. Consumers were categorized as direct or indirect consumers according to how they use the food sources. The majority of invertebrates were considered to be direct consumers. In total, 14 kinds of direct consumers were evaluated in this study. This number included the omnivorous crabs Charybdis japonica and Oregonia gracilis and the phytophagous fish species Chelon affinis, which were identified as using the food sources directly. The mean contributions of food sources to the diets of 14 direct consumers were calculated using the IsoSource model (Table 2). Phytoplankton made the greatest contribution (27%) to Aplysiidae and Ostreidae and less to zooplankton (26%). Sediment contributed most to Mya arenaria (29%) followed by Apostichopus japonicas (27%). S. thunbergii made the largest contribution (25%) to C. japonica followed by Rapana venosa (24%). All these three food sources contributed <30%. In contrast, the contributions of Z. marina and U. conglobata were much higher. The contributions of Z. marina to O. gracilis, Notoacmea schrenckii, Chlorostoma rustica, and C. affinis were 60%, 50%, 91%, and 53% on average, respectively, and the contribution of U. conglobata to Anthocidaris crassispina was 60% on average. In addition to the mean values, the contribution ranges of each contributing group were calculated (Table 2). Although the average contribution of phytoplankton to zooplankton diet (26%) was lower than that of U. conglobata (30%), the range of the phytoplankton contribution to zooplankton was broader (0–100%) than that of U. conglobata (0–54%). This means that it was possible for phytoplankton to contribute 100% to zooplankton, whereas the maximum that U. conglobata could contribute was 54%. The contributions of Z. marina to O. gracilis, N. schrenckii, C. rustica, and C. affinis ranged from 32% to 82%, 16% to 76%, 88% to 94%, and 20% to 78%, respectively. As Z. marina made such a large contribution (88–94%) to C. rustica, the contributions of other food sources were reduced to 6% on average. The contribution of U. conglobata to A. crassispina ranged from 44% to 74%. These ranges reflected the mean values of contributions. 3.4. Trophic level model To determine trophic level structure, the consumers were grouped into fishes and invertebrates. Two trophic structures

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409

Table 1 Categories, species/family, phylum, mean mass, and range (minimal and maximal mass) of the samples collected in this study. Categories

Species or family

Phylum

Mean mass (g)

Range (g)

Invertebrates

Mytilus galloprovincialis Ostreidae Notoacmea schrenckii Rapana venosa Mya arenaria Chlorostoma rustica Aplysiidae Octopus minor Actiniidae Apostichopus japonicas Anthocidaris crassispina Asterias amurensis Charybdis japonica Oregonia gracilis Oratosquilla oratoria Alpheus japonicus

Mollusca Mollusca Mollusca Mollusca Mollusca Mollusca Mollusca Mollusca Cnidaria Echinodermata Echinodermata Echinodermata Arthropoda Arthropoda Arthropoda Arthropoda

8.2 88.2 7.4 225.1 12.1 5.8 10.7 125.2 69.2 56.8 44.6 58.8 81.3 15.0 12.0 4.8

5.6–10.8 56.1–157.9 4.3–9.1 102.2–225.1 8.9–15.8 4.1–6.6 8.1–16.2 65.0–125.2 45.1–78.2 41.9–63.0 23.5–55.9 43.7–154.2 9.1–172.3 4.8–22.5 11.9–26.1 3.3–5.4

Fishes

Chelon affinis Pleuronichthys yokohamae Acanthopagrus schlegelii Clupanodon punctatus Enchelyopus elongatus Liparis tanakae Thamnaconus septentrionalis Eupleurogrammus muticus Sebastes schlegelii Ernogrammus hexagrammus Platycephalus indicus Enchelyopus fangi Hexagrammos otakii Hemiramphus sajori Raja pulchra Cryptocentrus filifer Sebastiscus marmoratus Scombermorus niphonius

Chordata Chordata Chordata Chordata Chordata Chordata Chordata Chordata Chordata Chordata Chordata Chordata Chordata Chordata Chordata Chordata Chordata Chordata

725.0 42.2 36.6 14.3 68.3 46.9 41.6 58.2 26.6 25.8 65.2 23.6 43.3 13.8 60.4 31.4 28.1 670.1

553.8–1021.4 34.1–58.3 30.1–48.7 11.9–16.2 25.3–92.5 41.2–53.1 32.1–53.0 58.2 22.0–59.9 19.8–33.0 17.3–164.1 12.7–45.9 22.9–78.2 11.3–15.2 60.4 23.8–41.2 20.0–63.9 670.1

Table 2 IsoSource calculation of direct dietary contributions of five food sources (mean (%) is the average of the total contributions, range (%) is the distribution breadth of feasible solutions) to the diets of 14 consumers. Species

Zooplankton Actiniidae Apostichopus japonicus Anthocidaris crassispina Charybdis japonica Oregonia gracilis Mytilus galloprovincialis Ostreidae Notoacmea schrenckii Rapana venosa Mya arenaria Chlorostoma rustica Aplysiidae Chelon affinis

Phytoplankton

Sediment

Mean

Range

Mean

26 22 16 15 19 8 25 27 9 25 14 1 27 9

0–100 0–76 0–96 0–54 0–64 0–30 0–96 0–84 0–36 0–78 0–50 0–4 0–92 0–32

15 12 27 8 26 18 15 18 22 20 29 6 16 21

Zostera marina

Sargassum thunbergii

Ulva conglobata

Range

Mean

Range

Mean

Range

Mean

Range

0–58 0–48 0–60 0–32 0–82 0–68 0–56 0–68 0–84 0–72 0–92 0–12 0–60 0–80

11 9 12 6 21 60* 11 13 50* 15 31 91* 12 53*

0–44 0–34 0–46 0–24 0–64 32–82** 0–42 0–48 16–76** 0–54 0–68 88–94** 0–46 20–78**

19 16 20 11 25 11 18 22 13 24 19 1 20 13

0–68 0–60 0–74 0–42 0–90 0–40 0–70 0–86 0–50 0–88 0–72 0–4 0–78 0–50

30 42 27 60* 10 4 31 20 5 16 7 0 25 4

0–54 0–60 0–52 44–74** 0–36 0–16 2–54** 0–46 0–18 0–42 0–28 0–2 0–50 0–18

(Fig. 3) then were built based on ␦15 N values using zooplankton (L-model) and weighted food sources (R-model) as references, respectively. As both models were built on the basis of ␦15 N data, they were considered to be reliable models for trophic level analysis. However, which one better reflected the real trophic condition required further analysis as follows. The L-model using zooplankton as the reference (Fig. 3, left) showed that the trophic level of fishes ranged from 2.50 to 4.10, with S. niphonius at the top. Eleven species of fishes were located at the third level, including Sebastiscus marmoratus (3.80), Cryptocentrus filifer (3.71), and Raja pulchra (3.69), and six species of fishes were at the second trophic level, including Liparis tanakae (2.97), Enchelyopus elongates (2.92), and Clupanodon punctatus (2.85). C.

affinis was the fish species collected at the lowest level (2.5). The trophic levels of invertebrates ranged from 1.12 to 3.00 and were significantly lower than those of fishes (average deviation = 1.29, t = 7.18, p < 0.01). Oratosquilla oratoria was at the highest trophic level (3.00), followed by seven species including Asterias amurensis (2.99), Octopus minor (2.67), and O. gracilis (2.59) at the second level. The remaining nine species of invertebrates, such as A. crassispina (1.74), Actiniidae (1.70), and A. japonicas (1.26), were below the second trophic level. The R-model using the weighted sources reference (Fig. 3, right) showed that the trophic level of fishes ranged from 2.24 to 3.56, with S. niphonius at the top. Relative to the L-model, three species, Thamnaconus septentrionalis, Eupleurogrammus muticus,

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Fig. 3. Trophic levels of species in coastal waters off Xiaoheishan Island based on ␦14 N data; for the L-model (left), the reference was zooplankton, and for the R-model (right), the reference was food sources (weighted). The underlined species differed in relative position between the two models.

and Sebastes schlegelii moved from the third level to the second. As a result, eight species of fishes were at the third trophic level, and the other nine species were at the second level. However, the relative positions of the fishes changed little, except for Platycephalus indicus and Ernogrammus hexagrammus, whose positions were exchanged after model transformation. In the R-model, the trophic levels of invertebrates ranged from 0.88 to 3.02 and were significantly lower than those of fishes (average deviation = 1.16, t = 6.46, p < 0.01). However, the majority of their relative positions differed from those in the L-model. In the R-model the top species was A. amurensis (3.02) and O. oratoria (2.88) was demoted to the second level with four other invertebrate species. The relative positions of all other invertebrates except O. minor, O. gracilis, Actiniidae, and A. crassispina differed between the two models.

The six shellfish species and A. japonicas were at the lower trophic level (<1.5) in the R-model. These results indicate that food sources influenced the grazers at lower trophic levels more than the fishes at higher levels. Thus, the results suggest that the R-model with weighted food sources as the reference was the more appropriate model for determining trophic level of invertebrates in the study area. However, the R-model also has limitations. For example, the trophic levels of Mytilus galloprovincialis (0.96) and Ostreidae (0.88) in this study were <1, which does not make sense. Together the findings indicate that the R-model is more appropriate when multiple food sources with direct consumers at lower trophic levels are present, and the L-model may be more appropriate when a single food source or high level consumers are present.

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4. Discussion 4.1. Food sources As the basis of the marine food chain, phytoplankton play an obviously important role in marine ecosystems (Uitz et al., 2009; Fu et al., 2009; Wollschläger et al., 2015). Although they are vulnerable to variations in environmental factors such as nutrient concentrations, metallic elements, light, pH, temperature (Mills et al., 2012; Thuróczy et al., 2012; Selph et al., 2013; Armbrecht et al., 2015; ´ et al., 2015), and monsoons (Li et al., 2013) and can Ninˇcevic-Gladan produce frequent harmful algal blooms in certain locales (Dale and Murphy, 2014), they are still a primary food source in the marine ecosystem (Longhurst et al., 1995). In the current study, the average contributions of phytoplankton to the diet of each herbivore species were no more than 30%, but the contribution ranged from 0% to 100% for zooplankton with the biggest indeterminacy in the marine ecosystem. Sediment contains two principal biological components: organic detritus and microphytobenthos (including its detritus). Organic detritus is the start of the detritus food chain, providing food to support the saprophages (Ross et al., 2003; Mintenbeck et al., 2007). In addition to being an important food source (Ezequiel et al., 2015), microphytobenthos forms extensive biofilms on surfaces and contributes to the stabilization of sediments (Hart and Lovvorn, 2003; Lavaud, 2007). In our study, organic detritus and microphytobenthos were not completely separated from the sediment, so the sediment compartment contained these two components. A. japonicas and M. arenaria were the typical herbivores that ingested the microphytobenthos in sediment, and C. japonica was an omnivore that could use both organic detritus and algae. The average contributions of sediment to the diets of A. japonicas, M. arenaria, and C. japonica exceeded 25%. Macroalgae in the intertidal and subtidal zone are another primary food source for the marine food web (Wieters et al., 2013; Fricke et al., 2014). Reefs in the study area around the island provided a favorable habitat for the growth of macroalgae. According to our food sources analysis, the average contributions of some macroalgae to consumers even exceeded 50%. Z. marina to O. gracilis, N. schrenckii, C. rustica, and C. affinis were 60% (range 32–82%), 50% (range 16–76%), 91% (range 88–94%), and 53% (range 20–78%), respectively. The contribution of U. conglobata to A. crassispina was 60% (range 44–74%). S. thunbergii, by comparison, contributed less and the highest value of its average contribution to consumers was just 25% (to C. japonica). According to previous studies (Newsome et al., 2004; Phillips et al., 2005; Phillips, 2012), we considered the three species of macroalgae as similar food sources to consumers for their similar habitat and features, and combined them as a posteriori group in the IsoSource analysis. Unexpectedly, the results calculated by IsoSource ranged significantly wider (p < 0.01) with higher uncertainty after combination. As shown in Fig. 4A–C, O. gracilis consumed Z. marina (the range of potential contribution was 32–82%) preferentially over U. conglobata (range 0–16%) and S. thunbergii (range 0–40%). After combination, the ranges of combined macroalgae for O. gracilis (Fig. 4D) were broad and diffuse from 32% to 100%, which limits meaningful conclusions about source contributions. As a result, combining the macroalgae into one food source was inappropriate for the study area. Our results indicated that these herbivores had different food preference on macroalgae and these three macroalgae showed unequal importance with Z. marina occupying the first position followed by U. conglobate and S. thunbergii. In coastal waters, Z. marina usually forms an enormous algal turf, which constitutes a system together with its epiphytes (Nelson and Waaland, 1997; Beal et al., 2004; Olsen et al., 2013 Mittermayr et al., 2014). Both substratum and epiphytes can provide an abundance of

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food sources (Keuskamp, 2004; Hays, 2005). In some cases algal turf supports high diversity with low productivity, whereas monospecific meadows can provide high productivity (Boström et al., 2014). In our study, the algal turf was not a multispecies assemblage but rather a monospecific food source with high productivity. In such a system, if the base macroalgae are destroyed, the biodiversity and biomass of the ecosystem would be reduced (Schmidt and Scheibling, 2007; Reich et al., 2012; Wieters et al., 2013; ArreguínSánchez and Ruiz-Barreiro, 2014; Fricke et al., 2014; Micheli et al., 2014). 4.2. Trophic structure The trophic level of each species was determined using its nitrogen isotope ratio. The two main factors that can affect the actual trophic level values are the TEF and the reference used. The TEF determines the interval distance between adjacent trophic levels (Govender et al., 2011; Sweeting et al., 2007; Valls et al., 2014), whereas the reference (e.g., primary producers (Cresson et al., 2014), primary consumers (Cresson et al., 2014; Valls et al., 2014), or other food sources such as particulate organic matter (Vinagre et al., 2008, 2011, 2012)) determines the threshold of the model structure. Any changes in these two factors will alter the trophic level values, so they must be chosen carefully. In general, the relative position of each species is more important than the specific trophic level values (Feng et al., 2014; Cresson et al., 2014; Du et al., 2015). Relative to the L-model, which neglected disparity of food sources, the relative positions of 11 of 15 invertebrates differed in the R-model. This finding indicates that the R-model was more appropriate for reflecting the real trophic structure when multiple food sources were provided to the herbivores, whereas the L-model with one reference was more suitable for the single food source condition (Vinagre et al., 2012) or for analyzing species at higher trophic levels (e.g., fishes) (Valls et al., 2014). The relative positions of only two fish species differed between the two models because most fishes at higher trophic levels ingest a wide array of food sources, which weakens the differences among original food sources. The ␦13 C results (Fig. 2) also indicated that the range of values narrowed with movement up the food change from initial food sources to carnivores (mainly fishes) (Valls et al., 2014; Viana et al., 2015). Herbivores and carnivores were analyzed using the R-model. A. japonicas and six species of shellfish with trophic level values <1.5 were considered to be typical herbivores. A. amurensis, O. oratoria, and O. minor were considered to be carnivores or scavengers, and the other invertebrates were mainly omnivores (Zheng and You, 2014). A. amurensis is a voracious generalist predator and is located at the highest trophic level among the invertebrates. This seastar is a major threat to benthic marine communities and commercial species in coastal waters (Beddingfield et al., 1993; Ross et al., 2003, 2006). According to our capture biomass data (Fig. 5), high proportions of A. amurensis were collected each season, and in spring it accounted for 80% of the total invertebrates. Shellfish species with poor moveability but high energy content were its main food source (Wong and Barbeau, 2005). Thus, the biomass of larger shellfish was reduced because of the predominance of A. amurensis in the habitat. The waters around Xiaoheishan Island are the major production area of A. japonicas and shellfish, and they provide a plentiful food source for A. amurensis. This predator-prey relationship has negatively impacted the stability of the ecosystem. For example, according to results of our questionnaires administered to local fishermen, wild abalone (diameter >12 cm), which once was as an important fishery resource in the study area, has been basically eliminated due to both human activity and predation by A. amurensis. The constant proliferation of A. amurensis likely

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Fig. 4. The ranges of potential contributions from Ulva conglobata, Sargassum thunbergii, and Zostera marina (A, B and C) to O. gracilis and the range after combination (D).The statistical bar chart based on IsoSource data, which show the potential contributions (x-axis, Source proportion) and their frequency (y-axis).

Fig. 5. Biomass variation of Asterias amurensis and Charybdis japonica among November, March, June, and August samples. Left: biomass, Right: proportion of biomass in total invertebrates.

will decrease the production of other major commercial shellfish species as well (Ross et al., 2003, 2006). C. japonica is another invertebrate species with high biomass, but it is not so abundant in every season. This crab is an omnivore that consumes mainly algae, small size invertebrates, and even larval fishes (Sudo et al., 2008). Our results indicate that it is an important fishery resource that is located at a high trophic level. In contrast to A. amurensis, C. japonica was mainly harvested in summer and autumn and was more sensitive to seasonal variation. Biomass increased significantly from June to August (Fig. 5) and then declined sharply due to harvesting and decreasing temperature. Based on this pattern, this species does not appear to over proliferate and does not appear to be a threat to the ecosystem. S. niphonius was at the highest trophic level of the fishes and of all species collected in this study. It is not only a top predator of smaller fishes but also an important fishery resource, providing food for local human inhabitants (Liu et al., 2014). As S. niphonius

is a mesopelagic fish species with strong migratory ability, we captured it only during the summer. With the continuous decrease in biodiversity caused by habitat deterioration in the study area (Lin et al., 2005; Zheng and You, 2014), further ecological conservation and restoration efforts are needed to maintain the suitability of the local coastal ecosystem as the main migration and feeding place for S. niphonius (Cardinale et al., 2006; Reich et al., 2012; Arreguín-Sánchez and Ruiz-Barreiro, 2014; Micheli et al., 2014). If S. niphonius stops utilizing the area, smaller fishes with better adaptability, such as Cryptocentrus filifer, Eupleurogrammus muticus, Acanthopagrus schlegelii, and Hexagrammos otakii will soon take its place. These fishes often are located at lower trophic levels and are discarded for their low fishery value (Watanabe, 2004; Eighani and Paighambari, 2013; Little et al., 2014). Certain species with small body size but at higher trophic levels, such as Cryptocentrus filifer, are harmful because they prey on eggs and larvae of fishery species and destroy the ecological balance of the waters around them. In

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summary, the extinction of large carnivores will result in the proliferation of smaller ones and increase the prey pressures on grazers and primary producers (Cardinale et al., 2006; Reich et al., 2012; Arreguín-Sánchez and Ruiz-Barreiro, 2014; Micheli et al., 2014). Subsequently, trophic relationships in the coastal ecosystem will change and the proportion of the food chain dominated by scavengers will increase (Sarica et al., 2005; Zheng and You, 2014). For these reasons, conservation efforts are needed to protect existing fish species in the Bohai Strait. 4.3. Conclusions Our results show that in coastal waters around Xiaoheishan Island, macroalgae provide the largest contribution among the food sources tested. O. gracilis, N. schrenckii, C. rustica, and Ch. affinis, preferentially consume Z. marina (p < 0.01), and A. crassispina preferentially eats U. conglobata (p < 0.01). The fish S. niphonius and the seastar A. amurensis are at the top trophic levels of fishes and invertebrates, and they are a major local fishery resource and grazer, respectively, in the study area. A. amurensis is a serious threat to other lower trophic level invertebrates, especially the shellfish that constitute economically important fisheries. Based on our results, we have two suggestions for conserving and restoring the local ecosystem. First, the biodiversity and distribution of algal turf (i.e., the base of the food web) should be improved (Boström et al., 2014). Second, numbers of the consumer A. amurensis must be restricted, and more conservation efforts should be focused on protecting economically important fish species such as S. niphonius. Acknowledgements This work was supported by the Public Science and Technology Research Funds Project of Ocean (grant no. 201305009-4), the NSFC-Shandong Joint Funds Project “Marine Ecology and Environmental Sciences” (grant no. U1406403), the National Natural Science Foundation of China (grant no. 41476091) and the Qingdao Municipal Science and Technology Plan Project (grant no. 13-14-234-jch). Pei Qu benefited from a post-doc grant given by the Qingdao Government. References Akin, S., Winemiller, K.O., 2008. Body size and trophic position in a temperate estuarine food web. Acta Oecol. 33 (2), 144–153, http://dx.doi.org/10.1016/j.actao. 2007.08.002. APEC Ocean and Fisheries Working Group, 2014. APEC Marine Sustainable Development Report. http://publications.apec.org/publication-detail.php?pub id=1552. Armbrecht, L.H., Thompson, P.A., Wright, S.W., Schaeffer, A., Roughan, M., Henderiks, J., Armand, L.K., 2015. Comparison of the cross-shelf phytoplankton distribution of two oceanographically distinct regions off Australia. J. Mar. Syst. 148, 26–38, http://dx.doi.org/10.1016/j.jmarsys.2015.02.002. Arreguín-Sánchez, F., Ruiz-Barreiro, T.M., 2014. Approaching a functional measure of vulnerability in marine ecosystems. Ecol. Indic. 45, 130–138, http://dx.doi. org/10.1016/j.ecolind.2014.04.009. Beal, B.F., Vadas Sr., R.L., Wright, W.A., Nickl, S., Lermond, N.W., 2004. Annual aboveground biomass and productivity estimates for intertidal eelgrass (Zostera marina L.) in Cobscook Bay, Maine. Northwest. Nat. 11 (2), 197–224, http://dx. doi.org/10.1656/1092-6194(2004)11[197:AABAPE]2.0.CO;2. Beddingfield, S.D., McClintock, J.B., Mcciintock, J.B., 1993. Feeding behavior of the sea star Astropecten articulatus (Echinodermata, Asteroidea): an evaluation of energy efficient foraging in a soft bottom predator. Mar. Biol. 115 (4), 669–676, http://dx.doi.org/10.1007/BF00349375. Ben-David, M., Flaherty, E.A., 2012. Stable isotopes in mammalian research: a beginner’s guide. J. Mammal. 93 (2), 312–328, http://dx.doi.org/10.1644/11-MAMMS-166.1. Bode, A., Carrera, P., Lens, S., 2003. The pelagic foodweb in the upwelling ecosystem of Galicia (NW Spain) during spring: natural abundance of stable carbon and nitrogen isotopes. ICES J. Mar. Sci. 60, 11–22, http://dx.doi.org/10.1006/2fjmsc. 2002.1326. Boström, C., Baden, S., Bockelmann, A.C., Dromph, K., Fredriksen, S., Gustafsson, C., Rinde, E., 2014. Distribution, structure and function of Nordic eelgrass (Zostera marina) ecosystems: implications for coastal management and conservation.

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