Elemental signature in otolith nuclei for stock discrimination of ...

Environ Biol Fish (2012) 95:431–443 DOI 10.1007/s10641-012-0032-3

Elemental signature in otolith nuclei for stock discrimination of anadromous tapertail anchovy (Coilia nasus) using laser ablation ICPMS Shuo-Zeng Dou & Yosuke Amano & Xin Yu & Liang Cao & Kotaro Shirai & Tsuguo Otake & Katsumi Tsukamoto

Received: 19 September 2011 / Accepted: 20 April 2012 / Published online: 5 May 2012 # Springer Science+Business Media B.V. 2012

Abstract The elemental signature in otolith nuclei was determined using laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS) for stock discrimination of adult anadromous tapertail anchovy, Coilia nasus, in five Chinese estuaries. Five elements (Na, Mg, K, Sr, and Ba) were well detected in the otolith nuclei of the adult fish. Results showed that the elemental composition in the otolith nuclei varied substantially among the estuaries. Age and fish length data showed no significant influences on the elemental concentration ratios across the sample sites. The Sr:Ca and Ba:Ca ratios were inter-site distinct and could be used as natal tags for discriminating among stocks. Discriminant function analyses (DFA) showed that these ratios can be used in discriminating the Liaohe River estuary (LD, 92.3 %), the Yangtze River estuary (CJ, 86.7 %), and the Yellow River estuary (HH, 76.9 %) samples with high S.-Z. Dou (*) : X. Yu : L. Cao Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, People’s Republic of China e-mail: [email protected] Y. Amano : K. Shirai : T. Otake : K. Tsukamoto Atmosphere and Ocean Research Institute, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba 277-8564, Japan X. Yu Graduate School, Chinese Academy of Sciences, Beijing 100049, People’s Republic of China

classification accuracy, followed by the Haihe River estuary (BH, 58.3 %) and the Daguhe River estuary (JZ, 46.2 %) samples. An overall classification accuracy rate of 72.7 % from the discriminant functions indicated that elemental fingerprinting appeared to have the potential to discriminate between tapertail anchovy stocks in these estuaries. Keywords Otolith chemistry . Elemental fingerprinting . Population discrimination . Anadromous fish . Chinese estuaries

Introduction In the past two decades, the study of otolith chemistry and application of elemental fingerprinting have been proven to be a useful natural marker in reconstructing the migratory history of individual fish and discriminating among populations (Edmonds et al. 1991; Thresher et al. 1994; Campana 1999; Kennedy et al. 2000; Gillanders 2002). Several papers have critically evaluated the recent advances in this field (Campana 1999; Thresher 1999; Campana and Thorrold 2001; Elsdon and Gillanders 2003; Elsdon et al. 2008). Otolith elemental fingerprinting is largely based on the assumptions that the environment (e.g., water chemistry) influences the incorporation of elements into the otolith and that once these elements were deposited, they are not altered or reabsorbed due to the metabolic inertness of the otolith. Therefore, trace

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elements in otoliths can be regarded as natural tags of environmental history, albeit variations in ambient water (e.g., temperature, salinity, and chemical composition) and variability in physiology among fish individuals may considerably influence the otolith microchemistry (Kalish 1989; Campana 1999; Elsdon and Gillanders 2003). More importantly, elemental fingerprinting is becoming more useful when it is combined with other methods, such as otolith morphometrics and genetic techniques (Longmore et al. 2010; Smith and Campana 2010; Clarke et al. 2011). Laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS) is often used to examine otolith chemical composition using a focused beam because it combines the beam capacities of a highenergy laser with the rapid and accurate analytical capacities of ICPMS (Campana 1999; Thorrold and Shuttleworth 2000; Gillanders and Joyce 2005; Stransky et al. 2005). Because the otolith nucleus roughly corresponds to the fish spawning and hatching, the chemistry of otolith nuclei detected with LAICPMS can be used as a natural marker of the spawning and natal home for both marine and anadromous fish (Campana et al. 1994; Thorrold et al. 1998; Brophy et al. 2003; Ashford et al. 2006). In contrast to marine fish species, one advantage for elemental fingerprinting in anadromous fish is that their natal rivers can be characterized by a unique chemical composition, suggesting that trace element uptake onto the otolith nucleus of anadromous fish may show distinct inter-site variation. Therefore, elemental fingerprinting in otolith nuclei of anadromous fish could serve as an effective delineator for discriminating among anadromous stocks (Thorrold et al. 1998). Tapertail anchovy, Coilia nasus, is an anadromous clupeid fish that inhabits the major estuaries along the Chinese coast. It was once an important commercial fishery species in China. Since the 1980s, however, the wild populations have drastically decreased or disappeared in most estuaries (Yuan and Qin 1984; Luo and Shen 1994). Aside from anadromous stocks, landlocked stocks that reside in freshwater over the entire life were also reported in some affiliated lakes of the Yangtze River, such as the Taihu lake (Cheng et al. 2005; Yang et al. 2006; Liu et al. 2008). Anadromous adults start to migrate upstream at about 2 year old from March to April (over 7°C SST and 17–30‰ salinity in the estuarine waters), during which sexual maturity is rapidly developed. The matured fish

Environ Biol Fish (2012) 95:431–443

usually spawn in still waters at 15 to 27.5°C from May to September, depending on spawning sites and timing. After spawning, the fish stay nearby for a certain period of time and then move downstream into the local estuaries to grow before the end of winter (Cai et al. 1980; Yuan and Qin 1984; Yuen 1987; Chen 1991; Liu et al. 2008). Although it is generally known that larvae drift into the estuarine areas and reside there until reaching sexual maturity for upstream spawning migration, the early life history, particularly the downstream larval transportation (e.g., freshwater duration and larval drift process) is poorly understood. To date, the tapertail anchovy populations in the Chinese waters, which is essential for fishery management, are not well documented. Because the Chinese rivers usually have distinct chemical properties (Hu et al. 1982; Liu 1985; Chen 2006; Wang et al. 2009), it is possible that the site-dependent elemental signatures from the otolith nuclei will show the natal sources of the tapertail anchovy. This provides the primary premise for elemental fingerprinting in discriminating among stocks. In the present study, we investigated the elemental composition from the otolith nuclei of adult tapertail anchovy collected from five Chinese estuaries to test if elemental fingerprinting can act as effective natural tags for discriminating among the stocks. To achieve this goal, otolith elemental concentrations were probed and analyzed using LA-ICPMS to look at their inter-site differences. Intra-estuary data of different age groups in each sample site was analyzed to explore if the otolith elemental signatures of the fish born in a specific river may undergo dramatic inter-annual variation.

Materials and methods Sample collection Samples used in this study were from one otolith collection of the Chinese Academy of Sciences, which was conducted during the fishery research surveys using otter trawl gear along the Chinese coastal waters in the 1980s. This collection included samples from the Liaohe River estuary (LD), the Haihe River estuary (BH), the Yellow River estuary (HH), the Daguhe River estuary (JZ), and the Yangtze River estuary (CJ), respectively (Table 1; Fig. 1). Immediately after capture, the fish were labeled and frozen for subsequent


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Table 1 Summary of tapertail anchovy samples collected in the five sample sites (codes as in Fig. 1) for chemistry analysis using LAICPMS (BL, body length; BW, body weight; W, otolith weight; Dmax, major axis diameter; Dmin, minor axis diameter) Sampling site

Sampling date

n

Fish samples BL (mm)

Otolith BW (g)

Age (yr)

W (mg)

Dmax (μm)

Dmin (μm)

LD

1983

13

279–402

65–222

2–4

12.3–20.4

4012–4965

3740–4535

BH

1983

12

282–404

72–220

2–4

13.0–21.5

4206–5087

3980–4626

HH

1983

13

270–387

65–218

2–4

11.7–19.8

4131–5012

3858–4492

JZ

1983

13

287–385

76–198

2–4

13.1–19.6

4089–4526

3890–4417

CJ

1985

15

262–372

59–204

2–4

11.3–19.2

3970–4673

3755–4318

biological analysis, including otolith removal. In the laboratory, fish length, weight, sex, maturity status, and age (estimated according to annual rings in scales or the empirical age-length relation) were determined and recorded. Sagittal otoliths were removed from each fish, cleaned of adhering tissue in distilled water, and stored dry in sealed glass vials until further examination. The otolith sampling program of the present study was designed to include fish of known stocks. As previously described, adult tapertail anchovy tend to return to the natal rivers to spawn and then migrate downstream to reside in the local estuarine areas to feed. To minimize the potential influence of stock mixing, otoliths were collected from the adult fish that had spawned (based on the sexual maturity) and resided in waters near the specific river mouths (according to sampling site). Samples are thus believed to be reasonable representations of discrete stocks. To examine the inter-annual variation in elemental composition of the otolith nuclei, fish samples of 2–4 year old (4–5 individuals representing each age cohort, i.e., born in different years) within a geographical stock were chosen for elemental analyses. A total of 66 otoliths were collected and analyzed for otolith nuclei using LA-ICPMS (Table 1). Otolith preparation Sagittal otoliths were sonicated in distilled water for 10 min to clean the otolith surface, and then were oven-dried overnight at 35°C. Samples were measured for the longest and shortest axes to the nearest 1 μm under a microscope (Nikon, SMZ-1000) and were weighed to the nearest 0.1 mg using an electrical balance (Sartorius BS-124 S). Each otolith was

embedded in epoxy resin (Struers, Epofix), mounted on a glass slide, and then cut and ground to expose the core on the sagittal plane using a grinding machine that was equipped with diamond cup wheels (Discoplan-TS; 70 μm, Struers; 13 μm, Sanwa Diamond, Tokyo). Because concentric rays from the core to the edge of the otolith can be clearly visible under microscopy, the otolith nucleus can be identified (Fig. 2). After grinding, otolith sections with 400– 600 μm thickness were polished with suspension (OPS, Struers) on an automated polishing wheel (Struers, Rotopol-35) to get finer and more exposed surfaces. To avoid possible contamination, otolith samples were cleaned in sonicated Milli-Q super water (Millipore S.A.S.) in the present study. After decontamination, sectioned otoliths were oven-dried at 35°C, and were randomly numbered across sample sites and placed in clean sealable plastic boxes until chemistry analyses. Chemistry analysis For LA-ICPMS analysis, concentrations of otolith elements were determined on a Merchantek UP-213 Nd: YAG deep UV laser ablation system (New Wave Research, Fremont, CA) coupled with an Agilent 7,500 s ICPMS (Agilent Technologies, Tokyo). The lasers were operated at a wavelength of 213 nm with a pulse rate of 10 Hz and an energy density of 0.3 Jcm−2. In each analysis session, 11–12 otolith sections, randomly numbered and selected from all sample groups, plus a reference standard glass (NIST 612, National Institute of Standard and Technology), were mounted on a carrying stage and then fixed in the sealed chamber where otolith material ablation took place. Otolith analysis sequences were randomized so that the order of analysis for any one sample group

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Fig. 1 Map showing estuaries in which tapertail anchovy samples were collected. LD, the Liaohe River estuary; BH, the Haihe River estuary; HH, the Yellow River estuary; JZ, the Daguhe River estuary; CJ, the Yangtze River estuary

was spread over the entire analysis sequence. When an otolith is analyzed on an ICPMS, instrument drift occurs due to the buildup of Ca ion on the instrument, as well as the changes in temperature, plasma, and

electronics, resulting in low detection limits of the elements (Campana et al. 1994; Elsdon and Gillanders 2002). To minimize the potential effects of instrument drift on the elemental analysis, the


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Fig. 2 Photographs showing the reflected-light microstructures of an adult tapertail anchovy otolith section (a). SEM photographs (b, × 30; c, × 400) showing the laser ablation points on the otolith nucleus for chemical analysis on LA-ICPMS

concentric rays

nucleus area

a c

b

check

standard was analyzed at the beginning, the middle (after ablating the first 6 otoliths), and the end of each analysis session. Ablation points in both the standard and the otoliths were positioned via a computer connected to the UP-213 using the default New Weave Research laser ablation system software. In the present study, the otolith nucleus region was defined as the round area that spread at a radius of 190–230 μm from the core, which was measured under microscope for each otolith section. The nucleus region was morphologically marked with its distinct circumference, from which concentric rays around the nucleus occurred outwards the edge (Fig. 2). To precisely locate the otolith

laser point diameter: 40 µm depth: 15 µm distance from core: 100 µm

cores for laser ablating, we took photos of each otolith section under microscope before chemical analysis so that the unique otolith characteristics (e.g., the concentric rays from the core outwards to the edge, the outline of the core area, or even the ‘accidental markers’ created during otolith preparation) could be referred for identifying the nucleus in the laser ablation system. On each otolith section, one point in the otolith core and four other points that were evenly positioned at a distance of 100 μm from the core were laser-ablated and chemically analyzed. The four ablations around the core ablation were expected to fall safely within the otolith nucleus area. After elemental analysis, otolith sections were

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examined under microscope to confirm the laser ablation locations or by scanning electron microscopy (SEM, Keyence VE-8800) to verify the validity of each laser ablation (Fig. 2). In this process, invalid laser ablation data, if any, could be excluded from statistical analysis. The average values of elemental data of the five ablations were assumed to accurately represent the elemental composition of the otolith nucleus. The ablation craters produced had a diameter of appropriately 40 μm with a depth of about 15 μm, and the dwell time was 15 s. The ablated material was transported from the ablation chamber to the ICPMS, via a settlement cell, by an argon (Ar) and helium (He) gas stream. The ablation chamber was purged for 90 s after each opening to remove any background gas or sample particles that may have contaminated future samplings. Data were collected using the default Agilent 7,500 s ICPMS software. The concentrations of each element were standardized to calcium by expressing concentrations of elements as ratios to Ca. To determine the actual limits of detection (LODs), blank ablations that only consisted of measuring Ar and He gases were conducted before and after each analysis session for approximately 120 s. Preliminary analyses had identified five elements (Na, Mg, K, Sr, and Ba), which were consistently detectable in the otolith nuclei. Relative standard deviations (% RSD), based on replicated measurements of the calibration standard, were calculated to reflect the level of precision achieved for each element. Data analysis Since K and Na are usually not bound to the lattice of the otolith but are weakly occluded in the interstitial spaces, they are easily leached during otolith preparation (grinding, washing, and polishing etc.). Furthermore, the concentration of these two elements in the otolith is under strong physiological regulation. For these reasons, they are believed to be unsuitable as stable elemental signatures in stock identification studies (Thresher et al. 1994; Proctor et al. 1995). Thus elemental data of K:Ca and Na:Ca were excluded from the statistical analyses in the present study. The elemental concentration ratios (Mg:Ca, Ba: Ca, and Sr:Ca) of the analytical data were first


examined for within-group normality (KolmogorovSmirnov’s test) and for homogeneity of variances among groups (Levene’s test). When both assumptions were met, one-way ANOVA was applied to examine the univariate differences in concentration ratios of each element among the sample sites to test their spatial differences. One-way ANOVA was also applied to examine the univariate differences in concentration ratios of each element among the age groups in each stock to explore their inter-annual variation so that the possible effects of inter-annual differences on spatial differences could be evaluated. Post hoc multiple comparisons using Bonferroni test were applied to compare the means between groups, when significant differences were computed. Furthermore, to assess the possible age effects on the intra-site differences of the elemental concentration ratios, two-way ANOVA was performed on the data of each elemental concentration ratio across the sample sites. Analyses of covariance (ANCOVA), with fish length as a covariate, were separately run on the concentration ratios of each element among sample sites to examine the possible fish length effects on otolith elemental compositions among sampling sites. To achieve this, all the interactions between site and fish length in each element were tested using the custom model. If no significant interactions were observed in all the elemental data, the full factorial model was then applied for ANCOVA to examine the fish length effect on the elemental concentration ratios. To determine the ability of elemental signatures to correctly classify the samples, discriminant function analysis (DFA, Fisher’s coefficient) was conducted to identify the elements that contributed the most to the spatial differences of the chemical signatures. Three elements (i.e., Mg, Ba, and Sr) that are likely to be influenced by the environment were used for DFA in the entering independent together method. Pooled within-group matrices were produced to examine the correlation and covariance among the concentration data of the three elements. Combined-groups plotting of the first two discriminant function axes against each other and the predicted group membership (cross-validated classification) were generated to reflect the accuracy of classifications. Statistical analyses were performed on SPSS 17.0 for windows (SPSS Inc.) at a significance level of P 0.05 in all cases) and homogeneity of variances among groups (Levene’s test, P>0.05 in all cases), except for the Mg:Ca and the Ba:Ca ratios in the JZ sample. The Sr:Ca and Ba:Ca ratios showed significant inter-site differences (ANOVA, P < 0.05 in both elements), whereas Mg:Ca ratio did not significantly differ among sample sites (ANOVA, P > 0.05; Table 2; Fig. 3). The Ba:Ca ratios of the LD and HH samples were significantly lower than those of other samples (Bonferroni test, P0.05 in all cases; Fig. 3). The Sr:Ca ratios were not significantly different between LD and CJ samples, JZ and BH samples, and JZ and HH samples (Bonferroni test, P>0.05 in all cases; Fig. 3), but significantly differed among other samples (Bonferroni test, P0.05; Table 3; Fig. 4), except for the Mg:Ca ratio (P0.05 in all elements; Table 4). Similarly, neither Table 2 Results of one-way ANOVA running on the elemental concentration ratios in the otolith nuclei of tapertail anchovy collected in the five sample sites

significant interactions between site and fish length nor fish length significantly affected the three elemental concentration ratios across the sample sites (ANCOVA, P> 0.05 in all elements; Table 4). Pooled within-group matrices generated low correlations between the concentration ratios of the three elements included in DFA (−0.065 between Mg:Ca and Ba:Ca; 0.096 between Mg:Ca and 0.179 between Sr:Ca and Ba:Ca), indicating that the three elemental concentration ratios were not closely correlated. The main DFA results were summarized in Table 5 and Fig. 5. The scores of the first canonical discriminant function (F1, eigenvalue09.31) explained 95.7 % of the variance and could easily discriminate the LD and CJ samples from other samples. It could marginally discriminate the HH and BH samples as well. F1 was closely correlated (canonical correlation00.95) to the three elemental concentration ratios with Sr:Ca ratio as the greatest contributor to the function scores (Fisher’s coefficient 01.022). The scores of function 2 (F2, eigenvalue00.37) could effectively discriminate between the LD and CJ samples and marginally discriminate the HH and BH samples, but it explained only 3.8 % of the variance. Ba:Ca contributed the most to F2 scores (Fisher’s coefficient00.942). Scores of both F1 and F2 through F3 significantly differed among sample sites (Wilks’ lambda test, P