Next Article in Journal
A Review of Neural Networks for Air Temperature Forecasting
Previous Article in Journal
Migrations of Young Fish in Anthropogenically Transformed Rivers: Responses of Cyprinids and Percids to Ecological Filters and Barriers
Open AccessArticle

Otolith Fingerprints and Tissue Stable Isotope Information Enable Allocation of Juvenile Fishes to Different Nursery Areas

1
Laboratory of Ichthyology and Coastal Fisheries, Institute of Oceanography and Fisheries, Šetalište I. Meštovića 63, 21000 Split, Croatia
2
Laboratory of Fisheries Science and Management of Pelagic and Demersal Resources, Institute of Oceanography and Fisheries, Šetalište I. Meštovića 63, 21000 Split, Croatia
3
Laboratory of Chemical Oceanography and Sedimentology of the Sea, Institute of Oceanography and Fisheries, Šetalište I. Meštovića 63, 21000 Split, Croatia
4
Institute for Geosciences, Johannes Gutenberg University, SaarstraBe 21, 55131 Mainz, Germany
5
Department of Bioscience, Ny Munkegade 114, 1540 Building, Aarhus University, 8000 Aarhus, Denmark
*
Author to whom correspondence should be addressed.
Academic Editor: George Kontakiotis
Water 2021, 13(9), 1293; https://doi.org/10.3390/w13091293
Received: 8 April 2021 / Revised: 30 April 2021 / Accepted: 1 May 2021 / Published: 4 May 2021

Abstract

Integrated otolith chemistry and muscle tissue stable isotope analyses were performed to allocate juvenile Diplodus puntazzo and Diplodus vulgaris to nurseries in the Adriatic Sea. Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) was used to quantify the concentrations of chemical elements in the otoliths. Fish muscle samples were analysed for δ13C and δ15N. In general, Ba/Ca and Sr/Ca ratios and isotopes varied between sites and species. Values of δ13C and δ15N were significantly different between species and sites. Multivariate analysis detected a significant difference in the element signature between species while there was no evidence for a significant interaction for sites. A clear pattern across the four groups of interest, D. puntazzo_Estuary > D. vulgaris_Estuary > D. puntazzo_Coastal > D. vulgaris_Coastal, following decreases in δ13C, and increases in δ15N were found. It seems that these species are feeding on the same local food web within more productive estuarine site while at costal site, feeding segregation among investigated species is evident. Both species were re-allocated correctly to the estuarine waters based on the otolith chemistry and stable isotopes information and higher value of δ15N. Combining otolith chemistry with tissue isotope ratios of juvenile fish provided complementary information on nursery habitat use at different spatial scales and elucidated ecological and environmental linkages.
Keywords: Diplodus vulgaris; Diplodus puntazzo; geochemistry; trophic relation; essential habitats; Adriatic Sea Diplodus vulgaris; Diplodus puntazzo; geochemistry; trophic relation; essential habitats; Adriatic Sea

1. Introduction

Elucidating movement and life-history characteristics of marine organism is of crucial importance for their management and conservation [1,2,3] and the knowledge gap still represents a challenge to scientists working on this issue. Nearshore estuarine and marine ecosystems such as seagrass meadows, marshes and mangrove forests are often referred to as nursery grounds [4] due their positive effects on the diversity and productivity of fish and invertebrates in coastal waters. The greater food abundance and lower predation risk of these shallow habitats support high juvenile densities and may contribute juveniles or sub-adults to adult populations [5]. Coastal ecosystems are highly structured and fragile environments, and many valuable coastal systems are under high anthropogenic pressures, resulting in species loss and habitat degradation [6,7,8]. In particular, the highly populated Mediterranean coastal areas are becoming progressively degraded, and increasing anthropogenic pressures and destructive and illegal fisheries are causing severe repercussions [9]. The Adriatic Sea, particularly its northern most part, is considered the most exploited basin of Mediterranean Sea [10].
The life history of many marine fishes begins with coastal spawning followed by larval ingress to nursery areas, which is influenced by physical oceanographic processes [4,11,12]. These areas provide critical habitats for larvae to settle and develop into juveniles, before leaving to join adult populations during their development to young adults [4,13,14]. Understanding how a specific nursery shapes juvenile behavior and consequently growth, and how connectivity determines the spatial scale between fish populations, population dynamics, and stock structure is ultimately necessary for conservation and management strategies [12]. This essential knowledge is increasingly being obtained from chemical analysis of fish otoliths.
The growing otoliths incorporate and store elements from the surrounding environment throughout the organism’s life [15]. The ambient concentrations of these elements are influenced by a range of external factors that vary at both spatial and temporal scales [12]. Consequently, the microchemistry of otoliths from different environmental conditions vary in their elemental composition [16]. These elemental fingerprints are widely used to successfully determine population structure [17], define estuarine nurseries [18] and asses’ connectivity between juvenile and adult populations [19,20].
In the marine environment, Ba/Ca, Mg/Ca, U/Ca, B/Ca, and Sr/Ca in various biological calcareous tissues (i.e., otolith) show strong correlations with ocean water temperatures [21,22,23,24]. Some elements (e.g., strontium and barium) are used successfully to reconstruct environmental and coastal-estuary migration histories for individual fish [25], as their concentrations reflect local availability in seawater. There are documented differences observed in the elemental ratios of otoliths of fish moving through freshwater, estuarine, and marine waters, with higher Sr/Ca found in marine and higher Ba/Ca found in freshwater [26,27]. A positive relationship between the Sr content of otoliths and ambient salinity has also been observed, though the magnitude of this effect varies with ambient water Sr concentrations [27,28,29,30,31]. Other elements, such as K, Na, Zn, and Mn, are likely to be mediated by the physiological regulation of organisms [32,33,34].
Additional information on the biotic environment can be obtained from stable isotope analysis of soft tissues and otoliths. These data reflect fish diet and can be used to determine movement from and within estuaries [35,36,37], migratory patterns [38,39], and habitat use [40,41]. Reis-Santos et al. [20] concluded existence of relationship between distinct isotope ratios of food sources and fish feeding in certain habitats primary producer groups exhibit distinctive isotope ratios that are propagated through local food webs. Thus, non-migratory individuals, such as juveniles within nurseries [33,42], are expected to exhibit stable isotope ratios in equilibrium with the local food webs, while transient individuals moving between habitats should display intermediate or greater isotope variation [36,43,44]. However, there are few studies that use both tissue stable isotopes and otolith chemistry to assess connectivity or population structure [39,45,46,47], though one study conducted an integral assessment using combined tissue isotope and otolith chemistry to determine connectivity within an estuary for two juvenile fish species [20].
Sparid fishes are highly valuable fish resources in the Mediterranean Sea [48]. Those of the genus Diplodus, including the common two-banded sea bream, Diplodus vulgaris (Geoffroy Saint-Hilaire, 1817) and the sharpsnout seabream, Diplodus puntazzo (Walbaum, 1792) inhabit coastal habitats from shallow waters to depths >50 m, with reproduction taking place in deep waters [49]. After one month of pelagic larval life, they settle in very shallow benthic habitats where they remain for several months before dispersing from the nurseries to join adults [50]. Settlement intensity varies spatially, temporally and among species, with D. puntazzo settling in October–November while D. vulgaris settles in two pulses, the first in November–December and the second in January–February [51,52]. However, these species are contemporaneous in nurseries [53], thus confirming the successful temporal partitioning of habitat use between different Diplodus species [51].
Juvenile fish from the genus Diplodus have been previously investigated in three studies. Correira et al. [33] applied solution-based analyses on whole otoliths and laser ablation analysis of otolith cores to obtain insight into the population structure of D. vulgaris. Di Franco et al. [54] investigated within-otolith variability in chemical fingerprints and found that individuals at the same site can show significant variability in elemental uptake. The possible use of otolith fingerprints as natural tags for the identification of juvenile D. sargus and D. vulgaris in ports were studied by Bouchoucha et al. [34]. However, there are no reports of any otolith chemistry studies using D. puntazzo. Other authors have recently conducted chemical analyses of juvenile fish otoliths [12,20,55,56,57,58,59].
The aim of the present study was to use both otolith chemistry and muscle stable isotope composition to allocate two closely related juveniles of D. vulgaris and D. puntazzo (age—zero) to two different nursery sites: an estuarine and a coastal (marine) nursery. We hypothesized that these closely related fish species, simultaneously present in the same nursery areas, exhibit different chemical signatures in estuarine and coastal waters as a reflection of their different behavior in foraging prey in specific nursery, which should consequently allow for the proper allocation of juveniles to a specific nursery. Such knowledge can help to accurately identify nursery origin and determine the relative contributions of individual nurseries to the coastal population of these species.

2. Materials and Methods

2.1. Study Locations and Fish Collection

Newly settled juveniles of sharpsnout seabream, Diplodus puntazzo and common two-banded sea bream Diplodus vulgaris were collected from two sites along the eastern Adriatic (Figure 1a,b): the estuarine site Pantan and coastal site Sovlja (Figure 1c), as sites known to be essential nursery areas for these species [60,61,62]. They are separated by a distance of 200 km and hydrologically represent different water types in the Adriatic Sea. The Pantan estuary is near Split, and receives the waters of the Pantan River, exhibiting variable salinity gradients during the year (transitional waters), with a muddy-sandy bottom partially overgrown with Zostera marina. Sovlja Cove is near Šibenik and is a typical coastal site, with a partially rocky-sandy bed with patches of Cymodocea nodosa meadows, and less influence of freshwater springs (Table 1).
Samples of juvenile fish specimens were collected using a special constructed small shore seine net (L = 25 m; mesh size 4 mm) in June 2018. Three hauls for each site were performed to collect an adequate number of specimens. To avoid temporal variation in otolith chemistry and stable isotope analysis, sampling was carried out in the shortest possible time. At both sites, Pantan and Sovlja, both species, Diplodus vulgaris and Diplodus puntazzo, were present with similar abundance (up to 7 specimens in each haul) and similar sizes (from 38 to 71 mm and 31 to 72 mm, respectively). Additionally, 5 individuals per site of blue mussel, Mytilus galloprovincialis were sampled. Upon collection, specimens were transported to the laboratory and frozen until analysis. For the analysis, total length (TL; cm) and weight (TW; g) were recorded and specimens were dissected to extract white fish muscle tissue and otoliths for stable isotope analyses and otolith chemistry, respectively.

2.2. Sample Preparation

Sagittal otoliths (hereafter: otoliths) were removed, rinsed with water, cleaned of soft tissue with plastic dissecting pins, washed with Milli-Q water, air dried, and stored in labelled plastic vials. The otoliths were embedded in epoxy resin (Buehler EpoThin 2) and sectioned transversely through the core using a low-speed precision saw (Buehler Isomet 1000) equipped with a 0.4 mm thick diamond-coated blade. Otoliths sections were affixed to glass slides using clear Crystalbond and subsequently ground (F800 and F1200 grit SiC powder) and polished using a soft cloth impregnated with diamond paste (3 μm). After polishing, otoliths were rinsed and cleaned ultrasonically (2 min).
Muscle tissue of M. galloprovincialis was used as appropriate baseline since sedentary bivalves can be useful indicators of isotopic baseline [63] in the coastal ecosystem. That is needed to integrate the variation in isotope values at the base of food webs [64] when trophic status of specific marine organisms is requested while data of prey spectra trophic status is unknown.
Standard preparation for stable isotope analysis consisted of oven drying samples at 60 °C until constant weight. Tissues were then ground to a fine powder with a mortar and pestle and approximately 1 mg of sample was weighed into tin cups. Lipid extraction of fish muscle samples was not performed as individuals were juveniles and body lipid was uniformly low (<5%) and insufficient to bias carbon stable isotope analysis or require corrections as suggested by Post et al. [65].

2.3. Element and Stable Isotopes Analyses

2.3.1. LA-ICP-MS Analysis of Otoliths

The concentrations of Li, Na, Ca, Mg, Mn, Zn, Sr, Mo, Ba, Pb, and U were determined using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) in line scan mode, through the otolith core from edge to edge (Figure 2). Each point on the otolith corresponds to a specific point on laser trajectory enabling selection of the otolith part to be analyzed.
Analyses were performed at the Institute of Geosciences, JGU, Mainz, Germany, using an ESI NWR193 ArF excimer laser ablation system equipped with the TwoVol2 ablation cell, operating at 193 nm wavelength, coupled to an Agilent 7500ce quadrupole ICP-MS. Sample surfaces were preablated prior to each line scan to prevent potential surface contamination. The laser repetition rate was 7 Hz and laser energy on samples was about 3 J/cm2. Background intensities were measured for 15 s. Line scans were carried out at a scan speed of 5 μm/s, using a rectangular beam of 50 x 40 µm (preablation beam 80 × 40 μm). Synthetic glass NIST SRM 612 (National Institute of Standards and Technology; Gaithersburg, Maryland, United States ) was used to calibrate element concentrations of otolith samples and quality control materials (QCMs) (USGS MACS-3, USGS BCR-2G, NIST SRM 610) (Table 2) were used to monitor accuracy and precision of the LA-ICP-MS analysis applying the preferred values available from the GeoReM database ([66], application version 26; compared with [67,68,69]). Signals were monitored in time-resolved mode and processed using an in-house Excel spreadsheet [70]. Details of the calculations are given in Mischel et al. [71]. The concentration of 43Ca as an internal standard in otoliths was taken as 38.8% by weight or 388,000 ppm following the determination of otolith Ca concentration [72]. Concentrations determined on the otoliths were converted to molar concentrations and standardized to calcium.

2.3.2. Stable Isotope Analyses of Muscle Tissue

Muscle samples were analyzed for δ13C and δ15N using a PDZ Europa ANCA-GSL elemental analyser interfaced to a PDZ Europa 20–20 isotope ratio mass spectrometer (Sercon Ltd., Cheshire, UK) at the UC Davis Stable Isotope Facility. Samples were combusted at 1000 °C in a reactor packed with chromium oxide and silvered copper oxide. Following combustion, oxides were removed in a reduction reactor (reduced copper at 650 °C) and the helium carrier was released through a water trap (magnesium perchlorate and phosphorous pentoxide). N2 and CO2 were separated on a Carbosieve GC column (65 °C, 65 mL/min) before entering the Isotope-ratio mass spectrometry (IRMS). Stable isotopes were expressed in standard delta (δ) notation as parts per thousand (‰).
During analysis, samples were interspersed with several replicates of at least four different laboratory reference materials, previously calibrated against international reference materials, including: IAEA-600, USGS-40, USGS-41, USGS-42, USGS-43, USGS-61, USGS-64, and USGS-65 reference materials. A sample’s provisional isotope ratio was measured relative to the reference gas peak analyzed against each sample. These provisional values were finalized by correcting the values for the entire batch based on the known values of the included laboratory reference materials. The long term standard deviation is 0.2 ‰ for 13C and 0.3 ‰ for 15N [73].

2.4. Data Analysis

Element-to-Ca data for Li, Na, Mg, Ba, Sr, Mn, Zn, Mo, Pb, and U were determined for all specimens. Most of these element-to-Ca data were below quantification and detection limits. Some ratios including Na/Ca, Mg/Ca, Zn/Ca, Mn/Ca, and Li/Ca exceeded the detection limit in several otoliths, although they were below the quantification limit in most samples. Ba/Ca and Sr/Ca ratios were above the detection and quantification limits [74] and thus subjected to further analysis. Element concentration data Ba/Ca and Sr/Ca ratios for D. vulgaris and D. puntazzo samples exceeding 31-point (31-pt) running averages by 5σ were considered outliers and excluded from further analysis (see [75,76]). For data visualization, element linear raster was smoothed using a 31-pt arithmetic running average.
Differences in otolith chemistry composition were evaluated via the permutational analysis of variance (PERMANOVA) using Manhattan distance dissimilarity matrices [77], since both elements were on very comparable measurement scales. The metric Multidimensional Scaling (mMDS) ordination were used for showing the patterns across the four groups of interest and the contribution of each element isotope composition to the obtained distance. Starting point for data selection on linear raster was 200 μm which corresponds approximately to the third month of fish juvenile life according to settlement mark [34,51,78,79]. We calculated the Manhattan measure separately for each of the barium and strontium variable sets and then averaged the resulting Manhattan distance matrices to get a single overall matrix that measures the differences between fish species for the overall otolith signatures for both elements. Differences in muscle δ13C and δ15N isotope ratios were normalized and evaluated via PERMANOVA using Euclidean distance dissimilarity matrices.
Canonical analysis of principal coordinates (CAP) was used to estimate the accuracy of otolith element signatures and muscle stable isotopes in classifying fish to their collection site. CAP is a routine for performing canonical analysis by calculating principal coordinates from the resemblance matrix among groups of samples to predict group membership, positions of samples along another single continuous variable or finding axes having maximum correlations with some other set of variables [77].
CAP analyses were run separately for each of the two factors: “Site” and “Species”. The CAP routine output scores were then merged for both factors. Finally, we relate the distance matrix based on otoliths to the distance matrix based on isotopes and performed CAP as a canonical correlation analysis of the otolith distance matrix on the isotope (continuous quantitative) values [77].
Univariate permutational analysis of variance (PERMANOVA) was used to test the difference of site or species effects on elemental data obtained from otoliths and stable isotope data obtained from white muscle. Statistical analysis was done using PRIMER (V. 7.0.13; Auckland, NZ) and graphs were prepared using SigmaPlot (v. 13.0; Systat Software Inc, San Jose, CA, USA).

3. Results

Juveniles of D. puntazzo ranged in TL from 5.2 to 6.1 cm (mean 5.58 ± SD 0.35 cm) and weight from 2.32 to 3.78 g (mean 2.95 ± SD 0.6 g), and from 3.1 to 7.2 cm (mean 5.40 ± SD 1.66 cm) and 0.42 to 5.68 g (mean 2.51 ± SD 2.48), at sites Pantan and Sovlja, respectively. Juveniles of D. vulgaris ranged in TL from 4.3 to 7.1 cm (mean 5.37 ± SD 1.23 cm) and weight from 1.17 to 5.50 g (mean 2.70 ± SD 1.95 g), and from 3.8 and 6.2 cm (mean 4.74 ± SD 1.08 cm), and 0.8 to 4.19 g (mean 1.82 ± SD 1.43 g), at sites Pantan and Sovlja, respectively.

3.1. Otolith Trace Element Chemistry

Ba/Ca and Sr/Ca ratios varied between sites and species. Data for 31-pt moving averages for Ba/Ca in D. puntazzo ranged from 0.30 to 5.78 µmol/mol (median 2.6 µmol/mol) and 0.35 to 4.78 µmol/mol (median 1.59 µmol/mol) for Sovlja and Pantan, respectively (Figure 3A). For D. vulgaris, 31 pt moving averages for Ba/Ca ranged from 0.46 to 8.61 µmol/mol (median 2.76 µmol/mol) for Sovlja and 0.12 to 3.7 µmol/mol (median 1.4 µmol/mol) for Pantan (Figure 3A). The median values of Ba/Ca were higher for both species, D. vulgaris and D. puntazzo, at Sovlja while spatial differences in Ba concentration was not significant neither between species (t = 1.345; p = 0.066), neither between sites (t = 1.247; p = 0.137).
Data for 31 pt moving averages for Sr/Ca values in D. puntazzo ranged from 1.47 to 2.3 mmol/mol (median 1.89 mmol/mol) and 1.52 to 2.20 mmol/mol (median 1.87 mmol/mol) for Sovlja and Pantan, respectively (Figure 3B). The Sr/Ca value in D. vulgaris ranged from 1.65 to 2.45 µmol/mol (median 2.06 mmol/mol) and 0.92 to 2.24 mmol/mol (median 1.50 mmol/mol) for Sovlja and Pantan, respectively (Figure 3B). Although the median Sr/Ca was higher for D. vulgaris at Sovlja, spatial differences in the Sr/Ca ratio were not significant between species (t = 1.126; p = 0.271) and also not between sites (t = 1.412; p = 0.093).

3.2. Stable Isotope Analyses

Differences were observed in stable isotope composition of muscle tissue (δ13C and δ15N) between sites and species. Values for carbon stable isotope in D. puntazzo ranged from −18.41 to −15.43‰ (median −17.59‰) and from −25.17 to −20.06‰ (median −23.60‰) for Sovlja and Pantan, respectively (Figure 4A). For D. vulgaris, δ13C values ranged from −18.11 to −15.14‰ (median −16.41‰) in Sovlja and from −19.61 to −17.25‰ (median −17.73‰) in Pantan (Figure 4B). Median values of δ13C were higher for D. vulgaris at both sites, and differences were significant both between species (t = 5.134; p = 0.0002) and sites (t = 5.550; p = 0.0003). Data for δ15N in D. puntazzo ranged from 10.12 to 10.93‰ (median 10.37‰) and 11.16 to 12.11‰ (median 11.84‰) for Sovlja and Pantan, respectively (Figure 4A). For D. vulgaris, data for δ15N ranged from 9.26 to 10.04‰ (median 9.63‰) and 11.25 to 12.12‰ (median 11.47 ‰) for Sovlja and Pantan, respectively (Figure 4B). Although the median of δ15N was higher for D. puntazzo at both sites, this difference was not statistically significant between species (t = 2.994; p = 0.011), though it was between sites (t = 10.039; p = 0.0001).

3.3. Multi-parameter Comparison

When the otolith chemistry data were combined into a single matrix, PERMANOVA analysis detected that “Species” differed significantly in their element signatures, although significant level is not high (P = 0.049) while “Site” did not (Table 3). There was also no evidence for a significant interaction, as PERMANOVA analysis conducted after pooling the Site x Species interaction term did not change this result.
After pooling the isotope data, the plot clearly showed effects for each of the four “Species x Site” groups and for each of the stable isotopes (Figure 5). PERMANOVA showed that both factors (“Species” and “Site”) had main effects and a significant interaction term (Table 3). The metric MDS of the bivariate isotope data showed patterns across the four groups, with an evident pattern with a decrease in δ13C (Figure 5A) and increase in δ15N (Figure 5B) (going from left to right). The four groups ordered along this axis as follows: D. puntazzo_Estuary > D. vulgaris_Estuary > D. puntazzo_Coastal > D. vulgaris_ Coastal.
Separate CAP analysis for each of the two factors (“Site” and “Species”) gave successful discrimination for species but not for sites. In particular, 80% D. puntazzo specimens were correctly allocated based on the otolith chemistry information, as opposed to 77.8% of D. vulgaris specimens. The two-way CAP plot obtained by merging output scores for the CAP analysis of “Site” and “Species” showed separation of the two species (Figure 6). It is apparent that the site differences (“E” estuary vs. “C” coastal) were able to distinguish for D. vulgaris. In contrast, the D. puntazzo samples from the estuary were consistently clustered, while coastal samples were more variable, making them difficult to classify.
The mean isotope values for the four groups of factors (Species x Site) were plotted as distances among centroids based on otolith data (Figure 7), which showed a clear separation of the coastal and estuarine sites. This was confirmed by CAP as a canonical correlation analysis of the otolith distance matrix on the isotope (continuous quantitative) values (Figure 8). According to our results, based on the otolith chemistry and stable isotope information, correct re-allocation of D. vulgaris individuals to the estuarine waters were confirmed. Samples of D. puntazzo were correctly re-allocated due to the higher value of δ15N to estuarine waters.

4. Discussion

This study investigated the potential of otolith chemistry and tissue stable isotope analyses to distinguish between two different nursery areas of two closely related fish species of the genus Diplodus. Juveniles of D. puntazzo and D. vulgaris from the Pantan and Sovlja sites have similar reproductive and early life characteristics [52], inhabiting nursery habitats and leaving them in early summer [53,60]. The larvae of D. puntazzo settle in these shallow sites earlier as they hatch several weeks before D. vulgaris, so their juveniles are larger at both sites [51].
A commonly used method is laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS), which produces an elemental fingerprint at a discrete time-point in the life of a fish [80]. Trace elements (e.g., Ba, Li, Mg, Mn, and Sr) and heavy metals (e.g., Pb, Cu, and Zn) are acquired by fish during the life history and preserved within the otolith structure [19,80,81,82]. In addition to these typically analyzed elements, we also examined Na, Mo, and U in line with the protocol of the Institute of Geosciences, JGU [83]. Unfortunately, as most of the analysed element/Ca ratios were below the quantification and detection limits, only Ba/Ca and Sr/Ca were analysed in this study. A number of factors, such as salinity, temperature, water chemistry, age and growth, physiology, and metabolism may be responsible for the incorporation of trace elements into otoliths, though this is a complex process and remains poorly understood for most elements (with the exception of Ba and Sr) [27,33,84,85,86,87,88,89,90,91,92].
Data for Ba/Ca elemental composition were not significant between species and sites, although more prominent differences were obtained between species. Generally, Ba incorporation into otoliths appears largely determined by ambient concentrations, which are spatially variable and typically higher in inshore waters, estuaries, and upwelling zones [1,91,92,93,94,95,96]. Although, both sites are inshore, Pantan is estuarine and Sovlja is coastal, and therefore the hydrological conditions differ. Though not substantial, there is some enrichment of Ba in the coastal Sovlja site, likely influenced by local fluvial runoff and groundwater input, as suggested by Correira et al. [33] which consequently raise this concentration of above expected. The Ba/Ca concentration ratios were different in both species at both sites, confirming variability in element uptake of different species at same site [34,74]. Further on, Bouchoucha et al. [34] studying life of juvenile D. vulgaris and D. sargus reported that Ba was systematically the most discriminating element, since its concentrations in otoliths were generally higher outside ports than inside, probably due to river runoff. The Sr/Ca ratio was also more variable between species and sites but this difference was not significant for site neither for species. Sr incorporation is also influenced by ambient concentration, and has been linked to salinity, though temperature, ontogeny and growth rate may also influence patterns of Sr incorporation into otoliths [1,16,33,87,92,97,98]. The higher Sr levels from Sovlja are likely related to exogenous factors (marine site with higher salinity and temperature), though there may also be certain endogenous causes since D. vulgaris incorporated more Sr at both sites but this influence is too weak to make a significant difference. However, the variability with at each otolith concentrations have to be discussed with attention due different sampling size and site.
Since the investigated species are closely related and show no temporal segregation in nursery areas, we hypothesized that foraging behavior and diet composition may have contributed to the observed differences in the element incorporation between species and sites. Both, δ13C and δ15N differed significantly between sites and species. The median of δ15N was higher for D. puntazzo while D. vulgaris had higher values of δ13C at both sites. For soft tissue stable isotopes, lower δ13C values were found at Pantan, which agrees with the expected natural patterns of δ13C variation and displays an enrichment trend along the terrestrial–estuarine–marine gradient [99]. In addition, the overall richer δ15N values at Pantan than at the coastal Sovlja site were likely due to anthropogenic nitrogen inputs in the estuary (e.g., wastewater, and fertilizers) [20,36,46,100]. The observed intra-species differences in fish muscle stable isotopes reflected the isotope composition of local food webs and available prey [20,101]. It seems that in estuarine Pantan, both species feed on the same local food web for a longer period and do not disperse widely around the sampling site. Since targeted specimens in this study are juveniles representing similar growing stage and values obtained for stable isotopes were adjusted to blue mussel baseline, one should consider that in general for fish muscle the turnover rate is around months [102,103], while short-living consumers, such as zooplankton, have high tissue turnover rates, similar to that of phytoplankton [104]. Abecasis et al. [42] reported that in estuarine waters, juvenile D. vulgaris make only short movements and typically remain in the same areas for extended periods, and this is likely also the case for D. puntazzo. Higher isotope values in D. puntazzo may reflect that these specimens are possible several weeks older and, thus, larger and are likely to forage on bigger prey. Estuarine areas are often highly productive with a narrow prey spectrum, but with high prey availability and abundance [105]. The marked differences in isotope concentration of muscle tissue in specimens from the coastal site Sovlja suggest that these two species feed on different local food webs, with D. vulgaris foraging at a higher trophic level [106]. In coastal areas, the availability and abundance of prey are usually lower though the prey spectrum is wider [107].
PERMANOVA clearly confirmed the different element signatures of D. vulgaris and D. puntazzo. Although the incorporation of Ba and Sr is largely influenced by environmental factors (temperature and salinity), these differences in the otolith fingerprints likely resulted from the homeostatic apparatus of the individual fish, i.e., its physiology and ultimately its genetic makeup [98]. The fact that PERMANOVA did not reveal significant difference between sites raises the question of how these sites, defined as estuarine and coastal, really differ in the study area due to the specific oceanographic properties of the eastern Adriatic Sea, with many freshwater grounds in the coastal area [108]. Unfortunately, lack of water sample from both habitats disable relevant comparison and establishment of the relationship between Ba and Sr concentration and otolith microchemistry in this study. For sure, such limitations have to be consider in future sampling designs.
The metric MDS of the bivariate isotope data clearly shows patterns that can be interpreted as decreases in δ13C and increases in δ15N (D. puntazzo_Estuary > D. vulgaris_Estuary > D. puntazzo_Coastal > D. vulgaris_Coastal). Both species exhibited different behaviours in estuarine and coastal waters, which is likely related to foraging and feeding. D. puntazzo is more efficient in feeding in estuarine waters than D. vulgaris, and it grows faster, incorporating more δ15N in the more productive estuarine waters [105]. Moreover, this greater efficiency of D. puntazzo over D. vulgaris is even more prominent in coastal waters, where prey is generally less available and foraging time is longer [106,107].
Furthermore, we attempted to correctly allocate these species to the estuarine or coastal environments through CAP analyses. 80% D. puntazzo and 77.8% of the D. vulgaris specimens were allocated correctly based on the otolith chemistry information. However, the results suggested that over time, the otolith fingerprint differences observed in D. vulgaris in different waters will become more significant and thus it can be allocated correctly in estuarine water using otolith chemistry and stable isotope information. D. puntazzo incorporates elements into otoliths in different environments in a similar way and therefore can be allocated according to the higher value of δ15N in estuarine waters.
The present study provides preliminary insight into juvenile fish nursery use at different spatial scales in the Adriatic Sea by combining otolith chemistry with tissue isotope ratios of the same individuals to determine distinct ecological and environmental linkages [20]. Although, conducted on relatively small sampling size, otolith chemistry results reflected the environmental characteristics of the juvenile Diplodus nursery areas, while muscle stable isotope analysis indicated the isotope differences between species and between sites, accentuating the need to consider both environmental gradients and species behaviour in movement and connectivity studies based on otolith fingerprints. Such knowledge can help to accurately identify nursery origin and determining the relative contributions of individual nursery areas to the adult coastal populations of species [18,39,46]. Moreover, better understanding of settlement and recruitment processes, and nursery habitat use and movement patterns between juveniles and adults enables more sustainable management of fishery resources and essential habitat conservation based on ecological principles.

Author Contributions

All of the authors conceived the research. D.V., S.M.-S., M.P., H.U., K.M., and R.M.-K. contributed to the sample design, collecting, and preparing otoliths and muscle tissue for analyses, and running analyses. P.G. helped to define the research questions and sampling design. D.V. and S.M.-S. wrote the draft of the paper and all authors participated in the improvement and revision of the document. All authors have read and agreed to the published version of the manuscript.

Funding

This study was fully supported by the Croatian Science Foundation (HRZZ) under project IP-2016-06-9884 (NurseFish).

Institutional Review Board Statement

Ethics statement. The methods involving animals in this study were conducted in accordance with the Laboratory Animal Management Principles of Croatia. All experimental protocols were approved by Ethics Committee of the Institute of Oceanography and Fisheries.

Informed Consent Statement

Not applicable

Data Availability Statement

Data used in this manuscript are available from the corresponding author upon reasonable request.

Acknowledgments

The authors are grateful to Distinguished Professor Marti J. Anderson (Director PRIMER-e) for all knowledge sharing with us during the PERMANOVA workshop at the University of Trieste, Italy (September 2019) and special thanks for assisting with the creation of the PERMANOVA design and run analyses for this study.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Elsdon, T.S.; Wells, B.K.; Campana, S.E.; Gillanders, B.M.; Jones, C.M.; Limburg, K.E.; Secor, D.H.; Thorrold, S.R.; Walther, B.D. Otolith chemistry to describe movements and life-history parameters of fishes: Hypotheses, assumptions, limitations and inferences. Oceanogr. Mar. Biol. 2008, 46, 297–330. [Google Scholar]
  2. Catalán, I.A.; Alós, J.; Díaz-Gil, C.; Pérez-Mayol, S.; Basterretxea, G.; Morales-Nin, B.; Palmer, M. Potential fishing-related effects on fish life history revealed by otolith microchemistry. Fish. Res. 2018, 199, 186–195. [Google Scholar] [CrossRef]
  3. Darnaude, A.M.; Hunter, E. Validation of otolith δ18O values as effective natural tags for shelf-scale geolocation of migrating fish. Mar. Ecol. Prog. Ser. 2018, 598, 167–185. [Google Scholar] [CrossRef]
  4. Beck, M.W.; Heck, K.L.; Able, K.W.; Childers, D.L.; Eggleston, D.B.; Gillanders, B.M.; Halpern, B.; Hays, C.G.; Hoshino, K.; Minello, T.J.; et al. The identification, conservation, and management of estuarine and marine nurseries for fish and invertebrates. Bioscience 2001, 51, 633–641. [Google Scholar] [CrossRef]
  5. Dahlgren, C.P.; Todd Kellison, G.; Adams, A.J.; Gillanders, B.M.; Kendall, M.S.; Layman, C.A.; Ley, J.A.; Nagelkerken, I.; Serafy, J.E. Marine nurseries and effective juvenile habitats: Concepts and applications. Mar. Ecol. Prog. Ser. 2006, 312, 291–295. [Google Scholar] [CrossRef]
  6. Lotze, H.K.; Lenihan, H.S.; Bourque, B.J.; Bradbury, R.H.; Cooke, R.G.; Kay, M.C.; Kidwell, S.M.; Kirby, M.X.; Peterson, C.H.; Jackson, J.B.C. Depletion degradation, and recovery potential of estuaries and coastal seas. Science 2006, 312, 1806–1809. [Google Scholar] [CrossRef]
  7. Worm, B.; Barbier, E.B.; Beaumont, N.; Duffy, J.E.; Folke, C.; Halpern, B.S.; Jackson, J.B.C.; Lotze, H.K.; Micheli, F.; Palumbi, S.R.; et al. Impacts of biodiversity loss on ocean ecosystem services. Science 2006, 344, 787–790. [Google Scholar] [CrossRef]
  8. Waycott, M.; Duarte, C.M.; Carruthers, T.J.B.; Orth, R.J.; Dennison, W.C.; Olyarnik, S.; Calladine, A.; Fourqurean, J.W.; Heck, K.L., Jr.; Hughes, A.R.; et al. Accelerating loss of seagrasses across the globe threatens coastal ecosystems. Proc. Natl. Acad. Sci. USA 2009, 106, 12377–12381. [Google Scholar] [CrossRef]
  9. Claudet, J.; Fraschetti, S. Human-driven impacts on marine habitats: A regional meta-analysis in the Mediterranean Sea. Biol. Conserv. 2010, 143, 2195–2206. [Google Scholar] [CrossRef]
  10. Barausse, A.; Duci, A.; Mazzoldi, C.; Artioli, Y.; Palmeri, L. Trophic network model of the Northern Adriatic Sea: Analysis of an exploited and eutrophic ecosystem. Est. Coast. Shelf. Sci. 2009, 83, 577–590. [Google Scholar] [CrossRef]
  11. Teodósio, M.A.; Paris, C.B.; Wolanski, E.; Morais, P. Biophysical processes leading to the ingress of temperate fish larvae into estuarine nursery areas: A review. Estuar. Coast. Shelf Sci. 2016, 183, 187–202. [Google Scholar] [CrossRef]
  12. Rogers, T.A.; Fowler, A.J.; Steer, M.A.; Gillanders, B.M. Spatial connectivity during the early life history of a temperate marine fish inferred from otolith microstructure and geochemistry. Estuar. Coast. Shelf Sci. 2019, 227, 106342. [Google Scholar] [CrossRef]
  13. Cowen, R.K.; Lwiza, K.M.M.; Sponaugle, S.; Paris, C.B.; Olson, D.B. Connectivity of marine populations: Open or closed? Science 2000, 287, 857–859. [Google Scholar] [CrossRef]
  14. Cowen, R.K.; Sponaugle, S. Larval dispersal and marine population Connectivity. Ann. Rev. Mar. Sci. 2009, 1, 443–466. [Google Scholar] [CrossRef]
  15. Campana, S.E.; Thorrold, S.R. Otoliths, increments, and elements: Keys to a comprehensive understanding of fish populations? Can. J. Fish. Aquat. Sci. 2001, 58, 30–38. [Google Scholar] [CrossRef]
  16. Campana, S.E.; Chouinard, G.A.; Hanson, J.M.; Fréchet, A.; Brattey, J. Otolith elemental fingerprints as biological tracers of fish stocks. Fish. Res. 2000, 46, 343–357. [Google Scholar] [CrossRef]
  17. Tanner, S.E.; Vasconcelos, R.P.; Cabral, H.N.; Thorrold, S.R. Testing an otolith geochemistry approach to determine population structure and movements of European hake in the northeast Atlantic Ocean and Mediterranean Sea. Fish. Res. 2012, 125, 198–205. [Google Scholar] [CrossRef]
  18. Gillanders, B.M.; Kingsford, M.J. Elemental fingerprints of otoliths of fish may distinguish estuarine “nursery” habitats. Mar. Ecol. Prog. Ser. 2000, 201, 273–286. [Google Scholar] [CrossRef]
  19. Reis-Santos, P.; Tanner, S.E.; Vasconcelos, R.P.; Elsdon, T.S.; Cabral, H.N.; Gillanders, B.M. Connectivity between estuarine and coastal fish populations: Contributions of estuaries are not consistent over time. Mar. Ecol. Prog. Ser. 2013, 491, 177–186. [Google Scholar] [CrossRef]
  20. Reis-Santos, P.; Tanner, S.E.; França, S.; Vasconcelos, R.P.; Gillanders, B.M.; Cabral, H.N. Connectivity within estuaries: An otolith chemistry and muscle stable isotope approach. Ocean Coast. Manag. 2015, 118, 51–59. [Google Scholar] [CrossRef]
  21. Sadekov, A.; Eggins, S.M.; De Deckker, P. Characterization of Mg/Ca distributions in planktonic foraminifera species by electron microprobe mapping. Geochem. Geophys. Geosyst. 2005, 6. [Google Scholar] [CrossRef]
  22. Montagna, P.; McCulloch, M.; Mazzoli, C.; Silenzi, S.; Odorico, R. The non-tropical coral Cladocora caespitosa as the new climate archive for the Mediterranean: High-resolution (∼weekly) trace element systematics. Quat. Sci. Rev. 2007, 26, 441–462. [Google Scholar] [CrossRef]
  23. Sadekov, A.; Eggins, S.M.; De Deckker, P.; Ninnemann, U.; Kuhnt, W.; Bassinot, F. Surface and subsurface seawater temperature reconstruction using Mg/Ca microanalysis of planktonic foraminifera Globigerinoides ruber, Globigerinoides sacculifer, and Pulleniatina obliquiloculata. Paleoce. Paleoclim. 2009, 24, PA3201. [Google Scholar]
  24. Long, K.; Stern, N.; Williams, I.S.; Kinsley, L.; Wood, R.; Sporcic, K.; Fallon, S.; Kokkonen, H.; Moffat, I.; Grün, R. Fish otolith geochemistry, environmental conditions and human occupation at Lake Mungo, Australia. Quaternery Sci. Rev. 2014, 88, 82–95. [Google Scholar] [CrossRef]
  25. Fowler, A.M.; Smith, S.M.; Booth, D.J.; Stewart, J. Partial migration of grey mullet (Mugil cephalus) on Australia’s east coast revealed by otolith chemistry. Mar. Environ. Res. 2016, 119, 238–244. [Google Scholar] [CrossRef]
  26. Gillanders, B.M. Using elemental chemistry of fish otoliths to determine connectivity between estuarine and coastal habitats. Estuar. Coast. Shelf Sci. 2005, 64, 47–57. [Google Scholar] [CrossRef]
  27. Gillikin, D.P.; Wanamaker, A.D.; Andrus, C.F.T. Chemical sclerochronology. Chem. Geol. 2019, 526. [Google Scholar] [CrossRef]
  28. Secor, D.H.; Rooker, J.R. Is otolith strontium a useful scalar of life-cycles in estuarine fishes? Fish. Res. 2000, 46, 359–371. [Google Scholar] [CrossRef]
  29. Kraus, R.T.; Secor, D.H. Dynamics of white perch Morone americana population contingents in the Patuxent River estuary, Maryland, USA. Mar. Ecol. Prog. Ser. 2004, 279, 247–259. [Google Scholar] [CrossRef]
  30. Tabouret, H.; Lord, C.; Bareille, G.; Pécheyran, C.; Monti, D.; Keith, P. Otolith microchemistry in Sicydium punctatum: Indices of environmental condition changes after recruitment. Aqua. Liv. Res. 2011, 24, 369–378. [Google Scholar] [CrossRef]
  31. Izzo, C.; Reis-Santos, P.; Gillanders, B.M. Otolith chemistry does not just reflect environmental conditions: A meta-analytic evaluation. Fish Fish. 2018, 19, 441–454. [Google Scholar] [CrossRef]
  32. Green, B.C.; Smith, D.J.; Earley, S.E.; Hepburn, L.J.; Underwood, G.J.C. Seasonal changes in community composition and trophic structure of fish populations of five salt marshes along the Essex coastline, United Kingdom. Estuar. Coast. Shelf. Sci. 2009, 85, 1–10. [Google Scholar] [CrossRef]
  33. Correira, A.T.; Pipac, T.; Gonçalves, J.M.S.; Erzini, K.; Hamer, P.A. Insights into population structure of Diplodus vulgaris along the SW Portuguese coast from otolith elemental signatures. Fish. Res. 2011, 111, 82–91. [Google Scholar] [CrossRef]
  34. Bouchoucha, M.; Pécheyran, C.; Gonzalez, J.L.; Lenfant, P.; Darnaude, A.M. Otolith fingerprints as natural tags to identify juvenile fish life in ports. Estuar. Coast. Shelf Sci. 2018, 212, 210–218. [Google Scholar] [CrossRef]
  35. Hobson, K.A. Tracing origins and migration of wildlife using stable isotopes: A review. Oecologia. 1999, 120, 314–326. [Google Scholar] [CrossRef] [PubMed]
  36. Herzka, S.Z. Assessing connectivity of estuarine fishes based on stable isotope ratio analysis. Estuar. Coast. Shelf Sci. 2005, 64, 58–69. [Google Scholar] [CrossRef]
  37. Trueman, C.N.; Mackenzie, K.M.; Palmer, M.R. Identifying migrations in marine fishes through stable-isotope analysis. J. Fish Biol. 2012, 81, 826–847. [Google Scholar] [CrossRef]
  38. Suzuki, K.W.; Kasai, A.; Ohta, T.; Nakayama, K.; Tanaka, M. Migration of Japanese temperate bass Lateolabrax japonicus juveniles within the Chikugo River estuary revealed by δ13C analysis. Mar. Ecol. Prog. Ser. 2008, 358, 246–256. [Google Scholar] [CrossRef]
  39. Verweij, M.C.; Nagelkerken, I.; Hans, I.; Ruseler, S.M.; Mason, P.R.D. Seagrass nurseries contribute to coral reef fish populations. Limnol. Oceanogr. 2008, 53, 1540–1547. [Google Scholar] [CrossRef]
  40. Green, B.C.; Smith, D.J.; Grey, J.; Underwood, G.J.C. High site fidelity and low site connectivity in temperate salt marsh fish populations: A stable isotope approach. Oecologia 2012, 168, 245–255. [Google Scholar] [CrossRef]
  41. Vinagre, C.; Salgado, J.; Costa, M.J.; Cabral, H.N. Nursery fidelity, food web interactions and primary sources of nutrition of the juveniles of Solea solea and S. senegalensis in the Tagus estuary (Portugal): A stable isotope approach. Estuar. Coast. Shelf Sci. 2008, 76, 255–264. [Google Scholar] [CrossRef]
  42. Abecasis, D.; Bentes, D.; Erzini, K. Home range, residency and movements of Diplodus sargus and Diplodus vulgaris in a coastal lagoon: Connectivity between nursery and adult habitats. Estuar. Coast. Shelf Sci. 2009, 85, 55–529. [Google Scholar] [CrossRef]
  43. Fry, B. Using stable isotopes to monitor watershed influences on aquatic trophodynamics. Can. J. Fish. Aquat. Sci. 1999, 56, 2167–2171. [Google Scholar]
  44. Rubenstein, D.R.; Hobson, K.A. From birds to butterflies: Animal movement patterns and stable isotopes. Trends Ecol. Evol. 2004, 19, 256–263. [Google Scholar] [CrossRef] [PubMed]
  45. Lawton, R.J.; Wing, S.R.; Lewis, A.M. Evidence for discrete subpopulations of sea perch (Helicolenus ercoides) across four fjords in Fiordland, New Zealand. New Zeal. J. Mar. Fresh. Res. 2010, 44, 309–322. [Google Scholar] [CrossRef]
  46. Dierking, J.; Morat, F.; Letourneur, Y.; Harmelin-Vivien, M. Fingerprints of lagoonal life: Migration of the marine flatfish Solea solea assessed by stable isotopes and otolith microchemistry. Estuar. Coast. Shelf Sci. 2012, 104, 23–32. [Google Scholar] [CrossRef]
  47. Fodrie, F.J.; Herzka, S.Z. A Comparison of Otolith Geochemistry and Stable Isotope Markers to Track Fish Movement: Describing Estuarine Ingress by Larval and Post-Larval Halibut. Estaur. Coast. 2013, 36, 906–917. [Google Scholar]
  48. Marengo, M.; Durieux, E.D.H.; Marchand, B.; Francour, P. A review of biology, fisheries and population structure of Dentex dentex (Sparidae). Rev. Fish. Biol. Fisheries 2014, 24, 1065–1088. [Google Scholar] [CrossRef]
  49. Divanach, P. Contribution de la Biologie et de l’élevage de 6 Sparidés Mediterranéens: Sparus aurata, Diplodus sargus, Diplodus vulgaris, Diplodus annularis, Lithognathus mormyrus, Puntazzo puntazzo (Poissons Téleosteens). Thèse d’Etat, Université des Sciences et Techniques de Languedoc, Montpellier, France, 1985; p. 479. [Google Scholar]
  50. MacPherson, E. Ontogenetic shifts in habitat use and aggregation in juvenile sparid fishes. J. Exp. Mar. Bio. Ecol. 1998, 220, 127–150. [Google Scholar]
  51. Vigliola, L.; Harmelin-Vivien, M.L.; Biagi, E.; Galzin, R.; Garcia-Rubies, A.; Harmelin, J.G.; Jouvenel, J.Y.; Le Direach-Boursier, L.; Macpherson, E.; Tunesi, L. Spatial and temporal patterns of settlement among sparid fishes of the genus Diplodus in the north-western Mediterranean. Mar. Ecol. Prog. Ser. 1998, 168, 45–56. [Google Scholar] [CrossRef]
  52. Mouine, N.; Francour, P.; Ktari, M.H.; Chakroun-Marzouk, N. Reproductive biology of four Diplodus species Diplodus vulgaris, D. annularis, D. sargus sargus and D. puntazzo (Sparidae) in the Gulf of Tunis (central Mediterranean). J. Mar. Biol. Ass. UK. 2012, 92, 623–631. [Google Scholar]
  53. Dulčić, J.; Kraljević, M.; Grbec, B.; Pallaoro, A. Composition and temporal fluctuations of inshore juvenile fish populations in the Kornati Archipelago, eastern middle Adriatic. Mar. Biol. 1997, 129, 267–277. [Google Scholar] [CrossRef]
  54. Di Franco, A.; Bulleri, F.; Pennetta, A.; De Benedetto, G.; Clarke, K.R.; Guidetti, P. Within-Otolith Variability in Chemical Fingerprints: Implications for Sampling Designs and Possible Environmental Interpretation. PLoS ONE 2014, 9, e101701. [Google Scholar] [CrossRef]
  55. Vasconcelos, R.P.; Reis-Santos, P.; Maia, A.; Fonseca, V.; França, S.; Wouters, N.; Costa, M.J.; Cabral, H.N. Nursery use patterns of commercially important marine fish species in estuarine systems along the Portuguese coast. Estuar. Coast. Shelf Sci. 2010, 86, 613–624. [Google Scholar] [CrossRef]
  56. Zeigler, J.M.; Whitledge, G.W. Otolith trace element and stable isotopic compositions differentiate fishes from the Middle Mississippi River, its tributaries, and floodplain lakes. Hydrobiologia 2011, 661, 289–302. [Google Scholar] [CrossRef]
  57. Gibb, F.M.; Régnier, T.; Donald, K.; Wright, P.J. Connectivity in the early life history of sandeel inferred from otolith microchemistry. J. Sea Res. 2017, 119, 8–16. [Google Scholar] [CrossRef]
  58. Avigliano, E.; Pisonero, J.; Dománico, A.; Silva, N.; Sánchez, S.; Vanina Volpedo, A. Spatial segregation and connectivity in young and adult stages of Megaleporinus obtusidens inferred from otolith elemental signatures: Implications for management. Fish. Res. 2018, 204, 239–244. [Google Scholar] [CrossRef]
  59. Ley, L.A.; Rolls, H.J. Using otolith microchemistry to assess nursery habitat contribution and function at a fine spatial scale. Mar. Ecol. Prog. Ser. 2018, 606, 151–173. [Google Scholar] [CrossRef]
  60. Dulčić, J.; Matić, S.; Kraljević, M. Shallow coves as nurseries for non-resident fish: A case study in the eastern middle Adriatic. J. Mar. Biol. Ass. U.K. 2002, 82, 991–993. [Google Scholar] [CrossRef]
  61. Dulčić, J.; Matić-Skoko, S.; Kraljević, M.; Fencil, M.; Glamuzina, B. Seasonality of a fish assemblage in shallow waters of Duće-Glava, eastern middle Adriatic. Cybium 2005, 29, 57–63. [Google Scholar]
  62. Matić-Skoko, S.; Kraljević, M.; Dulčić, J.; Pallaoro, A.; Lučić, D.; Glamuzina, B. Growth of juvenile sharpsnout seabream, Diplodus puntazzo (Teleostei: Sparidae) in the Kornati Archipelago, eastern Adriatic Sea. Vie Milieu. 2007, 57, 13–19. [Google Scholar]
  63. Fukumori, K.; Oi, M.; Doi, H.; Takahashi, D.; Okuda, N.; Miller, T.W. Bivalve tissue as a carbon and nitrogen isotope baseline indicator in coastal ecosystems. Estuar. Coast. Shelf Sci. 2008, 79, 45–50. [Google Scholar] [CrossRef]
  64. Post, D.M. Using stable isotopes to estimate trophic position: Models, methods, and assumptions. Ecology 2002, 83, 703–718. [Google Scholar] [CrossRef]
  65. Post, D.M.; Layman, C.A.; Arrington, D.A.; Takimoto, G.; Quattrochi, J.; Montaña, C.G. Getting to the fat of the matter: Models, methods and assumptions for dealing with lipids in stable isotope analyses. Oecologia 2007, 152, 179–189. [Google Scholar] [CrossRef]
  66. Available online: http://georem.mpch-mainz.gwdg.de/ (accessed on 15 May 2020).
  67. Jochum, K.P.; Nohl, U.; Herwig, K.; Lammel, E.; Stoll, B.; Hofmann, A.W. GeoReM: A new geochemical database for reference materials and isotopic standards. Geostand. Geoanalytical Res. 2005, 29, 333–338. [Google Scholar] [CrossRef]
  68. Jochum, K.P.; Weis, U.; Stoll, B.; Kuzmin, D.; Yang, Q.; Raczek, I.; Jacob, D.E.; Stracke, A.; Birbaum, K.; Frick, D.A.; et al. Determination of reference values for NIST SRM 610-617 glasses following ISO guidelines. Geostand. Geoanalytical Res. 2011, 36, 397–429. [Google Scholar] [CrossRef]
  69. Jochum, K.P.; Scholz, D.; Stoll, B.; Weis, U.; Wilson, S.A.; Yang, Q.; Schwalb, A.; Börner, N.; Jacob, D.E.; Andreae, M.O. Accurate trace element analysis of speleothems and biogenic calcium carbonates by LA-ICP-MS. Chem. Geol. 2012, 318–319, 31–44. [Google Scholar] [CrossRef]
  70. Jochum, K.P.; Stoll, B.; Herwig, K.; Willbold, M. Validation of LA-ICP-MS trace element analysis of geological glasses using a new solid-state 193 nm Nd:YAG laser and matrix-matched calibration. J. Anal. At. Spectrom. 2007, 22, 112–121. [Google Scholar] [CrossRef]
  71. Mischel, S.A.; Mertz-Kraus, R.; Jochum, K.P.; Scholz, D. TERMITE: An R script for fast reduction of laser ablation inductively coupled plasma mass spectrometry data and its application to trace element measurements. Rapid Commun. Mass Spectrom. 2017, 131, 1079–1087. [Google Scholar] [CrossRef]
  72. Yoshinaga, J.; Nakama, A.; Morita, M.; Edmonds, J.S. Fish otolith reference material for quality assurance of chemical analyses. Mar. Chem. 2000, 69, 91–97. [Google Scholar] [CrossRef]
  73. Sharp, Z. Principles of stable isotope geochemistry. Choice Rev. Online. 2007. [CrossRef]
  74. Vrdoljak, D.; Matić-Skoko, S.; Peharda, M.; Uvanović, H.; Markulin, K.; Mertz-Kraus, R. Otolith fingerprints reveals potential pollution exposure of newly settled juvenile Sparus aurata. Mar. Poll. Bull. 2020, 160, 111695. [Google Scholar] [CrossRef] [PubMed]
  75. Marali, S.; Schöne, B.R.; Mertz-Kraus, R.; Griffin, S.M.; Wanamaker, A.D., Jr.; Butler, P.G. Reproducibility of trace element time-series (Na/Ca, Mg/Ca, Mn/Ca, Sr/Ca, and Ba/Ca) within and between specimens of the bivalve Arctica islandica—a LA-ICP-MS line scan study. Palaeogeogr. Palaeoclimatol. Palaeoecol. 2017, 484, 109–128. [Google Scholar] [CrossRef]
  76. Marali, S.; Schöne, B.R.; Mertz-Kraus, R.; Griffin, S.M.; Wanamaker, A.D., Jr.; Matras, U. Ba/Ca ratios in shells of Arctica islandica—potential environmental proxy and crossdating tool. Palaeogeogr. Palaeoclimatol. Palaeoecol. 2017, 465, 347–361. [Google Scholar] [CrossRef]
  77. Anderson, M.J.; Willis, T.J. Canonical analysis of principal coordinates: A useful method of constrained ordination for ecology. Ecology 2003, 84, 511–525. [Google Scholar] [CrossRef]
  78. Dulčić, J.; Pallaoro, A.; Matić-Skoko, S.; Dragičević, B.; Tutman, P.; Grgičević, R.; Stagličić, N.; Bukvić, V.; Pavličević, J.; Glamuzina, B.; et al. Age, growth and mortality of common two-banded seabream, Diplodus vulgaris (Geoffroy Saint-Hilaire, 1817), in the eastern Adriatic Sea (Croatian coast). J. Appl. Icthyol. 2011, 27, 1254–1258. [Google Scholar] [CrossRef]
  79. Kraljević, M.; Matić-Skoko, S.; Dulčić, J.; Pallaoro, A.; Jardas, I.; Glamuzina, B. Age and growth of sharpsnout seabream Diplodus puntazzo (Cetti, 1777) in the eastern Adriatic Sea. Cah. Biol. Mar. 2007, 48, 145–154. [Google Scholar]
  80. Miller, J.A. Effects of water temperature and barium concentration on otolith composition along a salinity gradient: Implications for migratory reconstructions. J. Exp. Mar. Bio. Ecol. 2011, 405, 42–52. [Google Scholar] [CrossRef]
  81. Herrera-Reveles, A.T.; Lemus, M.; Marín, B.; Prin, J.L. Trace metal incorporation in otoliths of a territorial coral reef fish (Abudefduf saxatilis) as an environmental monitoring tool. E3S Web Conf. 2013, 1, 34007. [Google Scholar] [CrossRef]
  82. Sturrock, A.M.; Trueman, C.N.; Milton, J.A.; Waring, C.P.; Cooper, M.J.; Hunter, E. Physiological influences can outweigh environmental signals in otolith microchemistry research. Mar. Ecol. Prog. Ser. 2014, 500, 245–264. [Google Scholar] [CrossRef]
  83. Markulin, K.; Peharda, M.; Mertz-Kraus, R.; Schöne, B.R.; Uvanović, H.; Kovač, Ž.; Janeković, I. Trace and minor element records in aragonitic bivalve shells as environmental proxies. Chem. Geo. 2019, 507, 120–133. [Google Scholar] [CrossRef]
  84. Kalish, J.M. Otolith chemistry: Validation of the effects of physiology, age and environment on otolith composition. J. Exp. Mar. Biol. Ecol. 1989, 132, 151–178. [Google Scholar] [CrossRef]
  85. Kalish, J.M. Determinants of otolith chemistry: Seasonal variation in the composition of blood plasma, endolymph and otoliths of bearded rock cod Pseudophycis barbatus. Mar. Ecol. Prog. Ser. 1991, 74, 137–159. [Google Scholar] [CrossRef]
  86. Radtke, R.L.; Shafer, D.J. Environmental sensitivity of fish otolith microchemistry. Aust. J. Mar. Freshwater Res. 1992, 43, 935–951. [Google Scholar] [CrossRef]
  87. Sadovy, Y.; Severin, K. Elemental patterns in Red Hind (Epinephelus guttatus) otoliths from Bermuda and Puerto Rico reflect growth rate, not temperature. Can. J. Fish. Aquat. Sci. 1994, 51, 133–141. [Google Scholar] [CrossRef]
  88. Tzeng, W.N. Temperature effects on the incorporation on strontium in otoliths of Japanese eel Anguilla japonica. J. Fish Biol. 1994, 45, 1055–1066. [Google Scholar] [CrossRef]
  89. Campana, S.E. Chemistry and composition of fish otoliths: Pathways, mechanisms and applications. Mar. Ecol. Prog. Ser. 1999, 188, 263–297. [Google Scholar] [CrossRef]
  90. Elsdon, T.S.; Gillanders, B.M. Reconstructing migratory patterns of fish based on environmental influences on otolith chemistry. Rev. Fish Biol. Fisher. 2003, 13, 219–235. [Google Scholar] [CrossRef]
  91. Hamer, P.A.; Jenkins, G.P.; Coutin, P. Barium variation in Pagrus auratus (Sparidae) otoliths: A potential indicator of migration between an embayment and ocean waters in south-eastern Australia. Estuar. Coast. Shelf Sci. 2006, 68, 686–702. [Google Scholar] [CrossRef]
  92. Walther, B.D.; Thorrold, S.R. Water, not food, contributes the majority of strontium and barium deposited in the otoliths of a marine fish. Mar. Ecol. Prog. Ser. 2006, 311, 125–130. [Google Scholar] [CrossRef]
  93. Davis, W.J. Contamination of coastal versus open ocean surface waters: A brief meta-analysis. Mar. Pollut. Bull. 1993, 26, 128–134. [Google Scholar] [CrossRef]
  94. Patterson, H.M.; Thorrold, S.R.; Shenker, J.M. Analysis of otolith chemistry in Nassau grouper (Epinephelus striatus) from the Bahamas and Belize using solution-based ICP-MS. Coral Reefs 1999, 18, 171–178. [Google Scholar] [CrossRef]
  95. Patterson, H.M.; Kingsford, M.J.; McCulloch, M.T. Elemental signatures of Pomacentrus coelestis otoliths at multiple spatial scales on the Great Barrier Reef, Australia. Mar. Ecol. Prog. Ser. 2004, 270, 229–239. [Google Scholar]
  96. Elsdon, T.S.; Gillanders, B.M. Temporal variability in strontium, calcium, barium, and manganese in estuaries: Implications for reconstructing environmental histories of fish from chemicals in calcified structures. Estuar. Coast. Shelf Sci. 2006, 66, 147–156. [Google Scholar]
  97. Bath, G.E.; Thorrold, S.R.; Jones, C.M.; Campana, S.E.; McLaren, J.W.; Lam, J.W.H. Strontium and barium uptake in aragonitic otoliths of marine fish. Geochim. Cosmochim. Acta. 2000, 64, 1705–1714. [Google Scholar] [CrossRef]
  98. Grønkjær, P. Otoliths as individual indicators: A reappraisal of the link between fish physiology and otolith characteristics. Mar. Fresh. Res. 2006, 67, 881–888. [Google Scholar] [CrossRef]
  99. Fry, B.; Baltz, D.M.; Benfield, M.C.; Fleeger, J.W.; Gace, A.; Haas, H.L.; Quiñones-Rivera, Z.J. Stable isotope indicators of movement and residency for brown shrimp (Farfantepenaeus aztecus) in coastal Louisiana marshscapes. Estuaries 2003, 26, 82–97. [Google Scholar] [CrossRef]
  100. Schlacher, T.A.; Liddell, B.; Gaston, T.F.; Schlacher-Hoenlinger, M. Fish track wastewater pollution to estuaries. Oecologia 2005, 144, 570–584. [Google Scholar] [PubMed]
  101. França, S.; Vasconcelos, R.P.; Tanner, S.; Maguas, C.; Costa, M.J.; Cabral, H.N. Assessing food web dynamics and relative importance of organic matter sources for fish species in two Portuguese estuaries: A stable isotope approach. Mar. Environ. Res. 2011, 72, 204–215. [Google Scholar] [CrossRef]
  102. Hesslein, R.H.; Hallard, K.A.; Ramlal, P. Replacement of sulfur, carbon, and nitrogen in tissue of growing broad whitefish (Coregonus nasus) in response to a change in diet traced by δ34S, δ13C, and δ15N. Can. J. Fish. Aqua. Sci. 1993, 50, 2071–2076. [Google Scholar] [CrossRef]
  103. MacNeil, M.A.; Drouillard, K.G.; Fisk, A.T. Variable uptake and elimination of stable nitrogen isotopes between tissues in fish. Can. J. Fish. Aquat. Sci. 2006, 63, 345–353. [Google Scholar]
  104. Yoshioka, T.; Wada, E. A stable isotope study on seasonal food web dynamics in a eutrophic lake. Ecology 1994, 75, 835–846. [Google Scholar]
  105. Elliot, M.; Quintino, V. The Estuarine Quality Paradox, Environmental Homeostasis and the difficulty of detecting anthropogenic stress in naturally stressed areas. Mar. Poll. Bull. 2007, 54, 640–645. [Google Scholar]
  106. Nunn, A.D.; Tewson, L.H.; Cowx, I.G. The foraging ecology of larval and juvenile fishes. Rev. Fish Biol. Fisheries 2012, 22, 377–408. [Google Scholar] [CrossRef]
  107. van Leeuwen, A.; Huss, M.; Gärdmark, A.; Casini, M.; Vitale, F.; Hjelm, J.; Persson, L.; de Roos, A.M. Predators with multiple ontogenetic niche shifts have limited potential for population growth and top-down control of their prey. American Naturalist. 2013, 182, 53–66. [Google Scholar] [CrossRef]
  108. Buljan, M.; Zore-Armanda, M. Oceanographic properties of the Adriatic Sea. Oceanogr. Mar. Biol. Ann. 1976, 14, 11–98. [Google Scholar]
Figure 1. Sampling area in the Europe (A) along the eastern Adriatic coast (B) with selected sites: Pantan (square) and Sovlja (circle) (C).
Figure 1. Sampling area in the Europe (A) along the eastern Adriatic coast (B) with selected sites: Pantan (square) and Sovlja (circle) (C).
Water 13 01293 g001
Figure 2. Otolith of juvenile Diplodus vulgaris. The blue line represents the line scan through the otolith core from one edge to the opposite edge. Scale bar = 100 µm (Magnification 3x). Data for each otolith were selected approximately on distance 200 µm from the core.
Figure 2. Otolith of juvenile Diplodus vulgaris. The blue line represents the line scan through the otolith core from one edge to the opposite edge. Scale bar = 100 µm (Magnification 3x). Data for each otolith were selected approximately on distance 200 µm from the core.
Water 13 01293 g002
Figure 3. Box plots of median (±standard deviation) Ba/Ca (A) and Sr/Ca (B) otolith ratios (mmol/mol) of Diplodus puntazzo and Diplodus vulgaris collected from the Pantan estuarine site and Sovlja coastal site. Black dots present linear raster of Ba/Ca and Sr/Ca otolith ratios for each site and species.
Figure 3. Box plots of median (±standard deviation) Ba/Ca (A) and Sr/Ca (B) otolith ratios (mmol/mol) of Diplodus puntazzo and Diplodus vulgaris collected from the Pantan estuarine site and Sovlja coastal site. Black dots present linear raster of Ba/Ca and Sr/Ca otolith ratios for each site and species.
Water 13 01293 g003
Figure 4. Plots of median (and standard deviation) of δ13C and δ15N ratio muscle tissue of D. puntazzo (A) and D. vulgaris (B) collected from the Pantan estuarine site and Sovlja coastal site.
Figure 4. Plots of median (and standard deviation) of δ13C and δ15N ratio muscle tissue of D. puntazzo (A) and D. vulgaris (B) collected from the Pantan estuarine site and Sovlja coastal site.
Water 13 01293 g004
Figure 5. Metric MDS for juvenile Diplodus puntazzo and Diplodus vulgaris as a bubble plot for stable isotopes (A) δ13C and (B) δ15N for the coastal waters (C) and estuarine (E).
Figure 5. Metric MDS for juvenile Diplodus puntazzo and Diplodus vulgaris as a bubble plot for stable isotopes (A) δ13C and (B) δ15N for the coastal waters (C) and estuarine (E).
Water 13 01293 g005
Figure 6. Canonical variate plot (CAP) for Ba and Sr element chemistry of the otolith of juvenile Diplodus puntazzo and Diplodus vulgaris sampled in 2018, grouped by “Site” and “Species”.
Figure 6. Canonical variate plot (CAP) for Ba and Sr element chemistry of the otolith of juvenile Diplodus puntazzo and Diplodus vulgaris sampled in 2018, grouped by “Site” and “Species”.
Water 13 01293 g006
Figure 7. The metric MDS of the bivariate isotope data performed on Euclidean distances of normalized isotope values of δ13C and δ15N showing the patterns across the four groups of interest. Each half or circle correspond to δ13C and δ15N and its size reflects the contribution of each element isotope composition to the obtained distance.
Figure 7. The metric MDS of the bivariate isotope data performed on Euclidean distances of normalized isotope values of δ13C and δ15N showing the patterns across the four groups of interest. Each half or circle correspond to δ13C and δ15N and its size reflects the contribution of each element isotope composition to the obtained distance.
Water 13 01293 g007
Figure 8. Canonical variate plot (CAP) of the otolith distance matrix on the isotope (continuous quantitative) values. Previously, the distance matrix based on otoliths was related to the distance matrix based on isotopes.
Figure 8. Canonical variate plot (CAP) of the otolith distance matrix on the isotope (continuous quantitative) values. Previously, the distance matrix based on otoliths was related to the distance matrix based on isotopes.
Water 13 01293 g008
Table 1. Summary of hydrographic characteristic during collecting juveniles of Diplodus puntazzo and Diplodus vulgaris at sampling sites (June 2018).
Table 1. Summary of hydrographic characteristic during collecting juveniles of Diplodus puntazzo and Diplodus vulgaris at sampling sites (June 2018).
SitePantanSovlja
Bottom *SurfaceBottom *Surface
Temperature (°C) 27.826.52426.4
Salinity33.10.938.338
Oxygen (mg/L)8.888.6310.488.92
* Depth 1.5 m.
Table 2. Average concentrations and standard deviations (± 1σ) of strontium and barium in reference materials USGS MACS-3, USGS BCR-2G and NIST SRM 610 as determined during the LA-ICP-MS analysis. Reference values (± 1σ uncertainties) for USGS BCR-2G and NIST SRM 610 are available from the GeoReM database (application version 26; preferred values). Values for MACS-3 are from Jochum et al. ([68] Table 1, “Preliminary reference values”, “prel. RV”). Reference values given as oxide wt% in the GeoReM database have been calculated into element concentrations applying the respective stoichiometric factor.
Table 2. Average concentrations and standard deviations (± 1σ) of strontium and barium in reference materials USGS MACS-3, USGS BCR-2G and NIST SRM 610 as determined during the LA-ICP-MS analysis. Reference values (± 1σ uncertainties) for USGS BCR-2G and NIST SRM 610 are available from the GeoReM database (application version 26; preferred values). Values for MACS-3 are from Jochum et al. ([68] Table 1, “Preliminary reference values”, “prel. RV”). Reference values given as oxide wt% in the GeoReM database have been calculated into element concentrations applying the respective stoichiometric factor.
ElementUSG MACS-3 USG BCR-2G NIST SRM 610
Measured values (µg/g)Reference values (µg/g)Measured values (µg/g)Reference values (µg/g)Measured values (µg/g)Reference values (µg/g)
Sr6181 ± 1746760 ± 350345.6 ± 1342 ± 4530.5 ± 7515.5 ± 1
Ba57.9 ± 258.7 ± 2647.1 ± 5683 ± 7438.8 ± 9452 ± 9
Table 3. Summary of PERMANOVA results for the multivariate analysis of overall elemental composition of strontium (Sr) and barium (Ba) in otoliths (a) and overall carbon (δ13C) and nitrogen (δ15N) stable isotope values in muscle tissue (b) for juvenile Diplodus puntazzo and Diplodus vulgaris collected at different sites.
Table 3. Summary of PERMANOVA results for the multivariate analysis of overall elemental composition of strontium (Sr) and barium (Ba) in otoliths (a) and overall carbon (δ13C) and nitrogen (δ15N) stable isotope values in muscle tissue (b) for juvenile Diplodus puntazzo and Diplodus vulgaris collected at different sites.
Factors (a) Sr and Ba (b) δ13C and δ15N
dfMSPseudo-FP (perm)MSPseudo-FP (perm)
Species19.588E + 052.2390.0496.51719.3250.0005
Site16.134E + 051.4320.22719.93659.1110.0001
Sp x Site16.495E + 051.1570.1993.39410.0640.0001
Residauls154.283E + 05 0.337
Total18
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Back to TopTop